Turn speech from audio or video recordings into text using OpenAI. Save transcripts as text or JSON, with optional speaker labels and reference recordings to help identify known speakers in meetings or interviews.
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Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Transcribe audio using OpenAI, with optional speaker diarization when requested. Prefer the bundled CLI for deterministic, repeatable runs.
OPENAI_API_KEY is set. If missing, ask the user to set it locally (do not ask them to paste the key).transcribe_diarize.py CLI with sensible defaults (fast text transcription).output/transcribe/ when working in this repo.gpt-4o-mini-transcribe with --response-format text for fast transcription.--model gpt-4o-transcribe-diarize --response-format diarized_json.--chunking-strategy auto.gpt-4o-transcribe-diarize.output/transcribe/<job-id>/ for evaluation runs.--out-dir for multiple files to avoid overwriting.Prefer uv for dependency management.
uv pip install openai
If uv is unavailable:
python3 -m pip install openai
OPENAI_API_KEY must be set for live API calls.export CODEX_HOME="${CODEX_HOME:-$HOME/.codex}"
export TRANSCRIBE_CLI="$CODEX_HOME/skills/transcribe/scripts/transcribe_diarize.py"
User-scoped skills install under $CODEX_HOME/skills (default: ~/.codex/skills).
Single file (fast text default):
python3 "$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
references/api.md: supported formats, limits, response formats, and known-speaker notes.还没有评价。欢迎分享你的使用感受。
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Support experimental validation of designed proteins through a cloud laboratory. Prepare and optimize sequences, submit tests for binding, expression, thermal stability, or enzyme activity, track experiment progress, and retrieve results through the API.
中文简介正在准备中。当前显示英语简介。
Analyze time series, observations ordered over time, using aeon in Python. Build classification, prediction, and clustering workflows, detect unusual patterns or changes, and compare methods through an interface compatible with scikit-learn.
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Create original generative art with p5.js, using code to produce patterns and motion. Receive a written artistic concept and an interactive HTML viewer with adjustable parameters, reproducible random variations, seed navigation, and PNG downloads.
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Retrieve stock prices, exchange rates, cryptocurrency prices, company financial statements, and economic indicators through the Alpha Vantage API. It also covers historical data, news sentiment, and technical indicators, which summarize price and trading patterns.
中文简介正在准备中。当前显示英语简介。
Design backend systems with clear boundaries between business rules, databases, and external services. Use Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to organize new applications, refactor existing code, and make core logic easier to test.
中文简介正在准备中。当前显示英语简介。
Helps process astronomical data in Python by converting coordinates, units, and time scales, working with FITS observation files, matching object catalogs, and calculating distances using cosmological models.
中文简介正在准备中。当前显示英语简介。