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$
USD
I will build custom rag chatbot and ai agent for you using langchain and gpt4
About this Gig
Build a Smart RAG Chatbot & AI Agent for Your Business using LangChain and GPT-4
Are you tired of ChatGPT giving incorrect answers about your business? Do you want a chatbot trained on your own data like PDFs, documents, websites, or databases? You are in the right place.
I am a Full Stack Data Scientist with strong experience in AI, Machine Learning, and LLMs. I build real-world RAG (Retrieval-Augmented Generation) systems and AI agents that deliver accurate, context-aware responses for businesses.
What I Offer:
- Custom RAG Chatbot trained on your data
- AI Agents to automate tasks (email, search, CRM)
- Advanced LangChain pipelines with optimized retrieval
- Memory-enabled chatbot with multi-step reasoning
- Support for GPT-4, Claude, LLaMA, and more
Full Stack Delivery:
- Streamlit or FastAPI interface
- REST API for integration
- Docker-ready deployment
- Clean source code with documentation
Why Choose Me?
I use optimized chunking, hybrid search, query expansion, and re-ranking to ensure your chatbot gives accurate and reliable answers.
- You Get:
- Complete code
- Setup guide
- Video walkthrough
Support after delivery
Message me before ordering for a free consultation and project plan.
Expertise:
Software development
•
Website development
Frameworks:
PyTorch
Data type:
Text
Programming language:
Python
Tools:
TensorFlow
APIs:
OpenAI
Other Data Science & ML Services I Offer
FAQ
Q1: What exactly is RAG and why does my business need it?
RAG stands for Retrieval Augmented Generation. It allows a chatbot to answer questions using YOUR specific data — your PDFs, website, product catalog, manuals or database. Normal ChatGPT doesn't know your business. A RAG chatbot does. Every business that wants accurate AI answers needs RAG.
Q2: What data sources can you connect the chatbot to?
I can connect to PDFs, Word documents, Excel files, websites/URLs, Notion, Google Drive, SQL databases, APIs and more. If your data exists somewhere, I can build a RAG system on top of it.
Q3: Which LLM should I use — GPT-4, Claude or LLaMA?
GPT-4 is best for highest accuracy and general business use. Claude 3.5 is best for very long documents and detailed analysis. LLaMA or DeepSeek is best if you want free or private on-premise deployment. I will recommend the best option for your specific case during free consultation.
