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title: LoL Multi-Agent Coach
emoji: 🎮
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: "6.2.0"
app_file: app.py
pinned: false
license: mit
short_description: AI-powered League of Legends coaching system
---
# League of Legends Multi-Agent Coach 🎮
A sophisticated multi-agent AI coaching system for League of Legends that provides:
- 🎯 Match analysis and performance insights
- 🛠️ Build recommendations with real-time meta data
- 🎬 Video guides and educational content
- 📚 LoL knowledge base with FAISS vector search
- 🎲 Pregame strategy (bans, picks, team comp analysis)
## Features
- **5 Specialized AI Agents** working collaboratively
- **14 Tools** for comprehensive coaching
- **Real-time data** from Riot API, Tavily, and YouTube
- **FAISS Vector Database** for knowledge retrieval
## Setup
This Space requires three API keys to be set as Secrets:
1. **OPENAI_API_KEY** - Get from https://platform.openai.com/
2. **RIOT_API_KEY** - Get from https://developer.riotgames.com/
3. **TAVILY_API_KEY** - Get from https://tavily.com/
Optional: Configure your summoner information:
- **SUMMONER_NAME** - Your League summoner name
- **SUMMONER_TAG** - Your tagline (e.g., NA1)
- **REGION** - Your region (e.g., na1)
## Usage
Simply type your questions in the chat interface:
- "Analyze my last 5 games"
- "What's the best build for Yasuo?"
- "Find Yasuo vs Zed matchup videos"
- "What should I ban if playing mid?"
- "Analyze this team comp: Darius, Lee Sin, Ahri, Jinx, Thresh"
## Technology Stack
- **LangChain/LangGraph** - Multi-agent framework
- **OpenAI GPT-4** - Language model
- **Gradio 6.2.0** - Web interface
- **FAISS** - Vector database (optional, see FAISS_SETUP.md)
- **Riot API** - Live game data
- **Tavily** - Real-time web search
## Note: FAISS Knowledge Base
The FAISS knowledge base is **optional** and provides enhanced LoL knowledge retrieval. If not available, the system will work perfectly using Tavily web search instead. See [FAISS_SETUP.md](./FAISS_SETUP.md) for upload instructions if you want to enable it.
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