jefferyhcool/bilinote

AI 视频笔记生成工具 让 AI 为你的视频做笔记

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Summary Information

Updated 23 minutes ago
Added to GitGenius on September 9th, 2026
Created on April 13th, 2025
Open Issues & Pull Requests: 183 (+0)
GitHub issues: Enabled
Number of forks: 940
Total Stargazers: 7,276 (+0)
Total Subscribers: 33 (+0)

Repository Insights (GitGenius)

Median issue/PR response: N/A
Mean response time: 2.4 days
90th percentile: 12.0 hours
Tracked items: 212

Most active contributors

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How this project is maintained

Around half of the issues opened in the past year never receive a reply. 100% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 73% of tracked open issues have had no activity in three months, so the open count overstates what is actively being worked. Only 3% of issues opened in the past year have been closed. Three people close 69% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 170
New in 7 days: 1
Closed in 7 days: 0
Avg open age: 304 days
Stale 30+ days: 160
Stale 90+ days: 138

Recent activity

Opened in 7 days: 1
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • bug (125)
  • enhancement (56)

Detailed Description

BiliNote is an AI video note-generation tool that automatically extracts content from video links and produces structured Markdown notes.

The tool solves the problem of manually summarizing video content by accepting links from platforms like Bilibili, YouTube, and Douyin, then using AI to generate organized notes with clear key points. It works by extracting video content and processing it through AI models to produce formatted output that includes screenshots, links back to specific moments in the original video, and AI-powered question-answering capabilities.

Developers should choose this tool if they need to convert video content into written summaries at scale. It suits projects where video documentation needs to be transformed into searchable, referenceable text. The project offers both a hosted cloud version and a self-hosted option; those who prefer not to manage local deployment, dependencies, or model downloads can use the online version, while others can deploy locally using Docker. Desktop clients are available for Windows and macOS.

The project maintains active development with support for multiple AI backends including OpenAI, Deepseek, and Qwen. The codebase uses React for the frontend and FastAPI for the backend, with Docker containerization available. The tool is distributed under an open-source license and provides comprehensive documentation alongside the source code.