I will create rag advance rag agents with llm evaluations

Are you looking for a production-ready, high-precision Retrieval-Augmented Generation (RAG) system that delivers accurate results without hallucinations?

I specialize in architecting advanced AI systems, agentic workflows, and self-correcting RAG pipelines using cutting-edge frameworks like LangChain, LangGraph, and FastAPI.

What I Offer

• Standard RAG Setup: Custom vector database integration, optimized document chunking, and efficient context retrieval.
• Advanced & Agentic RAG: Implementation of CRAG (Corrective RAG), Self-RAG, and Graph RAG for multi-step reasoning, dynamic query routing, and automated self-correction.
• Tooling & MCP Integration: Connecting your LLM to pre-built tools and custom Model Context Protocol (MCP) servers for external API calls and sandbox execution.
• LLM Evaluation & Tracing: Automated evaluation pipelines to continuously monitor response precision and minimize hallucinations.

Tech Stack

• Frameworks: LangGraph, LangChain, FastAPI
• Databases: Supabase, FAISS, Pinecone, Qdrant, ChromaDB
• Models: OpenAI (GPT-4o), Anthropic (Claude 3.5), Gemini Open-Source LLMs

Note: Clients must provide their own API keys (e.g., OpenAI, Anthropic) for deployment and testing