feat(core): audio file/URL constructors and representation-aware capability guards

docs/docs/how-to/use-speech-and-audio.md

@@ -0,0 +1,227 @@
+---
+title: "Use Speech and Audio Input"
+description: "Pass audio to instruct() and chat() calls, and check which backends can send it."
+sidebar_label: "Use Speech and Audio"
+# diataxis: how-to
+---
+
+Mellea can send audio alongside your text prompt: pass it to any `instruct()` or `chat()`
+call using the `audio` parameter.
+
+**Prerequisites:** an audio-capable model reachable through an OpenAI-compatible endpoint,
+and an audio file.
+
+> **Backend note:** Only the OpenAI-compatible backends can send audio. `OllamaModelBackend`,
+> `WatsonxAIBackend`, and `LocalHFBackend` raise a `ValueError` rather than silently dropping
+> the clip — see [Backend support](#backend-support) below.
+
+---
+
+## Basic usage
+
+`audio` takes a list of audio blocks. Build one with the constructor that matches your
+source — `from_file` for a path on disk:
+
+```python
+# Requires: mellea
+# Returns: str
+from mellea import start_session
+from mellea.core import AudioBlock
+
+m = start_session("openai", model_id="gpt-audio-1.5")
+
+result = m.instruct(
+    "Transcribe the speech in this clip.",
+    audio=[AudioBlock.from_file("speech.wav")],
+)
+print(str(result))
+# Output will vary — LLM responses depend on model and temperature.
+```
+
+`audio` deliberately does **not** accept bare paths or URLs. Converting them is an
+explicit step, so the type you pass says exactly what will be sent and any read or
+download failure surfaces where you wrote it rather than mid-request.
+
+---
+
+## Choosing a constructor
+
+| Source | Use |
+| ------ | --- |
+| A file on disk | `AudioBlock.from_file(path)` |
+| Bytes in memory | `AudioBlock.from_bytes(data)` |
+| A remote URL, fetched now | `AudioBlock.from_url(url)` |
+| A remote URL, fetched at send time and cached | `AudioUrlBlock(url, format=...)` |
+| Base64 you already have | `AudioBlock(value, format=...)` |
+
+`from_file`, `from_bytes`, and `from_url` all detect the format from the data's magic
+bytes, so a mislabelled file is reported accurately — a WAV named `.mp3` yields
+`format == "wav"`:
+
+```python
+# Requires: mellea
+# Returns: str
+from mellea.core import AudioBlock
+
+clip = AudioBlock.from_file("speech.mp3")
+print(clip.format)  # "mp3"
+```
+
+```python
+# Requires: mellea, requests
+# Returns: AudioBlock
+import requests
+from mellea.core import AudioBlock
+
+wav = requests.get("https://cdn.openai.com/API/docs/audio/alloy.wav").content
+clip = AudioBlock.from_bytes(wav)
+```
+
+Pass `format=` explicitly to skip detection when you already know it, or when the payload
+is not one mellea recognises:
+
+```python
+# Requires: mellea
+# Returns: AudioBlock
+from mellea.core import AudioBlock
+
+clip = AudioBlock.from_file("recording.opus", format="opus")
+```
+
+You can also construct a block from base64 directly. With a data URI the format is read from
+the MIME type; with raw base64 you must supply `format`:
+
+```python
+# Requires: mellea
+# Returns: None
+import base64
+from mellea.core import AudioBlock
+
+with open("speech.wav", "rb") as f:
+    b64 = base64.b64encode(f.read()).decode()
+
+from_data_uri = AudioBlock(f"data:audio/wav;base64,{b64}")  # format inferred
+from_raw = AudioBlock(b64, format="wav")  # format required
+```
+
+### Remote audio
+
+No provider accepts audio by URL — OpenAI Chat Completions has no audio-by-URL content
+part — so Mellea downloads the clip and inlines it for you. There are two ways, differing
+only in *when* the fetch happens.
+
+`AudioBlock.from_url()` downloads immediately, so a bad URL fails at the call site:
+
+```python
+# Requires: mellea
+# Returns: AudioBlock
+from mellea.core import AudioBlock
+
+clip = AudioBlock.from_url("https://example.com/speech.wav")
+print(clip.format)  # detected from the downloaded bytes
+```
+
+`AudioUrlBlock` defers the download to send time and memoizes it per URL, so a clip reused
+across several turns is fetched once:
+
+```python
+# Requires: mellea
+# Returns: str
+from mellea import start_session
+from mellea.core import AudioUrlBlock
+
+m = start_session("openai", model_id="gpt-audio-1.5")
+
+clip = AudioUrlBlock("https://example.com/speech.wav", format="wav")
+result = m.instruct("Transcribe this clip.", audio=[clip])
+print(str(result))
+# Output will vary — LLM responses depend on model and temperature.
+```
+
+Prefer `AudioUrlBlock` when the same URL is used repeatedly; prefer `from_url` when you
+want the failure surfaced eagerly. Downloads are capped at 50 MB with a 30-second
+timeout, and `AudioUrlBlock` requires an explicit `format` because nothing has been
+fetched yet at construction time.
+
+---
+
+## Supported formats
+
+OpenAI Chat Completions accepts only `wav` and `mp3` for audio input. Other
+OpenAI-compatible servers may accept more, so mellea does not restrict the format it sends —
+`flac` and `ogg` are detected and passed through, and an explicit `format=` is always
+honoured. If a server rejects a format, that surfaces as a server-side error.
+
+**Mellea does not transcode audio.** Convert the file yourself (for example with `ffmpeg`),
+or transcribe it to text and pass the transcript as part of your prompt.
+
+Format detection covers `wav`, `mp3`, `flac`, and `ogg`. When the bytes match none of these
+and you did not pass `format=`, construction raises:
+
+```python
+# Requires: mellea
+# Returns: None
+from mellea.core import AudioBlock
+
+try:
+    AudioBlock.from_file("notes.txt")
+except ValueError as e:
+    print(e)
+    # Could not identify the audio format of 'notes.txt'. Pass format explicitly ...
+```
+
+---
+
+## Multi-turn audio with ChatContext
+
+Audio passed to `instruct()` or `chat()` is stored in the
+[`ChatContext`](../reference/glossary.md) turn history, so later calls in the same session
+can refer back to the clip without passing it again:
+
+```python
+# Requires: mellea
+# Returns: None
+from mellea import start_session
+from mellea.core import AudioBlock
+from mellea.stdlib.context import ChatContext
+
+m = start_session("openai", model_id="gpt-audio-1.5", ctx=ChatContext())
+
+# First turn — attach the clip
+r1 = m.instruct("Transcribe this clip.", audio=[AudioBlock.from_file("meeting.wav")])
+print(str(r1))
+
+# Second turn — the clip is still in context
+r2 = m.instruct("Summarise the main point in one sentence.")
+print(str(r2))
+```
+
+> **Cost warning:** the clip is re-sent on the wire on *every* subsequent turn, not just the
+> first. Audio is far larger than text — a few minutes of WAV is megabytes of base64 and
+> thousands of audio tokens — so a long conversation over one clip gets expensive quickly.
+> For extended multi-turn work over the same audio, consider transcribing once and
+> continuing over the transcript.
+
+---
+
+## Backend support
+
+| Backend | Audio support | Notes |
+| ------- | ------------- | ----- |
+| `OpenAIBackend` | ✓ | Requires an audio-capable model |
+| `LiteLLMBackend` | ✓ | Depends on the underlying provider and model |
+| `OllamaModelBackend` | ✗ | Ollama's chat API has no audio input |
+| `WatsonxAIBackend` | ✗ | The chat path carries no audio |
+| `LocalHFBackend` | ✗ | Would require a processor-based audio model |
+
+The ✗ backends raise a `ValueError` when handed audio. This is deliberate: silently dropping
+the clip would send a text-only prompt and produce a confident answer about audio the model
+never received.
+
+> **Full example:** [`docs/examples/audio_text_models/audio_examples.py`](https://github.com/generative-computing/mellea/blob/main/docs/examples/audio_text_models/audio_examples.py)
+> **Serving audio via `m serve`:** [`docs/examples/m_serve/multimodal-audio/`](https://github.com/generative-computing/mellea/tree/main/docs/examples/m_serve/multimodal-audio)
+
+---
+
+**See also:** [Use Images and Vision Models](../how-to/use-images-and-vision.md) |
+[Working with Data](../how-to/working-with-data.md)

docs/sidebars.ts

@@ -53,6 +53,7 @@ const sidebars: SidebarsConfig = {
         'how-to/evaluate-with-llm-as-a-judge',
         'how-to/configure-model-options',
         'how-to/use-images-and-vision',
+        'how-to/use-speech-and-audio',
         'how-to/build-a-rag-pipeline',
         'how-to/safety-guardrails',
         'how-to/refactor-prompts-with-cli',

mellea/backends/litellm.py

@@ -43,6 +43,7 @@
     extract_model_tool_requests,
     get_current_event_loop,
     message_to_openai_message,
+    prefetch_audio_urls,
     send_to_queue,
     should_replay_reasoning,
 )
@@ -359,6 +360,7 @@ async def _generate_from_chat_context_standard(
         system_prompt = model_opts.get(ModelOption.SYSTEM_PROMPT, "")
         if system_prompt != "":
             conversation.append({"role": "system", "content": system_prompt})
+        await prefetch_audio_urls(messages)
         replay_flags = should_replay_reasoning(messages, self._provider)
         conversation.extend(
             [

mellea/backends/openai.py

@@ -46,6 +46,7 @@
     is_vllm_server_with_structured_output,
     message_to_openai_message,
     messages_to_docs,
+    prefetch_audio_urls,
     send_to_queue,
     should_replay_reasoning,
 )
@@ -1007,6 +1008,10 @@ async def _generate_from_chat_context_standard(
 
         conversation: list[dict] = []
 
+        # Resolve any audio URLs off-thread so the sync serializer below hits the cache
+        # instead of blocking the event loop on a download.
+        await prefetch_audio_urls(messages)
+
         system_prompt = model_opts.get(ModelOption.SYSTEM_PROMPT, "")
         if system_prompt != "":
             conversation.append({"role": "system", "content": system_prompt})