[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-2583":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":10,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":24,"hasPages":22,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":26,"readmeContent":27,"aiSummary":28,"trendingCount":16,"starSnapshotCount":16,"syncStatus":29,"lastSyncTime":30,"discoverSource":31},2583,"llm-council","karpathy\u002Fllm-council","karpathy","LLM Council works together to answer your hardest questions","",null,"Python",20605,3861,266,60,0,59,506,1977,321,45,false,"master",true,[],"2026-06-12 02:00:42","# LLM Council\n\n![llmcouncil](header.jpg)\n\nThe idea of this repo is that instead of asking a question to your favorite LLM provider (e.g. OpenAI GPT 5.1, Google Gemini 3.0 Pro, Anthropic Claude Sonnet 4.5, xAI Grok 4, eg.c), you can group them into your \"LLM Council\". This repo is a simple, local web app that essentially looks like ChatGPT except it uses OpenRouter to send your query to multiple LLMs, it then asks them to review and rank each other's work, and finally a Chairman LLM produces the final response.\n\nIn a bit more detail, here is what happens when you submit a query:\n\n1. **Stage 1: First opinions**. The user query is given to all LLMs individually, and the responses are collected. The individual responses are shown in a \"tab view\", so that the user can inspect them all one by one.\n2. **Stage 2: Review**. Each individual LLM is given the responses of the other LLMs. Under the hood, the LLM identities are anonymized so that the LLM can't play favorites when judging their outputs. The LLM is asked to rank them in accuracy and insight.\n3. **Stage 3: Final response**. The designated Chairman of the LLM Council takes all of the model's responses and compiles them into a single final answer that is presented to the user.\n\n## Vibe Code Alert\n\nThis project was 99% vibe coded as a fun Saturday hack because I wanted to explore and evaluate a number of LLMs side by side in the process of [reading books together with LLMs](https:\u002F\u002Fx.com\u002Fkarpathy\u002Fstatus\u002F1990577951671509438). It's nice and useful to see multiple responses side by side, and also the cross-opinions of all LLMs on each other's outputs. I'm not going to support it in any way, it's provided here as is for other people's inspiration and I don't intend to improve it. Code is ephemeral now and libraries are over, ask your LLM to change it in whatever way you like.\n\n## Setup\n\n### 1. Install Dependencies\n\nThe project uses [uv](https:\u002F\u002Fdocs.astral.sh\u002Fuv\u002F) for project management.\n\n**Backend:**\n```bash\nuv sync\n```\n\n**Frontend:**\n```bash\ncd frontend\nnpm install\ncd ..\n```\n\n### 2. Configure API Key\n\nCreate a `.env` file in the project root:\n\n```bash\nOPENROUTER_API_KEY=sk-or-v1-...\n```\n\nGet your API key at [openrouter.ai](https:\u002F\u002Fopenrouter.ai\u002F). Make sure to purchase the credits you need, or sign up for automatic top up.\n\n### 3. Configure Models (Optional)\n\nEdit `backend\u002Fconfig.py` to customize the council:\n\n```python\nCOUNCIL_MODELS = [\n    \"openai\u002Fgpt-5.1\",\n    \"google\u002Fgemini-3-pro-preview\",\n    \"anthropic\u002Fclaude-sonnet-4.5\",\n    \"x-ai\u002Fgrok-4\",\n]\n\nCHAIRMAN_MODEL = \"google\u002Fgemini-3-pro-preview\"\n```\n\n## Running the Application\n\n**Option 1: Use the start script**\n```bash\n.\u002Fstart.sh\n```\n\n**Option 2: Run manually**\n\nTerminal 1 (Backend):\n```bash\nuv run python -m backend.main\n```\n\nTerminal 2 (Frontend):\n```bash\ncd frontend\nnpm run dev\n```\n\nThen open http:\u002F\u002Flocalhost:5173 in your browser.\n\n## Tech Stack\n\n- **Backend:** FastAPI (Python 3.10+), async httpx, OpenRouter API\n- **Frontend:** React + Vite, react-markdown for rendering\n- **Storage:** JSON files in `data\u002Fconversations\u002F`\n- **Package Management:** uv for Python, npm for JavaScript\n","LLM Council 是一个本地Web应用，旨在通过整合多个大型语言模型（如OpenAI GPT 5.1、Google Gemini 3.0 Pro等）来共同回答用户提出的复杂问题。其核心功能包括：首先，将用户的问题发送给每个参与的LLM以获取初步答案；接着，让这些模型匿名评估彼此的答案，并根据准确性和见解进行排名；最后，由指定的“主席”LLM综合所有反馈生成最终答案。该项目使用Python编写后端逻辑，前端基于React构建，利用FastAPI和OpenRouter API实现异步通信。适合需要从不同角度或知识领域获得深入分析与建议的研究人员、学生或是对多模型协同工作感兴趣的开发者探索使用。",2,"2026-06-11 02:50:26","top_language"]