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$
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I will build rag ai chatbot for PDF, documents or knowledge base
Gaurav Sonawane
About this gig
Are you looking to build an AI chatbot that can answer questions from your documents, PDFs, or company knowledge base?
I will build a custom AI chatbot using OpenAI GPT and Retrieval-Augmented Generation (RAG). The chatbot can understand your documents and provide accurate answers based on your data.
This solution is perfect for:
PDF document chatbots
company knowledge assistants
customer support automation
AI assistants for websites or SaaS products
What you will get:
RAG AI chatbot using OpenAI GPT
document processing and embeddings
vector database integration
scalable backend using Python and FastAPI
API integration with your website or application
Technologies:
Python, FastAPI, OpenAI API, LangChain, Vector Databases, PostgreSQL.
Please message me before placing an order so we can discuss your project requirements.
Get to know Gaurav Sonawane
Gaurav Sonawane
Python Backend Developer GenAI Engineer AI Chatbots
- FromIndia
- Member sinceApr 2022
- Last delivery3 weeks
Languages
Hindi, English
🚀 Python Backend Developer | GenAI Engineer
I help businesses build scalable FastAPI backends, REST APIs, AI chatbots, and RAG-powered applications.
✅ FastAPI Backend Development
✅ Custom REST APIs
✅ OpenAI & LangChain Integration
✅ AI Chatbots & Virtual Assistants
✅ PDF & Document Q&A Systems
✅ RAG Applications & Knowledge Bases
My expertise includes Python, FastAPI, OpenAI API, LangChain, PostgreSQL, SQLAlchemy, and Vector Databases.
I focus on clean code, scalable architecture, and production-ready solutions that deliver real business value.
My Portfolio
FAQ
What is a RAG AI chatbot?
What is a RAG AI chatbot?
What type of documents can the chatbot use?
The chatbot can work with many types of data including PDFs, text documents, knowledge bases, website content, or databases. It can answer questions based on the information provided in these sources.
Can the chatbot be integrated into my website or application?
Yes. I can integrate the chatbot into your website, web application, or backend system using APIs. It can also be connected to custom dashboards or internal tools.
