I will build a custom rag chatbot using langchain and vector db for your document


Over deze dienst
Tired of manually searching through hundreds of pages to find answers? I'll build a production-ready RAG (Retrieval-Augmented Generation) chatbot that lets you chat with your own documents PDFs, Word files, knowledge bases, or any text data.
What you get:
- Document ingestion pipeline with chunking and embedding
- Vector database setup (Pinecone, Weaviate, or Chroma)
- LLM integration (OpenAI, Claude, or AWS Bedrock)
- FastAPI backend with clean REST endpoints
- Conversational memory for follow-up questions
Why work with me: I'm a Senior GenAI Engineer with 5+ years of Python experience. I've built RAG systems that improved retrieval accuracy by 40% on enterprise-scale datasets. Every delivery is production-grade not just a notebook demo.
My stack: LangChain · LlamaIndex · FastAPI · PostgreSQL · AWS · Docker
Packages at a glance:
- Basic ($75) Single-doc RAG with API endpoint, up to 50 pages
- Standard ($150) Multi-doc RAG + memory + Streamlit UI
- Premium ($300) Full system with RBAC, semantic cache, AWS deployment
Message me before ordering if you have a specific use case happy to confirm it fits before you buy.
Maak kennis met Ganesh Mandape
AI Engineer Python Developer FastAPI Django RAG LangChain MCP OpenAI Claude
- Afkomstig uitIndia
- Lid sindsjun 2026
- Gem. reactietijd1 uur
Talen
Engels, Hindi

