I will build a production ready rag chatbot
AI and ML Engineer , LangChain , RAG , FastAPI , LangGraph
À propos de ce service
ooking for a chatbot that actually knows your data? This gig delivers a full Retrieval-Augmented Generation (RAG) pipeline not a basic wrapper around ChatGPT, but a real system with document ingestion, vector search, and a clean API endpoint your frontend can call.
What you get:
Document ingestion from PDF, TXT, or URL sources
Vector storage with ChromaDB or FAISS (your choice)
LangChain RetrievalQA chain with memory
FastAPI backend with clean REST endpoints
Dockerized and ready to deploy (Render, Railway, AWS)
UI included (Standard & Premium)
Clean GitHub repo with README, .env template, and folder structure
I use production-grade practices: structured logging, Pydantic settings, type hints, and pinned dependencies. This won't be spaghetti code you're afraid to touch.
Frameworks:
Scikit-learn
•
keras
•
Panda
Type de données:
Texte
Langage de programmation:
Python
•
SQL
Outils:
Jupyter Notebook
•
Excel
•
Colab
APIs:
OpenAI
FAQ
Which LLM providers do you support?
I work with OpenAI, Google Gemini, Groq (Llama), and Anthropic Claude. If you have an API key for any provider, I can integrate it. I'll recommend the best fit for your use case and budget.
Can you deploy this to my existing server or cloud account?
Yes — for the Premium package I handle deployment to Render, Railway, AWS EC2, or any Linux VPS. I'll need temporary access credentials, which you can revoke after delivery.
What document types can the chatbot handle?
PDFs, plain text files, Word documents (.docx), web URLs, and CSV files. Need something else? Just ask before ordering.

