transcribe

# Audio Transcribe Transcribe audio using OpenAI, with optional speaker diarization when requested. Prefer the bundled CLI for deterministic, repeatable runs. ## Workflow 1. Collect inputs: audio file path(s), desired response format (text/json/diarized_json), optional language hint, and any known speaker references. 2. Verify `OPENAI_API_KEY` is set. If missing, ask the user to set it locally (do not ask them to paste the key). 3. Run the bundled `transcribe_diarize.py` CLI with sensible defaults (fast text transcription). 4. Validate the output: transcription quality, speaker labels, and segment boundaries; iterate with a single targeted change if needed. 5. Save outputs under `output/transcribe/` when working in this repo. ## Decision rules - Default to `gpt-4o-mini-transcribe` with `--response-format text` for fast transcription. - If the user wants speaker labels or diarization, use `--model gpt-4o-transcribe-diarize --response-format diarized_json`. - If audio is longer than ~30 seconds, keep `--chunking-strategy auto`. - Prompting is not supported for `gpt-4o-transcribe-diarize`. ## Output conventions - Use `output/transcribe/<job-id>/` for evaluation runs. - Use `--out-dir` for multiple files to avoid overwriting. ## Dependencies (install if missing) Prefer `uv` for dependency management. ``` uv pip install openai ``` If `uv` is unavailable: ``` python3 -m pip install openai ``` ## Environment - `OPENAI_API_KEY` must be set for live API calls. - If the key is m...