Support for inference attachments

Author: piotrekno1

.gitignore

@@ -215,3 +215,5 @@ __marimo__/
 # Streamlit
 .streamlit/secrets.toml
 internal/
+
+.DS_Store

examples/attachments_example.py

@@ -0,0 +1,62 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = ["wildedge-sdk"]
+#
+# [tool.uv.sources]
+# wildedge-sdk = { path = "..", editable = true }
+# ///
+"""
+Attachment upload example. Run with: uv run attachments_example.py
+
+Opt-in raw input/output capture. When `attachments_enabled=True` (and the
+project has the paid feature turned on), the SDK buffers the raw bytes locally,
+writes a reference into the inference event, and uploads the bytes independently
+via a presigned URL — the batch flush never waits on the upload.
+
+Attachments are off by default and must be explicitly enabled. Set WILDEDGE_DSN
+to see real uploads; otherwise the client runs in no-op mode.
+"""
+
+import wildedge
+from wildedge import Attachment
+
+
+# Optional: redact / drop attachments before they are buffered.
+def redact(attachments: list[Attachment]) -> list[Attachment]:
+    return [a for a in attachments if a.content_type != "application/secret"]
+
+
+client = wildedge.init(
+    app_version="1.0.0",
+    attachments_enabled=True,
+    max_attachments_per_inference=5,
+    max_attachment_size_bytes=5 * 1024 * 1024,
+    attachment_storage_strategy="file",  # or "inline" for small blobs
+    attachment_filter=redact,
+)
+
+handle = client.register_model(
+    object(),
+    model_id="doc-classifier-v1",
+    source="local",
+    family="custom",
+)
+
+# Pretend these came from a real inference call.
+image_bytes = b"\xff\xd8\xff\xe0fake-jpeg-bytes"
+answer = "This document is an invoice."
+
+inference_id = handle.track_inference(
+    duration_ms=120,
+    input_modality="image",
+    output_modality="text",
+    attachments=[
+        Attachment(content_type="image/jpeg", role="input", data=image_bytes),
+        Attachment(content_type="text/plain", role="output", data=answer.encode()),
+    ],
+)
+
+print(f"tracked inference {inference_id[:8]}… with 2 attachments")
+
+# Bytes upload in the background; flush/close lets buffered events drain.
+client.close()