{"repo":"denizumutdereli/langchain-multi-agents-boilerplate","free":true,"listed":false,"github":"https://github.com/denizumutdereli/langchain-multi-agents-boilerplate","clone":"git clone https://github.com/denizumutdereli/langchain-multi-agents-boilerplate.git","description":"Boilerplate for multi-LLM agent applications using Langchain v3 with multi-model reasoning capabilities.","language":"TypeScript","stars":14,"topics":["agents","ai","boilerplate","embeddings","groq","langchain","langchain-js","llm","llm-agents","llm-models"],"license":"MIT","category":"ai-agents","readme_excerpt":"Langchain multi-agents boilerplate - Example app Football Analysis AI Platform A comprehensive AI-powered platform for football statistics analysis and real-time insights using LangChain v3, multiple LLM models, and advanced agent orchestration. 🌟 Key Features 1. Multi-Model LLM Integration - OpenAI GPT-4 Turbo : Primary model for complex analysis and reasoning - Groq Mixtral-8x7b : Used for real-time processing and initial query routing - Model Selection Logic : Automatic selection based on task complexity and requirements 📹 Demo GIF 2. Advanced Agent Architecture Supervisor Agent - Orchestrates the entire query processing pipeline - Manages agent delegation and task routing - Handles fallback scenarios and error recovery - Maintains processing state and debugging information Specialized Agents - Analysis Agent : Historical data analysis and statistical comparisons - Realtime Agent : Live scores and current match statistics - Enhancement Agent : Query refinement and context enrichment - Security Agent : Query validation and scope verification 3. RAG (Retrieval Augmented Generation) - Vector store integration for semantic search - Redis-based document storage - Dynamic context retrieval based on query relevance - Automatic document embedding and indexing - Support for multiple document types (team stats, player stats, tournament data) 4. Memory Management - Redis-based Chat History : Persistent conversation storage - Vector Store Memory : Efficient similarity search - Conte","default_branch":null,"files":null,"tree":[],"storefront":"/r/denizumutdereli","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/denizumutdereli/langchain-multi-agents-boilerplate/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}