Initial commit: llm-router — smart OpenAI/Anthropic/Ollama router

A stdlib pre-router in front of Ollama with LiteLLM backend:
- auto model selection by content/tools/modality, with fallbacks
- OpenAI /v1, Anthropic /v1/messages, and Ollama-native /api/* endpoints
- Whisper-shaped /v1/audio/transcriptions + in-chat audio
- key-based fleet policies (e.g. force a client onto uncensored models)
- optional Bearer auth; launchd/systemd service install
- benchmark harnesses (speed, quality, agentic tool use) with sample results

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

docs/AUDIO.md

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+# Audio / voice
+
+Ollama can *understand* audio with speech-capable models (e.g. Gemma 4 `e4b`/`e2b`/
+`12b`), but only via its **native `/api/chat`** with the audio base64 in the
+`images` field — the OpenAI `input_audio` format is silently dropped, and there's
+no native speech-to-text endpoint. This router bridges that gap.
+
+Set the model with `ROUTER_AUDIO_MODEL` (default `gemma4:e4b`). It must be a model
+whose `ollama show` capabilities include `audio`. **Note:** some fine-tunes/quants
+have broken audio even if the flag is set — test before relying on one.
+
+## Speech-to-text (Whisper-shaped)
+
+```bash
+curl http://<host>:8080/v1/audio/transcriptions \
+  -F file=@recording.wav \
+  -F model=whisper-1
+# -> {"text": "the transcription"}
+```
+- `response_format=text` returns plain text instead of JSON.
+- `/v1/audio/translations` does the same but translates to English.
+- Works with the OpenAI SDK: set `base_url` to the router and call
+  `audio.transcriptions.create(...)`. The `model` field is ignored — the router
+  always uses `ROUTER_AUDIO_MODEL`.
+
+## Audio inside a chat
+
+Send OpenAI `input_audio` content to `/v1/chat/completions` and ask about it:
+```json
+{"model":"auto","messages":[{"role":"user","content":[
+  {"type":"text","text":"answer the question in this audio"},
+  {"type":"input_audio","input_audio":{"data":"<base64-wav>","format":"wav"}}
+]}]}
+```
+The router detects the audio, translates it to Ollama's native call, runs it on
+`ROUTER_AUDIO_MODEL`, and returns a normal OpenAI response (streaming supported).
+
+## Limitations
+
+- **WAV is verified.** Other formats (mp3/m4a/ogg) depend on Ollama's decoding —
+  transcode to WAV if they fail.
+- **Not streaming STT** — it transcribes a complete clip per request (like
+  Whisper's file API), not a live mic stream. Perfect for record-then-send.
+- Audio only works through the router's native bridge, so audio requests always
+  target `ROUTER_AUDIO_MODEL` (they bypass the normal model-selection map).