1. Project Overview

AI video and text creation assistant

Based on AI large models, one-click conversion of videos and audio into various styles of documents such as small red books, public accounts, knowledge notes, and mind maps

AI video and text creation assistant is a Web tool based on AI large models, one-click conversion of videos and audio into various styles of documents, no need to log in or register, front-end and back-end local deployment, with extremely low cost to experience AI video/audio conversion to style document services, five dollars author developed and tested for a month, just used up

2. Open Source License

Licensed under MIT

3. Screenshots

Project screenshots

Newly designed home page, made a great effort

More concise loading page

Supports AI secondary questioning for video content

Supports generating mind maps

Generated mind maps can be exported to third-party platforms for editing and optimization

4. Feature Overview

✨ Core functions

• Completely open-source
  : MIT license agreement, supports local deployment
• Privacy protection
  : No need to log in or register, task records are saved locally
• Front-end processing
  : Using ffmpeg wasm technology, no need to install ffmpeg locally
• Multi-style support
  : Supports small red books, public accounts, knowledge notes, mind maps, and content summaries, and multiple document styles
• AI dialogue
  : Supports AI secondary questioning for video content
• One-click deployment
  : Supports Docker one-click deployment

Future plans

• Supports intelligent extraction of video key frames, achieving true picture and text
• Audio recognition supports using fast-whisper local large model processing, further reducing costs
• Using React to completely rebuild the front-end page, bringing a more smooth and smooth experience

5. Tech Stack

Processing flow

docker local one-click deployment

1️⃣: Image building:

$ make docker-image

2️⃣: Please complete the variables.env file in the root directory according to the back-end deployment guide and configuration item explanation

3️⃣: Modify the VITE_API_BASE_URL in evn.development to http://0.0.0.0:8080

4️⃣: Run the project

$ make run