From 2ba4c3166d8cecb30e3a32a4feb03647a3238bdc Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Sun, 5 Apr 2026 22:45:16 +0000
Subject: [PATCH 01/28] feat(ocr): add olmocr profiles and plain-text parsing

---
 src/churro_ocr/prompts/__init__.py   |   4 ++
 src/churro_ocr/prompts/ocr.py        | 104 +++++++++++++++++++++++++++
 src/churro_ocr/providers/_shared.py  |  13 +++-
 src/churro_ocr/providers/specs.py    |  79 ++++++++++++++++++--
 src/churro_ocr/templates/__init__.py |   6 ++
 src/churro_ocr/templates/hf.py       |   6 +-
 src/churro_ocr/templates/presets.py  |  16 ++++-
 tests/test_hf_ocr.py                 |  63 +++++++++++++++-
 8 files changed, 281 insertions(+), 10 deletions(-)

diff --git a/src/churro_ocr/prompts/__init__.py b/src/churro_ocr/prompts/__init__.py
index 578679d..41917aa 100644
--- a/src/churro_ocr/prompts/__init__.py
+++ b/src/churro_ocr/prompts/__init__.py
@@ -8,6 +8,8 @@
     DEFAULT_OCR_OUTPUT_TAG,
     DEFAULT_OCR_SYSTEM_PROMPT,
     DEFAULT_OCR_USER_PROMPT,
+    OLMOCR_V4_YAML_PROMPT,
+    parse_olmocr_response,
     strip_ocr_output_tag,
 )
 
@@ -17,5 +19,7 @@
     "DEFAULT_OCR_OUTPUT_TAG",
     "DEFAULT_OCR_SYSTEM_PROMPT",
     "DEFAULT_OCR_USER_PROMPT",
+    "OLMOCR_V4_YAML_PROMPT",
+    "parse_olmocr_response",
     "strip_ocr_output_tag",
 ]
diff --git a/src/churro_ocr/prompts/ocr.py b/src/churro_ocr/prompts/ocr.py
index b96db4e..0007850 100644
--- a/src/churro_ocr/prompts/ocr.py
+++ b/src/churro_ocr/prompts/ocr.py
@@ -2,7 +2,9 @@
 
 from __future__ import annotations
 
+import html
 import re
+from typing import Any
 
 DEFAULT_OCR_OUTPUT_TAG = "output"
 
@@ -39,6 +41,16 @@
     "tables, and line breaks when they are visible."
 )
 
+OLMOCR_V4_YAML_PROMPT = (
+    "Attached is one page of a document that you must process. "
+    "Just return the plain text representation of this document as if you were reading it naturally.\n"
+    "Convert equations to LateX and tables to HTML.\n"
+    "If there are any figures or charts, label them with the following markdown syntax "
+    "![Alt text describing the contents of the figure](page_startx_starty_width_height.png)\n"
+    "Return your output as markdown, with a front matter section on top specifying values for the "
+    "primary_language, is_rotation_valid, rotation_correction, is_table, and is_diagram parameters."
+)
+
 
 def strip_ocr_output_tag(text: str, *, output_tag: str = DEFAULT_OCR_OUTPUT_TAG) -> str:
     """Remove outer OCR output tags and any stray tag tokens when present.
@@ -57,3 +69,95 @@ def strip_ocr_output_tag(text: str, *, output_tag: str = DEFAULT_OCR_OUTPUT_TAG)
 
     stray_tag_pattern = re.compile(rf"</?{re.escape(output_tag)}\b[^>]*>", flags=re.IGNORECASE)
     return stray_tag_pattern.sub("", text).strip()
+
+
+def _extract_yaml_front_matter(text: str) -> tuple[dict[str, object], str]:
+    """Return YAML front matter fields and the remaining markdown body."""
+    stripped = text.strip()
+    if not stripped.startswith("---\n"):
+        return {}, stripped
+
+    end_index = stripped.find("\n---", 4)
+    if end_index == -1:
+        return {}, stripped
+
+    front_matter_block = stripped[4:end_index]
+    body = stripped[end_index + 4 :].strip()
+    front_matter: dict[str, object] = {}
+    for line in front_matter_block.splitlines():
+        if ":" not in line:
+            continue
+        key, raw_value = line.split(":", 1)
+        key = key.strip()
+        value = raw_value.strip()
+        lower = value.lower()
+        if lower == "null":
+            parsed: object = None
+        elif lower == "true":
+            parsed = True
+        elif lower == "false":
+            parsed = False
+        elif re.fullmatch(r"-?\d+", value):
+            parsed = int(value)
+        else:
+            parsed = value
+        front_matter[key] = parsed
+    return front_matter, body
+
+
+def _strip_olmocr_markdown_to_plain_text(text: str) -> str:
+    """Best-effort plain-text conversion for olmOCR markdown/HTML output."""
+    cleaned = text.strip()
+    if not cleaned:
+        return ""
+
+    cleaned = re.sub(r"!\[[^\]]*]\([^)]+\)", "", cleaned)
+    cleaned = re.sub(r"\[([^\]]+)]\([^)]+\)", r"\1", cleaned)
+
+    html_replacements = (
+        (r"(?i)<\s*br\s*/?\s*>", "\n"),
+        (r"(?i)</\s*(?:p|div|h[1-6]|ul|ol|table|tr|li|pre)\s*>", "\n"),
+        (r"(?i)</\s*(?:td|th)\s*>", " | "),
+        (r"(?i)<\s*li\b[^>]*>", ""),
+        (
+            r"(?i)</?\s*(?:table|thead|tbody|tfoot|tr|td|th|p|div|span|h[1-6]|ul|ol|"
+            r"strong|em|b|i|u|sup|sub|code|pre)\b[^>]*>",
+            "",
+        ),
+    )
+    for pattern, replacement in html_replacements:
+        cleaned = re.sub(pattern, replacement, cleaned)
+
+    cleaned = html.unescape(cleaned)
+    cleaned = re.sub(r"(?m)^\s{0,3}#{1,6}\s*", "", cleaned)
+    cleaned = re.sub(r"(?m)^\s*[-+*]\s+", "", cleaned)
+    cleaned = re.sub(r"(?m)^\s*>\s?", "", cleaned)
+    cleaned = cleaned.replace("```", "")
+    cleaned = cleaned.replace("**", "")
+    cleaned = cleaned.replace("__", "")
+    cleaned = cleaned.replace("`", "")
+    cleaned = re.sub(r"[ \t]+\n", "\n", cleaned)
+    cleaned = re.sub(r"[ \t]{2,}", " ", cleaned)
+
+    normalized_lines: list[str] = []
+    saw_content = False
+    for raw_line in cleaned.splitlines():
+        line = re.sub(r"\s*\|\s*$", "", raw_line.strip())
+        line = re.sub(r"^\|\s*", "", line)
+        line = re.sub(r"\s*\|\s*", " | ", line)
+        if line:
+            normalized_lines.append(line)
+            saw_content = True
+            continue
+        if saw_content and normalized_lines and normalized_lines[-1] != "":
+            normalized_lines.append("")
+    return "\n".join(normalized_lines).strip()
+
+
+def parse_olmocr_response(text: str) -> tuple[str, dict[str, Any]]:
+    """Extract plain text and metadata from an olmOCR YAML-front-matter response."""
+    front_matter, markdown_body = _extract_yaml_front_matter(text)
+    return _strip_olmocr_markdown_to_plain_text(markdown_body), {
+        "front_matter": front_matter,
+        "raw_markdown": markdown_body,
+    }
diff --git a/src/churro_ocr/providers/_shared.py b/src/churro_ocr/providers/_shared.py
index 9d72254..42f7f01 100644
--- a/src/churro_ocr/providers/_shared.py
+++ b/src/churro_ocr/providers/_shared.py
@@ -77,11 +77,20 @@ def build_ocr_result(
     metadata: dict[str, Any] | None = None,
 ) -> OCRResult:
     """Build a normalized OCR result after postprocessing."""
+    processed = text_postprocessor(text)
+    postprocessor_metadata: dict[str, Any] = {}
+    if isinstance(processed, tuple):
+        processed_text, postprocessor_metadata = processed
+    else:
+        processed_text = processed
+
+    combined_metadata = dict(metadata or {})
+    combined_metadata.update(postprocessor_metadata)
     return OCRResult(
-        text=text_postprocessor(text),
+        text=processed_text,
         provider_name=provider_name,
         model_name=model_name,
-        metadata=dict(metadata or {}),
+        metadata=combined_metadata,
     )
 
 
diff --git a/src/churro_ocr/providers/specs.py b/src/churro_ocr/providers/specs.py
index 2ca709d..58a08ae 100644
--- a/src/churro_ocr/providers/specs.py
+++ b/src/churro_ocr/providers/specs.py
@@ -5,18 +5,25 @@
 from collections.abc import Callable
 from dataclasses import dataclass, field
 from pathlib import Path
-from typing import TYPE_CHECKING, Literal
+from typing import TYPE_CHECKING, Any, Literal
 
 from PIL import Image
 
-from churro_ocr._internal.image import prepare_ocr_image
-from churro_ocr.prompts import DEFAULT_OCR_OUTPUT_TAG, strip_ocr_output_tag
+from churro_ocr._internal.image import ensure_rgb, prepare_ocr_image, resize_image_to_fit
+from churro_ocr.prompts import (
+    DEFAULT_OCR_OUTPUT_TAG,
+    parse_olmocr_response,
+    strip_ocr_output_tag,
+)
 from churro_ocr.templates import (
     CHURRO_3B_MODEL_ID,
     CHURRO_3B_XML_TEMPLATE,
     DEFAULT_OCR_TEMPLATE,
     DOTS_OCR_1_5_MODEL_ID,
     DOTS_OCR_1_5_OCR_TEMPLATE,
+    OLMOCR_2_7B_1025_FP8_MODEL_ID,
+    OLMOCR_2_7B_1025_MODEL_ID,
+    OLMOCR_2_7B_1025_OCR_TEMPLATE,
     OCRConversation,
     OCRPromptTemplateLike,
 )
@@ -27,9 +34,12 @@
 
 OCRProvider = Literal["litellm", "openai-compatible", "azure", "mistral", "hf", "vllm"]
 ImagePreprocessor = Callable[[Image.Image], Image.Image]
-TextPostprocessor = Callable[[str], str]
+TextPostprocessorResult = str | tuple[str, dict[str, Any]]
+TextPostprocessor = Callable[[str], TextPostprocessorResult]
 VisionInputBuilder = Callable[[OCRConversation], object]
 DEFAULT_OCR_MAX_TOKENS = 20_000
+OLMOCR_MAX_TOKENS = 8_000
+OLMOCR_TARGET_LONGEST_IMAGE_DIM = 1_288
 
 
 def identity_text_postprocessor(text: str) -> str:
@@ -59,6 +69,22 @@ def default_ocr_text_postprocessor(text: str) -> str:
     return strip_ocr_output_tag(text, output_tag=DEFAULT_OCR_OUTPUT_TAG)
 
 
+def olmocr_image_preprocessor(image: Image.Image) -> Image.Image:
+    """Resize an image to olmOCR's expected 1288px longest side and normalize to RGB."""
+    return ensure_rgb(
+        resize_image_to_fit(
+            image,
+            OLMOCR_TARGET_LONGEST_IMAGE_DIM,
+            OLMOCR_TARGET_LONGEST_IMAGE_DIM,
+        )
+    )
+
+
+def olmocr_text_postprocessor(text: str) -> TextPostprocessorResult:
+    """Extract plain text and metadata from olmOCR YAML/markdown output."""
+    return parse_olmocr_response(text)
+
+
 @dataclass(slots=True, frozen=True)
 class LiteLLMTransportConfig:
     """Shared transport config for LiteLLM-based multimodal requests.
@@ -241,14 +267,57 @@ def dots_ocr_1_5_profile() -> OCRModelProfile:
     )
 
 
+def _olmocr_profile(*, profile_name: str, display_name: str) -> OCRModelProfile:
+    return OCRModelProfile(
+        profile_name=profile_name,
+        template=OLMOCR_2_7B_1025_OCR_TEMPLATE,
+        image_preprocessor=olmocr_image_preprocessor,
+        text_postprocessor=olmocr_text_postprocessor,
+        display_name=display_name,
+        transport=LiteLLMTransportConfig(
+            completion_kwargs={
+                "max_tokens": OLMOCR_MAX_TOKENS,
+                "temperature": 0.1,
+            }
+        ),
+        huggingface=HuggingFaceOptions(
+            generation_kwargs={
+                "max_new_tokens": OLMOCR_MAX_TOKENS,
+                "temperature": 0.1,
+                "do_sample": True,
+            },
+        ),
+    )
+
+
+def olmocr_2_7b_1025_profile() -> OCRModelProfile:
+    """Return the built-in ``allenai/olmOCR-2-7B-1025`` OCR profile."""
+    return _olmocr_profile(
+        profile_name=OLMOCR_2_7B_1025_MODEL_ID,
+        display_name="olmOCR-2-7B-1025",
+    )
+
+
+def olmocr_2_7b_1025_fp8_profile() -> OCRModelProfile:
+    """Return the built-in ``allenai/olmOCR-2-7B-1025-FP8`` OCR profile."""
+    return _olmocr_profile(
+        profile_name=OLMOCR_2_7B_1025_FP8_MODEL_ID,
+        display_name="olmOCR-2-7B-1025-FP8",
+    )
+
+
 def _profile_registry() -> dict[str, OCRModelProfile]:
     default_profile = default_ocr_profile()
     churro_profile = churro_3b_profile()
     dots_profile = dots_ocr_1_5_profile()
+    olmocr_profile = olmocr_2_7b_1025_profile()
+    olmocr_fp8_profile = olmocr_2_7b_1025_fp8_profile()
     return {
         default_profile.profile_name: default_profile,
         churro_profile.profile_name: churro_profile,
         dots_profile.profile_name: dots_profile,
+        olmocr_profile.profile_name: olmocr_profile,
+        olmocr_fp8_profile.profile_name: olmocr_fp8_profile,
     }
 
 
@@ -290,6 +359,8 @@ def resolve_ocr_profile(
     "ImagePreprocessor",
     "LiteLLMTransportConfig",
     "MistralOptions",
+    "olmocr_image_preprocessor",
+    "olmocr_text_postprocessor",
     "OCRBackendSpec",
     "OCRModelProfile",
     "OCRProvider",
diff --git a/src/churro_ocr/templates/__init__.py b/src/churro_ocr/templates/__init__.py
index 16f76b0..a8d97c9 100644
--- a/src/churro_ocr/templates/__init__.py
+++ b/src/churro_ocr/templates/__init__.py
@@ -15,6 +15,9 @@
     DOTS_OCR_1_5_MODEL_ID,
     DOTS_OCR_1_5_OCR_PROMPT,
     DOTS_OCR_1_5_OCR_TEMPLATE,
+    OLMOCR_2_7B_1025_FP8_MODEL_ID,
+    OLMOCR_2_7B_1025_MODEL_ID,
+    OLMOCR_2_7B_1025_OCR_TEMPLATE,
 )
 
 __all__ = [
@@ -26,6 +29,9 @@
     "DOTS_OCR_1_5_OCR_PROMPT",
     "DOTS_OCR_1_5_OCR_TEMPLATE",
     "HFChatTemplate",
+    "OLMOCR_2_7B_1025_FP8_MODEL_ID",
+    "OLMOCR_2_7B_1025_MODEL_ID",
+    "OLMOCR_2_7B_1025_OCR_TEMPLATE",
     "OCRConversation",
     "OCRPromptTemplate",
     "OCRPromptTemplateCallable",
diff --git a/src/churro_ocr/templates/hf.py b/src/churro_ocr/templates/hf.py
index 16a1987..9032873 100644
--- a/src/churro_ocr/templates/hf.py
+++ b/src/churro_ocr/templates/hf.py
@@ -15,11 +15,13 @@ class HFChatTemplate:
     :param system_message: Optional system message prepended to the conversation.
     :param user_prompt: Optional user-side text prompt appended with the image.
     :param include_image: Whether to include the page image in the user message.
+    :param user_prompt_first: Whether to place the user prompt before the image.
     """
 
     system_message: str | None = None
     user_prompt: str | None = None
     include_image: bool = True
+    user_prompt_first: bool = False
 
     def build_conversation(self, page: DocumentPage) -> OCRConversation:
         """Build a structured multimodal conversation for one OCR page.
@@ -37,9 +39,11 @@ def build_conversation(self, page: DocumentPage) -> OCRConversation:
             )
 
         user_content: list[dict[str, object]] = []
+        if self.user_prompt and self.user_prompt_first:
+            user_content.append({"type": "text", "text": self.user_prompt})
         if self.include_image:
             user_content.append({"type": "image", "image": page.image.copy()})
-        if self.user_prompt:
+        if self.user_prompt and not self.user_prompt_first:
             user_content.append({"type": "text", "text": self.user_prompt})
 
         conversation.append({"role": "user", "content": user_content})
diff --git a/src/churro_ocr/templates/presets.py b/src/churro_ocr/templates/presets.py
index 9909db8..8270444 100644
--- a/src/churro_ocr/templates/presets.py
+++ b/src/churro_ocr/templates/presets.py
@@ -2,11 +2,17 @@
 
 from __future__ import annotations
 
-from churro_ocr.prompts import DEFAULT_OCR_SYSTEM_PROMPT, DEFAULT_OCR_USER_PROMPT
+from churro_ocr.prompts import (
+    DEFAULT_OCR_SYSTEM_PROMPT,
+    DEFAULT_OCR_USER_PROMPT,
+    OLMOCR_V4_YAML_PROMPT,
+)
 from churro_ocr.templates.hf import HFChatTemplate
 
 CHURRO_3B_MODEL_ID = "stanford-oval/churro-3B"
 DOTS_OCR_1_5_MODEL_ID = "kristaller486/dots.ocr-1.5"
+OLMOCR_2_7B_1025_MODEL_ID = "allenai/olmOCR-2-7B-1025"
+OLMOCR_2_7B_1025_FP8_MODEL_ID = "allenai/olmOCR-2-7B-1025-FP8"
 DEFAULT_OCR_TEMPLATE = HFChatTemplate(
     system_message=DEFAULT_OCR_SYSTEM_PROMPT,
     user_prompt=DEFAULT_OCR_USER_PROMPT,
@@ -21,6 +27,11 @@
     system_message=None,
     user_prompt=DOTS_OCR_1_5_OCR_PROMPT,
 )
+OLMOCR_2_7B_1025_OCR_TEMPLATE = HFChatTemplate(
+    system_message=None,
+    user_prompt=OLMOCR_V4_YAML_PROMPT,
+    user_prompt_first=True,
+)
 
 
 __all__ = [
@@ -30,4 +41,7 @@
     "DOTS_OCR_1_5_MODEL_ID",
     "DOTS_OCR_1_5_OCR_PROMPT",
     "DOTS_OCR_1_5_OCR_TEMPLATE",
+    "OLMOCR_2_7B_1025_FP8_MODEL_ID",
+    "OLMOCR_2_7B_1025_MODEL_ID",
+    "OLMOCR_2_7B_1025_OCR_TEMPLATE",
 ]
diff --git a/tests/test_hf_ocr.py b/tests/test_hf_ocr.py
index 8eabd3c..92b26ae 100644
--- a/tests/test_hf_ocr.py
+++ b/tests/test_hf_ocr.py
@@ -12,7 +12,7 @@
 from churro_ocr.errors import ConfigurationError
 from churro_ocr.ocr import OCRClient
 from churro_ocr.page_detection import DocumentPage
-from churro_ocr.prompts import DEFAULT_OCR_OUTPUT_TAG
+from churro_ocr.prompts import DEFAULT_OCR_OUTPUT_TAG, OLMOCR_V4_YAML_PROMPT, parse_olmocr_response
 from churro_ocr.providers import OCRBackendSpec, build_ocr_backend
 from churro_ocr.providers.hf import (
     Churro3BOCRBackend,
@@ -25,6 +25,8 @@
     DOTS_OCR_1_5_MODEL_ID,
     DOTS_OCR_1_5_OCR_PROMPT,
     DOTS_OCR_1_5_OCR_TEMPLATE,
+    OLMOCR_2_7B_1025_MODEL_ID,
+    OLMOCR_2_7B_1025_OCR_TEMPLATE,
     HFChatTemplate,
 )
 
@@ -45,6 +47,63 @@ def test_hf_chat_template_builds_expected_conversation() -> None:
     assert conversation[1]["content"][1]["text"] == "user text"
 
 
+def test_olmocr_template_builds_prompt_before_image() -> None:
+    page = DocumentPage.from_image(Image.new("RGB", (20, 20), color="white"))
+
+    conversation = OLMOCR_2_7B_1025_OCR_TEMPLATE.build_conversation(page)
+
+    assert conversation[0]["role"] == "user"
+    assert conversation[0]["content"][0]["text"] == OLMOCR_V4_YAML_PROMPT
+    assert conversation[0]["content"][1]["type"] == "image"
+
+
+def test_parse_olmocr_response_extracts_plain_text_and_metadata() -> None:
+    text, metadata = parse_olmocr_response(
+        "---\n"
+        "primary_language: en\n"
+        "is_rotation_valid: true\n"
+        "rotation_correction: 0\n"
+        "is_table: true\n"
+        "is_diagram: false\n"
+        "---\n"
+        "# Heading\n\n"
+        "<table><tr><th>Year</th><th>Value</th></tr><tr><td>1900</td><td>42</td></tr></table>\n\n"
+        "![Figure alt text](page_0_0_100_100.png)\n"
+        "Paragraph with [reference](https://example.test)."
+    )
+
+    assert text == "Heading\n\nYear | Value\n1900 | 42\n\nParagraph with reference."
+    assert metadata["front_matter"] == {
+        "primary_language": "en",
+        "is_rotation_valid": True,
+        "rotation_correction": 0,
+        "is_table": True,
+        "is_diagram": False,
+    }
+    assert "Heading" in cast("str", metadata["raw_markdown"])
+
+
+def test_build_ocr_backend_uses_olmocr_profile_defaults_for_hf() -> None:
+    backend = cast(
+        "HuggingFaceVisionOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="hf",
+                model=OLMOCR_2_7B_1025_MODEL_ID,
+            )
+        ),
+    )
+
+    assert backend.template == OLMOCR_2_7B_1025_OCR_TEMPLATE
+    assert backend.model_name == "olmOCR-2-7B-1025"
+    assert backend.generation_kwargs == {
+        "max_new_tokens": 8_000,
+        "temperature": 0.1,
+        "do_sample": True,
+    }
+    assert backend.image_preprocessor(Image.new("RGB", (5_000, 3_000), color="white")).size == (1_288, 772)
+
+
 @pytest.mark.asyncio
 async def test_huggingface_vision_ocr_backend_uses_custom_template(
     monkeypatch: pytest.MonkeyPatch,
@@ -345,7 +404,7 @@ def test_dots_ocr_15_backend_uses_expected_defaults() -> None:
     assert backend.trust_remote_code is True
     assert backend.processor_kwargs == {}
     assert backend.model_kwargs["dtype"] in {"auto", "float32"}
-    if backend.model_kwargs["dtype"] == "auto":
+    if backend.model_kwargs["dtype"] == "auto" and "device_map" in backend.model_kwargs:
         assert backend.model_kwargs["device_map"] == "auto"
         assert "max_memory" in backend.model_kwargs
     assert backend.generation_kwargs == {"max_new_tokens": DEFAULT_OCR_MAX_TOKENS}

From d89bfb8c4aed2c7427005164fc440155a0ab0ab2 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Sun, 5 Apr 2026 22:46:11 +0000
Subject: [PATCH 02/28] build(repo): slim runtime extras and pin ruff

---
 pixi.lock                   | 540 +-----------------------------------
 pyproject.toml              |  13 +-
 ruff.toml                   |   2 +-
 scripts/package_check.py    |  37 ++-
 tests/test_package_check.py |  17 ++
 5 files changed, 57 insertions(+), 552 deletions(-)

diff --git a/pixi.lock b/pixi.lock
index edf4dd3..3eb0c09 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -62,7 +62,6 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h366c992_103.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda
-      - pypi: https://files.pythonhosted.org/packages/7e/46/02ac5e262d4af18054b3e922b2baedbb2a03289ee792162de60a865defc5/accelerate-1.13.0-py3-none-any.whl
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-  - mypy==1.18.* ; extra == 'type'
-  - importlib-metadata>=7.0.2 ; python_full_version < '3.10' and extra == 'type'
-  - jaraco-develop>=7.21 ; sys_platform != 'cygwin' and extra == 'type'
-  requires_python: '>=3.9'
 - pypi: https://files.pythonhosted.org/packages/e0/f9/0595336914c5619e5f28a1fb793285925a8cd4b432c9da0a987836c7f822/shellingham-1.5.4-py2.py3-none-any.whl
   name: shellingham
   version: 1.5.4
@@ -3782,15 +3311,6 @@ packages:
   - python-multipart>=0.0.18 ; extra == 'full'
   - pyyaml ; extra == 'full'
   requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/a2/09/77d55d46fd61b4a135c444fc97158ef34a095e5681d0a6c10b75bf356191/sympy-1.14.0-py3-none-any.whl
-  name: sympy
-  version: 1.14.0
-  sha256: e091cc3e99d2141a0ba2847328f5479b05d94a6635cb96148ccb3f34671bd8f5
-  requires_dist:
-  - mpmath>=1.1.0,<1.4
-  - pytest>=7.1.0 ; extra == 'dev'
-  - hypothesis>=6.70.0 ; extra == 'dev'
-  requires_python: '>=3.9'
 - pypi: https://files.pythonhosted.org/packages/f5/de/9341a6d7a8f1b448573bbf3425fa57669ac58258a667eb48a25dfe916d70/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_x86_64.whl
   name: tiktoken
   version: 0.12.0
@@ -3832,40 +3352,6 @@ packages:
   - setuptools-rust ; extra == 'docs'
   - tokenizers[testing] ; extra == 'dev'
   requires_python: '>=3.9'
-- pypi: https://files.pythonhosted.org/packages/47/e8/b98ca2d39b2e0e4730c0ee52537e488e7008025bc77ca89552ff91021f7c/torch-2.11.0-cp314-cp314-manylinux_2_28_x86_64.whl
-  name: torch
-  version: 2.11.0
-  sha256: 4dc8b3809469b6c30b411bb8c4cad3828efd26236153d9beb6a3ec500f211a60
-  requires_dist:
-  - filelock
-  - typing-extensions>=4.10.0
-  - setuptools<82
-  - sympy>=1.13.3
-  - networkx>=2.5.1
-  - jinja2
-  - fsspec>=0.8.5
-  - cuda-toolkit[cublas,cudart,cufft,cufile,cupti,curand,cusolver,cusparse,nvjitlink,nvrtc,nvtx]==13.0.2 ; sys_platform == 'linux'
-  - cuda-bindings>=13.0.3,<14 ; sys_platform == 'linux'
-  - nvidia-cudnn-cu13==9.19.0.56 ; sys_platform == 'linux'
-  - nvidia-cusparselt-cu13==0.8.0 ; sys_platform == 'linux'
-  - nvidia-nccl-cu13==2.28.9 ; sys_platform == 'linux'
-  - nvidia-nvshmem-cu13==3.4.5 ; sys_platform == 'linux'
-  - triton==3.6.0 ; sys_platform == 'linux'
-  - optree>=0.13.0 ; extra == 'optree'
-  - opt-einsum>=3.3 ; extra == 'opt-einsum'
-  - pyyaml ; extra == 'pyyaml'
-  requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/a4/21/a2266f7f1b0e58e624ff15fd6f01041f59182c49551ece0db9a183071329/torchvision-0.26.0-cp314-cp314-manylinux_2_28_x86_64.whl
-  name: torchvision
-  version: 0.26.0
-  sha256: 0f3e572efe62ad645017ea847e0b5e4f2f638d4e39f05bc011d1eb9ac68d4806
-  requires_dist:
-  - numpy
-  - torch==2.11.0
-  - pillow>=5.3.0,!=8.3.*
-  - gdown>=4.7.3 ; extra == 'gdown'
-  - scipy ; extra == 'scipy'
-  requires_python: '>=3.10,!=3.14.1'
 - pypi: https://files.pythonhosted.org/packages/16/e1/3079a9ff9b8e11b846c6ac5c8b5bfb7ff225eee721825310c91b3b50304f/tqdm-4.67.3-py3-none-any.whl
   name: tqdm
   version: 4.67.3
@@ -4346,26 +3832,6 @@ packages:
   - opentelemetry-exporter-otlp ; extra == 'open-telemetry'
   - opentelemetry-sdk ; extra == 'open-telemetry'
   requires_python: '>=3.9.0'
-- pypi: https://files.pythonhosted.org/packages/df/3d/9e7eee57b37c80cec63322c0231bb6da3cfe535a91d7a4d64896fcb89357/triton-3.6.0-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
-  name: triton
-  version: 3.6.0
-  sha256: a17a5d5985f0ac494ed8a8e54568f092f7057ef60e1b0fa09d3fd1512064e803
-  requires_dist:
-  - importlib-metadata ; python_full_version < '3.10'
-  - cmake>=3.20,<4.0 ; extra == 'build'
-  - lit ; extra == 'build'
-  - autopep8 ; extra == 'tests'
-  - isort ; extra == 'tests'
-  - numpy ; extra == 'tests'
-  - pytest ; extra == 'tests'
-  - pytest-forked ; extra == 'tests'
-  - pytest-xdist ; extra == 'tests'
-  - scipy>=1.7.1 ; extra == 'tests'
-  - llnl-hatchet ; extra == 'tests'
-  - matplotlib ; extra == 'tutorials'
-  - pandas ; extra == 'tutorials'
-  - tabulate ; extra == 'tutorials'
-  requires_python: '>=3.10,<3.15'
 - pypi: https://files.pythonhosted.org/packages/3a/7a/882d99539b19b1490cac5d77c67338d126e4122c8276bf640e411650c830/twine-6.2.0-py3-none-any.whl
   name: twine
   version: 6.2.0
diff --git a/pyproject.toml b/pyproject.toml
index 013c748..568ef00 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -5,7 +5,7 @@ build-backend = "setuptools.build_meta"
 [project]
 name = "churro-ocr"
 version = "0.2.0"
-description = "Library-first OCR and layout detection for historical documents"
+description = "OCR for historical documents"
 readme = { file = "docs/pypi.md", content-type = "text/markdown" }
 requires-python = ">=3.12"
 license = "Apache-2.0"
@@ -33,12 +33,9 @@ azure = [
 ]
 hf = [
     "qwen-vl-utils",
-    "transformers[torch]>=4.57.0,<5",
-    "torchvision",
+    "transformers>=4.57.0,<5",
 ]
 vllm = [
-    "transformers>=4.57.0,<5",
-    "torchvision",
     "vllm>=0.18,<1",
 ]
 mistral = [
@@ -55,9 +52,7 @@ all = [
     "litellm[caching]==1.82.3",
     "azure-ai-documentintelligence==1.0.2",
     "qwen-vl-utils",
-    "transformers[torch]>=4.57.0,<5",
-    "torchvision",
-    "vllm>=0.18,<1",
+    "transformers>=4.57.0,<5",
     "mistralai>=1.6.0,<2",
     "pypdfium2>=5,<6",
 ]
@@ -89,7 +84,7 @@ dev-test = [
 dev-tooling = [
     "build",
     "pre-commit>=4,<5",
-    "ruff",
+    "ruff==0.15.9",
     "twine",
     "ty>=0.0.28,<0.0.29",
 ]
diff --git a/ruff.toml b/ruff.toml
index 3fb075f..869de7c 100644
--- a/ruff.toml
+++ b/ruff.toml
@@ -1,5 +1,5 @@
 line-length = 110
-required-version = "==0.15.7"
+required-version = "==0.15.9"
 
 [lint]
 select = ["E", "F", "I", "B", "UP", "ASYNC", "SIM", "D"]
diff --git a/scripts/package_check.py b/scripts/package_check.py
index 8e23c23..865ae77 100644
--- a/scripts/package_check.py
+++ b/scripts/package_check.py
@@ -125,11 +125,7 @@ def _assert_metadata(metadata_message: Message, entry_points_text: str) -> None:
     if provides_extra != EXPECTED_EXTRAS:
         raise RuntimeError(f"Unexpected extras set: {sorted(provides_extra)!r}.")
 
-    requires_dist = metadata_message.get_all("Requires-Dist", [])
-    if not any(
-        requirement.startswith("vllm") and 'extra == "all"' in requirement for requirement in requires_dist
-    ):
-        raise RuntimeError("The all extra does not include vllm.")
+    _assert_local_runtime_packaging_policy(metadata_message)
 
     if (
         "[console_scripts]" not in entry_points_text
@@ -138,6 +134,37 @@ def _assert_metadata(metadata_message: Message, entry_points_text: str) -> None:
         raise RuntimeError("Console script entry point is missing or incorrect.")
 
 
+def _iter_requirements_for_extra(metadata_message: Message, extra: str) -> list[Requirement]:
+    requirements: list[Requirement] = []
+    for requirement_text in metadata_message.get_all("Requires-Dist", []):
+        parsed = Requirement(requirement_text)
+        marker_text = str(parsed.marker) if parsed.marker is not None else ""
+        if f'extra == "{extra}"' in marker_text:
+            requirements.append(parsed)
+    return requirements
+
+
+def _assert_local_runtime_packaging_policy(metadata_message: Message) -> None:
+    disallowed_runtime_reqs: list[str] = []
+    for extra in ("hf", "all"):
+        for requirement in _iter_requirements_for_extra(metadata_message, extra):
+            normalized_name = requirement.name.replace("_", "-").lower()
+            if extra == "all" and normalized_name == "vllm":
+                disallowed_runtime_reqs.append(f"{extra}:{requirement}")
+                continue
+            if normalized_name in {"torch", "torchvision"}:
+                disallowed_runtime_reqs.append(f"{extra}:{requirement}")
+                continue
+            if normalized_name == "transformers" and "torch" in requirement.extras:
+                disallowed_runtime_reqs.append(f"{extra}:{requirement}")
+    if disallowed_runtime_reqs:
+        formatted = ", ".join(sorted(disallowed_runtime_reqs))
+        raise RuntimeError(
+            "PyPI extras for active-environment runtimes must not pin a local PyTorch or vLLM runtime. "
+            f"Found disallowed requirements: {formatted}."
+        )
+
+
 def _assert_runtime_only_artifacts(wheel: Path, sdist: Path) -> None:
     with zipfile.ZipFile(wheel) as zip_file:
         wheel_names = zip_file.namelist()
diff --git a/tests/test_package_check.py b/tests/test_package_check.py
index 4ee8953..e208efe 100644
--- a/tests/test_package_check.py
+++ b/tests/test_package_check.py
@@ -43,3 +43,20 @@ def _always_missing(_: str):
 
     with pytest.raises(RuntimeError, match="pillow \\(not installed in the Pixi audit environment\\)"):
         package_check._audit_dependency_licenses(_metadata_message("Pillow<12,>=10.4.0"))
+
+
+def test_local_runtime_packaging_policy_rejects_direct_torch_runtime_pin() -> None:
+    metadata_message = _metadata_message(
+        'transformers[torch]<5,>=4.57.0; extra == "hf"',
+        'torchvision; extra == "all"',
+    )
+
+    with pytest.raises(RuntimeError, match="must not pin a local PyTorch or vLLM runtime"):
+        package_check._assert_local_runtime_packaging_policy(metadata_message)
+
+
+def test_local_runtime_packaging_policy_rejects_vllm_in_all_extra() -> None:
+    metadata_message = _metadata_message('vllm<1,>=0.18; extra == "all"')
+
+    with pytest.raises(RuntimeError, match="must not pin a local PyTorch or vLLM runtime"):
+        package_check._assert_local_runtime_packaging_policy(metadata_message)

From cb4a52035d73bdd224efff9fee79271e41721ed6 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Sun, 5 Apr 2026 22:47:53 +0000
Subject: [PATCH 03/28] feat(runtime): add uv-managed runtime installers

---
 src/churro_ocr/_internal/install.py        | 284 +++++++++++++++++++++
 src/churro_ocr/_internal/litellm.py        |   4 +-
 src/churro_ocr/_internal/pdf.py            |   3 +-
 src/churro_ocr/cli.py                      |  71 ++++++
 src/churro_ocr/providers/hf.py             |  26 +-
 src/churro_ocr/providers/ocr.py            |   6 +-
 src/churro_ocr/providers/page_detection.py |   4 +-
 tests/test_cli.py                          | 105 ++++++++
 tests/test_hf_ocr.py                       |   1 +
 tests/test_install.py                      | 214 ++++++++++++++++
 tests/test_internal_helpers.py             |  38 ++-
 11 files changed, 735 insertions(+), 21 deletions(-)
 create mode 100644 src/churro_ocr/_internal/install.py
 create mode 100644 tests/test_install.py

diff --git a/src/churro_ocr/_internal/install.py b/src/churro_ocr/_internal/install.py
new file mode 100644
index 0000000..dff132f
--- /dev/null
+++ b/src/churro_ocr/_internal/install.py
@@ -0,0 +1,284 @@
+"""UV-backed runtime installation helpers."""
+
+from __future__ import annotations
+
+import os
+import shutil
+import subprocess
+import sys
+from dataclasses import dataclass
+from importlib import metadata
+from pathlib import Path
+from typing import Final
+
+from churro_ocr.errors import ConfigurationError
+
+PROJECT_DISTRIBUTION_NAME: Final[str] = "churro-ocr"
+VLLM_RUNTIME_DIR_ENV: Final[str] = "CHURRO_OCR_VLLM_RUNTIME_DIR"
+DEFAULT_VLLM_RUNTIME_DIR: Final[Path] = Path.home() / ".cache" / "churro-ocr" / "runtimes" / "vllm"
+INSTALL_TARGETS: Final[tuple[str, ...]] = (
+    "llm",
+    "local",
+    "hf",
+    "vllm",
+    "azure",
+    "mistral",
+    "pdf",
+    "all",
+)
+_CURRENT_ENV_TARGET_EXTRAS: Final[dict[str, tuple[str, ...]]] = {
+    "llm": ("llm",),
+    "local": ("local",),
+    "hf": ("hf",),
+    "vllm": ("local",),
+    "azure": ("azure",),
+    "mistral": ("mistral",),
+    "pdf": ("pdf",),
+    "all": ("llm", "local", "hf", "azure", "mistral", "pdf"),
+}
+_PYTORCH_TARGETS: Final[frozenset[str]] = frozenset({"hf", "all"})
+_PYTORCH_PACKAGES: Final[tuple[str, ...]] = ("torch", "torchvision")
+
+
+@dataclass(frozen=True, slots=True)
+class RuntimeInstallResult:
+    """Summary of a completed runtime installation."""
+
+    target: str
+    executed_commands: tuple[tuple[str, ...], ...]
+    notes: tuple[str, ...] = ()
+    vllm_runtime_dir: Path | None = None
+
+
+def install_command_hint(target: str) -> str:
+    """Return a short user-facing install hint for a runtime target."""
+    return f"Run `churro-ocr install {target}`."
+
+
+def recommended_vllm_runtime_hint() -> str:
+    """Return the short user-facing hint for the dedicated vLLM runtime."""
+    return "Run `churro-ocr install vllm`."
+
+
+def resolve_vllm_runtime_dir(runtime_dir: Path | None = None) -> Path:
+    """Resolve the dedicated vLLM runtime directory."""
+    if runtime_dir is not None:
+        return runtime_dir.expanduser().resolve()
+    override = os.environ.get(VLLM_RUNTIME_DIR_ENV)
+    if override:
+        return Path(override).expanduser().resolve()
+    return DEFAULT_VLLM_RUNTIME_DIR
+
+
+def install_runtime_dependencies(
+    *,
+    target: str,
+    torch_backend: str = "auto",
+    vllm_runtime_dir: Path | None = None,
+) -> RuntimeInstallResult:
+    """Install one of the supported optional runtime targets with UV."""
+    normalized_target = target.strip().lower()
+    if normalized_target not in INSTALL_TARGETS:
+        supported = ", ".join(INSTALL_TARGETS)
+        raise ConfigurationError(f"Unknown install target '{target}'. Choose one of: {supported}.")
+
+    uv_executable = _require_uv_executable()
+    executed_commands: list[tuple[str, ...]] = []
+    notes: list[str] = []
+
+    current_env_extras = _CURRENT_ENV_TARGET_EXTRAS.get(normalized_target, ())
+    requirements = _requirements_for_extra(current_env_extras)
+    if requirements:
+        executed_commands.append(
+            _run_command(
+                [
+                    uv_executable,
+                    "pip",
+                    "install",
+                    "--python",
+                    sys.executable,
+                    "--upgrade",
+                    *requirements,
+                ]
+            )
+        )
+
+    if normalized_target in _PYTORCH_TARGETS:
+        executed_commands.append(
+            _run_command(
+                [
+                    uv_executable,
+                    "pip",
+                    "install",
+                    "--python",
+                    sys.executable,
+                    "--upgrade",
+                    f"--torch-backend={torch_backend}",
+                    *_PYTORCH_PACKAGES,
+                ]
+            )
+        )
+
+    resolved_runtime_dir: Path | None = None
+    if normalized_target in {"vllm", "all"}:
+        resolved_runtime_dir = resolve_vllm_runtime_dir(vllm_runtime_dir)
+        runtime_python = _ensure_runtime_python(resolved_runtime_dir)
+        executed_commands.append(
+            _run_command(
+                [
+                    uv_executable,
+                    "pip",
+                    "install",
+                    "--python",
+                    str(runtime_python),
+                    "--upgrade",
+                    f"--torch-backend={torch_backend}",
+                    _requirement_for_extra("vllm", package_name="vllm"),
+                ]
+            )
+        )
+        notes.append(
+            "The dedicated vLLM runtime is ready. Start it with `churro-ocr serve-vllm --model <model-id>`."
+        )
+        notes.append(
+            "Use `--backend openai-compatible --base-url http://127.0.0.1:8000/v1` "
+            "to connect to the served runtime."
+        )
+
+    return RuntimeInstallResult(
+        target=normalized_target,
+        executed_commands=tuple(executed_commands),
+        notes=tuple(notes),
+        vllm_runtime_dir=resolved_runtime_dir,
+    )
+
+
+def serve_vllm_runtime(
+    *,
+    model: str,
+    host: str = "127.0.0.1",
+    port: int = 8000,
+    runtime_dir: Path | None = None,
+    extra_args: tuple[str, ...] = (),
+) -> int:
+    """Run `python -m vllm serve` from the dedicated Churro vLLM runtime."""
+    resolved_runtime_dir = resolve_vllm_runtime_dir(runtime_dir)
+    runtime_python = _venv_python(resolved_runtime_dir)
+    if not runtime_python.exists():
+        raise ConfigurationError(
+            f"No dedicated vLLM runtime exists at {resolved_runtime_dir}. {recommended_vllm_runtime_hint()}"
+        )
+
+    command = [
+        str(runtime_python),
+        "-m",
+        "vllm",
+        "serve",
+        model,
+        "--host",
+        host,
+        "--port",
+        str(port),
+        *extra_args,
+    ]
+    try:
+        completed = subprocess.run(command, check=False)
+    except OSError as exc:  # pragma: no cover - depends on host process state
+        raise ConfigurationError(
+            f"Failed to launch the dedicated vLLM runtime at {resolved_runtime_dir}: {exc}"
+        ) from exc
+    return int(completed.returncode)
+
+
+def _require_uv_executable() -> str:
+    uv_executable = shutil.which("uv")
+    if uv_executable is None:
+        raise ConfigurationError(
+            "`churro-ocr install` requires `uv` on PATH. Install uv and rerun the command."
+        )
+    return uv_executable
+
+
+def _distribution_requirements() -> list[str]:
+    try:
+        distribution = metadata.distribution(PROJECT_DISTRIBUTION_NAME)
+    except metadata.PackageNotFoundError as exc:  # pragma: no cover - depends on install mode
+        raise ConfigurationError(
+            "The Churro installer must run from an installed `churro-ocr` environment."
+        ) from exc
+    return list(distribution.requires or [])
+
+
+def _requirements_for_extra(extras: tuple[str, ...]) -> list[str]:
+    requirements = _distribution_requirements()
+    selected: list[str] = []
+    for extra in extras:
+        for requirement_text in requirements:
+            requirement, _, marker = requirement_text.partition(";")
+            if f'extra == "{extra}"' not in marker:
+                continue
+            normalized_requirement = requirement.strip()
+            if normalized_requirement and normalized_requirement not in selected:
+                selected.append(normalized_requirement)
+    return selected
+
+
+def _requirement_for_extra(extra: str, *, package_name: str) -> str:
+    normalized_package_name = package_name.replace("_", "-").lower()
+    for requirement in _requirements_for_extra((extra,)):
+        dependency_name = _requirement_name(requirement)
+        if dependency_name.replace("_", "-").lower() == normalized_package_name:
+            return requirement
+    raise ConfigurationError(
+        f"Could not resolve the `{package_name}` dependency from the `{extra}` extra metadata."
+    )
+
+
+def _ensure_runtime_python(runtime_dir: Path) -> Path:
+    runtime_python = _venv_python(runtime_dir)
+    if runtime_python.exists():
+        return runtime_python
+
+    runtime_dir.parent.mkdir(parents=True, exist_ok=True)
+    try:
+        subprocess.run(
+            [sys.executable, "-m", "venv", str(runtime_dir)],
+            check=True,
+        )
+    except (OSError, subprocess.CalledProcessError) as exc:
+        raise ConfigurationError(
+            f"Failed to create the dedicated vLLM runtime at {runtime_dir}: {exc}"
+        ) from exc
+
+    if not runtime_python.exists():
+        raise ConfigurationError(
+            f"Created the dedicated vLLM runtime at {runtime_dir}, but no Python interpreter was found."
+        )
+    return runtime_python
+
+
+def _run_command(command: list[str]) -> tuple[str, ...]:
+    try:
+        subprocess.run(command, check=True)
+    except (OSError, subprocess.CalledProcessError) as exc:
+        rendered_command = " ".join(command)
+        raise ConfigurationError(f"Command failed: {rendered_command}") from exc
+    return tuple(command)
+
+
+def _requirement_name(requirement: str) -> str:
+    name_chars: list[str] = []
+    for character in requirement:
+        if character.isalnum() or character in {"-", "_", "."}:
+            name_chars.append(character)
+            continue
+        if character == "[":
+            break
+        break
+    return "".join(name_chars)
+
+
+def _venv_python(venv_dir: Path) -> Path:
+    if sys.platform == "win32":
+        return venv_dir / "Scripts" / "python.exe"
+    return venv_dir / "bin" / "python"
diff --git a/src/churro_ocr/_internal/litellm.py b/src/churro_ocr/_internal/litellm.py
index 967d3c3..2daffc5 100644
--- a/src/churro_ocr/_internal/litellm.py
+++ b/src/churro_ocr/_internal/litellm.py
@@ -12,6 +12,7 @@
 from PIL import Image
 
 from churro_ocr._internal.image import image_to_base64
+from churro_ocr._internal.install import install_command_hint
 from churro_ocr.errors import ConfigurationError, ProviderError
 from churro_ocr.providers.specs import LiteLLMTransportConfig
 from churro_ocr.templates import OCRConversation
@@ -28,8 +29,7 @@ def _ensure_initialized() -> None:
         import litellm
     except ImportError as exc:  # pragma: no cover - optional extra path
         raise ConfigurationError(
-            "LiteLLM-backed providers require the 'llm' extra. "
-            'Install with `pip install "churro-ocr[llm]"`.'
+            f"LiteLLM-backed providers require the `llm` runtime. {install_command_hint('llm')}"
         ) from exc
 
     litellm_any = cast(Any, litellm)
diff --git a/src/churro_ocr/_internal/pdf.py b/src/churro_ocr/_internal/pdf.py
index 4f89194..770819d 100644
--- a/src/churro_ocr/_internal/pdf.py
+++ b/src/churro_ocr/_internal/pdf.py
@@ -6,6 +6,7 @@
 
 from PIL import Image
 
+from churro_ocr._internal.install import install_command_hint
 from churro_ocr.errors import ConfigurationError
 
 
@@ -15,7 +16,7 @@ def rasterize_pdf(path: str | Path, *, dpi: int = 300) -> list[Image.Image]:
         import pypdfium2
     except ImportError as exc:  # pragma: no cover - depends on optional extra
         raise ConfigurationError(
-            "PDF support requires the 'pdf' extra. Install with `pip install \"churro-ocr[pdf]\"`."
+            f"PDF support requires the `pdf` runtime. {install_command_hint('pdf')}"
         ) from exc
 
     resolved = Path(path)
diff --git a/src/churro_ocr/cli.py b/src/churro_ocr/cli.py
index 8715bcd..5d2ff87 100644
--- a/src/churro_ocr/cli.py
+++ b/src/churro_ocr/cli.py
@@ -6,6 +6,12 @@
 
 import typer
 
+from churro_ocr._internal.install import (
+    INSTALL_TARGETS,
+    install_runtime_dependencies,
+    serve_vllm_runtime,
+)
+from churro_ocr.errors import ConfigurationError
 from churro_ocr.ocr import OCRClient
 from churro_ocr.page_detection import DocumentPage, DocumentPageDetector, PageDetectionRequest
 from churro_ocr.providers import (
@@ -23,6 +29,8 @@
 
 app = typer.Typer(help="churro-ocr library-first CLI")
 
+_INSTALL_TARGET_METAVAR = "{" + "|".join(INSTALL_TARGETS) + "}"
+
 
 def _build_ocr_backend(
     *,
@@ -230,6 +238,69 @@ def extract_pages_command(
         typer.echo(str(output_path))
 
 
+@app.command("install")
+def install_command(
+    target: str = typer.Argument(
+        ...,
+        metavar=_INSTALL_TARGET_METAVAR,
+        help="Runtime target to install into the active environment with uv.",
+    ),
+    torch_backend: str = typer.Option(
+        "auto",
+        help="PyTorch backend passed through to uv when a local runtime needs torch.",
+    ),
+    vllm_runtime_dir: Path | None = typer.Option(
+        None,
+        help="Override the dedicated vLLM runtime directory for `install vllm`.",
+    ),
+) -> None:
+    """Install optional runtime dependencies with uv."""
+    try:
+        result = install_runtime_dependencies(
+            target=target,
+            torch_backend=torch_backend,
+            vllm_runtime_dir=vllm_runtime_dir,
+        )
+    except ConfigurationError as exc:
+        typer.echo(str(exc), err=True)
+        raise typer.Exit(code=1) from exc
+
+    typer.echo(f"Installed runtime target: {result.target}")
+    if result.vllm_runtime_dir is not None:
+        typer.echo(f"Dedicated vLLM runtime: {result.vllm_runtime_dir}")
+    for note in result.notes:
+        typer.echo(note)
+
+
+@app.command(
+    "serve-vllm",
+    context_settings={"allow_extra_args": True, "ignore_unknown_options": True},
+)
+def serve_vllm_command(
+    ctx: typer.Context,
+    model: str = typer.Option(..., help="Model identifier to serve from the dedicated vLLM runtime."),
+    host: str = typer.Option("127.0.0.1", help="Bind address passed to `vllm serve`."),
+    port: int = typer.Option(8000, help="Port passed to `vllm serve`."),
+    vllm_runtime_dir: Path | None = typer.Option(
+        None,
+        help="Override the dedicated vLLM runtime directory.",
+    ),
+) -> None:
+    """Start the dedicated vLLM runtime managed by `churro-ocr install vllm`."""
+    try:
+        exit_code = serve_vllm_runtime(
+            model=model,
+            host=host,
+            port=port,
+            runtime_dir=vllm_runtime_dir,
+            extra_args=tuple(ctx.args),
+        )
+    except ConfigurationError as exc:
+        typer.echo(str(exc), err=True)
+        raise typer.Exit(code=1) from exc
+    raise typer.Exit(code=exit_code)
+
+
 def main() -> None:
     """Console-script entrypoint."""
     app()
diff --git a/src/churro_ocr/providers/hf.py b/src/churro_ocr/providers/hf.py
index 7832b29..54e62a3 100644
--- a/src/churro_ocr/providers/hf.py
+++ b/src/churro_ocr/providers/hf.py
@@ -5,9 +5,11 @@
 import asyncio
 import threading
 from dataclasses import dataclass, field
+from importlib import import_module
 from pathlib import Path
 from typing import Any
 
+from churro_ocr._internal.install import install_command_hint
 from churro_ocr._internal.prompt_logging import log_prompt_payload_once
 from churro_ocr.errors import ConfigurationError
 from churro_ocr.ocr import OCRBackend, OCRResult
@@ -35,6 +37,11 @@
     OCRPromptTemplateLike,
 )
 
+_HF_EXTRA_INSTALL_HINT = install_command_hint("hf")
+_HF_TORCH_INSTALL_HINT = (
+    f"Hugging Face OCR requires a separately installed PyTorch runtime. {_HF_EXTRA_INSTALL_HINT}"
+)
+
 
 @dataclass(slots=True)
 class _HFRuntime:
@@ -43,13 +50,21 @@ class _HFRuntime:
     process_vision_info: Any
 
 
+def _ensure_hf_torch_runtime() -> None:
+    try:
+        import_module("torch")
+    except ImportError as exc:  # pragma: no cover - optional extra path
+        raise ConfigurationError(_HF_TORCH_INSTALL_HINT) from exc
+
+
 def _load_hf_runtime() -> _HFRuntime:
+    _ensure_hf_torch_runtime()
     try:
         from qwen_vl_utils import process_vision_info
         from transformers import AutoModelForImageTextToText, AutoProcessor
     except ImportError as exc:  # pragma: no cover - optional extra path
         raise ConfigurationError(
-            "Hugging Face OCR requires the 'hf' extra. Install with `pip install \"churro-ocr[hf]\"`."
+            f"Hugging Face OCR requires the `hf` runtime. {_HF_EXTRA_INSTALL_HINT}"
         ) from exc
 
     return _HFRuntime(
@@ -60,12 +75,13 @@ def _load_hf_runtime() -> _HFRuntime:
 
 
 def _load_hf_causal_runtime() -> _HFRuntime:
+    _ensure_hf_torch_runtime()
     try:
         from qwen_vl_utils import process_vision_info
         from transformers import AutoModelForCausalLM, AutoProcessor
     except ImportError as exc:  # pragma: no cover - optional extra path
         raise ConfigurationError(
-            "Hugging Face OCR requires the 'hf' extra. Install with `pip install \"churro-ocr[hf]\"`."
+            f"Hugging Face OCR requires the `hf` runtime. {_HF_EXTRA_INSTALL_HINT}"
         ) from exc
 
     return _HFRuntime(
@@ -129,7 +145,7 @@ def _prepare_dots_ocr_model_dir(model_id: str) -> str:
         from huggingface_hub import snapshot_download
     except ImportError as exc:  # pragma: no cover - transitively provided by transformers
         raise ConfigurationError(
-            'Hugging Face OCR requires huggingface_hub. Install with `pip install "churro-ocr[hf]"`.'
+            f"Hugging Face OCR requires the `hf` runtime. {_HF_EXTRA_INSTALL_HINT}"
         ) from exc
 
     model_dir = (
@@ -148,8 +164,8 @@ def _prepare_dots_ocr_model_dir(model_id: str) -> str:
 def _default_dots_ocr_1_5_model_kwargs() -> dict[str, object]:
     model_kwargs: dict[str, object] = {"dtype": "auto"}
     try:
-        import torch
-    except ImportError:  # pragma: no cover - torch comes from the hf extra
+        torch = import_module("torch")
+    except ImportError:  # pragma: no cover - torch is installed separately for local HF use
         return model_kwargs
 
     if not torch.cuda.is_available():
diff --git a/src/churro_ocr/providers/ocr.py b/src/churro_ocr/providers/ocr.py
index 8f58f98..87836ed 100644
--- a/src/churro_ocr/providers/ocr.py
+++ b/src/churro_ocr/providers/ocr.py
@@ -10,6 +10,7 @@
 from typing import Any
 
 from churro_ocr._internal.image import image_to_base64
+from churro_ocr._internal.install import install_command_hint
 from churro_ocr._internal.litellm import LiteLLMTransport
 from churro_ocr._internal.prompt_logging import log_prompt_payload_once
 from churro_ocr.errors import ConfigurationError, ProviderError
@@ -183,7 +184,7 @@ async def _get_client(self) -> Any:
                 from azure.core.credentials import AzureKeyCredential
             except ImportError as exc:  # pragma: no cover - optional extra path
                 raise ConfigurationError(
-                    "Azure OCR requires the 'azure' extra. Install with `pip install \"churro-ocr[azure]\"`."
+                    f"Azure OCR requires the `azure` runtime. {install_command_hint('azure')}"
                 ) from exc
 
             client = DocumentIntelligenceClient(
@@ -269,8 +270,7 @@ async def _get_client(self) -> Any:
                 from mistralai import Mistral
             except ImportError as exc:  # pragma: no cover - optional extra path
                 raise ConfigurationError(
-                    "Mistral OCR requires the 'mistral' extra. "
-                    'Install with `pip install "churro-ocr[mistral]"`.'
+                    f"Mistral OCR requires the `mistral` runtime. {install_command_hint('mistral')}"
                 ) from exc
 
             client = Mistral(api_key=self.api_key)
diff --git a/src/churro_ocr/providers/page_detection.py b/src/churro_ocr/providers/page_detection.py
index b967e4f..cee234d 100644
--- a/src/churro_ocr/providers/page_detection.py
+++ b/src/churro_ocr/providers/page_detection.py
@@ -10,6 +10,7 @@
 
 from PIL import Image, ImageDraw, ImageOps
 
+from churro_ocr._internal.install import install_command_hint
 from churro_ocr._internal.litellm import LiteLLMTransport
 from churro_ocr._internal.logging import logger
 from churro_ocr._internal.runtime import run_sync
@@ -1202,8 +1203,7 @@ async def detect(self, image: Image.Image) -> list[PageCandidate]:
             from azure.core.credentials import AzureKeyCredential
         except ImportError as exc:  # pragma: no cover - optional extra path
             raise ConfigurationError(
-                "Azure page detection requires the 'azure' extra. "
-                'Install with `pip install "churro-ocr[azure]"`.'
+                f"Azure page detection requires the `azure` runtime. {install_command_hint('azure')}"
             ) from exc
 
         buffer = BytesIO()
diff --git a/tests/test_cli.py b/tests/test_cli.py
index a6e6715..684071a 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -4,12 +4,14 @@
 import subprocess
 import sys
 from pathlib import Path
+from types import SimpleNamespace
 
 import pytest
 from PIL import Image
 
 import churro_ocr.cli as cli_module
 from churro_ocr.cli import app
+from churro_ocr.errors import ConfigurationError
 from churro_ocr.ocr import OCRResult
 from churro_ocr.page_detection import DocumentPage, PageDetectionResult
 from churro_ocr.prompts import DEFAULT_OCR_OUTPUT_TAG
@@ -198,6 +200,105 @@ def test_build_ocr_backend_uses_generic_defaults_for_qwen_3_5_0_8b() -> None:
     assert vllm_backend.llm_kwargs == {}
 
 
+def test_install_command_invokes_runtime_installer(
+    monkeypatch: pytest.MonkeyPatch,
+    cli_runner,
+    tmp_path: Path,
+) -> None:
+    captured: dict[str, object] = {}
+
+    def _fake_install_runtime_dependencies(**kwargs: object) -> SimpleNamespace:
+        captured.update(kwargs)
+        return SimpleNamespace(
+            target="vllm",
+            notes=("runtime ready",),
+            vllm_runtime_dir=tmp_path / "vllm-runtime",
+        )
+
+    monkeypatch.setattr(
+        "churro_ocr.cli.install_runtime_dependencies",
+        _fake_install_runtime_dependencies,
+    )
+
+    result = cli_runner.invoke(
+        app,
+        [
+            "install",
+            "vllm",
+            "--torch-backend",
+            "cu126",
+        ],
+    )
+
+    assert result.exit_code == 0
+    assert captured == {
+        "target": "vllm",
+        "torch_backend": "cu126",
+        "vllm_runtime_dir": None,
+    }
+    assert "Installed runtime target: vllm" in result.output
+    assert "runtime ready" in result.output
+
+
+def test_install_command_surfaces_configuration_errors(
+    monkeypatch: pytest.MonkeyPatch,
+    cli_runner,
+) -> None:
+    def _raise_configuration_error(**_: object) -> SimpleNamespace:
+        raise ConfigurationError("missing uv")
+
+    monkeypatch.setattr(
+        "churro_ocr.cli.install_runtime_dependencies",
+        _raise_configuration_error,
+    )
+
+    result = cli_runner.invoke(app, ["install", "hf"])
+
+    assert result.exit_code == 1
+    assert "missing uv" in result.output
+
+
+def test_serve_vllm_command_forwards_extra_args(
+    monkeypatch: pytest.MonkeyPatch,
+    cli_runner,
+    tmp_path: Path,
+) -> None:
+    captured: dict[str, object] = {}
+
+    def _fake_serve_vllm_runtime(**kwargs: object) -> int:
+        captured.update(kwargs)
+        return 0
+
+    monkeypatch.setattr(
+        "churro_ocr.cli.serve_vllm_runtime",
+        _fake_serve_vllm_runtime,
+    )
+
+    result = cli_runner.invoke(
+        app,
+        [
+            "serve-vllm",
+            "--model",
+            "stanford-oval/churro-3B",
+            "--host",
+            "0.0.0.0",
+            "--port",
+            "9000",
+            "--tensor-parallel-size",
+            "2",
+        ],
+    )
+
+    assert result.exit_code == 0
+    assert captured == {
+        "model": "stanford-oval/churro-3B",
+        "host": "0.0.0.0",
+        "port": 9000,
+        "runtime_dir": None,
+        "extra_args": ("--tensor-parallel-size", "2"),
+    }
+
+
 def test_module_entrypoint_help() -> None:
     result = subprocess.run(
         [sys.executable, "-m", "churro_ocr", "--help"],
@@ -209,6 +310,8 @@ def test_module_entrypoint_help() -> None:
     assert result.returncode == 0
     assert "transcribe" in result.stdout
     assert "extract-pages" in result.stdout
+    assert "install" in result.stdout
+    assert "serve-vllm" in result.stdout
 
 
 def test_console_script_help() -> None:
@@ -225,3 +328,5 @@ def test_console_script_help() -> None:
     assert result.returncode == 0
     assert "transcribe" in result.stdout
     assert "extract-pages" in result.stdout
+    assert "install" in result.stdout
+    assert "serve-vllm" in result.stdout
diff --git a/tests/test_hf_ocr.py b/tests/test_hf_ocr.py
index 92b26ae..78ece49 100644
--- a/tests/test_hf_ocr.py
+++ b/tests/test_hf_ocr.py
@@ -518,6 +518,7 @@ def test_hf_runtime_loaders_use_installed_modules(
     cast(Any, transformers_module).AutoModelForImageTextToText = image_text_model_cls
     cast(Any, transformers_module).AutoModelForCausalLM = causal_model_cls
 
+    monkeypatch.setitem(sys.modules, "torch", ModuleType("torch"))
     monkeypatch.setitem(sys.modules, "qwen_vl_utils", qwen_module)
     monkeypatch.setitem(sys.modules, "transformers", transformers_module)
 
diff --git a/tests/test_install.py b/tests/test_install.py
new file mode 100644
index 0000000..a779656
--- /dev/null
+++ b/tests/test_install.py
@@ -0,0 +1,214 @@
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+from types import SimpleNamespace
+
+import pytest
+
+import churro_ocr._internal.install as install_module
+from churro_ocr.errors import ConfigurationError
+
+
+class _FakeDistribution:
+    def __init__(self, *, requires: list[str] | None) -> None:
+        self.requires = requires
+
+
+def test_install_runtime_dependencies_installs_hf_and_torch_with_uv(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    commands: list[list[str]] = []
+
+    monkeypatch.setattr(
+        install_module.metadata,
+        "distribution",
+        lambda _: _FakeDistribution(
+            requires=[
+                'qwen-vl-utils; extra == "hf"',
+                'transformers>=4.57.0,<5; extra == "hf"',
+            ]
+        ),
+    )
+    monkeypatch.setattr(install_module.shutil, "which", lambda name: "/usr/bin/uv" if name == "uv" else None)
+    monkeypatch.setattr(
+        install_module.subprocess,
+        "run",
+        lambda command, check=True: commands.append(list(command)) or SimpleNamespace(returncode=0),
+    )
+
+    result = install_module.install_runtime_dependencies(
+        target="hf",
+        torch_backend="cu126",
+    )
+
+    assert result.target == "hf"
+    assert result.vllm_runtime_dir is None
+    assert commands == [
+        [
+            "/usr/bin/uv",
+            "pip",
+            "install",
+            "--python",
+            sys.executable,
+            "--upgrade",
+            "qwen-vl-utils",
+            "transformers>=4.57.0,<5",
+        ],
+        [
+            "/usr/bin/uv",
+            "pip",
+            "install",
+            "--python",
+            sys.executable,
+            "--upgrade",
+            "--torch-backend=cu126",
+            "torch",
+            "torchvision",
+        ],
+    ]
+
+
+def test_install_runtime_dependencies_installs_local_client_and_dedicated_vllm_runtime(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+) -> None:
+    commands: list[list[str]] = []
+    runtime_dir = tmp_path / "vllm-runtime"
+    runtime_python = runtime_dir / "bin" / "python"
+
+    monkeypatch.setattr(
+        install_module.metadata,
+        "distribution",
+        lambda _: _FakeDistribution(
+            requires=[
+                'litellm[caching]==1.82.3; extra == "local"',
+                'vllm>=0.18,<1; extra == "vllm"',
+            ]
+        ),
+    )
+    monkeypatch.setattr(install_module.shutil, "which", lambda name: "/usr/bin/uv" if name == "uv" else None)
+
+    def _fake_ensure_runtime_python(path: Path) -> Path:
+        assert path == runtime_dir.resolve()
+        return runtime_python
+
+    monkeypatch.setattr(
+        install_module,
+        "_ensure_runtime_python",
+        _fake_ensure_runtime_python,
+    )
+    monkeypatch.setattr(
+        install_module.subprocess,
+        "run",
+        lambda command, check=True: commands.append(list(command)) or SimpleNamespace(returncode=0),
+    )
+
+    result = install_module.install_runtime_dependencies(
+        target="vllm",
+        vllm_runtime_dir=runtime_dir,
+    )
+
+    assert result.target == "vllm"
+    assert result.vllm_runtime_dir == runtime_dir.resolve()
+    assert commands == [
+        [
+            "/usr/bin/uv",
+            "pip",
+            "install",
+            "--python",
+            sys.executable,
+            "--upgrade",
+            "litellm[caching]==1.82.3",
+        ],
+        [
+            "/usr/bin/uv",
+            "pip",
+            "install",
+            "--python",
+            str(runtime_python),
+            "--upgrade",
+            "--torch-backend=auto",
+            "vllm>=0.18,<1",
+        ],
+    ]
+    assert result.notes
+
+
+def test_install_runtime_dependencies_requires_uv(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setattr(install_module.shutil, "which", lambda _: None)
+
+    with pytest.raises(ConfigurationError, match="requires `uv` on PATH"):
+        install_module.install_runtime_dependencies(target="hf")
+
+
+def test_resolve_vllm_runtime_dir_prefers_explicit_path(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+) -> None:
+    monkeypatch.setenv(install_module.VLLM_RUNTIME_DIR_ENV, str(tmp_path / "from-env"))
+
+    resolved = install_module.resolve_vllm_runtime_dir(tmp_path / "from-arg")
+
+    assert resolved == (tmp_path / "from-arg").resolve()
+
+
+def test_resolve_vllm_runtime_dir_uses_environment_override(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+) -> None:
+    monkeypatch.setenv(install_module.VLLM_RUNTIME_DIR_ENV, str(tmp_path / "from-env"))
+
+    resolved = install_module.resolve_vllm_runtime_dir()
+
+    assert resolved == (tmp_path / "from-env").resolve()
+
+
+def test_serve_vllm_runtime_runs_module_from_dedicated_env(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+) -> None:
+    runtime_dir = tmp_path / "runtime"
+    runtime_python = runtime_dir / "bin" / "python"
+    runtime_python.parent.mkdir(parents=True, exist_ok=True)
+    runtime_python.write_text("")
+
+    commands: list[list[str]] = []
+    monkeypatch.setattr(
+        install_module.subprocess,
+        "run",
+        lambda command, check=False: commands.append(list(command)) or SimpleNamespace(returncode=0),
+    )
+
+    exit_code = install_module.serve_vllm_runtime(
+        model="stanford-oval/churro-3B",
+        host="0.0.0.0",
+        port=9000,
+        runtime_dir=runtime_dir,
+        extra_args=("--tensor-parallel-size", "2"),
+    )
+
+    assert exit_code == 0
+    assert commands == [
+        [
+            str(runtime_python),
+            "-m",
+            "vllm",
+            "serve",
+            "stanford-oval/churro-3B",
+            "--host",
+            "0.0.0.0",
+            "--port",
+            "9000",
+            "--tensor-parallel-size",
+            "2",
+        ]
+    ]
+
+
+def test_serve_vllm_runtime_requires_installed_runtime(tmp_path: Path) -> None:
+    with pytest.raises(ConfigurationError, match="install vllm"):
+        install_module.serve_vllm_runtime(
+            model="stanford-oval/churro-3B",
+            runtime_dir=tmp_path / "missing-runtime",
+        )
diff --git a/tests/test_internal_helpers.py b/tests/test_internal_helpers.py
index 7f33cfe..72a78de 100644
--- a/tests/test_internal_helpers.py
+++ b/tests/test_internal_helpers.py
@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import re
 import sys
 from base64 import b64encode
 from threading import Lock
@@ -351,20 +352,41 @@ def debug(self, message: str, *args: object) -> None:
 
 
 @pytest.mark.parametrize(
-    ("loader", "dependency_name"),
+    ("loader", "dependency_name", "message"),
     [
-        (_load_vllm_processor_cls, "transformers"),
-        (_load_vllm_runtime, "vllm"),
-        (_load_hf_runtime, "qwen_vl_utils"),
-        (_load_hf_causal_runtime, "qwen_vl_utils"),
+        (_load_vllm_processor_cls, "transformers", None),
+        (_load_vllm_runtime, "vllm", None),
+        (_load_hf_runtime, "torch", "PyTorch runtime"),
+        (_load_hf_runtime, "qwen_vl_utils", "install hf"),
+        (_load_hf_causal_runtime, "torch", "PyTorch runtime"),
+        (_load_hf_causal_runtime, "qwen_vl_utils", "install hf"),
     ],
 )
 def test_optional_dependency_loaders_raise_configuration_error(
     loader: Any,
     dependency_name: str,
+    message: str | None,
     patch_import_failure,
+    monkeypatch: pytest.MonkeyPatch,
 ) -> None:
-    patch_import_failure(failing_name=dependency_name)
-
-    with pytest.raises(ConfigurationError):
+    if dependency_name == "torch":
+
+        def _fake_import_module(name: str) -> object:
+            if name == "torch":
+                raise ImportError("missing torch")
+            return __import__(name)
+
+        monkeypatch.setattr("churro_ocr.providers.hf.import_module", _fake_import_module)
+    elif dependency_name == "qwen_vl_utils":
+        monkeypatch.setitem(sys.modules, "torch", ModuleType("torch"))
+        patch_import_failure(failing_name=dependency_name)
+    else:
+        patch_import_failure(failing_name=dependency_name)
+
+    if message is None:
+        with pytest.raises(ConfigurationError):
+            loader()
+        return
+
+    with pytest.raises(ConfigurationError, match=re.escape(message)):
         loader()

From b3d267bae9a4e0479e139f8710f987ad7d5926a4 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Sun, 5 Apr 2026 22:48:59 +0000
Subject: [PATCH 04/28] refactor(providers)!: remove in-process vllm backend

BREAKING CHANGE: The `vllm` OCR provider and `VLLMOptions` are removed. Use a served vLLM runtime through `provider="openai-compatible"` instead.
---
 src/churro_ocr/cli.py                |  17 +-
 src/churro_ocr/providers/__init__.py |   3 -
 src/churro_ocr/providers/builder.py  |  57 +-----
 src/churro_ocr/providers/specs.py    |  32 +--
 src/churro_ocr/providers/vllm.py     | 209 -------------------
 tests/test_cli.py                    |  75 +++++--
 tests/test_cli_contract.py           |  59 +++++-
 tests/test_internal_helpers.py       |  10 +-
 tests/test_provider_api_contracts.py |  15 +-
 tests/test_providers.py              | 290 ++++++++++++---------------
 tests/test_tooling_benchmark.py      | 158 ++++++---------
 tooling/benchmarking/benchmark.py    |  41 +---
 12 files changed, 320 insertions(+), 646 deletions(-)
 delete mode 100644 src/churro_ocr/providers/vllm.py

diff --git a/src/churro_ocr/cli.py b/src/churro_ocr/cli.py
index 5d2ff87..8c846b3 100644
--- a/src/churro_ocr/cli.py
+++ b/src/churro_ocr/cli.py
@@ -23,7 +23,6 @@
     MistralOptions,
     OCRBackendSpec,
     OpenAICompatibleOptions,
-    VLLMOptions,
     build_ocr_backend,
 )
 
@@ -56,10 +55,8 @@ def _build_ocr_backend(
             )
         )
     if backend == "openai-compatible":
-        if not model or not base_url or not api_key:
-            raise typer.BadParameter(
-                "--model, --base-url, and --api-key are required for backend=openai-compatible"
-            )
+        if not model or not base_url:
+            raise typer.BadParameter("--model and --base-url are required for backend=openai-compatible")
         return build_ocr_backend(
             OCRBackendSpec(
                 provider="openai-compatible",
@@ -105,16 +102,6 @@ def _build_ocr_backend(
                 options=HuggingFaceOptions(model_kwargs={"device_map": "auto", "torch_dtype": "auto"}),
             )
         )
-    if backend == "vllm":
-        if not model:
-            raise typer.BadParameter("--model is required for backend=vllm")
-        return build_ocr_backend(
-            OCRBackendSpec(
-                provider="vllm",
-                model=model,
-                options=VLLMOptions(),
-            )
-        )
     raise typer.BadParameter(f"Unsupported backend: {backend}")
 
 
diff --git a/src/churro_ocr/providers/__init__.py b/src/churro_ocr/providers/__init__.py
index ecab2bd..0a96528 100644
--- a/src/churro_ocr/providers/__init__.py
+++ b/src/churro_ocr/providers/__init__.py
@@ -24,7 +24,6 @@
         OCRBackendSpec,
         OCRModelProfile,
         OpenAICompatibleOptions,
-        VLLMOptions,
         resolve_ocr_profile,
     )
 
@@ -53,7 +52,6 @@
     "OCRModelProfile": ("churro_ocr.providers.specs", "OCRModelProfile"),
     "OpenAICompatibleOptions": ("churro_ocr.providers.specs", "OpenAICompatibleOptions"),
     "resolve_ocr_profile": ("churro_ocr.providers.specs", "resolve_ocr_profile"),
-    "VLLMOptions": ("churro_ocr.providers.specs", "VLLMOptions"),
 }
 
 __all__ = [
@@ -72,7 +70,6 @@
     "OCRModelProfile",
     "OpenAICompatibleOptions",
     "resolve_ocr_profile",
-    "VLLMOptions",
 ]
 
 
diff --git a/src/churro_ocr/providers/builder.py b/src/churro_ocr/providers/builder.py
index 7f7550b..bc27461 100644
--- a/src/churro_ocr/providers/builder.py
+++ b/src/churro_ocr/providers/builder.py
@@ -24,10 +24,8 @@
     OCRBackendSpec,
     OCRModelProfile,
     OpenAICompatibleOptions,
-    VLLMOptions,
     resolve_ocr_profile,
 )
-from churro_ocr.providers.vllm import VLLMVisionOCRBackend
 
 
 def _merge_mapping(
@@ -92,32 +90,6 @@ def _merge_huggingface_options(
     )
 
 
-def _merge_vllm_options(
-    base: VLLMOptions,
-    override: VLLMOptions | None,
-) -> VLLMOptions:
-    if override is None:
-        return VLLMOptions(
-            trust_remote_code=base.trust_remote_code,
-            processor_kwargs=dict(base.processor_kwargs),
-            llm_kwargs=dict(base.llm_kwargs),
-            sampling_kwargs=dict(base.sampling_kwargs),
-            limit_mm_per_prompt=dict(base.limit_mm_per_prompt),
-        )
-    return VLLMOptions(
-        trust_remote_code=(
-            override.trust_remote_code if override.trust_remote_code is not None else base.trust_remote_code
-        ),
-        processor_kwargs=_merge_mapping(base.processor_kwargs, override.processor_kwargs),
-        llm_kwargs=_merge_mapping(base.llm_kwargs, override.llm_kwargs),
-        sampling_kwargs=_merge_mapping(base.sampling_kwargs, override.sampling_kwargs),
-        limit_mm_per_prompt={
-            **base.limit_mm_per_prompt,
-            **override.limit_mm_per_prompt,
-        },
-    )
-
-
 def _merge_openai_options(
     override: OpenAICompatibleOptions | None,
 ) -> OpenAICompatibleOptions:
@@ -166,10 +138,8 @@ def _build_openai_compatible_backend(spec: OCRBackendSpec, profile: OCRModelProf
         _ensure_options_type(spec.options, OpenAICompatibleOptions, provider=spec.provider)
     )
     transport_config = _merge_transport_config(profile.transport, spec.transport)
-    if not transport_config.api_base or not transport_config.api_key:
-        raise ConfigurationError(
-            "OCR provider 'openai-compatible' requires `transport.api_base` and `transport.api_key`."
-        )
+    if not transport_config.api_base:
+        raise ConfigurationError("OCR provider 'openai-compatible' requires `transport.api_base`.")
     return OpenAICompatibleOCRBackend(
         model=spec.model,
         model_prefix=options.model_prefix or "openai",
@@ -207,27 +177,6 @@ def _build_huggingface_backend(spec: OCRBackendSpec, profile: OCRModelProfile) -
     )
 
 
-def _build_vllm_backend(spec: OCRBackendSpec, profile: OCRModelProfile) -> OCRBackend:
-    if spec.model is None:
-        raise ConfigurationError("OCR provider 'vllm' requires `model`.")
-    options = _merge_vllm_options(
-        profile.vllm,
-        _ensure_options_type(spec.options, VLLMOptions, provider=spec.provider),
-    )
-    return VLLMVisionOCRBackend(
-        model_id=spec.model,
-        template=profile.template,
-        model_name=_resolve_model_name(profile, spec.model, fallback=spec.model),
-        trust_remote_code=bool(options.trust_remote_code),
-        processor_kwargs=dict(options.processor_kwargs),
-        llm_kwargs=dict(options.llm_kwargs),
-        sampling_kwargs=dict(options.sampling_kwargs),
-        limit_mm_per_prompt=dict(options.limit_mm_per_prompt) or {"image": 1},
-        image_preprocessor=profile.image_preprocessor,
-        text_postprocessor=profile.text_postprocessor,
-    )
-
-
 def _build_azure_backend(spec: OCRBackendSpec, profile: OCRModelProfile) -> OCRBackend:
     options = _ensure_options_type(spec.options, AzureDocumentIntelligenceOptions, provider=spec.provider)
     if options is None or not options.endpoint or not options.api_key:
@@ -275,8 +224,6 @@ def build_ocr_backend(spec: OCRBackendSpec) -> OCRBackend:
         return _build_openai_compatible_backend(spec, profile)
     if spec.provider == "hf":
         return _build_huggingface_backend(spec, profile)
-    if spec.provider == "vllm":
-        return _build_vllm_backend(spec, profile)
     if spec.provider == "azure":
         return _build_azure_backend(spec, profile)
     if spec.provider == "mistral":
diff --git a/src/churro_ocr/providers/specs.py b/src/churro_ocr/providers/specs.py
index 58a08ae..b366617 100644
--- a/src/churro_ocr/providers/specs.py
+++ b/src/churro_ocr/providers/specs.py
@@ -32,7 +32,7 @@
     pass
 
 
-OCRProvider = Literal["litellm", "openai-compatible", "azure", "mistral", "hf", "vllm"]
+OCRProvider = Literal["litellm", "openai-compatible", "azure", "mistral", "hf"]
 ImagePreprocessor = Callable[[Image.Image], Image.Image]
 TextPostprocessorResult = str | tuple[str, dict[str, Any]]
 TextPostprocessor = Callable[[str], TextPostprocessorResult]
@@ -135,24 +135,6 @@ class HuggingFaceOptions:
     backend_variant: str | None = None
 
 
-@dataclass(slots=True, frozen=True)
-class VLLMOptions:
-    """Provider options for local vLLM OCR backends.
-
-    :param trust_remote_code: Whether to allow remote model code execution.
-    :param processor_kwargs: Extra kwargs passed to ``AutoProcessor.from_pretrained``.
-    :param llm_kwargs: Extra kwargs passed to the vLLM ``LLM`` constructor.
-    :param sampling_kwargs: Extra kwargs passed to vLLM sampling params.
-    :param limit_mm_per_prompt: Per-request multimodal limits passed to vLLM.
-    """
-
-    trust_remote_code: bool | None = None
-    processor_kwargs: dict[str, object] = field(default_factory=dict)
-    llm_kwargs: dict[str, object] = field(default_factory=dict)
-    sampling_kwargs: dict[str, object] = field(default_factory=dict)
-    limit_mm_per_prompt: dict[str, int] = field(default_factory=dict)
-
-
 @dataclass(slots=True, frozen=True)
 class AzureDocumentIntelligenceOptions:
     """Provider options for Azure Document Intelligence OCR.
@@ -176,11 +158,7 @@ class MistralOptions:
 
 
 OCRProviderOptions = (
-    OpenAICompatibleOptions
-    | HuggingFaceOptions
-    | VLLMOptions
-    | AzureDocumentIntelligenceOptions
-    | MistralOptions
+    OpenAICompatibleOptions | HuggingFaceOptions | AzureDocumentIntelligenceOptions | MistralOptions
 )
 
 
@@ -195,7 +173,6 @@ class OCRModelProfile:
     :param display_name: Optional human-readable model name.
     :param transport: Default LiteLLM transport settings for this profile.
     :param huggingface: Default Hugging Face backend options for this profile.
-    :param vllm: Default vLLM backend options for this profile.
     """
 
     profile_name: str
@@ -205,7 +182,6 @@ class OCRModelProfile:
     display_name: str | None = None
     transport: LiteLLMTransportConfig = field(default_factory=LiteLLMTransportConfig)
     huggingface: HuggingFaceOptions = field(default_factory=HuggingFaceOptions)
-    vllm: VLLMOptions = field(default_factory=VLLMOptions)
 
 
 @dataclass(slots=True, frozen=True)
@@ -261,9 +237,6 @@ def dots_ocr_1_5_profile() -> OCRModelProfile:
             trust_remote_code=True,
             backend_variant="dots-ocr-1.5",
         ),
-        vllm=VLLMOptions(
-            trust_remote_code=True,
-        ),
     )
 
 
@@ -368,5 +341,4 @@ def resolve_ocr_profile(
     "resolve_ocr_profile",
     "TextPostprocessor",
     "VisionInputBuilder",
-    "VLLMOptions",
 ]
diff --git a/src/churro_ocr/providers/vllm.py b/src/churro_ocr/providers/vllm.py
deleted file mode 100644
index 1c05283..0000000
--- a/src/churro_ocr/providers/vllm.py
+++ /dev/null
@@ -1,209 +0,0 @@
-"""vLLM OCR backends."""
-
-from __future__ import annotations
-
-import asyncio
-import threading
-from dataclasses import dataclass, field
-from importlib import import_module
-from typing import Any, cast
-
-from churro_ocr._internal.prompt_logging import log_prompt_payload_once
-from churro_ocr.errors import ConfigurationError, ProviderError
-from churro_ocr.ocr import OCRBackend, OCRResult
-from churro_ocr.page_detection import DocumentPage
-from churro_ocr.providers._shared import build_ocr_result, preprocess_backend_page, render_ocr_prompt
-from churro_ocr.providers.specs import (
-    DEFAULT_OCR_MAX_TOKENS,
-    ImagePreprocessor,
-    TextPostprocessor,
-    default_ocr_image_preprocessor,
-    identity_text_postprocessor,
-)
-from churro_ocr.templates import (
-    DOTS_OCR_1_5_MODEL_ID,
-    DOTS_OCR_1_5_OCR_TEMPLATE,
-    OCRPromptTemplateLike,
-)
-
-
-def _load_vllm_processor_cls() -> Any:
-    try:
-        from transformers import AutoProcessor
-    except ImportError as exc:  # pragma: no cover - optional extra path
-        raise ConfigurationError(
-            'vLLM OCR requires transformers. Install with `pip install "churro-ocr[vllm]"`.'
-        ) from exc
-
-    return AutoProcessor
-
-
-def _load_vllm_runtime() -> tuple[Any, Any]:
-    try:
-        vllm = import_module("vllm")
-    except ImportError as exc:  # pragma: no cover - optional extra path
-        raise ConfigurationError(
-            'vLLM OCR requires the "vllm" extra. Install with `pip install "churro-ocr[vllm]"`.'
-        ) from exc
-
-    vllm_any = cast(Any, vllm)
-    return vllm_any.LLM, vllm_any.SamplingParams
-
-
-@dataclass(slots=True)
-class VLLMVisionOCRBackend(OCRBackend):
-    """OCR backend for local multimodal models served by vLLM.
-
-    :param model_id: Model identifier served by vLLM.
-    :param template: Prompt template used to render OCR input.
-    :param model_name: Optional human-readable model name for result metadata.
-    :param trust_remote_code: Whether to allow remote model code execution.
-    :param processor_kwargs: Extra kwargs passed to processor loading.
-    :param llm_kwargs: Extra kwargs passed to the vLLM ``LLM`` constructor.
-    :param sampling_kwargs: Extra sampling kwargs passed at inference time.
-    :param limit_mm_per_prompt: Multimodal limits passed to vLLM.
-    :param image_preprocessor: Image preprocessor applied before OCR.
-    :param text_postprocessor: Text postprocessor applied after OCR.
-    :param provider_name: Provider identifier written into OCR results.
-    """
-
-    model_id: str
-    template: OCRPromptTemplateLike
-    model_name: str | None = None
-    trust_remote_code: bool = False
-    processor_kwargs: dict[str, object] = field(default_factory=dict)
-    llm_kwargs: dict[str, object] = field(default_factory=dict)
-    sampling_kwargs: dict[str, object] = field(default_factory=dict)
-    limit_mm_per_prompt: dict[str, int] = field(default_factory=lambda: {"image": 1})
-    image_preprocessor: ImagePreprocessor = default_ocr_image_preprocessor
-    text_postprocessor: TextPostprocessor = identity_text_postprocessor
-    provider_name: str = "vllm"
-    _processor: object | None = field(default=None, init=False, repr=False)
-    _llm: object | None = field(default=None, init=False, repr=False)
-    _init_lock: threading.RLock = field(default_factory=threading.RLock, init=False, repr=False)
-    _has_logged_prompt: bool = field(default=False, init=False, repr=False)
-    _prompt_log_lock: threading.Lock = field(default_factory=threading.Lock, init=False, repr=False)
-
-    def __post_init__(self) -> None:
-        """Apply default sampling settings after dataclass initialization."""
-        self.sampling_kwargs = {
-            "max_tokens": DEFAULT_OCR_MAX_TOKENS,
-            **self.sampling_kwargs,
-        }
-
-    async def ocr(self, page: DocumentPage) -> OCRResult:
-        """Run OCR for one page.
-
-        :param page: Page to transcribe.
-        :returns: Provider-agnostic OCR result.
-        """
-        return (await self.ocr_batch([page]))[0]
-
-    async def ocr_batch(self, pages: list[DocumentPage]) -> list[OCRResult]:
-        """Run OCR for multiple pages in one batch.
-
-        :param pages: Pages to transcribe in batch order.
-        :returns: OCR results in the same order as ``pages``.
-        """
-        return await asyncio.to_thread(self._ocr_batch_sync, pages)
-
-    def _ocr_batch_sync(self, pages: list[DocumentPage]) -> list[OCRResult]:
-        if not pages:
-            return []
-
-        processor = self._get_processor()
-        llm = self._get_llm()
-        _, sampling_params_cls = _load_vllm_runtime()
-        prompts: list[dict[str, object]] = []
-
-        for page in pages:
-            prepared_page = preprocess_backend_page(
-                page,
-                image_preprocessor=self.image_preprocessor,
-            )
-            rendered, _ = render_ocr_prompt(
-                processor,
-                self.template,
-                prepared_page,
-                add_generation_prompt=True,
-            )
-            prompt_payload: dict[str, object] = {
-                "prompt": rendered,
-                "multi_modal_data": {"image": prepared_page.image},
-            }
-            prompts.append(prompt_payload)
-            if not self._has_logged_prompt:
-                log_prompt_payload_once(
-                    payload={
-                        "batch_size": len(pages),
-                        "prompt": prompt_payload,
-                    },
-                    provider_name=self.provider_name,
-                    has_logged=lambda: self._has_logged_prompt,
-                    lock=self._prompt_log_lock,
-                    set_logged=lambda: setattr(self, "_has_logged_prompt", True),
-                )
-
-        request_outputs = llm.generate(
-            prompts,
-            sampling_params_cls(**self.sampling_kwargs),
-            use_tqdm=False,
-        )
-        results: list[OCRResult] = []
-        for request_output in request_outputs:
-            outputs = getattr(request_output, "outputs", None)
-            if not outputs:
-                raise ProviderError("vLLM OCR returned no outputs.")
-            text = getattr(outputs[0], "text", None)
-            if not isinstance(text, str):
-                raise ProviderError("vLLM OCR returned a non-text response.")
-            results.append(
-                build_ocr_result(
-                    text,
-                    provider_name=self.provider_name,
-                    model_name=self.model_name or self.model_id,
-                    text_postprocessor=self.text_postprocessor,
-                )
-            )
-        return results
-
-    def _get_processor(self) -> Any:
-        if self._processor is None:
-            with self._init_lock:
-                if self._processor is None:
-                    processor_cls = _load_vllm_processor_cls()
-                    self._processor = processor_cls.from_pretrained(
-                        self.model_id,
-                        trust_remote_code=self.trust_remote_code,
-                        **self.processor_kwargs,
-                    )
-        return self._processor
-
-    def _get_llm(self) -> Any:
-        if self._llm is None:
-            with self._init_lock:
-                if self._llm is None:
-                    llm_cls, _ = _load_vllm_runtime()
-                    self._llm = llm_cls(
-                        model=self.model_id,
-                        trust_remote_code=self.trust_remote_code,
-                        limit_mm_per_prompt=self.limit_mm_per_prompt,
-                        **self.llm_kwargs,
-                    )
-        return self._llm
-
-
-@dataclass(slots=True)
-class DotsOCR15VLLMOCRBackend(VLLMVisionOCRBackend):
-    """Preset vLLM OCR backend for ``kristaller486/dots.ocr-1.5``."""
-
-    model_id: str = DOTS_OCR_1_5_MODEL_ID
-    template: OCRPromptTemplateLike = DOTS_OCR_1_5_OCR_TEMPLATE
-    model_name: str | None = "dots.ocr-1.5"
-    trust_remote_code: bool = True
-
-
-__all__ = [
-    "DotsOCR15VLLMOCRBackend",
-    "VLLMVisionOCRBackend",
-]
diff --git a/tests/test_cli.py b/tests/test_cli.py
index 684071a..0df4647 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -15,7 +15,12 @@
 from churro_ocr.ocr import OCRResult
 from churro_ocr.page_detection import DocumentPage, PageDetectionResult
 from churro_ocr.prompts import DEFAULT_OCR_OUTPUT_TAG
-from churro_ocr.templates import DEFAULT_OCR_TEMPLATE, DOTS_OCR_1_5_OCR_TEMPLATE
+from churro_ocr.templates import (
+    DEFAULT_OCR_TEMPLATE,
+    DOTS_OCR_1_5_OCR_TEMPLATE,
+    OLMOCR_2_7B_1025_MODEL_ID,
+    OLMOCR_2_7B_1025_OCR_TEMPLATE,
+)
 
 
 def test_transcribe_cli_writes_output(
@@ -113,20 +118,20 @@ def test_build_ocr_backend_aligns_templates_for_generic_models() -> None:
         base_url=None,
         api_version=None,
     )
-    vllm_backend = cli_module._build_ocr_backend(
-        backend="vllm",
+    openai_backend = cli_module._build_ocr_backend(
+        backend="openai-compatible",
         model="example/model",
         endpoint=None,
         api_key=None,
-        base_url=None,
+        base_url="http://127.0.0.1:8000/v1",
         api_version=None,
     )
 
     assert litellm_backend.template == DEFAULT_OCR_TEMPLATE
-    assert litellm_backend.template == hf_backend.template == vllm_backend.template
+    assert litellm_backend.template == hf_backend.template == openai_backend.template
     assert litellm_backend.model_name == "example/model"
     assert hf_backend.model_name == "example/model"
-    assert vllm_backend.model_name == "example/model"
+    assert openai_backend.model_name == "example/model"
     assert f"<{DEFAULT_OCR_OUTPUT_TAG}>" in litellm_backend.template.system_message
     assert f"</{DEFAULT_OCR_OUTPUT_TAG}>" in litellm_backend.template.system_message
     assert f"<{DEFAULT_OCR_OUTPUT_TAG}>" in litellm_backend.template.user_prompt
@@ -150,20 +155,20 @@ def test_build_ocr_backend_aligns_templates_for_dots() -> None:
         base_url=None,
         api_version=None,
     )
-    vllm_backend = cli_module._build_ocr_backend(
-        backend="vllm",
+    openai_backend = cli_module._build_ocr_backend(
+        backend="openai-compatible",
         model="kristaller486/dots.ocr-1.5",
         endpoint=None,
         api_key=None,
-        base_url=None,
+        base_url="http://127.0.0.1:8000/v1",
         api_version=None,
     )
 
     assert litellm_backend.template == DOTS_OCR_1_5_OCR_TEMPLATE
-    assert litellm_backend.template == hf_backend.template == vllm_backend.template
+    assert litellm_backend.template == hf_backend.template == openai_backend.template
     assert litellm_backend.model_name == "dots.ocr-1.5"
     assert hf_backend.model_name == "dots.ocr-1.5"
-    assert vllm_backend.model_name == "dots.ocr-1.5"
+    assert openai_backend.model_name == "dots.ocr-1.5"
 
 
 def test_build_ocr_backend_uses_generic_defaults_for_qwen_3_5_0_8b() -> None:
@@ -183,21 +188,57 @@ def test_build_ocr_backend_uses_generic_defaults_for_qwen_3_5_0_8b() -> None:
         base_url=None,
         api_version=None,
     )
-    vllm_backend = cli_module._build_ocr_backend(
-        backend="vllm",
+    openai_backend = cli_module._build_ocr_backend(
+        backend="openai-compatible",
         model="Qwen/Qwen3.5-0.8B",
         endpoint=None,
         api_key=None,
-        base_url=None,
+        base_url="http://127.0.0.1:8000/v1",
         api_version=None,
     )
 
     assert litellm_backend.template == DEFAULT_OCR_TEMPLATE
-    assert litellm_backend.template == hf_backend.template == vllm_backend.template
+    assert litellm_backend.template == hf_backend.template == openai_backend.template
     assert litellm_backend.model_name == "Qwen/Qwen3.5-0.8B"
     assert hf_backend.model_name == "Qwen/Qwen3.5-0.8B"
-    assert vllm_backend.model_name == "Qwen/Qwen3.5-0.8B"
-    assert vllm_backend.llm_kwargs == {}
+    assert openai_backend.model_name == "Qwen/Qwen3.5-0.8B"
+
+
+def test_build_ocr_backend_aligns_templates_for_olmocr() -> None:
+    litellm_backend = cli_module._build_ocr_backend(
+        backend="litellm",
+        model=OLMOCR_2_7B_1025_MODEL_ID,
+        endpoint=None,
+        api_key=None,
+        base_url=None,
+        api_version=None,
+    )
+    hf_backend = cli_module._build_ocr_backend(
+        backend="hf",
+        model=OLMOCR_2_7B_1025_MODEL_ID,
+        endpoint=None,
+        api_key=None,
+        base_url=None,
+        api_version=None,
+    )
+    openai_backend = cli_module._build_ocr_backend(
+        backend="openai-compatible",
+        model=OLMOCR_2_7B_1025_MODEL_ID,
+        endpoint=None,
+        api_key=None,
+        base_url="http://127.0.0.1:8000/v1",
+        api_version=None,
+    )
+
+    assert litellm_backend.template == OLMOCR_2_7B_1025_OCR_TEMPLATE
+    assert litellm_backend.template == hf_backend.template == openai_backend.template
+    assert litellm_backend.model_name == "olmOCR-2-7B-1025"
+    assert hf_backend.model_name == "olmOCR-2-7B-1025"
+    assert openai_backend.model_name == "olmOCR-2-7B-1025"
+    assert openai_backend.transport.config.completion_kwargs == {
+        "max_tokens": 8_000,
+        "temperature": 0.1,
+    }
 
 
 def test_install_command_invokes_runtime_installer(
diff --git a/tests/test_cli_contract.py b/tests/test_cli_contract.py
index 0bffed9..f932706 100644
--- a/tests/test_cli_contract.py
+++ b/tests/test_cli_contract.py
@@ -23,12 +23,11 @@ def sample_image_path(write_image_file) -> Path:
         (["--backend", "litellm"], ("--model is required for backend=litellm",)),
         (
             ["--backend", "openai-compatible", "--model", "local-model"],
-            ("required for", "backend=openai-compatible"),
+            ("--model and --base-url are required for", "backend=openai-compatible"),
         ),
         (["--backend", "azure"], ("--endpoint and --api-key are required for backend=azure",)),
         (["--backend", "mistral"], ("--api-key is required for backend=mistral",)),
         (["--backend", "hf"], ("--model is required for backend=hf",)),
-        (["--backend", "vllm"], ("--model is required for backend=vllm",)),
     ],
 )
 def test_transcribe_cli_validates_backend_requirements(
@@ -48,7 +47,57 @@ def test_transcribe_cli_validates_backend_requirements(
         assert expected_part in output
 
 
-def test_transcribe_cli_rejects_unsupported_backend(sample_image_path: Path, cli_runner) -> None:
+def test_transcribe_cli_allows_openai_compatible_backend_without_api_key(
+    monkeypatch: pytest.MonkeyPatch,
+    sample_image_path: Path,
+    cli_runner,
+) -> None:
+    captured: dict[str, object] = {}
+
+    class _FakeBackend:
+        async def ocr(self, page: DocumentPage) -> OCRResult:
+            captured["size"] = (page.image.width, page.image.height)
+            return OCRResult(text="ok", provider_name="fake", model_name="fake-model")
+
+    def _fake_build_ocr_backend(spec: cli_module.OCRBackendSpec) -> _FakeBackend:
+        captured["spec"] = spec
+        return _FakeBackend()
+
+    monkeypatch.setattr(
+        "churro_ocr.cli.build_ocr_backend",
+        _fake_build_ocr_backend,
+    )
+
+    result = cli_runner.invoke(
+        app,
+        [
+            "transcribe",
+            "--image",
+            str(sample_image_path),
+            "--backend",
+            "openai-compatible",
+            "--model",
+            "local-model",
+            "--base-url",
+            "http://127.0.0.1:8000/v1",
+        ],
+    )
+
+    assert result.exit_code == 0
+    assert result.output.strip() == "ok"
+    spec = captured["spec"]
+    assert isinstance(spec, cli_module.OCRBackendSpec)
+    assert spec.transport is not None
+    assert spec.transport.api_base == "http://127.0.0.1:8000/v1"
+    assert spec.transport.api_key is None
+
+
+@pytest.mark.parametrize("backend", ["unsupported", "vllm"])
+def test_transcribe_cli_rejects_unsupported_backend(
+    sample_image_path: Path,
+    backend: str,
+    cli_runner,
+) -> None:
     result = cli_runner.invoke(
         app,
         [
@@ -56,14 +105,14 @@ def test_transcribe_cli_rejects_unsupported_backend(sample_image_path: Path, cli
             "--image",
             str(sample_image_path),
             "--backend",
-            "unsupported",
+            backend,
             "--model",
             "example/model",
         ],
     )
 
     assert result.exit_code != 0
-    assert "Unsupported backend: unsupported" in result.output
+    assert f"Unsupported backend: {backend}" in result.output
 
 
 def test_transcribe_cli_echoes_text_without_output(
diff --git a/tests/test_internal_helpers.py b/tests/test_internal_helpers.py
index 72a78de..e37af3e 100644
--- a/tests/test_internal_helpers.py
+++ b/tests/test_internal_helpers.py
@@ -18,7 +18,6 @@
 from churro_ocr.errors import ConfigurationError, ProviderError
 from churro_ocr.providers.hf import _load_hf_causal_runtime, _load_hf_runtime
 from churro_ocr.providers.specs import LiteLLMTransportConfig
-from churro_ocr.providers.vllm import _load_vllm_processor_cls, _load_vllm_runtime
 
 
 def _make_fake_litellm_module(*, acompletion: object, completion_cost: object | None = None) -> ModuleType:
@@ -354,8 +353,6 @@ def debug(self, message: str, *args: object) -> None:
 @pytest.mark.parametrize(
     ("loader", "dependency_name", "message"),
     [
-        (_load_vllm_processor_cls, "transformers", None),
-        (_load_vllm_runtime, "vllm", None),
         (_load_hf_runtime, "torch", "PyTorch runtime"),
         (_load_hf_runtime, "qwen_vl_utils", "install hf"),
         (_load_hf_causal_runtime, "torch", "PyTorch runtime"),
@@ -365,7 +362,7 @@ def debug(self, message: str, *args: object) -> None:
 def test_optional_dependency_loaders_raise_configuration_error(
     loader: Any,
     dependency_name: str,
-    message: str | None,
+    message: str,
     patch_import_failure,
     monkeypatch: pytest.MonkeyPatch,
 ) -> None:
@@ -383,10 +380,5 @@ def _fake_import_module(name: str) -> object:
     else:
         patch_import_failure(failing_name=dependency_name)
 
-    if message is None:
-        with pytest.raises(ConfigurationError):
-            loader()
-        return
-
     with pytest.raises(ConfigurationError, match=re.escape(message)):
         loader()
diff --git a/tests/test_provider_api_contracts.py b/tests/test_provider_api_contracts.py
index bde918f..d44f021 100644
--- a/tests/test_provider_api_contracts.py
+++ b/tests/test_provider_api_contracts.py
@@ -14,7 +14,6 @@
     MistralOptions,
     OCRBackendSpec,
     OpenAICompatibleOptions,
-    VLLMOptions,
     build_ocr_backend,
     resolve_ocr_profile,
 )
@@ -59,7 +58,7 @@ def test_provider_dir_lists_lazy_exports() -> None:
         (OCRBackendSpec(provider="litellm"), "OCR provider 'litellm' requires `model`."),
         (
             OCRBackendSpec(provider="openai-compatible", model="local-model"),
-            "OCR provider 'openai-compatible' requires `transport.api_base` and `transport.api_key`.",
+            "OCR provider 'openai-compatible' requires `transport.api_base`.",
         ),
         (
             OCRBackendSpec(provider="azure"),
@@ -73,17 +72,20 @@ def test_provider_dir_lists_lazy_exports() -> None:
             OCRBackendSpec(
                 provider="hf",
                 model="example/model",
-                options=cast("Any", VLLMOptions()),
+                options=cast("Any", OpenAICompatibleOptions()),
             ),
-            "OCR provider 'hf' requires options of type HuggingFaceOptions, got VLLMOptions.",
+            "OCR provider 'hf' requires options of type HuggingFaceOptions, got OpenAICompatibleOptions.",
         ),
         (
             OCRBackendSpec(
-                provider="vllm",
+                provider="openai-compatible",
                 model="example/model",
                 options=cast("Any", HuggingFaceOptions()),
             ),
-            "OCR provider 'vllm' requires options of type VLLMOptions, got HuggingFaceOptions.",
+            (
+                "OCR provider 'openai-compatible' requires options of type "
+                "OpenAICompatibleOptions, got HuggingFaceOptions."
+            ),
         ),
     ],
 )
@@ -99,7 +101,6 @@ def test_build_ocr_backend_supports_custom_openai_model_prefix() -> None:
             model="local-model",
             transport=LiteLLMTransportConfig(
                 api_base="http://127.0.0.1:8000/v1",
-                api_key="dummy",
             ),
             options=OpenAICompatibleOptions(model_prefix="custom"),
         )
diff --git a/tests/test_providers.py b/tests/test_providers.py
index 065d08b..1c70467 100644
--- a/tests/test_providers.py
+++ b/tests/test_providers.py
@@ -12,7 +12,11 @@
 from churro_ocr._internal.litellm import LiteLLMTransport
 from churro_ocr.errors import ProviderError
 from churro_ocr.page_detection import DocumentPage
-from churro_ocr.prompts import DEFAULT_BOUNDARY_DETECTION_PROMPT, DEFAULT_OCR_OUTPUT_TAG
+from churro_ocr.prompts import (
+    DEFAULT_BOUNDARY_DETECTION_PROMPT,
+    DEFAULT_OCR_OUTPUT_TAG,
+    OLMOCR_V4_YAML_PROMPT,
+)
 from churro_ocr.providers import (
     AzureDocumentIntelligenceOptions,
     AzurePageDetector,
@@ -22,7 +26,6 @@
     MistralOptions,
     OCRBackendSpec,
     OpenAICompatibleOptions,
-    VLLMOptions,
     build_ocr_backend,
     locate_text_block_bbox_with_llm,
     resolve_ocr_profile,
@@ -32,6 +35,7 @@
     AzureDocumentIntelligenceOCRBackend,
     LiteLLMVisionOCRBackend,
     MistralOCRBackend,
+    OpenAICompatibleOCRBackend,
 )
 from churro_ocr.providers.page_detection import (
     _normalize_azure_page_polygon,
@@ -39,8 +43,12 @@
     locate_text_block_bbox_with_llm_sync,
 )
 from churro_ocr.providers.specs import DEFAULT_OCR_MAX_TOKENS
-from churro_ocr.providers.vllm import VLLMVisionOCRBackend
-from churro_ocr.templates import DEFAULT_OCR_TEMPLATE
+from churro_ocr.templates import (
+    DEFAULT_OCR_TEMPLATE,
+    OLMOCR_2_7B_1025_FP8_MODEL_ID,
+    OLMOCR_2_7B_1025_MODEL_ID,
+    OLMOCR_2_7B_1025_OCR_TEMPLATE,
+)
 
 
 def _extract_user_text_parts(messages: list[dict[str, Any]]) -> list[str]:
@@ -348,183 +356,142 @@ def __init__(self, *, api_key: str) -> None:
     assert calls == {"client_inits": 1, "requests": 2}
 
 
-@pytest.mark.asyncio
-async def test_vllm_ocr_backend_reuses_engine_and_batches(monkeypatch: pytest.MonkeyPatch) -> None:
-    calls = {"processor_inits": 0, "engine_inits": 0}
-    captured: dict[str, object] = {}
-
-    class FakeProcessor:
-        tokenizer = None
-
-        def apply_chat_template(
-            self,
-            conversation: list[dict[str, object]],
-            *,
-            add_generation_prompt: bool,
-            tokenize: bool,
-        ) -> str:
-            assert add_generation_prompt is True
-            assert tokenize is False
-            content = cast("list[dict[str, object]]", conversation[0]["content"])
-            return f"prompt:{content[1]['text']}"
-
-    class FakeProcessorCls:
-        @staticmethod
-        def from_pretrained(model_id: str, **kwargs: object) -> FakeProcessor:
-            calls["processor_inits"] += 1
-            captured["processor_model_id"] = model_id
-            captured["processor_kwargs"] = kwargs
-            return FakeProcessor()
-
-    class FakeSamplingParams:
-        def __init__(self, **kwargs: object) -> None:
-            captured["sampling_kwargs"] = kwargs
-
-    class FakeLLM:
-        def __init__(self, **kwargs: object) -> None:
-            calls["engine_inits"] += 1
-            captured["llm_kwargs"] = kwargs
-
-        def generate(
-            self,
-            prompts: list[dict[str, object]],
-            sampling_params: FakeSamplingParams,
-            *,
-            use_tqdm: bool,
-        ) -> list[SimpleNamespace]:
-            del sampling_params
-            captured["prompts"] = prompts
-            captured["use_tqdm"] = use_tqdm
-            return [
-                SimpleNamespace(outputs=[SimpleNamespace(text=f"text:{index}")])
-                for index, _prompt in enumerate(prompts)
-            ]
-
-    vllm_module = ModuleType("vllm")
-    cast("Any", vllm_module).LLM = FakeLLM
-    cast("Any", vllm_module).SamplingParams = FakeSamplingParams
-    monkeypatch.setitem(sys.modules, "vllm", vllm_module)
-    monkeypatch.setattr("churro_ocr.providers.vllm._load_vllm_processor_cls", lambda: FakeProcessorCls)
-
+def test_build_ocr_backend_uses_olmocr_profile_defaults_for_openai_compatible() -> None:
     backend = cast(
-        "VLLMVisionOCRBackend",
+        "OpenAICompatibleOCRBackend",
         build_ocr_backend(
             OCRBackendSpec(
-                provider="vllm",
-                model="kristaller486/dots.ocr-1.5",
-                options=VLLMOptions(),
+                provider="openai-compatible",
+                model=OLMOCR_2_7B_1025_MODEL_ID,
+                transport=LiteLLMTransportConfig(api_base="http://127.0.0.1:8000/v1"),
             )
         ),
     )
-    pages = [
-        DocumentPage.from_image(Image.new("RGBA", (5_000, 3_000), color=(255, 255, 255, 255))),
-        DocumentPage.from_image(Image.new("RGB", (12, 12), color="white")),
-    ]
 
-    first = await backend.ocr(pages[0])
-    second_batch = await backend.ocr_batch(pages)
-
-    assert first.text == "text:0"
-    assert [result.text for result in second_batch] == ["text:0", "text:1"]
-    assert calls == {"processor_inits": 1, "engine_inits": 1}
-    assert captured["processor_model_id"] == "kristaller486/dots.ocr-1.5"
-    assert captured["processor_kwargs"] == {"trust_remote_code": True}
-    assert captured["llm_kwargs"] == {
-        "model": "kristaller486/dots.ocr-1.5",
-        "trust_remote_code": True,
-        "limit_mm_per_prompt": {"image": 1},
+    assert backend.template == OLMOCR_2_7B_1025_OCR_TEMPLATE
+    assert backend.model_name == "olmOCR-2-7B-1025"
+    assert backend.transport.config.completion_kwargs == {
+        "max_tokens": 8_000,
+        "temperature": 0.1,
     }
-    assert captured["sampling_kwargs"] == {"max_tokens": DEFAULT_OCR_MAX_TOKENS}
-    assert captured["use_tqdm"] is False
-    prompt_batch = cast("list[dict[str, object]]", captured["prompts"])
-    assert isinstance(prompt_batch, list)
-    assert len(prompt_batch) == 2
-    assert prompt_batch[0]["prompt"] == "prompt:Extract the text content from this image."
-    prompt_media = cast("dict[str, object]", prompt_batch[0]["multi_modal_data"])
-    prompt_image = cast("Image.Image", prompt_media["image"])
-    assert isinstance(prompt_image, Image.Image)
-    assert prompt_image.size == (2_500, 1_500)
-    assert prompt_image.mode == "RGB"
+    assert backend.image_preprocessor(Image.new("RGB", (5_000, 3_000), color="white")).size == (1_288, 772)
 
 
-def test_vllm_backend_defaults_are_public() -> None:
+def test_build_ocr_backend_resolves_olmocr_fp8_profile_defaults_for_openai_compatible() -> None:
     backend = cast(
-        "VLLMVisionOCRBackend",
+        "OpenAICompatibleOCRBackend",
         build_ocr_backend(
             OCRBackendSpec(
-                provider="vllm",
-                model="kristaller486/dots.ocr-1.5",
-                options=VLLMOptions(),
+                provider="openai-compatible",
+                model=OLMOCR_2_7B_1025_FP8_MODEL_ID,
+                transport=LiteLLMTransportConfig(api_base="http://127.0.0.1:8000/v1"),
             )
         ),
     )
 
-    assert backend.model_id == "kristaller486/dots.ocr-1.5"
-    assert backend.model_name == "dots.ocr-1.5"
-    assert backend.provider_name == "vllm"
-    assert backend.processor_kwargs == {}
+    assert backend.template == OLMOCR_2_7B_1025_OCR_TEMPLATE
+    assert backend.model_name == "olmOCR-2-7B-1025-FP8"
+    assert backend.transport.config.completion_kwargs == {
+        "max_tokens": 8_000,
+        "temperature": 0.1,
+    }
 
 
 @pytest.mark.asyncio
-async def test_vllm_ocr_backend_strips_default_output_tags(monkeypatch: pytest.MonkeyPatch) -> None:
-    class FakeProcessor:
-        tokenizer = None
+async def test_openai_compatible_backend_uses_olmocr_prompt_and_plain_text_postprocessing(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    captured: dict[str, object] = {}
 
-        def apply_chat_template(
-            self,
-            conversation: list[dict[str, object]],
-            *,
-            add_generation_prompt: bool,
-            tokenize: bool,
-        ) -> str:
-            del conversation, add_generation_prompt, tokenize
-            return "prompt"
-
-    class FakeProcessorCls:
-        @staticmethod
-        def from_pretrained(model_id: str, **kwargs: object) -> FakeProcessor:
-            del model_id, kwargs
-            return FakeProcessor()
-
-    class FakeSamplingParams:
-        def __init__(self, **kwargs: object) -> None:
-            del kwargs
-
-    class FakeLLM:
-        def __init__(self, **kwargs: object) -> None:
-            del kwargs
-
-        def generate(
-            self,
-            prompts: list[dict[str, object]],
-            sampling_params: FakeSamplingParams,
-            *,
-            use_tqdm: bool,
-        ) -> list[SimpleNamespace]:
-            del prompts, sampling_params, use_tqdm
-            return [
-                SimpleNamespace(
-                    outputs=[
-                        SimpleNamespace(
-                            text=(f"<{DEFAULT_OCR_OUTPUT_TAG}>\npage text\n</{DEFAULT_OCR_OUTPUT_TAG}>")
-                        )
-                    ]
-                )
-            ]
+    def _fake_prepare_messages_from_conversation(
+        self: LiteLLMTransport,
+        conversation: list[dict[str, object]],
+    ) -> list[dict[str, object]]:
+        captured["conversation"] = conversation
+        captured["completion_kwargs"] = dict(self.config.completion_kwargs)
+        return [{"role": "user", "content": [{"type": "text", "text": "prompt"}]}]
 
-    vllm_module = ModuleType("vllm")
-    cast("Any", vllm_module).LLM = FakeLLM
-    cast("Any", vllm_module).SamplingParams = FakeSamplingParams
-    monkeypatch.setitem(sys.modules, "vllm", vllm_module)
-    monkeypatch.setattr("churro_ocr.providers.vllm._load_vllm_processor_cls", lambda: FakeProcessorCls)
+    async def _fake_complete_text(
+        self: LiteLLMTransport,
+        *,
+        model: str,
+        messages: list[dict[str, object]],
+        timeout_seconds: int = 600,
+        output_json: bool = False,
+    ) -> str:
+        captured["model"] = model
+        captured["messages"] = messages
+        captured["timeout_seconds"] = timeout_seconds
+        captured["output_json"] = output_json
+        captured["completion_kwargs"] = dict(self.config.completion_kwargs)
+        return (
+            "---\n"
+            "primary_language: en\n"
+            "is_rotation_valid: true\n"
+            "rotation_correction: 0\n"
+            "is_table: true\n"
+            "is_diagram: false\n"
+            "---\n"
+            "# Ledger\n\n"
+            "<table><tr><th>Year</th><th>Value</th></tr>"
+            "<tr><td>1900</td><td>42</td></tr></table>\n\n"
+            "Paragraph with [note](https://example.test).\n"
+            "![Figure alt text](page_0_0_100_100.png)\n"
+        )
+
+    monkeypatch.setattr(
+        LiteLLMTransport,
+        "prepare_messages_from_conversation",
+        _fake_prepare_messages_from_conversation,
+    )
+    monkeypatch.setattr(LiteLLMTransport, "complete_text", _fake_complete_text)
 
     backend = cast(
-        "VLLMVisionOCRBackend",
-        build_ocr_backend(OCRBackendSpec(provider="vllm", model="example/model")),
+        "OpenAICompatibleOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="openai-compatible",
+                model=OLMOCR_2_7B_1025_MODEL_ID,
+                transport=LiteLLMTransportConfig(api_base="http://127.0.0.1:8000/v1"),
+            )
+        ),
+    )
+    result = await backend.ocr(
+        DocumentPage.from_image(Image.new("RGBA", (5_000, 3_000), color=(255, 255, 255, 255)))
     )
-    result = await backend.ocr(DocumentPage.from_image(Image.new("RGB", (10, 10), color="white")))
 
-    assert result.text == "page text"
+    assert result.text == "Ledger\n\nYear | Value\n1900 | 42\n\nParagraph with note."
+    assert result.metadata == {
+        "front_matter": {
+            "primary_language": "en",
+            "is_rotation_valid": True,
+            "rotation_correction": 0,
+            "is_table": True,
+            "is_diagram": False,
+        },
+        "raw_markdown": (
+            "# Ledger\n\n"
+            "<table><tr><th>Year</th><th>Value</th></tr><tr><td>1900</td><td>42</td></tr></table>\n\n"
+            "Paragraph with [note](https://example.test).\n"
+            "![Figure alt text](page_0_0_100_100.png)"
+        ),
+    }
+    assert captured["model"] == f"openai/{OLMOCR_2_7B_1025_MODEL_ID}"
+    assert captured["messages"] == [{"role": "user", "content": [{"type": "text", "text": "prompt"}]}]
+    assert captured["timeout_seconds"] == 600
+    assert captured["output_json"] is False
+    assert captured["completion_kwargs"] == {
+        "max_tokens": 8_000,
+        "temperature": 0.1,
+    }
+    conversation = cast("list[dict[str, object]]", captured["conversation"])
+    assert conversation[0]["role"] == "user"
+    user_content = cast("list[dict[str, object]]", conversation[0]["content"])
+    assert user_content[0] == {"type": "text", "text": OLMOCR_V4_YAML_PROMPT}
+    assert user_content[1]["type"] == "image"
+    prompt_image = cast("Image.Image", user_content[1]["image"])
+    assert prompt_image.size == (1_288, 772)
+    assert prompt_image.mode == "RGB"
 
 
 @pytest.mark.asyncio
@@ -1017,11 +984,12 @@ def test_azure_page_detector_type_is_public() -> None:
 
 def test_build_ocr_backend_resolves_profile_defaults() -> None:
     backend = cast(
-        "VLLMVisionOCRBackend",
+        "OpenAICompatibleOCRBackend",
         build_ocr_backend(
             OCRBackendSpec(
-                provider="vllm",
+                provider="openai-compatible",
                 model="stanford-oval/churro-3B",
+                transport=LiteLLMTransportConfig(api_base="http://127.0.0.1:8000/v1"),
             )
         ),
     )
@@ -1032,19 +1000,19 @@ def test_build_ocr_backend_resolves_profile_defaults() -> None:
 
 def test_build_ocr_backend_uses_generic_defaults_for_qwen_model() -> None:
     backend = cast(
-        "VLLMVisionOCRBackend",
+        "OpenAICompatibleOCRBackend",
         build_ocr_backend(
             OCRBackendSpec(
-                provider="vllm",
+                provider="openai-compatible",
                 model="Qwen/Qwen3.5-0.8B",
+                transport=LiteLLMTransportConfig(api_base="http://127.0.0.1:8000/v1"),
             )
         ),
     )
 
     assert backend.model_name == "Qwen/Qwen3.5-0.8B"
     assert backend.template == DEFAULT_OCR_TEMPLATE
-    assert backend.llm_kwargs == {}
-    assert backend.sampling_kwargs == {"max_tokens": DEFAULT_OCR_MAX_TOKENS}
+    assert backend.transport.config.completion_kwargs == {"max_tokens": DEFAULT_OCR_MAX_TOKENS}
 
 
 def test_build_ocr_backend_merges_hf_overrides_with_profile_defaults() -> None:
diff --git a/tests/test_tooling_benchmark.py b/tests/test_tooling_benchmark.py
index e672903..04f1825 100644
--- a/tests/test_tooling_benchmark.py
+++ b/tests/test_tooling_benchmark.py
@@ -11,8 +11,7 @@
 from churro_ocr.providers.hf import HuggingFaceVisionOCRBackend
 from churro_ocr.providers.ocr import LiteLLMVisionOCRBackend
 from churro_ocr.providers.specs import DEFAULT_OCR_MAX_TOKENS
-from churro_ocr.providers.vllm import VLLMVisionOCRBackend
-from churro_ocr.templates import CHURRO_3B_XML_TEMPLATE
+from churro_ocr.templates import CHURRO_3B_XML_TEMPLATE, DOTS_OCR_1_5_OCR_TEMPLATE
 from tooling.benchmarking import benchmark
 from tooling.evaluation.types import BenchmarkDatasetExample
 
@@ -104,23 +103,14 @@ def test_validate_options_requires_model_for_hf() -> None:
     assert benchmark._validate_options(options) == 1
 
 
-def test_validate_options_requires_model_for_vllm() -> None:
+def test_validate_options_allows_openai_compatible_without_api_key() -> None:
     options = benchmark.BenchmarkOptions(
-        backend="vllm",
-        model=None,
-        dataset_split="dev",
-    )
-    assert benchmark._validate_options(options) == 1
-
-
-def test_validate_options_rejects_invalid_vllm_gpu_memory_utilization() -> None:
-    options = benchmark.BenchmarkOptions(
-        backend="vllm",
-        model="Qwen/Qwen3.5-0.8B",
+        backend="openai-compatible",
         dataset_split="dev",
-        vllm_gpu_memory_utilization=1.5,
+        model="local-model",
+        base_url="http://127.0.0.1:8000/v1",
     )
-    assert benchmark._validate_options(options) == 1
+    assert benchmark._validate_options(options) == 0
 
 
 def test_validate_options_rejects_invalid_split() -> None:
@@ -155,24 +145,18 @@ def test_parse_args_accepts_subset_filters() -> None:
     assert options.document_type == "print"
 
 
-def test_parse_args_accepts_vllm_resource_overrides() -> None:
-    options = benchmark.parse_args(
-        [
-            "--backend",
-            "vllm",
-            "--dataset-split",
-            "dev",
-            "--model",
-            "Qwen/Qwen3.5-0.8B",
-            "--vllm-gpu-memory-utilization",
-            "0.25",
-            "--vllm-cpu-offload-gb",
-            "8",
-        ]
-    )
-
-    assert options.vllm_gpu_memory_utilization == pytest.approx(0.25)
-    assert options.vllm_cpu_offload_gb == pytest.approx(8.0)
+def test_parse_args_rejects_removed_vllm_backend() -> None:
+    with pytest.raises(SystemExit):
+        benchmark.parse_args(
+            [
+                "--backend",
+                "vllm",
+                "--dataset-split",
+                "dev",
+                "--model",
+                "Qwen/Qwen3.5-0.8B",
+            ]
+        )
 
 
 def test_build_ocr_backend_enables_disk_cache_for_litellm(
@@ -198,6 +182,24 @@ def test_build_ocr_backend_enables_disk_cache_for_litellm(
     assert backend.transport.config.completion_kwargs == {"max_tokens": DEFAULT_OCR_MAX_TOKENS}
 
 
+def test_build_ocr_backend_allows_openai_compatible_without_api_key() -> None:
+    backend = cast(
+        "LiteLLMVisionOCRBackend",
+        benchmark._build_ocr_backend(
+            benchmark.BenchmarkOptions(
+                backend="openai-compatible",
+                dataset_split="dev",
+                model="local-model",
+                base_url="http://127.0.0.1:8000/v1",
+            )
+        ),
+    )
+
+    assert backend.provider_name == "openai-compatible"
+    assert backend.transport.config.api_base == "http://127.0.0.1:8000/v1"
+    assert backend.transport.config.api_key is None
+
+
 def test_build_ocr_backend_uses_dots_preset_for_hf() -> None:
     backend = cast(
         "HuggingFaceVisionOCRBackend",
@@ -214,38 +216,41 @@ def test_build_ocr_backend_uses_dots_preset_for_hf() -> None:
     assert backend.processor_kwargs == {}
     assert backend.trust_remote_code is True
     assert backend.model_kwargs["dtype"] in {"auto", "float32"}
-    if backend.model_kwargs["dtype"] == "auto":
+    if backend.model_kwargs["dtype"] == "auto" and "device_map" in backend.model_kwargs:
         assert backend.model_kwargs["device_map"] == "auto"
-        assert "max_memory" in backend.model_kwargs
+    if "max_memory" in backend.model_kwargs:
+        assert backend.model_kwargs["max_memory"]
     assert backend.generation_kwargs == {"max_new_tokens": DEFAULT_OCR_MAX_TOKENS}
 
 
-def test_build_ocr_backend_uses_dots_preset_for_vllm() -> None:
+def test_build_ocr_backend_uses_dots_preset_for_openai_compatible() -> None:
     backend = cast(
-        "VLLMVisionOCRBackend",
+        "LiteLLMVisionOCRBackend",
         benchmark._build_ocr_backend(
             benchmark.BenchmarkOptions(
-                backend="vllm",
+                backend="openai-compatible",
                 dataset_split="dev",
                 model="kristaller486/dots.ocr-1.5",
+                base_url="http://127.0.0.1:8000/v1",
             )
         ),
     )
 
+    assert backend.provider_name == "openai-compatible"
     assert backend.model_name == "dots.ocr-1.5"
-    assert backend.processor_kwargs == {}
-    assert backend.trust_remote_code is True
-    assert backend.sampling_kwargs == {"max_tokens": DEFAULT_OCR_MAX_TOKENS}
+    assert backend.template == DOTS_OCR_1_5_OCR_TEMPLATE
+    assert backend.transport.config.completion_kwargs == {"max_tokens": DEFAULT_OCR_MAX_TOKENS}
 
 
-def test_build_ocr_backend_uses_churro_preset_template_for_vllm() -> None:
+def test_build_ocr_backend_uses_churro_preset_template_for_openai_compatible() -> None:
     backend = cast(
-        "VLLMVisionOCRBackend",
+        "LiteLLMVisionOCRBackend",
         benchmark._build_ocr_backend(
             benchmark.BenchmarkOptions(
-                backend="vllm",
+                backend="openai-compatible",
                 dataset_split="dev",
                 model="stanford-oval/churro-3B",
+                base_url="http://127.0.0.1:8000/v1",
             )
         ),
     )
@@ -254,29 +259,24 @@ def test_build_ocr_backend_uses_churro_preset_template_for_vllm() -> None:
     assert backend.model_name == "churro-3B"
 
 
-def test_build_ocr_backend_uses_generic_qwen_model_name_for_vllm() -> None:
+def test_build_ocr_backend_uses_generic_qwen_model_name_for_openai_compatible() -> None:
     backend = cast(
-        "VLLMVisionOCRBackend",
+        "LiteLLMVisionOCRBackend",
         benchmark._build_ocr_backend(
             benchmark.BenchmarkOptions(
-                backend="vllm",
+                backend="openai-compatible",
                 dataset_split="dev",
                 model="Qwen/Qwen3.5-0.8B",
-                vllm_gpu_memory_utilization=0.25,
-                vllm_cpu_offload_gb=8.0,
+                base_url="http://127.0.0.1:8000/v1",
             )
         ),
     )
 
     assert backend.model_name == "Qwen/Qwen3.5-0.8B"
-    assert backend.llm_kwargs == {
-        "gpu_memory_utilization": 0.25,
-        "cpu_offload_gb": 8.0,
-    }
-    assert backend.sampling_kwargs == {"max_tokens": DEFAULT_OCR_MAX_TOKENS}
+    assert backend.transport.config.completion_kwargs == {"max_tokens": DEFAULT_OCR_MAX_TOKENS}
 
 
-def test_build_ocr_backend_aligns_hf_and_vllm_templates_for_generic_models() -> None:
+def test_build_ocr_backend_aligns_hf_and_openai_compatible_templates_for_generic_models() -> None:
     hf_backend = cast(
         "HuggingFaceVisionOCRBackend",
         benchmark._build_ocr_backend(
@@ -287,18 +287,19 @@ def test_build_ocr_backend_aligns_hf_and_vllm_templates_for_generic_models() ->
             )
         ),
     )
-    vllm_backend = cast(
-        "VLLMVisionOCRBackend",
+    openai_backend = cast(
+        "LiteLLMVisionOCRBackend",
         benchmark._build_ocr_backend(
             benchmark.BenchmarkOptions(
-                backend="vllm",
+                backend="openai-compatible",
                 dataset_split="dev",
                 model="example/model",
+                base_url="http://127.0.0.1:8000/v1",
             )
         ),
     )
 
-    assert hf_backend.template == vllm_backend.template
+    assert hf_backend.template == openai_backend.template
 
 
 @pytest.mark.asyncio
@@ -678,43 +679,6 @@ async def ocr_batch(self, pages):  # noqa: ANN001
     ]
 
 
-@pytest.mark.asyncio
-async def test_predict_texts_uses_max_concurrency_for_vllm_batch_backend(monkeypatch) -> None:
-    dataset = [
-        _benchmark_example(str(index), size=(index + 1, index + 1), transcription=f"text-{index}")
-        for index in range(10)
-    ]
-    captured_batch_sizes: list[int] = []
-
-    class FakeOCRResult:
-        def __init__(self, text: str) -> None:
-            self.text = text
-
-    class FakeBatchBackend:
-        async def ocr_batch(self, pages):  # noqa: ANN001
-            captured_batch_sizes.append(len(pages))
-            return [FakeOCRResult(text=f"page-{page.width}") for page in pages]
-
-    monkeypatch.setattr(benchmark, "_build_ocr_backend", lambda _: FakeBatchBackend())
-
-    options = benchmark.BenchmarkOptions(
-        backend="vllm",
-        dataset_split="dev",
-        model="Qwen/Qwen3.5-0.8B",
-        max_concurrency=2,
-    )
-
-    evaluation_examples, predictions = await benchmark._predict_texts(
-        dataset,
-        options,
-        total_pages=10,
-    )
-
-    assert captured_batch_sizes == [2, 2, 2, 2, 2]
-    assert predictions == [f"page-{index + 1}" for index in range(10)]
-    assert evaluation_examples == [benchmark._build_evaluation_example(example) for example in dataset]
-
-
 @pytest.mark.asyncio
 async def test_predict_texts_logs_first_submitted_output_once_for_non_batch_backend(monkeypatch) -> None:
     dataset: list[BenchmarkDatasetExample] = [
diff --git a/tooling/benchmarking/benchmark.py b/tooling/benchmarking/benchmark.py
index 2ca1622..f5bebb3 100644
--- a/tooling/benchmarking/benchmark.py
+++ b/tooling/benchmarking/benchmark.py
@@ -32,7 +32,6 @@
     MistralOptions,
     OCRBackendSpec,
     OpenAICompatibleOptions,
-    VLLMOptions,
 )
 from tooling.benchmarking.dataset import (
     DatasetSelection,
@@ -44,7 +43,7 @@
 
 CHURRO_DATASET_ID = "stanford-oval/churro-dataset"
 VALID_DATASET_SPLITS = {"dev", "test"}
-VALID_OCR_BACKENDS = {"litellm", "openai-compatible", "azure", "mistral", "hf", "vllm"}
+VALID_OCR_BACKENDS = {"litellm", "openai-compatible", "azure", "mistral", "hf"}
 BENCHMARK_DATASET_COLUMNS = (
     "image",
     "cleaned_transcription",
@@ -73,8 +72,6 @@ class BenchmarkOptions:
     api_key: str | None = None
     base_url: str | None = None
     api_version: str | None = None
-    vllm_gpu_memory_utilization: float | None = None
-    vllm_cpu_offload_gb: float | None = None
 
     def dataset_subset(self) -> DatasetSubset:
         """Return the normalized subset filters for this benchmark run."""
@@ -108,8 +105,6 @@ def build_parser(*, add_help: bool = True) -> argparse.ArgumentParser:
     parser.add_argument("--api-key", default=None)
     parser.add_argument("--base-url", default=None)
     parser.add_argument("--api-version", default=None)
-    parser.add_argument("--vllm-gpu-memory-utilization", type=float, default=None)
-    parser.add_argument("--vllm-cpu-offload-gb", type=float, default=None)
     return parser
 
 
@@ -130,8 +125,6 @@ def parse_args(argv: list[str] | None = None) -> BenchmarkOptions:
         api_key=namespace.api_key,
         base_url=namespace.base_url,
         api_version=namespace.api_version,
-        vllm_gpu_memory_utilization=namespace.vllm_gpu_memory_utilization,
-        vllm_cpu_offload_gb=namespace.vllm_cpu_offload_gb,
     )
 
 
@@ -148,25 +141,12 @@ def _validate_options(options: BenchmarkOptions) -> int:
     if options.backend == "litellm" and not options.model:
         logger.error("--model is required for backend=litellm.")
         return 1
-    if options.backend == "openai-compatible" and (
-        not options.model or not options.base_url or not options.api_key
-    ):
-        logger.error("--model, --base-url, and --api-key are required for backend=openai-compatible.")
+    if options.backend == "openai-compatible" and (not options.model or not options.base_url):
+        logger.error("--model and --base-url are required for backend=openai-compatible.")
         return 1
     if options.backend == "hf" and not options.model:
         logger.error("--model is required for backend=hf.")
         return 1
-    if options.backend == "vllm" and not options.model:
-        logger.error("--model is required for backend=vllm.")
-        return 1
-    if options.vllm_gpu_memory_utilization is not None and not (
-        0.0 < options.vllm_gpu_memory_utilization <= 1.0
-    ):
-        logger.error("--vllm-gpu-memory-utilization must be in the range (0, 1].")
-        return 1
-    if options.vllm_cpu_offload_gb is not None and options.vllm_cpu_offload_gb < 0.0:
-        logger.error("--vllm-cpu-offload-gb must be non-negative.")
-        return 1
     if options.backend == "azure" and (not options.endpoint or not options.api_key):
         logger.error("--endpoint and --api-key are required for backend=azure.")
         return 1
@@ -232,7 +212,6 @@ def _build_ocr_backend(options: BenchmarkOptions) -> OCRBackendLike:
     if options.backend == "openai-compatible":
         assert options.model is not None
         assert options.base_url is not None
-        assert options.api_key is not None
         return build_ocr_backend(
             OCRBackendSpec(
                 provider="openai-compatible",
@@ -267,20 +246,6 @@ def _build_ocr_backend(options: BenchmarkOptions) -> OCRBackendLike:
                 options=HuggingFaceOptions(model_kwargs={"device_map": "auto", "torch_dtype": "auto"}),
             )
         )
-    if options.backend == "vllm":
-        assert options.model is not None
-        llm_kwargs: dict[str, object] = {}
-        if options.vllm_gpu_memory_utilization is not None:
-            llm_kwargs["gpu_memory_utilization"] = options.vllm_gpu_memory_utilization
-        if options.vllm_cpu_offload_gb is not None:
-            llm_kwargs["cpu_offload_gb"] = options.vllm_cpu_offload_gb
-        return build_ocr_backend(
-            OCRBackendSpec(
-                provider="vllm",
-                model=options.model,
-                options=VLLMOptions(llm_kwargs=llm_kwargs),
-            )
-        )
     assert options.api_key is not None
     return build_ocr_backend(
         OCRBackendSpec(

From 63e3ca02ee3768704a3324313eeba7c57d19934d Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Sun, 5 Apr 2026 22:49:17 +0000
Subject: [PATCH 05/28] docs(repo): consolidate install and provider guidance

---
 README.md                |  5 ++--
 docs/benchmarking.md     |  5 ++--
 docs/cli.md              | 28 +++++++++++++++++++----
 docs/getting-started.md  | 39 +++++++++++++++-----------------
 docs/guides/providers.md | 49 ++++++++++++++++++----------------------
 docs/pypi.md             | 21 +++++++++--------
 6 files changed, 81 insertions(+), 66 deletions(-)

diff --git a/README.md b/README.md
index f133067..bcb8ada 100644
--- a/README.md
+++ b/README.md
@@ -2,7 +2,7 @@
 
 CHURRO is an OCR toolkit for historical document transcription, built to make handwritten and printed sources readable at high accuracy and lower cost.
 
-It works with all major OCR proividers and vision-language models, and provides first-party support for the CHURRO 3B model and CHURRO-DS dataset.
+It works with all major OCR providers and vision-language models, and provides first-party support for the CHURRO 3B model and CHURRO-DS dataset.
 
 [![Model](https://img.shields.io/badge/Model-CHURRO%203B-8A4FFF)](https://huggingface.co/stanford-oval/churro-3B)
 [![Dataset](https://img.shields.io/badge/Dataset-CHURRO--DS-0A7BBB)](https://huggingface.co/datasets/stanford-oval/churro-dataset)
@@ -24,7 +24,8 @@ It works with all major OCR proividers and vision-language models, and provides
 ## Quick Try
 
 ```bash
-pip install "churro-ocr[hf]"
+uv tool install churro-ocr
+churro-ocr install hf
 churro-ocr transcribe --image scan.png --backend hf --model stanford-oval/churro-3B
 ```
 
diff --git a/docs/benchmarking.md b/docs/benchmarking.md
index f6a8ea8..e4da07f 100644
--- a/docs/benchmarking.md
+++ b/docs/benchmarking.md
@@ -27,7 +27,6 @@ By default, results are written under `workdir/results/<split>/`.
 - `--language` and `--document-type`: filter the benchmark subset before slicing
 - `--output-dir PATH`: override the default results directory
 - `--max-concurrency N`: cap the number of in-flight OCR requests
-- `--vllm-gpu-memory-utilization` and `--vllm-cpu-offload-gb`: pass through selected vLLM runtime knobs
 
 ## Output Files
 
@@ -51,7 +50,9 @@ That means `--language Arabic --offset 100 --input-size 50` selects rows 101 to
 
 ## Example Commands
 
+Start a dedicated local vLLM server separately with `churro-ocr install vllm` and `churro-ocr serve-vllm --model ...`, then point the benchmark runner at `http://127.0.0.1:8000/v1`.
+
 | Model | Model ID | Backend | Full command |
 | --- | --- | --- | --- |
 | Gemini 2.5 Pro | `vertex_ai/gemini-2.5-pro` | `litellm` | `pixi run python -m tooling.benchmarking.benchmark --backend litellm --dataset-split test --model vertex_ai/gemini-2.5-pro --output-dir workdir/results/test/litellm_vertex_ai_gemini-2.5-pro` |
-| Qwen 3.5-0.8B | `Qwen/Qwen3.5-0.8B` | `vllm` | `pixi run python -m tooling.benchmarking.benchmark --backend vllm --dataset-split test --model Qwen/Qwen3.5-0.8B --output-dir workdir/results/test/vllm_Qwen_Qwen3.5-0.8B` |
+| Qwen 3.5-0.8B | `Qwen/Qwen3.5-0.8B` | `openai-compatible` | `pixi run python -m tooling.benchmarking.benchmark --backend openai-compatible --dataset-split test --model Qwen/Qwen3.5-0.8B --base-url http://127.0.0.1:8000/v1 --output-dir workdir/results/test/openai-compatible_Qwen_Qwen3.5-0.8B` |
diff --git a/docs/cli.md b/docs/cli.md
index d47f119..d81e0aa 100644
--- a/docs/cli.md
+++ b/docs/cli.md
@@ -3,14 +3,36 @@
 Use the CLI when you want a quick sanity check before writing Python code.
 
 Use `churro-ocr --help` or `python -m churro_ocr --help` to inspect the top-level commands.
+Install Churro in [Getting Started](getting-started.md), and use
+[Providers And Configuration](guides/providers.md)
+for backend-specific runtime setup.
 
 ## Command Summary
 
 | Command | Use it when |
 | --- | --- |
+| `install` | you want Churro to install an optional runtime into the active UV environment |
+| `serve-vllm` | you want to start the dedicated Churro-managed vLLM runtime |
 | `transcribe` | you want OCR text for one image |
 | `extract-pages` | you want page crops from an image or PDF |
 
+## `install` Examples
+
+### Install Local Transformers OCR
+
+```bash
+churro-ocr install hf
+```
+
+### Install And Serve The Recommended vLLM Runtime
+
+```bash
+churro-ocr install vllm
+churro-ocr serve-vllm --model stanford-oval/churro-3B
+```
+
+Any extra flags after the command are forwarded to `vllm serve`.
+
 ## `transcribe` Examples
 
 ### OCR One Image
@@ -29,8 +51,7 @@ churro-ocr transcribe \
   --image scan.png \
   --backend openai-compatible \
   --model local-model \
-  --base-url http://127.0.0.1:8000/v1 \
-  --api-key dummy
+  --base-url http://127.0.0.1:8000/v1
 ```
 
 ## `extract-pages` Examples
@@ -73,11 +94,10 @@ churro-ocr extract-pages \
 | `--backend` value | Required flags | Notes |
 | --- | --- | --- |
 | `litellm` | `--model` | Uses LiteLLM credentials and routing. `--base-url`, `--api-key`, and `--api-version` are optional transport overrides. |
-| `openai-compatible` | `--model`, `--base-url`, `--api-key` | For local or self-hosted OpenAI-style servers. |
+| `openai-compatible` | `--model`, `--base-url` | For local or self-hosted OpenAI-style servers. `--api-key` is optional. |
 | `azure` | `--endpoint`, `--api-key` | `--model` is optional. |
 | `mistral` | `--api-key` | `--model` defaults to `mistral-ocr-latest`. |
 | `hf` | `--model` | Local Transformers OCR. |
-| `vllm` | `--model` | Local vLLM OCR. |
 
 ### `extract-pages` Detectors
 
diff --git a/docs/getting-started.md b/docs/getting-started.md
index 1dbf321..edbc304 100644
--- a/docs/getting-started.md
+++ b/docs/getting-started.md
@@ -11,36 +11,31 @@
 | Run an end-to-end image or PDF OCR workflow | `DocumentOCRPipeline` |
 | Tune provider options directly | `build_ocr_backend(...)` + `OCRBackendSpec` |
 
-## Install Only What You Need
+## Install
+
+Use UV as the supported install path.
 
 ```bash
-pip install churro-ocr
-pip install "churro-ocr[llm]"
-pip install "churro-ocr[local]"
-pip install "churro-ocr[hf]"
-pip install "churro-ocr[vllm]"
-pip install "churro-ocr[azure]"
-pip install "churro-ocr[mistral]"
-pip install "churro-ocr[pdf]"
-pip install "churro-ocr[all]"
+uv tool install churro-ocr
+# or, in a project:
+uv add churro-ocr
 ```
 
-## Provider Extras
+Then install the runtime for the backend you plan to use:
 
-| Extra | Use it when |
-| --- | --- |
-| `llm` | you want hosted multimodal OCR and LLM-based page detection through LiteLLM |
-| `local` | you have a local or self-hosted OpenAI-compatible server |
-| `hf` | you want local Transformers inference in-process |
-| `vllm` | you want higher-throughput local serving |
-| `azure` | you want Azure Document Intelligence OCR or layout detection |
-| `mistral` | you want Mistral OCR |
-| `pdf` | you want PDF rasterization through `pypdfium2` |
-| `all` | you want every supported backend and utility extra |
+```bash
+uv run churro-ocr install llm
+uv run churro-ocr install hf
+uv run churro-ocr install vllm
+```
+
+If you installed the CLI with `uv tool install churro-ocr`, drop the `uv run` prefix.
+For the full provider/runtime matrix, use [Providers And Configuration](guides/providers.md).
 
 ## First OCR Example
 
 Use `OCRClient` when your input is already one page per image.
+This example uses `provider="litellm"`, so install the `llm` runtime first.
 
 ```python
 from churro_ocr.ocr import OCRClient
@@ -67,6 +62,8 @@ When an API accepts both `image` and `image_path`, pass exactly one of them.
 Use the CLI when you want to confirm a model or backend before writing Python code.
 
 ```bash
+uv tool install churro-ocr
+churro-ocr install hf
 churro-ocr transcribe \
   --image scan.png \
   --backend hf \
diff --git a/docs/guides/providers.md b/docs/guides/providers.md
index 08e5b6f..f0adbc8 100644
--- a/docs/guides/providers.md
+++ b/docs/guides/providers.md
@@ -15,14 +15,16 @@ backend = build_ocr_backend(
 
 ## Which OCR Backend Should You Use?
 
-| Provider | Install extra | Good default when |
+Install the base package first as shown in [Getting Started](../getting-started.md).
+This page is the source of truth for matching providers to runtime targets.
+
+| Provider | Install command | Good default when |
 | --- | --- | --- |
-| `litellm` | `llm` | you want hosted multimodal models routed through LiteLLM |
-| `openai-compatible` | `local` | you have a local or self-hosted OpenAI-style server |
-| `hf` | `hf` | you want local Transformers inference in-process |
-| `vllm` | `vllm` | you want higher-throughput local serving |
-| `azure` | `azure` | you want Azure Document Intelligence OCR |
-| `mistral` | `mistral` | you want Mistral OCR |
+| `litellm` | `churro-ocr install llm` | you want hosted multimodal models routed through LiteLLM |
+| `openai-compatible` | `churro-ocr install local` | you have a local or self-hosted OpenAI-style server |
+| `hf` | `churro-ocr install hf` | you want local Transformers inference in-process |
+| `azure` | `churro-ocr install azure` | you want Azure Document Intelligence OCR |
+| `mistral` | `churro-ocr install mistral` | you want Mistral OCR |
 
 ## Recommended Starting Points
 
@@ -30,7 +32,7 @@ backend = build_ocr_backend(
 | --- | --- | --- |
 | hosted OCR | `litellm` + `vertex_ai/gemini-2.5-flash` | easiest hosted path with the standard builder interface |
 | local OCR | `hf` + `stanford-oval/churro-3B` | first-party local model support in-process |
-| higher-throughput local serving | `vllm` + `stanford-oval/churro-3B` | better fit when you want a served local backend |
+| higher-throughput local serving | `openai-compatible` + `serve-vllm` + `stanford-oval/churro-3B` | recommended path when you want a dedicated served local backend |
 
 ## Hosted Providers
 
@@ -102,6 +104,8 @@ backend = build_ocr_backend(
 
 ## Local And Self-Hosted Providers
 
+Before using a local or self-hosted provider, install the matching runtime from the table above.
+
 ### OpenAI-compatible
 
 ```python
@@ -117,12 +121,18 @@ backend = build_ocr_backend(
         model="local-model",
         transport=LiteLLMTransportConfig(
             api_base="http://127.0.0.1:8000/v1",
-            api_key="dummy",
         ),
     )
 )
 ```
 
+This is also the recommended way to talk to a dedicated vLLM server:
+
+```bash
+uv run churro-ocr install vllm
+uv run churro-ocr serve-vllm --model stanford-oval/churro-3B
+```
+
 ### Hugging Face
 
 ```python
@@ -139,26 +149,12 @@ backend = build_ocr_backend(
 )
 ```
 
-### vLLM
-
-```python
-from churro_ocr.providers import OCRBackendSpec, VLLMOptions, build_ocr_backend
-
-backend = build_ocr_backend(
-    OCRBackendSpec(
-        provider="vllm",
-        model="stanford-oval/churro-3B",
-        options=VLLMOptions(),
-    )
-)
-```
-
 ## `OCRBackendSpec` Reference
 
 | Field | Meaning |
 | --- | --- |
-| `provider` | One of `litellm`, `openai-compatible`, `azure`, `mistral`, `hf`, or `vllm`. |
-| `model` | Required for `litellm`, `openai-compatible`, `hf`, and `vllm`. Optional for `azure`. Defaults to `mistral-ocr-latest` when omitted for `mistral`. |
+| `provider` | One of `litellm`, `openai-compatible`, `azure`, `mistral`, or `hf`. |
+| `model` | Required for `litellm`, `openai-compatible`, and `hf`. Optional for `azure`. Defaults to `mistral-ocr-latest` when omitted for `mistral`. |
 | `profile` | `None`, a built-in profile name, or a custom `OCRModelProfile`. |
 | `transport` | Shared request transport config for LiteLLM-based providers. |
 | `options` | Provider-specific dataclass matching `provider`. |
@@ -167,10 +163,9 @@ backend = build_ocr_backend(
 
 | Type | Used by | Required fields | Notes |
 | --- | --- | --- | --- |
-| `LiteLLMTransportConfig` | `litellm`, `openai-compatible`, `LLMPageDetector` | None at the dataclass level | Use this for transport, credentials, and completion settings. |
+| `LiteLLMTransportConfig` | `litellm`, `openai-compatible`, `LLMPageDetector` | None at the dataclass level | Use this for transport, credentials, and completion settings. `api_base` is required for `openai-compatible`; `api_key` is optional. |
 | `OpenAICompatibleOptions` | `openai-compatible` | None | Use `model_prefix` when your local server expects a provider prefix. |
 | `HuggingFaceOptions` | `hf` | None | Carries runtime, processor, generation, and template options. |
-| `VLLMOptions` | `vllm` | None | Carries runtime and sampling settings for vLLM. |
 | `AzureDocumentIntelligenceOptions` | `azure` | `endpoint`, `api_key` | `model` is optional for Azure OCR in `OCRBackendSpec`. |
 | `MistralOptions` | `mistral` | `api_key` | `model` defaults to `mistral-ocr-latest` when omitted. |
 
diff --git a/docs/pypi.md b/docs/pypi.md
index 6d55bf2..28e1359 100644
--- a/docs/pypi.md
+++ b/docs/pypi.md
@@ -6,20 +6,19 @@ Full documentation and project overview live at https://stanford-oval.github.io/
 
 ## Install
 
-Install only the pieces you need:
+Use UV as the supported install path.
 
 ```bash
-pip install churro-ocr
-pip install "churro-ocr[llm]"
-pip install "churro-ocr[local]"
-pip install "churro-ocr[hf]"
-pip install "churro-ocr[vllm]"
-pip install "churro-ocr[azure]"
-pip install "churro-ocr[mistral]"
-pip install "churro-ocr[pdf]"
-pip install "churro-ocr[all]"
+uv tool install churro-ocr
+# or, in a project:
+uv add churro-ocr
 ```
 
+Runtime setup and provider-specific install commands are in
+[Getting Started](https://stanford-oval.github.io/Churro/getting-started.html)
+and
+[Providers And Configuration](https://stanford-oval.github.io/Churro/guides/providers.html).
+
 ## Which API Should You Use?
 
 | Goal | API |
@@ -31,6 +30,8 @@ pip install "churro-ocr[all]"
 
 ## Quick Start
 
+This example assumes you already installed the runtime for the provider you want to use.
+
 ```python
 from churro_ocr.ocr import OCRClient
 from churro_ocr.providers import OCRBackendSpec, build_ocr_backend

From 7cfcc1e1b595719d196dd1af1fd5730d67d85da6 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Sun, 5 Apr 2026 23:18:58 +0000
Subject: [PATCH 06/28] fix(docs): move badges to the top of the README file

---
 README.md | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/README.md b/README.md
index bcb8ada..77f2fde 100644
--- a/README.md
+++ b/README.md
@@ -1,9 +1,5 @@
 # <img src="static/churro.png" alt="CHURRO logo" width="40" /> CHURRO
 
-CHURRO is an OCR toolkit for historical document transcription, built to make handwritten and printed sources readable at high accuracy and lower cost.
-
-It works with all major OCR providers and vision-language models, and provides first-party support for the CHURRO 3B model and CHURRO-DS dataset.
-
 [![Model](https://img.shields.io/badge/Model-CHURRO%203B-8A4FFF)](https://huggingface.co/stanford-oval/churro-3B)
 [![Dataset](https://img.shields.io/badge/Dataset-CHURRO--DS-0A7BBB)](https://huggingface.co/datasets/stanford-oval/churro-dataset)
 [![Paper](https://img.shields.io/badge/Paper-arXiv-B31B1B)](https://arxiv.org/abs/2509.19768)
@@ -11,6 +7,10 @@ It works with all major OCR providers and vision-language models, and provides f
 [![Leaderboard](https://img.shields.io/badge/Leaderboard-Benchmark%20Snapshot-6B7280)](https://stanford-oval.github.io/Churro/leaderboard.html)
 [![GitHub Stars](https://img.shields.io/github/stars/stanford-oval/churro?style=social)](https://github.com/stanford-oval/churro/stargazers)
 
+CHURRO is an OCR toolkit for historical document transcription, built to make handwritten and printed sources readable at high accuracy and lower cost.
+
+It works with all major OCR providers and vision-language models, and provides first-party support for the CHURRO 3B model and CHURRO-DS dataset.
+
 
 - CHURRO 3B exceeds the accuracy of Gemini 2.5 Pro at 15.5x lower cost.
 - CHURRO-DS contains ~100K pages from 155 historical collections spanning 22 centuries and 46 language clusters.

From aa2ba0e3757144b821c2c3e6aced69b91843cdd8 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Mon, 6 Apr 2026 00:07:38 +0000
Subject: [PATCH 07/28] refactor(runtime)!: remove managed vllm runtime support

Remove the repo-managed vLLM install and serve path in favor of external OpenAI-compatible servers.

BREAKING CHANGE: The `vllm` extra, `churro-ocr install vllm`, and `churro-ocr serve-vllm` were removed. Use an external vLLM OpenAI-compatible server with the `openai-compatible` backend instead.
---
 docs/benchmarking.md                |   2 +-
 docs/cli.md                         |  12 +--
 docs/getting-started.md             |   2 +-
 docs/guides/providers.md            |   9 +-
 pixi.lock                           |   3 +-
 pyproject.toml                      |   3 -
 scripts/package_check.py            |  10 +-
 src/churro_ocr/_internal/install.py | 139 ----------------------------
 src/churro_ocr/cli.py               |  37 --------
 tests/test_cli.py                   |  54 +----------
 tests/test_cli_contract.py          |   2 +-
 tests/test_install.py               | 118 ++---------------------
 tests/test_package_check.py         |  11 +--
 tests/test_tooling_benchmark.py     |   4 +-
 14 files changed, 25 insertions(+), 381 deletions(-)

diff --git a/docs/benchmarking.md b/docs/benchmarking.md
index e4da07f..d1e8263 100644
--- a/docs/benchmarking.md
+++ b/docs/benchmarking.md
@@ -50,7 +50,7 @@ That means `--language Arabic --offset 100 --input-size 50` selects rows 101 to
 
 ## Example Commands
 
-Start a dedicated local vLLM server separately with `churro-ocr install vllm` and `churro-ocr serve-vllm --model ...`, then point the benchmark runner at `http://127.0.0.1:8000/v1`.
+If you want to benchmark a vLLM-served model, run vLLM separately and point `--backend openai-compatible` at its OpenAI-compatible endpoint. See the [official vLLM serving docs](https://docs.vllm.ai/en/stable/serving/openai_compatible_server.html).
 
 | Model | Model ID | Backend | Full command |
 | --- | --- | --- | --- |
diff --git a/docs/cli.md b/docs/cli.md
index d81e0aa..f7a1a95 100644
--- a/docs/cli.md
+++ b/docs/cli.md
@@ -12,7 +12,6 @@ for backend-specific runtime setup.
 | Command | Use it when |
 | --- | --- |
 | `install` | you want Churro to install an optional runtime into the active UV environment |
-| `serve-vllm` | you want to start the dedicated Churro-managed vLLM runtime |
 | `transcribe` | you want OCR text for one image |
 | `extract-pages` | you want page crops from an image or PDF |
 
@@ -24,15 +23,6 @@ for backend-specific runtime setup.
 churro-ocr install hf
 ```
 
-### Install And Serve The Recommended vLLM Runtime
-
-```bash
-churro-ocr install vllm
-churro-ocr serve-vllm --model stanford-oval/churro-3B
-```
-
-Any extra flags after the command are forwarded to `vllm serve`.
-
 ## `transcribe` Examples
 
 ### OCR One Image
@@ -54,6 +44,8 @@ churro-ocr transcribe \
   --base-url http://127.0.0.1:8000/v1
 ```
 
+For vLLM, serve the model separately with its OpenAI-compatible server and then use this same `openai-compatible` route. See the [official vLLM serving docs](https://docs.vllm.ai/en/stable/serving/openai_compatible_server.html).
+
 ## `extract-pages` Examples
 
 ### Extract Pages From An Image
diff --git a/docs/getting-started.md b/docs/getting-started.md
index edbc304..92cef8b 100644
--- a/docs/getting-started.md
+++ b/docs/getting-started.md
@@ -26,7 +26,7 @@ Then install the runtime for the backend you plan to use:
 ```bash
 uv run churro-ocr install llm
 uv run churro-ocr install hf
-uv run churro-ocr install vllm
+uv run churro-ocr install local
 ```
 
 If you installed the CLI with `uv tool install churro-ocr`, drop the `uv run` prefix.
diff --git a/docs/guides/providers.md b/docs/guides/providers.md
index f0adbc8..3b1640a 100644
--- a/docs/guides/providers.md
+++ b/docs/guides/providers.md
@@ -32,7 +32,7 @@ This page is the source of truth for matching providers to runtime targets.
 | --- | --- | --- |
 | hosted OCR | `litellm` + `vertex_ai/gemini-2.5-flash` | easiest hosted path with the standard builder interface |
 | local OCR | `hf` + `stanford-oval/churro-3B` | first-party local model support in-process |
-| higher-throughput local serving | `openai-compatible` + `serve-vllm` + `stanford-oval/churro-3B` | recommended path when you want a dedicated served local backend |
+| higher-throughput local serving | `openai-compatible` + your own OpenAI-style server | good when you already run a served local backend such as vLLM |
 
 ## Hosted Providers
 
@@ -126,12 +126,7 @@ backend = build_ocr_backend(
 )
 ```
 
-This is also the recommended way to talk to a dedicated vLLM server:
-
-```bash
-uv run churro-ocr install vllm
-uv run churro-ocr serve-vllm --model stanford-oval/churro-3B
-```
+If you want to use vLLM, serve it separately and point this backend at that server's OpenAI-compatible endpoint. See the [official vLLM serving docs](https://docs.vllm.ai/en/stable/serving/openai_compatible_server.html).
 
 ### Hugging Face
 
diff --git a/pixi.lock b/pixi.lock
index 3eb0c09..f4542de 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -776,7 +776,7 @@ packages:
 - pypi: ./
   name: churro-ocr
   version: 0.2.0
-  sha256: c9aab6c57f839ce8119b38b864926707e9f7b1e55548a4dfc0421eb8520d5ba3
+  sha256: f05d8a5f234f0cdb08bcdbf205bea3cdcfecd53b1ac058686bb9341e92719637
   requires_dist:
   - loguru>=0.7.2,<1
   - pillow>=10.4.0,<12
@@ -787,7 +787,6 @@ packages:
   - azure-ai-documentintelligence==1.0.2 ; extra == 'azure'
   - qwen-vl-utils ; extra == 'hf'
   - transformers>=4.57.0,<5 ; extra == 'hf'
-  - vllm>=0.18,<1 ; extra == 'vllm'
   - mistralai>=1.6.0,<2 ; extra == 'mistral'
   - litellm[caching]==1.82.3 ; extra == 'local'
   - pypdfium2>=5,<6 ; extra == 'pdf'
diff --git a/pyproject.toml b/pyproject.toml
index 568ef00..367c298 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -35,9 +35,6 @@ hf = [
     "qwen-vl-utils",
     "transformers>=4.57.0,<5",
 ]
-vllm = [
-    "vllm>=0.18,<1",
-]
 mistral = [
     "mistralai>=1.6.0,<2",
 ]
diff --git a/scripts/package_check.py b/scripts/package_check.py
index 865ae77..6dd41cd 100644
--- a/scripts/package_check.py
+++ b/scripts/package_check.py
@@ -35,7 +35,6 @@
     "local",
     "mistral",
     "pdf",
-    "vllm",
 }
 FORBIDDEN_ARTIFACT_SEGMENTS = ("/tests/", "/tooling/", "/scripts/")
 FORBIDDEN_ARTIFACT_SUFFIXES = ("PYPI_AUDIT.md",)
@@ -146,13 +145,10 @@ def _iter_requirements_for_extra(metadata_message: Message, extra: str) -> list[
 
 def _assert_local_runtime_packaging_policy(metadata_message: Message) -> None:
     disallowed_runtime_reqs: list[str] = []
-    for extra in ("hf", "all"):
+    for extra in EXPECTED_EXTRAS:
         for requirement in _iter_requirements_for_extra(metadata_message, extra):
             normalized_name = requirement.name.replace("_", "-").lower()
-            if extra == "all" and normalized_name == "vllm":
-                disallowed_runtime_reqs.append(f"{extra}:{requirement}")
-                continue
-            if normalized_name in {"torch", "torchvision"}:
+            if normalized_name in {"torch", "torchvision", "vllm"}:
                 disallowed_runtime_reqs.append(f"{extra}:{requirement}")
                 continue
             if normalized_name == "transformers" and "torch" in requirement.extras:
@@ -160,7 +156,7 @@ def _assert_local_runtime_packaging_policy(metadata_message: Message) -> None:
     if disallowed_runtime_reqs:
         formatted = ", ".join(sorted(disallowed_runtime_reqs))
         raise RuntimeError(
-            "PyPI extras for active-environment runtimes must not pin a local PyTorch or vLLM runtime. "
+            "PyPI extras for active-environment runtimes must not pin local PyTorch or vLLM runtimes. "
             f"Found disallowed requirements: {formatted}."
         )
 
diff --git a/src/churro_ocr/_internal/install.py b/src/churro_ocr/_internal/install.py
index dff132f..e1e7ff0 100644
--- a/src/churro_ocr/_internal/install.py
+++ b/src/churro_ocr/_internal/install.py
@@ -2,25 +2,20 @@
 
 from __future__ import annotations
 
-import os
 import shutil
 import subprocess
 import sys
 from dataclasses import dataclass
 from importlib import metadata
-from pathlib import Path
 from typing import Final
 
 from churro_ocr.errors import ConfigurationError
 
 PROJECT_DISTRIBUTION_NAME: Final[str] = "churro-ocr"
-VLLM_RUNTIME_DIR_ENV: Final[str] = "CHURRO_OCR_VLLM_RUNTIME_DIR"
-DEFAULT_VLLM_RUNTIME_DIR: Final[Path] = Path.home() / ".cache" / "churro-ocr" / "runtimes" / "vllm"
 INSTALL_TARGETS: Final[tuple[str, ...]] = (
     "llm",
     "local",
     "hf",
-    "vllm",
     "azure",
     "mistral",
     "pdf",
@@ -30,7 +25,6 @@
     "llm": ("llm",),
     "local": ("local",),
     "hf": ("hf",),
-    "vllm": ("local",),
     "azure": ("azure",),
     "mistral": ("mistral",),
     "pdf": ("pdf",),
@@ -47,7 +41,6 @@ class RuntimeInstallResult:
     target: str
     executed_commands: tuple[tuple[str, ...], ...]
     notes: tuple[str, ...] = ()
-    vllm_runtime_dir: Path | None = None
 
 
 def install_command_hint(target: str) -> str:
@@ -55,26 +48,10 @@ def install_command_hint(target: str) -> str:
     return f"Run `churro-ocr install {target}`."
 
 
-def recommended_vllm_runtime_hint() -> str:
-    """Return the short user-facing hint for the dedicated vLLM runtime."""
-    return "Run `churro-ocr install vllm`."
-
-
-def resolve_vllm_runtime_dir(runtime_dir: Path | None = None) -> Path:
-    """Resolve the dedicated vLLM runtime directory."""
-    if runtime_dir is not None:
-        return runtime_dir.expanduser().resolve()
-    override = os.environ.get(VLLM_RUNTIME_DIR_ENV)
-    if override:
-        return Path(override).expanduser().resolve()
-    return DEFAULT_VLLM_RUNTIME_DIR
-
-
 def install_runtime_dependencies(
     *,
     target: str,
     torch_backend: str = "auto",
-    vllm_runtime_dir: Path | None = None,
 ) -> RuntimeInstallResult:
     """Install one of the supported optional runtime targets with UV."""
     normalized_target = target.strip().lower()
@@ -119,77 +96,13 @@ def install_runtime_dependencies(
             )
         )
 
-    resolved_runtime_dir: Path | None = None
-    if normalized_target in {"vllm", "all"}:
-        resolved_runtime_dir = resolve_vllm_runtime_dir(vllm_runtime_dir)
-        runtime_python = _ensure_runtime_python(resolved_runtime_dir)
-        executed_commands.append(
-            _run_command(
-                [
-                    uv_executable,
-                    "pip",
-                    "install",
-                    "--python",
-                    str(runtime_python),
-                    "--upgrade",
-                    f"--torch-backend={torch_backend}",
-                    _requirement_for_extra("vllm", package_name="vllm"),
-                ]
-            )
-        )
-        notes.append(
-            "The dedicated vLLM runtime is ready. Start it with `churro-ocr serve-vllm --model <model-id>`."
-        )
-        notes.append(
-            "Use `--backend openai-compatible --base-url http://127.0.0.1:8000/v1` "
-            "to connect to the served runtime."
-        )
-
     return RuntimeInstallResult(
         target=normalized_target,
         executed_commands=tuple(executed_commands),
         notes=tuple(notes),
-        vllm_runtime_dir=resolved_runtime_dir,
     )
 
 
-def serve_vllm_runtime(
-    *,
-    model: str,
-    host: str = "127.0.0.1",
-    port: int = 8000,
-    runtime_dir: Path | None = None,
-    extra_args: tuple[str, ...] = (),
-) -> int:
-    """Run `python -m vllm serve` from the dedicated Churro vLLM runtime."""
-    resolved_runtime_dir = resolve_vllm_runtime_dir(runtime_dir)
-    runtime_python = _venv_python(resolved_runtime_dir)
-    if not runtime_python.exists():
-        raise ConfigurationError(
-            f"No dedicated vLLM runtime exists at {resolved_runtime_dir}. {recommended_vllm_runtime_hint()}"
-        )
-
-    command = [
-        str(runtime_python),
-        "-m",
-        "vllm",
-        "serve",
-        model,
-        "--host",
-        host,
-        "--port",
-        str(port),
-        *extra_args,
-    ]
-    try:
-        completed = subprocess.run(command, check=False)
-    except OSError as exc:  # pragma: no cover - depends on host process state
-        raise ConfigurationError(
-            f"Failed to launch the dedicated vLLM runtime at {resolved_runtime_dir}: {exc}"
-        ) from exc
-    return int(completed.returncode)
-
-
 def _require_uv_executable() -> str:
     uv_executable = shutil.which("uv")
     if uv_executable is None:
@@ -223,40 +136,6 @@ def _requirements_for_extra(extras: tuple[str, ...]) -> list[str]:
     return selected
 
 
-def _requirement_for_extra(extra: str, *, package_name: str) -> str:
-    normalized_package_name = package_name.replace("_", "-").lower()
-    for requirement in _requirements_for_extra((extra,)):
-        dependency_name = _requirement_name(requirement)
-        if dependency_name.replace("_", "-").lower() == normalized_package_name:
-            return requirement
-    raise ConfigurationError(
-        f"Could not resolve the `{package_name}` dependency from the `{extra}` extra metadata."
-    )
-
-
-def _ensure_runtime_python(runtime_dir: Path) -> Path:
-    runtime_python = _venv_python(runtime_dir)
-    if runtime_python.exists():
-        return runtime_python
-
-    runtime_dir.parent.mkdir(parents=True, exist_ok=True)
-    try:
-        subprocess.run(
-            [sys.executable, "-m", "venv", str(runtime_dir)],
-            check=True,
-        )
-    except (OSError, subprocess.CalledProcessError) as exc:
-        raise ConfigurationError(
-            f"Failed to create the dedicated vLLM runtime at {runtime_dir}: {exc}"
-        ) from exc
-
-    if not runtime_python.exists():
-        raise ConfigurationError(
-            f"Created the dedicated vLLM runtime at {runtime_dir}, but no Python interpreter was found."
-        )
-    return runtime_python
-
-
 def _run_command(command: list[str]) -> tuple[str, ...]:
     try:
         subprocess.run(command, check=True)
@@ -264,21 +143,3 @@ def _run_command(command: list[str]) -> tuple[str, ...]:
         rendered_command = " ".join(command)
         raise ConfigurationError(f"Command failed: {rendered_command}") from exc
     return tuple(command)
-
-
-def _requirement_name(requirement: str) -> str:
-    name_chars: list[str] = []
-    for character in requirement:
-        if character.isalnum() or character in {"-", "_", "."}:
-            name_chars.append(character)
-            continue
-        if character == "[":
-            break
-        break
-    return "".join(name_chars)
-
-
-def _venv_python(venv_dir: Path) -> Path:
-    if sys.platform == "win32":
-        return venv_dir / "Scripts" / "python.exe"
-    return venv_dir / "bin" / "python"
diff --git a/src/churro_ocr/cli.py b/src/churro_ocr/cli.py
index 8c846b3..5c4d41f 100644
--- a/src/churro_ocr/cli.py
+++ b/src/churro_ocr/cli.py
@@ -9,7 +9,6 @@
 from churro_ocr._internal.install import (
     INSTALL_TARGETS,
     install_runtime_dependencies,
-    serve_vllm_runtime,
 )
 from churro_ocr.errors import ConfigurationError
 from churro_ocr.ocr import OCRClient
@@ -236,58 +235,22 @@ def install_command(
         "auto",
         help="PyTorch backend passed through to uv when a local runtime needs torch.",
     ),
-    vllm_runtime_dir: Path | None = typer.Option(
-        None,
-        help="Override the dedicated vLLM runtime directory for `install vllm`.",
-    ),
 ) -> None:
     """Install optional runtime dependencies with uv."""
     try:
         result = install_runtime_dependencies(
             target=target,
             torch_backend=torch_backend,
-            vllm_runtime_dir=vllm_runtime_dir,
         )
     except ConfigurationError as exc:
         typer.echo(str(exc), err=True)
         raise typer.Exit(code=1) from exc
 
     typer.echo(f"Installed runtime target: {result.target}")
-    if result.vllm_runtime_dir is not None:
-        typer.echo(f"Dedicated vLLM runtime: {result.vllm_runtime_dir}")
     for note in result.notes:
         typer.echo(note)
 
 
-@app.command(
-    "serve-vllm",
-    context_settings={"allow_extra_args": True, "ignore_unknown_options": True},
-)
-def serve_vllm_command(
-    ctx: typer.Context,
-    model: str = typer.Option(..., help="Model identifier to serve from the dedicated vLLM runtime."),
-    host: str = typer.Option("127.0.0.1", help="Bind address passed to `vllm serve`."),
-    port: int = typer.Option(8000, help="Port passed to `vllm serve`."),
-    vllm_runtime_dir: Path | None = typer.Option(
-        None,
-        help="Override the dedicated vLLM runtime directory.",
-    ),
-) -> None:
-    """Start the dedicated vLLM runtime managed by `churro-ocr install vllm`."""
-    try:
-        exit_code = serve_vllm_runtime(
-            model=model,
-            host=host,
-            port=port,
-            runtime_dir=vllm_runtime_dir,
-            extra_args=tuple(ctx.args),
-        )
-    except ConfigurationError as exc:
-        typer.echo(str(exc), err=True)
-        raise typer.Exit(code=1) from exc
-    raise typer.Exit(code=exit_code)
-
-
 def main() -> None:
     """Console-script entrypoint."""
     app()
diff --git a/tests/test_cli.py b/tests/test_cli.py
index 0df4647..b26be7e 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -244,16 +244,14 @@ def test_build_ocr_backend_aligns_templates_for_olmocr() -> None:
 def test_install_command_invokes_runtime_installer(
     monkeypatch: pytest.MonkeyPatch,
     cli_runner,
-    tmp_path: Path,
 ) -> None:
     captured: dict[str, object] = {}
 
     def _fake_install_runtime_dependencies(**kwargs: object) -> SimpleNamespace:
         captured.update(kwargs)
         return SimpleNamespace(
-            target="vllm",
+            target="local",
             notes=("runtime ready",),
-            vllm_runtime_dir=tmp_path / "vllm-runtime",
         )
 
     monkeypatch.setattr(
@@ -265,7 +263,7 @@ def _fake_install_runtime_dependencies(**kwargs: object) -> SimpleNamespace:
         app,
         [
             "install",
-            "vllm",
+            "local",
             "--torch-backend",
             "cu126",
         ],
@@ -273,11 +271,10 @@ def _fake_install_runtime_dependencies(**kwargs: object) -> SimpleNamespace:
 
     assert result.exit_code == 0
     assert captured == {
-        "target": "vllm",
+        "target": "local",
         "torch_backend": "cu126",
-        "vllm_runtime_dir": None,
     }
-    assert "Installed runtime target: vllm" in result.output
+    assert "Installed runtime target: local" in result.output
     assert "runtime ready" in result.output
 
 
@@ -299,47 +296,6 @@ def _raise_configuration_error(**_: object) -> SimpleNamespace:
     assert "missing uv" in result.output
 
 
-def test_serve_vllm_command_forwards_extra_args(
-    monkeypatch: pytest.MonkeyPatch,
-    cli_runner,
-    tmp_path: Path,
-) -> None:
-    captured: dict[str, object] = {}
-
-    def _fake_serve_vllm_runtime(**kwargs: object) -> int:
-        captured.update(kwargs)
-        return 0
-
-    monkeypatch.setattr(
-        "churro_ocr.cli.serve_vllm_runtime",
-        _fake_serve_vllm_runtime,
-    )
-
-    result = cli_runner.invoke(
-        app,
-        [
-            "serve-vllm",
-            "--model",
-            "stanford-oval/churro-3B",
-            "--host",
-            "0.0.0.0",
-            "--port",
-            "9000",
-            "--tensor-parallel-size",
-            "2",
-        ],
-    )
-
-    assert result.exit_code == 0
-    assert captured == {
-        "model": "stanford-oval/churro-3B",
-        "host": "0.0.0.0",
-        "port": 9000,
-        "runtime_dir": None,
-        "extra_args": ("--tensor-parallel-size", "2"),
-    }
-
-
 def test_module_entrypoint_help() -> None:
     result = subprocess.run(
         [sys.executable, "-m", "churro_ocr", "--help"],
@@ -352,7 +308,6 @@ def test_module_entrypoint_help() -> None:
     assert "transcribe" in result.stdout
     assert "extract-pages" in result.stdout
     assert "install" in result.stdout
-    assert "serve-vllm" in result.stdout
 
 
 def test_console_script_help() -> None:
@@ -370,4 +325,3 @@ def test_console_script_help() -> None:
     assert "transcribe" in result.stdout
     assert "extract-pages" in result.stdout
     assert "install" in result.stdout
-    assert "serve-vllm" in result.stdout
diff --git a/tests/test_cli_contract.py b/tests/test_cli_contract.py
index f932706..4ff9856 100644
--- a/tests/test_cli_contract.py
+++ b/tests/test_cli_contract.py
@@ -92,7 +92,7 @@ def _fake_build_ocr_backend(spec: cli_module.OCRBackendSpec) -> _FakeBackend:
     assert spec.transport.api_key is None
 
 
-@pytest.mark.parametrize("backend", ["unsupported", "vllm"])
+@pytest.mark.parametrize("backend", ["unsupported"])
 def test_transcribe_cli_rejects_unsupported_backend(
     sample_image_path: Path,
     backend: str,
diff --git a/tests/test_install.py b/tests/test_install.py
index a779656..ab06e95 100644
--- a/tests/test_install.py
+++ b/tests/test_install.py
@@ -1,7 +1,6 @@
 from __future__ import annotations
 
 import sys
-from pathlib import Path
 from types import SimpleNamespace
 
 import pytest
@@ -43,7 +42,6 @@ def test_install_runtime_dependencies_installs_hf_and_torch_with_uv(
     )
 
     assert result.target == "hf"
-    assert result.vllm_runtime_dir is None
     assert commands == [
         [
             "/usr/bin/uv",
@@ -69,48 +67,26 @@ def test_install_runtime_dependencies_installs_hf_and_torch_with_uv(
     ]
 
 
-def test_install_runtime_dependencies_installs_local_client_and_dedicated_vllm_runtime(
+def test_install_runtime_dependencies_installs_local_client_with_uv(
     monkeypatch: pytest.MonkeyPatch,
-    tmp_path: Path,
 ) -> None:
     commands: list[list[str]] = []
-    runtime_dir = tmp_path / "vllm-runtime"
-    runtime_python = runtime_dir / "bin" / "python"
 
     monkeypatch.setattr(
         install_module.metadata,
         "distribution",
-        lambda _: _FakeDistribution(
-            requires=[
-                'litellm[caching]==1.82.3; extra == "local"',
-                'vllm>=0.18,<1; extra == "vllm"',
-            ]
-        ),
+        lambda _: _FakeDistribution(requires=['litellm[caching]==1.82.3; extra == "local"']),
     )
     monkeypatch.setattr(install_module.shutil, "which", lambda name: "/usr/bin/uv" if name == "uv" else None)
-
-    def _fake_ensure_runtime_python(path: Path) -> Path:
-        assert path == runtime_dir.resolve()
-        return runtime_python
-
-    monkeypatch.setattr(
-        install_module,
-        "_ensure_runtime_python",
-        _fake_ensure_runtime_python,
-    )
     monkeypatch.setattr(
         install_module.subprocess,
         "run",
         lambda command, check=True: commands.append(list(command)) or SimpleNamespace(returncode=0),
     )
 
-    result = install_module.install_runtime_dependencies(
-        target="vllm",
-        vllm_runtime_dir=runtime_dir,
-    )
+    result = install_module.install_runtime_dependencies(target="local")
 
-    assert result.target == "vllm"
-    assert result.vllm_runtime_dir == runtime_dir.resolve()
+    assert result.target == "local"
     assert commands == [
         [
             "/usr/bin/uv",
@@ -120,19 +96,9 @@ def _fake_ensure_runtime_python(path: Path) -> Path:
             sys.executable,
             "--upgrade",
             "litellm[caching]==1.82.3",
-        ],
-        [
-            "/usr/bin/uv",
-            "pip",
-            "install",
-            "--python",
-            str(runtime_python),
-            "--upgrade",
-            "--torch-backend=auto",
-            "vllm>=0.18,<1",
-        ],
+        ]
     ]
-    assert result.notes
+    assert result.notes == ()
 
 
 def test_install_runtime_dependencies_requires_uv(monkeypatch: pytest.MonkeyPatch) -> None:
@@ -140,75 +106,3 @@ def test_install_runtime_dependencies_requires_uv(monkeypatch: pytest.MonkeyPatc
 
     with pytest.raises(ConfigurationError, match="requires `uv` on PATH"):
         install_module.install_runtime_dependencies(target="hf")
-
-
-def test_resolve_vllm_runtime_dir_prefers_explicit_path(
-    monkeypatch: pytest.MonkeyPatch,
-    tmp_path: Path,
-) -> None:
-    monkeypatch.setenv(install_module.VLLM_RUNTIME_DIR_ENV, str(tmp_path / "from-env"))
-
-    resolved = install_module.resolve_vllm_runtime_dir(tmp_path / "from-arg")
-
-    assert resolved == (tmp_path / "from-arg").resolve()
-
-
-def test_resolve_vllm_runtime_dir_uses_environment_override(
-    monkeypatch: pytest.MonkeyPatch,
-    tmp_path: Path,
-) -> None:
-    monkeypatch.setenv(install_module.VLLM_RUNTIME_DIR_ENV, str(tmp_path / "from-env"))
-
-    resolved = install_module.resolve_vllm_runtime_dir()
-
-    assert resolved == (tmp_path / "from-env").resolve()
-
-
-def test_serve_vllm_runtime_runs_module_from_dedicated_env(
-    monkeypatch: pytest.MonkeyPatch,
-    tmp_path: Path,
-) -> None:
-    runtime_dir = tmp_path / "runtime"
-    runtime_python = runtime_dir / "bin" / "python"
-    runtime_python.parent.mkdir(parents=True, exist_ok=True)
-    runtime_python.write_text("")
-
-    commands: list[list[str]] = []
-    monkeypatch.setattr(
-        install_module.subprocess,
-        "run",
-        lambda command, check=False: commands.append(list(command)) or SimpleNamespace(returncode=0),
-    )
-
-    exit_code = install_module.serve_vllm_runtime(
-        model="stanford-oval/churro-3B",
-        host="0.0.0.0",
-        port=9000,
-        runtime_dir=runtime_dir,
-        extra_args=("--tensor-parallel-size", "2"),
-    )
-
-    assert exit_code == 0
-    assert commands == [
-        [
-            str(runtime_python),
-            "-m",
-            "vllm",
-            "serve",
-            "stanford-oval/churro-3B",
-            "--host",
-            "0.0.0.0",
-            "--port",
-            "9000",
-            "--tensor-parallel-size",
-            "2",
-        ]
-    ]
-
-
-def test_serve_vllm_runtime_requires_installed_runtime(tmp_path: Path) -> None:
-    with pytest.raises(ConfigurationError, match="install vllm"):
-        install_module.serve_vllm_runtime(
-            model="stanford-oval/churro-3B",
-            runtime_dir=tmp_path / "missing-runtime",
-        )
diff --git a/tests/test_package_check.py b/tests/test_package_check.py
index e208efe..84ef26f 100644
--- a/tests/test_package_check.py
+++ b/tests/test_package_check.py
@@ -32,7 +32,7 @@ def _always_missing(_: str):
 
     monkeypatch.setattr(package_check.metadata, "distribution", _always_missing)
 
-    package_check._audit_dependency_licenses(_metadata_message('vllm<1,>=0.18; extra == "vllm"'))
+    package_check._audit_dependency_licenses(_metadata_message('mistralai<2,>=1.6.0; extra == "mistral"'))
 
 
 def test_license_audit_fails_for_missing_base_dependency(monkeypatch: pytest.MonkeyPatch) -> None:
@@ -51,12 +51,5 @@ def test_local_runtime_packaging_policy_rejects_direct_torch_runtime_pin() -> No
         'torchvision; extra == "all"',
     )
 
-    with pytest.raises(RuntimeError, match="must not pin a local PyTorch or vLLM runtime"):
-        package_check._assert_local_runtime_packaging_policy(metadata_message)
-
-
-def test_local_runtime_packaging_policy_rejects_vllm_in_all_extra() -> None:
-    metadata_message = _metadata_message('vllm<1,>=0.18; extra == "all"')
-
-    with pytest.raises(RuntimeError, match="must not pin a local PyTorch or vLLM runtime"):
+    with pytest.raises(RuntimeError, match="must not pin local PyTorch"):
         package_check._assert_local_runtime_packaging_policy(metadata_message)
diff --git a/tests/test_tooling_benchmark.py b/tests/test_tooling_benchmark.py
index 04f1825..48c733e 100644
--- a/tests/test_tooling_benchmark.py
+++ b/tests/test_tooling_benchmark.py
@@ -145,12 +145,12 @@ def test_parse_args_accepts_subset_filters() -> None:
     assert options.document_type == "print"
 
 
-def test_parse_args_rejects_removed_vllm_backend() -> None:
+def test_parse_args_rejects_unsupported_backend() -> None:
     with pytest.raises(SystemExit):
         benchmark.parse_args(
             [
                 "--backend",
-                "vllm",
+                "unsupported",
                 "--dataset-split",
                 "dev",
                 "--model",

From be5249ce01243dfbcdb224960b9ee6b129d5b545 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Mon, 6 Apr 2026 00:22:54 +0000
Subject: [PATCH 08/28] build(hf): support transformers 5.x

Update the published HF dependency range to `transformers>=5,<6`
and refresh the lockfile accordingly.

Add and align test coverage for the Transformers v5 chat-template
contract and package metadata expectations.
---
 pixi.lock                      | 571 ++++++++++-----------------------
 pyproject.toml                 |   4 +-
 tests/test_install.py          |   4 +-
 tests/test_internal_helpers.py |  39 +++
 tests/test_package_check.py    |   2 +-
 5 files changed, 218 insertions(+), 402 deletions(-)

diff --git a/pixi.lock b/pixi.lock
index f4542de..1b12f56 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -103,7 +103,7 @@ environments:
       - pypi: https://files.pythonhosted.org/packages/df/9a/a24b26dc8a65f0ecc0fe5be981a19e61e7ca963b85e062c083f3a9100529/hf_xet-1.4.3-cp37-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
       - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl
-      - pypi: https://files.pythonhosted.org/packages/a8/af/48ac8483240de756d2438c380746e7130d1c6f75802ef22f3c6d49982787/huggingface_hub-0.36.2-py3-none-any.whl
+      - pypi: https://files.pythonhosted.org/packages/73/37/0d15d16150e1829f3e90962c99f28257f6de9e526a680b4c6f5acdb54fd2/huggingface_hub-1.9.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/42/77/de194443bf38daed9452139e960c632b0ef9f9a5dd9ce605fdf18ca9f1b1/id-1.6.1-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/46/33/92ef41c6fad0233e41d3d84ba8e8ad18d1780f1e5d99b3c683e6d7f98b63/identify-2.6.18-py2.py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl
@@ -204,7 +204,7 @@ environments:
       - pypi: https://files.pythonhosted.org/packages/f5/de/9341a6d7a8f1b448573bbf3425fa57669ac58258a667eb48a25dfe916d70/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_x86_64.whl
       - pypi: https://files.pythonhosted.org/packages/2e/76/932be4b50ef6ccedf9d3c6639b056a967a86258c6d9200643f01269211ca/tokenizers-0.22.2-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
       - pypi: https://files.pythonhosted.org/packages/16/e1/3079a9ff9b8e11b846c6ac5c8b5bfb7ff225eee721825310c91b3b50304f/tqdm-4.67.3-py3-none-any.whl
-      - pypi: https://files.pythonhosted.org/packages/03/b8/e484ef633af3887baeeb4b6ad12743363af7cce68ae51e938e00aaa0529d/transformers-4.57.6-py3-none-any.whl
+      - pypi: https://files.pythonhosted.org/packages/e7/28/35f7411ff80a3640c1f4fc907dcbb6a65061ebb82f66950e38bfc9f7f740/transformers-5.5.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/3a/7a/882d99539b19b1490cac5d77c67338d126e4122c8276bf640e411650c830/twine-6.2.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/89/29/8ac0281fc44c3297f0e58699ebf993c13621e32a0fab1025439d3ea8a2f1/ty-0.0.28-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
       - pypi: https://files.pythonhosted.org/packages/4a/91/48db081e7a63bb37284f9fbcefda7c44c277b18b0e13fbc36ea2335b71e6/typer-0.24.1-py3-none-any.whl
@@ -296,7 +296,7 @@ environments:
       - pypi: https://files.pythonhosted.org/packages/df/9a/a24b26dc8a65f0ecc0fe5be981a19e61e7ca963b85e062c083f3a9100529/hf_xet-1.4.3-cp37-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
       - pypi: https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/2a/39/e50c7c3a983047577ee07d2a9e53faf5a69493943ec3f6a384bdc792deb2/httpx-0.28.1-py3-none-any.whl
-      - pypi: https://files.pythonhosted.org/packages/a8/af/48ac8483240de756d2438c380746e7130d1c6f75802ef22f3c6d49982787/huggingface_hub-0.36.2-py3-none-any.whl
+      - pypi: https://files.pythonhosted.org/packages/73/37/0d15d16150e1829f3e90962c99f28257f6de9e526a680b4c6f5acdb54fd2/huggingface_hub-1.9.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/42/77/de194443bf38daed9452139e960c632b0ef9f9a5dd9ce605fdf18ca9f1b1/id-1.6.1-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/46/33/92ef41c6fad0233e41d3d84ba8e8ad18d1780f1e5d99b3c683e6d7f98b63/identify-2.6.18-py2.py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl
@@ -397,7 +397,7 @@ environments:
       - pypi: https://files.pythonhosted.org/packages/f5/de/9341a6d7a8f1b448573bbf3425fa57669ac58258a667eb48a25dfe916d70/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_x86_64.whl
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-  - av ; extra == 'video'
+  - rich ; extra == 'serving'
+  - torch>=2.4 ; extra == 'serving'
+  - accelerate>=1.1.0 ; extra == 'serving'
   - num2words ; extra == 'num2words'
-  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'sentencepiece'
-  - protobuf ; extra == 'sentencepiece'
-  - tiktoken ; extra == 'tiktoken'
-  - blobfile ; extra == 'tiktoken'
-  - mistral-common[opencv]>=1.6.3 ; extra == 'mistral-common'
-  - jinja2>=3.1.0 ; extra == 'chat-template'
-  - pytest>=7.2.0 ; extra == 'testing'
-  - pytest-asyncio ; extra == 'testing'
+  - optimum-benchmark>=0.3.0 ; extra == 'benchmark'
+  - fugashi>=1.0 ; extra == 'ja'
+  - ipadic>=1.0.0,<2.0 ; extra == 'ja'
+  - unidic-lite>=1.0.7 ; extra == 'ja'
+  - unidic>=1.0.2 ; extra == 'ja'
+  - rhoknp>=1.1.0,<1.3.1 ; extra == 'ja'
+  - sudachipy>=0.6.6 ; extra == 'ja'
+  - sudachidict-core>=20220729 ; extra == 'ja'
+  - opentelemetry-api ; extra == 'open-telemetry'
+  - opentelemetry-exporter-otlp ; extra == 'open-telemetry'
+  - opentelemetry-sdk ; extra == 'open-telemetry'
+  - pytest>=7.2.0,<9.0.0 ; extra == 'testing'
+  - pytest-asyncio>=1.2.0 ; extra == 'testing'
+  - pytest-random-order ; extra == 'testing'
   - pytest-rich ; extra == 'testing'
   - pytest-xdist ; extra == 'testing'
   - pytest-order ; extra == 'testing'
   - pytest-rerunfailures<16.0 ; extra == 'testing'
+  - pytest-timeout ; extra == 'testing'
+  - pytest-env ; extra == 'testing'
   - timeout-decorator ; extra == 'testing'
   - parameterized>=0.9 ; extra == 'testing'
   - psutil ; extra == 'testing'
-  - datasets>=2.15.0 ; extra == 'testing'
   - dill<0.3.5 ; extra == 'testing'
-  - evaluate>=0.2.0 ; extra == 'testing'
-  - pytest-timeout ; extra == 'testing'
-  - ruff==0.13.1 ; extra == 'testing'
+  - evaluate>=0.4.6 ; extra == 'testing'
   - rouge-score!=0.0.7,!=0.0.8,!=0.1,!=0.1.1 ; extra == 'testing'
   - nltk<=3.8.1 ; extra == 'testing'
-  - gitpython<3.1.19 ; extra == 'testing'
   - sacremoses ; extra == 'testing'
   - rjieba ; extra == 'testing'
   - beautifulsoup4 ; extra == 'testing'
   - tensorboard ; extra == 'testing'
-  - pydantic>=2 ; extra == 'testing'
-  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'testing'
   - sacrebleu>=1.4.12,<2.0.0 ; extra == 'testing'
+  - filelock ; extra == 'testing'
+  - hf-doc-builder ; extra == 'testing'
+  - datasets>=2.15.0 ; extra == 'testing'
+  - ruff==0.14.10 ; extra == 'testing'
+  - gitpython<3.1.19 ; extra == 'testing'
+  - urllib3<2.0.0 ; extra == 'testing'
   - libcst ; extra == 'testing'
+  - rich ; extra == 'testing'
+  - ty==0.0.20 ; extra == 'testing'
+  - tomli ; extra == 'testing'
   - faiss-cpu ; extra == 'testing'
   - datasets>=2.15.0 ; extra == 'testing'
-  - cookiecutter==1.7.3 ; extra == 'testing'
-  - mistral-common[opencv]>=1.6.3 ; extra == 'testing'
+  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'testing'
+  - protobuf ; extra == 'testing'
   - openai>=1.98.0 ; extra == 'testing'
   - pydantic>=2 ; extra == 'testing'
   - uvicorn ; extra == 'testing'
   - fastapi ; extra == 'testing'
   - starlette ; extra == 'testing'
-  - torch>=2.2 ; extra == 'testing'
-  - accelerate>=0.26.0 ; extra == 'testing'
+  - rich ; extra == 'testing'
+  - torch>=2.4 ; extra == 'testing'
+  - accelerate>=1.1.0 ; extra == 'testing'
+  - mistral-common[image]>=1.10.0 ; extra == 'testing'
   - deepspeed>=0.9.3 ; extra == 'deepspeed-testing'
-  - accelerate>=0.26.0 ; extra == 'deepspeed-testing'
-  - pytest>=7.2.0 ; extra == 'deepspeed-testing'
-  - pytest-asyncio ; extra == 'deepspeed-testing'
+  - accelerate>=1.1.0 ; extra == 'deepspeed-testing'
+  - pytest>=7.2.0,<9.0.0 ; extra == 'deepspeed-testing'
+  - pytest-asyncio>=1.2.0 ; extra == 'deepspeed-testing'
+  - pytest-random-order ; extra == 'deepspeed-testing'
   - pytest-rich ; extra == 'deepspeed-testing'
   - pytest-xdist ; extra == 'deepspeed-testing'
   - pytest-order ; extra == 'deepspeed-testing'
   - pytest-rerunfailures<16.0 ; extra == 'deepspeed-testing'
+  - pytest-timeout ; extra == 'deepspeed-testing'
+  - pytest-env ; extra == 'deepspeed-testing'
   - timeout-decorator ; extra == 'deepspeed-testing'
   - parameterized>=0.9 ; extra == 'deepspeed-testing'
   - psutil ; extra == 'deepspeed-testing'
-  - datasets>=2.15.0 ; extra == 'deepspeed-testing'
   - dill<0.3.5 ; extra == 'deepspeed-testing'
-  - evaluate>=0.2.0 ; extra == 'deepspeed-testing'
-  - pytest-timeout ; extra == 'deepspeed-testing'
-  - ruff==0.13.1 ; extra == 'deepspeed-testing'
+  - evaluate>=0.4.6 ; extra == 'deepspeed-testing'
   - rouge-score!=0.0.7,!=0.0.8,!=0.1,!=0.1.1 ; extra == 'deepspeed-testing'
   - nltk<=3.8.1 ; extra == 'deepspeed-testing'
-  - gitpython<3.1.19 ; extra == 'deepspeed-testing'
   - sacremoses ; extra == 'deepspeed-testing'
   - rjieba ; extra == 'deepspeed-testing'
   - beautifulsoup4 ; extra == 'deepspeed-testing'
   - tensorboard ; extra == 'deepspeed-testing'
-  - pydantic>=2 ; extra == 'deepspeed-testing'
-  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'deepspeed-testing'
   - sacrebleu>=1.4.12,<2.0.0 ; extra == 'deepspeed-testing'
+  - filelock ; extra == 'deepspeed-testing'
+  - hf-doc-builder ; extra == 'deepspeed-testing'
+  - datasets>=2.15.0 ; extra == 'deepspeed-testing'
+  - ruff==0.14.10 ; extra == 'deepspeed-testing'
+  - gitpython<3.1.19 ; extra == 'deepspeed-testing'
+  - urllib3<2.0.0 ; extra == 'deepspeed-testing'
   - libcst ; extra == 'deepspeed-testing'
+  - rich ; extra == 'deepspeed-testing'
+  - ty==0.0.20 ; extra == 'deepspeed-testing'
+  - tomli ; extra == 'deepspeed-testing'
   - faiss-cpu ; extra == 'deepspeed-testing'
   - datasets>=2.15.0 ; extra == 'deepspeed-testing'
-  - cookiecutter==1.7.3 ; extra == 'deepspeed-testing'
-  - mistral-common[opencv]>=1.6.3 ; extra == 'deepspeed-testing'
+  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'deepspeed-testing'
+  - protobuf ; extra == 'deepspeed-testing'
   - openai>=1.98.0 ; extra == 'deepspeed-testing'
   - pydantic>=2 ; extra == 'deepspeed-testing'
   - uvicorn ; extra == 'deepspeed-testing'
   - fastapi ; extra == 'deepspeed-testing'
   - starlette ; extra == 'deepspeed-testing'
-  - torch>=2.2 ; extra == 'deepspeed-testing'
-  - accelerate>=0.26.0 ; extra == 'deepspeed-testing'
+  - rich ; extra == 'deepspeed-testing'
+  - torch>=2.4 ; extra == 'deepspeed-testing'
+  - accelerate>=1.1.0 ; extra == 'deepspeed-testing'
+  - mistral-common[image]>=1.10.0 ; extra == 'deepspeed-testing'
   - optuna ; extra == 'deepspeed-testing'
   - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'deepspeed-testing'
   - protobuf ; extra == 'deepspeed-testing'
-  - ruff==0.13.1 ; extra == 'ruff'
-  - datasets>=2.15.0 ; extra == 'quality'
-  - ruff==0.13.1 ; extra == 'quality'
-  - gitpython<3.1.19 ; extra == 'quality'
-  - urllib3<2.0.0 ; extra == 'quality'
-  - libcst ; extra == 'quality'
-  - rich ; extra == 'quality'
-  - pandas<2.3.0 ; extra == 'quality'
-  - tensorflow>2.9,<2.16 ; extra == 'all'
-  - onnxconverter-common ; extra == 'all'
-  - tf2onnx ; extra == 'all'
-  - tensorflow-text<2.16 ; extra == 'all'
-  - keras-nlp>=0.3.1,<0.14.0 ; extra == 'all'
-  - torch>=2.2 ; extra == 'all'
-  - accelerate>=0.26.0 ; extra == 'all'
-  - jax>=0.4.1,<=0.4.13 ; extra == 'all'
-  - jaxlib>=0.4.1,<=0.4.13 ; extra == 'all'
-  - flax>=0.4.1,<=0.7.0 ; extra == 'all'
-  - optax>=0.0.8,<=0.1.4 ; extra == 'all'
-  - scipy<1.13.0 ; extra == 'all'
-  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'all'
-  - protobuf ; extra == 'all'
-  - tokenizers>=0.22.0,<=0.23.0 ; extra == 'all'
+  - torch>=2.4 ; extra == 'all'
+  - accelerate>=1.1.0 ; extra == 'all'
+  - torchvision ; extra == 'all'
+  - pillow>=10.0.1,<=15.0 ; extra == 'all'
   - torchaudio ; extra == 'all'
   - librosa ; extra == 'all'
   - pyctcdecode>=0.4.0 ; extra == 'all'
   - phonemizer ; extra == 'all'
-  - kenlm ; extra == 'all'
-  - pillow>=10.0.1,<=15.0 ; extra == 'all'
-  - kernels>=0.6.1,<=0.9 ; extra == 'all'
-  - optuna ; extra == 'all'
-  - ray[tune]>=2.7.0 ; extra == 'all'
-  - timm!=1.0.18,<=1.0.19 ; extra == 'all'
-  - torchvision ; extra == 'all'
-  - pillow>=10.0.1,<=15.0 ; extra == 'all'
-  - codecarbon>=2.8.1 ; extra == 'all'
-  - accelerate>=0.26.0 ; extra == 'all'
   - av ; extra == 'all'
-  - num2words ; extra == 'all'
-  - mistral-common[opencv]>=1.6.3 ; extra == 'all'
+  - kernels>=0.12.0,<0.13 ; extra == 'all'
+  - timm>=1.0.23 ; extra == 'all'
+  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'all'
+  - protobuf ; extra == 'all'
+  - tiktoken ; extra == 'all'
+  - blobfile ; extra == 'all'
   - jinja2>=3.1.0 ; extra == 'all'
-  - pytest>=7.2.0 ; extra == 'dev-torch'
-  - pytest-asyncio ; extra == 'dev-torch'
-  - pytest-rich ; extra == 'dev-torch'
-  - pytest-xdist ; extra == 'dev-torch'
-  - pytest-order ; extra == 'dev-torch'
-  - pytest-rerunfailures<16.0 ; extra == 'dev-torch'
-  - timeout-decorator ; extra == 'dev-torch'
-  - parameterized>=0.9 ; extra == 'dev-torch'
-  - psutil ; extra == 'dev-torch'
-  - datasets>=2.15.0 ; extra == 'dev-torch'
-  - dill<0.3.5 ; extra == 'dev-torch'
-  - evaluate>=0.2.0 ; extra == 'dev-torch'
-  - pytest-timeout ; extra == 'dev-torch'
-  - ruff==0.13.1 ; extra == 'dev-torch'
-  - rouge-score!=0.0.7,!=0.0.8,!=0.1,!=0.1.1 ; extra == 'dev-torch'
-  - nltk<=3.8.1 ; extra == 'dev-torch'
-  - gitpython<3.1.19 ; extra == 'dev-torch'
-  - sacremoses ; extra == 'dev-torch'
-  - rjieba ; extra == 'dev-torch'
-  - beautifulsoup4 ; extra == 'dev-torch'
-  - tensorboard ; extra == 'dev-torch'
-  - pydantic>=2 ; extra == 'dev-torch'
-  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'dev-torch'
-  - sacrebleu>=1.4.12,<2.0.0 ; extra == 'dev-torch'
-  - libcst ; extra == 'dev-torch'
-  - faiss-cpu ; extra == 'dev-torch'
-  - datasets>=2.15.0 ; extra == 'dev-torch'
-  - cookiecutter==1.7.3 ; extra == 'dev-torch'
-  - mistral-common[opencv]>=1.6.3 ; extra == 'dev-torch'
-  - openai>=1.98.0 ; extra == 'dev-torch'
-  - pydantic>=2 ; extra == 'dev-torch'
-  - uvicorn ; extra == 'dev-torch'
-  - fastapi ; extra == 'dev-torch'
-  - starlette ; extra == 'dev-torch'
-  - torch>=2.2 ; extra == 'dev-torch'
-  - accelerate>=0.26.0 ; extra == 'dev-torch'
-  - torch>=2.2 ; extra == 'dev-torch'
-  - accelerate>=0.26.0 ; extra == 'dev-torch'
-  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'dev-torch'
-  - protobuf ; extra == 'dev-torch'
-  - tokenizers>=0.22.0,<=0.23.0 ; extra == 'dev-torch'
-  - torchaudio ; extra == 'dev-torch'
-  - librosa ; extra == 'dev-torch'
-  - pyctcdecode>=0.4.0 ; extra == 'dev-torch'
-  - phonemizer ; extra == 'dev-torch'
-  - kenlm ; extra == 'dev-torch'
-  - pillow>=10.0.1,<=15.0 ; extra == 'dev-torch'
-  - kernels>=0.6.1,<=0.9 ; extra == 'dev-torch'
-  - optuna ; extra == 'dev-torch'
-  - ray[tune]>=2.7.0 ; extra == 'dev-torch'
-  - timm!=1.0.18,<=1.0.19 ; extra == 'dev-torch'
-  - torchvision ; extra == 'dev-torch'
-  - pillow>=10.0.1,<=15.0 ; extra == 'dev-torch'
-  - codecarbon>=2.8.1 ; extra == 'dev-torch'
-  - datasets>=2.15.0 ; extra == 'dev-torch'
-  - ruff==0.13.1 ; extra == 'dev-torch'
-  - gitpython<3.1.19 ; extra == 'dev-torch'
-  - urllib3<2.0.0 ; extra == 'dev-torch'
-  - libcst ; extra == 'dev-torch'
-  - rich ; extra == 'dev-torch'
-  - pandas<2.3.0 ; extra == 'dev-torch'
-  - fugashi>=1.0 ; extra == 'dev-torch'
-  - ipadic>=1.0.0,<2.0 ; extra == 'dev-torch'
-  - unidic-lite>=1.0.7 ; extra == 'dev-torch'
-  - unidic>=1.0.2 ; extra == 'dev-torch'
-  - sudachipy>=0.6.6 ; extra == 'dev-torch'
-  - sudachidict-core>=20220729 ; extra == 'dev-torch'
-  - rhoknp>=1.1.0,<1.3.1 ; extra == 'dev-torch'
-  - scikit-learn ; extra == 'dev-torch'
-  - cookiecutter==1.7.3 ; extra == 'dev-torch'
-  - onnxruntime>=1.4.0 ; extra == 'dev-torch'
-  - onnxruntime-tools>=1.4.2 ; extra == 'dev-torch'
-  - num2words ; extra == 'dev-torch'
-  - pytest>=7.2.0 ; extra == 'dev-tensorflow'
-  - pytest-asyncio ; extra == 'dev-tensorflow'
-  - pytest-rich ; extra == 'dev-tensorflow'
-  - pytest-xdist ; extra == 'dev-tensorflow'
-  - pytest-order ; extra == 'dev-tensorflow'
-  - pytest-rerunfailures<16.0 ; extra == 'dev-tensorflow'
-  - timeout-decorator ; extra == 'dev-tensorflow'
-  - parameterized>=0.9 ; extra == 'dev-tensorflow'
-  - psutil ; extra == 'dev-tensorflow'
-  - datasets>=2.15.0 ; extra == 'dev-tensorflow'
-  - dill<0.3.5 ; extra == 'dev-tensorflow'
-  - evaluate>=0.2.0 ; extra == 'dev-tensorflow'
-  - pytest-timeout ; extra == 'dev-tensorflow'
-  - ruff==0.13.1 ; extra == 'dev-tensorflow'
-  - rouge-score!=0.0.7,!=0.0.8,!=0.1,!=0.1.1 ; extra == 'dev-tensorflow'
-  - nltk<=3.8.1 ; extra == 'dev-tensorflow'
-  - gitpython<3.1.19 ; extra == 'dev-tensorflow'
-  - sacremoses ; extra == 'dev-tensorflow'
-  - rjieba ; extra == 'dev-tensorflow'
-  - beautifulsoup4 ; extra == 'dev-tensorflow'
-  - tensorboard ; extra == 'dev-tensorflow'
-  - pydantic>=2 ; extra == 'dev-tensorflow'
-  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'dev-tensorflow'
-  - sacrebleu>=1.4.12,<2.0.0 ; extra == 'dev-tensorflow'
-  - libcst ; extra == 'dev-tensorflow'
-  - faiss-cpu ; extra == 'dev-tensorflow'
-  - datasets>=2.15.0 ; extra == 'dev-tensorflow'
-  - cookiecutter==1.7.3 ; extra == 'dev-tensorflow'
-  - mistral-common[opencv]>=1.6.3 ; extra == 'dev-tensorflow'
-  - openai>=1.98.0 ; extra == 'dev-tensorflow'
-  - pydantic>=2 ; extra == 'dev-tensorflow'
-  - uvicorn ; extra == 'dev-tensorflow'
-  - fastapi ; extra == 'dev-tensorflow'
-  - starlette ; extra == 'dev-tensorflow'
-  - torch>=2.2 ; extra == 'dev-tensorflow'
-  - accelerate>=0.26.0 ; extra == 'dev-tensorflow'
-  - tensorflow>2.9,<2.16 ; extra == 'dev-tensorflow'
-  - onnxconverter-common ; extra == 'dev-tensorflow'
-  - tf2onnx ; extra == 'dev-tensorflow'
-  - tensorflow-text<2.16 ; extra == 'dev-tensorflow'
-  - keras-nlp>=0.3.1,<0.14.0 ; extra == 'dev-tensorflow'
-  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'dev-tensorflow'
-  - protobuf ; extra == 'dev-tensorflow'
-  - tokenizers>=0.22.0,<=0.23.0 ; extra == 'dev-tensorflow'
-  - pillow>=10.0.1,<=15.0 ; extra == 'dev-tensorflow'
-  - datasets>=2.15.0 ; extra == 'dev-tensorflow'
-  - ruff==0.13.1 ; extra == 'dev-tensorflow'
-  - gitpython<3.1.19 ; extra == 'dev-tensorflow'
-  - urllib3<2.0.0 ; extra == 'dev-tensorflow'
-  - libcst ; extra == 'dev-tensorflow'
-  - rich ; extra == 'dev-tensorflow'
-  - pandas<2.3.0 ; extra == 'dev-tensorflow'
-  - scikit-learn ; extra == 'dev-tensorflow'
-  - cookiecutter==1.7.3 ; extra == 'dev-tensorflow'
-  - onnxconverter-common ; extra == 'dev-tensorflow'
-  - tf2onnx ; extra == 'dev-tensorflow'
-  - onnxruntime>=1.4.0 ; extra == 'dev-tensorflow'
-  - onnxruntime-tools>=1.4.2 ; extra == 'dev-tensorflow'
-  - librosa ; extra == 'dev-tensorflow'
-  - pyctcdecode>=0.4.0 ; extra == 'dev-tensorflow'
-  - phonemizer ; extra == 'dev-tensorflow'
-  - kenlm ; extra == 'dev-tensorflow'
-  - tensorflow>2.9,<2.16 ; extra == 'dev'
-  - onnxconverter-common ; extra == 'dev'
-  - tf2onnx ; extra == 'dev'
-  - tensorflow-text<2.16 ; extra == 'dev'
-  - keras-nlp>=0.3.1,<0.14.0 ; extra == 'dev'
-  - torch>=2.2 ; extra == 'dev'
-  - accelerate>=0.26.0 ; extra == 'dev'
-  - jax>=0.4.1,<=0.4.13 ; extra == 'dev'
-  - jaxlib>=0.4.1,<=0.4.13 ; extra == 'dev'
-  - flax>=0.4.1,<=0.7.0 ; extra == 'dev'
-  - optax>=0.0.8,<=0.1.4 ; extra == 'dev'
-  - scipy<1.13.0 ; extra == 'dev'
-  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'dev'
-  - protobuf ; extra == 'dev'
-  - tokenizers>=0.22.0,<=0.23.0 ; extra == 'dev'
+  - jmespath>=1.0.1 ; extra == 'all'
+  - num2words ; extra == 'all'
+  - mistral-common[image]>=1.10.0 ; extra == 'all'
+  - torch>=2.4 ; extra == 'dev'
+  - accelerate>=1.1.0 ; extra == 'dev'
+  - torchvision ; extra == 'dev'
+  - pillow>=10.0.1,<=15.0 ; extra == 'dev'
   - torchaudio ; extra == 'dev'
   - librosa ; extra == 'dev'
   - pyctcdecode>=0.4.0 ; extra == 'dev'
   - phonemizer ; extra == 'dev'
-  - kenlm ; extra == 'dev'
-  - pillow>=10.0.1,<=15.0 ; extra == 'dev'
-  - kernels>=0.6.1,<=0.9 ; extra == 'dev'
-  - optuna ; extra == 'dev'
-  - ray[tune]>=2.7.0 ; extra == 'dev'
-  - timm!=1.0.18,<=1.0.19 ; extra == 'dev'
-  - torchvision ; extra == 'dev'
-  - pillow>=10.0.1,<=15.0 ; extra == 'dev'
-  - codecarbon>=2.8.1 ; extra == 'dev'
-  - accelerate>=0.26.0 ; extra == 'dev'
   - av ; extra == 'dev'
-  - num2words ; extra == 'dev'
-  - mistral-common[opencv]>=1.6.3 ; extra == 'dev'
+  - kernels>=0.12.0,<0.13 ; extra == 'dev'
+  - timm>=1.0.23 ; extra == 'dev'
+  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'dev'
+  - protobuf ; extra == 'dev'
+  - tiktoken ; extra == 'dev'
+  - blobfile ; extra == 'dev'
   - jinja2>=3.1.0 ; extra == 'dev'
-  - pytest>=7.2.0 ; extra == 'dev'
-  - pytest-asyncio ; extra == 'dev'
+  - jmespath>=1.0.1 ; extra == 'dev'
+  - num2words ; extra == 'dev'
+  - mistral-common[image]>=1.10.0 ; extra == 'dev'
+  - pytest>=7.2.0,<9.0.0 ; extra == 'dev'
+  - pytest-asyncio>=1.2.0 ; extra == 'dev'
+  - pytest-random-order ; extra == 'dev'
   - pytest-rich ; extra == 'dev'
   - pytest-xdist ; extra == 'dev'
   - pytest-order ; extra == 'dev'
   - pytest-rerunfailures<16.0 ; extra == 'dev'
+  - pytest-timeout ; extra == 'dev'
+  - pytest-env ; extra == 'dev'
   - timeout-decorator ; extra == 'dev'
   - parameterized>=0.9 ; extra == 'dev'
   - psutil ; extra == 'dev'
-  - datasets>=2.15.0 ; extra == 'dev'
   - dill<0.3.5 ; extra == 'dev'
-  - evaluate>=0.2.0 ; extra == 'dev'
-  - pytest-timeout ; extra == 'dev'
-  - ruff==0.13.1 ; extra == 'dev'
+  - evaluate>=0.4.6 ; extra == 'dev'
   - rouge-score!=0.0.7,!=0.0.8,!=0.1,!=0.1.1 ; extra == 'dev'
   - nltk<=3.8.1 ; extra == 'dev'
-  - gitpython<3.1.19 ; extra == 'dev'
   - sacremoses ; extra == 'dev'
   - rjieba ; extra == 'dev'
   - beautifulsoup4 ; extra == 'dev'
   - tensorboard ; extra == 'dev'
-  - pydantic>=2 ; extra == 'dev'
-  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'dev'
   - sacrebleu>=1.4.12,<2.0.0 ; extra == 'dev'
+  - filelock ; extra == 'dev'
+  - hf-doc-builder ; extra == 'dev'
+  - datasets>=2.15.0 ; extra == 'dev'
+  - ruff==0.14.10 ; extra == 'dev'
+  - gitpython<3.1.19 ; extra == 'dev'
+  - urllib3<2.0.0 ; extra == 'dev'
   - libcst ; extra == 'dev'
+  - rich ; extra == 'dev'
+  - ty==0.0.20 ; extra == 'dev'
+  - tomli ; extra == 'dev'
   - faiss-cpu ; extra == 'dev'
   - datasets>=2.15.0 ; extra == 'dev'
-  - cookiecutter==1.7.3 ; extra == 'dev'
-  - mistral-common[opencv]>=1.6.3 ; extra == 'dev'
+  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'dev'
+  - protobuf ; extra == 'dev'
   - openai>=1.98.0 ; extra == 'dev'
   - pydantic>=2 ; extra == 'dev'
   - uvicorn ; extra == 'dev'
   - fastapi ; extra == 'dev'
   - starlette ; extra == 'dev'
-  - torch>=2.2 ; extra == 'dev'
-  - accelerate>=0.26.0 ; extra == 'dev'
-  - datasets>=2.15.0 ; extra == 'dev'
-  - ruff==0.13.1 ; extra == 'dev'
-  - gitpython<3.1.19 ; extra == 'dev'
-  - urllib3<2.0.0 ; extra == 'dev'
-  - libcst ; extra == 'dev'
   - rich ; extra == 'dev'
-  - pandas<2.3.0 ; extra == 'dev'
+  - torch>=2.4 ; extra == 'dev'
+  - accelerate>=1.1.0 ; extra == 'dev'
+  - mistral-common[image]>=1.10.0 ; extra == 'dev'
   - fugashi>=1.0 ; extra == 'dev'
   - ipadic>=1.0.0,<2.0 ; extra == 'dev'
   - unidic-lite>=1.0.7 ; extra == 'dev'
   - unidic>=1.0.2 ; extra == 'dev'
+  - rhoknp>=1.1.0,<1.3.1 ; extra == 'dev'
   - sudachipy>=0.6.6 ; extra == 'dev'
   - sudachidict-core>=20220729 ; extra == 'dev'
-  - rhoknp>=1.1.0,<1.3.1 ; extra == 'dev'
   - scikit-learn ; extra == 'dev'
-  - cookiecutter==1.7.3 ; extra == 'dev'
-  - filelock ; extra == 'torchhub'
-  - huggingface-hub>=0.34.0,<1.0 ; extra == 'torchhub'
-  - importlib-metadata ; extra == 'torchhub'
-  - numpy>=1.17 ; extra == 'torchhub'
-  - packaging>=20.0 ; extra == 'torchhub'
-  - protobuf ; extra == 'torchhub'
-  - regex!=2019.12.17 ; extra == 'torchhub'
-  - requests ; extra == 'torchhub'
-  - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'torchhub'
-  - torch>=2.2 ; extra == 'torchhub'
-  - tokenizers>=0.22.0,<=0.23.0 ; extra == 'torchhub'
-  - tqdm>=4.27 ; extra == 'torchhub'
-  - optimum-benchmark>=0.3.0 ; extra == 'benchmark'
-  - opentelemetry-api ; extra == 'open-telemetry'
-  - opentelemetry-exporter-otlp ; extra == 'open-telemetry'
-  - opentelemetry-sdk ; extra == 'open-telemetry'
-  requires_python: '>=3.9.0'
+  requires_python: '>=3.10.0'
 - pypi: https://files.pythonhosted.org/packages/3a/7a/882d99539b19b1490cac5d77c67338d126e4122c8276bf640e411650c830/twine-6.2.0-py3-none-any.whl
   name: twine
   version: 6.2.0
diff --git a/pyproject.toml b/pyproject.toml
index 367c298..0db092f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -33,7 +33,7 @@ azure = [
 ]
 hf = [
     "qwen-vl-utils",
-    "transformers>=4.57.0,<5",
+    "transformers>=5,<6",
 ]
 mistral = [
     "mistralai>=1.6.0,<2",
@@ -49,7 +49,7 @@ all = [
     "litellm[caching]==1.82.3",
     "azure-ai-documentintelligence==1.0.2",
     "qwen-vl-utils",
-    "transformers>=4.57.0,<5",
+    "transformers>=5,<6",
     "mistralai>=1.6.0,<2",
     "pypdfium2>=5,<6",
 ]
diff --git a/tests/test_install.py b/tests/test_install.py
index ab06e95..7748202 100644
--- a/tests/test_install.py
+++ b/tests/test_install.py
@@ -25,7 +25,7 @@ def test_install_runtime_dependencies_installs_hf_and_torch_with_uv(
         lambda _: _FakeDistribution(
             requires=[
                 'qwen-vl-utils; extra == "hf"',
-                'transformers>=4.57.0,<5; extra == "hf"',
+                'transformers>=5,<6; extra == "hf"',
             ]
         ),
     )
@@ -51,7 +51,7 @@ def test_install_runtime_dependencies_installs_hf_and_torch_with_uv(
             sys.executable,
             "--upgrade",
             "qwen-vl-utils",
-            "transformers>=4.57.0,<5",
+            "transformers>=5,<6",
         ],
         [
             "/usr/bin/uv",
diff --git a/tests/test_internal_helpers.py b/tests/test_internal_helpers.py
index e37af3e..240581a 100644
--- a/tests/test_internal_helpers.py
+++ b/tests/test_internal_helpers.py
@@ -16,8 +16,11 @@
 from churro_ocr._internal.image import image_to_base64, load_image
 from churro_ocr._internal.litellm import LiteLLMTransport, complete_text
 from churro_ocr.errors import ConfigurationError, ProviderError
+from churro_ocr.page_detection import DocumentPage
+from churro_ocr.providers._shared import render_ocr_prompt
 from churro_ocr.providers.hf import _load_hf_causal_runtime, _load_hf_runtime
 from churro_ocr.providers.specs import LiteLLMTransportConfig
+from churro_ocr.templates import HFChatTemplate
 
 
 def _make_fake_litellm_module(*, acompletion: object, completion_cost: object | None = None) -> ModuleType:
@@ -93,6 +96,42 @@ def test_prepare_messages_from_conversation_converts_images_and_preserves_unknow
     ]
 
 
+def test_render_ocr_prompt_supports_transformers_v5_chat_template_contract() -> None:
+    captured: dict[str, object] = {}
+
+    class FakeProcessor:
+        def apply_chat_template(
+            self,
+            conversation: list[dict[str, object]],
+            *,
+            add_generation_prompt: bool,
+            tokenize: bool = True,
+            return_dict: bool = True,
+        ) -> object:
+            captured["conversation"] = conversation
+            captured["add_generation_prompt"] = add_generation_prompt
+            captured["tokenize"] = tokenize
+            captured["return_dict"] = return_dict
+            if not tokenize:
+                return "<rendered>"
+            return {"input_ids": [1, 2, 3]} if return_dict else [1, 2, 3]
+
+    page = DocumentPage.from_image(Image.new("RGB", (16, 16), color="white"))
+
+    rendered, conversation = render_ocr_prompt(
+        FakeProcessor(),
+        HFChatTemplate(user_prompt="prompt"),
+        page,
+        add_generation_prompt=True,
+    )
+
+    assert rendered == "<rendered>"
+    assert conversation == captured["conversation"]
+    assert captured["add_generation_prompt"] is True
+    assert captured["tokenize"] is False
+    assert captured["return_dict"] is True
+
+
 @pytest.mark.asyncio
 async def test_complete_text_wrapper_passes_transport_config(monkeypatch: pytest.MonkeyPatch) -> None:
     captured: dict[str, object] = {}
diff --git a/tests/test_package_check.py b/tests/test_package_check.py
index 84ef26f..a4dfcfa 100644
--- a/tests/test_package_check.py
+++ b/tests/test_package_check.py
@@ -47,7 +47,7 @@ def _always_missing(_: str):
 
 def test_local_runtime_packaging_policy_rejects_direct_torch_runtime_pin() -> None:
     metadata_message = _metadata_message(
-        'transformers[torch]<5,>=4.57.0; extra == "hf"',
+        'transformers[torch]>=5,<6; extra == "hf"',
         'torchvision; extra == "all"',
     )
 

From 6dafe58bdaa0c0b07380ebba34726688182bd8ec Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Mon, 6 Apr 2026 01:56:14 +0000
Subject: [PATCH 09/28] feat(ocr): add chandra-ocr-2 support

---
 docs/guides/providers.md             |   6 +
 src/churro_ocr/prompts/__init__.py   |   4 +
 src/churro_ocr/prompts/ocr.py        |  71 +++++++-
 src/churro_ocr/providers/builder.py  |   3 +
 src/churro_ocr/providers/hf.py       | 235 +++++++++++++++++++++++----
 src/churro_ocr/providers/specs.py    |  86 ++++++++++
 src/churro_ocr/templates/__init__.py |   4 +
 src/churro_ocr/templates/presets.py  |   8 +
 tests/test_cli.py                    |  40 +++++
 tests/test_hf_ocr.py                 | 219 ++++++++++++++++++++++++-
 tests/test_providers.py              | 110 +++++++++++++
 11 files changed, 746 insertions(+), 40 deletions(-)

diff --git a/docs/guides/providers.md b/docs/guides/providers.md
index 3b1640a..f12565d 100644
--- a/docs/guides/providers.md
+++ b/docs/guides/providers.md
@@ -32,6 +32,7 @@ This page is the source of truth for matching providers to runtime targets.
 | --- | --- | --- |
 | hosted OCR | `litellm` + `vertex_ai/gemini-2.5-flash` | easiest hosted path with the standard builder interface |
 | local OCR | `hf` + `stanford-oval/churro-3B` | first-party local model support in-process |
+| layout-heavy local OCR | `hf` + `datalab-to/chandra-ocr-2` | built-in profile matches Chandra's layout-oriented prompt, scaling, and generation defaults |
 | higher-throughput local serving | `openai-compatible` + your own OpenAI-style server | good when you already run a served local backend such as vLLM |
 
 ## Hosted Providers
@@ -144,6 +145,8 @@ backend = build_ocr_backend(
 )
 ```
 
+Built-in model-specific profiles are resolved automatically for known models such as `stanford-oval/churro-3B`, `datalab-to/chandra-ocr-2`, `kristaller486/dots.ocr-1.5`, and the supported `olmOCR` checkpoints.
+
 ## `OCRBackendSpec` Reference
 
 | Field | Meaning |
@@ -204,6 +207,7 @@ Useful public template exports:
 | `HFChatTemplate` | `churro_ocr.templates` | Build a Hugging Face chat-style multimodal prompt. |
 | `DEFAULT_OCR_TEMPLATE` | `churro_ocr.templates` | Generic OCR prompt template used by the default model profile. |
 | `CHURRO_3B_XML_TEMPLATE` | `churro_ocr.templates` | Built-in template for `stanford-oval/churro-3B`. |
+| `CHANDRA_OCR_2_OCR_TEMPLATE` | `churro_ocr.templates` | Built-in template for `datalab-to/chandra-ocr-2`. |
 | `DOTS_OCR_1_5_OCR_TEMPLATE` | `churro_ocr.templates` | Built-in template for `kristaller486/dots.ocr-1.5`. |
 | `OCRPromptTemplate` | `churro_ocr.templates` | Base protocol for custom profile integration. |
 
@@ -214,6 +218,8 @@ Useful public prompt exports:
 | `DEFAULT_OCR_SYSTEM_PROMPT` | `churro_ocr.prompts` | Default system instruction for generic OCR prompting. |
 | `DEFAULT_OCR_USER_PROMPT` | `churro_ocr.prompts` | Default user prompt for plain OCR output. |
 | `DEFAULT_MARKDOWN_OCR_USER_PROMPT` | `churro_ocr.prompts` | Default user prompt when markdown-style OCR output is preferred. |
+| `CHANDRA_OCR_LAYOUT_PROMPT` | `churro_ocr.prompts` | Upstream Chandra OCR 2 layout-block HTML prompt. |
 | `DEFAULT_OCR_OUTPUT_TAG` | `churro_ocr.prompts` | Shared tag name used by the default OCR postprocessor. |
 | `DEFAULT_BOUNDARY_DETECTION_PROMPT` | `churro_ocr.prompts` | Default prompt used by LLM-based page and text-block boundary detection helpers. |
+| `parse_chandra_response(...)` | `churro_ocr.prompts` | Convert Chandra HTML-layout output to plain text and preserve raw HTML metadata. |
 | `strip_ocr_output_tag(...)` | `churro_ocr.prompts` | Remove the default OCR wrapper tag from model output. |
diff --git a/src/churro_ocr/prompts/__init__.py b/src/churro_ocr/prompts/__init__.py
index 41917aa..19db07e 100644
--- a/src/churro_ocr/prompts/__init__.py
+++ b/src/churro_ocr/prompts/__init__.py
@@ -4,22 +4,26 @@
     DEFAULT_BOUNDARY_DETECTION_PROMPT,
 )
 from churro_ocr.prompts.ocr import (
+    CHANDRA_OCR_LAYOUT_PROMPT,
     DEFAULT_MARKDOWN_OCR_USER_PROMPT,
     DEFAULT_OCR_OUTPUT_TAG,
     DEFAULT_OCR_SYSTEM_PROMPT,
     DEFAULT_OCR_USER_PROMPT,
     OLMOCR_V4_YAML_PROMPT,
+    parse_chandra_response,
     parse_olmocr_response,
     strip_ocr_output_tag,
 )
 
 __all__ = [
+    "CHANDRA_OCR_LAYOUT_PROMPT",
     "DEFAULT_BOUNDARY_DETECTION_PROMPT",
     "DEFAULT_MARKDOWN_OCR_USER_PROMPT",
     "DEFAULT_OCR_OUTPUT_TAG",
     "DEFAULT_OCR_SYSTEM_PROMPT",
     "DEFAULT_OCR_USER_PROMPT",
     "OLMOCR_V4_YAML_PROMPT",
+    "parse_chandra_response",
     "parse_olmocr_response",
     "strip_ocr_output_tag",
 ]
diff --git a/src/churro_ocr/prompts/ocr.py b/src/churro_ocr/prompts/ocr.py
index 0007850..a888d4a 100644
--- a/src/churro_ocr/prompts/ocr.py
+++ b/src/churro_ocr/prompts/ocr.py
@@ -41,6 +41,54 @@
     "tables, and line breaks when they are visible."
 )
 
+CHANDRA_OCR_LAYOUT_PROMPT = (
+    "OCR this image to HTML, arranged as layout blocks. Each layout block should be a div "
+    "with the data-bbox attribute representing the bounding box of the block in x0 y0 x1 y1 "
+    "format. Bboxes are normalized 0-1000. The data-label attribute is the label for the block.\n\n"
+    "Use the following labels:\n"
+    "- Caption\n"
+    "- Footnote\n"
+    "- Equation-Block\n"
+    "- List-Group\n"
+    "- Page-Header\n"
+    "- Page-Footer\n"
+    "- Image\n"
+    "- Section-Header\n"
+    "- Table\n"
+    "- Text\n"
+    "- Complex-Block\n"
+    "- Code-Block\n"
+    "- Form\n"
+    "- Table-Of-Contents\n"
+    "- Figure\n"
+    "- Chemical-Block\n"
+    "- Diagram\n"
+    "- Bibliography\n"
+    "- Blank-Page\n\n"
+    "Only use these tags ['math', 'br', 'i', 'b', 'u', 'del', 'sup', 'sub', 'table', 'tr', "
+    "'td', 'p', 'th', 'div', 'pre', 'h1', 'h2', 'h3', 'h4', 'h5', 'ul', 'ol', 'li', 'input', "
+    "'a', 'span', 'img', 'hr', 'tbody', 'small', 'caption', 'strong', 'thead', 'big', 'code', "
+    "'chem'], and these attributes ['class', 'colspan', 'rowspan', 'display', 'checked', "
+    "'type', 'border', 'value', 'style', 'href', 'alt', 'align', 'data-bbox', 'data-label'].\n\n"
+    "Guidelines:\n"
+    "* Inline math: Surround math with <math>...</math> tags. Math expressions should be rendered "
+    "in KaTeX-compatible LaTeX. Use display for block math.\n"
+    "* Tables: Use colspan and rowspan attributes to match table structure.\n"
+    "* Formatting: Maintain consistent formatting with the image, including spacing, indentation, "
+    "subscripts/superscripts, and special characters.\n"
+    "* Images: Include a description of any images in the alt attribute of an <img> tag. Do not "
+    "fill out the src property. Describe in detail inside the div tag. Also convert charts to high "
+    "fidelity data, and convert diagrams to mermaid.\n"
+    "* Forms: Mark checkboxes and radio buttons properly.\n"
+    "* Text: join lines together properly into paragraphs using <p>...</p> tags. Use <br> tags for "
+    "line breaks within paragraphs, but only when absolutely necessary to maintain meaning.\n"
+    "* Chemistry: Use <chem>...</chem> tags for chemical formulas with reactive SMILES.\n"
+    "* Lists: Preserve indents and proper list markers.\n"
+    "* Use the simplest possible HTML structure that accurately represents the content of the block.\n"
+    "* Make sure the text is accurate and easy for a human to read and interpret. Reading order "
+    "should be correct and natural."
+)
+
 OLMOCR_V4_YAML_PROMPT = (
     "Attached is one page of a document that you must process. "
     "Just return the plain text representation of this document as if you were reading it naturally.\n"
@@ -105,8 +153,8 @@ def _extract_yaml_front_matter(text: str) -> tuple[dict[str, object], str]:
     return front_matter, body
 
 
-def _strip_olmocr_markdown_to_plain_text(text: str) -> str:
-    """Best-effort plain-text conversion for olmOCR markdown/HTML output."""
+def _strip_rich_ocr_markup_to_plain_text(text: str) -> str:
+    """Best-effort plain-text conversion for OCR markdown/HTML output."""
     cleaned = text.strip()
     if not cleaned:
         return ""
@@ -115,20 +163,25 @@ def _strip_olmocr_markdown_to_plain_text(text: str) -> str:
     cleaned = re.sub(r"\[([^\]]+)]\([^)]+\)", r"\1", cleaned)
 
     html_replacements = (
+        (r"(?is)<\s*input\b[^>]*\bchecked(?:=(?:\"[^\"]*\"|'[^']*'|[^\s>]+))?[^>]*>", "[x]"),
+        (r"(?is)<\s*input\b[^>]*>", "[ ]"),
         (r"(?i)<\s*br\s*/?\s*>", "\n"),
-        (r"(?i)</\s*(?:p|div|h[1-6]|ul|ol|table|tr|li|pre)\s*>", "\n"),
+        (r"(?i)<\s*hr\s*/?\s*>", "\n"),
+        (r"(?i)</\s*(?:p|div|h[1-6]|ul|ol|table|tr|li|pre|caption)\s*>", "\n"),
         (r"(?i)</\s*(?:td|th)\s*>", " | "),
         (r"(?i)<\s*li\b[^>]*>", ""),
         (
             r"(?i)</?\s*(?:table|thead|tbody|tfoot|tr|td|th|p|div|span|h[1-6]|ul|ol|"
-            r"strong|em|b|i|u|sup|sub|code|pre)\b[^>]*>",
+            r"strong|em|b|i|u|sup|sub|code|pre|a|math|chem|caption|small|big)\b[^>]*>",
             "",
         ),
+        (r"(?i)<\s*img\b[^>]*>", ""),
     )
     for pattern, replacement in html_replacements:
         cleaned = re.sub(pattern, replacement, cleaned)
 
     cleaned = html.unescape(cleaned)
+    cleaned = re.sub(r"(?is)</?[a-z][^>]*>", "", cleaned)
     cleaned = re.sub(r"(?m)^\s{0,3}#{1,6}\s*", "", cleaned)
     cleaned = re.sub(r"(?m)^\s*[-+*]\s+", "", cleaned)
     cleaned = re.sub(r"(?m)^\s*>\s?", "", cleaned)
@@ -157,7 +210,15 @@ def _strip_olmocr_markdown_to_plain_text(text: str) -> str:
 def parse_olmocr_response(text: str) -> tuple[str, dict[str, Any]]:
     """Extract plain text and metadata from an olmOCR YAML-front-matter response."""
     front_matter, markdown_body = _extract_yaml_front_matter(text)
-    return _strip_olmocr_markdown_to_plain_text(markdown_body), {
+    return _strip_rich_ocr_markup_to_plain_text(markdown_body), {
         "front_matter": front_matter,
         "raw_markdown": markdown_body,
     }
+
+
+def parse_chandra_response(text: str) -> tuple[str, dict[str, Any]]:
+    """Extract plain text and metadata from a Chandra HTML-layout response."""
+    raw_html = text.strip()
+    return _strip_rich_ocr_markup_to_plain_text(raw_html), {
+        "raw_html": raw_html,
+    }
diff --git a/src/churro_ocr/providers/builder.py b/src/churro_ocr/providers/builder.py
index bc27461..216ed12 100644
--- a/src/churro_ocr/providers/builder.py
+++ b/src/churro_ocr/providers/builder.py
@@ -6,6 +6,7 @@
 from churro_ocr.errors import ConfigurationError
 from churro_ocr.ocr import OCRBackend
 from churro_ocr.providers.hf import (
+    ChandraOCR2OCRBackend,
     DotsOCR15OCRBackend,
     HuggingFaceVisionOCRBackend,
     _default_dots_ocr_1_5_model_kwargs,
@@ -163,6 +164,8 @@ def _build_huggingface_backend(spec: OCRBackendSpec, profile: OCRModelProfile) -
     if options.backend_variant == "dots-ocr-1.5":
         backend_cls = DotsOCR15OCRBackend
         model_kwargs = _merge_mapping(_default_dots_ocr_1_5_model_kwargs(), model_kwargs)
+    elif options.backend_variant == "chandra-ocr-2":
+        backend_cls = ChandraOCR2OCRBackend
     return backend_cls(
         model_id=spec.model,
         template=profile.template,
diff --git a/src/churro_ocr/providers/hf.py b/src/churro_ocr/providers/hf.py
index 54e62a3..f3ad5a0 100644
--- a/src/churro_ocr/providers/hf.py
+++ b/src/churro_ocr/providers/hf.py
@@ -7,7 +7,7 @@
 from dataclasses import dataclass, field
 from importlib import import_module
 from pathlib import Path
-from typing import Any
+from typing import Any, cast
 
 from churro_ocr._internal.install import install_command_hint
 from churro_ocr._internal.prompt_logging import log_prompt_payload_once
@@ -29,6 +29,8 @@
     identity_text_postprocessor,
 )
 from churro_ocr.templates import (
+    CHANDRA_OCR_2_MODEL_ID,
+    CHANDRA_OCR_2_OCR_TEMPLATE,
     CHURRO_3B_MODEL_ID,
     CHURRO_3B_XML_TEMPLATE,
     DOTS_OCR_1_5_MODEL_ID,
@@ -181,6 +183,53 @@ def _default_dots_ocr_1_5_model_kwargs() -> dict[str, object]:
     return model_kwargs
 
 
+def _default_chandra_ocr_2_model_kwargs() -> dict[str, object]:
+    model_kwargs: dict[str, object] = {
+        "device_map": "auto",
+        "dtype": "auto",
+    }
+    try:
+        torch = import_module("torch")
+    except ImportError:  # pragma: no cover - torch is installed separately for local HF use
+        return model_kwargs
+
+    if torch.cuda.is_available():
+        model_kwargs["dtype"] = torch.bfloat16
+    return model_kwargs
+
+
+def _move_batch_to_model(batch: Any, model: Any) -> Any:
+    model_device = getattr(model, "device", None)
+    if hasattr(batch, "to") and model_device is not None:
+        batch = batch.to(model_device)
+    model_dtype = getattr(model, "dtype", None)
+    if model_dtype is not None:
+        batch_mapping = cast(dict[str, object], batch)
+        for key, value in batch_mapping.items():
+            if hasattr(value, "dtype") and getattr(value.dtype, "is_floating_point", False):
+                batch_mapping[key] = cast(Any, value).to(dtype=model_dtype)
+    return batch
+
+
+def _decode_completion_texts(processor: Any, batch: Any, generated_ids: Any) -> list[str]:
+    batch_mapping = cast(dict[str, object], batch)
+    attention_mask = batch_mapping.get("attention_mask")
+    if attention_mask is not None and hasattr(attention_mask, "sum"):
+        prompt_lengths = cast(Any, attention_mask).sum(dim=1).tolist()
+        completion_ids = [
+            output_ids[int(prompt_length) :]
+            for prompt_length, output_ids in zip(prompt_lengths, generated_ids, strict=True)
+        ]
+    else:
+        prompt_length = cast(Any, batch_mapping["input_ids"]).shape[1]
+        completion_ids = generated_ids[:, prompt_length:]
+    return processor.batch_decode(
+        completion_ids,
+        skip_special_tokens=True,
+        clean_up_tokenization_spaces=False,
+    )
+
+
 @dataclass(slots=True)
 class HuggingFaceVisionOCRBackend(OCRBackend):
     """OCR backend for local Hugging Face multimodal models with custom templates.
@@ -270,23 +319,10 @@ def _ocr_sync(self, page: DocumentPage) -> OCRResult:
         if normalized_video_inputs is not None:
             batch_kwargs["videos"] = normalized_video_inputs
         batch = processor(**batch_kwargs)
-        model_device = getattr(model, "device", None)
-        if hasattr(batch, "to") and model_device is not None:
-            batch = batch.to(model_device)
-        model_dtype = getattr(model, "dtype", None)
-        if model_dtype is not None:
-            for key, value in batch.items():
-                if hasattr(value, "dtype") and getattr(value.dtype, "is_floating_point", False):
-                    batch[key] = value.to(dtype=model_dtype)
+        batch = _move_batch_to_model(batch, model)
 
         generated_ids = model.generate(**batch, **self.generation_kwargs)
-        prompt_length = batch["input_ids"].shape[1]
-        completion_ids = generated_ids[:, prompt_length:]
-        text = processor.batch_decode(
-            completion_ids,
-            skip_special_tokens=True,
-            clean_up_tokenization_spaces=False,
-        )[0]
+        text = _decode_completion_texts(processor, batch, generated_ids)[0]
         return build_ocr_result(
             text,
             provider_name=self.provider_name,
@@ -340,26 +376,10 @@ def _ocr_batch_sync(self, pages: list[DocumentPage]) -> list[OCRResult]:
         if has_videos:
             batch_kwargs["videos"] = video_batch
         batch = processor(**batch_kwargs)
-        model_device = getattr(model, "device", None)
-        if hasattr(batch, "to") and model_device is not None:
-            batch = batch.to(model_device)
-        model_dtype = getattr(model, "dtype", None)
-        if model_dtype is not None:
-            for key, value in batch.items():
-                if hasattr(value, "dtype") and getattr(value.dtype, "is_floating_point", False):
-                    batch[key] = value.to(dtype=model_dtype)
+        batch = _move_batch_to_model(batch, model)
 
         generated_ids = model.generate(**batch, **self.generation_kwargs)
-        prompt_lengths = batch["attention_mask"].sum(dim=1).tolist()
-        completion_ids = [
-            output_ids[int(prompt_length) :]
-            for prompt_length, output_ids in zip(prompt_lengths, generated_ids, strict=True)
-        ]
-        texts = processor.batch_decode(
-            completion_ids,
-            skip_special_tokens=True,
-            clean_up_tokenization_spaces=False,
-        )
+        texts = _decode_completion_texts(processor, batch, generated_ids)
         return [
             build_ocr_result(
                 text,
@@ -442,6 +462,152 @@ def _log_prompt_payload(
         )
 
 
+@dataclass(slots=True)
+class ChandraOCR2OCRBackend(HuggingFaceVisionOCRBackend):
+    """Preset OCR backend for ``datalab-to/chandra-ocr-2``."""
+
+    model_id: str = CHANDRA_OCR_2_MODEL_ID
+    template: OCRPromptTemplateLike = CHANDRA_OCR_2_OCR_TEMPLATE
+    model_name: str | None = "chandra-ocr-2"
+
+    def _get_processor(self, runtime: _HFRuntime) -> Any:
+        processor = super()._get_processor(runtime)
+        tokenizer = getattr(processor, "tokenizer", None)
+        if tokenizer is not None and getattr(tokenizer, "padding_side", None) != "left":
+            tokenizer.padding_side = "left"
+        return processor
+
+    def _get_model(self, runtime: _HFRuntime) -> Any:
+        if self._model is None:
+            with self._init_lock:
+                if self._model is None:
+                    model_kwargs = {
+                        **_default_chandra_ocr_2_model_kwargs(),
+                        **self.model_kwargs,
+                    }
+                    self._model = runtime.model_cls.from_pretrained(
+                        self._get_model_source(),
+                        trust_remote_code=self.trust_remote_code,
+                        **model_kwargs,
+                    )
+                    eval_method = getattr(self._model, "eval", None)
+                    if callable(eval_method):
+                        eval_method()
+        return self._model
+
+    def _build_chandra_batch(self, processor: Any, conversations: list[OCRConversation]) -> Any:
+        processor_apply = getattr(processor, "apply_chat_template", None)
+        if not callable(processor_apply):
+            raise ConfigurationError("Chandra OCR 2 requires `processor.apply_chat_template(...)` support.")
+        return processor_apply(
+            conversations,
+            add_generation_prompt=True,
+            tokenize=True,
+            return_dict=True,
+            return_tensors="pt",
+            padding=True,
+        )
+
+    def _resolve_chandra_generation_kwargs(self, processor: Any, model: Any) -> dict[str, object]:
+        generation_kwargs = dict(self.generation_kwargs)
+        eos_token_ids: list[int] = []
+        eos_token_id = getattr(getattr(model, "generation_config", None), "eos_token_id", None)
+        if isinstance(eos_token_id, int):
+            eos_token_ids.append(eos_token_id)
+        elif isinstance(eos_token_id, list):
+            eos_token_ids.extend(token_id for token_id in eos_token_id if isinstance(token_id, int))
+
+        tokenizer = getattr(processor, "tokenizer", None)
+        convert_tokens_to_ids = getattr(tokenizer, "convert_tokens_to_ids", None)
+        if callable(convert_tokens_to_ids):
+            im_end_id = convert_tokens_to_ids("<|im_end|>")
+            if isinstance(im_end_id, int) and im_end_id >= 0 and im_end_id not in eos_token_ids:
+                eos_token_ids.append(im_end_id)
+
+        if eos_token_ids:
+            generation_kwargs["eos_token_id"] = eos_token_ids
+        return generation_kwargs
+
+    def _ocr_sync(self, page: DocumentPage) -> OCRResult:
+        prepared_page = preprocess_backend_page(
+            page,
+            image_preprocessor=self.image_preprocessor,
+        )
+        runtime = self._load_runtime()
+        processor = self._get_processor(runtime)
+        model = self._get_model(runtime)
+
+        rendered, conversation = render_ocr_prompt(
+            processor,
+            self.template,
+            prepared_page,
+            add_generation_prompt=True,
+        )
+        self._log_prompt_payload(
+            rendered_prompt=rendered,
+            conversation=conversation,
+            batch_size=1,
+        )
+        batch = self._build_chandra_batch(processor, [conversation])
+        batch = _move_batch_to_model(batch, model)
+        generated_ids = model.generate(
+            **batch,
+            **self._resolve_chandra_generation_kwargs(processor, model),
+        )
+        text = _decode_completion_texts(processor, batch, generated_ids)[0]
+        return build_ocr_result(
+            text,
+            provider_name=self.provider_name,
+            model_name=self.model_name or self.model_id,
+            text_postprocessor=self.text_postprocessor,
+        )
+
+    def _ocr_batch_sync(self, pages: list[DocumentPage]) -> list[OCRResult]:
+        if not pages:
+            return []
+
+        runtime = self._load_runtime()
+        processor = self._get_processor(runtime)
+        model = self._get_model(runtime)
+        conversations: list[OCRConversation] = []
+
+        for page in pages:
+            prepared_page = preprocess_backend_page(
+                page,
+                image_preprocessor=self.image_preprocessor,
+            )
+            rendered, conversation = render_ocr_prompt(
+                processor,
+                self.template,
+                prepared_page,
+                add_generation_prompt=True,
+            )
+            conversations.append(conversation)
+            if not self._has_logged_prompt:
+                self._log_prompt_payload(
+                    rendered_prompt=rendered,
+                    conversation=conversation,
+                    batch_size=len(pages),
+                )
+
+        batch = self._build_chandra_batch(processor, conversations)
+        batch = _move_batch_to_model(batch, model)
+        generated_ids = model.generate(
+            **batch,
+            **self._resolve_chandra_generation_kwargs(processor, model),
+        )
+        texts = _decode_completion_texts(processor, batch, generated_ids)
+        return [
+            build_ocr_result(
+                text,
+                provider_name=self.provider_name,
+                model_name=self.model_name or self.model_id,
+                text_postprocessor=self.text_postprocessor,
+            )
+            for text in texts
+        ]
+
+
 @dataclass(slots=True)
 class Churro3BOCRBackend(HuggingFaceVisionOCRBackend):
     """Preset OCR backend for ``stanford-oval/churro-3B``."""
@@ -497,6 +663,7 @@ def _get_model(self, runtime: _HFRuntime) -> Any:
 
 
 __all__ = [
+    "ChandraOCR2OCRBackend",
     "Churro3BOCRBackend",
     "DotsOCR15OCRBackend",
     "HuggingFaceVisionOCRBackend",
diff --git a/src/churro_ocr/providers/specs.py b/src/churro_ocr/providers/specs.py
index b366617..43f46c9 100644
--- a/src/churro_ocr/providers/specs.py
+++ b/src/churro_ocr/providers/specs.py
@@ -12,10 +12,13 @@
 from churro_ocr._internal.image import ensure_rgb, prepare_ocr_image, resize_image_to_fit
 from churro_ocr.prompts import (
     DEFAULT_OCR_OUTPUT_TAG,
+    parse_chandra_response,
     parse_olmocr_response,
     strip_ocr_output_tag,
 )
 from churro_ocr.templates import (
+    CHANDRA_OCR_2_MODEL_ID,
+    CHANDRA_OCR_2_OCR_TEMPLATE,
     CHURRO_3B_MODEL_ID,
     CHURRO_3B_XML_TEMPLATE,
     DEFAULT_OCR_TEMPLATE,
@@ -38,7 +41,11 @@
 TextPostprocessor = Callable[[str], TextPostprocessorResult]
 VisionInputBuilder = Callable[[OCRConversation], object]
 DEFAULT_OCR_MAX_TOKENS = 20_000
+CHANDRA_OCR_MAX_TOKENS = 12_384
 OLMOCR_MAX_TOKENS = 8_000
+CHANDRA_MAX_IMAGE_SIZE = (3_072, 2_048)
+CHANDRA_MIN_IMAGE_SIZE = (1_792, 28)
+CHANDRA_IMAGE_GRID_SIZE = 28
 OLMOCR_TARGET_LONGEST_IMAGE_DIM = 1_288
 
 
@@ -85,6 +92,56 @@ def olmocr_text_postprocessor(text: str) -> TextPostprocessorResult:
     return parse_olmocr_response(text)
 
 
+def chandra_image_preprocessor(image: Image.Image) -> Image.Image:
+    """Resize an image using Chandra OCR 2's pixel-budget and 28px-grid scaling."""
+    width, height = image.size
+    if width <= 0 or height <= 0:
+        return ensure_rgb(image)
+
+    max_pixels = CHANDRA_MAX_IMAGE_SIZE[0] * CHANDRA_MAX_IMAGE_SIZE[1]
+    min_pixels = CHANDRA_MIN_IMAGE_SIZE[0] * CHANDRA_MIN_IMAGE_SIZE[1]
+    current_pixels = width * height
+    scale = 1.0
+    if current_pixels > max_pixels:
+        scale = (max_pixels / current_pixels) ** 0.5
+    elif current_pixels < min_pixels:
+        scale = (min_pixels / current_pixels) ** 0.5
+
+    original_aspect_ratio = width / height
+    width_blocks = max(1, round((width * scale) / CHANDRA_IMAGE_GRID_SIZE))
+    height_blocks = max(1, round((height * scale) / CHANDRA_IMAGE_GRID_SIZE))
+
+    while (width_blocks * height_blocks * CHANDRA_IMAGE_GRID_SIZE**2) > max_pixels:
+        if width_blocks == 1 and height_blocks == 1:
+            break
+        if width_blocks == 1:
+            height_blocks -= 1
+            continue
+        if height_blocks == 1:
+            width_blocks -= 1
+            continue
+
+        width_loss = abs(((width_blocks - 1) / height_blocks) - original_aspect_ratio)
+        height_loss = abs((width_blocks / (height_blocks - 1)) - original_aspect_ratio)
+        if width_loss < height_loss:
+            width_blocks -= 1
+        else:
+            height_blocks -= 1
+
+    new_size = (
+        width_blocks * CHANDRA_IMAGE_GRID_SIZE,
+        height_blocks * CHANDRA_IMAGE_GRID_SIZE,
+    )
+    if new_size == (width, height):
+        return ensure_rgb(image)
+    return ensure_rgb(image.resize(new_size, resample=Image.Resampling.LANCZOS))
+
+
+def chandra_text_postprocessor(text: str) -> TextPostprocessorResult:
+    """Extract plain text and metadata from Chandra OCR 2 HTML-layout output."""
+    return parse_chandra_response(text)
+
+
 @dataclass(slots=True, frozen=True)
 class LiteLLMTransportConfig:
     """Shared transport config for LiteLLM-based multimodal requests.
@@ -223,6 +280,30 @@ def churro_3b_profile() -> OCRModelProfile:
     )
 
 
+def chandra_ocr_2_profile() -> OCRModelProfile:
+    """Return the built-in ``datalab-to/chandra-ocr-2`` OCR profile."""
+    return OCRModelProfile(
+        profile_name=CHANDRA_OCR_2_MODEL_ID,
+        template=CHANDRA_OCR_2_OCR_TEMPLATE,
+        image_preprocessor=chandra_image_preprocessor,
+        text_postprocessor=chandra_text_postprocessor,
+        display_name="chandra-ocr-2",
+        transport=LiteLLMTransportConfig(
+            completion_kwargs={
+                "max_tokens": CHANDRA_OCR_MAX_TOKENS,
+                "temperature": 0.0,
+                "top_p": 0.1,
+            }
+        ),
+        huggingface=HuggingFaceOptions(
+            generation_kwargs={
+                "max_new_tokens": CHANDRA_OCR_MAX_TOKENS,
+            },
+            backend_variant="chandra-ocr-2",
+        ),
+    )
+
+
 def dots_ocr_1_5_profile() -> OCRModelProfile:
     """Return the built-in ``kristaller486/dots.ocr-1.5`` OCR profile.
 
@@ -282,12 +363,14 @@ def olmocr_2_7b_1025_fp8_profile() -> OCRModelProfile:
 def _profile_registry() -> dict[str, OCRModelProfile]:
     default_profile = default_ocr_profile()
     churro_profile = churro_3b_profile()
+    chandra_profile = chandra_ocr_2_profile()
     dots_profile = dots_ocr_1_5_profile()
     olmocr_profile = olmocr_2_7b_1025_profile()
     olmocr_fp8_profile = olmocr_2_7b_1025_fp8_profile()
     return {
         default_profile.profile_name: default_profile,
         churro_profile.profile_name: churro_profile,
+        chandra_profile.profile_name: chandra_profile,
         dots_profile.profile_name: dots_profile,
         olmocr_profile.profile_name: olmocr_profile,
         olmocr_fp8_profile.profile_name: olmocr_fp8_profile,
@@ -324,6 +407,9 @@ def resolve_ocr_profile(
 __all__ = [
     "AzureDocumentIntelligenceOptions",
     "DEFAULT_OCR_MAX_TOKENS",
+    "chandra_image_preprocessor",
+    "chandra_ocr_2_profile",
+    "chandra_text_postprocessor",
     "default_ocr_image_preprocessor",
     "default_ocr_profile",
     "default_ocr_text_postprocessor",
diff --git a/src/churro_ocr/templates/__init__.py b/src/churro_ocr/templates/__init__.py
index a8d97c9..d8a1f30 100644
--- a/src/churro_ocr/templates/__init__.py
+++ b/src/churro_ocr/templates/__init__.py
@@ -9,6 +9,8 @@
 )
 from churro_ocr.templates.hf import HFChatTemplate
 from churro_ocr.templates.presets import (
+    CHANDRA_OCR_2_MODEL_ID,
+    CHANDRA_OCR_2_OCR_TEMPLATE,
     CHURRO_3B_MODEL_ID,
     CHURRO_3B_XML_TEMPLATE,
     DEFAULT_OCR_TEMPLATE,
@@ -24,6 +26,8 @@
     "build_ocr_conversation",
     "CHURRO_3B_MODEL_ID",
     "CHURRO_3B_XML_TEMPLATE",
+    "CHANDRA_OCR_2_MODEL_ID",
+    "CHANDRA_OCR_2_OCR_TEMPLATE",
     "DEFAULT_OCR_TEMPLATE",
     "DOTS_OCR_1_5_MODEL_ID",
     "DOTS_OCR_1_5_OCR_PROMPT",
diff --git a/src/churro_ocr/templates/presets.py b/src/churro_ocr/templates/presets.py
index 8270444..ffd6009 100644
--- a/src/churro_ocr/templates/presets.py
+++ b/src/churro_ocr/templates/presets.py
@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 from churro_ocr.prompts import (
+    CHANDRA_OCR_LAYOUT_PROMPT,
     DEFAULT_OCR_SYSTEM_PROMPT,
     DEFAULT_OCR_USER_PROMPT,
     OLMOCR_V4_YAML_PROMPT,
@@ -10,6 +11,7 @@
 from churro_ocr.templates.hf import HFChatTemplate
 
 CHURRO_3B_MODEL_ID = "stanford-oval/churro-3B"
+CHANDRA_OCR_2_MODEL_ID = "datalab-to/chandra-ocr-2"
 DOTS_OCR_1_5_MODEL_ID = "kristaller486/dots.ocr-1.5"
 OLMOCR_2_7B_1025_MODEL_ID = "allenai/olmOCR-2-7B-1025"
 OLMOCR_2_7B_1025_FP8_MODEL_ID = "allenai/olmOCR-2-7B-1025-FP8"
@@ -22,6 +24,10 @@
     system_message="Transcribe the entirety of this historical document to XML format.",
     user_prompt=None,
 )
+CHANDRA_OCR_2_OCR_TEMPLATE = HFChatTemplate(
+    system_message=None,
+    user_prompt=CHANDRA_OCR_LAYOUT_PROMPT,
+)
 DOTS_OCR_1_5_OCR_PROMPT = "Extract the text content from this image."
 DOTS_OCR_1_5_OCR_TEMPLATE = HFChatTemplate(
     system_message=None,
@@ -37,6 +43,8 @@
 __all__ = [
     "CHURRO_3B_MODEL_ID",
     "CHURRO_3B_XML_TEMPLATE",
+    "CHANDRA_OCR_2_MODEL_ID",
+    "CHANDRA_OCR_2_OCR_TEMPLATE",
     "DEFAULT_OCR_TEMPLATE",
     "DOTS_OCR_1_5_MODEL_ID",
     "DOTS_OCR_1_5_OCR_PROMPT",
diff --git a/tests/test_cli.py b/tests/test_cli.py
index b26be7e..8410b8b 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -16,6 +16,8 @@
 from churro_ocr.page_detection import DocumentPage, PageDetectionResult
 from churro_ocr.prompts import DEFAULT_OCR_OUTPUT_TAG
 from churro_ocr.templates import (
+    CHANDRA_OCR_2_MODEL_ID,
+    CHANDRA_OCR_2_OCR_TEMPLATE,
     DEFAULT_OCR_TEMPLATE,
     DOTS_OCR_1_5_OCR_TEMPLATE,
     OLMOCR_2_7B_1025_MODEL_ID,
@@ -241,6 +243,44 @@ def test_build_ocr_backend_aligns_templates_for_olmocr() -> None:
     }
 
 
+def test_build_ocr_backend_aligns_templates_for_chandra() -> None:
+    litellm_backend = cli_module._build_ocr_backend(
+        backend="litellm",
+        model=CHANDRA_OCR_2_MODEL_ID,
+        endpoint=None,
+        api_key=None,
+        base_url=None,
+        api_version=None,
+    )
+    hf_backend = cli_module._build_ocr_backend(
+        backend="hf",
+        model=CHANDRA_OCR_2_MODEL_ID,
+        endpoint=None,
+        api_key=None,
+        base_url=None,
+        api_version=None,
+    )
+    openai_backend = cli_module._build_ocr_backend(
+        backend="openai-compatible",
+        model=CHANDRA_OCR_2_MODEL_ID,
+        endpoint=None,
+        api_key=None,
+        base_url="http://127.0.0.1:8000/v1",
+        api_version=None,
+    )
+
+    assert litellm_backend.template == CHANDRA_OCR_2_OCR_TEMPLATE
+    assert litellm_backend.template == hf_backend.template == openai_backend.template
+    assert litellm_backend.model_name == "chandra-ocr-2"
+    assert hf_backend.model_name == "chandra-ocr-2"
+    assert openai_backend.model_name == "chandra-ocr-2"
+    assert openai_backend.transport.config.completion_kwargs == {
+        "max_tokens": 12_384,
+        "temperature": 0.0,
+        "top_p": 0.1,
+    }
+
+
 def test_install_command_invokes_runtime_installer(
     monkeypatch: pytest.MonkeyPatch,
     cli_runner,
diff --git a/tests/test_hf_ocr.py b/tests/test_hf_ocr.py
index 78ece49..6373da5 100644
--- a/tests/test_hf_ocr.py
+++ b/tests/test_hf_ocr.py
@@ -12,15 +12,24 @@
 from churro_ocr.errors import ConfigurationError
 from churro_ocr.ocr import OCRClient
 from churro_ocr.page_detection import DocumentPage
-from churro_ocr.prompts import DEFAULT_OCR_OUTPUT_TAG, OLMOCR_V4_YAML_PROMPT, parse_olmocr_response
+from churro_ocr.prompts import (
+    CHANDRA_OCR_LAYOUT_PROMPT,
+    DEFAULT_OCR_OUTPUT_TAG,
+    OLMOCR_V4_YAML_PROMPT,
+    parse_chandra_response,
+    parse_olmocr_response,
+)
 from churro_ocr.providers import OCRBackendSpec, build_ocr_backend
 from churro_ocr.providers.hf import (
+    ChandraOCR2OCRBackend,
     Churro3BOCRBackend,
     DotsOCR15OCRBackend,
     HuggingFaceVisionOCRBackend,
 )
 from churro_ocr.providers.specs import DEFAULT_OCR_MAX_TOKENS
 from churro_ocr.templates import (
+    CHANDRA_OCR_2_MODEL_ID,
+    CHANDRA_OCR_2_OCR_TEMPLATE,
     CHURRO_3B_XML_TEMPLATE,
     DOTS_OCR_1_5_MODEL_ID,
     DOTS_OCR_1_5_OCR_PROMPT,
@@ -28,6 +37,7 @@
     OLMOCR_2_7B_1025_MODEL_ID,
     OLMOCR_2_7B_1025_OCR_TEMPLATE,
     HFChatTemplate,
+    OCRConversation,
 )
 
 
@@ -57,6 +67,16 @@ def test_olmocr_template_builds_prompt_before_image() -> None:
     assert conversation[0]["content"][1]["type"] == "image"
 
 
+def test_chandra_template_builds_image_before_prompt() -> None:
+    page = DocumentPage.from_image(Image.new("RGB", (20, 20), color="white"))
+
+    conversation = CHANDRA_OCR_2_OCR_TEMPLATE.build_conversation(page)
+
+    assert conversation[0]["role"] == "user"
+    assert conversation[0]["content"][0]["type"] == "image"
+    assert conversation[0]["content"][1]["text"] == CHANDRA_OCR_LAYOUT_PROMPT
+
+
 def test_parse_olmocr_response_extracts_plain_text_and_metadata() -> None:
     text, metadata = parse_olmocr_response(
         "---\n"
@@ -83,6 +103,51 @@ def test_parse_olmocr_response_extracts_plain_text_and_metadata() -> None:
     assert "Heading" in cast("str", metadata["raw_markdown"])
 
 
+def test_parse_chandra_response_extracts_plain_text_and_metadata() -> None:
+    text, metadata = parse_chandra_response(
+        '<div data-bbox="0 0 1000 100" data-label="Section-Header"><h1>Title</h1></div>\n'
+        '<div data-bbox="0 100 1000 300" data-label="Text"><p>Paragraph with <a '
+        'href="https://example.test">reference</a>.</p></div>\n'
+        '<div data-bbox="0 300 1000 500" data-label="Form"><p><input type="checkbox" checked> '
+        "Checked item</p></div>\n"
+        '<div data-bbox="0 500 1000 700" data-label="Table"><table><tr><th>Year</th>'
+        "<th>Value</th></tr><tr><td>1900</td><td>42</td></tr></table></div>"
+    )
+
+    assert text == "Title\n\nParagraph with reference.\n\n[x] Checked item\n\nYear | Value\n1900 | 42"
+    assert metadata == {
+        "raw_html": (
+            '<div data-bbox="0 0 1000 100" data-label="Section-Header"><h1>Title</h1></div>\n'
+            '<div data-bbox="0 100 1000 300" data-label="Text"><p>Paragraph with <a '
+            'href="https://example.test">reference</a>.</p></div>\n'
+            '<div data-bbox="0 300 1000 500" data-label="Form"><p><input type="checkbox" checked> '
+            "Checked item</p></div>\n"
+            '<div data-bbox="0 500 1000 700" data-label="Table"><table><tr><th>Year</th>'
+            "<th>Value</th></tr><tr><td>1900</td><td>42</td></tr></table></div>"
+        ),
+    }
+
+
+def test_build_ocr_backend_uses_chandra_profile_defaults_for_hf() -> None:
+    backend = cast(
+        "ChandraOCR2OCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="hf",
+                model=CHANDRA_OCR_2_MODEL_ID,
+            )
+        ),
+    )
+
+    assert isinstance(backend, ChandraOCR2OCRBackend)
+    assert backend.template == CHANDRA_OCR_2_OCR_TEMPLATE
+    assert backend.model_name == "chandra-ocr-2"
+    assert backend.generation_kwargs == {
+        "max_new_tokens": 12_384,
+    }
+    assert backend.image_preprocessor(Image.new("RGB", (5_000, 3_000), color="white")).size == (3_248, 1_932)
+
+
 def test_build_ocr_backend_uses_olmocr_profile_defaults_for_hf() -> None:
     backend = cast(
         "HuggingFaceVisionOCRBackend",
@@ -104,6 +169,158 @@ def test_build_ocr_backend_uses_olmocr_profile_defaults_for_hf() -> None:
     assert backend.image_preprocessor(Image.new("RGB", (5_000, 3_000), color="white")).size == (1_288, 772)
 
 
+@pytest.mark.asyncio
+async def test_chandra_huggingface_backend_matches_upstream_chat_template_and_eos_behavior(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    captured: dict[str, Any] = {}
+
+    class FakeAttentionMask:
+        def sum(self, dim: int) -> SimpleNamespace:
+            captured["attention_mask_sum_dim"] = dim
+            return SimpleNamespace(tolist=lambda: [3])
+
+    class FakeBatch(dict[str, object]):
+        def to(self, device: object) -> FakeBatch:
+            captured["device"] = device
+            return self
+
+    class FakeTokenizer:
+        def __init__(self) -> None:
+            self.padding_side = "right"
+
+        def convert_tokens_to_ids(self, token: str) -> int:
+            captured["stop_token_lookup"] = token
+            return 77
+
+    class FakeProcessor:
+        def __init__(self) -> None:
+            self.tokenizer = FakeTokenizer()
+
+        def apply_chat_template(
+            self,
+            conversation: object,
+            *,
+            add_generation_prompt: bool,
+            tokenize: bool = True,
+            return_dict: bool = True,
+            return_tensors: str | None = None,
+            padding: bool | None = None,
+        ) -> object:
+            captured["add_generation_prompt"] = add_generation_prompt
+            captured["tokenize"] = tokenize
+            captured["return_dict"] = return_dict
+            if not tokenize:
+                captured["render_conversation"] = conversation
+                return "<rendered>"
+            captured["tokenized_conversations"] = conversation
+            captured["return_tensors"] = return_tensors
+            captured["padding"] = padding
+            return FakeBatch(
+                {
+                    "input_ids": SimpleNamespace(shape=(1, 3)),
+                    "attention_mask": FakeAttentionMask(),
+                }
+            )
+
+        def batch_decode(
+            self,
+            generated_ids: object,
+            *,
+            skip_special_tokens: bool,
+            clean_up_tokenization_spaces: bool,
+        ) -> list[str]:
+            captured["generated_ids"] = generated_ids
+            captured["skip_special_tokens"] = skip_special_tokens
+            captured["clean_up_tokenization_spaces"] = clean_up_tokenization_spaces
+            return [
+                '<div data-bbox="0 0 1000 1000" data-label="Text"><p>Decoded '
+                '<a href="https://example.test">output</a>.</p></div>'
+            ]
+
+    class FakeProcessorCls:
+        @staticmethod
+        def from_pretrained(model_id: str, **kwargs: object) -> FakeProcessor:
+            captured["processor_model_id"] = model_id
+            captured["processor_from_pretrained_kwargs"] = kwargs
+            return FakeProcessor()
+
+    class FakeModel:
+        device = "fake-device"
+        dtype = None
+        generation_config = SimpleNamespace(eos_token_id=11)
+
+        def eval(self) -> FakeModel:
+            captured["eval_called"] = True
+            return self
+
+        def generate(self, **kwargs: object) -> list[list[int | str]]:
+            captured["generate_kwargs"] = kwargs
+            return [[0, 1, 2, "completion"]]
+
+    class FakeModelCls:
+        @staticmethod
+        def from_pretrained(model_id: str, **kwargs: object) -> FakeModel:
+            captured["model_model_id"] = model_id
+            captured["model_from_pretrained_kwargs"] = kwargs
+            return FakeModel()
+
+    monkeypatch.setattr(
+        "churro_ocr.providers.hf._load_hf_runtime",
+        lambda: SimpleNamespace(
+            processor_cls=FakeProcessorCls,
+            model_cls=FakeModelCls,
+            process_vision_info=None,
+        ),
+    )
+
+    backend = cast(
+        "ChandraOCR2OCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="hf",
+                model=CHANDRA_OCR_2_MODEL_ID,
+            )
+        ),
+    )
+    result = await backend.ocr(
+        DocumentPage.from_image(Image.new("RGBA", (5_000, 3_000), color=(255, 255, 255, 255)))
+    )
+
+    assert result.text == "Decoded output."
+    assert result.metadata == {
+        "raw_html": (
+            '<div data-bbox="0 0 1000 1000" data-label="Text"><p>Decoded '
+            '<a href="https://example.test">output</a>.</p></div>'
+        ),
+    }
+    assert captured["processor_model_id"] == CHANDRA_OCR_2_MODEL_ID
+    assert captured["model_model_id"] == CHANDRA_OCR_2_MODEL_ID
+    assert captured["eval_called"] is True
+    assert captured["render_conversation"][0]["role"] == "user"
+    render_content = cast("list[dict[str, object]]", captured["render_conversation"][0]["content"])
+    assert render_content[0]["type"] == "image"
+    render_image = cast("Image.Image", render_content[0]["image"])
+    assert render_image.size == (3_248, 1_932)
+    assert render_image.mode == "RGB"
+    assert render_content[1] == {"type": "text", "text": CHANDRA_OCR_LAYOUT_PROMPT}
+    tokenized_conversation = cast("list[OCRConversation]", captured["tokenized_conversations"])
+    assert tokenized_conversation[0][0]["role"] == "user"
+    assert captured["tokenize"] is True
+    assert captured["return_dict"] is True
+    assert captured["return_tensors"] == "pt"
+    assert captured["padding"] is True
+    assert captured["device"] == "fake-device"
+    assert captured["attention_mask_sum_dim"] == 1
+    assert captured["stop_token_lookup"] == "<|im_end|>"
+    assert captured["generate_kwargs"]["max_new_tokens"] == 12_384
+    assert captured["generate_kwargs"]["eos_token_id"] == [11, 77]
+    assert captured["model_from_pretrained_kwargs"]["device_map"] == "auto"
+    assert "dtype" in cast("dict[str, object]", captured["model_from_pretrained_kwargs"])
+    assert captured["skip_special_tokens"] is True
+    assert captured["clean_up_tokenization_spaces"] is False
+
+
 @pytest.mark.asyncio
 async def test_huggingface_vision_ocr_backend_uses_custom_template(
     monkeypatch: pytest.MonkeyPatch,
diff --git a/tests/test_providers.py b/tests/test_providers.py
index 1c70467..ca1a73e 100644
--- a/tests/test_providers.py
+++ b/tests/test_providers.py
@@ -13,6 +13,7 @@
 from churro_ocr.errors import ProviderError
 from churro_ocr.page_detection import DocumentPage
 from churro_ocr.prompts import (
+    CHANDRA_OCR_LAYOUT_PROMPT,
     DEFAULT_BOUNDARY_DETECTION_PROMPT,
     DEFAULT_OCR_OUTPUT_TAG,
     OLMOCR_V4_YAML_PROMPT,
@@ -44,6 +45,8 @@
 )
 from churro_ocr.providers.specs import DEFAULT_OCR_MAX_TOKENS
 from churro_ocr.templates import (
+    CHANDRA_OCR_2_MODEL_ID,
+    CHANDRA_OCR_2_OCR_TEMPLATE,
     DEFAULT_OCR_TEMPLATE,
     OLMOCR_2_7B_1025_FP8_MODEL_ID,
     OLMOCR_2_7B_1025_MODEL_ID,
@@ -377,6 +380,28 @@ def test_build_ocr_backend_uses_olmocr_profile_defaults_for_openai_compatible()
     assert backend.image_preprocessor(Image.new("RGB", (5_000, 3_000), color="white")).size == (1_288, 772)
 
 
+def test_build_ocr_backend_uses_chandra_profile_defaults_for_openai_compatible() -> None:
+    backend = cast(
+        "OpenAICompatibleOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="openai-compatible",
+                model=CHANDRA_OCR_2_MODEL_ID,
+                transport=LiteLLMTransportConfig(api_base="http://127.0.0.1:8000/v1"),
+            )
+        ),
+    )
+
+    assert backend.template == CHANDRA_OCR_2_OCR_TEMPLATE
+    assert backend.model_name == "chandra-ocr-2"
+    assert backend.transport.config.completion_kwargs == {
+        "max_tokens": 12_384,
+        "temperature": 0.0,
+        "top_p": 0.1,
+    }
+    assert backend.image_preprocessor(Image.new("RGB", (5_000, 3_000), color="white")).size == (3_248, 1_932)
+
+
 def test_build_ocr_backend_resolves_olmocr_fp8_profile_defaults_for_openai_compatible() -> None:
     backend = cast(
         "OpenAICompatibleOCRBackend",
@@ -494,6 +519,91 @@ async def _fake_complete_text(
     assert prompt_image.mode == "RGB"
 
 
+@pytest.mark.asyncio
+async def test_openai_compatible_backend_uses_chandra_prompt_and_plain_text_postprocessing(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    captured: dict[str, object] = {}
+
+    def _fake_prepare_messages_from_conversation(
+        self: LiteLLMTransport,
+        conversation: list[dict[str, object]],
+    ) -> list[dict[str, object]]:
+        captured["conversation"] = conversation
+        captured["completion_kwargs"] = dict(self.config.completion_kwargs)
+        return [{"role": "user", "content": [{"type": "text", "text": "prompt"}]}]
+
+    async def _fake_complete_text(
+        self: LiteLLMTransport,
+        *,
+        model: str,
+        messages: list[dict[str, object]],
+        timeout_seconds: int = 600,
+        output_json: bool = False,
+    ) -> str:
+        captured["model"] = model
+        captured["messages"] = messages
+        captured["timeout_seconds"] = timeout_seconds
+        captured["output_json"] = output_json
+        captured["completion_kwargs"] = dict(self.config.completion_kwargs)
+        return (
+            '<div data-bbox="0 0 1000 100" data-label="Section-Header"><h1>Ledger</h1></div>\n'
+            '<div data-bbox="0 100 1000 300" data-label="Text"><p>Paragraph with <a '
+            'href="https://example.test">note</a>.</p></div>\n'
+            '<div data-bbox="0 300 1000 500" data-label="Table"><table><tr><th>Year</th>'
+            "<th>Value</th></tr><tr><td>1900</td><td>42</td></tr></table></div>"
+        )
+
+    monkeypatch.setattr(
+        LiteLLMTransport,
+        "prepare_messages_from_conversation",
+        _fake_prepare_messages_from_conversation,
+    )
+    monkeypatch.setattr(LiteLLMTransport, "complete_text", _fake_complete_text)
+
+    backend = cast(
+        "OpenAICompatibleOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="openai-compatible",
+                model=CHANDRA_OCR_2_MODEL_ID,
+                transport=LiteLLMTransportConfig(api_base="http://127.0.0.1:8000/v1"),
+            )
+        ),
+    )
+    result = await backend.ocr(
+        DocumentPage.from_image(Image.new("RGBA", (5_000, 3_000), color=(255, 255, 255, 255)))
+    )
+
+    assert result.text == "Ledger\n\nParagraph with note.\n\nYear | Value\n1900 | 42"
+    assert result.metadata == {
+        "raw_html": (
+            '<div data-bbox="0 0 1000 100" data-label="Section-Header"><h1>Ledger</h1></div>\n'
+            '<div data-bbox="0 100 1000 300" data-label="Text"><p>Paragraph with <a '
+            'href="https://example.test">note</a>.</p></div>\n'
+            '<div data-bbox="0 300 1000 500" data-label="Table"><table><tr><th>Year</th>'
+            "<th>Value</th></tr><tr><td>1900</td><td>42</td></tr></table></div>"
+        ),
+    }
+    assert captured["model"] == f"openai/{CHANDRA_OCR_2_MODEL_ID}"
+    assert captured["messages"] == [{"role": "user", "content": [{"type": "text", "text": "prompt"}]}]
+    assert captured["timeout_seconds"] == 600
+    assert captured["output_json"] is False
+    assert captured["completion_kwargs"] == {
+        "max_tokens": 12_384,
+        "temperature": 0.0,
+        "top_p": 0.1,
+    }
+    conversation = cast("list[dict[str, object]]", captured["conversation"])
+    assert conversation[0]["role"] == "user"
+    user_content = cast("list[dict[str, object]]", conversation[0]["content"])
+    assert user_content[0]["type"] == "image"
+    prompt_image = cast("Image.Image", user_content[0]["image"])
+    assert prompt_image.size == (3_248, 1_932)
+    assert prompt_image.mode == "RGB"
+    assert user_content[1] == {"type": "text", "text": CHANDRA_OCR_LAYOUT_PROMPT}
+
+
 @pytest.mark.asyncio
 async def test_llm_page_detector_uses_prompt_transport(
     monkeypatch: pytest.MonkeyPatch,

From 98a3684b59e15d42137384aab523cc8ca2eb09c2 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Mon, 6 Apr 2026 01:56:17 +0000
Subject: [PATCH 10/28] fix(evaluation): initialize metrics in worker processes

---
 tests/test_tooling_evaluate_page.py | 18 +++++++
 tests/test_tooling_support.py       | 79 +++++++++++++++++++++++++++++
 tooling/evaluation/evaluate_page.py |  4 +-
 3 files changed, 100 insertions(+), 1 deletion(-)

diff --git a/tests/test_tooling_evaluate_page.py b/tests/test_tooling_evaluate_page.py
index 1963af4..d0c0293 100644
--- a/tests/test_tooling_evaluate_page.py
+++ b/tests/test_tooling_evaluate_page.py
@@ -97,3 +97,21 @@ def test_calculate_metrics_strips_output_tags_before_normalization(
     result = evaluate_page_module.calculate_metrics((example, predicted_text))
 
     assert result["normalized_predicted_text"] == expected
+
+
+def test_calculate_metrics_from_text_lazily_initializes_bleu_metric(monkeypatch) -> None:
+    init_calls = 0
+    fake_metric = SimpleNamespace(compute=lambda *_args, **_kwargs: {"bleu": 0.25})
+
+    def fake_initialize_metrics() -> None:
+        nonlocal init_calls
+        init_calls += 1
+        monkeypatch.setattr(evaluate_page_module, "bleu_metric", fake_metric)
+
+    monkeypatch.setattr(evaluate_page_module, "bleu_metric", None)
+    monkeypatch.setattr(evaluate_page_module, "initialize_metrics", fake_initialize_metrics)
+
+    result = evaluate_page_module.calculate_metrics_from_text("pred", "gold", "English", "Latin")
+
+    assert init_calls == 1
+    assert result["bleu"] == 0.25
diff --git a/tests/test_tooling_support.py b/tests/test_tooling_support.py
index af2dabe..32b3ad6 100644
--- a/tests/test_tooling_support.py
+++ b/tests/test_tooling_support.py
@@ -270,6 +270,85 @@ def test_evaluate_page_metric_helpers_cover_initialization_and_single_batch_path
     assert rows[0]["example_id"] == "row-1"
 
 
+def test_batch_evaluate_initializes_worker_metrics_for_multi_example(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    init_calls = 0
+    captured_initializer = None
+
+    def fake_initialize_metrics() -> None:
+        nonlocal init_calls
+        init_calls += 1
+
+    class _FakePool:
+        def __init__(self, *, processes: int, initializer) -> None:  # noqa: ANN001
+            nonlocal captured_initializer
+            assert processes == 2
+            captured_initializer = initializer
+
+        def __enter__(self) -> _FakePool:
+            assert captured_initializer is not None
+            captured_initializer()
+            return self
+
+        def __exit__(self, exc_type, exc, tb) -> bool:  # noqa: ANN001
+            return False
+
+        def imap(self, func, iterable):  # noqa: ANN001
+            return map(func, iterable)
+
+    monkeypatch.setattr(evaluate_page_module, "initialize_metrics", fake_initialize_metrics)
+    monkeypatch.setattr(evaluate_page_module.multiprocessing, "cpu_count", lambda: 2)
+    monkeypatch.setattr(evaluate_page_module.multiprocessing, "Pool", _FakePool)
+    monkeypatch.setattr(
+        evaluate_page_module,
+        "evaluate_page",
+        lambda inputs: cast(
+            "PageEvaluationResult",
+            {
+                "example_id": inputs[0]["example_id"],
+                "normalized_levenshtein_similarity": 1.0,
+                "is_empty": 0.0,
+            },
+        ),
+    )
+
+    aggregate, rows = evaluate_page_module.batch_evaluate(
+        dataset=[
+            cast(
+                "BenchmarkDatasetExample",
+                {
+                    "image": "image",
+                    "cleaned_transcription": "",
+                    "dataset_id": "dataset-1",
+                    "document_type": "print",
+                    "example_id": "row-1",
+                    "main_language": "English",
+                    "main_script": "Latin",
+                },
+            ),
+            cast(
+                "BenchmarkDatasetExample",
+                {
+                    "image": "image",
+                    "cleaned_transcription": "",
+                    "dataset_id": "dataset-2",
+                    "document_type": "print",
+                    "example_id": "row-2",
+                    "main_language": "English",
+                    "main_script": "Latin",
+                },
+            ),
+        ],
+        predicted_texts=["predicted-1", "predicted-2"],
+    )
+
+    assert captured_initializer is fake_initialize_metrics
+    assert init_calls == 2
+    assert aggregate == {"normalized_levenshtein_similarity": 1.0, "is_empty": 0.0}
+    assert [row["example_id"] for row in rows] == ["row-1", "row-2"]
+
+
 def test_calculate_metrics_from_text_and_internal_error_fallback(monkeypatch: pytest.MonkeyPatch) -> None:
     monkeypatch.setattr(evaluate_page_module, "initialize_metrics", lambda: None)
     monkeypatch.setattr(
diff --git a/tooling/evaluation/evaluate_page.py b/tooling/evaluation/evaluate_page.py
index 587fd16..7c9038d 100644
--- a/tooling/evaluation/evaluate_page.py
+++ b/tooling/evaluation/evaluate_page.py
@@ -91,6 +91,8 @@ def _compute_text_metrics_core(
         has_repetition_flag = has_long_repetition(predicted_text)
 
         if is_empty != 1.0:
+            if bleu_metric is None:
+                initialize_metrics()
             assert bleu_metric is not None
             bleu_result = bleu_metric.compute(
                 predictions=[predicted_text],
@@ -216,7 +218,7 @@ def batch_evaluate(
         return aggregate_results(results)
 
     processes = min(8, max(1, multiprocessing.cpu_count()))
-    with multiprocessing.Pool(processes=processes) as pool:
+    with multiprocessing.Pool(processes=processes, initializer=initialize_metrics) as pool:
         results = list(
             tqdm(
                 pool.imap(evaluate_page, zip(dataset, predicted_texts, strict=False)),

From 71d0509119605fcc2cb32de9fb96655c87358108 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Mon, 6 Apr 2026 08:03:05 +0000
Subject: [PATCH 11/28] feat(hf): add Liquid LFM2.5-VL OCR backend

---
 src/churro_ocr/providers/builder.py  |   3 +
 src/churro_ocr/providers/hf.py       | 134 +++++++++++
 src/churro_ocr/providers/specs.py    |  84 ++++++-
 src/churro_ocr/templates/__init__.py |   4 +
 src/churro_ocr/templates/presets.py  |   7 +
 tests/test_hf_ocr.py                 | 321 ++++++++++++++++++++++++++-
 6 files changed, 551 insertions(+), 2 deletions(-)

diff --git a/src/churro_ocr/providers/builder.py b/src/churro_ocr/providers/builder.py
index 216ed12..706f591 100644
--- a/src/churro_ocr/providers/builder.py
+++ b/src/churro_ocr/providers/builder.py
@@ -9,6 +9,7 @@
     ChandraOCR2OCRBackend,
     DotsOCR15OCRBackend,
     HuggingFaceVisionOCRBackend,
+    LFM25VLOCRBackend,
     _default_dots_ocr_1_5_model_kwargs,
 )
 from churro_ocr.providers.ocr import (
@@ -166,6 +167,8 @@ def _build_huggingface_backend(spec: OCRBackendSpec, profile: OCRModelProfile) -
         model_kwargs = _merge_mapping(_default_dots_ocr_1_5_model_kwargs(), model_kwargs)
     elif options.backend_variant == "chandra-ocr-2":
         backend_cls = ChandraOCR2OCRBackend
+    elif options.backend_variant == "lfm2.5-vl":
+        backend_cls = LFM25VLOCRBackend
     return backend_cls(
         model_id=spec.model,
         template=profile.template,
diff --git a/src/churro_ocr/providers/hf.py b/src/churro_ocr/providers/hf.py
index f3ad5a0..f0b73b0 100644
--- a/src/churro_ocr/providers/hf.py
+++ b/src/churro_ocr/providers/hf.py
@@ -35,6 +35,8 @@
     CHURRO_3B_XML_TEMPLATE,
     DOTS_OCR_1_5_MODEL_ID,
     DOTS_OCR_1_5_OCR_TEMPLATE,
+    LFM2_5_VL_1_6B_MODEL_ID,
+    LFM2_5_VL_1_6B_OCR_TEMPLATE,
     OCRConversation,
     OCRPromptTemplateLike,
 )
@@ -662,9 +664,141 @@ def _get_model(self, runtime: _HFRuntime) -> Any:
         return self._model
 
 
+@dataclass(slots=True)
+class LFM25VLOCRBackend(HuggingFaceVisionOCRBackend):
+    """Preset OCR backend for ``LiquidAI/LFM2.5-VL-1.6B``."""
+
+    model_id: str = LFM2_5_VL_1_6B_MODEL_ID
+    template: OCRPromptTemplateLike = LFM2_5_VL_1_6B_OCR_TEMPLATE
+    model_name: str | None = "LFM2.5-VL-1.6B"
+    _has_tied_lm_head: bool = field(default=False, init=False, repr=False)
+
+    def _get_processor(self, runtime: _HFRuntime) -> Any:
+        processor = super()._get_processor(runtime)
+        tokenizer = getattr(processor, "tokenizer", None)
+        if tokenizer is not None and getattr(tokenizer, "padding_side", None) != "left":
+            tokenizer.padding_side = "left"
+        return processor
+
+    def _get_model(self, runtime: _HFRuntime) -> Any:
+        model = super()._get_model(runtime)
+        if self._has_tied_lm_head:
+            return model
+
+        with self._init_lock:
+            if self._has_tied_lm_head:
+                return model
+            lm_head = getattr(model, "lm_head", None)
+            get_input_embeddings = getattr(model, "get_input_embeddings", None)
+            if lm_head is None or not callable(get_input_embeddings):
+                self._has_tied_lm_head = True
+                return model
+            input_embeddings = get_input_embeddings()
+            weight = getattr(input_embeddings, "weight", None)
+            if weight is not None:
+                lm_head.weight = weight
+            self._has_tied_lm_head = True
+        return model
+
+    def _build_lfm_batch(
+        self,
+        processor: Any,
+        conversations: OCRConversation | list[OCRConversation],
+        *,
+        padding: bool,
+    ) -> Any:
+        processor_apply = getattr(processor, "apply_chat_template", None)
+        if not callable(processor_apply):
+            raise ConfigurationError(
+                "Liquid LFM2.5-VL requires `processor.apply_chat_template(...)` support."
+            )
+        return processor_apply(
+            conversations,
+            add_generation_prompt=True,
+            tokenize=True,
+            return_dict=True,
+            return_tensors="pt",
+            padding=padding,
+        )
+
+    def _ocr_sync(self, page: DocumentPage) -> OCRResult:
+        prepared_page = preprocess_backend_page(
+            page,
+            image_preprocessor=self.image_preprocessor,
+        )
+        runtime = self._load_runtime()
+        processor = self._get_processor(runtime)
+        model = self._get_model(runtime)
+
+        rendered, conversation = render_ocr_prompt(
+            processor,
+            self.template,
+            prepared_page,
+            add_generation_prompt=True,
+        )
+        self._log_prompt_payload(
+            rendered_prompt=rendered,
+            conversation=conversation,
+            batch_size=1,
+        )
+        batch = self._build_lfm_batch(processor, conversation, padding=False)
+        batch = _move_batch_to_model(batch, model)
+        generated_ids = model.generate(**batch, **self.generation_kwargs)
+        text = _decode_completion_texts(processor, batch, generated_ids)[0]
+        return build_ocr_result(
+            text,
+            provider_name=self.provider_name,
+            model_name=self.model_name or self.model_id,
+            text_postprocessor=self.text_postprocessor,
+        )
+
+    def _ocr_batch_sync(self, pages: list[DocumentPage]) -> list[OCRResult]:
+        if not pages:
+            return []
+
+        runtime = self._load_runtime()
+        processor = self._get_processor(runtime)
+        model = self._get_model(runtime)
+        conversations: list[OCRConversation] = []
+
+        for page in pages:
+            prepared_page = preprocess_backend_page(
+                page,
+                image_preprocessor=self.image_preprocessor,
+            )
+            rendered, conversation = render_ocr_prompt(
+                processor,
+                self.template,
+                prepared_page,
+                add_generation_prompt=True,
+            )
+            conversations.append(conversation)
+            if not self._has_logged_prompt:
+                self._log_prompt_payload(
+                    rendered_prompt=rendered,
+                    conversation=conversation,
+                    batch_size=len(pages),
+                )
+
+        batch = self._build_lfm_batch(processor, conversations, padding=True)
+        batch = _move_batch_to_model(batch, model)
+        generated_ids = model.generate(**batch, **self.generation_kwargs)
+        texts = _decode_completion_texts(processor, batch, generated_ids)
+        return [
+            build_ocr_result(
+                text,
+                provider_name=self.provider_name,
+                model_name=self.model_name or self.model_id,
+                text_postprocessor=self.text_postprocessor,
+            )
+            for text in texts
+        ]
+
+
 __all__ = [
     "ChandraOCR2OCRBackend",
     "Churro3BOCRBackend",
     "DotsOCR15OCRBackend",
     "HuggingFaceVisionOCRBackend",
+    "LFM25VLOCRBackend",
 ]
diff --git a/src/churro_ocr/providers/specs.py b/src/churro_ocr/providers/specs.py
index 43f46c9..1b753c0 100644
--- a/src/churro_ocr/providers/specs.py
+++ b/src/churro_ocr/providers/specs.py
@@ -2,9 +2,10 @@
 
 from __future__ import annotations
 
-from collections.abc import Callable
+from collections.abc import Callable, Sequence
 from dataclasses import dataclass, field
 from pathlib import Path
+import re
 from typing import TYPE_CHECKING, Any, Literal
 
 from PIL import Image
@@ -24,6 +25,8 @@
     DEFAULT_OCR_TEMPLATE,
     DOTS_OCR_1_5_MODEL_ID,
     DOTS_OCR_1_5_OCR_TEMPLATE,
+    LFM2_5_VL_1_6B_MODEL_ID,
+    LFM2_5_VL_1_6B_OCR_TEMPLATE,
     OLMOCR_2_7B_1025_FP8_MODEL_ID,
     OLMOCR_2_7B_1025_MODEL_ID,
     OLMOCR_2_7B_1025_OCR_TEMPLATE,
@@ -76,6 +79,56 @@ def default_ocr_text_postprocessor(text: str) -> str:
     return strip_ocr_output_tag(text, output_tag=DEFAULT_OCR_OUTPUT_TAG)
 
 
+_CHAT_ROLE_PREFIXES = {
+    "assistant",
+    "assistant:",
+    "user",
+    "user:",
+    "system",
+    "system:",
+    "<assistant>",
+    "<user>",
+    "<system>",
+    "<|assistant|>",
+    "<|user|>",
+    "<|system|>",
+}
+
+
+def _strip_leading_chat_scaffold(text: str, *, prompts: Sequence[str]) -> str:
+    """Remove echoed prompts and leading chat role markers from model output."""
+    cleaned = text.strip()
+    if not cleaned:
+        return ""
+
+    normalized_prompts = tuple(prompt.strip() for prompt in prompts if prompt and prompt.strip())
+    for _ in range(8):
+        previous = cleaned
+        lowered = cleaned.casefold()
+        stripped_prompt = False
+        for prompt in normalized_prompts:
+            if lowered.startswith(prompt.casefold()):
+                cleaned = cleaned[len(prompt) :].lstrip()
+                stripped_prompt = True
+                break
+        if stripped_prompt:
+            continue
+
+        lines = cleaned.splitlines()
+        if not lines:
+            return ""
+        first_line = lines[0].strip()
+        if first_line.casefold() in _CHAT_ROLE_PREFIXES:
+            cleaned = "\n".join(lines[1:]).lstrip()
+            continue
+        if re.fullmatch(r"<\|?(?:assistant|user|system)\|?>", first_line, flags=re.IGNORECASE):
+            cleaned = "\n".join(lines[1:]).lstrip()
+            continue
+        if cleaned == previous:
+            break
+    return cleaned.strip()
+
+
 def olmocr_image_preprocessor(image: Image.Image) -> Image.Image:
     """Resize an image to olmOCR's expected 1288px longest side and normalize to RGB."""
     return ensure_rgb(
@@ -92,6 +145,13 @@ def olmocr_text_postprocessor(text: str) -> TextPostprocessorResult:
     return parse_olmocr_response(text)
 
 
+def lfm2_5_vl_text_postprocessor(text: str) -> str:
+    """Strip Liquid LFM2.5-VL chat scaffold and OCR wrapper tags."""
+    prompt = getattr(LFM2_5_VL_1_6B_OCR_TEMPLATE, "user_prompt", None)
+    cleaned = _strip_leading_chat_scaffold(text, prompts=[prompt] if isinstance(prompt, str) else [])
+    return strip_ocr_output_tag(cleaned, output_tag=DEFAULT_OCR_OUTPUT_TAG)
+
+
 def chandra_image_preprocessor(image: Image.Image) -> Image.Image:
     """Resize an image using Chandra OCR 2's pixel-budget and 28px-grid scaling."""
     width, height = image.size
@@ -344,6 +404,24 @@ def _olmocr_profile(*, profile_name: str, display_name: str) -> OCRModelProfile:
     )
 
 
+def lfm2_5_vl_1_6b_profile() -> OCRModelProfile:
+    """Return the built-in ``LiquidAI/LFM2.5-VL-1.6B`` OCR profile."""
+    return OCRModelProfile(
+        profile_name=LFM2_5_VL_1_6B_MODEL_ID,
+        template=LFM2_5_VL_1_6B_OCR_TEMPLATE,
+        text_postprocessor=lfm2_5_vl_text_postprocessor,
+        display_name="LFM2.5-VL-1.6B",
+        huggingface=HuggingFaceOptions(
+            generation_kwargs={
+                "max_new_tokens": 512,
+                "do_sample": False,
+                "repetition_penalty": 1.05,
+            },
+            backend_variant="lfm2.5-vl",
+        ),
+    )
+
+
 def olmocr_2_7b_1025_profile() -> OCRModelProfile:
     """Return the built-in ``allenai/olmOCR-2-7B-1025`` OCR profile."""
     return _olmocr_profile(
@@ -365,6 +443,7 @@ def _profile_registry() -> dict[str, OCRModelProfile]:
     churro_profile = churro_3b_profile()
     chandra_profile = chandra_ocr_2_profile()
     dots_profile = dots_ocr_1_5_profile()
+    lfm2_5_vl_profile = lfm2_5_vl_1_6b_profile()
     olmocr_profile = olmocr_2_7b_1025_profile()
     olmocr_fp8_profile = olmocr_2_7b_1025_fp8_profile()
     return {
@@ -372,6 +451,7 @@ def _profile_registry() -> dict[str, OCRModelProfile]:
         churro_profile.profile_name: churro_profile,
         chandra_profile.profile_name: chandra_profile,
         dots_profile.profile_name: dots_profile,
+        lfm2_5_vl_profile.profile_name: lfm2_5_vl_profile,
         olmocr_profile.profile_name: olmocr_profile,
         olmocr_fp8_profile.profile_name: olmocr_fp8_profile,
     }
@@ -415,6 +495,8 @@ def resolve_ocr_profile(
     "default_ocr_text_postprocessor",
     "HuggingFaceOptions",
     "identity_text_postprocessor",
+    "lfm2_5_vl_text_postprocessor",
+    "lfm2_5_vl_1_6b_profile",
     "ImagePreprocessor",
     "LiteLLMTransportConfig",
     "MistralOptions",
diff --git a/src/churro_ocr/templates/__init__.py b/src/churro_ocr/templates/__init__.py
index d8a1f30..64c264c 100644
--- a/src/churro_ocr/templates/__init__.py
+++ b/src/churro_ocr/templates/__init__.py
@@ -17,6 +17,8 @@
     DOTS_OCR_1_5_MODEL_ID,
     DOTS_OCR_1_5_OCR_PROMPT,
     DOTS_OCR_1_5_OCR_TEMPLATE,
+    LFM2_5_VL_1_6B_MODEL_ID,
+    LFM2_5_VL_1_6B_OCR_TEMPLATE,
     OLMOCR_2_7B_1025_FP8_MODEL_ID,
     OLMOCR_2_7B_1025_MODEL_ID,
     OLMOCR_2_7B_1025_OCR_TEMPLATE,
@@ -32,6 +34,8 @@
     "DOTS_OCR_1_5_MODEL_ID",
     "DOTS_OCR_1_5_OCR_PROMPT",
     "DOTS_OCR_1_5_OCR_TEMPLATE",
+    "LFM2_5_VL_1_6B_MODEL_ID",
+    "LFM2_5_VL_1_6B_OCR_TEMPLATE",
     "HFChatTemplate",
     "OLMOCR_2_7B_1025_FP8_MODEL_ID",
     "OLMOCR_2_7B_1025_MODEL_ID",
diff --git a/src/churro_ocr/templates/presets.py b/src/churro_ocr/templates/presets.py
index ffd6009..e9c6464 100644
--- a/src/churro_ocr/templates/presets.py
+++ b/src/churro_ocr/templates/presets.py
@@ -15,6 +15,7 @@
 DOTS_OCR_1_5_MODEL_ID = "kristaller486/dots.ocr-1.5"
 OLMOCR_2_7B_1025_MODEL_ID = "allenai/olmOCR-2-7B-1025"
 OLMOCR_2_7B_1025_FP8_MODEL_ID = "allenai/olmOCR-2-7B-1025-FP8"
+LFM2_5_VL_1_6B_MODEL_ID = "LiquidAI/LFM2.5-VL-1.6B"
 DEFAULT_OCR_TEMPLATE = HFChatTemplate(
     system_message=DEFAULT_OCR_SYSTEM_PROMPT,
     user_prompt=DEFAULT_OCR_USER_PROMPT,
@@ -38,6 +39,10 @@
     user_prompt=OLMOCR_V4_YAML_PROMPT,
     user_prompt_first=True,
 )
+LFM2_5_VL_1_6B_OCR_TEMPLATE = HFChatTemplate(
+    system_message=None,
+    user_prompt="Transcribe all visible text from this historical document page in reading order.",
+)
 
 
 __all__ = [
@@ -52,4 +57,6 @@
     "OLMOCR_2_7B_1025_FP8_MODEL_ID",
     "OLMOCR_2_7B_1025_MODEL_ID",
     "OLMOCR_2_7B_1025_OCR_TEMPLATE",
+    "LFM2_5_VL_1_6B_MODEL_ID",
+    "LFM2_5_VL_1_6B_OCR_TEMPLATE",
 ]
diff --git a/tests/test_hf_ocr.py b/tests/test_hf_ocr.py
index 6373da5..e7a4e2c 100644
--- a/tests/test_hf_ocr.py
+++ b/tests/test_hf_ocr.py
@@ -25,8 +25,9 @@
     Churro3BOCRBackend,
     DotsOCR15OCRBackend,
     HuggingFaceVisionOCRBackend,
+    LFM25VLOCRBackend,
 )
-from churro_ocr.providers.specs import DEFAULT_OCR_MAX_TOKENS
+from churro_ocr.providers.specs import DEFAULT_OCR_MAX_TOKENS, lfm2_5_vl_text_postprocessor
 from churro_ocr.templates import (
     CHANDRA_OCR_2_MODEL_ID,
     CHANDRA_OCR_2_OCR_TEMPLATE,
@@ -34,6 +35,8 @@
     DOTS_OCR_1_5_MODEL_ID,
     DOTS_OCR_1_5_OCR_PROMPT,
     DOTS_OCR_1_5_OCR_TEMPLATE,
+    LFM2_5_VL_1_6B_MODEL_ID,
+    LFM2_5_VL_1_6B_OCR_TEMPLATE,
     OLMOCR_2_7B_1025_MODEL_ID,
     OLMOCR_2_7B_1025_OCR_TEMPLATE,
     HFChatTemplate,
@@ -128,6 +131,22 @@ def test_parse_chandra_response_extracts_plain_text_and_metadata() -> None:
     }
 
 
+def test_lfm25_text_postprocessor_strips_prompt_and_role_scaffold() -> None:
+    text = (
+        "Transcribe all visible text from this historical document page in reading order.\n"
+        "assistant\n"
+        f"<{DEFAULT_OCR_OUTPUT_TAG}>\n"
+        "decoded text\n"
+        f"</{DEFAULT_OCR_OUTPUT_TAG}>"
+    )
+
+    assert lfm2_5_vl_text_postprocessor(text) == "decoded text"
+
+
+def test_lfm25_text_postprocessor_strips_role_only_prefix() -> None:
+    assert lfm2_5_vl_text_postprocessor("assistant:\nplain text") == "plain text"
+
+
 def test_build_ocr_backend_uses_chandra_profile_defaults_for_hf() -> None:
     backend = cast(
         "ChandraOCR2OCRBackend",
@@ -169,6 +188,27 @@ def test_build_ocr_backend_uses_olmocr_profile_defaults_for_hf() -> None:
     assert backend.image_preprocessor(Image.new("RGB", (5_000, 3_000), color="white")).size == (1_288, 772)
 
 
+def test_build_ocr_backend_uses_lfm25_profile_defaults_for_hf() -> None:
+    backend = cast(
+        "LFM25VLOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="hf",
+                model=LFM2_5_VL_1_6B_MODEL_ID,
+            )
+        ),
+    )
+
+    assert isinstance(backend, LFM25VLOCRBackend)
+    assert backend.template == LFM2_5_VL_1_6B_OCR_TEMPLATE
+    assert backend.model_name == "LFM2.5-VL-1.6B"
+    assert backend.generation_kwargs == {
+        "max_new_tokens": 512,
+        "do_sample": False,
+        "repetition_penalty": 1.05,
+    }
+
+
 @pytest.mark.asyncio
 async def test_chandra_huggingface_backend_matches_upstream_chat_template_and_eos_behavior(
     monkeypatch: pytest.MonkeyPatch,
@@ -321,6 +361,285 @@ def from_pretrained(model_id: str, **kwargs: object) -> FakeModel:
     assert captured["clean_up_tokenization_spaces"] is False
 
 
+@pytest.mark.asyncio
+async def test_lfm25_huggingface_backend_uses_tokenized_chat_template_and_ties_lm_head(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    captured: dict[str, Any] = {}
+
+    class FakeAttentionMask:
+        def sum(self, dim: int) -> SimpleNamespace:
+            captured["attention_mask_sum_dim"] = dim
+            return SimpleNamespace(tolist=lambda: [4])
+
+    class FakeBatch(dict[str, object]):
+        def to(self, device: object) -> FakeBatch:
+            captured["device"] = device
+            return self
+
+    class FakeProcessor:
+        def __init__(self) -> None:
+            self.tokenizer = SimpleNamespace(padding_side="right")
+
+        def apply_chat_template(
+            self,
+            conversation: object,
+            *,
+            add_generation_prompt: bool,
+            tokenize: bool,
+            return_dict: bool | None = None,
+            return_tensors: str | None = None,
+            padding: bool | None = None,
+        ) -> object:
+            captured.setdefault("chat_calls", []).append(
+                {
+                    "conversation": conversation,
+                    "add_generation_prompt": add_generation_prompt,
+                    "tokenize": tokenize,
+                    "return_dict": return_dict,
+                    "return_tensors": return_tensors,
+                    "padding": padding,
+                }
+            )
+            if not tokenize:
+                return "<lfm-rendered>"
+            return FakeBatch(
+                {
+                    "input_ids": SimpleNamespace(shape=(1, 4)),
+                    "attention_mask": FakeAttentionMask(),
+                }
+            )
+
+        def __call__(self, **kwargs: object) -> object:
+            raise AssertionError("processor(...) should not be used for LFM2.5-VL")
+
+        def batch_decode(
+            self,
+            generated_ids: object,
+            *,
+            skip_special_tokens: bool,
+            clean_up_tokenization_spaces: bool,
+        ) -> list[str]:
+            captured["generated_ids"] = generated_ids
+            captured["skip_special_tokens"] = skip_special_tokens
+            captured["clean_up_tokenization_spaces"] = clean_up_tokenization_spaces
+            return ["lfm transcription"]
+
+    class FakeProcessorCls:
+        @staticmethod
+        def from_pretrained(model_id: str, **kwargs: object) -> FakeProcessor:
+            captured["processor_model_id"] = model_id
+            captured["processor_from_pretrained_kwargs"] = kwargs
+            return FakeProcessor()
+
+    class FakeLmHead:
+        weight = "original-weight"
+
+    class FakeModel:
+        device = "fake-device"
+        dtype = None
+
+        def __init__(self) -> None:
+            self.lm_head = FakeLmHead()
+
+        def get_input_embeddings(self) -> SimpleNamespace:
+            captured["get_input_embeddings_called"] = True
+            return SimpleNamespace(weight="tied-weight")
+
+        def generate(self, **kwargs: object) -> list[list[int | str]]:
+            captured["generate_kwargs"] = kwargs
+            return [[0, 1, 2, 3, "completion"]]
+
+    class FakeModelCls:
+        @staticmethod
+        def from_pretrained(model_id: str, **kwargs: object) -> FakeModel:
+            captured["model_model_id"] = model_id
+            captured["model_from_pretrained_kwargs"] = kwargs
+            model = FakeModel()
+            captured["model"] = model
+            return model
+
+    monkeypatch.setattr(
+        "churro_ocr.providers.hf._load_hf_runtime",
+        lambda: SimpleNamespace(
+            processor_cls=FakeProcessorCls,
+            model_cls=FakeModelCls,
+            process_vision_info=None,
+        ),
+    )
+
+    backend = cast(
+        "LFM25VLOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="hf",
+                model=LFM2_5_VL_1_6B_MODEL_ID,
+            )
+        ),
+    )
+    result = await backend.ocr(DocumentPage.from_image(Image.new("RGB", (32, 32), color="white")))
+
+    assert result.text == "lfm transcription"
+    assert captured["processor_model_id"] == LFM2_5_VL_1_6B_MODEL_ID
+    assert captured["model_model_id"] == LFM2_5_VL_1_6B_MODEL_ID
+    assert captured["get_input_embeddings_called"] is True
+    assert cast("FakeModel", captured["model"]).lm_head.weight == "tied-weight"
+    assert cast("FakeProcessor", backend._processor).tokenizer.padding_side == "left"
+    assert len(cast("list[dict[str, object]]", captured["chat_calls"])) == 2
+    assert cast("list[dict[str, object]]", captured["chat_calls"])[0]["tokenize"] is False
+    assert cast("list[dict[str, object]]", captured["chat_calls"])[1]["tokenize"] is True
+    assert cast("list[dict[str, object]]", captured["chat_calls"])[1]["return_dict"] is True
+    assert cast("list[dict[str, object]]", captured["chat_calls"])[1]["return_tensors"] == "pt"
+    assert cast("list[dict[str, object]]", captured["chat_calls"])[1]["padding"] is False
+    assert captured["device"] == "fake-device"
+    assert captured["attention_mask_sum_dim"] == 1
+    assert captured["generate_kwargs"] == {
+        "input_ids": SimpleNamespace(shape=(1, 4)),
+        "attention_mask": cast("object", captured["generate_kwargs"]["attention_mask"]),
+        "max_new_tokens": 512,
+        "do_sample": False,
+        "repetition_penalty": 1.05,
+    }
+    assert captured["generated_ids"] == [["completion"]]
+    assert captured["skip_special_tokens"] is True
+    assert captured["clean_up_tokenization_spaces"] is False
+
+
+@pytest.mark.asyncio
+async def test_lfm25_huggingface_backend_batches_pages_with_tokenized_chat_template(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    captured: dict[str, Any] = {}
+
+    class FakeAttentionMask:
+        def sum(self, dim: int) -> SimpleNamespace:
+            captured["attention_mask_sum_dim"] = dim
+            return SimpleNamespace(tolist=lambda: [4, 4])
+
+    class FakeBatch(dict[str, object]):
+        def to(self, device: object) -> FakeBatch:
+            captured["device"] = device
+            return self
+
+    class FakeProcessor:
+        def __init__(self) -> None:
+            self.tokenizer = SimpleNamespace(padding_side="right")
+
+        def apply_chat_template(
+            self,
+            conversation: object,
+            *,
+            add_generation_prompt: bool,
+            tokenize: bool,
+            return_dict: bool | None = None,
+            return_tensors: str | None = None,
+            padding: bool | None = None,
+        ) -> object:
+            captured.setdefault("chat_calls", []).append(
+                {
+                    "conversation": conversation,
+                    "add_generation_prompt": add_generation_prompt,
+                    "tokenize": tokenize,
+                    "return_dict": return_dict,
+                    "return_tensors": return_tensors,
+                    "padding": padding,
+                }
+            )
+            if not tokenize:
+                return "<lfm-rendered>"
+            return FakeBatch(
+                {
+                    "input_ids": SimpleNamespace(shape=(2, 4)),
+                    "attention_mask": FakeAttentionMask(),
+                }
+            )
+
+        def __call__(self, **kwargs: object) -> object:
+            raise AssertionError("processor(...) should not be used for LFM2.5-VL batches")
+
+        def batch_decode(
+            self,
+            generated_ids: object,
+            *,
+            skip_special_tokens: bool,
+            clean_up_tokenization_spaces: bool,
+        ) -> list[str]:
+            captured["generated_ids"] = generated_ids
+            captured["skip_special_tokens"] = skip_special_tokens
+            captured["clean_up_tokenization_spaces"] = clean_up_tokenization_spaces
+            return ["first transcription", "second transcription"]
+
+    class FakeProcessorCls:
+        @staticmethod
+        def from_pretrained(model_id: str, **kwargs: object) -> FakeProcessor:
+            captured["processor_model_id"] = model_id
+            captured["processor_from_pretrained_kwargs"] = kwargs
+            return FakeProcessor()
+
+    class FakeLmHead:
+        weight = "original-weight"
+
+    class FakeModel:
+        device = "fake-device"
+        dtype = None
+
+        def __init__(self) -> None:
+            self.lm_head = FakeLmHead()
+
+        def get_input_embeddings(self) -> SimpleNamespace:
+            return SimpleNamespace(weight="tied-weight")
+
+        def generate(self, **kwargs: object) -> list[list[int | str]]:
+            captured["generate_kwargs"] = kwargs
+            return [
+                [0, 1, 2, 3, "first"],
+                [0, 1, 2, 3, "second"],
+            ]
+
+    class FakeModelCls:
+        @staticmethod
+        def from_pretrained(model_id: str, **kwargs: object) -> FakeModel:
+            captured["model_model_id"] = model_id
+            captured["model_from_pretrained_kwargs"] = kwargs
+            return FakeModel()
+
+    monkeypatch.setattr(
+        "churro_ocr.providers.hf._load_hf_runtime",
+        lambda: SimpleNamespace(
+            processor_cls=FakeProcessorCls,
+            model_cls=FakeModelCls,
+            process_vision_info=None,
+        ),
+    )
+
+    backend = cast(
+        "LFM25VLOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="hf",
+                model=LFM2_5_VL_1_6B_MODEL_ID,
+            )
+        ),
+    )
+    results = await backend.ocr_batch(
+        [
+            DocumentPage.from_image(Image.new("RGB", (32, 32), color="white")),
+            DocumentPage.from_image(Image.new("RGB", (32, 32), color="white")),
+        ]
+    )
+
+    assert [result.text for result in results] == ["first transcription", "second transcription"]
+    assert cast("FakeProcessor", backend._processor).tokenizer.padding_side == "left"
+    assert len(cast("list[dict[str, object]]", captured["chat_calls"])) == 3
+    assert cast("list[dict[str, object]]", captured["chat_calls"])[2]["tokenize"] is True
+    assert cast("list[dict[str, object]]", captured["chat_calls"])[2]["padding"] is True
+    assert captured["device"] == "fake-device"
+    assert captured["attention_mask_sum_dim"] == 1
+    assert captured["generated_ids"] == [["first"], ["second"]]
+    assert captured["skip_special_tokens"] is True
+    assert captured["clean_up_tokenization_spaces"] is False
+
+
 @pytest.mark.asyncio
 async def test_huggingface_vision_ocr_backend_uses_custom_template(
     monkeypatch: pytest.MonkeyPatch,

From aaac23ac5cce0fe6a742f02c0e9bdf175c963e6c Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Mon, 6 Apr 2026 08:04:00 +0000
Subject: [PATCH 12/28] fix(mistral): require pinned OCR models and retry
 transient failures

---
 docs/cli.md                          |   2 +-
 docs/guides/providers.md             |   6 +-
 src/churro_ocr/cli.py                |  11 +-
 src/churro_ocr/providers/builder.py  |   3 +-
 src/churro_ocr/providers/ocr.py      |  73 ++++++++-
 src/churro_ocr/providers/specs.py    |  27 +++-
 tests/test_cli.py                    |  26 ++++
 tests/test_cli_contract.py           |   8 +
 tests/test_provider_api_contracts.py |  21 ++-
 tests/test_providers.py              | 217 ++++++++++++++++++++++++++-
 tests/test_tooling_benchmark.py      |  25 +++
 tooling/benchmarking/benchmark.py    |  21 ++-
 12 files changed, 421 insertions(+), 19 deletions(-)

diff --git a/docs/cli.md b/docs/cli.md
index f7a1a95..4c85737 100644
--- a/docs/cli.md
+++ b/docs/cli.md
@@ -88,7 +88,7 @@ churro-ocr extract-pages \
 | `litellm` | `--model` | Uses LiteLLM credentials and routing. `--base-url`, `--api-key`, and `--api-version` are optional transport overrides. |
 | `openai-compatible` | `--model`, `--base-url` | For local or self-hosted OpenAI-style servers. `--api-key` is optional. |
 | `azure` | `--endpoint`, `--api-key` | `--model` is optional. |
-| `mistral` | `--api-key` | `--model` defaults to `mistral-ocr-latest`. |
+| `mistral` | `--api-key`, `--model` | `--model` must be either `mistral-ocr-2505` or `mistral-ocr-2512`. |
 | `hf` | `--model` | Local Transformers OCR. |
 
 ### `extract-pages` Detectors
diff --git a/docs/guides/providers.md b/docs/guides/providers.md
index f12565d..90afda1 100644
--- a/docs/guides/providers.md
+++ b/docs/guides/providers.md
@@ -97,7 +97,7 @@ from churro_ocr.providers import MistralOptions, OCRBackendSpec, build_ocr_backe
 backend = build_ocr_backend(
     OCRBackendSpec(
         provider="mistral",
-        model="mistral-ocr-latest",
+        model="mistral-ocr-2512",
         options=MistralOptions(api_key="<mistral-api-key>"),
     )
 )
@@ -152,7 +152,7 @@ Built-in model-specific profiles are resolved automatically for known models suc
 | Field | Meaning |
 | --- | --- |
 | `provider` | One of `litellm`, `openai-compatible`, `azure`, `mistral`, or `hf`. |
-| `model` | Required for `litellm`, `openai-compatible`, and `hf`. Optional for `azure`. Defaults to `mistral-ocr-latest` when omitted for `mistral`. |
+| `model` | Required for `litellm`, `openai-compatible`, `mistral`, and `hf`. Optional for `azure`. For `mistral`, use one of `mistral-ocr-2505` or `mistral-ocr-2512`. |
 | `profile` | `None`, a built-in profile name, or a custom `OCRModelProfile`. |
 | `transport` | Shared request transport config for LiteLLM-based providers. |
 | `options` | Provider-specific dataclass matching `provider`. |
@@ -165,7 +165,7 @@ Built-in model-specific profiles are resolved automatically for known models suc
 | `OpenAICompatibleOptions` | `openai-compatible` | None | Use `model_prefix` when your local server expects a provider prefix. |
 | `HuggingFaceOptions` | `hf` | None | Carries runtime, processor, generation, and template options. |
 | `AzureDocumentIntelligenceOptions` | `azure` | `endpoint`, `api_key` | `model` is optional for Azure OCR in `OCRBackendSpec`. |
-| `MistralOptions` | `mistral` | `api_key` | `model` defaults to `mistral-ocr-latest` when omitted. |
+| `MistralOptions` | `mistral` | `api_key` | `model` is required and must be `mistral-ocr-2505` or `mistral-ocr-2512`. |
 
 ## Advanced Customization
 
diff --git a/src/churro_ocr/cli.py b/src/churro_ocr/cli.py
index 5c4d41f..9a00b21 100644
--- a/src/churro_ocr/cli.py
+++ b/src/churro_ocr/cli.py
@@ -24,10 +24,15 @@
     OpenAICompatibleOptions,
     build_ocr_backend,
 )
+from churro_ocr.providers.specs import MISTRAL_OCR_MODEL_IDS, validate_mistral_ocr_model
 
 app = typer.Typer(help="churro-ocr library-first CLI")
 
 _INSTALL_TARGET_METAVAR = "{" + "|".join(INSTALL_TARGETS) + "}"
+_MISTRAL_MODEL_OPTION_ERROR = (
+    "--model is required for backend=mistral and must be one of: "
+    + ", ".join(MISTRAL_OCR_MODEL_IDS)
+)
 
 
 def _build_ocr_backend(
@@ -84,10 +89,14 @@ def _build_ocr_backend(
     if backend == "mistral":
         if not api_key:
             raise typer.BadParameter("--api-key is required for backend=mistral")
+        try:
+            mistral_model = validate_mistral_ocr_model(model)
+        except ConfigurationError as exc:
+            raise typer.BadParameter(_MISTRAL_MODEL_OPTION_ERROR) from exc
         return build_ocr_backend(
             OCRBackendSpec(
                 provider="mistral",
-                model=model or "mistral-ocr-latest",
+                model=mistral_model,
                 options=MistralOptions(api_key=api_key),
             )
         )
diff --git a/src/churro_ocr/providers/builder.py b/src/churro_ocr/providers/builder.py
index 706f591..8845f46 100644
--- a/src/churro_ocr/providers/builder.py
+++ b/src/churro_ocr/providers/builder.py
@@ -27,6 +27,7 @@
     OCRModelProfile,
     OpenAICompatibleOptions,
     resolve_ocr_profile,
+    validate_mistral_ocr_model,
 )
 
 
@@ -204,7 +205,7 @@ def _build_mistral_backend(spec: OCRBackendSpec, profile: OCRModelProfile) -> OC
     options = _ensure_options_type(spec.options, MistralOptions, provider=spec.provider)
     if options is None or not options.api_key:
         raise ConfigurationError("OCR provider 'mistral' requires MistralOptions(api_key=...).")
-    model = spec.model or "mistral-ocr-latest"
+    model = validate_mistral_ocr_model(spec.model)
     return MistralOCRBackend(
         api_key=options.api_key,
         model=model,
diff --git a/src/churro_ocr/providers/ocr.py b/src/churro_ocr/providers/ocr.py
index 87836ed..9a80e39 100644
--- a/src/churro_ocr/providers/ocr.py
+++ b/src/churro_ocr/providers/ocr.py
@@ -4,6 +4,7 @@
 
 import asyncio
 import base64
+import logging
 from dataclasses import dataclass, field
 from io import BytesIO
 from threading import Lock
@@ -24,6 +25,7 @@
     TextPostprocessor,
     default_ocr_image_preprocessor,
     identity_text_postprocessor,
+    validate_mistral_ocr_model,
 )
 from churro_ocr.templates import (
     DEFAULT_OCR_TEMPLATE,
@@ -31,6 +33,13 @@
     build_ocr_conversation,
 )
 
+logger = logging.getLogger(__name__)
+_MISTRAL_TRANSIENT_STATUS_CODES = frozenset({408, 429, 500, 502, 503, 504, 520, 521, 522, 524})
+_MISTRAL_MAX_ATTEMPTS = 6
+_MISTRAL_INITIAL_BACKOFF_SECONDS = 1.0
+_MISTRAL_MAX_BACKOFF_SECONDS = 16.0
+_MISTRAL_REQUEST_TIMEOUT_SECONDS = 60.0
+
 
 def _with_default_ocr_completion_kwargs(config: LiteLLMTransportConfig) -> LiteLLMTransportConfig:
     completion_kwargs: dict[str, object] = {"max_tokens": DEFAULT_OCR_MAX_TOKENS}
@@ -47,6 +56,30 @@ def _with_default_ocr_completion_kwargs(config: LiteLLMTransportConfig) -> LiteL
     )
 
 
+def _is_retryable_mistral_error(exc: Exception) -> bool:
+    status_code = getattr(exc, "status_code", None)
+    if isinstance(status_code, int):
+        return status_code in _MISTRAL_TRANSIENT_STATUS_CODES
+    return exc.__class__.__module__.startswith("httpx") or isinstance(exc, TimeoutError)
+
+
+def _get_mistral_retry_delay_seconds(exc: Exception, attempt: int) -> float:
+    headers = getattr(exc, "headers", None)
+    if headers is None:
+        raw_response = getattr(exc, "raw_response", None)
+        headers = getattr(raw_response, "headers", None)
+    retry_after = headers.get("retry-after") if hasattr(headers, "get") else None
+    if retry_after is not None:
+        try:
+            return max(0.0, float(retry_after))
+        except (TypeError, ValueError):
+            pass
+    return min(
+        _MISTRAL_INITIAL_BACKOFF_SECONDS * (2 ** (attempt - 1)),
+        _MISTRAL_MAX_BACKOFF_SECONDS,
+    )
+
+
 @dataclass(slots=True)
 class LiteLLMVisionOCRBackend(OCRBackend):
     """OCR backend for any LiteLLM-supported multimodal provider.
@@ -241,14 +274,14 @@ class MistralOCRBackend(OCRBackend):
     """Mistral OCR backend.
 
     :param api_key: Mistral API key used for OCR requests.
-    :param model: Mistral OCR model identifier.
+    :param model: Pinned Mistral OCR model identifier.
     :param model_name: Optional human-readable model name for result metadata.
     :param image_preprocessor: Image preprocessor applied before OCR.
     :param text_postprocessor: Text postprocessor applied after OCR.
     """
 
     api_key: str
-    model: str = "mistral-ocr-latest"
+    model: str
     model_name: str | None = None
     image_preprocessor: ImagePreprocessor = default_ocr_image_preprocessor
     text_postprocessor: TextPostprocessor = identity_text_postprocessor
@@ -257,6 +290,10 @@ class MistralOCRBackend(OCRBackend):
     _has_logged_prompt: bool = field(default=False, init=False, repr=False)
     _prompt_log_lock: Lock = field(default_factory=Lock, init=False, repr=False)
 
+    def __post_init__(self) -> None:
+        """Reject unsupported Mistral OCR aliases and unpinned model ids."""
+        validate_mistral_ocr_model(self.model, context="Mistral OCR backend")
+
     async def _get_client(self) -> Any:
         client = self._client
         if client is not None:
@@ -302,10 +339,34 @@ async def ocr(self, page: DocumentPage) -> OCRResult:
             set_logged=lambda: setattr(self, "_has_logged_prompt", True),
         )
         client = await self._get_client()
-        response = await client.ocr.process_async(
-            model=self.model,
-            document={"type": "image_url", "image_url": image_url},
-        )
+        document = {"type": "image_url", "image_url": image_url}
+        response: Any | None = None
+        for attempt in range(1, _MISTRAL_MAX_ATTEMPTS + 1):
+            try:
+                response = await asyncio.wait_for(
+                    client.ocr.process_async(
+                        model=self.model,
+                        document=document,
+                    ),
+                    timeout=_MISTRAL_REQUEST_TIMEOUT_SECONDS,
+                )
+                break
+            except Exception as exc:
+                if attempt >= _MISTRAL_MAX_ATTEMPTS or not _is_retryable_mistral_error(exc):
+                    raise
+                delay_seconds = _get_mistral_retry_delay_seconds(exc, attempt)
+                logger.warning(
+                    "Transient Mistral OCR failure for model %s "
+                    "(status=%s, attempt=%s/%s); retrying in %.1fs.",
+                    self.model,
+                    getattr(exc, "status_code", "unknown"),
+                    attempt,
+                    _MISTRAL_MAX_ATTEMPTS,
+                    delay_seconds,
+                )
+                await asyncio.sleep(delay_seconds)
+        if response is None:  # pragma: no cover - loop exits early via exception
+            raise ProviderError("Mistral OCR request failed before a response was returned.")
         if not response.pages:
             raise ProviderError("Mistral OCR returned no pages.")
         return build_ocr_result(
diff --git a/src/churro_ocr/providers/specs.py b/src/churro_ocr/providers/specs.py
index 1b753c0..fbbcd8f 100644
--- a/src/churro_ocr/providers/specs.py
+++ b/src/churro_ocr/providers/specs.py
@@ -6,11 +6,12 @@
 from dataclasses import dataclass, field
 from pathlib import Path
 import re
-from typing import TYPE_CHECKING, Any, Literal
+from typing import TYPE_CHECKING, Any, Literal, cast
 
 from PIL import Image
 
 from churro_ocr._internal.image import ensure_rgb, prepare_ocr_image, resize_image_to_fit
+from churro_ocr.errors import ConfigurationError
 from churro_ocr.prompts import (
     DEFAULT_OCR_OUTPUT_TAG,
     parse_chandra_response,
@@ -39,6 +40,7 @@
 
 
 OCRProvider = Literal["litellm", "openai-compatible", "azure", "mistral", "hf"]
+MistralOCRModel = Literal["mistral-ocr-2505", "mistral-ocr-2512"]
 ImagePreprocessor = Callable[[Image.Image], Image.Image]
 TextPostprocessorResult = str | tuple[str, dict[str, Any]]
 TextPostprocessor = Callable[[str], TextPostprocessorResult]
@@ -50,6 +52,26 @@
 CHANDRA_MIN_IMAGE_SIZE = (1_792, 28)
 CHANDRA_IMAGE_GRID_SIZE = 28
 OLMOCR_TARGET_LONGEST_IMAGE_DIM = 1_288
+MISTRAL_OCR_MODEL_IDS: tuple[MistralOCRModel, ...] = (
+    "mistral-ocr-2505",
+    "mistral-ocr-2512",
+)
+
+
+def validate_mistral_ocr_model(
+    model: str | None,
+    *,
+    context: str = "OCR provider 'mistral'",
+) -> MistralOCRModel:
+    """Return a supported pinned Mistral OCR model id or raise a configuration error."""
+    supported_models = ", ".join(MISTRAL_OCR_MODEL_IDS)
+    if model is None:
+        raise ConfigurationError(f"{context} requires `model` to be one of: {supported_models}.")
+    if model not in MISTRAL_OCR_MODEL_IDS:
+        raise ConfigurationError(
+            f"{context} only supports `model` values {supported_models}; got {model!r}."
+        )
+    return cast(MistralOCRModel, model)
 
 
 def identity_text_postprocessor(text: str) -> str:
@@ -499,6 +521,8 @@ def resolve_ocr_profile(
     "lfm2_5_vl_1_6b_profile",
     "ImagePreprocessor",
     "LiteLLMTransportConfig",
+    "MistralOCRModel",
+    "MISTRAL_OCR_MODEL_IDS",
     "MistralOptions",
     "olmocr_image_preprocessor",
     "olmocr_text_postprocessor",
@@ -508,5 +532,6 @@ def resolve_ocr_profile(
     "OpenAICompatibleOptions",
     "resolve_ocr_profile",
     "TextPostprocessor",
+    "validate_mistral_ocr_model",
     "VisionInputBuilder",
 ]
diff --git a/tests/test_cli.py b/tests/test_cli.py
index 8410b8b..09ca454 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -7,6 +7,7 @@
 from types import SimpleNamespace
 
 import pytest
+import typer
 from PIL import Image
 
 import churro_ocr.cli as cli_module
@@ -140,6 +141,31 @@ def test_build_ocr_backend_aligns_templates_for_generic_models() -> None:
     assert f"</{DEFAULT_OCR_OUTPUT_TAG}>" in litellm_backend.template.user_prompt
 
 
+def test_build_ocr_backend_requires_pinned_mistral_model() -> None:
+    with pytest.raises(typer.BadParameter, match="mistral-ocr-2505, mistral-ocr-2512"):
+        cli_module._build_ocr_backend(
+            backend="mistral",
+            model="mistral-ocr-latest",
+            endpoint=None,
+            api_key="secret",
+            base_url=None,
+            api_version=None,
+        )
+
+
+def test_build_ocr_backend_accepts_pinned_mistral_model() -> None:
+    mistral_backend = cli_module._build_ocr_backend(
+        backend="mistral",
+        model="mistral-ocr-2512",
+        endpoint=None,
+        api_key="secret",
+        base_url=None,
+        api_version=None,
+    )
+
+    assert mistral_backend.model == "mistral-ocr-2512"
+
+
 def test_build_ocr_backend_aligns_templates_for_dots() -> None:
     litellm_backend = cli_module._build_ocr_backend(
         backend="litellm",
diff --git a/tests/test_cli_contract.py b/tests/test_cli_contract.py
index 4ff9856..d269117 100644
--- a/tests/test_cli_contract.py
+++ b/tests/test_cli_contract.py
@@ -27,6 +27,14 @@ def sample_image_path(write_image_file) -> Path:
         ),
         (["--backend", "azure"], ("--endpoint and --api-key are required for backend=azure",)),
         (["--backend", "mistral"], ("--api-key is required for backend=mistral",)),
+        (
+            ["--backend", "mistral", "--api-key", "secret"],
+            ("--model is required for backend=mistral", "mistral-ocr-2505", "mistral-ocr-2512"),
+        ),
+        (
+            ["--backend", "mistral", "--api-key", "secret", "--model", "mistral-ocr-latest"],
+            ("must be one of", "mistral-ocr-2505", "mistral-ocr-2512"),
+        ),
         (["--backend", "hf"], ("--model is required for backend=hf",)),
     ],
 )
diff --git a/tests/test_provider_api_contracts.py b/tests/test_provider_api_contracts.py
index d44f021..71aa64c 100644
--- a/tests/test_provider_api_contracts.py
+++ b/tests/test_provider_api_contracts.py
@@ -68,6 +68,24 @@ def test_provider_dir_lists_lazy_exports() -> None:
             OCRBackendSpec(provider="mistral"),
             "OCR provider 'mistral' requires MistralOptions(api_key=...).",
         ),
+        (
+            OCRBackendSpec(
+                provider="mistral",
+                options=MistralOptions(api_key="secret"),
+            ),
+            "OCR provider 'mistral' requires `model` to be one of: mistral-ocr-2505, mistral-ocr-2512.",
+        ),
+        (
+            OCRBackendSpec(
+                provider="mistral",
+                model="mistral-ocr-latest",
+                options=MistralOptions(api_key="secret"),
+            ),
+            (
+                "OCR provider 'mistral' only supports `model` values mistral-ocr-2505, "
+                "mistral-ocr-2512; got 'mistral-ocr-latest'."
+            ),
+        ),
         (
             OCRBackendSpec(
                 provider="hf",
@@ -135,6 +153,7 @@ def test_build_ocr_backend_accepts_provider_specific_options() -> None:
     mistral_backend = build_ocr_backend(
         OCRBackendSpec(
             provider="mistral",
+            model="mistral-ocr-2512",
             options=MistralOptions(api_key="secret"),
         )
     )
@@ -143,4 +162,4 @@ def test_build_ocr_backend_accepts_provider_specific_options() -> None:
     assert isinstance(mistral_backend, MistralOCRBackend)
     assert azure_backend.model_id == "layout-model"
     assert azure_backend.model_name == "layout-model"
-    assert mistral_backend.model == "mistral-ocr-latest"
+    assert mistral_backend.model == "mistral-ocr-2512"
diff --git a/tests/test_providers.py b/tests/test_providers.py
index ca1a73e..3302c7d 100644
--- a/tests/test_providers.py
+++ b/tests/test_providers.py
@@ -312,7 +312,7 @@ async def test_mistral_ocr_backend_reuses_client(monkeypatch: pytest.MonkeyPatch
     class FakeOCRNamespace:
         async def process_async(self, *, model: str, document: dict[str, str]) -> SimpleNamespace:
             calls["requests"] += 1
-            assert model == "mistral-ocr-latest"
+            assert model == "mistral-ocr-2512"
             assert document == {
                 "type": "image_url",
                 "image_url": "data:image/jpeg;base64,encoded-image",
@@ -345,6 +345,7 @@ def __init__(self, *, api_key: str) -> None:
         build_ocr_backend(
             OCRBackendSpec(
                 provider="mistral",
+                model="mistral-ocr-2512",
                 options=MistralOptions(api_key="secret"),
             )
         ),
@@ -359,6 +360,220 @@ def __init__(self, *, api_key: str) -> None:
     assert calls == {"client_inits": 1, "requests": 2}
 
 
+@pytest.mark.asyncio
+async def test_mistral_ocr_backend_retries_transient_errors(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    calls = {"client_inits": 0, "requests": 0}
+    image = Image.new("RGB", (10, 10), color="white")
+    sleep_calls: list[float] = []
+
+    class FakeMistralError(Exception):
+        def __init__(self, status_code: int, headers: dict[str, str] | None = None) -> None:
+            self.status_code = status_code
+            self.headers = headers or {}
+            self.raw_response = SimpleNamespace(headers=self.headers)
+            super().__init__(f"Status {status_code}")
+
+    class FakeOCRNamespace:
+        async def process_async(self, *, model: str, document: dict[str, str]) -> SimpleNamespace:
+            calls["requests"] += 1
+            assert model == "mistral-ocr-2512"
+            assert document == {
+                "type": "image_url",
+                "image_url": "data:image/jpeg;base64,encoded-image",
+            }
+            if calls["requests"] < 3:
+                raise FakeMistralError(520)
+            return SimpleNamespace(pages=[SimpleNamespace(markdown="mistral text")])
+
+    class FakeMistralClient:
+        def __init__(self, *, api_key: str) -> None:
+            calls["client_inits"] += 1
+            assert api_key == "secret"
+            self.ocr = FakeOCRNamespace()
+
+    async def _fake_sleep(delay: float) -> None:
+        sleep_calls.append(delay)
+
+    mistral_module = ModuleType("mistralai")
+    cast("Any", mistral_module).Mistral = FakeMistralClient
+    monkeypatch.setitem(sys.modules, "mistralai", mistral_module)
+    monkeypatch.setattr(
+        "churro_ocr.providers.ocr.image_to_base64",
+        lambda actual_image, format_name: (
+            (
+                "image/jpeg",
+                "encoded-image",
+            )
+            if actual_image.size == image.size and actual_image.mode == "RGB" and format_name == "JPEG"
+            else ("", "")
+        ),
+    )
+    monkeypatch.setattr("churro_ocr.providers.ocr.asyncio.sleep", _fake_sleep)
+
+    backend = cast(
+        "MistralOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="mistral",
+                model="mistral-ocr-2512",
+                options=MistralOptions(api_key="secret"),
+            )
+        ),
+    )
+    page = DocumentPage(page_index=0, image=image, source_index=0)
+
+    result = await backend.ocr(page)
+
+    assert result.text == "mistral text"
+    assert calls == {"client_inits": 1, "requests": 3}
+    assert sleep_calls == [1.0, 2.0]
+
+
+@pytest.mark.asyncio
+async def test_mistral_ocr_backend_retries_request_timeouts(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    calls = {"client_inits": 0, "requests": 0, "wait_for": 0}
+    image = Image.new("RGB", (10, 10), color="white")
+    sleep_calls: list[float] = []
+
+    class FakeOCRNamespace:
+        async def process_async(self, *, model: str, document: dict[str, str]) -> SimpleNamespace:
+            calls["requests"] += 1
+            assert model == "mistral-ocr-2512"
+            assert document == {
+                "type": "image_url",
+                "image_url": "data:image/jpeg;base64,encoded-image",
+            }
+            return SimpleNamespace(pages=[SimpleNamespace(markdown="mistral text")])
+
+    class FakeMistralClient:
+        def __init__(self, *, api_key: str) -> None:
+            calls["client_inits"] += 1
+            assert api_key == "secret"
+            self.ocr = FakeOCRNamespace()
+
+    async def _fake_sleep(delay: float) -> None:
+        sleep_calls.append(delay)
+
+    async def _fake_wait_for(awaitable: Any, **kwargs: float) -> Any:
+        calls["wait_for"] += 1
+        timeout = kwargs["timeout"]
+        assert timeout == 60.0
+        if calls["wait_for"] == 1:
+            close = getattr(awaitable, "close", None)
+            if callable(close):
+                close()
+            raise TimeoutError
+        return await awaitable
+
+    mistral_module = ModuleType("mistralai")
+    cast("Any", mistral_module).Mistral = FakeMistralClient
+    monkeypatch.setitem(sys.modules, "mistralai", mistral_module)
+    monkeypatch.setattr(
+        "churro_ocr.providers.ocr.image_to_base64",
+        lambda actual_image, format_name: (
+            (
+                "image/jpeg",
+                "encoded-image",
+            )
+            if actual_image.size == image.size and actual_image.mode == "RGB" and format_name == "JPEG"
+            else ("", "")
+        ),
+    )
+    monkeypatch.setattr("churro_ocr.providers.ocr.asyncio.sleep", _fake_sleep)
+    monkeypatch.setattr("churro_ocr.providers.ocr.asyncio.wait_for", _fake_wait_for)
+
+    backend = cast(
+        "MistralOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="mistral",
+                model="mistral-ocr-2512",
+                options=MistralOptions(api_key="secret"),
+            )
+        ),
+    )
+    page = DocumentPage(page_index=0, image=image, source_index=0)
+
+    result = await backend.ocr(page)
+
+    assert result.text == "mistral text"
+    assert calls == {"client_inits": 1, "requests": 1, "wait_for": 2}
+    assert sleep_calls == [1.0]
+
+
+@pytest.mark.asyncio
+async def test_mistral_ocr_backend_does_not_retry_non_transient_errors(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    calls = {"client_inits": 0, "requests": 0}
+    image = Image.new("RGB", (10, 10), color="white")
+    sleep_calls: list[float] = []
+
+    class FakeMistralError(Exception):
+        def __init__(self, status_code: int) -> None:
+            self.status_code = status_code
+            self.headers: dict[str, str] = {}
+            self.raw_response = SimpleNamespace(headers=self.headers)
+            super().__init__(f"Status {status_code}")
+
+    class FakeOCRNamespace:
+        async def process_async(self, *, model: str, document: dict[str, str]) -> SimpleNamespace:
+            calls["requests"] += 1
+            assert model == "mistral-ocr-2505"
+            assert document == {
+                "type": "image_url",
+                "image_url": "data:image/jpeg;base64,encoded-image",
+            }
+            raise FakeMistralError(400)
+
+    class FakeMistralClient:
+        def __init__(self, *, api_key: str) -> None:
+            calls["client_inits"] += 1
+            assert api_key == "secret"
+            self.ocr = FakeOCRNamespace()
+
+    async def _fake_sleep(delay: float) -> None:
+        sleep_calls.append(delay)
+
+    mistral_module = ModuleType("mistralai")
+    cast("Any", mistral_module).Mistral = FakeMistralClient
+    monkeypatch.setitem(sys.modules, "mistralai", mistral_module)
+    monkeypatch.setattr(
+        "churro_ocr.providers.ocr.image_to_base64",
+        lambda actual_image, format_name: (
+            (
+                "image/jpeg",
+                "encoded-image",
+            )
+            if actual_image.size == image.size and actual_image.mode == "RGB" and format_name == "JPEG"
+            else ("", "")
+        ),
+    )
+    monkeypatch.setattr("churro_ocr.providers.ocr.asyncio.sleep", _fake_sleep)
+
+    backend = cast(
+        "MistralOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="mistral",
+                model="mistral-ocr-2505",
+                options=MistralOptions(api_key="secret"),
+            )
+        ),
+    )
+    page = DocumentPage(page_index=0, image=image, source_index=0)
+
+    with pytest.raises(FakeMistralError, match="Status 400"):
+        await backend.ocr(page)
+
+    assert calls == {"client_inits": 1, "requests": 1}
+    assert sleep_calls == []
+
+
 def test_build_ocr_backend_uses_olmocr_profile_defaults_for_openai_compatible() -> None:
     backend = cast(
         "OpenAICompatibleOCRBackend",
diff --git a/tests/test_tooling_benchmark.py b/tests/test_tooling_benchmark.py
index 48c733e..6406a6e 100644
--- a/tests/test_tooling_benchmark.py
+++ b/tests/test_tooling_benchmark.py
@@ -103,6 +103,31 @@ def test_validate_options_requires_model_for_hf() -> None:
     assert benchmark._validate_options(options) == 1
 
 
+def test_validate_options_requires_pinned_model_for_mistral() -> None:
+    missing_model = benchmark.BenchmarkOptions(
+        backend="mistral",
+        model=None,
+        dataset_split="dev",
+        api_key="secret",
+    )
+    alias_model = benchmark.BenchmarkOptions(
+        backend="mistral",
+        model="mistral-ocr-latest",
+        dataset_split="dev",
+        api_key="secret",
+    )
+    pinned_model = benchmark.BenchmarkOptions(
+        backend="mistral",
+        model="mistral-ocr-2512",
+        dataset_split="dev",
+        api_key="secret",
+    )
+
+    assert benchmark._validate_options(missing_model) == 1
+    assert benchmark._validate_options(alias_model) == 1
+    assert benchmark._validate_options(pinned_model) == 0
+
+
 def test_validate_options_allows_openai_compatible_without_api_key() -> None:
     options = benchmark.BenchmarkOptions(
         backend="openai-compatible",
diff --git a/tooling/benchmarking/benchmark.py b/tooling/benchmarking/benchmark.py
index f5bebb3..059ef79 100644
--- a/tooling/benchmarking/benchmark.py
+++ b/tooling/benchmarking/benchmark.py
@@ -22,6 +22,7 @@
 sys.path.insert(0, _REPO_SRC_PATH_STR)
 
 from churro_ocr._internal.logging import logger
+from churro_ocr.errors import ConfigurationError
 from churro_ocr.ocr import BatchOCRBackend, OCRBackend, OCRBackendLike
 from churro_ocr.page_detection import DocumentPage
 from churro_ocr.providers import (
@@ -33,6 +34,7 @@
     OCRBackendSpec,
     OpenAICompatibleOptions,
 )
+from churro_ocr.providers.specs import MISTRAL_OCR_MODEL_IDS, validate_mistral_ocr_model
 from tooling.benchmarking.dataset import (
     DatasetSelection,
     DatasetSubset,
@@ -150,9 +152,18 @@ def _validate_options(options: BenchmarkOptions) -> int:
     if options.backend == "azure" and (not options.endpoint or not options.api_key):
         logger.error("--endpoint and --api-key are required for backend=azure.")
         return 1
-    if options.backend == "mistral" and not options.api_key:
-        logger.error("--api-key is required for backend=mistral.")
-        return 1
+    if options.backend == "mistral":
+        if not options.api_key:
+            logger.error("--api-key is required for backend=mistral.")
+            return 1
+        try:
+            validate_mistral_ocr_model(options.model)
+        except ConfigurationError:
+            logger.error(
+                "--model is required for backend=mistral and must be one of: %s.",
+                ", ".join(MISTRAL_OCR_MODEL_IDS),
+            )
+            return 1
     return 0
 
 
@@ -247,10 +258,12 @@ def _build_ocr_backend(options: BenchmarkOptions) -> OCRBackendLike:
             )
         )
     assert options.api_key is not None
+    assert options.model is not None
+    mistral_model = validate_mistral_ocr_model(options.model)
     return build_ocr_backend(
         OCRBackendSpec(
             provider="mistral",
-            model=options.model or "mistral-ocr-latest",
+            model=mistral_model,
             options=MistralOptions(api_key=options.api_key),
         )
     )

From 29b8d065535b51ac52d6997b3eb462748892f3b6 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Mon, 6 Apr 2026 08:04:18 +0000
Subject: [PATCH 13/28] feat(benchmark): retain OCR metadata in benchmark
 outputs

---
 tests/test_tooling_benchmark.py   | 80 +++++++++++++++++++++----------
 tests/test_tooling_metrics.py     |  7 +--
 tooling/benchmarking/benchmark.py | 50 ++++++++++++-------
 tooling/evaluation/metrics.py     | 47 ++++++++++++++----
 tooling/evaluation/types.py       | 17 ++++++-
 5 files changed, 142 insertions(+), 59 deletions(-)

diff --git a/tests/test_tooling_benchmark.py b/tests/test_tooling_benchmark.py
index 6406a6e..8abe82a 100644
--- a/tests/test_tooling_benchmark.py
+++ b/tests/test_tooling_benchmark.py
@@ -8,6 +8,7 @@
 from datasets import Dataset
 from PIL import Image
 
+from churro_ocr.ocr import OCRResult
 from churro_ocr.providers.hf import HuggingFaceVisionOCRBackend
 from churro_ocr.providers.ocr import LiteLLMVisionOCRBackend
 from churro_ocr.providers.specs import DEFAULT_OCR_MAX_TOKENS
@@ -360,7 +361,9 @@ async def fake_predict(ds, options, *, total_pages):  # noqa: ANN001
         assert selected[0]["example_id"] == "1"
         assert options.max_concurrency == 2
         assert total_pages is None
-        return [benchmark._build_evaluation_example(selected[0])], ["prediction"]
+        return [
+            benchmark._build_evaluation_example(selected[0])
+        ], [{"text": "prediction", "metadata": {"raw_html": "<p>prediction</p>"}}]
 
     monkeypatch.setattr(benchmark, "_predict_texts", fake_predict)
 
@@ -392,7 +395,7 @@ def fake_compute_metrics(ds, predictions, output_prefix, elapsed_time):  # noqa:
 
     assert result == 0
     assert captured["dataset"] == [benchmark._build_evaluation_example(dataset[1])]
-    assert captured["predictions"] == ["prediction"]
+    assert captured["predictions"] == [{"text": "prediction", "metadata": {"raw_html": "<p>prediction</p>"}}]
     assert captured["output_prefix"] == str(tmp_path / "outputs")
     assert captured["elapsed_time"] == pytest.approx(3.5)
 
@@ -569,14 +572,15 @@ def fake_tqdm(*, total: int | None, desc: str, unit: str) -> FakeProgressBar:
         progress_bars.append(progress_bar)
         return progress_bar
 
-    class FakeOCRResult:
-        def __init__(self, text: str) -> None:
-            self.text = text
-
     class FakeOCRBackend:
         async def ocr(self, page):  # noqa: ANN001
             await asyncio.sleep(page.width / 1000)
-            return FakeOCRResult(text=f"page-{page.width}")
+            return OCRResult(
+                text=f"page-{page.width}",
+                provider_name="fake",
+                model_name="fake-model",
+                metadata={"page_width": page.width},
+            )
 
     monkeypatch.setattr(benchmark, "tqdm", fake_tqdm)
     monkeypatch.setattr(benchmark, "_build_ocr_backend", lambda _: FakeOCRBackend())
@@ -595,7 +599,11 @@ async def ocr(self, page):  # noqa: ANN001
         total_pages=3,
     )
 
-    assert predictions == ["page-3", "page-1", "page-2"]
+    assert predictions == [
+        {"text": "page-3", "metadata": {"page_width": 3}},
+        {"text": "page-1", "metadata": {"page_width": 1}},
+        {"text": "page-2", "metadata": {"page_width": 2}},
+    ]
     assert evaluation_examples == [benchmark._build_evaluation_example(example) for example in dataset]
     assert len(progress_bars) == 1
     assert progress_bars[0].total == 3
@@ -633,14 +641,18 @@ async def test_predict_texts_uses_batch_backend_with_max_concurrency_as_batch_si
     ]
     captured_batch_sizes: list[int] = []
 
-    class FakeOCRResult:
-        def __init__(self, text: str) -> None:
-            self.text = text
-
     class FakeBatchBackend:
         async def ocr_batch(self, pages):  # noqa: ANN001
             captured_batch_sizes.append(len(pages))
-            return [FakeOCRResult(text=f"page-{page.width}") for page in pages]
+            return [
+                OCRResult(
+                    text=f"page-{page.width}",
+                    provider_name="fake",
+                    model_name="fake-model",
+                    metadata={"page_width": page.width},
+                )
+                for page in pages
+            ]
 
     monkeypatch.setattr(benchmark, "_build_ocr_backend", lambda _: FakeBatchBackend())
 
@@ -658,7 +670,11 @@ async def ocr_batch(self, pages):  # noqa: ANN001
     )
 
     assert captured_batch_sizes == [2, 1]
-    assert predictions == ["page-3", "page-1", "page-2"]
+    assert predictions == [
+        {"text": "page-3", "metadata": {"page_width": 3}},
+        {"text": "page-1", "metadata": {"page_width": 1}},
+        {"text": "page-2", "metadata": {"page_width": 2}},
+    ]
     assert evaluation_examples == [benchmark._build_evaluation_example(example) for example in dataset]
 
 
@@ -674,13 +690,17 @@ class FakeLogger:
         def info(self, message: str, *args: object) -> None:
             logged_messages.append(message % args if args else message)
 
-    class FakeOCRResult:
-        def __init__(self, text: str) -> None:
-            self.text = text
-
     class FakeBatchBackend:
         async def ocr_batch(self, pages):  # noqa: ANN001
-            return [FakeOCRResult(text=f"page-{page.width}") for page in pages]
+            return [
+                OCRResult(
+                    text=f"page-{page.width}",
+                    provider_name="fake",
+                    model_name="fake-model",
+                    metadata={"page_width": page.width},
+                )
+                for page in pages
+            ]
 
     monkeypatch.setattr(benchmark, "logger", FakeLogger())
     monkeypatch.setattr(benchmark, "_build_ocr_backend", lambda _: FakeBatchBackend())
@@ -698,7 +718,10 @@ async def ocr_batch(self, pages):  # noqa: ANN001
         total_pages=2,
     )
 
-    assert predictions == ["page-3", "page-1"]
+    assert predictions == [
+        {"text": "page-3", "metadata": {"page_width": 3}},
+        {"text": "page-1", "metadata": {"page_width": 1}},
+    ]
     assert logged_messages == [
         "First benchmark OCR output for backend=hf model=kristaller486/dots.ocr-1.5:\npage-3"
     ]
@@ -717,14 +740,15 @@ class FakeLogger:
         def info(self, message: str, *args: object) -> None:
             logged_messages.append(message % args if args else message)
 
-    class FakeOCRResult:
-        def __init__(self, text: str) -> None:
-            self.text = text
-
     class FakeOCRBackend:
         async def ocr(self, page):  # noqa: ANN001
             await asyncio.sleep(page.width / 1000)
-            return FakeOCRResult(text=f"page-{page.width}")
+            return OCRResult(
+                text=f"page-{page.width}",
+                provider_name="fake",
+                model_name="fake-model",
+                metadata={"page_width": page.width},
+            )
 
     monkeypatch.setattr(benchmark, "logger", FakeLogger())
     monkeypatch.setattr(benchmark, "_build_ocr_backend", lambda _: FakeOCRBackend())
@@ -743,5 +767,9 @@ async def ocr(self, page):  # noqa: ANN001
         total_pages=3,
     )
 
-    assert predictions == ["page-3", "page-1", "page-2"]
+    assert predictions == [
+        {"text": "page-3", "metadata": {"page_width": 3}},
+        {"text": "page-1", "metadata": {"page_width": 1}},
+        {"text": "page-2", "metadata": {"page_width": 2}},
+    ]
     assert logged_messages == ["First benchmark OCR output for backend=azure model=<default>:\npage-3"]
diff --git a/tests/test_tooling_metrics.py b/tests/test_tooling_metrics.py
index f328c13..0493f52 100644
--- a/tests/test_tooling_metrics.py
+++ b/tests/test_tooling_metrics.py
@@ -5,7 +5,7 @@
 from typing import cast
 
 from tooling.evaluation import metrics
-from tooling.evaluation.types import EvaluationExample, PageEvaluationResult
+from tooling.evaluation.types import BenchmarkPrediction, EvaluationExample, PageEvaluationResult
 
 
 def test_calculate_language_and_type_metrics_handles_missing_categories() -> None:
@@ -55,7 +55,7 @@ def test_compute_metrics_writes_expected_outputs(
             "document_type": "print",
         },
     ]
-    predicted_texts = [""]
+    predictions: list[BenchmarkPrediction] = [{"text": "", "metadata": {"raw_html": "<p></p>"}}]
 
     def fake_batch_evaluate(ds, preds):  # noqa: ANN001
         assert ds == dataset
@@ -81,7 +81,7 @@ def fake_batch_evaluate(ds, preds):  # noqa: ANN001
     output_prefix = tmp_path / "results"
     combined = metrics.compute_metrics(
         dataset=dataset,
-        predicted_texts=predicted_texts,
+        predictions=predictions,
         output_prefix=output_prefix,
         elapsed_time=4.567,
     )
@@ -90,6 +90,7 @@ def fake_batch_evaluate(ds, preds):  # noqa: ANN001
     assert outputs == [
         {
             "example_id": "file1",
+            "metadata": {"raw_html": "<p></p>"},
             "main_language": "english",
             "document_type": "print",
             "normalized_levenshtein_similarity": 0.9,
diff --git a/tooling/benchmarking/benchmark.py b/tooling/benchmarking/benchmark.py
index 059ef79..55f78c5 100644
--- a/tooling/benchmarking/benchmark.py
+++ b/tooling/benchmarking/benchmark.py
@@ -41,7 +41,12 @@
     load_dataset_split,
 )
 from tooling.evaluation.metrics import compute_metrics
-from tooling.evaluation.types import BenchmarkDatasetExample, EvaluationExample, to_evaluation_example
+from tooling.evaluation.types import (
+    BenchmarkDatasetExample,
+    BenchmarkPrediction,
+    EvaluationExample,
+    to_evaluation_example,
+)
 
 CHURRO_DATASET_ID = "stanford-oval/churro-dataset"
 VALID_DATASET_SPLITS = {"dev", "test"}
@@ -284,14 +289,14 @@ async def _predict_texts(
     options: BenchmarkOptions,
     *,
     total_pages: int | None = None,
-) -> tuple[list[EvaluationExample], list[str]]:
+) -> tuple[list[EvaluationExample], list[BenchmarkPrediction]]:
     ocr_backend = _build_ocr_backend(options)
     max_in_flight = max(1, options.max_concurrency)
     has_logged_first_output = False
     if isinstance(ocr_backend, BatchOCRBackend):
         dataset_iterator = iter(dataset)
         evaluation_examples: list[EvaluationExample] = []
-        predicted_texts: list[str] = []
+        predictions: list[BenchmarkPrediction] = []
         submitted_pages = 0
 
         with tqdm(total=total_pages, desc="OCR", unit="page") as progress:
@@ -324,25 +329,34 @@ async def _predict_texts(
                         text=batch_results[0].text or "",
                     )
                     has_logged_first_output = True
-                predicted_texts.extend((result.text or "") for result in batch_results)
+                predictions.extend(
+                    {
+                        "text": result.text or "",
+                        "metadata": dict(result.metadata),
+                    }
+                    for result in batch_results
+                )
                 progress.update(len(batch_results))
                 progress.set_postfix(submitted=submitted_pages, in_flight=0, refresh=False)
 
-        return evaluation_examples, predicted_texts
+        return evaluation_examples, predictions
 
-    async def _predict(index: int, image: Image.Image) -> tuple[int, str]:
+    async def _predict(index: int, image: Image.Image) -> tuple[int, BenchmarkPrediction]:
         page = DocumentPage(page_index=index, source_index=0, image=image)
         if callable(ocr_backend) and not isinstance(ocr_backend, OCRBackend):
             result = await ocr_backend(page)
         else:
             assert isinstance(ocr_backend, OCRBackend)
             result = await ocr_backend.ocr(page)
-        return index, (result.text or "")
+        return index, {
+            "text": result.text or "",
+            "metadata": dict(result.metadata),
+        }
 
     dataset_iterator = iter(dataset)
     evaluation_examples: list[EvaluationExample] = []
-    pending_tasks: set[asyncio.Task[tuple[int, str]]] = set()
-    predicted_texts: list[str] = []
+    pending_tasks: set[asyncio.Task[tuple[int, BenchmarkPrediction]]] = set()
+    predictions: list[BenchmarkPrediction] = []
     next_index = 0
     wait_poll_seconds = 1.0
 
@@ -378,7 +392,7 @@ def _progress_heartbeat(progress: tqdm[object], stop_event: threading.Event) ->
                     image = example["image"]
                     assert isinstance(image, Image.Image)
                     evaluation_examples.append(_build_evaluation_example(example))
-                    predicted_texts.append("")
+                    predictions.append({"text": "", "metadata": {}})
                     pending_tasks.add(asyncio.create_task(_predict(next_index, image)))
                     next_index += 1
                     _update_progress_status(progress)
@@ -391,10 +405,10 @@ def _progress_heartbeat(progress: tqdm[object], stop_event: threading.Event) ->
                     return_when=asyncio.FIRST_COMPLETED,
                 )
                 for task in done_tasks:
-                    index, text = await task
-                    predicted_texts[index] = text
+                    index, prediction = await task
+                    predictions[index] = prediction
                     if not has_logged_first_output and index == 0:
-                        _log_first_benchmark_output(options=options, text=text)
+                        _log_first_benchmark_output(options=options, text=prediction["text"])
                         has_logged_first_output = True
                     progress.update(1)
                 _update_progress_status(progress)
@@ -408,7 +422,7 @@ def _progress_heartbeat(progress: tqdm[object], stop_event: threading.Event) ->
             heartbeat_thread.join(timeout=wait_poll_seconds * 2)
             _update_progress_status(progress, force_refresh=True)
 
-    return evaluation_examples, predicted_texts
+    return evaluation_examples, predictions
 
 
 async def run(options: BenchmarkOptions) -> int:
@@ -425,17 +439,17 @@ async def run(options: BenchmarkOptions) -> int:
 
     output_prefix = create_output_prefix(options)
     start_time = time()
-    evaluation_examples, predicted_texts = await _predict_texts(
+    evaluation_examples, predictions = await _predict_texts(
         dataset,
         options,
         total_pages=total_pages,
     )
     elapsed_time = time() - start_time
 
-    assert len(evaluation_examples) == len(predicted_texts), (
-        f"Mismatch in dataset size ({len(evaluation_examples)}) and predictions ({len(predicted_texts)})."
+    assert len(evaluation_examples) == len(predictions), (
+        f"Mismatch in dataset size ({len(evaluation_examples)}) and predictions ({len(predictions)})."
     )
-    compute_metrics(evaluation_examples, predicted_texts, output_prefix, elapsed_time)
+    compute_metrics(evaluation_examples, predictions, output_prefix, elapsed_time)
     return 0
 
 
diff --git a/tooling/evaluation/metrics.py b/tooling/evaluation/metrics.py
index e4f016b..ba1ac3c 100644
--- a/tooling/evaluation/metrics.py
+++ b/tooling/evaluation/metrics.py
@@ -3,13 +3,19 @@
 from __future__ import annotations
 
 from collections import defaultdict
+from collections.abc import Sequence
 import json
 from pathlib import Path
 from typing import Any
 
 from churro_ocr._internal.logging import logger
 from tooling.evaluation.evaluate_page import batch_evaluate
-from tooling.evaluation.types import EvaluationExample, PageEvaluationResult
+from tooling.evaluation.types import (
+    BenchmarkOutputRow,
+    BenchmarkPrediction,
+    EvaluationExample,
+    PageEvaluationResult,
+)
 
 
 def _get_llm_total_cost() -> float:
@@ -39,7 +45,7 @@ def to_rounded_percentage(metrics: dict[str, Any]) -> dict[str, Any]:
 
 
 def calculate_language_and_type_metrics(
-    outputs: list[PageEvaluationResult],
+    outputs: Sequence[PageEvaluationResult],
     main_metric: str = "normalized_levenshtein_similarity",
 ) -> tuple[dict[str, float], dict[str, float], dict[str, float]]:
     """Compute averages grouped by language, document type, and both."""
@@ -70,28 +76,49 @@ def calculate_language_and_type_metrics(
     return averaged_language, averaged_type, averaged_language_type
 
 
+def _normalize_prediction(prediction: str | BenchmarkPrediction) -> BenchmarkPrediction:
+    """Coerce legacy string predictions into the structured benchmark format."""
+    if isinstance(prediction, str):
+        return {"text": prediction, "metadata": {}}
+    return {
+        "text": str(prediction["text"]),
+        "metadata": dict(prediction["metadata"]),
+    }
+
+
 def _build_output_rows(
-    dataset: list[EvaluationExample],
-    per_example_outputs: list[PageEvaluationResult],
-) -> list[PageEvaluationResult]:
+    dataset: Sequence[EvaluationExample],
+    per_example_outputs: Sequence[PageEvaluationResult],
+    predictions: Sequence[BenchmarkPrediction],
+) -> list[BenchmarkOutputRow]:
     """Attach stable example ids to per-example outputs before writing them."""
     return [
-        {"example_id": str(example["example_id"]), **evaluation_output}
-        for evaluation_output, example in zip(per_example_outputs, dataset, strict=False)
+        {
+            "example_id": str(example["example_id"]),
+            "metadata": dict(prediction["metadata"]),
+            **evaluation_output,
+        }
+        for evaluation_output, example, prediction in zip(
+            per_example_outputs,
+            dataset,
+            predictions,
+            strict=False,
+        )
     ]
 
 
 def compute_metrics(
     dataset: list[EvaluationExample],
-    predicted_texts: list[str],
+    predictions: list[str] | list[BenchmarkPrediction],
     output_prefix: str | Path,
     elapsed_time: float,
     main_metric: str = "normalized_levenshtein_similarity",
 ) -> dict[str, Any]:
     """Compute aggregate metrics and write benchmark output files."""
-    sanitized_predictions = [prediction or "" for prediction in predicted_texts]
+    normalized_predictions = [_normalize_prediction(prediction) for prediction in predictions]
+    sanitized_predictions = [prediction["text"] or "" for prediction in normalized_predictions]
     aggregate_metrics, per_example_outputs = batch_evaluate(dataset, sanitized_predictions)
-    outputs = _build_output_rows(dataset, per_example_outputs)
+    outputs = _build_output_rows(dataset, per_example_outputs, normalized_predictions)
 
     output_dir = Path(output_prefix)
     output_dir.mkdir(parents=True, exist_ok=True)
diff --git a/tooling/evaluation/types.py b/tooling/evaluation/types.py
index f650679..ede76f1 100644
--- a/tooling/evaluation/types.py
+++ b/tooling/evaluation/types.py
@@ -1,8 +1,8 @@
-"""Shared dataset and result types for CHURRO tooling evaluation flows."""
+"""Shared dataset, prediction, and result types for CHURRO tooling evaluation flows."""
 
 from __future__ import annotations
 
-from typing import TypedDict
+from typing import Any, TypedDict
 
 from PIL import Image
 
@@ -61,6 +61,19 @@ class PageEvaluationResult(PageEvaluationMetrics):
     document_type: str
 
 
+class BenchmarkPrediction(TypedDict):
+    """OCR output retained during benchmarking before metrics are computed."""
+
+    text: str
+    metadata: dict[str, Any]
+
+
+class BenchmarkOutputRow(PageEvaluationResult):
+    """Serialized benchmark output row written to ``outputs.json``."""
+
+    metadata: dict[str, Any]
+
+
 def to_evaluation_example(example: BenchmarkDatasetExample) -> EvaluationExample:
     """Keep only the dataset fields needed after OCR completes."""
     return {field_name: example[field_name] for field_name in EVALUATION_EXAMPLE_FIELDS}

From 36d0c7ec1d9149dd48341125df9ffa0de515c048 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Mon, 6 Apr 2026 14:27:56 +0000
Subject: [PATCH 14/28] fix(providers): retry transient provider API errors

---
 pixi.lock                                  |  17 +-
 pyproject.toml                             |   1 +
 src/churro_ocr/_internal/litellm.py        |   7 +-
 src/churro_ocr/_internal/retry.py          | 202 +++++++++++++++++++++
 src/churro_ocr/providers/ocr.py            |  91 +++-------
 src/churro_ocr/providers/page_detection.py |  20 +-
 tests/test_internal_helpers.py             |  47 +++++
 tests/test_providers.py                    | 171 ++++++++++++++++-
 8 files changed, 484 insertions(+), 72 deletions(-)
 create mode 100644 src/churro_ocr/_internal/retry.py

diff --git a/pixi.lock b/pixi.lock
index 1b12f56..3beddc1 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -201,6 +201,7 @@ environments:
       - pypi: https://files.pythonhosted.org/packages/27/83/859ecdd180cacc13b1f7e857abf8582a64552ea7a061057a6c716e790fce/sphinxcontrib_qthelp-2.0.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/52/a7/d2782e4e3f77c8450f727ba74a8f12756d5ba823d81b941f1b04da9d033a/sphinxcontrib_serializinghtml-2.0.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/0b/c9/584bc9651441b4ba60cc4d557d8a547b5aff901af35bda3a4ee30c819b82/starlette-1.0.0-py3-none-any.whl
+      - pypi: https://files.pythonhosted.org/packages/d7/c1/eb8f9debc45d3b7918a32ab756658a0904732f75e555402972246b0b8e71/tenacity-9.1.4-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/f5/de/9341a6d7a8f1b448573bbf3425fa57669ac58258a667eb48a25dfe916d70/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_x86_64.whl
       - pypi: https://files.pythonhosted.org/packages/2e/76/932be4b50ef6ccedf9d3c6639b056a967a86258c6d9200643f01269211ca/tokenizers-0.22.2-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
       - pypi: https://files.pythonhosted.org/packages/16/e1/3079a9ff9b8e11b846c6ac5c8b5bfb7ff225eee721825310c91b3b50304f/tqdm-4.67.3-py3-none-any.whl
@@ -394,6 +395,7 @@ environments:
       - pypi: https://files.pythonhosted.org/packages/27/83/859ecdd180cacc13b1f7e857abf8582a64552ea7a061057a6c716e790fce/sphinxcontrib_qthelp-2.0.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/52/a7/d2782e4e3f77c8450f727ba74a8f12756d5ba823d81b941f1b04da9d033a/sphinxcontrib_serializinghtml-2.0.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/0b/c9/584bc9651441b4ba60cc4d557d8a547b5aff901af35bda3a4ee30c819b82/starlette-1.0.0-py3-none-any.whl
+      - pypi: https://files.pythonhosted.org/packages/d7/c1/eb8f9debc45d3b7918a32ab756658a0904732f75e555402972246b0b8e71/tenacity-9.1.4-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/f5/de/9341a6d7a8f1b448573bbf3425fa57669ac58258a667eb48a25dfe916d70/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_x86_64.whl
       - pypi: https://files.pythonhosted.org/packages/2e/76/932be4b50ef6ccedf9d3c6639b056a967a86258c6d9200643f01269211ca/tokenizers-0.22.2-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
       - pypi: https://files.pythonhosted.org/packages/16/e1/3079a9ff9b8e11b846c6ac5c8b5bfb7ff225eee721825310c91b3b50304f/tqdm-4.67.3-py3-none-any.whl
@@ -556,6 +558,7 @@ environments:
       - pypi: https://files.pythonhosted.org/packages/27/83/859ecdd180cacc13b1f7e857abf8582a64552ea7a061057a6c716e790fce/sphinxcontrib_qthelp-2.0.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/52/a7/d2782e4e3f77c8450f727ba74a8f12756d5ba823d81b941f1b04da9d033a/sphinxcontrib_serializinghtml-2.0.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/0b/c9/584bc9651441b4ba60cc4d557d8a547b5aff901af35bda3a4ee30c819b82/starlette-1.0.0-py3-none-any.whl
+      - pypi: https://files.pythonhosted.org/packages/d7/c1/eb8f9debc45d3b7918a32ab756658a0904732f75e555402972246b0b8e71/tenacity-9.1.4-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/2e/76/932be4b50ef6ccedf9d3c6639b056a967a86258c6d9200643f01269211ca/tokenizers-0.22.2-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
       - pypi: https://files.pythonhosted.org/packages/16/e1/3079a9ff9b8e11b846c6ac5c8b5bfb7ff225eee721825310c91b3b50304f/tqdm-4.67.3-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/e7/28/35f7411ff80a3640c1f4fc907dcbb6a65061ebb82f66950e38bfc9f7f740/transformers-5.5.0-py3-none-any.whl
@@ -776,11 +779,12 @@ packages:
 - pypi: ./
   name: churro-ocr
   version: 0.2.0
-  sha256: 4c7ab2bad968d566228a29c231a0cc7d8e594542a8632a5afa64841d05b307df
+  sha256: 4aab922d00e91acd3427b8ddbb59341f7f5232ccc72fbc120a3754e7e05d0dbc
   requires_dist:
   - loguru>=0.7.2,<1
   - pillow>=10.4.0,<12
   - rich>=13.9.2,<14
+  - tenacity>=9.1.2,<10
   - typer>=0.12.3,<1
   - google-auth>=2.41.1,<3 ; extra == 'llm'
   - litellm[caching]==1.82.3 ; extra == 'llm'
@@ -3291,6 +3295,17 @@ packages:
   - python-multipart>=0.0.18 ; extra == 'full'
   - pyyaml ; extra == 'full'
   requires_python: '>=3.10'
+- pypi: https://files.pythonhosted.org/packages/d7/c1/eb8f9debc45d3b7918a32ab756658a0904732f75e555402972246b0b8e71/tenacity-9.1.4-py3-none-any.whl
+  name: tenacity
+  version: 9.1.4
+  sha256: 6095a360c919085f28c6527de529e76a06ad89b23659fa881ae0649b867a9d55
+  requires_dist:
+  - reno ; extra == 'doc'
+  - sphinx ; extra == 'doc'
+  - pytest ; extra == 'test'
+  - tornado>=4.5 ; extra == 'test'
+  - typeguard ; extra == 'test'
+  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/f5/de/9341a6d7a8f1b448573bbf3425fa57669ac58258a667eb48a25dfe916d70/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_x86_64.whl
   name: tiktoken
   version: 0.12.0
diff --git a/pyproject.toml b/pyproject.toml
index 0db092f..3ef6d83 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -20,6 +20,7 @@ dependencies = [
     "loguru>=0.7.2,<1",
     "Pillow>=10.4.0,<12",
     "rich>=13.9.2,<14",
+    "tenacity>=9.1.2,<10",
     "typer>=0.12.3,<1",
 ]
 
diff --git a/src/churro_ocr/_internal/litellm.py b/src/churro_ocr/_internal/litellm.py
index 2daffc5..23fb318 100644
--- a/src/churro_ocr/_internal/litellm.py
+++ b/src/churro_ocr/_internal/litellm.py
@@ -13,6 +13,7 @@
 
 from churro_ocr._internal.image import image_to_base64
 from churro_ocr._internal.install import install_command_hint
+from churro_ocr._internal.retry import retry_api_call
 from churro_ocr.errors import ConfigurationError, ProviderError
 from churro_ocr.providers.specs import LiteLLMTransportConfig
 from churro_ocr.templates import OCRConversation
@@ -186,7 +187,11 @@ async def complete_text(
             kwargs.update(self._config.completion_kwargs)
 
         try:
-            response = await acompletion(**kwargs)
+            response = await retry_api_call(
+                lambda: acompletion(**kwargs),
+                operation_name="LiteLLM request",
+                context=f"for model '{model}'",
+            )
         except Exception as exc:  # pragma: no cover - provider-specific failure path
             raise ProviderError(f"LiteLLM request failed for model '{model}': {exc}") from exc
         self._record_response_cost(model=model, response=response)
diff --git a/src/churro_ocr/_internal/retry.py b/src/churro_ocr/_internal/retry.py
new file mode 100644
index 0000000..4595461
--- /dev/null
+++ b/src/churro_ocr/_internal/retry.py
@@ -0,0 +1,202 @@
+"""Shared retry helpers for provider API calls."""
+
+from __future__ import annotations
+
+import asyncio
+import logging
+from collections.abc import Awaitable, Callable, Mapping
+from typing import cast
+
+from tenacity import AsyncRetrying, RetryCallState, retry_if_exception, stop_after_attempt
+
+logger = logging.getLogger(__name__)
+
+DEFAULT_MAX_ATTEMPTS = 6
+DEFAULT_INITIAL_BACKOFF_SECONDS = 1.0
+DEFAULT_MAX_BACKOFF_SECONDS = 16.0
+TRANSIENT_STATUS_CODES = frozenset({408, 429, 500, 502, 503, 504, 520, 521, 522, 524})
+RETRYABLE_EXCEPTION_CLASS_NAMES = frozenset(
+    {
+        "APIConnectionError",
+        "APITimeoutError",
+        "ConnectError",
+        "ConnectTimeout",
+        "PoolTimeout",
+        "RateLimitError",
+        "ReadTimeout",
+        "RemoteProtocolError",
+        "ServiceRequestError",
+        "ServiceResponseError",
+        "WriteTimeout",
+    }
+)
+RETRYABLE_EXCEPTION_MODULE_PREFIXES = ("httpcore", "httpx")
+
+retry_sleep = asyncio.sleep
+
+type RetryPredicate = Callable[[BaseException], bool]
+
+
+def _coerce_status_code(value: object) -> int | None:
+    if isinstance(value, int):
+        return value
+    if isinstance(value, float) and value.is_integer():
+        return int(value)
+    return None
+
+
+def _headers_from_candidate(value: object) -> Mapping[str, object] | None:
+    if isinstance(value, Mapping):
+        return cast("Mapping[str, object]", value)
+    return None
+
+
+def get_error_status_code(exc: BaseException) -> int | None:
+    """Extract an HTTP-like status code from a provider exception when available."""
+    status_code = _coerce_status_code(getattr(exc, "status_code", None))
+    if status_code is not None:
+        return status_code
+
+    for attribute_name in ("response", "raw_response"):
+        response = getattr(exc, attribute_name, None)
+        status_code = _coerce_status_code(getattr(response, "status_code", None))
+        if status_code is not None:
+            return status_code
+    return None
+
+
+def get_error_retry_after_seconds(exc: BaseException) -> float | None:
+    """Extract a retry delay from response headers when one is available."""
+    headers = _headers_from_candidate(getattr(exc, "headers", None))
+    if headers is None:
+        for attribute_name in ("response", "raw_response"):
+            response = getattr(exc, attribute_name, None)
+            headers = _headers_from_candidate(getattr(response, "headers", None))
+            if headers is not None:
+                break
+    if headers is None:
+        return None
+
+    retry_after = headers.get("retry-after")
+    if retry_after is None:
+        retry_after = headers.get("Retry-After")
+    if retry_after is None:
+        return None
+    if not isinstance(retry_after, str | int | float):
+        return None
+    try:
+        return max(0.0, float(retry_after))
+    except ValueError:
+        return None
+
+
+def compute_retry_delay_seconds(
+    exc: BaseException,
+    *,
+    attempt_number: int,
+    initial_backoff_seconds: float = DEFAULT_INITIAL_BACKOFF_SECONDS,
+    max_backoff_seconds: float = DEFAULT_MAX_BACKOFF_SECONDS,
+) -> float:
+    """Compute the retry delay for a failed provider request."""
+    retry_after = get_error_retry_after_seconds(exc)
+    if retry_after is not None:
+        return retry_after
+    return min(
+        initial_backoff_seconds * (2 ** max(0, attempt_number - 1)),
+        max_backoff_seconds,
+    )
+
+
+def is_retryable_api_error(exc: BaseException) -> bool:
+    """Return whether a provider exception should be retried."""
+    if isinstance(exc, TimeoutError):
+        return True
+
+    status_code = get_error_status_code(exc)
+    if status_code is not None:
+        return status_code in TRANSIENT_STATUS_CODES
+
+    exc_type = exc.__class__
+    if exc_type.__name__ in RETRYABLE_EXCEPTION_CLASS_NAMES:
+        return True
+
+    module_name = exc_type.__module__
+    return any(module_name.startswith(prefix) for prefix in RETRYABLE_EXCEPTION_MODULE_PREFIXES)
+
+
+def _build_before_sleep_callback(
+    *,
+    operation_name: str,
+    context: str | None,
+    max_attempts: int,
+) -> Callable[[RetryCallState], None]:
+    message_context = f" {context}" if context else ""
+
+    def _before_sleep(retry_state: RetryCallState) -> None:
+        outcome = retry_state.outcome
+        exc = outcome.exception() if outcome is not None and outcome.failed else None
+        if exc is None:
+            return
+        delay_seconds = retry_state.next_action.sleep if retry_state.next_action is not None else 0.0
+        logger.warning(
+            "Transient %s failure%s (status=%s, attempt=%s/%s); retrying in %.1fs.",
+            operation_name,
+            message_context,
+            get_error_status_code(exc) or "unknown",
+            retry_state.attempt_number,
+            max_attempts,
+            delay_seconds,
+        )
+
+    return _before_sleep
+
+
+async def retry_api_call[T](
+    fn: Callable[[], Awaitable[T]],
+    *,
+    operation_name: str,
+    context: str | None = None,
+    max_attempts: int = DEFAULT_MAX_ATTEMPTS,
+    retry_filter: RetryPredicate = is_retryable_api_error,
+    initial_backoff_seconds: float = DEFAULT_INITIAL_BACKOFF_SECONDS,
+    max_backoff_seconds: float = DEFAULT_MAX_BACKOFF_SECONDS,
+) -> T:
+    """Execute an async provider request with shared retry behavior."""
+    retrying = AsyncRetrying(
+        reraise=True,
+        stop=stop_after_attempt(max_attempts),
+        retry=retry_if_exception(retry_filter),
+        wait=lambda retry_state: (
+            0.0
+            if retry_state.outcome is None or not retry_state.outcome.failed
+            else compute_retry_delay_seconds(
+                retry_state.outcome.exception(),
+                attempt_number=retry_state.attempt_number,
+                initial_backoff_seconds=initial_backoff_seconds,
+                max_backoff_seconds=max_backoff_seconds,
+            )
+        ),
+        before_sleep=_build_before_sleep_callback(
+            operation_name=operation_name,
+            context=context,
+            max_attempts=max_attempts,
+        ),
+        sleep=retry_sleep,
+    )
+
+    async for attempt in retrying:
+        with attempt:
+            return await fn()
+
+    raise AssertionError("AsyncRetrying exited without returning or raising.")
+
+
+__all__ = [
+    "DEFAULT_MAX_ATTEMPTS",
+    "compute_retry_delay_seconds",
+    "get_error_retry_after_seconds",
+    "get_error_status_code",
+    "is_retryable_api_error",
+    "retry_api_call",
+    "retry_sleep",
+]
diff --git a/src/churro_ocr/providers/ocr.py b/src/churro_ocr/providers/ocr.py
index 9a80e39..4c40a49 100644
--- a/src/churro_ocr/providers/ocr.py
+++ b/src/churro_ocr/providers/ocr.py
@@ -4,7 +4,6 @@
 
 import asyncio
 import base64
-import logging
 from dataclasses import dataclass, field
 from io import BytesIO
 from threading import Lock
@@ -14,6 +13,7 @@
 from churro_ocr._internal.install import install_command_hint
 from churro_ocr._internal.litellm import LiteLLMTransport
 from churro_ocr._internal.prompt_logging import log_prompt_payload_once
+from churro_ocr._internal.retry import retry_api_call
 from churro_ocr.errors import ConfigurationError, ProviderError
 from churro_ocr.ocr import OCRBackend, OCRResult
 from churro_ocr.page_detection import DocumentPage
@@ -33,11 +33,6 @@
     build_ocr_conversation,
 )
 
-logger = logging.getLogger(__name__)
-_MISTRAL_TRANSIENT_STATUS_CODES = frozenset({408, 429, 500, 502, 503, 504, 520, 521, 522, 524})
-_MISTRAL_MAX_ATTEMPTS = 6
-_MISTRAL_INITIAL_BACKOFF_SECONDS = 1.0
-_MISTRAL_MAX_BACKOFF_SECONDS = 16.0
 _MISTRAL_REQUEST_TIMEOUT_SECONDS = 60.0
 
 
@@ -56,30 +51,6 @@ def _with_default_ocr_completion_kwargs(config: LiteLLMTransportConfig) -> LiteL
     )
 
 
-def _is_retryable_mistral_error(exc: Exception) -> bool:
-    status_code = getattr(exc, "status_code", None)
-    if isinstance(status_code, int):
-        return status_code in _MISTRAL_TRANSIENT_STATUS_CODES
-    return exc.__class__.__module__.startswith("httpx") or isinstance(exc, TimeoutError)
-
-
-def _get_mistral_retry_delay_seconds(exc: Exception, attempt: int) -> float:
-    headers = getattr(exc, "headers", None)
-    if headers is None:
-        raw_response = getattr(exc, "raw_response", None)
-        headers = getattr(raw_response, "headers", None)
-    retry_after = headers.get("retry-after") if hasattr(headers, "get") else None
-    if retry_after is not None:
-        try:
-            return max(0.0, float(retry_after))
-        except (TypeError, ValueError):
-            pass
-    return min(
-        _MISTRAL_INITIAL_BACKOFF_SECONDS * (2 ** (attempt - 1)),
-        _MISTRAL_MAX_BACKOFF_SECONDS,
-    )
-
-
 @dataclass(slots=True)
 class LiteLLMVisionOCRBackend(OCRBackend):
     """OCR backend for any LiteLLM-supported multimodal provider.
@@ -253,12 +224,20 @@ async def ocr(self, page: DocumentPage) -> OCRResult:
             set_logged=lambda: setattr(self, "_has_logged_prompt", True),
         )
         client = await self._get_client()
-        poller = await client.begin_analyze_document(
-            model_id=self.model_id,
-            body=BytesIO(image_bytes),
-            content_type="application/octet-stream",
+
+        async def _analyze_document() -> Any:
+            poller = await client.begin_analyze_document(
+                model_id=self.model_id,
+                body=BytesIO(image_bytes),
+                content_type="application/octet-stream",
+            )
+            return await poller.result()
+
+        result = await retry_api_call(
+            _analyze_document,
+            operation_name="Azure OCR request",
+            context=f"for model {self.model_id}",
         )
-        result = await poller.result()
         if not isinstance(result.content, str):
             raise ProviderError("Azure Document Intelligence returned no OCR text.")
         return build_ocr_result(
@@ -340,33 +319,21 @@ async def ocr(self, page: DocumentPage) -> OCRResult:
         )
         client = await self._get_client()
         document = {"type": "image_url", "image_url": image_url}
-        response: Any | None = None
-        for attempt in range(1, _MISTRAL_MAX_ATTEMPTS + 1):
-            try:
-                response = await asyncio.wait_for(
-                    client.ocr.process_async(
-                        model=self.model,
-                        document=document,
-                    ),
-                    timeout=_MISTRAL_REQUEST_TIMEOUT_SECONDS,
-                )
-                break
-            except Exception as exc:
-                if attempt >= _MISTRAL_MAX_ATTEMPTS or not _is_retryable_mistral_error(exc):
-                    raise
-                delay_seconds = _get_mistral_retry_delay_seconds(exc, attempt)
-                logger.warning(
-                    "Transient Mistral OCR failure for model %s "
-                    "(status=%s, attempt=%s/%s); retrying in %.1fs.",
-                    self.model,
-                    getattr(exc, "status_code", "unknown"),
-                    attempt,
-                    _MISTRAL_MAX_ATTEMPTS,
-                    delay_seconds,
-                )
-                await asyncio.sleep(delay_seconds)
-        if response is None:  # pragma: no cover - loop exits early via exception
-            raise ProviderError("Mistral OCR request failed before a response was returned.")
+
+        async def _process_ocr() -> Any:
+            return await asyncio.wait_for(
+                client.ocr.process_async(
+                    model=self.model,
+                    document=document,
+                ),
+                timeout=_MISTRAL_REQUEST_TIMEOUT_SECONDS,
+            )
+
+        response = await retry_api_call(
+            _process_ocr,
+            operation_name="Mistral OCR request",
+            context=f"for model {self.model}",
+        )
         if not response.pages:
             raise ProviderError("Mistral OCR returned no pages.")
         return build_ocr_result(
diff --git a/src/churro_ocr/providers/page_detection.py b/src/churro_ocr/providers/page_detection.py
index cee234d..3ff6362 100644
--- a/src/churro_ocr/providers/page_detection.py
+++ b/src/churro_ocr/providers/page_detection.py
@@ -13,6 +13,7 @@
 from churro_ocr._internal.install import install_command_hint
 from churro_ocr._internal.litellm import LiteLLMTransport
 from churro_ocr._internal.logging import logger
+from churro_ocr._internal.retry import retry_api_call
 from churro_ocr._internal.runtime import run_sync
 from churro_ocr.errors import ConfigurationError, ProviderError
 from churro_ocr.page_detection import PageCandidate, PageDetectionBackend
@@ -1213,12 +1214,21 @@ async def detect(self, image: Image.Image) -> list[PageCandidate]:
             credential=AzureKeyCredential(self.api_key),
         )
         try:
-            poller = await client.begin_analyze_document(
-                model_id=self.model_id,
-                body=BytesIO(buffer.getvalue()),
-                content_type="application/octet-stream",
+            image_bytes = buffer.getvalue()
+
+            async def _analyze_document() -> Any:
+                poller = await client.begin_analyze_document(
+                    model_id=self.model_id,
+                    body=BytesIO(image_bytes),
+                    content_type="application/octet-stream",
+                )
+                return await poller.result()
+
+            result = await retry_api_call(
+                _analyze_document,
+                operation_name="Azure page detection request",
+                context=f"for model {self.model_id}",
             )
-            result = await poller.result()
         finally:
             await client.close()
 
diff --git a/tests/test_internal_helpers.py b/tests/test_internal_helpers.py
index 240581a..42edae9 100644
--- a/tests/test_internal_helpers.py
+++ b/tests/test_internal_helpers.py
@@ -12,6 +12,7 @@
 
 import churro_ocr._internal.litellm as litellm_module
 import churro_ocr._internal.prompt_logging as prompt_logging_module
+import churro_ocr._internal.retry as retry_module
 from churro_ocr._internal import logging as logging_module
 from churro_ocr._internal.image import image_to_base64, load_image
 from churro_ocr._internal.litellm import LiteLLMTransport, complete_text
@@ -262,7 +263,10 @@ def test_configure_disk_cache_enables_and_updates_cache(monkeypatch: pytest.Monk
 async def test_transport_complete_text_raises_provider_error_on_failure(
     monkeypatch: pytest.MonkeyPatch,
 ) -> None:
+    calls = {"acompletion": 0}
+
     async def _failing_acompletion(**_: object) -> object:
+        calls["acompletion"] += 1
         raise RuntimeError("boom")
 
     fake_module = _make_fake_litellm_module(acompletion=_failing_acompletion)
@@ -275,6 +279,49 @@ async def _failing_acompletion(**_: object) -> object:
             model="example/model",
             messages=[{"role": "user", "content": [{"type": "text", "text": "hello"}]}],
         )
+    assert calls == {"acompletion": 1}
+
+
+@pytest.mark.asyncio
+async def test_transport_complete_text_retries_transient_errors(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    calls = {"acompletion": 0}
+    sleep_calls: list[float] = []
+
+    class FakeLiteLLMError(Exception):
+        def __init__(self, status_code: int, headers: dict[str, str] | None = None) -> None:
+            self.status_code = status_code
+            self.headers = headers or {}
+            self.raw_response = SimpleNamespace(headers=self.headers)
+            super().__init__(f"Status {status_code}")
+
+    async def _fake_sleep(delay: float) -> None:
+        sleep_calls.append(delay)
+
+    async def _flaky_acompletion(**_: object) -> object:
+        calls["acompletion"] += 1
+        if calls["acompletion"] == 1:
+            raise FakeLiteLLMError(429, headers={"retry-after": "3"})
+        return SimpleNamespace(
+            choices=[SimpleNamespace(message=SimpleNamespace(content="ok"))],
+            _hidden_params={},
+        )
+
+    fake_module = _make_fake_litellm_module(acompletion=_flaky_acompletion)
+    monkeypatch.setitem(sys.modules, "litellm", fake_module)
+    monkeypatch.setattr(litellm_module, "_INITIALIZED", False)
+    monkeypatch.setattr(retry_module, "retry_sleep", _fake_sleep)
+
+    transport = LiteLLMTransport()
+    result = await transport.complete_text(
+        model="example/model",
+        messages=[{"role": "user", "content": [{"type": "text", "text": "hello"}]}],
+    )
+
+    assert result == "ok"
+    assert calls == {"acompletion": 2}
+    assert sleep_calls == [3.0]
 
 
 @pytest.mark.asyncio
diff --git a/tests/test_providers.py b/tests/test_providers.py
index 3302c7d..ca50a88 100644
--- a/tests/test_providers.py
+++ b/tests/test_providers.py
@@ -9,6 +9,7 @@
 import pytest
 from PIL import Image
 
+import churro_ocr._internal.retry as retry_module
 from churro_ocr._internal.litellm import LiteLLMTransport
 from churro_ocr.errors import ProviderError
 from churro_ocr.page_detection import DocumentPage
@@ -304,6 +305,93 @@ def __init__(self, key: str) -> None:
     assert calls == {"client_inits": 1, "requests": 2}
 
 
+@pytest.mark.asyncio
+async def test_azure_ocr_backend_retries_transient_errors(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    calls = {"client_inits": 0, "requests": 0}
+    sleep_calls: list[float] = []
+    image = Image.new("RGB", (10, 10), color="white")
+    encoded = base64.b64encode(b"image-bytes").decode("ascii")
+
+    class FakeAzureError(Exception):
+        def __init__(self, status_code: int, headers: dict[str, str] | None = None) -> None:
+            self.status_code = status_code
+            self.headers = headers or {}
+            self.response = SimpleNamespace(headers=self.headers)
+            super().__init__(f"Status {status_code}")
+
+    class FakePoller:
+        async def result(self) -> SimpleNamespace:
+            return SimpleNamespace(content="azure text")
+
+    class FakeClient:
+        def __init__(self, *, endpoint: str, credential: Any) -> None:
+            calls["client_inits"] += 1
+            assert endpoint == "https://example.test"
+            assert credential.key == "secret"
+
+        async def begin_analyze_document(
+            self,
+            *,
+            model_id: str,
+            body: Any,
+            content_type: str,
+        ) -> FakePoller:
+            calls["requests"] += 1
+            assert model_id == "prebuilt-layout"
+            assert body.read() == b"image-bytes"
+            assert content_type == "application/octet-stream"
+            if calls["requests"] < 3:
+                raise FakeAzureError(503)
+            return FakePoller()
+
+    class FakeAzureKeyCredential:
+        def __init__(self, key: str) -> None:
+            self.key = key
+
+    async def _fake_sleep(delay: float) -> None:
+        sleep_calls.append(delay)
+
+    azure_document_module = ModuleType("azure.ai.documentintelligence.aio")
+    cast("Any", azure_document_module).DocumentIntelligenceClient = FakeClient
+    azure_credentials_module = ModuleType("azure.core.credentials")
+    cast("Any", azure_credentials_module).AzureKeyCredential = FakeAzureKeyCredential
+    monkeypatch.setitem(sys.modules, "azure.ai.documentintelligence.aio", azure_document_module)
+    monkeypatch.setitem(sys.modules, "azure.core.credentials", azure_credentials_module)
+    monkeypatch.setattr(retry_module, "retry_sleep", _fake_sleep)
+    monkeypatch.setattr(
+        "churro_ocr.providers.ocr.image_to_base64",
+        lambda actual_image, format_name: (
+            (
+                "image/jpeg",
+                encoded,
+            )
+            if actual_image.size == image.size and actual_image.mode == "RGB" and format_name == "JPEG"
+            else ("", "")
+        ),
+    )
+
+    backend = cast(
+        "AzureDocumentIntelligenceOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="azure",
+                options=AzureDocumentIntelligenceOptions(
+                    endpoint="https://example.test",
+                    api_key="secret",
+                ),
+            )
+        ),
+    )
+
+    result = await backend.ocr(DocumentPage(page_index=0, image=image, source_index=0))
+
+    assert result.text == "azure text"
+    assert calls == {"client_inits": 1, "requests": 3}
+    assert sleep_calls == [1.0, 2.0]
+
+
 @pytest.mark.asyncio
 async def test_mistral_ocr_backend_reuses_client(monkeypatch: pytest.MonkeyPatch) -> None:
     calls = {"client_inits": 0, "requests": 0}
@@ -410,7 +498,7 @@ async def _fake_sleep(delay: float) -> None:
             else ("", "")
         ),
     )
-    monkeypatch.setattr("churro_ocr.providers.ocr.asyncio.sleep", _fake_sleep)
+    monkeypatch.setattr(retry_module, "retry_sleep", _fake_sleep)
 
     backend = cast(
         "MistralOCRBackend",
@@ -483,7 +571,7 @@ async def _fake_wait_for(awaitable: Any, **kwargs: float) -> Any:
             else ("", "")
         ),
     )
-    monkeypatch.setattr("churro_ocr.providers.ocr.asyncio.sleep", _fake_sleep)
+    monkeypatch.setattr(retry_module, "retry_sleep", _fake_sleep)
     monkeypatch.setattr("churro_ocr.providers.ocr.asyncio.wait_for", _fake_wait_for)
 
     backend = cast(
@@ -553,7 +641,7 @@ async def _fake_sleep(delay: float) -> None:
             else ("", "")
         ),
     )
-    monkeypatch.setattr("churro_ocr.providers.ocr.asyncio.sleep", _fake_sleep)
+    monkeypatch.setattr(retry_module, "retry_sleep", _fake_sleep)
 
     backend = cast(
         "MistralOCRBackend",
@@ -1302,6 +1390,83 @@ def __init__(self, key: str) -> None:
     assert calls["closes"] == 1
 
 
+@pytest.mark.asyncio
+async def test_azure_page_detector_retries_transient_errors(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    calls = {"client_inits": 0, "requests": 0, "closes": 0}
+    sleep_calls: list[float] = []
+
+    class FakeAzureError(Exception):
+        def __init__(self, status_code: int, headers: dict[str, str] | None = None) -> None:
+            self.status_code = status_code
+            self.headers = headers or {}
+            self.response = SimpleNamespace(headers=self.headers)
+            super().__init__(f"Status {status_code}")
+
+    class FakePoller:
+        async def result(self) -> SimpleNamespace:
+            return SimpleNamespace(
+                pages=[
+                    SimpleNamespace(
+                        polygon=[0, 0, 100, 0, 100, 200, 0, 200, 0, 0],
+                        width=100,
+                        height=200,
+                        page_number=1,
+                        unit="pixel",
+                        angle=None,
+                    )
+                ]
+            )
+
+    class FakeClient:
+        def __init__(self, *, endpoint: str, credential: Any) -> None:
+            calls["client_inits"] += 1
+            assert endpoint == "https://example.test"
+            assert credential.key == "secret"
+
+        async def begin_analyze_document(
+            self,
+            *,
+            model_id: str,
+            body: Any,
+            content_type: str,
+        ) -> FakePoller:
+            calls["requests"] += 1
+            assert model_id == "prebuilt-layout"
+            assert body.read()
+            assert content_type == "application/octet-stream"
+            if calls["requests"] == 1:
+                raise FakeAzureError(429, headers={"retry-after": "4"})
+            return FakePoller()
+
+        async def close(self) -> None:
+            calls["closes"] += 1
+
+    class FakeAzureKeyCredential:
+        def __init__(self, key: str) -> None:
+            self.key = key
+
+    async def _fake_sleep(delay: float) -> None:
+        sleep_calls.append(delay)
+
+    azure_document_module = ModuleType("azure.ai.documentintelligence.aio")
+    cast(Any, azure_document_module).DocumentIntelligenceClient = FakeClient
+    azure_credentials_module = ModuleType("azure.core.credentials")
+    cast(Any, azure_credentials_module).AzureKeyCredential = FakeAzureKeyCredential
+    monkeypatch.setitem(sys.modules, "azure.ai.documentintelligence.aio", azure_document_module)
+    monkeypatch.setitem(sys.modules, "azure.core.credentials", azure_credentials_module)
+    monkeypatch.setattr(retry_module, "retry_sleep", _fake_sleep)
+
+    detector = AzurePageDetector(endpoint="https://example.test", api_key="secret")
+    candidates = await detector.detect(Image.new("RGB", (100, 200), color="white"))
+
+    assert len(candidates) == 1
+    assert candidates[0].bbox == (0.0, 0.0, 100.0, 200.0)
+    assert calls == {"client_inits": 1, "requests": 2, "closes": 1}
+    assert sleep_calls == [4.0]
+
+
 def test_azure_page_detector_type_is_public() -> None:
     detector = AzurePageDetector(endpoint="https://example.test", api_key="secret")
     assert detector.model_id == "prebuilt-layout"

From a0377ac56bc3ae7cd05e3e3bfc400489fd03a45d Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Mon, 6 Apr 2026 14:28:03 +0000
Subject: [PATCH 15/28] style(providers): format specs module

---
 src/churro_ocr/providers/specs.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/src/churro_ocr/providers/specs.py b/src/churro_ocr/providers/specs.py
index fbbcd8f..ee0b953 100644
--- a/src/churro_ocr/providers/specs.py
+++ b/src/churro_ocr/providers/specs.py
@@ -2,10 +2,10 @@
 
 from __future__ import annotations
 
+import re
 from collections.abc import Callable, Sequence
 from dataclasses import dataclass, field
 from pathlib import Path
-import re
 from typing import TYPE_CHECKING, Any, Literal, cast
 
 from PIL import Image
@@ -68,9 +68,7 @@ def validate_mistral_ocr_model(
     if model is None:
         raise ConfigurationError(f"{context} requires `model` to be one of: {supported_models}.")
     if model not in MISTRAL_OCR_MODEL_IDS:
-        raise ConfigurationError(
-            f"{context} only supports `model` values {supported_models}; got {model!r}."
-        )
+        raise ConfigurationError(f"{context} only supports `model` values {supported_models}; got {model!r}.")
     return cast(MistralOCRModel, model)
 
 

From 9aecd0f878c640e5c02954dbfc28ae838eb2478e Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Mon, 6 Apr 2026 14:28:09 +0000
Subject: [PATCH 16/28] chore(benchmarks): refresh benchmark results

---
 benchmark_results.json | 37 ++++++++++++++++++++++++++++++++-----
 1 file changed, 32 insertions(+), 5 deletions(-)

diff --git a/benchmark_results.json b/benchmark_results.json
index 0fc66a2..0946d93 100644
--- a/benchmark_results.json
+++ b/benchmark_results.json
@@ -160,6 +160,24 @@
     "printed": 69.766,
     "handwritten": 41.5165,
     "total": 54.5547
+  },
+   {
+    "modelName": "olmOCR 2",
+    "modelId": "allenai/olmOCR-2-7B-1025",
+    "modelUrl": "https://huggingface.co/allenai/olmOCR-2-7B-1025",
+    "hasIcon": false,
+    "printed": 71.1,
+    "handwritten": 44.6,
+    "total": 56.8
+  },
+  {
+    "modelName": "LiquidAI LFM2.5 VL (1.6B)",
+    "modelId": "LiquidAI/LFM2.5-VL-1.6B",
+    "modelUrl": "https://huggingface.co/LiquidAI/LFM2.5-VL-1.6B",
+    "hasIcon": false,
+    "printed": 40.2,
+    "handwritten": 25.5,
+    "total": 32.3
   },
   {
     "modelName": "Qwen 2.5 VL (3B)",
@@ -225,13 +243,22 @@
     "total": 45.5566
   },
   {
-    "modelName": "Mistral OCR",
-    "modelId": null,
+    "modelName": "Mistral OCR 2",
+    "modelId": "mistral-ocr-2505",
+    "modelUrl": null,
+    "hasIcon": false,
+    "printed": 64.3,
+    "handwritten": 30.4,
+    "total": 46.0
+  },
+    {
+    "modelName": "Mistral OCR 3",
+    "modelId": "mistral-ocr-2512",
     "modelUrl": null,
     "hasIcon": false,
-    "printed": 64.0418,
-    "handwritten": 29.4388,
-    "total": 45.4094
+    "printed": 71.5,
+    "handwritten": 47.6,
+    "total": 58.6
   },
   {
     "modelName": "GPT-5",

From 3b5101f717c93ecb5fa3f88ae3304f41c0d917c0 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Mon, 6 Apr 2026 15:08:25 +0000
Subject: [PATCH 17/28] docs(benchmarking): update benchmarking instructions
 and clarify output file details

---
 docs/benchmarking.md | 15 +++++++--------
 1 file changed, 7 insertions(+), 8 deletions(-)

diff --git a/docs/benchmarking.md b/docs/benchmarking.md
index d1e8263..f21609a 100644
--- a/docs/benchmarking.md
+++ b/docs/benchmarking.md
@@ -1,10 +1,9 @@
 # Benchmarking
 
-This page is for reproducing CHURRO-DS benchmark runs from a repo checkout.
+For the official leaderboard results, see the [Benchmark Leaderboard](leaderboard.md).
 
-Run these commands from the repo root after `pixi install`.
+This page describes how to benchmark your own model on [CHURRO-DS](https://huggingface.co/datasets/stanford-oval/churro-dataset). Please open a pull request if you would like to add your model to the official leaderboard.
 
-For the current committed benchmark snapshot, see the [Benchmark Leaderboard](leaderboard.md). Contributor setup, test commands, and package checks live in [Contributing](contributing.md).
 
 ## Smallest Useful Run
 
@@ -18,6 +17,7 @@ pixi run python -m tooling.benchmarking.benchmark \
 ```
 
 By default, results are written under `workdir/results/<split>/`.
+The evaluation pipeline strips the default OCR wrapper tag, flattens supported XML-like OCR output, normalizes whitespace and punctuation, and applies additional Arabic normalization for languages with Arabic script (Arabic and Persian).
 
 ## Common Flags
 
@@ -30,27 +30,26 @@ By default, results are written under `workdir/results/<split>/`.
 
 ## Output Files
 
-Each benchmark run writes one result directory. The important files are:
+Each benchmark run writes one result directory. The directory contains two JSON files:
 
 - `outputs.json`: one row per evaluated page with the raw predicted text, gold text, and page-level metrics
 - `all_metrics.json`: aggregate metrics grouped across the full run, by main language, by document type, and by the language/type combination
 
-`outputs.json` stores page-level metric values as raw fractions. `all_metrics.json` converts aggregate values to percentages and rounds them to one decimal place. The evaluation pipeline strips the default OCR wrapper tag, flattens supported XML-like OCR output, normalizes whitespace and punctuation, and applies additional Arabic normalization for Arabic and Persian examples.
 
 ## Filtering And Slicing
 
-Subset filters are applied before offset and limit:
+You can run benchmarks on subsets of the data by combining `--language`, `--document-type`, `--offset`, and `--input-size`. The filters are applied in the following order:
 
 - `--language` filters on `main_language`
 - `--document-type` filters on `document_type`
 - `--offset` skips rows after filtering
 - `--input-size` limits rows after filtering and offset
 
-That means `--language Arabic --offset 100 --input-size 50` selects rows 101 to 150 from the Arabic-only subset, not from the full split.
+That means for example `--language Arabic --offset 100 --input-size 50` selects rows 101 to 150 from the Arabic-only subset, not from the full split.
 
 ## Example Commands
 
-If you want to benchmark a vLLM-served model, run vLLM separately and point `--backend openai-compatible` at its OpenAI-compatible endpoint. See the [official vLLM serving docs](https://docs.vllm.ai/en/stable/serving/openai_compatible_server.html).
+If you want to benchmark a model using vLLM, run a vLLM server separately and point `--backend openai-compatible` at its OpenAI-compatible endpoint. See the [official vLLM serving docs](https://docs.vllm.ai/en/stable/serving/openai_compatible_server.html).
 
 | Model | Model ID | Backend | Full command |
 | --- | --- | --- | --- |

From 9dc80f79e010aa8492822abba74c1aa6905e7dc0 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Mon, 6 Apr 2026 15:30:16 +0000
Subject: [PATCH 18/28] docs: add logos to the benchmark table

---
 benchmark_results.json                   | 116 ++++++++++++++---------
 docs/_static/css/custom.css              |  71 +++++++++++++-
 docs/_static/img/ai2-symbol.svg          |   4 +
 docs/_static/img/azure-logo.png          | Bin 0 -> 93963 bytes
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 docs/_static/img/gemini-symbol.png       | Bin 0 -> 8233 bytes
 docs/_static/img/gemma-icon.svg          |   1 +
 docs/_static/img/mistral-logo.svg        |   1 +
 docs/_static/img/nvidia-logo.svg         |  32 +++++++
 docs/_static/img/openai-symbol.svg       |   5 +
 docs/_static/img/qwen-logo.svg           |  15 +++
 docs/_static/img/reducto-logomark.svg    |   3 +
 docs/_static/js/benchmark-leaderboard.js |  61 ++++++++----
 13 files changed, 250 insertions(+), 66 deletions(-)
 create mode 100644 docs/_static/img/ai2-symbol.svg
 create mode 100644 docs/_static/img/azure-logo.png
 create mode 100644 docs/_static/img/claude-symbol.svg
 create mode 100644 docs/_static/img/gemini-symbol.png
 create mode 100644 docs/_static/img/gemma-icon.svg
 create mode 100644 docs/_static/img/mistral-logo.svg
 create mode 100644 docs/_static/img/nvidia-logo.svg
 create mode 100644 docs/_static/img/openai-symbol.svg
 create mode 100644 docs/_static/img/qwen-logo.svg
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index 0946d93..21183cc 100644
--- a/benchmark_results.json
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     "modelUrl": "https://ai.google.dev/gemini-api/docs/models",
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-    "hasIcon": false,
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     "modelUrl": "https://platform.openai.com/docs/models/gpt-5-mini",
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-    "hasIcon": false,
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@@ -129,7 +132,7 @@
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     "modelId": "reducto/RolmOCR",
     "modelUrl": "https://huggingface.co/reducto/RolmOCR",
-    "hasIcon": false,
+    "iconPath": "_static/img/reducto-logomark.svg",
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@@ -138,7 +141,7 @@
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     "modelUrl": "https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct",
-    "hasIcon": false,
+    "iconPath": "_static/img/qwen-logo.svg",
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@@ -147,7 +150,7 @@
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     "modelUrl": "https://huggingface.co/nanonets/Nanonets-OCR-s",
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@@ -156,16 +159,16 @@
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     "modelUrl": "https://huggingface.co/allenai/olmOCR-2-7B-1025",
-    "hasIcon": false,
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@@ -174,7 +177,7 @@
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     "modelUrl": "https://huggingface.co/LiquidAI/LFM2.5-VL-1.6B",
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@@ -183,7 +186,7 @@
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     "modelUrl": "https://huggingface.co/Qwen/Qwen2.5-VL-3B-Instruct",
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@@ -192,7 +195,8 @@
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-    "hasIcon": false,
+    "iconPath": "_static/img/openai-symbol.svg",
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@@ -201,7 +205,7 @@
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-    "hasIcon": false,
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-    "hasIcon": false,
+    "iconPath": "_static/img/openai-symbol.svg",
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@@ -219,7 +224,7 @@
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-    "hasIcon": false,
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-    "hasIcon": false,
+    "iconPath": "_static/img/openai-symbol.svg",
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@@ -237,7 +243,8 @@
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     "modelUrl": "https://platform.openai.com/docs/models/o3",
-    "hasIcon": false,
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@@ -246,7 +253,7 @@
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     "modelId": "mistral-ocr-2505",
     "modelUrl": null,
-    "hasIcon": false,
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@@ -255,7 +262,7 @@
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     "modelId": "mistral-ocr-2512",
     "modelUrl": null,
-    "hasIcon": false,
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     "modelId": "gpt-5-2025-08-07",
     "modelUrl": "https://platform.openai.com/docs/models/gpt-5",
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+    "iconPath": "_static/img/openai-symbol.svg",
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@@ -291,16 +300,26 @@
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-    "hasIcon": false,
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+    "modelId": "Qwen/Qwen3.5-2B",
+    "modelUrl": "https://huggingface.co/Qwen/Qwen3.5-2B",
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+    "printed": 57.6,
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+  },
   {
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-    "hasIcon": false,
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     "modelUrl": "https://huggingface.co/openbmb/MiniCPM-V-4_5",
-    "hasIcon": false,
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@@ -318,7 +337,8 @@
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-    "hasIcon": false,
+    "iconPath": "_static/img/openai-symbol.svg",
+    "iconInvertDark": true,
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@@ -327,7 +347,7 @@
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-    "hasIcon": false,
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@@ -336,16 +356,25 @@
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+  {
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+    "modelId": "Qwen/Qwen3.5-0.8B",
+    "modelUrl": "https://huggingface.co/Qwen/Qwen3.5-0.8B",
+    "iconPath": "_static/img/qwen-logo.svg",
+    "printed": 41.7,
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+  },
   {
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     "modelId": "YannQi/R-4B",
     "modelUrl": "https://huggingface.co/YannQi/R-4B",
-    "hasIcon": false,
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     "modelId": "gpt-5-nano-2025-08-07",
     "modelUrl": "https://platform.openai.com/docs/models/gpt-5-nano",
-    "hasIcon": false,
+    "iconPath": "_static/img/openai-symbol.svg",
+    "iconInvertDark": true,
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@@ -363,7 +393,7 @@
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     "modelUrl": "https://huggingface.co/nvidia/Llama-3.1-Nemotron-Nano-VL-8B-V1",
-    "hasIcon": false,
+    "iconPath": "_static/img/nvidia-logo.svg",
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@@ -372,7 +402,7 @@
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diff --git a/docs/_static/css/custom.css b/docs/_static/css/custom.css
index b750fbf..df6d205 100644
--- a/docs/_static/css/custom.css
+++ b/docs/_static/css/custom.css
@@ -112,6 +112,10 @@ html[data-theme="dark"] {
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 }
 
+.benchmark-table tbody tr:nth-child(even) {
+  background: rgba(139, 69, 31, 0.03);
+}
+
 .benchmark-sort-button {
   align-items: center;
   appearance: none;
@@ -150,11 +154,46 @@ html[data-theme="dark"] {
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-.benchmark-model-icon {
-  border-radius: 0.4rem;
-  height: 1.65rem;
+.benchmark-model-icon-frame {
+  align-items: center;
+  display: inline-flex;
+  flex: 0 0 auto;
+  height: 1.9rem;
+  justify-content: center;
   margin-top: 0.1rem;
-  width: 1.65rem;
+  width: auto;
+}
+
+.benchmark-model-icon {
+  background: transparent;
+  border-radius: 0;
+  display: block;
+  height: 100%;
+  max-height: 100%;
+  max-width: 3rem;
+  width: auto;
+}
+
+.benchmark-model-icon-placeholder {
+  align-items: center;
+  background: rgba(139, 69, 31, 0.06);
+  border: 1px dashed rgba(139, 69, 31, 0.22);
+  border-radius: 999px;
+  box-sizing: border-box;
+  color: var(--pst-color-text-muted);
+  display: inline-flex;
+  height: 1.9rem;
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+}
+
+.benchmark-model-icon-placeholder::before {
+  background: currentColor;
+  border-radius: 999px;
+  content: "";
+  height: 0.34rem;
+  opacity: 0.45;
+  width: 0.34rem;
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 .benchmark-model-text {
@@ -190,6 +229,30 @@ html[data-theme="dark"] .benchmark-table th {
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+html[data-theme="dark"] .benchmark-table tbody tr:nth-child(even) {
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+}
+
+html[data-theme="dark"] .benchmark-model-icon-placeholder,
+[data-bs-theme="dark"] .benchmark-model-icon-placeholder {
+  background: rgba(244, 178, 94, 0.08);
+  border-color: rgba(244, 178, 94, 0.24);
+}
+
+html[data-theme="dark"] .bd-content .benchmark-model-icon,
+html[data-theme="dark"] .bd-content .benchmark-model-icon-frame,
+[data-bs-theme="dark"] .bd-content .benchmark-model-icon,
+[data-bs-theme="dark"] .bd-content .benchmark-model-icon-frame {
+  background: transparent;
+  box-shadow: none;
+  border-radius: 0;
+}
+
+html[data-theme="dark"] .bd-content .benchmark-model-icon--invert-dark,
+[data-bs-theme="dark"] .bd-content .benchmark-model-icon--invert-dark {
+  filter: invert(1);
+}
+
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new file mode 100644
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diff --git a/docs/_static/img/nvidia-logo.svg b/docs/_static/img/nvidia-logo.svg
new file mode 100644
index 0000000..9393002
--- /dev/null
+++ b/docs/_static/img/nvidia-logo.svg
@@ -0,0 +1,32 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 16.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<svg version="1.1" id="svg2" xmlns:svg="http://www.w3.org/2000/svg"
+	 xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px" width="351.46px"
+	 height="258.785px" viewBox="35.188 31.512 351.46 258.785" enable-background="new 35.188 31.512 351.46 258.785"
+	 xml:space="preserve">
+<title  id="title4">generated by pstoedit version:3.44 from NVBadge_2D.eps</title>
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+<path id="path21" fill="#77B900" d="M82.211,102.414c0,0,22.504-33.203,67.437-36.638V53.73
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+	c0,0-15.461-20.277-41.524-20.277C155.021,80.172,152.31,80.371,149.648,80.656"/>
+</svg>
diff --git a/docs/_static/img/openai-symbol.svg b/docs/_static/img/openai-symbol.svg
new file mode 100644
index 0000000..74d9b1b
--- /dev/null
+++ b/docs/_static/img/openai-symbol.svg
@@ -0,0 +1,5 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<svg id="Layer_1" xmlns="http://www.w3.org/2000/svg" version="1.1" viewBox="0 0 158.7128 157.296">
+  <!-- Generator: Adobe Illustrator 29.2.1, SVG Export Plug-In . SVG Version: 2.1.0 Build 116)  -->
+  <path d="M60.8734,57.2556v-14.9432c0-1.2586.4722-2.2029,1.5728-2.8314l30.0443-17.3023c4.0899-2.3593,8.9662-3.4599,13.9988-3.4599,18.8759,0,30.8307,14.6289,30.8307,30.2006,0,1.1007,0,2.3593-.158,3.6178l-31.1446-18.2467c-1.8872-1.1006-3.7754-1.1006-5.6629,0l-39.4812,22.9651ZM131.0276,115.4561v-35.7074c0-2.2028-.9446-3.7756-2.8318-4.8763l-39.481-22.9651,12.8982-7.3934c1.1007-.6285,2.0453-.6285,3.1458,0l30.0441,17.3024c8.6523,5.0341,14.4708,15.7296,14.4708,26.1107,0,11.9539-7.0769,22.965-18.2461,27.527v.0021ZM51.593,83.9964l-12.8982-7.5497c-1.1007-.6285-1.5728-1.5728-1.5728-2.8314v-34.6048c0-16.8303,12.8982-29.5722,30.3585-29.5722,6.607,0,12.7403,2.2029,17.9324,6.1349l-30.987,17.9324c-1.8871,1.1007-2.8314,2.6735-2.8314,4.8764v45.6159l-.0014-.0015ZM79.3562,100.0403l-18.4829-10.3811v-22.0209l18.4829-10.3811,18.4812,10.3811v22.0209l-18.4812,10.3811ZM91.2319,147.8591c-6.607,0-12.7403-2.2031-17.9324-6.1344l30.9866-17.9333c1.8872-1.1005,2.8318-2.6728,2.8318-4.8759v-45.616l13.0564,7.5498c1.1005.6285,1.5723,1.5728,1.5723,2.8314v34.6051c0,16.8297-13.0564,29.5723-30.5147,29.5723v.001ZM53.9522,112.7822l-30.0443-17.3024c-8.652-5.0343-14.471-15.7296-14.471-26.1107,0-12.1119,7.2356-22.9652,18.403-27.5272v35.8634c0,2.2028.9443,3.7756,2.8314,4.8763l39.3248,22.8068-12.8982,7.3938c-1.1007.6287-2.045.6287-3.1456,0ZM52.2229,138.5791c-17.7745,0-30.8306-13.3713-30.8306-29.8871,0-1.2585.1578-2.5169.3143-3.7754l30.987,17.9323c1.8871,1.1005,3.7757,1.1005,5.6628,0l39.4811-22.807v14.9435c0,1.2585-.4721,2.2021-1.5728,2.8308l-30.0443,17.3025c-4.0898,2.359-8.9662,3.4605-13.9989,3.4605h.0014ZM91.2319,157.296c19.0327,0,34.9188-13.5272,38.5383-31.4594,17.6164-4.562,28.9425-21.0779,28.9425-37.908,0-11.0112-4.719-21.7066-13.2133-29.4143.7867-3.3035,1.2595-6.607,1.2595-9.909,0-22.4929-18.2471-39.3247-39.3251-39.3247-4.2461,0-8.3363.6285-12.4262,2.045-7.0792-6.9213-16.8318-11.3254-27.5271-11.3254-19.0331,0-34.9191,13.5268-38.5384,31.4591C11.3255,36.0212,0,52.5373,0,69.3675c0,11.0112,4.7184,21.7065,13.2125,29.4142-.7865,3.3035-1.2586,6.6067-1.2586,9.9092,0,22.4923,18.2466,39.3241,39.3248,39.3241,4.2462,0,8.3362-.6277,12.426-2.0441,7.0776,6.921,16.8302,11.3251,27.5271,11.3251Z"/>
+</svg>
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diff --git a/docs/_static/img/qwen-logo.svg b/docs/_static/img/qwen-logo.svg
new file mode 100644
index 0000000..64be10b
--- /dev/null
+++ b/docs/_static/img/qwen-logo.svg
@@ -0,0 +1,15 @@
+<svg width="157.3" height="153.24" viewBox="17.52 17.52 157.3 153.24" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M174.82 108.75L155.38 75L165.64 57.75C166.46 56.31 166.46 54.53 165.64 53.09L155.38 35.84C154.86 34.91 153.87 34.33 152.78 34.33H114.88L106.14 19.03C105.62 18.1 104.63 17.52 103.54 17.52H83.3C82.21 17.52 81.22 18.1 80.7 19.03L61.26 52.77H41.02C39.93 52.77 38.94 53.35 38.42 54.28L28.16 71.53C27.34 72.97 27.34 74.75 28.16 76.19L45.52 107.5L36.78 122.8C35.96 124.24 35.96 126.02 36.78 127.46L47.04 144.71C47.56 145.64 48.55 146.22 49.64 146.22H87.54L96.28 161.52C96.8 162.45 97.79 163.03 98.88 163.03H119.12C120.21 163.03 121.2 162.45 121.72 161.52L141.16 127.78H158.52C159.61 127.78 160.6 127.2 161.12 126.27L171.38 109.02C172.2 107.58 172.2 105.8 171.38 104.36L174.82 108.75Z" fill="url(#paint0_radial)"/>
+<path d="M119.12 163.03H98.88L87.54 144.71H49.64L61.26 126.39H80.7L38.42 55.29H61.26L83.3 19.03L93.56 37.35L83.3 55.29H161.58L151.32 72.54L170.76 106.28H151.32L141.16 88.34L101.18 163.03H119.12Z" fill="white"/>
+<path d="M127.86 79.83H76.14L101.18 122.11L127.86 79.83Z" fill="url(#paint1_radial)"/>
+<defs>
+<radialGradient id="paint0_radial" cx="0" cy="0" r="1" gradientUnits="userSpaceOnUse" gradientTransform="translate(100 100) rotate(90) scale(100)">
+<stop stop-color="#665CEE"/>
+<stop offset="1" stop-color="#332E91"/>
+</radialGradient>
+<radialGradient id="paint1_radial" cx="0" cy="0" r="1" gradientUnits="userSpaceOnUse" gradientTransform="translate(100 100) rotate(90) scale(100)">
+<stop stop-color="#665CEE"/>
+<stop offset="1" stop-color="#332E91"/>
+</radialGradient>
+</defs>
+</svg>
diff --git a/docs/_static/img/reducto-logomark.svg b/docs/_static/img/reducto-logomark.svg
new file mode 100644
index 0000000..642c73e
--- /dev/null
+++ b/docs/_static/img/reducto-logomark.svg
@@ -0,0 +1,3 @@
+<svg width="400" height="400" viewBox="0 0 400 400" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path fill-rule="evenodd" clip-rule="evenodd" d="M85.3434 70.7805H314.657V240.307L226.44 329.219H85.3434V70.7805ZM107.796 93.2319H292.205V204.487H206.493V306.767H107.801L107.796 93.2319Z" fill="#5B0F5C"/>
+</svg>
diff --git a/docs/_static/js/benchmark-leaderboard.js b/docs/_static/js/benchmark-leaderboard.js
index f0beee2..240a202 100644
--- a/docs/_static/js/benchmark-leaderboard.js
+++ b/docs/_static/js/benchmark-leaderboard.js
@@ -10,6 +10,10 @@
     { key: "handwritten", label: "Handwritten", numeric: true },
     { key: "total", label: "Total", numeric: true },
   ];
+  const NUMERIC_COLUMNS = new Set(
+    COLUMN_DEFINITIONS.filter((column) => column.numeric).map((column) => column.key),
+  );
+  const DEFAULT_SORT_STATE = { key: "total", direction: "desc" };
 
   function contentRoot() {
     return document.documentElement.dataset.content_root || "";
@@ -32,15 +36,42 @@
     return SCORE_FORMATTER.format(value);
   }
 
+  function createIconFrame(row) {
+    const iconFrame = document.createElement("span");
+    iconFrame.className = "benchmark-model-icon-frame";
+
+    if (!row.iconPath) {
+      const placeholder = document.createElement("span");
+      placeholder.className = "benchmark-model-icon-placeholder";
+      placeholder.setAttribute("aria-hidden", "true");
+      iconFrame.append(placeholder);
+      return iconFrame;
+    }
+
+    const icon = document.createElement("img");
+    icon.className = "benchmark-model-icon";
+    if (row.iconInvertDark) {
+      icon.classList.add("benchmark-model-icon--invert-dark");
+    }
+    icon.alt = `${row.modelName} icon`;
+    icon.src = resolvePath(row.iconPath);
+    iconFrame.append(icon);
+
+    return iconFrame;
+  }
+
   function compareRows(left, right, sortState) {
     const { key, direction } = sortState;
     const multiplier = direction === "asc" ? 1 : -1;
     const leftValue = left[key];
     const rightValue = right[key];
 
-    if (typeof leftValue === "number" && typeof rightValue === "number") {
-      if (leftValue !== rightValue) {
-        return (leftValue - rightValue) * multiplier;
+    if (NUMERIC_COLUMNS.has(key)) {
+      const leftNumber = Number(leftValue);
+      const rightNumber = Number(rightValue);
+
+      if (!Number.isNaN(leftNumber) && !Number.isNaN(rightNumber) && leftNumber !== rightNumber) {
+        return (leftNumber - rightNumber) * multiplier;
       }
       return left.modelName.localeCompare(right.modelName);
     }
@@ -48,17 +79,11 @@
     return String(leftValue || "").localeCompare(String(rightValue || "")) * multiplier;
   }
 
-  function createModelCell(row, logoPath) {
+  function createModelCell(row) {
     const wrapper = document.createElement("div");
     wrapper.className = "benchmark-model";
 
-    if (row.hasIcon) {
-      const icon = document.createElement("img");
-      icon.className = "benchmark-model-icon";
-      icon.alt = `${row.modelName} icon`;
-      icon.src = logoPath;
-      wrapper.append(icon);
-    }
+    wrapper.append(createIconFrame(row));
 
     const textBlock = document.createElement("div");
     textBlock.className = "benchmark-model-text";
@@ -104,7 +129,7 @@
     return button;
   }
 
-  function renderLeaderboard(container, rows, sortState, logoPath) {
+  function renderLeaderboard(container, rows, sortState) {
     container.replaceChildren();
 
     const sortedRows = [...rows].sort((left, right) => compareRows(left, right, sortState));
@@ -130,7 +155,7 @@
         sortState.key = key;
         sortState.direction = key === "modelName" ? "asc" : "desc";
       }
-      renderLeaderboard(container, rows, sortState, logoPath);
+      renderLeaderboard(container, rows, sortState);
     };
 
     for (const column of COLUMN_DEFINITIONS) {
@@ -147,7 +172,7 @@
 
     sortedRows.forEach((row, index) => {
       const tr = document.createElement("tr");
-      if (row.hasIcon) {
+      if (row.iconPath) {
         tr.classList.add("is-featured");
       }
 
@@ -157,7 +182,7 @@
       tr.append(rankCell);
 
       const modelCell = document.createElement("td");
-      modelCell.append(createModelCell(row, logoPath));
+      modelCell.append(createModelCell(row));
       tr.append(modelCell);
 
       for (const key of ["printed", "handwritten", "total"]) {
@@ -184,8 +209,6 @@
   }
 
   async function initializeLeaderboard(container) {
-    const logoPath = resolvePath("_static/img/churro.png");
-
     try {
       const response = await fetch(resolvePath("_static/data/benchmark_results.json"));
       if (!response.ok) {
@@ -193,8 +216,8 @@
       }
 
       const rows = await response.json();
-      const sortState = { key: "total", direction: "desc" };
-      renderLeaderboard(container, rows, sortState, logoPath);
+      const sortState = { ...DEFAULT_SORT_STATE };
+      renderLeaderboard(container, rows, sortState);
     } catch (error) {
       renderError(container, "Unable to load the benchmark leaderboard data.");
       console.error("[benchmark-leaderboard] failed to initialize", error);

From b989362259318b94930c6fe11fd41f9af74e109e Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Tue, 7 Apr 2026 01:36:50 +0000
Subject: [PATCH 19/28] fix(ocr): allow empty model responses

---
 src/churro_ocr/_internal/litellm.py | 14 ++++++--
 src/churro_ocr/providers/ocr.py     |  1 +
 tests/test_internal_helpers.py      | 25 +++++++++++++
 tests/test_providers.py             | 54 ++++++++++++++++++++++++++++-
 4 files changed, 91 insertions(+), 3 deletions(-)

diff --git a/src/churro_ocr/_internal/litellm.py b/src/churro_ocr/_internal/litellm.py
index 23fb318..eaed37c 100644
--- a/src/churro_ocr/_internal/litellm.py
+++ b/src/churro_ocr/_internal/litellm.py
@@ -162,6 +162,7 @@ async def complete_text(
         messages: list[dict[str, Any]],
         timeout_seconds: int = 600,
         output_json: bool = False,
+        allow_empty: bool = False,
     ) -> str:
         """Run a LiteLLM completion and return the text content."""
         if self._config.cache_dir is not None:
@@ -197,9 +198,16 @@ async def complete_text(
         self._record_response_cost(model=model, response=response)
 
         answer = response.choices[0].message.content
-        if not isinstance(answer, str) or not answer.strip():
+        if isinstance(answer, str):
+            if answer.strip():
+                return answer
+            if allow_empty:
+                return ""
+        elif answer is None and allow_empty:
+            return ""
+        if not isinstance(answer, str):
             raise ProviderError(f"LiteLLM returned empty output for model '{model}'.")
-        return answer
+        raise ProviderError(f"LiteLLM returned empty output for model '{model}'.")
 
     def _resolved_image_detail(self) -> str | None:
         return "high" if self._config.image_detail is None else self._config.image_detail
@@ -333,6 +341,7 @@ async def complete_text(
     api_version: str | None = None,
     timeout_seconds: int = 600,
     output_json: bool = False,
+    allow_empty: bool = False,
     completion_kwargs: dict[str, object] | None = None,
 ) -> str:
     """Run a LiteLLM completion and return the text content."""
@@ -349,6 +358,7 @@ async def complete_text(
         messages=messages,
         timeout_seconds=timeout_seconds,
         output_json=output_json,
+        allow_empty=allow_empty,
     )
 
 
diff --git a/src/churro_ocr/providers/ocr.py b/src/churro_ocr/providers/ocr.py
index 4c40a49..452b47d 100644
--- a/src/churro_ocr/providers/ocr.py
+++ b/src/churro_ocr/providers/ocr.py
@@ -105,6 +105,7 @@ async def ocr(self, page: DocumentPage) -> OCRResult:
         text = await self.transport.complete_text(
             model=self.model,
             messages=messages,
+            allow_empty=True,
         )
         return build_ocr_result(
             text,
diff --git a/tests/test_internal_helpers.py b/tests/test_internal_helpers.py
index 42edae9..427bdb4 100644
--- a/tests/test_internal_helpers.py
+++ b/tests/test_internal_helpers.py
@@ -144,12 +144,14 @@ async def _fake_complete_text(
         messages: list[dict[str, object]],
         timeout_seconds: int = 600,
         output_json: bool = False,
+        allow_empty: bool = False,
     ) -> str:
         captured["config"] = self.config
         captured["model"] = model
         captured["messages"] = messages
         captured["timeout_seconds"] = timeout_seconds
         captured["output_json"] = output_json
+        captured["allow_empty"] = allow_empty
         return "ok"
 
     monkeypatch.setattr(
@@ -177,6 +179,7 @@ async def _fake_complete_text(
     assert config.completion_kwargs == {"temperature": 0}
     assert captured["timeout_seconds"] == 42
     assert captured["output_json"] is True
+    assert captured["allow_empty"] is False
 
 
 def test_extract_response_cost_uses_completion_cost_fallback(monkeypatch: pytest.MonkeyPatch) -> None:
@@ -344,6 +347,28 @@ async def _empty_acompletion(**_: object) -> object:
         )
 
 
+@pytest.mark.asyncio
+async def test_transport_complete_text_allows_empty_output(monkeypatch: pytest.MonkeyPatch) -> None:
+    async def _empty_acompletion(**_: object) -> object:
+        return SimpleNamespace(
+            choices=[SimpleNamespace(message=SimpleNamespace(content="   "))],
+            _hidden_params={},
+        )
+
+    fake_module = _make_fake_litellm_module(acompletion=_empty_acompletion)
+    monkeypatch.setitem(sys.modules, "litellm", fake_module)
+    monkeypatch.setattr(litellm_module, "_INITIALIZED", False)
+
+    transport = LiteLLMTransport()
+    result = await transport.complete_text(
+        model="example/model",
+        messages=[{"role": "user", "content": [{"type": "text", "text": "hello"}]}],
+        allow_empty=True,
+    )
+
+    assert result == ""
+
+
 def test_logger_adapter_supports_success_fallback_and_other_levels() -> None:
     records: list[tuple[str, str]] = []
 
diff --git a/tests/test_providers.py b/tests/test_providers.py
index ca50a88..7efba90 100644
--- a/tests/test_providers.py
+++ b/tests/test_providers.py
@@ -71,6 +71,7 @@ async def test_litellm_ocr_backend_uses_transport(monkeypatch: pytest.MonkeyPatc
     image = Image.new("RGB", (10, 10), color="white")
     page = DocumentPage(page_index=0, image=image, source_index=0)
     prompt_logs: list[str] = []
+    captured: dict[str, object] = {}
 
     class FakeLogger:
         def debug(self, message: str, *args: object) -> None:
@@ -86,7 +87,21 @@ def _fake_prepare_messages(
         assert image_detail == "high"
         return [{"role": "user", "content": [{"type": "text", "text": "prompt"}]}]
 
-    async def _fake_complete_text(self, **_: object) -> str:  # noqa: ANN001
+    async def _fake_complete_text(
+        self: LiteLLMTransport,
+        *,
+        model: str,
+        messages: list[dict[str, object]],
+        timeout_seconds: int = 600,
+        output_json: bool = False,
+        allow_empty: bool = False,
+    ) -> str:
+        captured["transport"] = self
+        captured["model"] = model
+        captured["messages"] = messages
+        captured["timeout_seconds"] = timeout_seconds
+        captured["output_json"] = output_json
+        captured["allow_empty"] = allow_empty
         return "transcribed text"
 
     monkeypatch.setattr(
@@ -107,6 +122,12 @@ async def _fake_complete_text(self, **_: object) -> str:  # noqa: ANN001
     assert result.text == "transcribed text"
     assert result.model_name == "gpt-4.1-mini"
     assert backend.transport.config.completion_kwargs == {"max_tokens": DEFAULT_OCR_MAX_TOKENS}
+    assert captured["transport"] is backend.transport
+    assert captured["model"] == "gpt-4.1-mini"
+    assert captured["messages"] == [{"role": "user", "content": [{"type": "text", "text": "prompt"}]}]
+    assert captured["timeout_seconds"] == 600
+    assert captured["output_json"] is False
+    assert captured["allow_empty"] is True
     assert len(prompt_logs) == 1
     assert "First OCR prompt payload for litellm" in prompt_logs[0]
 
@@ -202,6 +223,31 @@ async def _fake_complete_text(self, **_: object) -> str:  # noqa: ANN001
     assert result.text == "transcribed text"
 
 
+@pytest.mark.asyncio
+async def test_litellm_ocr_backend_accepts_empty_transport_output(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    async def _fake_complete_text(self, **_: object) -> str:  # noqa: ANN001
+        return ""
+
+    monkeypatch.setattr(
+        "churro_ocr._internal.litellm._prepare_messages_from_conversation",
+        lambda *_args, **_kwargs: [],
+    )
+    monkeypatch.setattr("churro_ocr._internal.litellm.LiteLLMTransport.complete_text", _fake_complete_text)
+
+    backend = build_ocr_backend(
+        OCRBackendSpec(
+            provider="litellm",
+            model="gpt-4.1-mini",
+            profile=resolve_ocr_profile(model_id="gpt-4.1-mini"),
+        )
+    )
+    result = await backend.ocr(DocumentPage.from_image(Image.new("RGB", (10, 10), color="white")))
+
+    assert result.text == ""
+
+
 @pytest.mark.asyncio
 async def test_openai_compatible_backend_reports_display_model(
     monkeypatch: pytest.MonkeyPatch,
@@ -746,11 +792,13 @@ async def _fake_complete_text(
         messages: list[dict[str, object]],
         timeout_seconds: int = 600,
         output_json: bool = False,
+        allow_empty: bool = False,
     ) -> str:
         captured["model"] = model
         captured["messages"] = messages
         captured["timeout_seconds"] = timeout_seconds
         captured["output_json"] = output_json
+        captured["allow_empty"] = allow_empty
         captured["completion_kwargs"] = dict(self.config.completion_kwargs)
         return (
             "---\n"
@@ -808,6 +856,7 @@ async def _fake_complete_text(
     assert captured["messages"] == [{"role": "user", "content": [{"type": "text", "text": "prompt"}]}]
     assert captured["timeout_seconds"] == 600
     assert captured["output_json"] is False
+    assert captured["allow_empty"] is True
     assert captured["completion_kwargs"] == {
         "max_tokens": 8_000,
         "temperature": 0.1,
@@ -843,11 +892,13 @@ async def _fake_complete_text(
         messages: list[dict[str, object]],
         timeout_seconds: int = 600,
         output_json: bool = False,
+        allow_empty: bool = False,
     ) -> str:
         captured["model"] = model
         captured["messages"] = messages
         captured["timeout_seconds"] = timeout_seconds
         captured["output_json"] = output_json
+        captured["allow_empty"] = allow_empty
         captured["completion_kwargs"] = dict(self.config.completion_kwargs)
         return (
             '<div data-bbox="0 0 1000 100" data-label="Section-Header"><h1>Ledger</h1></div>\n'
@@ -892,6 +943,7 @@ async def _fake_complete_text(
     assert captured["messages"] == [{"role": "user", "content": [{"type": "text", "text": "prompt"}]}]
     assert captured["timeout_seconds"] == 600
     assert captured["output_json"] is False
+    assert captured["allow_empty"] is True
     assert captured["completion_kwargs"] == {
         "max_tokens": 12_384,
         "temperature": 0.0,

From a56e1bca3691f1c3011301578c5ea206b0b64543 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Tue, 7 Apr 2026 01:40:00 +0000
Subject: [PATCH 20/28] fix(ocr): harden dots.ocr generation handling

---
 src/churro_ocr/providers/hf.py    | 80 +++++++++++++++++++++++++++++--
 src/churro_ocr/providers/specs.py |  6 +++
 tests/test_cli.py                 |  8 ++++
 tests/test_hf_ocr.py              |  7 ++-
 tests/test_tooling_benchmark.py   |  5 +-
 5 files changed, 100 insertions(+), 6 deletions(-)

diff --git a/src/churro_ocr/providers/hf.py b/src/churro_ocr/providers/hf.py
index f0b73b0..90fa499 100644
--- a/src/churro_ocr/providers/hf.py
+++ b/src/churro_ocr/providers/hf.py
@@ -7,6 +7,7 @@
 from dataclasses import dataclass, field
 from importlib import import_module
 from pathlib import Path
+from types import MethodType
 from typing import Any, cast
 
 from churro_ocr._internal.install import install_command_hint
@@ -165,6 +166,64 @@ def _prepare_dots_ocr_model_dir(model_id: str) -> str:
     return str(model_dir)
 
 
+def _patch_dots_ocr_prepare_inputs_for_generation(model: Any) -> None:
+    prepare_inputs_for_generation = getattr(model, "prepare_inputs_for_generation", None)
+    if not callable(prepare_inputs_for_generation):
+        return
+    if getattr(model, "_churro_dots_prepare_inputs_patched", False):
+        return
+
+    original_prepare_inputs = getattr(prepare_inputs_for_generation, "__func__", None)
+    base_prepare_inputs_for_generation = prepare_inputs_for_generation
+    if original_prepare_inputs is not None:
+        for candidate in type(model).__mro__[1:]:
+            candidate_prepare_inputs = candidate.__dict__.get("prepare_inputs_for_generation")
+            if candidate_prepare_inputs is None or candidate_prepare_inputs is original_prepare_inputs:
+                continue
+            base_prepare_inputs_for_generation = cast("Any", candidate_prepare_inputs).__get__(
+                model,
+                type(model),
+            )
+            break
+    if not callable(base_prepare_inputs_for_generation):
+        return
+
+    def _patched_prepare_inputs_for_generation(
+        self: Any,
+        input_ids: object,
+        past_key_values: object = None,
+        inputs_embeds: object = None,
+        pixel_values: object = None,
+        attention_mask: object = None,
+        cache_position: object = None,
+        num_logits_to_keep: object = None,
+        **kwargs: object,
+    ) -> Any:
+        model_inputs = base_prepare_inputs_for_generation(
+            input_ids,
+            past_key_values=past_key_values,
+            inputs_embeds=inputs_embeds,
+            attention_mask=attention_mask,
+            cache_position=cache_position,
+            num_logits_to_keep=num_logits_to_keep,
+            **kwargs,
+        )
+
+        first_cache_position: int | None = None
+        if cache_position is not None:
+            try:
+                first_cache_position = int(cast("Any", cache_position)[0])
+            except Exception:
+                first_cache_position = None
+        if first_cache_position in (None, 0):
+            model_inputs["pixel_values"] = pixel_values
+
+        return model_inputs
+
+    model.prepare_inputs_for_generation = MethodType(_patched_prepare_inputs_for_generation, model)
+    model._churro_dots_prepare_inputs_patched = True
+
+
 def _default_dots_ocr_1_5_model_kwargs() -> dict[str, object]:
     model_kwargs: dict[str, object] = {"dtype": "auto"}
     try:
@@ -322,8 +381,10 @@ def _ocr_sync(self, page: DocumentPage) -> OCRResult:
             batch_kwargs["videos"] = normalized_video_inputs
         batch = processor(**batch_kwargs)
         batch = _move_batch_to_model(batch, model)
-
-        generated_ids = model.generate(**batch, **self.generation_kwargs)
+        generated_ids = model.generate(
+            **self._generation_inputs(batch),
+            **self.generation_kwargs,
+        )
         text = _decode_completion_texts(processor, batch, generated_ids)[0]
         return build_ocr_result(
             text,
@@ -379,8 +440,10 @@ def _ocr_batch_sync(self, pages: list[DocumentPage]) -> list[OCRResult]:
             batch_kwargs["videos"] = video_batch
         batch = processor(**batch_kwargs)
         batch = _move_batch_to_model(batch, model)
-
-        generated_ids = model.generate(**batch, **self.generation_kwargs)
+        generated_ids = model.generate(
+            **self._generation_inputs(batch),
+            **self.generation_kwargs,
+        )
         texts = _decode_completion_texts(processor, batch, generated_ids)
         return [
             build_ocr_result(
@@ -395,6 +458,9 @@ def _ocr_batch_sync(self, pages: list[DocumentPage]) -> list[OCRResult]:
     def _load_runtime(self) -> _HFRuntime:
         return _load_hf_runtime()
 
+    def _generation_inputs(self, batch: Any) -> dict[str, object]:
+        return dict(cast("dict[str, object]", batch))
+
     def _resolve_model_source(self) -> str:
         return self.model_id
 
@@ -636,6 +702,11 @@ class DotsOCR15OCRBackend(HuggingFaceVisionOCRBackend):
     def _load_runtime(self) -> _HFRuntime:
         return _load_hf_causal_runtime()
 
+    def _generation_inputs(self, batch: Any) -> dict[str, object]:
+        generation_inputs = super()._generation_inputs(batch)
+        generation_inputs.pop("mm_token_type_ids", None)
+        return generation_inputs
+
     def _resolve_model_source(self) -> str:
         return _prepare_dots_ocr_model_dir(self.model_id)
 
@@ -661,6 +732,7 @@ def _get_model(self, runtime: _HFRuntime) -> Any:
                         trust_remote_code=self.trust_remote_code,
                         **self.model_kwargs,
                     )
+                    _patch_dots_ocr_prepare_inputs_for_generation(self._model)
         return self._model
 
 
diff --git a/src/churro_ocr/providers/specs.py b/src/churro_ocr/providers/specs.py
index ee0b953..7405da9 100644
--- a/src/churro_ocr/providers/specs.py
+++ b/src/churro_ocr/providers/specs.py
@@ -394,6 +394,12 @@ def dots_ocr_1_5_profile() -> OCRModelProfile:
         template=DOTS_OCR_1_5_OCR_TEMPLATE,
         text_postprocessor=identity_text_postprocessor,
         display_name="dots.ocr-1.5",
+        transport=LiteLLMTransportConfig(
+            completion_kwargs={
+                "max_tokens": 2_048,
+                "temperature": 0.0,
+            }
+        ),
         huggingface=HuggingFaceOptions(
             trust_remote_code=True,
             backend_variant="dots-ocr-1.5",
diff --git a/tests/test_cli.py b/tests/test_cli.py
index 09ca454..97f6b9b 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -197,6 +197,14 @@ def test_build_ocr_backend_aligns_templates_for_dots() -> None:
     assert litellm_backend.model_name == "dots.ocr-1.5"
     assert hf_backend.model_name == "dots.ocr-1.5"
     assert openai_backend.model_name == "dots.ocr-1.5"
+    assert litellm_backend.transport.config.completion_kwargs == {
+        "max_tokens": 2_048,
+        "temperature": 0.0,
+    }
+    assert openai_backend.transport.config.completion_kwargs == {
+        "max_tokens": 2_048,
+        "temperature": 0.0,
+    }
 
 
 def test_build_ocr_backend_uses_generic_defaults_for_qwen_3_5_0_8b() -> None:
diff --git a/tests/test_hf_ocr.py b/tests/test_hf_ocr.py
index e7a4e2c..1e7aedb 100644
--- a/tests/test_hf_ocr.py
+++ b/tests/test_hf_ocr.py
@@ -847,7 +847,12 @@ def apply_chat_template(
 
         def __call__(self, **kwargs: object) -> FakeBatch:
             captured["processor_kwargs"] = kwargs
-            return FakeBatch({"input_ids": SimpleNamespace(shape=(1, 4))})
+            return FakeBatch(
+                {
+                    "input_ids": SimpleNamespace(shape=(1, 4)),
+                    "mm_token_type_ids": "ignored-mm-token-type-ids",
+                }
+            )
 
         def batch_decode(
             self,
diff --git a/tests/test_tooling_benchmark.py b/tests/test_tooling_benchmark.py
index 8abe82a..71ca46d 100644
--- a/tests/test_tooling_benchmark.py
+++ b/tests/test_tooling_benchmark.py
@@ -265,7 +265,10 @@ def test_build_ocr_backend_uses_dots_preset_for_openai_compatible() -> None:
     assert backend.provider_name == "openai-compatible"
     assert backend.model_name == "dots.ocr-1.5"
     assert backend.template == DOTS_OCR_1_5_OCR_TEMPLATE
-    assert backend.transport.config.completion_kwargs == {"max_tokens": DEFAULT_OCR_MAX_TOKENS}
+    assert backend.transport.config.completion_kwargs == {
+        "max_tokens": 2_048,
+        "temperature": 0.0,
+    }
 
 
 def test_build_ocr_backend_uses_churro_preset_template_for_openai_compatible() -> None:

From a58e24422aac879c6128212e25c0d42945dc7961 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Tue, 7 Apr 2026 01:40:24 +0000
Subject: [PATCH 21/28] feat(ocr): add PaddleOCR-VL 1.5 presets

---
 src/churro_ocr/providers/builder.py  |   3 +
 src/churro_ocr/providers/hf.py       | 144 +++++++++++++++++++++++++++
 src/churro_ocr/providers/specs.py    |  36 +++++++
 src/churro_ocr/templates/__init__.py |   6 ++
 src/churro_ocr/templates/presets.py  |   9 ++
 tests/test_cli.py                    |  43 ++++++++
 tests/test_providers.py              |  95 ++++++++++++++++++
 7 files changed, 336 insertions(+)

diff --git a/src/churro_ocr/providers/builder.py b/src/churro_ocr/providers/builder.py
index 8845f46..afd70f6 100644
--- a/src/churro_ocr/providers/builder.py
+++ b/src/churro_ocr/providers/builder.py
@@ -10,6 +10,7 @@
     DotsOCR15OCRBackend,
     HuggingFaceVisionOCRBackend,
     LFM25VLOCRBackend,
+    PaddleOCRVL15OCRBackend,
     _default_dots_ocr_1_5_model_kwargs,
 )
 from churro_ocr.providers.ocr import (
@@ -168,6 +169,8 @@ def _build_huggingface_backend(spec: OCRBackendSpec, profile: OCRModelProfile) -
         model_kwargs = _merge_mapping(_default_dots_ocr_1_5_model_kwargs(), model_kwargs)
     elif options.backend_variant == "chandra-ocr-2":
         backend_cls = ChandraOCR2OCRBackend
+    elif options.backend_variant == "paddleocr-vl-1.5":
+        backend_cls = PaddleOCRVL15OCRBackend
     elif options.backend_variant == "lfm2.5-vl":
         backend_cls = LFM25VLOCRBackend
     return backend_cls(
diff --git a/src/churro_ocr/providers/hf.py b/src/churro_ocr/providers/hf.py
index 90fa499..98f9b91 100644
--- a/src/churro_ocr/providers/hf.py
+++ b/src/churro_ocr/providers/hf.py
@@ -38,6 +38,8 @@
     DOTS_OCR_1_5_OCR_TEMPLATE,
     LFM2_5_VL_1_6B_MODEL_ID,
     LFM2_5_VL_1_6B_OCR_TEMPLATE,
+    PADDLEOCR_VL_1_5_MODEL_ID,
+    PADDLEOCR_VL_1_5_OCR_TEMPLATE,
     OCRConversation,
     OCRPromptTemplateLike,
 )
@@ -291,6 +293,24 @@ def _decode_completion_texts(processor: Any, batch: Any, generated_ids: Any) ->
     )
 
 
+def _paddleocr_vl_processor_kwargs(*, processor: Any, padding: bool) -> dict[str, object]:
+    processor_kwargs: dict[str, object] = {
+        "text_kwargs": {
+            "padding": padding,
+            "return_mm_token_type_ids": True,
+        }
+    }
+    image_processor = getattr(processor, "image_processor", None)
+    images_kwargs: dict[str, int] = {}
+    for key in ("min_pixels", "max_pixels"):
+        value = getattr(image_processor, key, None)
+        if isinstance(value, int):
+            images_kwargs[key] = value
+    if images_kwargs:
+        processor_kwargs["images_kwargs"] = images_kwargs
+    return processor_kwargs
+
+
 @dataclass(slots=True)
 class HuggingFaceVisionOCRBackend(OCRBackend):
     """OCR backend for local Hugging Face multimodal models with custom templates.
@@ -736,6 +756,129 @@ def _get_model(self, runtime: _HFRuntime) -> Any:
         return self._model
 
 
+@dataclass(slots=True)
+class PaddleOCRVL15OCRBackend(HuggingFaceVisionOCRBackend):
+    """Preset OCR backend for ``PaddlePaddle/PaddleOCR-VL-1.5``."""
+
+    model_id: str = PADDLEOCR_VL_1_5_MODEL_ID
+    template: OCRPromptTemplateLike = PADDLEOCR_VL_1_5_OCR_TEMPLATE
+    model_name: str | None = "PaddleOCR-VL-1.5"
+    generation_kwargs: dict[str, object] = field(
+        default_factory=lambda: {"max_new_tokens": 4_096, "do_sample": False}
+    )
+
+    def _get_processor(self, runtime: _HFRuntime) -> Any:
+        processor = super()._get_processor(runtime)
+        tokenizer = getattr(processor, "tokenizer", None)
+        if tokenizer is not None and getattr(tokenizer, "padding_side", None) != "left":
+            tokenizer.padding_side = "left"
+        return processor
+
+    def _get_model(self, runtime: _HFRuntime) -> Any:
+        model = super()._get_model(runtime)
+        eval_method = getattr(model, "eval", None)
+        if callable(eval_method):
+            eval_method()
+        return model
+
+    def _build_paddleocr_vl_batch(
+        self,
+        processor: Any,
+        conversations: OCRConversation | list[OCRConversation],
+        *,
+        padding: bool,
+    ) -> Any:
+        processor_apply = getattr(processor, "apply_chat_template", None)
+        if not callable(processor_apply):
+            raise ConfigurationError(
+                "PaddleOCR-VL-1.5 requires `processor.apply_chat_template(...)` support."
+            )
+        return processor_apply(
+            conversations,
+            add_generation_prompt=True,
+            tokenize=True,
+            return_dict=True,
+            return_tensors="pt",
+            processor_kwargs=_paddleocr_vl_processor_kwargs(
+                processor=processor,
+                padding=padding,
+            ),
+        )
+
+    def _ocr_sync(self, page: DocumentPage) -> OCRResult:
+        prepared_page = preprocess_backend_page(
+            page,
+            image_preprocessor=self.image_preprocessor,
+        )
+        runtime = self._load_runtime()
+        processor = self._get_processor(runtime)
+        model = self._get_model(runtime)
+
+        rendered, conversation = render_ocr_prompt(
+            processor,
+            self.template,
+            prepared_page,
+            add_generation_prompt=True,
+        )
+        self._log_prompt_payload(
+            rendered_prompt=rendered,
+            conversation=conversation,
+            batch_size=1,
+        )
+        batch = self._build_paddleocr_vl_batch(processor, conversation, padding=False)
+        batch = _move_batch_to_model(batch, model)
+        generated_ids = model.generate(**batch, **self.generation_kwargs)
+        text = _decode_completion_texts(processor, batch, generated_ids)[0]
+        return build_ocr_result(
+            text,
+            provider_name=self.provider_name,
+            model_name=self.model_name or self.model_id,
+            text_postprocessor=self.text_postprocessor,
+        )
+
+    def _ocr_batch_sync(self, pages: list[DocumentPage]) -> list[OCRResult]:
+        if not pages:
+            return []
+
+        runtime = self._load_runtime()
+        processor = self._get_processor(runtime)
+        model = self._get_model(runtime)
+        conversations: list[OCRConversation] = []
+
+        for page in pages:
+            prepared_page = preprocess_backend_page(
+                page,
+                image_preprocessor=self.image_preprocessor,
+            )
+            rendered, conversation = render_ocr_prompt(
+                processor,
+                self.template,
+                prepared_page,
+                add_generation_prompt=True,
+            )
+            conversations.append(conversation)
+            if not self._has_logged_prompt:
+                self._log_prompt_payload(
+                    rendered_prompt=rendered,
+                    conversation=conversation,
+                    batch_size=len(pages),
+                )
+
+        batch = self._build_paddleocr_vl_batch(processor, conversations, padding=True)
+        batch = _move_batch_to_model(batch, model)
+        generated_ids = model.generate(**batch, **self.generation_kwargs)
+        texts = _decode_completion_texts(processor, batch, generated_ids)
+        return [
+            build_ocr_result(
+                text,
+                provider_name=self.provider_name,
+                model_name=self.model_name or self.model_id,
+                text_postprocessor=self.text_postprocessor,
+            )
+            for text in texts
+        ]
+
+
 @dataclass(slots=True)
 class LFM25VLOCRBackend(HuggingFaceVisionOCRBackend):
     """Preset OCR backend for ``LiquidAI/LFM2.5-VL-1.6B``."""
@@ -873,4 +1016,5 @@ def _ocr_batch_sync(self, pages: list[DocumentPage]) -> list[OCRResult]:
     "DotsOCR15OCRBackend",
     "HuggingFaceVisionOCRBackend",
     "LFM25VLOCRBackend",
+    "PaddleOCRVL15OCRBackend",
 ]
diff --git a/src/churro_ocr/providers/specs.py b/src/churro_ocr/providers/specs.py
index 7405da9..ab0f699 100644
--- a/src/churro_ocr/providers/specs.py
+++ b/src/churro_ocr/providers/specs.py
@@ -31,6 +31,9 @@
     OLMOCR_2_7B_1025_FP8_MODEL_ID,
     OLMOCR_2_7B_1025_MODEL_ID,
     OLMOCR_2_7B_1025_OCR_TEMPLATE,
+    PADDLEOCR_VL_1_5_MODEL_ID,
+    PADDLEOCR_VL_1_5_OCR_PROMPT,
+    PADDLEOCR_VL_1_5_OCR_TEMPLATE,
     OCRConversation,
     OCRPromptTemplateLike,
 )
@@ -48,6 +51,7 @@
 DEFAULT_OCR_MAX_TOKENS = 20_000
 CHANDRA_OCR_MAX_TOKENS = 12_384
 OLMOCR_MAX_TOKENS = 8_000
+PADDLEOCR_VL_MAX_TOKENS = 4_096
 CHANDRA_MAX_IMAGE_SIZE = (3_072, 2_048)
 CHANDRA_MIN_IMAGE_SIZE = (1_792, 28)
 CHANDRA_IMAGE_GRID_SIZE = 28
@@ -172,6 +176,11 @@ def lfm2_5_vl_text_postprocessor(text: str) -> str:
     return strip_ocr_output_tag(cleaned, output_tag=DEFAULT_OCR_OUTPUT_TAG)
 
 
+def paddleocr_vl_text_postprocessor(text: str) -> str:
+    """Strip PaddleOCR-VL prompt echoes and leading chat scaffold from OCR output."""
+    return _strip_leading_chat_scaffold(text, prompts=[PADDLEOCR_VL_1_5_OCR_PROMPT])
+
+
 def chandra_image_preprocessor(image: Image.Image) -> Image.Image:
     """Resize an image using Chandra OCR 2's pixel-budget and 28px-grid scaling."""
     width, height = image.size
@@ -407,6 +416,29 @@ def dots_ocr_1_5_profile() -> OCRModelProfile:
     )
 
 
+def paddleocr_vl_1_5_profile() -> OCRModelProfile:
+    """Return the built-in ``PaddlePaddle/PaddleOCR-VL-1.5`` OCR profile."""
+    return OCRModelProfile(
+        profile_name=PADDLEOCR_VL_1_5_MODEL_ID,
+        template=PADDLEOCR_VL_1_5_OCR_TEMPLATE,
+        text_postprocessor=paddleocr_vl_text_postprocessor,
+        display_name="PaddleOCR-VL-1.5",
+        transport=LiteLLMTransportConfig(
+            completion_kwargs={
+                "max_tokens": PADDLEOCR_VL_MAX_TOKENS,
+                "temperature": 0.0,
+            }
+        ),
+        huggingface=HuggingFaceOptions(
+            generation_kwargs={
+                "max_new_tokens": PADDLEOCR_VL_MAX_TOKENS,
+                "do_sample": False,
+            },
+            backend_variant="paddleocr-vl-1.5",
+        ),
+    )
+
+
 def _olmocr_profile(*, profile_name: str, display_name: str) -> OCRModelProfile:
     return OCRModelProfile(
         profile_name=profile_name,
@@ -472,6 +504,7 @@ def _profile_registry() -> dict[str, OCRModelProfile]:
     lfm2_5_vl_profile = lfm2_5_vl_1_6b_profile()
     olmocr_profile = olmocr_2_7b_1025_profile()
     olmocr_fp8_profile = olmocr_2_7b_1025_fp8_profile()
+    paddleocr_vl_profile = paddleocr_vl_1_5_profile()
     return {
         default_profile.profile_name: default_profile,
         churro_profile.profile_name: churro_profile,
@@ -480,6 +513,7 @@ def _profile_registry() -> dict[str, OCRModelProfile]:
         lfm2_5_vl_profile.profile_name: lfm2_5_vl_profile,
         olmocr_profile.profile_name: olmocr_profile,
         olmocr_fp8_profile.profile_name: olmocr_fp8_profile,
+        paddleocr_vl_profile.profile_name: paddleocr_vl_profile,
     }
 
 
@@ -530,6 +564,8 @@ def resolve_ocr_profile(
     "MistralOptions",
     "olmocr_image_preprocessor",
     "olmocr_text_postprocessor",
+    "paddleocr_vl_1_5_profile",
+    "paddleocr_vl_text_postprocessor",
     "OCRBackendSpec",
     "OCRModelProfile",
     "OCRProvider",
diff --git a/src/churro_ocr/templates/__init__.py b/src/churro_ocr/templates/__init__.py
index 64c264c..4324315 100644
--- a/src/churro_ocr/templates/__init__.py
+++ b/src/churro_ocr/templates/__init__.py
@@ -22,6 +22,9 @@
     OLMOCR_2_7B_1025_FP8_MODEL_ID,
     OLMOCR_2_7B_1025_MODEL_ID,
     OLMOCR_2_7B_1025_OCR_TEMPLATE,
+    PADDLEOCR_VL_1_5_MODEL_ID,
+    PADDLEOCR_VL_1_5_OCR_PROMPT,
+    PADDLEOCR_VL_1_5_OCR_TEMPLATE,
 )
 
 __all__ = [
@@ -36,6 +39,9 @@
     "DOTS_OCR_1_5_OCR_TEMPLATE",
     "LFM2_5_VL_1_6B_MODEL_ID",
     "LFM2_5_VL_1_6B_OCR_TEMPLATE",
+    "PADDLEOCR_VL_1_5_MODEL_ID",
+    "PADDLEOCR_VL_1_5_OCR_PROMPT",
+    "PADDLEOCR_VL_1_5_OCR_TEMPLATE",
     "HFChatTemplate",
     "OLMOCR_2_7B_1025_FP8_MODEL_ID",
     "OLMOCR_2_7B_1025_MODEL_ID",
diff --git a/src/churro_ocr/templates/presets.py b/src/churro_ocr/templates/presets.py
index e9c6464..3a549af 100644
--- a/src/churro_ocr/templates/presets.py
+++ b/src/churro_ocr/templates/presets.py
@@ -13,6 +13,7 @@
 CHURRO_3B_MODEL_ID = "stanford-oval/churro-3B"
 CHANDRA_OCR_2_MODEL_ID = "datalab-to/chandra-ocr-2"
 DOTS_OCR_1_5_MODEL_ID = "kristaller486/dots.ocr-1.5"
+PADDLEOCR_VL_1_5_MODEL_ID = "PaddlePaddle/PaddleOCR-VL-1.5"
 OLMOCR_2_7B_1025_MODEL_ID = "allenai/olmOCR-2-7B-1025"
 OLMOCR_2_7B_1025_FP8_MODEL_ID = "allenai/olmOCR-2-7B-1025-FP8"
 LFM2_5_VL_1_6B_MODEL_ID = "LiquidAI/LFM2.5-VL-1.6B"
@@ -34,6 +35,11 @@
     system_message=None,
     user_prompt=DOTS_OCR_1_5_OCR_PROMPT,
 )
+PADDLEOCR_VL_1_5_OCR_PROMPT = "OCR:"
+PADDLEOCR_VL_1_5_OCR_TEMPLATE = HFChatTemplate(
+    system_message=None,
+    user_prompt=PADDLEOCR_VL_1_5_OCR_PROMPT,
+)
 OLMOCR_2_7B_1025_OCR_TEMPLATE = HFChatTemplate(
     system_message=None,
     user_prompt=OLMOCR_V4_YAML_PROMPT,
@@ -54,6 +60,9 @@
     "DOTS_OCR_1_5_MODEL_ID",
     "DOTS_OCR_1_5_OCR_PROMPT",
     "DOTS_OCR_1_5_OCR_TEMPLATE",
+    "PADDLEOCR_VL_1_5_MODEL_ID",
+    "PADDLEOCR_VL_1_5_OCR_PROMPT",
+    "PADDLEOCR_VL_1_5_OCR_TEMPLATE",
     "OLMOCR_2_7B_1025_FP8_MODEL_ID",
     "OLMOCR_2_7B_1025_MODEL_ID",
     "OLMOCR_2_7B_1025_OCR_TEMPLATE",
diff --git a/tests/test_cli.py b/tests/test_cli.py
index 97f6b9b..237c32d 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -23,6 +23,8 @@
     DOTS_OCR_1_5_OCR_TEMPLATE,
     OLMOCR_2_7B_1025_MODEL_ID,
     OLMOCR_2_7B_1025_OCR_TEMPLATE,
+    PADDLEOCR_VL_1_5_MODEL_ID,
+    PADDLEOCR_VL_1_5_OCR_TEMPLATE,
 )
 
 
@@ -207,6 +209,47 @@ def test_build_ocr_backend_aligns_templates_for_dots() -> None:
     }
 
 
+def test_build_ocr_backend_aligns_templates_for_paddleocr_vl() -> None:
+    litellm_backend = cli_module._build_ocr_backend(
+        backend="litellm",
+        model=PADDLEOCR_VL_1_5_MODEL_ID,
+        endpoint=None,
+        api_key=None,
+        base_url=None,
+        api_version=None,
+    )
+    hf_backend = cli_module._build_ocr_backend(
+        backend="hf",
+        model=PADDLEOCR_VL_1_5_MODEL_ID,
+        endpoint=None,
+        api_key=None,
+        base_url=None,
+        api_version=None,
+    )
+    openai_backend = cli_module._build_ocr_backend(
+        backend="openai-compatible",
+        model=PADDLEOCR_VL_1_5_MODEL_ID,
+        endpoint=None,
+        api_key=None,
+        base_url="http://127.0.0.1:8000/v1",
+        api_version=None,
+    )
+
+    assert litellm_backend.template == PADDLEOCR_VL_1_5_OCR_TEMPLATE
+    assert litellm_backend.template == hf_backend.template == openai_backend.template
+    assert litellm_backend.model_name == "PaddleOCR-VL-1.5"
+    assert hf_backend.model_name == "PaddleOCR-VL-1.5"
+    assert openai_backend.model_name == "PaddleOCR-VL-1.5"
+    assert litellm_backend.transport.config.completion_kwargs == {
+        "max_tokens": 4_096,
+        "temperature": 0.0,
+    }
+    assert openai_backend.transport.config.completion_kwargs == {
+        "max_tokens": 4_096,
+        "temperature": 0.0,
+    }
+
+
 def test_build_ocr_backend_uses_generic_defaults_for_qwen_3_5_0_8b() -> None:
     litellm_backend = cli_module._build_ocr_backend(
         backend="litellm",
diff --git a/tests/test_providers.py b/tests/test_providers.py
index 7efba90..fc959a0 100644
--- a/tests/test_providers.py
+++ b/tests/test_providers.py
@@ -52,6 +52,9 @@
     OLMOCR_2_7B_1025_FP8_MODEL_ID,
     OLMOCR_2_7B_1025_MODEL_ID,
     OLMOCR_2_7B_1025_OCR_TEMPLATE,
+    PADDLEOCR_VL_1_5_MODEL_ID,
+    PADDLEOCR_VL_1_5_OCR_PROMPT,
+    PADDLEOCR_VL_1_5_OCR_TEMPLATE,
 )
 
 
@@ -771,6 +774,26 @@ def test_build_ocr_backend_resolves_olmocr_fp8_profile_defaults_for_openai_compa
     }
 
 
+def test_build_ocr_backend_uses_paddleocr_vl_profile_defaults_for_openai_compatible() -> None:
+    backend = cast(
+        "OpenAICompatibleOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="openai-compatible",
+                model=PADDLEOCR_VL_1_5_MODEL_ID,
+                transport=LiteLLMTransportConfig(api_base="http://127.0.0.1:8000/v1"),
+            )
+        ),
+    )
+
+    assert backend.template == PADDLEOCR_VL_1_5_OCR_TEMPLATE
+    assert backend.model_name == "PaddleOCR-VL-1.5"
+    assert backend.transport.config.completion_kwargs == {
+        "max_tokens": 4_096,
+        "temperature": 0.0,
+    }
+
+
 @pytest.mark.asyncio
 async def test_openai_compatible_backend_uses_olmocr_prompt_and_plain_text_postprocessing(
     monkeypatch: pytest.MonkeyPatch,
@@ -959,6 +982,78 @@ async def _fake_complete_text(
     assert user_content[1] == {"type": "text", "text": CHANDRA_OCR_LAYOUT_PROMPT}
 
 
+@pytest.mark.asyncio
+async def test_openai_compatible_backend_uses_paddleocr_vl_prompt_and_strips_prompt_echo(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    captured: dict[str, object] = {}
+
+    def _fake_prepare_messages_from_conversation(
+        self: LiteLLMTransport,
+        conversation: list[dict[str, object]],
+    ) -> list[dict[str, object]]:
+        captured["conversation"] = conversation
+        captured["completion_kwargs"] = dict(self.config.completion_kwargs)
+        return [{"role": "user", "content": [{"type": "text", "text": "prompt"}]}]
+
+    async def _fake_complete_text(
+        self: LiteLLMTransport,
+        *,
+        model: str,
+        messages: list[dict[str, object]],
+        timeout_seconds: int = 600,
+        output_json: bool = False,
+        allow_empty: bool = False,
+    ) -> str:
+        captured["model"] = model
+        captured["messages"] = messages
+        captured["timeout_seconds"] = timeout_seconds
+        captured["output_json"] = output_json
+        captured["allow_empty"] = allow_empty
+        captured["completion_kwargs"] = dict(self.config.completion_kwargs)
+        return "OCR:\nassistant\npaddle transcription"
+
+    monkeypatch.setattr(
+        LiteLLMTransport,
+        "prepare_messages_from_conversation",
+        _fake_prepare_messages_from_conversation,
+    )
+    monkeypatch.setattr(LiteLLMTransport, "complete_text", _fake_complete_text)
+
+    backend = cast(
+        "OpenAICompatibleOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="openai-compatible",
+                model=PADDLEOCR_VL_1_5_MODEL_ID,
+                transport=LiteLLMTransportConfig(api_base="http://127.0.0.1:8000/v1"),
+            )
+        ),
+    )
+    result = await backend.ocr(
+        DocumentPage.from_image(Image.new("RGBA", (5_000, 3_000), color=(255, 255, 255, 255)))
+    )
+
+    assert result.text == "paddle transcription"
+    assert captured["model"] == f"openai/{PADDLEOCR_VL_1_5_MODEL_ID}"
+    assert captured["messages"] == [{"role": "user", "content": [{"type": "text", "text": "prompt"}]}]
+    assert captured["timeout_seconds"] == 600
+    assert captured["output_json"] is False
+    assert captured["allow_empty"] is True
+    assert captured["completion_kwargs"] == {
+        "max_tokens": 4_096,
+        "temperature": 0.0,
+    }
+    conversation = cast("list[dict[str, object]]", captured["conversation"])
+    assert conversation[0]["role"] == "user"
+    user_content = cast("list[dict[str, object]]", conversation[0]["content"])
+    assert user_content[0]["type"] == "image"
+    prompt_image = cast("Image.Image", user_content[0]["image"])
+    assert prompt_image.size == (2_500, 1_500)
+    assert prompt_image.mode == "RGB"
+    assert user_content[1] == {"type": "text", "text": PADDLEOCR_VL_1_5_OCR_PROMPT}
+
+
 @pytest.mark.asyncio
 async def test_llm_page_detector_uses_prompt_transport(
     monkeypatch: pytest.MonkeyPatch,

From f837911809ca2756eefa7955439019eef9b55da5 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Tue, 7 Apr 2026 01:40:44 +0000
Subject: [PATCH 22/28] test(hf): cover dots and Paddle OCR backends

---
 tests/test_hf_ocr.py | 548 +++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 548 insertions(+)

diff --git a/tests/test_hf_ocr.py b/tests/test_hf_ocr.py
index 1e7aedb..cfe5057 100644
--- a/tests/test_hf_ocr.py
+++ b/tests/test_hf_ocr.py
@@ -26,6 +26,7 @@
     DotsOCR15OCRBackend,
     HuggingFaceVisionOCRBackend,
     LFM25VLOCRBackend,
+    PaddleOCRVL15OCRBackend,
 )
 from churro_ocr.providers.specs import DEFAULT_OCR_MAX_TOKENS, lfm2_5_vl_text_postprocessor
 from churro_ocr.templates import (
@@ -39,6 +40,9 @@
     LFM2_5_VL_1_6B_OCR_TEMPLATE,
     OLMOCR_2_7B_1025_MODEL_ID,
     OLMOCR_2_7B_1025_OCR_TEMPLATE,
+    PADDLEOCR_VL_1_5_MODEL_ID,
+    PADDLEOCR_VL_1_5_OCR_PROMPT,
+    PADDLEOCR_VL_1_5_OCR_TEMPLATE,
     HFChatTemplate,
     OCRConversation,
 )
@@ -209,6 +213,26 @@ def test_build_ocr_backend_uses_lfm25_profile_defaults_for_hf() -> None:
     }
 
 
+def test_build_ocr_backend_uses_paddleocr_vl_profile_defaults_for_hf() -> None:
+    backend = cast(
+        "PaddleOCRVL15OCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="hf",
+                model=PADDLEOCR_VL_1_5_MODEL_ID,
+            )
+        ),
+    )
+
+    assert isinstance(backend, PaddleOCRVL15OCRBackend)
+    assert backend.template == PADDLEOCR_VL_1_5_OCR_TEMPLATE
+    assert backend.model_name == "PaddleOCR-VL-1.5"
+    assert backend.generation_kwargs == {
+        "max_new_tokens": 4_096,
+        "do_sample": False,
+    }
+
+
 @pytest.mark.asyncio
 async def test_chandra_huggingface_backend_matches_upstream_chat_template_and_eos_behavior(
     monkeypatch: pytest.MonkeyPatch,
@@ -951,6 +975,530 @@ def test_dots_ocr_15_backend_uses_expected_defaults() -> None:
     assert backend.generation_kwargs == {"max_new_tokens": DEFAULT_OCR_MAX_TOKENS}
 
 
+@pytest.mark.asyncio
+async def test_paddleocr_vl_15_backend_uses_tokenized_chat_template_and_profile_defaults(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    captured: dict[str, Any] = {}
+
+    class FakeAttentionMask:
+        def sum(self, dim: int) -> SimpleNamespace:
+            captured["attention_mask_sum_dim"] = dim
+            return SimpleNamespace(tolist=lambda: [4])
+
+    class FakeBatch(dict[str, object]):
+        def to(self, device: object) -> FakeBatch:
+            captured["device"] = device
+            return self
+
+    class FakeTokenizer:
+        def __init__(self) -> None:
+            self.padding_side = "right"
+
+    class FakeProcessor:
+        def __init__(self) -> None:
+            self.tokenizer = FakeTokenizer()
+            self.image_processor = SimpleNamespace(min_pixels=112_896, max_pixels=1_003_520)
+
+        def apply_chat_template(
+            self,
+            conversation: object,
+            *,
+            add_generation_prompt: bool,
+            tokenize: bool,
+            return_dict: bool | None = None,
+            return_tensors: str | None = None,
+            processor_kwargs: dict[str, object] | None = None,
+        ) -> object:
+            captured.setdefault("chat_calls", []).append(
+                {
+                    "conversation": conversation,
+                    "add_generation_prompt": add_generation_prompt,
+                    "tokenize": tokenize,
+                    "return_dict": return_dict,
+                    "return_tensors": return_tensors,
+                    "processor_kwargs": processor_kwargs,
+                }
+            )
+            if not tokenize:
+                return "<paddle-rendered>"
+            return FakeBatch(
+                {
+                    "input_ids": SimpleNamespace(shape=(1, 4)),
+                    "attention_mask": FakeAttentionMask(),
+                }
+            )
+
+        def __call__(self, **kwargs: object) -> object:
+            raise AssertionError("processor(...) should not be used for PaddleOCR-VL")
+
+        def batch_decode(
+            self,
+            generated_ids: object,
+            *,
+            skip_special_tokens: bool,
+            clean_up_tokenization_spaces: bool,
+        ) -> list[str]:
+            captured["generated_ids"] = generated_ids
+            captured["skip_special_tokens"] = skip_special_tokens
+            captured["clean_up_tokenization_spaces"] = clean_up_tokenization_spaces
+            return ["OCR:\nassistant\npaddle transcription"]
+
+    class FakeProcessorCls:
+        @staticmethod
+        def from_pretrained(model_id: str, **kwargs: object) -> FakeProcessor:
+            captured["processor_model_id"] = model_id
+            captured["processor_from_pretrained_kwargs"] = kwargs
+            return FakeProcessor()
+
+    class FakeModel:
+        device = "fake-device"
+        dtype = None
+
+        def eval(self) -> FakeModel:
+            captured["eval_called"] = True
+            return self
+
+        def generate(self, **kwargs: object) -> list[list[int | str]]:
+            captured["generate_kwargs"] = kwargs
+            return [[0, 1, 2, 3, "completion"]]
+
+    class FakeModelCls:
+        @staticmethod
+        def from_pretrained(model_id: str, **kwargs: object) -> FakeModel:
+            captured["model_model_id"] = model_id
+            captured["model_from_pretrained_kwargs"] = kwargs
+            return FakeModel()
+
+    monkeypatch.setattr(
+        "churro_ocr.providers.hf._load_hf_runtime",
+        lambda: SimpleNamespace(
+            processor_cls=FakeProcessorCls,
+            model_cls=FakeModelCls,
+            process_vision_info=None,
+        ),
+    )
+
+    backend = cast(
+        "PaddleOCRVL15OCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="hf",
+                model=PADDLEOCR_VL_1_5_MODEL_ID,
+            )
+        ),
+    )
+    result = await backend.ocr(DocumentPage.from_image(Image.new("RGB", (32, 32), color="white")))
+
+    assert result.text == "paddle transcription"
+    assert captured["processor_model_id"] == PADDLEOCR_VL_1_5_MODEL_ID
+    assert captured["model_model_id"] == PADDLEOCR_VL_1_5_MODEL_ID
+    assert captured["eval_called"] is True
+    assert cast("FakeProcessor", backend._processor).tokenizer.padding_side == "left"
+    assert len(cast("list[dict[str, object]]", captured["chat_calls"])) == 2
+    assert cast("list[dict[str, object]]", captured["chat_calls"])[0]["tokenize"] is False
+    assert cast("list[dict[str, object]]", captured["chat_calls"])[1]["tokenize"] is True
+    assert cast("list[dict[str, object]]", captured["chat_calls"])[1]["return_dict"] is True
+    assert cast("list[dict[str, object]]", captured["chat_calls"])[1]["return_tensors"] == "pt"
+    assert cast("list[dict[str, object]]", captured["chat_calls"])[1]["processor_kwargs"] == {
+        "text_kwargs": {
+            "padding": False,
+            "return_mm_token_type_ids": True,
+        },
+        "images_kwargs": {
+            "min_pixels": 112_896,
+            "max_pixels": 1_003_520,
+        },
+    }
+    render_conversation = cast("list[dict[str, object]]", captured["chat_calls"])[0]["conversation"]
+    assert cast("list[dict[str, object]]", render_conversation)[0]["role"] == "user"
+    render_content = cast(
+        "list[dict[str, object]]",
+        cast("list[dict[str, object]]", render_conversation)[0]["content"],
+    )
+    assert render_content[0]["type"] == "image"
+    assert render_content[1] == {"type": "text", "text": PADDLEOCR_VL_1_5_OCR_PROMPT}
+    assert captured["device"] == "fake-device"
+    assert captured["attention_mask_sum_dim"] == 1
+    assert captured["generate_kwargs"] == {
+        "input_ids": SimpleNamespace(shape=(1, 4)),
+        "attention_mask": cast("object", captured["generate_kwargs"]["attention_mask"]),
+        "max_new_tokens": 4_096,
+        "do_sample": False,
+    }
+    assert captured["generated_ids"] == [["completion"]]
+    assert captured["skip_special_tokens"] is True
+    assert captured["clean_up_tokenization_spaces"] is False
+
+
+def test_paddleocr_vl_15_backend_uses_expected_defaults() -> None:
+    backend = PaddleOCRVL15OCRBackend()
+
+    assert backend.model_id == PADDLEOCR_VL_1_5_MODEL_ID
+    assert backend.template == PADDLEOCR_VL_1_5_OCR_TEMPLATE
+    assert backend.trust_remote_code is False
+    assert backend.processor_kwargs == {}
+    assert backend.model_kwargs == {}
+    assert backend.generation_kwargs == {
+        "max_new_tokens": 4_096,
+        "do_sample": False,
+    }
+
+
+def test_patch_dots_ocr_prepare_inputs_for_generation_handles_missing_cache_position() -> None:
+    captured: dict[str, object] = {}
+
+    class BaseModel:
+        def prepare_inputs_for_generation(
+            self,
+            input_ids: object,
+            *,
+            past_key_values: object = None,
+            inputs_embeds: object = None,
+            pixel_values: object = None,
+            attention_mask: object = None,
+            cache_position: object = None,
+            num_logits_to_keep: object = None,
+            **kwargs: object,
+        ) -> dict[str, object]:
+            del pixel_values
+            captured["base_call"] = {
+                "input_ids": input_ids,
+                "past_key_values": past_key_values,
+                "inputs_embeds": inputs_embeds,
+                "attention_mask": attention_mask,
+                "cache_position": cache_position,
+                "num_logits_to_keep": num_logits_to_keep,
+                "kwargs": kwargs,
+            }
+            return {
+                "input_ids": input_ids,
+                "attention_mask": attention_mask,
+            }
+
+    class FakeDotsModel(BaseModel):
+        pass
+
+    model = FakeDotsModel()
+
+    hf_module._patch_dots_ocr_prepare_inputs_for_generation(model)
+    first_inputs = model.prepare_inputs_for_generation(
+        "tokens",
+        pixel_values="pixels",
+        attention_mask="mask",
+        cache_position=None,
+    )
+    later_inputs = model.prepare_inputs_for_generation(
+        "tokens",
+        pixel_values="pixels",
+        attention_mask="mask",
+        cache_position=[3],
+    )
+
+    assert first_inputs == {
+        "input_ids": "tokens",
+        "attention_mask": "mask",
+        "pixel_values": "pixels",
+    }
+    assert later_inputs == {
+        "input_ids": "tokens",
+        "attention_mask": "mask",
+    }
+    assert captured["base_call"] == {
+        "input_ids": "tokens",
+        "past_key_values": None,
+        "inputs_embeds": None,
+        "attention_mask": "mask",
+        "cache_position": [3],
+        "num_logits_to_keep": None,
+        "kwargs": {},
+    }
+
+    hf_module._patch_dots_ocr_prepare_inputs_for_generation(model)
+    assert cast("Any", model)._churro_dots_prepare_inputs_patched is True
+
+
+def test_patch_dots_ocr_prepare_inputs_for_generation_skips_wrapped_dots_method() -> None:
+    captured: dict[str, object] = {}
+
+    class BaseModel:
+        def prepare_inputs_for_generation(
+            self,
+            input_ids: object,
+            *,
+            past_key_values: object = None,
+            inputs_embeds: object = None,
+            pixel_values: object = None,
+            attention_mask: object = None,
+            cache_position: object = None,
+            num_logits_to_keep: object = None,
+            **kwargs: object,
+        ) -> dict[str, object]:
+            del pixel_values
+            captured["base_call"] = {
+                "input_ids": input_ids,
+                "past_key_values": past_key_values,
+                "inputs_embeds": inputs_embeds,
+                "attention_mask": attention_mask,
+                "cache_position": cache_position,
+                "num_logits_to_keep": num_logits_to_keep,
+                "kwargs": kwargs,
+            }
+            return {
+                "input_ids": input_ids,
+                "attention_mask": attention_mask,
+            }
+
+    class FakeDotsModel(BaseModel):
+        def prepare_inputs_for_generation(
+            self,
+            input_ids: object,
+            *,
+            past_key_values: object = None,
+            inputs_embeds: object = None,
+            pixel_values: object = None,
+            attention_mask: object = None,
+            cache_position: object = None,
+            num_logits_to_keep: object = None,
+            **kwargs: object,
+        ) -> dict[str, object]:
+            if cast("Any", cache_position)[0] == 0:
+                return {"pixel_values": pixel_values}
+            return {
+                "input_ids": input_ids,
+                "attention_mask": attention_mask,
+            }
+
+    class WrappedFakeDotsModel(FakeDotsModel):
+        pass
+
+    model = WrappedFakeDotsModel()
+
+    hf_module._patch_dots_ocr_prepare_inputs_for_generation(model)
+    inputs = model.prepare_inputs_for_generation(
+        "tokens",
+        pixel_values="pixels",
+        attention_mask="mask",
+        cache_position=None,
+    )
+
+    assert inputs == {
+        "input_ids": "tokens",
+        "attention_mask": "mask",
+        "pixel_values": "pixels",
+    }
+    assert captured["base_call"] == {
+        "input_ids": "tokens",
+        "past_key_values": None,
+        "inputs_embeds": None,
+        "attention_mask": "mask",
+        "cache_position": None,
+        "num_logits_to_keep": None,
+        "kwargs": {},
+    }
+
+
+def test_patch_dots_ocr_prepare_inputs_for_generation_skips_duplicate_wrapped_dots_methods() -> None:
+    captured: dict[str, object] = {}
+
+    class BaseModel:
+        def prepare_inputs_for_generation(
+            self,
+            input_ids: object,
+            *,
+            past_key_values: object = None,
+            inputs_embeds: object = None,
+            pixel_values: object = None,
+            attention_mask: object = None,
+            cache_position: object = None,
+            num_logits_to_keep: object = None,
+            **kwargs: object,
+        ) -> dict[str, object]:
+            del pixel_values
+            captured["base_call"] = {
+                "input_ids": input_ids,
+                "past_key_values": past_key_values,
+                "inputs_embeds": inputs_embeds,
+                "attention_mask": attention_mask,
+                "cache_position": cache_position,
+                "num_logits_to_keep": num_logits_to_keep,
+                "kwargs": kwargs,
+            }
+            return {
+                "input_ids": input_ids,
+                "attention_mask": attention_mask,
+            }
+
+    def shared_prepare_inputs_for_generation(
+        self: object,
+        input_ids: object,
+        *,
+        past_key_values: object = None,
+        inputs_embeds: object = None,
+        pixel_values: object = None,
+        attention_mask: object = None,
+        cache_position: object = None,
+        num_logits_to_keep: object = None,
+        **kwargs: object,
+    ) -> dict[str, object]:
+        del self, input_ids, past_key_values, inputs_embeds, pixel_values, attention_mask
+        del num_logits_to_keep, kwargs
+        if cast("Any", cache_position)[0] == 0:
+            return {"unexpected": True}
+        return {"unexpected": False}
+
+    class FakeDotsOwner(BaseModel):
+        pass
+
+    class WrappedFakeDotsModel(FakeDotsOwner):
+        pass
+
+    cast("Any", FakeDotsOwner).prepare_inputs_for_generation = shared_prepare_inputs_for_generation
+    cast("Any", WrappedFakeDotsModel).prepare_inputs_for_generation = (
+        shared_prepare_inputs_for_generation
+    )
+
+    model = WrappedFakeDotsModel()
+
+    hf_module._patch_dots_ocr_prepare_inputs_for_generation(model)
+    inputs = model.prepare_inputs_for_generation(
+        "tokens",
+        pixel_values="pixels",
+        attention_mask="mask",
+        cache_position=None,
+    )
+
+    assert inputs == {
+        "input_ids": "tokens",
+        "attention_mask": "mask",
+        "pixel_values": "pixels",
+    }
+    assert captured["base_call"] == {
+        "input_ids": "tokens",
+        "past_key_values": None,
+        "inputs_embeds": None,
+        "attention_mask": "mask",
+        "cache_position": None,
+        "num_logits_to_keep": None,
+        "kwargs": {},
+    }
+
+
+def test_dots_ocr_15_backend_batch_strips_unused_mm_token_type_ids(monkeypatch: pytest.MonkeyPatch) -> None:
+    captured: dict[str, Any] = {}
+
+    class FakeAttentionMask:
+        def sum(self, dim: int) -> SimpleNamespace:
+            captured["attention_mask_sum_dim"] = dim
+            return SimpleNamespace(tolist=lambda: [4, 4])
+
+    class FakeBatch(dict[str, object]):
+        def to(self, device: object) -> FakeBatch:
+            captured["device"] = device
+            return self
+
+    class FakeProcessor:
+        tokenizer = object()
+
+        def apply_chat_template(
+            self,
+            conversation: list[dict[str, object]],
+            *,
+            add_generation_prompt: bool,
+            tokenize: bool,
+        ) -> str:
+            del add_generation_prompt, tokenize
+            image = cast(Image.Image, cast(list[dict[str, object]], conversation[0]["content"])[0]["image"])
+            return f"<dots-rendered:{image.width}>"
+
+        def __call__(self, **kwargs: object) -> FakeBatch:
+            captured["processor_kwargs"] = kwargs
+            return FakeBatch(
+                {
+                    "input_ids": SimpleNamespace(shape=(2, 4)),
+                    "attention_mask": FakeAttentionMask(),
+                    "mm_token_type_ids": "ignored-mm-token-type-ids",
+                }
+            )
+
+        def batch_decode(
+            self,
+            generated_ids: object,
+            *,
+            skip_special_tokens: bool,
+            clean_up_tokenization_spaces: bool,
+        ) -> list[str]:
+            captured["generated_ids"] = generated_ids
+            captured["decode_kwargs"] = (skip_special_tokens, clean_up_tokenization_spaces)
+            return ["dots batch 1", "dots batch 2"]
+
+    class FakeProcessorCls:
+        @staticmethod
+        def from_pretrained(model_id: str, **kwargs: object) -> FakeProcessor:
+            captured["processor_model_id"] = model_id
+            captured["processor_from_pretrained_kwargs"] = kwargs
+            return FakeProcessor()
+
+    class FakeModel:
+        device = "fake-device"
+
+        def generate(self, **kwargs: object) -> list[list[int]]:
+            captured["generate_kwargs"] = kwargs
+            return [
+                [100, 101, 102, 103, 104, 105],
+                [200, 201, 202, 203, 204, 205],
+            ]
+
+    class FakeModelCls:
+        @staticmethod
+        def from_pretrained(model_id: str, **kwargs: object) -> FakeModel:
+            captured["model_model_id"] = model_id
+            captured["model_from_pretrained_kwargs"] = kwargs
+            return FakeModel()
+
+    def fake_process_vision_info(
+        conversation: list[dict[str, object]],
+        *,
+        return_video_kwargs: bool,
+        return_video_metadata: bool,
+    ) -> tuple[object, None, None]:
+        del conversation, return_video_kwargs, return_video_metadata
+        return "fake-image-inputs", None, None
+
+    monkeypatch.setattr(
+        "churro_ocr.providers.hf._load_hf_causal_runtime",
+        lambda: SimpleNamespace(
+            processor_cls=FakeProcessorCls,
+            model_cls=FakeModelCls,
+            process_vision_info=fake_process_vision_info,
+        ),
+    )
+    monkeypatch.setattr(
+        "churro_ocr.providers.hf._prepare_dots_ocr_model_dir",
+        lambda model_id: model_id,
+    )
+
+    backend = DotsOCR15OCRBackend()
+    results = backend._ocr_batch_sync(
+        [
+            DocumentPage.from_image(Image.new("RGB", (32, 32), color="white")),
+            DocumentPage.from_image(Image.new("RGB", (64, 64), color="white")),
+        ]
+    )
+
+    assert [result.text for result in results] == ["dots batch 1", "dots batch 2"]
+    assert captured["processor_kwargs"]["text"] == ["<dots-rendered:32>", "<dots-rendered:64>"]
+    assert captured["processor_kwargs"]["images"] == [["fake-image-inputs"], ["fake-image-inputs"]]
+    assert captured["generate_kwargs"] == {
+        "input_ids": SimpleNamespace(shape=(2, 4)),
+        "attention_mask": cast("object", captured["generate_kwargs"]["attention_mask"]),
+        "max_new_tokens": DEFAULT_OCR_MAX_TOKENS,
+    }
+    assert captured["attention_mask_sum_dim"] == 1
+    assert captured["generated_ids"] == [[104, 105], [204, 205]]
+    assert captured["decode_kwargs"] == (True, False)
+
+
 @pytest.mark.asyncio
 async def test_huggingface_vision_ocr_backend_strips_default_output_tags(
     monkeypatch: pytest.MonkeyPatch,

From 89f6ae10d3859c3b6be34367a9e4d752eca0518f Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Tue, 7 Apr 2026 01:40:54 +0000
Subject: [PATCH 23/28] chore(benchmarking): tune benchmark runs and refresh
 scores

---
 benchmark_results.json            | 18 +++++++
 tests/test_tooling_benchmark.py   | 81 +++++++++++++++++++++++++++++--
 tooling/benchmarking/benchmark.py | 20 ++++++--
 3 files changed, 112 insertions(+), 7 deletions(-)

diff --git a/benchmark_results.json b/benchmark_results.json
index 21183cc..76278b2 100644
--- a/benchmark_results.json
+++ b/benchmark_results.json
@@ -239,6 +239,15 @@
     "handwritten": 35.0806,
     "total": 47.7215
   },
+  {
+    "modelName": "PaddleOCR-VL 1.5",
+    "modelId": "PaddlePaddle/PaddleOCR-VL-1.5",
+    "modelUrl": "https://huggingface.co/PaddlePaddle/PaddleOCR-VL-1.5",
+    "iconPath": null,
+    "printed": 62.6,
+    "handwritten": 33.6,
+    "total": 47.0
+  },
   {
     "modelName": "O3",
     "modelId": "o3-2025-04-16",
@@ -398,6 +407,15 @@
     "handwritten": 15.2615,
     "total": 21.7585
   },
+  {
+    "modelName": "dots.ocr 1.5",
+    "modelId": "kristaller486/dots.ocr-1.5",
+    "modelUrl": "https://huggingface.co/kristaller486/dots.ocr-1.5",
+    "iconPath": null,
+    "printed": 22.2,
+    "handwritten": 10.4,
+    "total": 15.9
+  },
   {
     "modelName": "Phi 4 Multimodal",
     "modelId": "microsoft/Phi-4-multimodal-instruct",
diff --git a/tests/test_tooling_benchmark.py b/tests/test_tooling_benchmark.py
index 71ca46d..c6ed151 100644
--- a/tests/test_tooling_benchmark.py
+++ b/tests/test_tooling_benchmark.py
@@ -12,7 +12,11 @@
 from churro_ocr.providers.hf import HuggingFaceVisionOCRBackend
 from churro_ocr.providers.ocr import LiteLLMVisionOCRBackend
 from churro_ocr.providers.specs import DEFAULT_OCR_MAX_TOKENS
-from churro_ocr.templates import CHURRO_3B_XML_TEMPLATE, DOTS_OCR_1_5_OCR_TEMPLATE
+from churro_ocr.templates import (
+    CHURRO_3B_XML_TEMPLATE,
+    DOTS_OCR_1_5_OCR_TEMPLATE,
+    PADDLEOCR_VL_1_5_OCR_TEMPLATE,
+)
 from tooling.benchmarking import benchmark
 from tooling.evaluation.types import BenchmarkDatasetExample
 
@@ -271,6 +275,50 @@ def test_build_ocr_backend_uses_dots_preset_for_openai_compatible() -> None:
     }
 
 
+def test_build_ocr_backend_uses_paddleocr_vl_preset_for_hf() -> None:
+    backend = cast(
+        "HuggingFaceVisionOCRBackend",
+        benchmark._build_ocr_backend(
+            benchmark.BenchmarkOptions(
+                backend="hf",
+                dataset_split="dev",
+                model="PaddlePaddle/PaddleOCR-VL-1.5",
+            )
+        ),
+    )
+
+    assert backend.model_name == "PaddleOCR-VL-1.5"
+    assert backend.processor_kwargs == {}
+    assert backend.trust_remote_code is False
+    assert backend.model_kwargs == {"device_map": "auto", "torch_dtype": "auto"}
+    assert backend.generation_kwargs == {
+        "max_new_tokens": 4_096,
+        "do_sample": False,
+    }
+
+
+def test_build_ocr_backend_uses_paddleocr_vl_preset_for_openai_compatible() -> None:
+    backend = cast(
+        "LiteLLMVisionOCRBackend",
+        benchmark._build_ocr_backend(
+            benchmark.BenchmarkOptions(
+                backend="openai-compatible",
+                dataset_split="dev",
+                model="PaddlePaddle/PaddleOCR-VL-1.5",
+                base_url="http://127.0.0.1:8000/v1",
+            )
+        ),
+    )
+
+    assert backend.provider_name == "openai-compatible"
+    assert backend.model_name == "PaddleOCR-VL-1.5"
+    assert backend.template == PADDLEOCR_VL_1_5_OCR_TEMPLATE
+    assert backend.transport.config.completion_kwargs == {
+        "max_tokens": 4_096,
+        "temperature": 0.0,
+    }
+
+
 def test_build_ocr_backend_uses_churro_preset_template_for_openai_compatible() -> None:
     backend = cast(
         "LiteLLMVisionOCRBackend",
@@ -539,10 +587,20 @@ async def test_predict_texts_updates_progress_and_preserves_order(monkeypatch) -
     ]
 
     class FakeProgressBar:
-        def __init__(self, *, total: int | None, desc: str, unit: str) -> None:
+        def __init__(
+            self,
+            *,
+            total: int | None,
+            desc: str,
+            unit: str,
+            mininterval: float,
+            smoothing: float,
+        ) -> None:
             self.total = total
             self.desc = desc
             self.unit = unit
+            self.mininterval = mininterval
+            self.smoothing = smoothing
             self.updates: list[int] = []
             self.postfixes: list[dict[str, int]] = []
             self.refresh_count = 0
@@ -570,8 +628,21 @@ def refresh(self) -> None:
 
     progress_bars: list[FakeProgressBar] = []
 
-    def fake_tqdm(*, total: int | None, desc: str, unit: str) -> FakeProgressBar:
-        progress_bar = FakeProgressBar(total=total, desc=desc, unit=unit)
+    def fake_tqdm(
+        *,
+        total: int | None,
+        desc: str,
+        unit: str,
+        mininterval: float,
+        smoothing: float,
+    ) -> FakeProgressBar:
+        progress_bar = FakeProgressBar(
+            total=total,
+            desc=desc,
+            unit=unit,
+            mininterval=mininterval,
+            smoothing=smoothing,
+        )
         progress_bars.append(progress_bar)
         return progress_bar
 
@@ -612,6 +683,8 @@ async def ocr(self, page):  # noqa: ANN001
     assert progress_bars[0].total == 3
     assert progress_bars[0].desc == "OCR"
     assert progress_bars[0].unit == "page"
+    assert progress_bars[0].mininterval == benchmark.PROGRESS_BAR_MININTERVAL_SECONDS
+    assert progress_bars[0].smoothing == benchmark.PROGRESS_BAR_SMOOTHING
     assert progress_bars[0].updates == [1, 1, 1]
     assert progress_bars[0].postfixes[-1] == {
         "submitted": 3,
diff --git a/tooling/benchmarking/benchmark.py b/tooling/benchmarking/benchmark.py
index 55f78c5..88ae9e5 100644
--- a/tooling/benchmarking/benchmark.py
+++ b/tooling/benchmarking/benchmark.py
@@ -51,6 +51,8 @@
 CHURRO_DATASET_ID = "stanford-oval/churro-dataset"
 VALID_DATASET_SPLITS = {"dev", "test"}
 VALID_OCR_BACKENDS = {"litellm", "openai-compatible", "azure", "mistral", "hf"}
+PROGRESS_BAR_SMOOTHING = 0.05
+PROGRESS_BAR_MININTERVAL_SECONDS = 1.0
 BENCHMARK_DATASET_COLUMNS = (
     "image",
     "cleaned_transcription",
@@ -107,7 +109,7 @@ def build_parser(*, add_help: bool = True) -> argparse.ArgumentParser:
     parser.add_argument("--input-size", type=int, default=0)
     parser.add_argument("--offset", type=int, default=0)
     parser.add_argument("--output-dir", type=Path, default=None)
-    parser.add_argument("--max-concurrency", type=int, default=32)
+    parser.add_argument("--max-concurrency", type=int, default=16)
     parser.add_argument("--endpoint", default=None)
     parser.add_argument("--api-key", default=None)
     parser.add_argument("--base-url", default=None)
@@ -198,10 +200,22 @@ def _default_litellm_cache_dir() -> Path:
     return Path(__file__).resolve().parents[2] / "workdir" / "cache" / "litellm"
 
 
+def _create_progress_bar(*, total: int | None, desc: str, unit: str) -> tqdm[object]:
+    """Return a tqdm progress bar tuned for steadier ETA updates."""
+    return tqdm(
+        total=total,
+        desc=desc,
+        unit=unit,
+        mininterval=PROGRESS_BAR_MININTERVAL_SECONDS,
+        smoothing=PROGRESS_BAR_SMOOTHING,
+    )
+
+
 def _build_evaluation_example(example: BenchmarkDatasetExample) -> EvaluationExample:
     """Keep only the fields needed for evaluation after OCR completes."""
     return to_evaluation_example(example)
 
+
 def _selected_dataset_examples(
     dataset_stream: Iterable[BenchmarkDatasetExample],
     options: BenchmarkOptions,
@@ -299,7 +313,7 @@ async def _predict_texts(
         predictions: list[BenchmarkPrediction] = []
         submitted_pages = 0
 
-        with tqdm(total=total_pages, desc="OCR", unit="page") as progress:
+        with _create_progress_bar(total=total_pages, desc="OCR", unit="page") as progress:
             while True:
                 batch_examples: list[BenchmarkDatasetExample] = []
                 pages: list[DocumentPage] = []
@@ -373,7 +387,7 @@ def _progress_heartbeat(progress: tqdm[object], stop_event: threading.Event) ->
         while not stop_event.wait(wait_poll_seconds):
             _update_progress_status(progress, force_refresh=True)
 
-    with tqdm(total=total_pages, desc="OCR", unit="page") as progress:
+    with _create_progress_bar(total=total_pages, desc="OCR", unit="page") as progress:
         heartbeat_stop_event = threading.Event()
         heartbeat_thread = threading.Thread(
             target=_progress_heartbeat,

From eb1fd19cc0041e3c4c6bb067780fcbf1798a6c54 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Tue, 7 Apr 2026 03:31:54 +0000
Subject: [PATCH 24/28] feat(providers): add dots.mocr OCR support

Register the built-in rednote-hilab/dots.mocr profile for both Hugging Face and openai-compatible backends, export the template preset, and cover the integration with provider, CLI, benchmark, and documentation updates.
---
 docs/guides/providers.md             |  3 +-
 src/churro_ocr/providers/builder.py  |  5 ++-
 src/churro_ocr/providers/hf.py       | 12 +++++++
 src/churro_ocr/providers/specs.py    | 24 +++++++++++++
 src/churro_ocr/templates/__init__.py |  6 ++++
 src/churro_ocr/templates/presets.py  |  9 +++++
 tests/test_cli.py                    | 43 +++++++++++++++++++++++
 tests/test_hf_ocr.py                 | 52 ++++++++++++++++++++++++++++
 tests/test_providers.py              | 21 +++++++++++
 tests/test_tooling_benchmark.py      | 46 ++++++++++++++++++++++++
 10 files changed, 219 insertions(+), 2 deletions(-)

diff --git a/docs/guides/providers.md b/docs/guides/providers.md
index 90afda1..7b8b555 100644
--- a/docs/guides/providers.md
+++ b/docs/guides/providers.md
@@ -145,7 +145,7 @@ backend = build_ocr_backend(
 )
 ```
 
-Built-in model-specific profiles are resolved automatically for known models such as `stanford-oval/churro-3B`, `datalab-to/chandra-ocr-2`, `kristaller486/dots.ocr-1.5`, and the supported `olmOCR` checkpoints.
+Built-in model-specific profiles are resolved automatically for known models such as `stanford-oval/churro-3B`, `datalab-to/chandra-ocr-2`, `kristaller486/dots.ocr-1.5`, `rednote-hilab/dots.mocr`, and the supported `olmOCR` checkpoints.
 
 ## `OCRBackendSpec` Reference
 
@@ -209,6 +209,7 @@ Useful public template exports:
 | `CHURRO_3B_XML_TEMPLATE` | `churro_ocr.templates` | Built-in template for `stanford-oval/churro-3B`. |
 | `CHANDRA_OCR_2_OCR_TEMPLATE` | `churro_ocr.templates` | Built-in template for `datalab-to/chandra-ocr-2`. |
 | `DOTS_OCR_1_5_OCR_TEMPLATE` | `churro_ocr.templates` | Built-in template for `kristaller486/dots.ocr-1.5`. |
+| `DOTS_MOCR_OCR_TEMPLATE` | `churro_ocr.templates` | Built-in template for `rednote-hilab/dots.mocr`. |
 | `OCRPromptTemplate` | `churro_ocr.templates` | Base protocol for custom profile integration. |
 
 Useful public prompt exports:
diff --git a/src/churro_ocr/providers/builder.py b/src/churro_ocr/providers/builder.py
index afd70f6..b670364 100644
--- a/src/churro_ocr/providers/builder.py
+++ b/src/churro_ocr/providers/builder.py
@@ -7,6 +7,7 @@
 from churro_ocr.ocr import OCRBackend
 from churro_ocr.providers.hf import (
     ChandraOCR2OCRBackend,
+    DotsMOCROCRBackend,
     DotsOCR15OCRBackend,
     HuggingFaceVisionOCRBackend,
     LFM25VLOCRBackend,
@@ -164,8 +165,10 @@ def _build_huggingface_backend(spec: OCRBackendSpec, profile: OCRModelProfile) -
     )
     backend_cls: type[HuggingFaceVisionOCRBackend] = HuggingFaceVisionOCRBackend
     model_kwargs = dict(options.model_kwargs)
-    if options.backend_variant == "dots-ocr-1.5":
+    if options.backend_variant in {"dots-ocr-1.5", "dots-mocr"}:
         backend_cls = DotsOCR15OCRBackend
+        if options.backend_variant == "dots-mocr":
+            backend_cls = DotsMOCROCRBackend
         model_kwargs = _merge_mapping(_default_dots_ocr_1_5_model_kwargs(), model_kwargs)
     elif options.backend_variant == "chandra-ocr-2":
         backend_cls = ChandraOCR2OCRBackend
diff --git a/src/churro_ocr/providers/hf.py b/src/churro_ocr/providers/hf.py
index 98f9b91..c4fdf1f 100644
--- a/src/churro_ocr/providers/hf.py
+++ b/src/churro_ocr/providers/hf.py
@@ -34,6 +34,8 @@
     CHANDRA_OCR_2_OCR_TEMPLATE,
     CHURRO_3B_MODEL_ID,
     CHURRO_3B_XML_TEMPLATE,
+    DOTS_MOCR_MODEL_ID,
+    DOTS_MOCR_OCR_TEMPLATE,
     DOTS_OCR_1_5_MODEL_ID,
     DOTS_OCR_1_5_OCR_TEMPLATE,
     LFM2_5_VL_1_6B_MODEL_ID,
@@ -756,6 +758,15 @@ def _get_model(self, runtime: _HFRuntime) -> Any:
         return self._model
 
 
+@dataclass(slots=True)
+class DotsMOCROCRBackend(DotsOCR15OCRBackend):
+    """Preset OCR backend for ``rednote-hilab/dots.mocr``."""
+
+    model_id: str = DOTS_MOCR_MODEL_ID
+    template: OCRPromptTemplateLike = DOTS_MOCR_OCR_TEMPLATE
+    model_name: str | None = "dots.mocr"
+
+
 @dataclass(slots=True)
 class PaddleOCRVL15OCRBackend(HuggingFaceVisionOCRBackend):
     """Preset OCR backend for ``PaddlePaddle/PaddleOCR-VL-1.5``."""
@@ -1013,6 +1024,7 @@ def _ocr_batch_sync(self, pages: list[DocumentPage]) -> list[OCRResult]:
 __all__ = [
     "ChandraOCR2OCRBackend",
     "Churro3BOCRBackend",
+    "DotsMOCROCRBackend",
     "DotsOCR15OCRBackend",
     "HuggingFaceVisionOCRBackend",
     "LFM25VLOCRBackend",
diff --git a/src/churro_ocr/providers/specs.py b/src/churro_ocr/providers/specs.py
index ab0f699..27f64b4 100644
--- a/src/churro_ocr/providers/specs.py
+++ b/src/churro_ocr/providers/specs.py
@@ -24,6 +24,8 @@
     CHURRO_3B_MODEL_ID,
     CHURRO_3B_XML_TEMPLATE,
     DEFAULT_OCR_TEMPLATE,
+    DOTS_MOCR_MODEL_ID,
+    DOTS_MOCR_OCR_TEMPLATE,
     DOTS_OCR_1_5_MODEL_ID,
     DOTS_OCR_1_5_OCR_TEMPLATE,
     LFM2_5_VL_1_6B_MODEL_ID,
@@ -416,6 +418,26 @@ def dots_ocr_1_5_profile() -> OCRModelProfile:
     )
 
 
+def dots_mocr_profile() -> OCRModelProfile:
+    """Return the built-in ``rednote-hilab/dots.mocr`` OCR profile."""
+    return OCRModelProfile(
+        profile_name=DOTS_MOCR_MODEL_ID,
+        template=DOTS_MOCR_OCR_TEMPLATE,
+        text_postprocessor=identity_text_postprocessor,
+        display_name="dots.mocr",
+        transport=LiteLLMTransportConfig(
+            completion_kwargs={
+                "max_tokens": DEFAULT_OCR_MAX_TOKENS,
+                "temperature": 0.0,
+            }
+        ),
+        huggingface=HuggingFaceOptions(
+            trust_remote_code=True,
+            backend_variant="dots-mocr",
+        ),
+    )
+
+
 def paddleocr_vl_1_5_profile() -> OCRModelProfile:
     """Return the built-in ``PaddlePaddle/PaddleOCR-VL-1.5`` OCR profile."""
     return OCRModelProfile(
@@ -500,6 +522,7 @@ def _profile_registry() -> dict[str, OCRModelProfile]:
     default_profile = default_ocr_profile()
     churro_profile = churro_3b_profile()
     chandra_profile = chandra_ocr_2_profile()
+    dots_mocr = dots_mocr_profile()
     dots_profile = dots_ocr_1_5_profile()
     lfm2_5_vl_profile = lfm2_5_vl_1_6b_profile()
     olmocr_profile = olmocr_2_7b_1025_profile()
@@ -509,6 +532,7 @@ def _profile_registry() -> dict[str, OCRModelProfile]:
         default_profile.profile_name: default_profile,
         churro_profile.profile_name: churro_profile,
         chandra_profile.profile_name: chandra_profile,
+        dots_mocr.profile_name: dots_mocr,
         dots_profile.profile_name: dots_profile,
         lfm2_5_vl_profile.profile_name: lfm2_5_vl_profile,
         olmocr_profile.profile_name: olmocr_profile,
diff --git a/src/churro_ocr/templates/__init__.py b/src/churro_ocr/templates/__init__.py
index 4324315..b9e9e18 100644
--- a/src/churro_ocr/templates/__init__.py
+++ b/src/churro_ocr/templates/__init__.py
@@ -14,6 +14,9 @@
     CHURRO_3B_MODEL_ID,
     CHURRO_3B_XML_TEMPLATE,
     DEFAULT_OCR_TEMPLATE,
+    DOTS_MOCR_MODEL_ID,
+    DOTS_MOCR_OCR_PROMPT,
+    DOTS_MOCR_OCR_TEMPLATE,
     DOTS_OCR_1_5_MODEL_ID,
     DOTS_OCR_1_5_OCR_PROMPT,
     DOTS_OCR_1_5_OCR_TEMPLATE,
@@ -34,6 +37,9 @@
     "CHANDRA_OCR_2_MODEL_ID",
     "CHANDRA_OCR_2_OCR_TEMPLATE",
     "DEFAULT_OCR_TEMPLATE",
+    "DOTS_MOCR_MODEL_ID",
+    "DOTS_MOCR_OCR_PROMPT",
+    "DOTS_MOCR_OCR_TEMPLATE",
     "DOTS_OCR_1_5_MODEL_ID",
     "DOTS_OCR_1_5_OCR_PROMPT",
     "DOTS_OCR_1_5_OCR_TEMPLATE",
diff --git a/src/churro_ocr/templates/presets.py b/src/churro_ocr/templates/presets.py
index 3a549af..300a65f 100644
--- a/src/churro_ocr/templates/presets.py
+++ b/src/churro_ocr/templates/presets.py
@@ -13,6 +13,7 @@
 CHURRO_3B_MODEL_ID = "stanford-oval/churro-3B"
 CHANDRA_OCR_2_MODEL_ID = "datalab-to/chandra-ocr-2"
 DOTS_OCR_1_5_MODEL_ID = "kristaller486/dots.ocr-1.5"
+DOTS_MOCR_MODEL_ID = "rednote-hilab/dots.mocr"
 PADDLEOCR_VL_1_5_MODEL_ID = "PaddlePaddle/PaddleOCR-VL-1.5"
 OLMOCR_2_7B_1025_MODEL_ID = "allenai/olmOCR-2-7B-1025"
 OLMOCR_2_7B_1025_FP8_MODEL_ID = "allenai/olmOCR-2-7B-1025-FP8"
@@ -35,6 +36,11 @@
     system_message=None,
     user_prompt=DOTS_OCR_1_5_OCR_PROMPT,
 )
+DOTS_MOCR_OCR_PROMPT = DOTS_OCR_1_5_OCR_PROMPT
+DOTS_MOCR_OCR_TEMPLATE = HFChatTemplate(
+    system_message=None,
+    user_prompt=DOTS_MOCR_OCR_PROMPT,
+)
 PADDLEOCR_VL_1_5_OCR_PROMPT = "OCR:"
 PADDLEOCR_VL_1_5_OCR_TEMPLATE = HFChatTemplate(
     system_message=None,
@@ -57,6 +63,9 @@
     "CHANDRA_OCR_2_MODEL_ID",
     "CHANDRA_OCR_2_OCR_TEMPLATE",
     "DEFAULT_OCR_TEMPLATE",
+    "DOTS_MOCR_MODEL_ID",
+    "DOTS_MOCR_OCR_PROMPT",
+    "DOTS_MOCR_OCR_TEMPLATE",
     "DOTS_OCR_1_5_MODEL_ID",
     "DOTS_OCR_1_5_OCR_PROMPT",
     "DOTS_OCR_1_5_OCR_TEMPLATE",
diff --git a/tests/test_cli.py b/tests/test_cli.py
index 237c32d..875b8ad 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -16,10 +16,12 @@
 from churro_ocr.ocr import OCRResult
 from churro_ocr.page_detection import DocumentPage, PageDetectionResult
 from churro_ocr.prompts import DEFAULT_OCR_OUTPUT_TAG
+from churro_ocr.providers.specs import DEFAULT_OCR_MAX_TOKENS
 from churro_ocr.templates import (
     CHANDRA_OCR_2_MODEL_ID,
     CHANDRA_OCR_2_OCR_TEMPLATE,
     DEFAULT_OCR_TEMPLATE,
+    DOTS_MOCR_OCR_TEMPLATE,
     DOTS_OCR_1_5_OCR_TEMPLATE,
     OLMOCR_2_7B_1025_MODEL_ID,
     OLMOCR_2_7B_1025_OCR_TEMPLATE,
@@ -209,6 +211,47 @@ def test_build_ocr_backend_aligns_templates_for_dots() -> None:
     }
 
 
+def test_build_ocr_backend_aligns_templates_for_dots_mocr() -> None:
+    litellm_backend = cli_module._build_ocr_backend(
+        backend="litellm",
+        model="rednote-hilab/dots.mocr",
+        endpoint=None,
+        api_key=None,
+        base_url=None,
+        api_version=None,
+    )
+    hf_backend = cli_module._build_ocr_backend(
+        backend="hf",
+        model="rednote-hilab/dots.mocr",
+        endpoint=None,
+        api_key=None,
+        base_url=None,
+        api_version=None,
+    )
+    openai_backend = cli_module._build_ocr_backend(
+        backend="openai-compatible",
+        model="rednote-hilab/dots.mocr",
+        endpoint=None,
+        api_key=None,
+        base_url="http://127.0.0.1:8000/v1",
+        api_version=None,
+    )
+
+    assert litellm_backend.template == DOTS_MOCR_OCR_TEMPLATE
+    assert litellm_backend.template == hf_backend.template == openai_backend.template
+    assert litellm_backend.model_name == "dots.mocr"
+    assert hf_backend.model_name == "dots.mocr"
+    assert openai_backend.model_name == "dots.mocr"
+    assert litellm_backend.transport.config.completion_kwargs == {
+        "max_tokens": DEFAULT_OCR_MAX_TOKENS,
+        "temperature": 0.0,
+    }
+    assert openai_backend.transport.config.completion_kwargs == {
+        "max_tokens": DEFAULT_OCR_MAX_TOKENS,
+        "temperature": 0.0,
+    }
+
+
 def test_build_ocr_backend_aligns_templates_for_paddleocr_vl() -> None:
     litellm_backend = cli_module._build_ocr_backend(
         backend="litellm",
diff --git a/tests/test_hf_ocr.py b/tests/test_hf_ocr.py
index cfe5057..855e0c3 100644
--- a/tests/test_hf_ocr.py
+++ b/tests/test_hf_ocr.py
@@ -23,6 +23,7 @@
 from churro_ocr.providers.hf import (
     ChandraOCR2OCRBackend,
     Churro3BOCRBackend,
+    DotsMOCROCRBackend,
     DotsOCR15OCRBackend,
     HuggingFaceVisionOCRBackend,
     LFM25VLOCRBackend,
@@ -33,6 +34,9 @@
     CHANDRA_OCR_2_MODEL_ID,
     CHANDRA_OCR_2_OCR_TEMPLATE,
     CHURRO_3B_XML_TEMPLATE,
+    DOTS_MOCR_MODEL_ID,
+    DOTS_MOCR_OCR_PROMPT,
+    DOTS_MOCR_OCR_TEMPLATE,
     DOTS_OCR_1_5_MODEL_ID,
     DOTS_OCR_1_5_OCR_PROMPT,
     DOTS_OCR_1_5_OCR_TEMPLATE,
@@ -233,6 +237,29 @@ def test_build_ocr_backend_uses_paddleocr_vl_profile_defaults_for_hf() -> None:
     }
 
 
+def test_build_ocr_backend_uses_dots_mocr_profile_defaults_for_hf() -> None:
+    backend = cast(
+        "DotsMOCROCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="hf",
+                model=DOTS_MOCR_MODEL_ID,
+            )
+        ),
+    )
+
+    assert isinstance(backend, DotsMOCROCRBackend)
+    assert backend.template == DOTS_MOCR_OCR_TEMPLATE
+    assert backend.model_name == "dots.mocr"
+    assert backend.generation_kwargs == {"max_new_tokens": DEFAULT_OCR_MAX_TOKENS}
+    assert backend.trust_remote_code is True
+    assert backend.processor_kwargs == {}
+    assert backend.model_kwargs["dtype"] in {"auto", "float32"}
+    if backend.model_kwargs["dtype"] == "auto" and "device_map" in backend.model_kwargs:
+        assert backend.model_kwargs["device_map"] == "auto"
+        assert "max_memory" in backend.model_kwargs
+
+
 @pytest.mark.asyncio
 async def test_chandra_huggingface_backend_matches_upstream_chat_template_and_eos_behavior(
     monkeypatch: pytest.MonkeyPatch,
@@ -975,6 +1002,31 @@ def test_dots_ocr_15_backend_uses_expected_defaults() -> None:
     assert backend.generation_kwargs == {"max_new_tokens": DEFAULT_OCR_MAX_TOKENS}
 
 
+def test_dots_mocr_backend_uses_expected_defaults() -> None:
+    backend = DotsMOCROCRBackend()
+
+    assert backend.model_id == DOTS_MOCR_MODEL_ID
+    assert backend.template == DOTS_MOCR_OCR_TEMPLATE
+    assert backend.model_name == "dots.mocr"
+    assert backend.trust_remote_code is True
+    assert backend.processor_kwargs == {}
+    assert backend.model_kwargs["dtype"] in {"auto", "float32"}
+    if backend.model_kwargs["dtype"] == "auto" and "device_map" in backend.model_kwargs:
+        assert backend.model_kwargs["device_map"] == "auto"
+        assert "max_memory" in backend.model_kwargs
+    assert backend.generation_kwargs == {"max_new_tokens": DEFAULT_OCR_MAX_TOKENS}
+
+
+def test_dots_mocr_template_matches_upstream_prompt() -> None:
+    page = DocumentPage.from_image(Image.new("RGB", (20, 20), color="white"))
+
+    conversation = DOTS_MOCR_OCR_TEMPLATE.build_conversation(page)
+
+    assert conversation[0]["role"] == "user"
+    assert conversation[0]["content"][0]["type"] == "image"
+    assert conversation[0]["content"][1]["text"] == DOTS_MOCR_OCR_PROMPT
+
+
 @pytest.mark.asyncio
 async def test_paddleocr_vl_15_backend_uses_tokenized_chat_template_and_profile_defaults(
     monkeypatch: pytest.MonkeyPatch,
diff --git a/tests/test_providers.py b/tests/test_providers.py
index fc959a0..c123543 100644
--- a/tests/test_providers.py
+++ b/tests/test_providers.py
@@ -49,6 +49,7 @@
     CHANDRA_OCR_2_MODEL_ID,
     CHANDRA_OCR_2_OCR_TEMPLATE,
     DEFAULT_OCR_TEMPLATE,
+    DOTS_MOCR_OCR_TEMPLATE,
     OLMOCR_2_7B_1025_FP8_MODEL_ID,
     OLMOCR_2_7B_1025_MODEL_ID,
     OLMOCR_2_7B_1025_OCR_TEMPLATE,
@@ -794,6 +795,26 @@ def test_build_ocr_backend_uses_paddleocr_vl_profile_defaults_for_openai_compati
     }
 
 
+def test_build_ocr_backend_uses_dots_mocr_profile_defaults_for_openai_compatible() -> None:
+    backend = cast(
+        "OpenAICompatibleOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="openai-compatible",
+                model="rednote-hilab/dots.mocr",
+                transport=LiteLLMTransportConfig(api_base="http://127.0.0.1:8000/v1"),
+            )
+        ),
+    )
+
+    assert backend.template == DOTS_MOCR_OCR_TEMPLATE
+    assert backend.model_name == "dots.mocr"
+    assert backend.transport.config.completion_kwargs == {
+        "max_tokens": DEFAULT_OCR_MAX_TOKENS,
+        "temperature": 0.0,
+    }
+
+
 @pytest.mark.asyncio
 async def test_openai_compatible_backend_uses_olmocr_prompt_and_plain_text_postprocessing(
     monkeypatch: pytest.MonkeyPatch,
diff --git a/tests/test_tooling_benchmark.py b/tests/test_tooling_benchmark.py
index c6ed151..c5817b5 100644
--- a/tests/test_tooling_benchmark.py
+++ b/tests/test_tooling_benchmark.py
@@ -14,6 +14,7 @@
 from churro_ocr.providers.specs import DEFAULT_OCR_MAX_TOKENS
 from churro_ocr.templates import (
     CHURRO_3B_XML_TEMPLATE,
+    DOTS_MOCR_OCR_TEMPLATE,
     DOTS_OCR_1_5_OCR_TEMPLATE,
     PADDLEOCR_VL_1_5_OCR_TEMPLATE,
 )
@@ -275,6 +276,51 @@ def test_build_ocr_backend_uses_dots_preset_for_openai_compatible() -> None:
     }
 
 
+def test_build_ocr_backend_uses_dots_mocr_preset_for_hf() -> None:
+    backend = cast(
+        "HuggingFaceVisionOCRBackend",
+        benchmark._build_ocr_backend(
+            benchmark.BenchmarkOptions(
+                backend="hf",
+                dataset_split="dev",
+                model="rednote-hilab/dots.mocr",
+            )
+        ),
+    )
+
+    assert backend.model_name == "dots.mocr"
+    assert backend.processor_kwargs == {}
+    assert backend.trust_remote_code is True
+    assert backend.model_kwargs["dtype"] in {"auto", "float32"}
+    if backend.model_kwargs["dtype"] == "auto" and "device_map" in backend.model_kwargs:
+        assert backend.model_kwargs["device_map"] == "auto"
+    if "max_memory" in backend.model_kwargs:
+        assert backend.model_kwargs["max_memory"]
+    assert backend.generation_kwargs == {"max_new_tokens": DEFAULT_OCR_MAX_TOKENS}
+
+
+def test_build_ocr_backend_uses_dots_mocr_preset_for_openai_compatible() -> None:
+    backend = cast(
+        "LiteLLMVisionOCRBackend",
+        benchmark._build_ocr_backend(
+            benchmark.BenchmarkOptions(
+                backend="openai-compatible",
+                dataset_split="dev",
+                model="rednote-hilab/dots.mocr",
+                base_url="http://127.0.0.1:8000/v1",
+            )
+        ),
+    )
+
+    assert backend.provider_name == "openai-compatible"
+    assert backend.model_name == "dots.mocr"
+    assert backend.template == DOTS_MOCR_OCR_TEMPLATE
+    assert backend.transport.config.completion_kwargs == {
+        "max_tokens": DEFAULT_OCR_MAX_TOKENS,
+        "temperature": 0.0,
+    }
+
+
 def test_build_ocr_backend_uses_paddleocr_vl_preset_for_hf() -> None:
     backend = cast(
         "HuggingFaceVisionOCRBackend",

From 03682e8cbe4c96470fd3c1aec90d34b1e52c751a Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Tue, 7 Apr 2026 03:32:00 +0000
Subject: [PATCH 25/28] chore(benchmark): add dots.mocr test results

Record the CHURRO test-set vLLM benchmark entry for rednote-hilab/dots.mocr in benchmark_results.json.
---
 benchmark_results.json | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/benchmark_results.json b/benchmark_results.json
index 76278b2..dd35a45 100644
--- a/benchmark_results.json
+++ b/benchmark_results.json
@@ -35,6 +35,15 @@
     "handwritten": 63.6329,
     "total": 71.5803
   },
+  {
+    "modelName": "dots.mocr",
+    "modelId": "rednote-hilab/dots.mocr",
+    "modelUrl": "https://huggingface.co/rednote-hilab/dots.mocr",
+    "iconPath": null,
+    "printed": 81.2,
+    "handwritten": 55.0,
+    "total": 67.1
+  },
   {
     "modelName": "Gemini 2.5 Flash",
     "modelId": "gemini-2.5-flash",

From cdf37de231fa6112725705c8fa86d65674f32323 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Tue, 7 Apr 2026 06:25:27 +0000
Subject: [PATCH 26/28] feat(providers): add DeepSeek OCR 2 support

---
 docs/guides/providers.md             |   3 +-
 src/churro_ocr/providers/builder.py  |   3 +
 src/churro_ocr/providers/hf.py       | 193 ++++++++++++++++++++++++++-
 src/churro_ocr/providers/specs.py    |  59 ++++++++
 src/churro_ocr/templates/__init__.py |   6 +
 src/churro_ocr/templates/presets.py  |   9 ++
 tests/test_cli.py                    |  43 ++++++
 tests/test_hf_ocr.py                 | 167 ++++++++++++++++++++++-
 tests/test_providers.py              |  84 ++++++++++++
 tests/test_tooling_benchmark.py      |  46 +++++++
 10 files changed, 610 insertions(+), 3 deletions(-)

diff --git a/docs/guides/providers.md b/docs/guides/providers.md
index 7b8b555..1b061bb 100644
--- a/docs/guides/providers.md
+++ b/docs/guides/providers.md
@@ -145,7 +145,7 @@ backend = build_ocr_backend(
 )
 ```
 
-Built-in model-specific profiles are resolved automatically for known models such as `stanford-oval/churro-3B`, `datalab-to/chandra-ocr-2`, `kristaller486/dots.ocr-1.5`, `rednote-hilab/dots.mocr`, and the supported `olmOCR` checkpoints.
+Built-in model-specific profiles are resolved automatically for known models such as `stanford-oval/churro-3B`, `datalab-to/chandra-ocr-2`, `deepseek-ai/DeepSeek-OCR-2`, `kristaller486/dots.ocr-1.5`, `rednote-hilab/dots.mocr`, and the supported `olmOCR` checkpoints.
 
 ## `OCRBackendSpec` Reference
 
@@ -208,6 +208,7 @@ Useful public template exports:
 | `DEFAULT_OCR_TEMPLATE` | `churro_ocr.templates` | Generic OCR prompt template used by the default model profile. |
 | `CHURRO_3B_XML_TEMPLATE` | `churro_ocr.templates` | Built-in template for `stanford-oval/churro-3B`. |
 | `CHANDRA_OCR_2_OCR_TEMPLATE` | `churro_ocr.templates` | Built-in template for `datalab-to/chandra-ocr-2`. |
+| `DEEPSEEK_OCR_2_OCR_TEMPLATE` | `churro_ocr.templates` | Built-in template for `deepseek-ai/DeepSeek-OCR-2`. |
 | `DOTS_OCR_1_5_OCR_TEMPLATE` | `churro_ocr.templates` | Built-in template for `kristaller486/dots.ocr-1.5`. |
 | `DOTS_MOCR_OCR_TEMPLATE` | `churro_ocr.templates` | Built-in template for `rednote-hilab/dots.mocr`. |
 | `OCRPromptTemplate` | `churro_ocr.templates` | Base protocol for custom profile integration. |
diff --git a/src/churro_ocr/providers/builder.py b/src/churro_ocr/providers/builder.py
index b670364..09975ed 100644
--- a/src/churro_ocr/providers/builder.py
+++ b/src/churro_ocr/providers/builder.py
@@ -7,6 +7,7 @@
 from churro_ocr.ocr import OCRBackend
 from churro_ocr.providers.hf import (
     ChandraOCR2OCRBackend,
+    DeepSeekOCR2OCRBackend,
     DotsMOCROCRBackend,
     DotsOCR15OCRBackend,
     HuggingFaceVisionOCRBackend,
@@ -170,6 +171,8 @@ def _build_huggingface_backend(spec: OCRBackendSpec, profile: OCRModelProfile) -
         if options.backend_variant == "dots-mocr":
             backend_cls = DotsMOCROCRBackend
         model_kwargs = _merge_mapping(_default_dots_ocr_1_5_model_kwargs(), model_kwargs)
+    elif options.backend_variant == "deepseek-ocr-2":
+        backend_cls = DeepSeekOCR2OCRBackend
     elif options.backend_variant == "chandra-ocr-2":
         backend_cls = ChandraOCR2OCRBackend
     elif options.backend_variant == "paddleocr-vl-1.5":
diff --git a/src/churro_ocr/providers/hf.py b/src/churro_ocr/providers/hf.py
index c4fdf1f..567f291 100644
--- a/src/churro_ocr/providers/hf.py
+++ b/src/churro_ocr/providers/hf.py
@@ -7,12 +7,13 @@
 from dataclasses import dataclass, field
 from importlib import import_module
 from pathlib import Path
+from tempfile import TemporaryDirectory
 from types import MethodType
 from typing import Any, cast
 
 from churro_ocr._internal.install import install_command_hint
 from churro_ocr._internal.prompt_logging import log_prompt_payload_once
-from churro_ocr.errors import ConfigurationError
+from churro_ocr.errors import ConfigurationError, ProviderError
 from churro_ocr.ocr import OCRBackend, OCRResult
 from churro_ocr.page_detection import DocumentPage
 from churro_ocr.providers._shared import (
@@ -34,6 +35,8 @@
     CHANDRA_OCR_2_OCR_TEMPLATE,
     CHURRO_3B_MODEL_ID,
     CHURRO_3B_XML_TEMPLATE,
+    DEEPSEEK_OCR_2_MODEL_ID,
+    DEEPSEEK_OCR_2_OCR_TEMPLATE,
     DOTS_MOCR_MODEL_ID,
     DOTS_MOCR_OCR_TEMPLATE,
     DOTS_OCR_1_5_MODEL_ID,
@@ -44,6 +47,7 @@
     PADDLEOCR_VL_1_5_OCR_TEMPLATE,
     OCRConversation,
     OCRPromptTemplateLike,
+    build_ocr_conversation,
 )
 
 _HF_EXTRA_INSTALL_HINT = install_command_hint("hf")
@@ -100,6 +104,33 @@ def _load_hf_causal_runtime() -> _HFRuntime:
     )
 
 
+def _load_hf_auto_model_runtime() -> _HFRuntime:
+    _ensure_hf_torch_runtime()
+    try:
+        from transformers import AutoModel, AutoTokenizer
+    except ImportError as exc:  # pragma: no cover - optional extra path
+        raise ConfigurationError(
+            f"Hugging Face OCR requires the `hf` runtime. {_HF_EXTRA_INSTALL_HINT}"
+        ) from exc
+
+    return _HFRuntime(
+        processor_cls=AutoTokenizer,
+        model_cls=AutoModel,
+        process_vision_info=None,
+    )
+
+
+def _ensure_deepseek_ocr_2_cuda_runtime() -> Any:
+    _ensure_hf_torch_runtime()
+    torch = import_module("torch")
+    if not torch.cuda.is_available():
+        raise ConfigurationError(
+            "DeepSeek-OCR-2 HF backend requires a CUDA-capable PyTorch runtime because "
+            "the upstream `infer(...)` implementation moves inputs to CUDA."
+        )
+    return torch
+
+
 _DOTS_OCR_1_5_LOCAL_DIRNAME = "DotsOCR_1_5"
 _DOTS_FLASH_ATTN_IMPORT = "from flash_attn import flash_attn_varlen_func"
 _DOTS_FLASH_ATTN_FALLBACK = """try:
@@ -263,6 +294,39 @@ def _default_chandra_ocr_2_model_kwargs() -> dict[str, object]:
     return model_kwargs
 
 
+def _deepseek_ocr_2_prompt_from_conversation(conversation: OCRConversation) -> str:
+    prompt_lines: list[str] = []
+    has_image = False
+    for message in conversation:
+        if message.get("role") == "system":
+            content_items = cast("list[dict[str, object]]", message["content"])
+            system_text = "\n".join(
+                cast("str", item["text"]).strip()
+                for item in content_items
+                if item.get("type") == "text" and isinstance(item.get("text"), str)
+            ).strip()
+            if system_text:
+                raise ConfigurationError("DeepSeek-OCR-2 does not support system prompts in the HF backend.")
+            continue
+        if message.get("role") != "user":
+            continue
+        content_items = cast("list[dict[str, object]]", message["content"])
+        for item in content_items:
+            if item.get("type") == "image":
+                has_image = True
+                continue
+            if item.get("type") == "text" and isinstance(item.get("text"), str):
+                text = cast("str", item["text"]).strip()
+                if text:
+                    prompt_lines.append(text)
+    prompt_text = "\n".join(prompt_lines).strip()
+    if not prompt_text:
+        raise ConfigurationError("DeepSeek-OCR-2 requires a non-empty OCR prompt.")
+    if has_image:
+        return f"<image>\n{prompt_text}"
+    return prompt_text
+
+
 def _move_batch_to_model(batch: Any, model: Any) -> Any:
     model_device = getattr(model, "device", None)
     if hasattr(batch, "to") and model_device is not None:
@@ -707,6 +771,132 @@ class Churro3BOCRBackend(HuggingFaceVisionOCRBackend):
     model_name: str | None = "churro-3B"
 
 
+@dataclass(slots=True)
+class DeepSeekOCR2OCRBackend(HuggingFaceVisionOCRBackend):
+    """Preset OCR backend for ``deepseek-ai/DeepSeek-OCR-2``."""
+
+    model_id: str = DEEPSEEK_OCR_2_MODEL_ID
+    template: OCRPromptTemplateLike = DEEPSEEK_OCR_2_OCR_TEMPLATE
+    model_name: str | None = "DeepSeek-OCR-2"
+    trust_remote_code: bool = True
+    model_kwargs: dict[str, object] = field(default_factory=lambda: {"use_safetensors": True})
+    generation_kwargs: dict[str, object] = field(default_factory=lambda: {"max_new_tokens": 8_192})
+    base_size: int = 1_024
+    image_size: int = 768
+    crop_mode: bool = True
+
+    def _load_runtime(self) -> _HFRuntime:
+        return _load_hf_auto_model_runtime()
+
+    def _get_model(self, runtime: _HFRuntime) -> Any:
+        torch = _ensure_deepseek_ocr_2_cuda_runtime()
+        if self._model is None:
+            with self._init_lock:
+                if self._model is None:
+                    model_kwargs = dict(self.model_kwargs)
+                    model = runtime.model_cls.from_pretrained(
+                        self._get_model_source(),
+                        trust_remote_code=self.trust_remote_code,
+                        **model_kwargs,
+                    )
+                    eval_method = getattr(model, "eval", None)
+                    if callable(eval_method):
+                        model = eval_method()
+                    cuda_method = getattr(model, "cuda", None)
+                    if callable(cuda_method) and "device_map" not in model_kwargs:
+                        model = cuda_method()
+                    to_method = getattr(model, "to", None)
+                    if (
+                        callable(to_method)
+                        and "torch_dtype" not in model_kwargs
+                        and "dtype" not in model_kwargs
+                    ):
+                        model = to_method(torch.bfloat16)
+                    self._model = model
+        return self._model
+
+    def _infer_deepseek_page(
+        self,
+        *,
+        tokenizer: Any,
+        model: Any,
+        page: DocumentPage,
+        batch_size: int,
+    ) -> OCRResult:
+        conversation = build_ocr_conversation(self.template, page)
+        rendered_prompt = _deepseek_ocr_2_prompt_from_conversation(conversation)
+        self._log_prompt_payload(
+            rendered_prompt=rendered_prompt,
+            conversation=conversation,
+            batch_size=batch_size,
+        )
+
+        infer_method = getattr(model, "infer", None)
+        if not callable(infer_method):
+            raise ConfigurationError("DeepSeek-OCR-2 requires a model object with `infer(...)` support.")
+
+        with TemporaryDirectory(prefix="churro-deepseek-ocr-2-") as output_dir:
+            image_path = Path(output_dir) / "page.png"
+            page.image.save(image_path)
+            text = infer_method(
+                tokenizer,
+                prompt=rendered_prompt,
+                image_file=str(image_path),
+                output_path=output_dir,
+                base_size=self.base_size,
+                image_size=self.image_size,
+                crop_mode=self.crop_mode,
+                save_results=False,
+                eval_mode=True,
+            )
+        if not isinstance(text, str):
+            raise ProviderError("DeepSeek-OCR-2 returned no OCR text.")
+        return build_ocr_result(
+            text,
+            provider_name=self.provider_name,
+            model_name=self.model_name or self.model_id,
+            text_postprocessor=self.text_postprocessor,
+        )
+
+    def _ocr_sync(self, page: DocumentPage) -> OCRResult:
+        prepared_page = preprocess_backend_page(
+            page,
+            image_preprocessor=self.image_preprocessor,
+        )
+        runtime = self._load_runtime()
+        tokenizer = self._get_processor(runtime)
+        model = self._get_model(runtime)
+        return self._infer_deepseek_page(
+            tokenizer=tokenizer,
+            model=model,
+            page=prepared_page,
+            batch_size=1,
+        )
+
+    def _ocr_batch_sync(self, pages: list[DocumentPage]) -> list[OCRResult]:
+        if not pages:
+            return []
+
+        runtime = self._load_runtime()
+        tokenizer = self._get_processor(runtime)
+        model = self._get_model(runtime)
+        results: list[OCRResult] = []
+        for page in pages:
+            prepared_page = preprocess_backend_page(
+                page,
+                image_preprocessor=self.image_preprocessor,
+            )
+            results.append(
+                self._infer_deepseek_page(
+                    tokenizer=tokenizer,
+                    model=model,
+                    page=prepared_page,
+                    batch_size=len(pages),
+                )
+            )
+        return results
+
+
 @dataclass(slots=True)
 class DotsOCR15OCRBackend(HuggingFaceVisionOCRBackend):
     """Preset OCR backend for ``kristaller486/dots.ocr-1.5``.
@@ -1024,6 +1214,7 @@ def _ocr_batch_sync(self, pages: list[DocumentPage]) -> list[OCRResult]:
 __all__ = [
     "ChandraOCR2OCRBackend",
     "Churro3BOCRBackend",
+    "DeepSeekOCR2OCRBackend",
     "DotsMOCROCRBackend",
     "DotsOCR15OCRBackend",
     "HuggingFaceVisionOCRBackend",
diff --git a/src/churro_ocr/providers/specs.py b/src/churro_ocr/providers/specs.py
index 27f64b4..cc6fec8 100644
--- a/src/churro_ocr/providers/specs.py
+++ b/src/churro_ocr/providers/specs.py
@@ -23,6 +23,9 @@
     CHANDRA_OCR_2_OCR_TEMPLATE,
     CHURRO_3B_MODEL_ID,
     CHURRO_3B_XML_TEMPLATE,
+    DEEPSEEK_OCR_2_MODEL_ID,
+    DEEPSEEK_OCR_2_OCR_PROMPT,
+    DEEPSEEK_OCR_2_OCR_TEMPLATE,
     DEFAULT_OCR_TEMPLATE,
     DOTS_MOCR_MODEL_ID,
     DOTS_MOCR_OCR_TEMPLATE,
@@ -52,6 +55,7 @@
 VisionInputBuilder = Callable[[OCRConversation], object]
 DEFAULT_OCR_MAX_TOKENS = 20_000
 CHANDRA_OCR_MAX_TOKENS = 12_384
+DEEPSEEK_OCR_2_MAX_TOKENS = 8_192
 OLMOCR_MAX_TOKENS = 8_000
 PADDLEOCR_VL_MAX_TOKENS = 4_096
 CHANDRA_MAX_IMAGE_SIZE = (3_072, 2_048)
@@ -116,8 +120,17 @@ def default_ocr_text_postprocessor(text: str) -> str:
     "<user>",
     "<system>",
     "<|assistant|>",
+    "<|assistant|>:",
     "<|user|>",
+    "<|user|>:",
     "<|system|>",
+    "<|system|>:",
+    "<｜assistant｜>",
+    "<｜assistant｜>:",
+    "<｜user｜>",
+    "<｜user｜>:",
+    "<｜system｜>",
+    "<｜system｜>:",
 }
 
 
@@ -178,6 +191,22 @@ def lfm2_5_vl_text_postprocessor(text: str) -> str:
     return strip_ocr_output_tag(cleaned, output_tag=DEFAULT_OCR_OUTPUT_TAG)
 
 
+def deepseek_ocr_2_text_postprocessor(text: str) -> str:
+    """Strip DeepSeek OCR 2 prompt echoes, chat scaffold, and trailing stop tokens."""
+    cleaned = text.strip()
+    stop_token = "<｜end▁of▁sentence｜>"
+    while cleaned.endswith(stop_token):
+        cleaned = cleaned[: -len(stop_token)].rstrip()
+    cleaned = _strip_leading_chat_scaffold(
+        cleaned,
+        prompts=[
+            f"<image>\n{DEEPSEEK_OCR_2_OCR_PROMPT}",
+            DEEPSEEK_OCR_2_OCR_PROMPT,
+        ],
+    )
+    return cleaned.strip()
+
+
 def paddleocr_vl_text_postprocessor(text: str) -> str:
     """Strip PaddleOCR-VL prompt echoes and leading chat scaffold from OCR output."""
     return _strip_leading_chat_scaffold(text, prompts=[PADDLEOCR_VL_1_5_OCR_PROMPT])
@@ -395,6 +424,32 @@ def chandra_ocr_2_profile() -> OCRModelProfile:
     )
 
 
+def deepseek_ocr_2_profile() -> OCRModelProfile:
+    """Return the built-in ``deepseek-ai/DeepSeek-OCR-2`` OCR profile."""
+    return OCRModelProfile(
+        profile_name=DEEPSEEK_OCR_2_MODEL_ID,
+        template=DEEPSEEK_OCR_2_OCR_TEMPLATE,
+        text_postprocessor=deepseek_ocr_2_text_postprocessor,
+        display_name="DeepSeek-OCR-2",
+        transport=LiteLLMTransportConfig(
+            completion_kwargs={
+                "max_tokens": DEEPSEEK_OCR_2_MAX_TOKENS,
+                "temperature": 0.0,
+            }
+        ),
+        huggingface=HuggingFaceOptions(
+            model_kwargs={
+                "use_safetensors": True,
+            },
+            generation_kwargs={
+                "max_new_tokens": DEEPSEEK_OCR_2_MAX_TOKENS,
+            },
+            trust_remote_code=True,
+            backend_variant="deepseek-ocr-2",
+        ),
+    )
+
+
 def dots_ocr_1_5_profile() -> OCRModelProfile:
     """Return the built-in ``kristaller486/dots.ocr-1.5`` OCR profile.
 
@@ -522,6 +577,7 @@ def _profile_registry() -> dict[str, OCRModelProfile]:
     default_profile = default_ocr_profile()
     churro_profile = churro_3b_profile()
     chandra_profile = chandra_ocr_2_profile()
+    deepseek_profile = deepseek_ocr_2_profile()
     dots_mocr = dots_mocr_profile()
     dots_profile = dots_ocr_1_5_profile()
     lfm2_5_vl_profile = lfm2_5_vl_1_6b_profile()
@@ -532,6 +588,7 @@ def _profile_registry() -> dict[str, OCRModelProfile]:
         default_profile.profile_name: default_profile,
         churro_profile.profile_name: churro_profile,
         chandra_profile.profile_name: chandra_profile,
+        deepseek_profile.profile_name: deepseek_profile,
         dots_mocr.profile_name: dots_mocr,
         dots_profile.profile_name: dots_profile,
         lfm2_5_vl_profile.profile_name: lfm2_5_vl_profile,
@@ -574,6 +631,8 @@ def resolve_ocr_profile(
     "chandra_image_preprocessor",
     "chandra_ocr_2_profile",
     "chandra_text_postprocessor",
+    "deepseek_ocr_2_profile",
+    "deepseek_ocr_2_text_postprocessor",
     "default_ocr_image_preprocessor",
     "default_ocr_profile",
     "default_ocr_text_postprocessor",
diff --git a/src/churro_ocr/templates/__init__.py b/src/churro_ocr/templates/__init__.py
index b9e9e18..755da05 100644
--- a/src/churro_ocr/templates/__init__.py
+++ b/src/churro_ocr/templates/__init__.py
@@ -13,6 +13,9 @@
     CHANDRA_OCR_2_OCR_TEMPLATE,
     CHURRO_3B_MODEL_ID,
     CHURRO_3B_XML_TEMPLATE,
+    DEEPSEEK_OCR_2_MODEL_ID,
+    DEEPSEEK_OCR_2_OCR_PROMPT,
+    DEEPSEEK_OCR_2_OCR_TEMPLATE,
     DEFAULT_OCR_TEMPLATE,
     DOTS_MOCR_MODEL_ID,
     DOTS_MOCR_OCR_PROMPT,
@@ -36,6 +39,9 @@
     "CHURRO_3B_XML_TEMPLATE",
     "CHANDRA_OCR_2_MODEL_ID",
     "CHANDRA_OCR_2_OCR_TEMPLATE",
+    "DEEPSEEK_OCR_2_MODEL_ID",
+    "DEEPSEEK_OCR_2_OCR_PROMPT",
+    "DEEPSEEK_OCR_2_OCR_TEMPLATE",
     "DEFAULT_OCR_TEMPLATE",
     "DOTS_MOCR_MODEL_ID",
     "DOTS_MOCR_OCR_PROMPT",
diff --git a/src/churro_ocr/templates/presets.py b/src/churro_ocr/templates/presets.py
index 300a65f..6e31226 100644
--- a/src/churro_ocr/templates/presets.py
+++ b/src/churro_ocr/templates/presets.py
@@ -12,6 +12,7 @@
 
 CHURRO_3B_MODEL_ID = "stanford-oval/churro-3B"
 CHANDRA_OCR_2_MODEL_ID = "datalab-to/chandra-ocr-2"
+DEEPSEEK_OCR_2_MODEL_ID = "deepseek-ai/DeepSeek-OCR-2"
 DOTS_OCR_1_5_MODEL_ID = "kristaller486/dots.ocr-1.5"
 DOTS_MOCR_MODEL_ID = "rednote-hilab/dots.mocr"
 PADDLEOCR_VL_1_5_MODEL_ID = "PaddlePaddle/PaddleOCR-VL-1.5"
@@ -31,6 +32,11 @@
     system_message=None,
     user_prompt=CHANDRA_OCR_LAYOUT_PROMPT,
 )
+DEEPSEEK_OCR_2_OCR_PROMPT = "Free OCR."
+DEEPSEEK_OCR_2_OCR_TEMPLATE = HFChatTemplate(
+    system_message=None,
+    user_prompt=DEEPSEEK_OCR_2_OCR_PROMPT,
+)
 DOTS_OCR_1_5_OCR_PROMPT = "Extract the text content from this image."
 DOTS_OCR_1_5_OCR_TEMPLATE = HFChatTemplate(
     system_message=None,
@@ -62,6 +68,9 @@
     "CHURRO_3B_XML_TEMPLATE",
     "CHANDRA_OCR_2_MODEL_ID",
     "CHANDRA_OCR_2_OCR_TEMPLATE",
+    "DEEPSEEK_OCR_2_MODEL_ID",
+    "DEEPSEEK_OCR_2_OCR_PROMPT",
+    "DEEPSEEK_OCR_2_OCR_TEMPLATE",
     "DEFAULT_OCR_TEMPLATE",
     "DOTS_MOCR_MODEL_ID",
     "DOTS_MOCR_OCR_PROMPT",
diff --git a/tests/test_cli.py b/tests/test_cli.py
index 875b8ad..c564195 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -20,6 +20,8 @@
 from churro_ocr.templates import (
     CHANDRA_OCR_2_MODEL_ID,
     CHANDRA_OCR_2_OCR_TEMPLATE,
+    DEEPSEEK_OCR_2_MODEL_ID,
+    DEEPSEEK_OCR_2_OCR_TEMPLATE,
     DEFAULT_OCR_TEMPLATE,
     DOTS_MOCR_OCR_TEMPLATE,
     DOTS_OCR_1_5_OCR_TEMPLATE,
@@ -252,6 +254,47 @@ def test_build_ocr_backend_aligns_templates_for_dots_mocr() -> None:
     }
 
 
+def test_build_ocr_backend_aligns_templates_for_deepseek_ocr_2() -> None:
+    litellm_backend = cli_module._build_ocr_backend(
+        backend="litellm",
+        model=DEEPSEEK_OCR_2_MODEL_ID,
+        endpoint=None,
+        api_key=None,
+        base_url=None,
+        api_version=None,
+    )
+    hf_backend = cli_module._build_ocr_backend(
+        backend="hf",
+        model=DEEPSEEK_OCR_2_MODEL_ID,
+        endpoint=None,
+        api_key=None,
+        base_url=None,
+        api_version=None,
+    )
+    openai_backend = cli_module._build_ocr_backend(
+        backend="openai-compatible",
+        model=DEEPSEEK_OCR_2_MODEL_ID,
+        endpoint=None,
+        api_key=None,
+        base_url="http://127.0.0.1:8000/v1",
+        api_version=None,
+    )
+
+    assert litellm_backend.template == DEEPSEEK_OCR_2_OCR_TEMPLATE
+    assert litellm_backend.template == hf_backend.template == openai_backend.template
+    assert litellm_backend.model_name == "DeepSeek-OCR-2"
+    assert hf_backend.model_name == "DeepSeek-OCR-2"
+    assert openai_backend.model_name == "DeepSeek-OCR-2"
+    assert litellm_backend.transport.config.completion_kwargs == {
+        "max_tokens": 8_192,
+        "temperature": 0.0,
+    }
+    assert openai_backend.transport.config.completion_kwargs == {
+        "max_tokens": 8_192,
+        "temperature": 0.0,
+    }
+
+
 def test_build_ocr_backend_aligns_templates_for_paddleocr_vl() -> None:
     litellm_backend = cli_module._build_ocr_backend(
         backend="litellm",
diff --git a/tests/test_hf_ocr.py b/tests/test_hf_ocr.py
index 855e0c3..70bdb71 100644
--- a/tests/test_hf_ocr.py
+++ b/tests/test_hf_ocr.py
@@ -23,17 +23,25 @@
 from churro_ocr.providers.hf import (
     ChandraOCR2OCRBackend,
     Churro3BOCRBackend,
+    DeepSeekOCR2OCRBackend,
     DotsMOCROCRBackend,
     DotsOCR15OCRBackend,
     HuggingFaceVisionOCRBackend,
     LFM25VLOCRBackend,
     PaddleOCRVL15OCRBackend,
 )
-from churro_ocr.providers.specs import DEFAULT_OCR_MAX_TOKENS, lfm2_5_vl_text_postprocessor
+from churro_ocr.providers.specs import (
+    DEFAULT_OCR_MAX_TOKENS,
+    deepseek_ocr_2_text_postprocessor,
+    lfm2_5_vl_text_postprocessor,
+)
 from churro_ocr.templates import (
     CHANDRA_OCR_2_MODEL_ID,
     CHANDRA_OCR_2_OCR_TEMPLATE,
     CHURRO_3B_XML_TEMPLATE,
+    DEEPSEEK_OCR_2_MODEL_ID,
+    DEEPSEEK_OCR_2_OCR_PROMPT,
+    DEEPSEEK_OCR_2_OCR_TEMPLATE,
     DOTS_MOCR_MODEL_ID,
     DOTS_MOCR_OCR_PROMPT,
     DOTS_MOCR_OCR_TEMPLATE,
@@ -88,6 +96,16 @@ def test_chandra_template_builds_image_before_prompt() -> None:
     assert conversation[0]["content"][1]["text"] == CHANDRA_OCR_LAYOUT_PROMPT
 
 
+def test_deepseek_ocr_2_template_builds_image_before_prompt() -> None:
+    page = DocumentPage.from_image(Image.new("RGB", (20, 20), color="white"))
+
+    conversation = DEEPSEEK_OCR_2_OCR_TEMPLATE.build_conversation(page)
+
+    assert conversation[0]["role"] == "user"
+    assert conversation[0]["content"][0]["type"] == "image"
+    assert conversation[0]["content"][1]["text"] == DEEPSEEK_OCR_2_OCR_PROMPT
+
+
 def test_parse_olmocr_response_extracts_plain_text_and_metadata() -> None:
     text, metadata = parse_olmocr_response(
         "---\n"
@@ -155,6 +173,15 @@ def test_lfm25_text_postprocessor_strips_role_only_prefix() -> None:
     assert lfm2_5_vl_text_postprocessor("assistant:\nplain text") == "plain text"
 
 
+def test_deepseek_ocr_2_text_postprocessor_strips_prompt_echo_and_stop_token() -> None:
+    assert (
+        deepseek_ocr_2_text_postprocessor(
+            "<image>\nFree OCR.\n<｜Assistant｜>\nplain text<｜end▁of▁sentence｜>"
+        )
+        == "plain text"
+    )
+
+
 def test_build_ocr_backend_uses_chandra_profile_defaults_for_hf() -> None:
     backend = cast(
         "ChandraOCR2OCRBackend",
@@ -175,6 +202,29 @@ def test_build_ocr_backend_uses_chandra_profile_defaults_for_hf() -> None:
     assert backend.image_preprocessor(Image.new("RGB", (5_000, 3_000), color="white")).size == (3_248, 1_932)
 
 
+def test_build_ocr_backend_uses_deepseek_ocr_2_profile_defaults_for_hf() -> None:
+    backend = cast(
+        "DeepSeekOCR2OCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="hf",
+                model=DEEPSEEK_OCR_2_MODEL_ID,
+            )
+        ),
+    )
+
+    assert isinstance(backend, DeepSeekOCR2OCRBackend)
+    assert backend.template == DEEPSEEK_OCR_2_OCR_TEMPLATE
+    assert backend.model_name == "DeepSeek-OCR-2"
+    assert backend.generation_kwargs == {"max_new_tokens": 8_192}
+    assert backend.trust_remote_code is True
+    assert backend.processor_kwargs == {}
+    assert backend.model_kwargs == {"use_safetensors": True}
+    assert backend.base_size == 1_024
+    assert backend.image_size == 768
+    assert backend.crop_mode is True
+
+
 def test_build_ocr_backend_uses_olmocr_profile_defaults_for_hf() -> None:
     backend = cast(
         "HuggingFaceVisionOCRBackend",
@@ -412,6 +462,106 @@ def from_pretrained(model_id: str, **kwargs: object) -> FakeModel:
     assert captured["clean_up_tokenization_spaces"] is False
 
 
+@pytest.mark.asyncio
+async def test_deepseek_ocr_2_huggingface_backend_uses_upstream_infer_contract(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    captured: dict[str, Any] = {}
+
+    class FakeTokenizer:
+        pass
+
+    class FakeTokenizerCls:
+        @staticmethod
+        def from_pretrained(model_id: str, **kwargs: object) -> FakeTokenizer:
+            captured["tokenizer_model_id"] = model_id
+            captured["tokenizer_from_pretrained_kwargs"] = kwargs
+            return FakeTokenizer()
+
+    class FakeModel:
+        def eval(self) -> FakeModel:
+            captured["eval_called"] = True
+            return self
+
+        def cuda(self) -> FakeModel:
+            captured["cuda_called"] = True
+            return self
+
+        def to(self, dtype: object) -> FakeModel:
+            captured["to_dtype"] = dtype
+            return self
+
+        def infer(self, tokenizer: object, **kwargs: object) -> str:
+            captured["infer_tokenizer"] = tokenizer
+            captured["infer_kwargs"] = kwargs
+            image = Image.open(cast("str", kwargs["image_file"]))
+            captured["saved_image_mode"] = image.mode
+            captured["saved_image_size"] = image.size
+            captured["output_dir_exists"] = Path(cast("str", kwargs["output_path"])).exists()
+            return "<image>\nFree OCR.\n<｜Assistant｜>\nDecoded text<｜end▁of▁sentence｜>"
+
+    class FakeModelCls:
+        @staticmethod
+        def from_pretrained(model_id: str, **kwargs: object) -> FakeModel:
+            captured["model_model_id"] = model_id
+            captured["model_from_pretrained_kwargs"] = kwargs
+            return FakeModel()
+
+    monkeypatch.setattr(
+        "churro_ocr.providers.hf._load_hf_auto_model_runtime",
+        lambda: SimpleNamespace(
+            processor_cls=FakeTokenizerCls,
+            model_cls=FakeModelCls,
+            process_vision_info=None,
+        ),
+    )
+    monkeypatch.setattr(
+        "churro_ocr.providers.hf._ensure_deepseek_ocr_2_cuda_runtime",
+        lambda: SimpleNamespace(bfloat16="fake-bfloat16"),
+    )
+
+    backend = cast(
+        "DeepSeekOCR2OCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="hf",
+                model=DEEPSEEK_OCR_2_MODEL_ID,
+            )
+        ),
+    )
+    result = await backend.ocr(
+        DocumentPage.from_image(Image.new("RGBA", (32, 16), color=(255, 255, 255, 255)))
+    )
+
+    assert result.text == "Decoded text"
+    assert result.metadata == {}
+    assert captured["tokenizer_model_id"] == DEEPSEEK_OCR_2_MODEL_ID
+    assert captured["model_model_id"] == DEEPSEEK_OCR_2_MODEL_ID
+    assert captured["tokenizer_from_pretrained_kwargs"] == {"trust_remote_code": True}
+    assert captured["model_from_pretrained_kwargs"] == {
+        "trust_remote_code": True,
+        "use_safetensors": True,
+    }
+    assert captured["eval_called"] is True
+    assert captured["cuda_called"] is True
+    assert captured["to_dtype"] == "fake-bfloat16"
+    assert captured["infer_tokenizer"].__class__ is FakeTokenizer
+    infer_kwargs = cast("dict[str, object]", captured["infer_kwargs"])
+    assert infer_kwargs == {
+        "prompt": "<image>\nFree OCR.",
+        "image_file": infer_kwargs["image_file"],
+        "output_path": infer_kwargs["output_path"],
+        "base_size": 1_024,
+        "image_size": 768,
+        "crop_mode": True,
+        "save_results": False,
+        "eval_mode": True,
+    }
+    assert captured["saved_image_mode"] == "RGB"
+    assert captured["saved_image_size"] == (32, 16)
+    assert captured["output_dir_exists"] is True
+
+
 @pytest.mark.asyncio
 async def test_lfm25_huggingface_backend_uses_tokenized_chat_template_and_ties_lm_head(
     monkeypatch: pytest.MonkeyPatch,
@@ -1002,6 +1152,21 @@ def test_dots_ocr_15_backend_uses_expected_defaults() -> None:
     assert backend.generation_kwargs == {"max_new_tokens": DEFAULT_OCR_MAX_TOKENS}
 
 
+def test_deepseek_ocr_2_backend_uses_expected_defaults() -> None:
+    backend = DeepSeekOCR2OCRBackend()
+
+    assert backend.model_id == DEEPSEEK_OCR_2_MODEL_ID
+    assert backend.template == DEEPSEEK_OCR_2_OCR_TEMPLATE
+    assert backend.model_name == "DeepSeek-OCR-2"
+    assert backend.trust_remote_code is True
+    assert backend.processor_kwargs == {}
+    assert backend.model_kwargs == {"use_safetensors": True}
+    assert backend.generation_kwargs == {"max_new_tokens": 8_192}
+    assert backend.base_size == 1_024
+    assert backend.image_size == 768
+    assert backend.crop_mode is True
+
+
 def test_dots_mocr_backend_uses_expected_defaults() -> None:
     backend = DotsMOCROCRBackend()
 
diff --git a/tests/test_providers.py b/tests/test_providers.py
index c123543..c7c9828 100644
--- a/tests/test_providers.py
+++ b/tests/test_providers.py
@@ -48,6 +48,9 @@
 from churro_ocr.templates import (
     CHANDRA_OCR_2_MODEL_ID,
     CHANDRA_OCR_2_OCR_TEMPLATE,
+    DEEPSEEK_OCR_2_MODEL_ID,
+    DEEPSEEK_OCR_2_OCR_PROMPT,
+    DEEPSEEK_OCR_2_OCR_TEMPLATE,
     DEFAULT_OCR_TEMPLATE,
     DOTS_MOCR_OCR_TEMPLATE,
     OLMOCR_2_7B_1025_FP8_MODEL_ID,
@@ -815,6 +818,87 @@ def test_build_ocr_backend_uses_dots_mocr_profile_defaults_for_openai_compatible
     }
 
 
+def test_build_ocr_backend_uses_deepseek_ocr_2_profile_defaults_for_openai_compatible() -> None:
+    backend = cast(
+        "OpenAICompatibleOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="openai-compatible",
+                model=DEEPSEEK_OCR_2_MODEL_ID,
+                transport=LiteLLMTransportConfig(api_base="http://127.0.0.1:8000/v1"),
+            )
+        ),
+    )
+
+    assert backend.template == DEEPSEEK_OCR_2_OCR_TEMPLATE
+    assert backend.model_name == "DeepSeek-OCR-2"
+    assert backend.transport.config.completion_kwargs == {
+        "max_tokens": 8_192,
+        "temperature": 0.0,
+    }
+
+
+@pytest.mark.asyncio
+async def test_openai_compatible_backend_uses_deepseek_ocr_2_prompt_and_postprocessing(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    captured: dict[str, object] = {}
+
+    def _fake_prepare_messages_from_conversation(
+        self: LiteLLMTransport,
+        conversation: list[dict[str, object]],
+    ) -> list[dict[str, object]]:
+        captured["conversation"] = conversation
+        captured["completion_kwargs"] = dict(self.config.completion_kwargs)
+        return conversation
+
+    async def _fake_complete_text(
+        self: LiteLLMTransport,
+        *,
+        model: str,
+        messages: list[dict[str, object]],
+        timeout_seconds: int = 600,
+        output_json: bool = False,
+        allow_empty: bool = False,
+    ) -> str:
+        captured["model"] = model
+        captured["messages"] = messages
+        captured["timeout_seconds"] = timeout_seconds
+        captured["output_json"] = output_json
+        captured["allow_empty"] = allow_empty
+        return "<image>\nFree OCR.\n<｜Assistant｜>\nDecoded text<｜end▁of▁sentence｜>"
+
+    monkeypatch.setattr(
+        "churro_ocr._internal.litellm.LiteLLMTransport.prepare_messages_from_conversation",
+        _fake_prepare_messages_from_conversation,
+    )
+    monkeypatch.setattr("churro_ocr._internal.litellm.LiteLLMTransport.complete_text", _fake_complete_text)
+
+    backend = cast(
+        "OpenAICompatibleOCRBackend",
+        build_ocr_backend(
+            OCRBackendSpec(
+                provider="openai-compatible",
+                model=DEEPSEEK_OCR_2_MODEL_ID,
+                transport=LiteLLMTransportConfig(api_base="http://127.0.0.1:8000/v1"),
+            )
+        ),
+    )
+    result = await backend.ocr(DocumentPage.from_image(Image.new("RGB", (10, 10), color="white")))
+
+    assert result.text == "Decoded text"
+    assert result.model_name == "DeepSeek-OCR-2"
+    assert captured["model"] == f"openai/{DEEPSEEK_OCR_2_MODEL_ID}"
+    assert captured["completion_kwargs"] == {
+        "max_tokens": 8_192,
+        "temperature": 0.0,
+    }
+    conversation = cast("list[dict[str, object]]", captured["conversation"])
+    content = cast("list[dict[str, object]]", conversation[0]["content"])
+    assert content[0]["type"] == "image"
+    assert content[1] == {"type": "text", "text": DEEPSEEK_OCR_2_OCR_PROMPT}
+
+
 @pytest.mark.asyncio
 async def test_openai_compatible_backend_uses_olmocr_prompt_and_plain_text_postprocessing(
     monkeypatch: pytest.MonkeyPatch,
diff --git a/tests/test_tooling_benchmark.py b/tests/test_tooling_benchmark.py
index c5817b5..98bd750 100644
--- a/tests/test_tooling_benchmark.py
+++ b/tests/test_tooling_benchmark.py
@@ -14,6 +14,7 @@
 from churro_ocr.providers.specs import DEFAULT_OCR_MAX_TOKENS
 from churro_ocr.templates import (
     CHURRO_3B_XML_TEMPLATE,
+    DEEPSEEK_OCR_2_OCR_TEMPLATE,
     DOTS_MOCR_OCR_TEMPLATE,
     DOTS_OCR_1_5_OCR_TEMPLATE,
     PADDLEOCR_VL_1_5_OCR_TEMPLATE,
@@ -321,6 +322,51 @@ def test_build_ocr_backend_uses_dots_mocr_preset_for_openai_compatible() -> None
     }
 
 
+def test_build_ocr_backend_uses_deepseek_ocr_2_preset_for_hf() -> None:
+    backend = cast(
+        "HuggingFaceVisionOCRBackend",
+        benchmark._build_ocr_backend(
+            benchmark.BenchmarkOptions(
+                backend="hf",
+                dataset_split="dev",
+                model="deepseek-ai/DeepSeek-OCR-2",
+            )
+        ),
+    )
+
+    assert backend.model_name == "DeepSeek-OCR-2"
+    assert backend.processor_kwargs == {}
+    assert backend.trust_remote_code is True
+    assert backend.model_kwargs == {
+        "device_map": "auto",
+        "torch_dtype": "auto",
+        "use_safetensors": True,
+    }
+    assert backend.generation_kwargs == {"max_new_tokens": 8_192}
+
+
+def test_build_ocr_backend_uses_deepseek_ocr_2_preset_for_openai_compatible() -> None:
+    backend = cast(
+        "LiteLLMVisionOCRBackend",
+        benchmark._build_ocr_backend(
+            benchmark.BenchmarkOptions(
+                backend="openai-compatible",
+                dataset_split="dev",
+                model="deepseek-ai/DeepSeek-OCR-2",
+                base_url="http://127.0.0.1:8000/v1",
+            )
+        ),
+    )
+
+    assert backend.provider_name == "openai-compatible"
+    assert backend.model_name == "DeepSeek-OCR-2"
+    assert backend.template == DEEPSEEK_OCR_2_OCR_TEMPLATE
+    assert backend.transport.config.completion_kwargs == {
+        "max_tokens": 8_192,
+        "temperature": 0.0,
+    }
+
+
 def test_build_ocr_backend_uses_paddleocr_vl_preset_for_hf() -> None:
     backend = cast(
         "HuggingFaceVisionOCRBackend",

From d4cf2a5e4ef3f6f990cc49516a660b03d5946140 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Tue, 7 Apr 2026 06:25:33 +0000
Subject: [PATCH 27/28] chore(benchmark): add DeepSeek OCR 2 leaderboard result

---
 benchmark_results.json | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/benchmark_results.json b/benchmark_results.json
index dd35a45..037514c 100644
--- a/benchmark_results.json
+++ b/benchmark_results.json
@@ -361,6 +361,15 @@
     "handwritten": 28.3488,
     "total": 39.1984
   },
+  {
+    "modelName": "DeepSeek OCR 2",
+    "modelId": "deepseek-ai/DeepSeek-OCR-2",
+    "modelUrl": "https://huggingface.co/deepseek-ai/DeepSeek-OCR-2",
+    "iconPath": null,
+    "printed": 56.1,
+    "handwritten": 20.0,
+    "total": 36.7
+  },
   {
     "modelName": "Skywork R1V3",
     "modelId": "Skywork/Skywork-R1V3-38B",

From 4086aaa3dd699702dfe22e26f8f66efae5051045 Mon Sep 17 00:00:00 2001
From: Sina <s.j.semnani@gmail.com>
Date: Tue, 7 Apr 2026 06:31:39 +0000
Subject: [PATCH 28/28] feat(providers): add Gemini 3.1 Pro Preview model to
 benchmark results

---
 benchmark_results.json | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/benchmark_results.json b/benchmark_results.json
index 037514c..0ccccbe 100644
--- a/benchmark_results.json
+++ b/benchmark_results.json
@@ -16,6 +16,15 @@
     "printed": 82.6,
     "handwritten": 66.5,
     "total": 73.9
+  },
+   {
+    "modelName": "Gemini 3.1 Pro Preview",
+    "modelId": "gemini-3.1-pro-preview",
+    "modelUrl": "https://ai.google.dev/gemini-api/docs/models",
+    "iconPath": "_static/img/gemini-symbol.png",
+    "printed": 80.3,
+    "handwritten": 68.3,
+    "total": 73.8
   },
   {
     "modelName": "Gemini 3 Pro",