AutoShow automates the processing of audio and video content from various sources, including YouTube videos, playlists, podcast RSS feeds, and local media files. It leverages advanced transcription services and language models (LLMs) to perform transcription, summarization, and chapter generation.
AutoShow can generate diverse content formats including:
- Summaries and Chapters:
- Concise summaries
- Detailed chapter descriptions
- Bullet-point summaries
- Chapter titles with timestamps
- Social Media Posts:
- X (Twitter)
- Creative Content:
- Rap songs
- Rock songs
- Country songs
- Educational and Informative Content:
- Key takeaways
- Comprehension questions
- Frequently asked questions (FAQs)
- Curated quotes
- Blog outlines and drafts
- Support for multiple input types (YouTube links, local video and audio files)
- Integration with various:
- LLMs (ChatGPT, Claude, Gemini)
- Transcription services (Deepgram, Assembly)
- Customizable prompts for generating titles, summaries, chapter titles/descriptions, key takeaways, and questions to test comprehension
- Markdown output with metadata and formatted content
The AutoShow workflow includes the following steps that feed sequentially into each other:
- The user provides a content input (video URL or local file) and front matter is created based on the content's metadata.
- The audio is downloaded (if necessary).
- Transcription is performed using the selected transcription service.
- A customizable prompt is inserted containing instructions for the show notes or other content forms.
- The transcript is processed by the selected LLM service to generate the desired output based on the selected prompts.
.github/setup.sh checks to ensure a .env file exists and Node dependencies are installed. Run the workflow with the setup script in package.json.
npm run setupExample commands for all available options can be found in docs/README.md.
npm run devOpen localhost:4321.
- ✨Hello beautiful human! ✨Jenn Junod host of Teach Jenn Tech & Shit2TalkAbout