# Technical Documentation: JimmyLv/BibiGPT-v1 > ℹ️ **Provenance:** Multi-Tier Ingestion · [CodeWiki Reference](https://codewiki.google/github.com/JimmyLv/BibiGPT-v1) ### Overview (`README.md`) > This repo is only for v1 and supports Bilibil and YouTube! # 🤖 BibiGPT: one-Click AI Summary for Audio/Video & Chat with Learning Content [https://bibigpt.co](https://bibigpt.co) 🎉 Effortlessly summarize YouTube and Bilibili videos with our AI-driven Video Summarizer. It also works for Podcasts, Twitter, Meetings, Lectures, Tiktok videos, and more. Discover a more brilliant way to learn with ChatGPT, your best AI-powered study companion! (formerly BiliGPT) "stream-saving artifact & class representative". Alternate address: https://b.jimmylv.cn Browser extension: https://bibigpt.co/extension --- ## 🤖 BibiGPT · AI 音视频内容一键总结 & 对话 [https://bibigpt.co](https://bibigpt.co) 🎉 ChatGPT AI 音视频一键总结，轻松学习哔哩哔哩丨 YouTube 丨本地视频丨本地音频丨播客丨小红书丨抖音丨会议丨讲座丨网页等任意内容。BibiGPT 助力于成为最好的 AI 学习助理，支持免费试用！(原 BiliGPT 省流神器 & AI 课代表)（支持 iOS 快捷指令 & 微信服务号）。 备用地址：https://b.jimmylv.cn 浏览器插件: https://bibigpt.co/extension --- 🎬 This project summarizes YouTube/Bilibili/Twitter/TikTok/Podcast/Lecture/Meeting/... videos or audios for you using AI. 🤯 Inspired by [Nutlope/news-summarizer](https://github.com/Nutlope/news-summarizer) & [zhengbangbo/chat-simplifier](https://github.com/zhengbangbo/chat-simplifier/) & [lxfater/BilibiliSummary](https://github.com/lxfater/BilibiliSummary) [](https://twitter.com/Jimmy_JingLv/status/1630137750572728320?s=20) 🚀 First Launch: [【BibiGPT】AI 自动总结 B 站视频内容，GPT-3 智能提取并总结字幕](https://www.bilibili.com/video/BV1fX4y1Q7Ux/?vd_source=dd5a650b0ad84edd0d54bb18196ecb86) ## How it works This project uses the [AI SDK OpenAI-compatible provider](https://ai-sdk.dev/providers/openai-compatible-providers) with [Vercel Edge functions](https://vercel.com/features/edge-functions) for streaming, plus [Upstash](https://console.upstash.com/) for Redis cache and rate limiting. It fetches the content on a Bilibili video, sends it in a prompt to an OpenAI-compatible API, then streams the response back to the application. ## Saving costs Projects like this can get expensive so in order to save costs if you want to make your own version and share it publicly, I recommend three things: - [x] 1. Implement rate limiting so people can't abuse your site - [x] 2. Implement caching to avoid expensive AI re-generations - [x] 3. Use `text-curie-001` instead of `text-dacinci-003` in the `summarize` edge function ## Running Locally After cloning the repo, go to [OpenAI](https://beta.openai.com/account/api-keys) to make an account and put your API key in a file called `.env`. Then, run the application in the command line and it will be available at `http://localhost:3000`. [specific running procedure is described in this document - Chinese version](./deploy-ch.md) ```bash npm run dev ``` ## Deployment Deploy the example using [Vercel](https://vercel.com?utm_source=github&utm_medium=readme&utm_campaign=vercel-examples) Setup the env variables, by following the `./example.env` file. ## Support Docker https://github.com/JimmyLv/BibiGPT/pull/133 ```shell # make sure setup .env file firstly docker compose up -d ``` ## Support -> Contact Me ## Star History [](https://star-history.com/#JimmyLv/BibiGPT&Date) ## Contributors This project exists thanks to all the people who contribute. --- ### Overview (`.agents/skills/vercel-react-best-practices/README.md`) # React Best Practices A structured repository for creating and maintaining React Best Practices optimized for agents and LLMs. ## Structure - `rules/` - Individual rule files (one per rule) - `_sections.md` - Section metadata (titles, impacts, descriptions) - `_template.md` - Template for creating new rules - `area-description.md` - Individual rule files - `src/` - Build scripts and utilities - `metadata.json` - Document metadata (version, organization, abstract) - **`AGENTS.md`** - Compiled output (generated) - **`test-cases.json`** - Test cases for LLM evaluation (generated) ## Getting Started 1. Install dependencies: ```bash pnpm install ``` 2. Build AGENTS.md from rules: ```bash pnpm build ``` 3. Validate rule files: ```bash pnpm validate ``` 4. Extract test cases: ```bash pnpm extract-tests ``` ## Creating a New Rule 1. Copy `rules/_template.md` to `rules/area-description.md` 2. Choose the appropriate area prefix: - `async-` for Eliminating Waterfalls (Section 1) - `bundle-` for Bundle Size Optimization (Section 2) - `server-` for Server-Side Performance (Section 3) - `client-` for Client-Side Data Fetching (Section 4) - `rerender-` for Re-render Optimization (Section 5) - `rendering-` for Rendering Performance (Section 6) - `js-` for JavaScript Performance (Section 7) - `advanced-` for Advanced Patterns (Section 8) 3. Fill in the frontmatter and content 4. Ensure you have clear examples with explanations 5. Run `pnpm build` to regenerate AGENTS.md and test-cases.json ## Rule File Structure Each rule file should follow this structure: ````markdown --- title: Rule Title Here impact: MEDIUM impactDescription: Optional description tags: tag1, tag2, tag3 --- ## Rule Title Here Brief explanation of the rule and why it matters. **Incorrect (description of what's wrong):** ```typescript // Bad code example ``` ```` **Correct (description of what's right):** ```typescript // Good code example ``` Optional explanatory text after examples. Reference: [Link](https://example.com) ## File Naming Convention - Files starting with `_` are special (excluded from build) - Rule files: `area-description.md` (e.g., `async-parallel.md`) - Section is automatically inferred from filename prefix - Rules are sorted alphabetically by title within each section - IDs (e.g., 1.1, 1.2) are auto-generated during build ## Impact Levels - `CRITICAL` - Highest priority, major performance gains - `HIGH` - Significant performance improvements - `MEDIUM-HIGH` - Moderate-high gains - `MEDIUM` - Moderate performance improvements - `LOW-MEDIUM` - Low-medium gains - `LOW` - Incremental improvements ## Scripts - `pnpm build` - Compile rules into AGENTS.md - `pnpm validate` - Validate all rule files - `pnpm extract-tests` - Extract test cases for LLM evaluation - `pnpm dev` - Build and validate ## Contributing When adding or modifying rules: 1. Use the correct filename prefix for your section 2. Follow the `_template.md` structure 3. Include clear bad/good examples with explanations 4. Add appropriate tags 5. Run `pnpm build` to regenerate AGENTS.md and test-cases.json 6. Rules are automatically sorted by title - no need to manage numbers! ## Acknowledgments Originally created by [@shuding](https://x.com/shuding) at [Vercel](https://vercel.com). --- --- METRICS --- - Files Extracted: 2 - Estimated Token Budget: ~1711 tokens - Canonical Reference: https://codewiki.google/github.com/JimmyLv/BibiGPT-v1