Audio Transcribe

Transcribe audio using OpenAI, with optional speaker diarization when requested. Prefer the bundled CLI for deterministic, repeatable runs.

Workflow

• Collect inputs: audio file path(s), desired response format (text/json/diarized_json), optional language hint, and any known speaker references.

• Verify OPENAI_API_KEY is set. If missing, ask the user to set it locally (do not ask them to paste the key).

• Run the bundled transcribe_diarize.py CLI with sensible defaults (fast text transcription).

• Validate the output: transcription quality, speaker labels, and segment boundaries; iterate with a single targeted change if needed.

• 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 missing, instruct the user to create one in the OpenAI platform UI and export it in their shell.

• Never ask the user to paste the full key in chat.

Skill path (set once)

export CODEX_HOME="${CODEX_HOME:-$HOME/.codex}" export TRANSCRIBE_CLI="$CODEX_HOME/skills/transcribe/scripts/transcribe_diarize.py"

User-scoped skills install under $CODEX_HOME/skills (default: ~/.codex/skills ).

CLI quick start

Single file (fast text default):

python3 "$TRANSCRIBE_CLI"
path/to/audio.wav
--out transcript.txt

Diarization with known speakers (up to 4):

python3 "$TRANSCRIBE_CLI"
meeting.m4a
--model gpt-4o-transcribe-diarize
--known-speaker "Alice=refs/alice.wav"
--known-speaker "Bob=refs/bob.wav"
--response-format diarized_json
--out-dir output/transcribe/meeting

Plain text output (explicit):

python3 "$TRANSCRIBE_CLI"
interview.mp3
--response-format text
--out interview.txt

Reference map

• references/api.md : supported formats, limits, response formats, and known-speaker notes.