Transcribe audio and video from URLs (YouTube, direct media links) using WhisperKit locally. Optionally analyze transcripts with AI when explicitly requested. Use when users provide URLs to media content and request transcription or speech-to-text conversion.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Local transcription of audio/video content using WhisperKit. Analysis is available on request using OpenAI or local Ollama.
python3 scripts/transcribe.py "https://youtube.com/watch?v=..."
python3 scripts/transcribe.py "https://youtube.com/watch?v=..."
python3 scripts/analyze_transcript.py whisper-transcriptions/video.md
python3 scripts/transcribe.py "https://youtube.com/watch?v=..."
python3 scripts/analyze_transcript.py whisper-transcriptions/video.md --local
# Basic
python3 scripts/transcribe.py "URL"
# Custom output directory
python3 scripts/transcribe.py "URL" --output-dir "/path/to/save"
# Higher accuracy (slower)
python3 scripts/transcribe.py "URL" --model medium
# Without timestamps
python3 scripts/transcribe.py "URL" --no-timestamps
# Custom filename
python3 scripts/transcribe.py "URL" --filename "my-transcription.md"
| Model | Speed | Accuracy | Use Case |
|---|---|---|---|
tiny | Fastest | Lowest | Quick drafts, testing |
base | Fast | Reasonable | Simple content |
small | Balanced | Good | Default - most use cases |
medium | Slower | High | Lectures, important content |
large | Slowest | Highest | Critical accuracy needed |
pip install yt-dlp or brew install yt-dlpScript checks for these and provides install instructions if missing.
Transcriptions save to ./whisper-transcriptions/ as markdown:
# Transcription
**Source:** https://youtube.com/watch?v=example
**Transcribed:** 2025-01-15 14:30:00
**Tool:** WhisperKit
---
[00:00:00.000 --> 00:00:05.000] Welcome to this video...
OpenAI API (default):
python3 scripts/analyze_transcript.py transcript.md
python3 scripts/analyze_transcript.py transcript.md --model gpt-4o
Requires OPENAI_API_KEY environment variable.
Local Ollama:
python3 scripts/analyze_transcript.py transcript.md --local
python3 scripts/analyze_transcript.py transcript.md --local --model mistral
Requires Ollama running (ollama serve).
# Default comprehensive analysis (OpenAI)
python3 scripts/analyze_transcript.py transcript.md
# Use local Ollama
python3 scripts/analyze_transcript.py transcript.md --local
# Specify model
python3 scripts/analyze_transcript.py transcript.md --model gpt-4o
python3 scripts/analyze_transcript.py transcript.md --local --model llama3.2
# Custom analysis prompt
python3 scripts/analyze_transcript.py transcript.md --prompt "List all tools mentioned"
# Custom output location
python3 scripts/analyze_transcript.py transcript.md --output ~/Documents/analysis.md
# Print to stdout instead of saving
python3 scripts/analyze_transcript.py transcript.md --print
--prompt "List all technologies and tools mentioned"
--prompt "What are the main arguments presented?"
--prompt "Extract all statistics and data points"
--prompt "Summarize in 5 bullet points"
--prompt "What questions were asked and how were they answered?"
pip install openai (used for both OpenAI and Ollama)Analysis saves alongside transcript as transcript_name_analysis.md:
# Transcript Analysis
**Source Transcript:** path/to/transcript.md
**Analysis Model:** gpt-4o-mini (OpenAI)
**Tokens Used:** 33,763
---
[Analysis content]
python3 scripts/transcribe.py "https://youtube.com/watch?v=abc123"
python3 scripts/analyze_transcript.py whisper-transcriptions/watch.md
python3 scripts/transcribe.py "https://youtube.com/watch?v=abc123"
python3 scripts/analyze_transcript.py whisper-transcriptions/watch.md --local
python3 scripts/analyze_transcript.py transcript.md --output summary.md
python3 scripts/analyze_transcript.py transcript.md --prompt "List action items" --output actions.md
python3 scripts/analyze_transcript.py transcript.md --prompt "Extract quotes" --output quotes.md
python3 scripts/transcribe.py "URL1"
python3 scripts/transcribe.py "URL2"
python3 scripts/transcribe.py "URL3"
references/troubleshooting.md)references/configuration.md)references/usage-patterns.md)| Script | Purpose |
|---|---|
scripts/transcribe.py | Download and transcribe audio/video from URLs (WhisperKit) |
scripts/analyze_transcript.py | AI analysis of transcript files (OpenAI or Ollama) |
还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问，或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
Comprehensive China A-share stock analysis covering fundamental analysis, technical analysis, policy impact assessment, and market-specific features (T+1 trading, price limits, northbound capital flow). Use when user asks about A股分析, Chinese mainland stocks, Shanghai/Shenzhen listed stocks, or needs analysis considering China market characteristics.
中文简介正在准备中。当前显示原文说明。
Screen and filter A-share stocks based on fundamental metrics, technical indicators, capital flow, and custom criteria. Support multiple screening strategies including value investing, growth investing, momentum trading, and dividend hunting. Use when user wants to find stocks meeting specific criteria like "低PE高ROE股票", "北向资金加仓股", "突破年线的股票".
中文简介正在准备中。当前显示原文说明。
Generate high-converting ad copy for Google Ads, Meta (Facebook/Instagram), LinkedIn, and TikTok. Creates multiple variations with A/B testing in mind. Includes headlines, descriptions, CTAs, and platform-specific formats. Use when creating ads, generating ad variations, or A/B testing ad copy.
中文简介正在准备中。当前显示原文说明。
Add new skills to an existing workflow and update all related documentation. Use when user wants to add skills from GitHub URLs to a workflow (e.g., "add this skill to the workflow", "为工作流添加技能"). Triggers on adding skills to workflows, updating workflow documentation after skill additions.
中文简介正在准备中。当前显示原文说明。
Agile product management, Scrum practices, and team collaboration for iterative product development.
中文简介正在准备中。当前显示原文说明。
Plan and execute effective sprints using Agile methodologies. Define sprint goals, estimate user stories, manage sprint backlog, and facilitate daily standups to maximize team productivity and deliver value incrementally.
中文简介正在准备中。当前显示原文说明。