I will a custom rag chatbot with langchain and chromadb

I will build a custom Retrieval-Augmented Generation (RAG) chatbot that can understand your documents, retrieve relevant information, and generate context-aware answers using modern LLM technology.

Im an AI/ML Engineer with hands-on experience building RAG systems using LangChain, ChromaDB, FastAPI, embeddings, vector search, and LLMs.

What I can build

• Chat with PDF / document chatbot
• Custom AI knowledge-base chatbot
• Semantic search systems
• Retrieval-Augmented Generation (RAG)
• Document Q&A systems
• ️ Multiple-document knowledge bases
• LangChain RAG pipelines
• ️ ChromaDB / vector database integration
• FastAPI AI backends
• LLM and API integration
• Dockerized AI applications
• ️ AWS deployment

RAG pipeline can include

Documents Text Extraction Chunking Embeddings Vector Database Retrieval LLM Context-Aware Answer

I can customize the pipeline according to your data, application requirements, and expected user workflow.

Technologies

Python | LangChain | ChromaDB | RAG | LLMs | Embeddings | Vector Search | FastAPI | Docker | AWS

Why work with me?

AI/ML engineering background

Real-world RAG development experience

LangChain + ChromaDB experience

FastAPI backend development

Vector search and embedd