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$
USD
I will build a rag chatbot using langchain and your documents
Muhammad Mahad
About this gig
Looking for an intelligent AI chatbot that understands your documents and provides relevant answers?
I will build a custom RAG (Retrieval-Augmented Generation) chatbot tailored to your business needs, including PDF chatbots, document-based AI assistants, and knowledge-based chatbots.
What I offer:
- Custom AI chatbot development using Python
- RAG pipelines and document-based question answering
- LLM integration (OpenAI, Gemini, Claude, and more)
- LangChain and embedding model integration
- Vector databases: ChromaDB, FAISS, and more
- Semantic search and hybrid retrieval (BM25 + vector search)
- Document processing, chunking, and retrieval
- FastAPI backend and API integration
Why work with me?
- Customized AI solutions
- Clean and maintainable code
- Relevant document retrieval and responses
- Source code and deployment support
Let's build an intelligent AI chatbot that makes your data accessible and useful.
Contact me before ordering to discuss your requirements.
Get to know Muhammad Mahad
Muhammad Mahad
AI Engineer, Machine Learning, RAG Chatbots and LLM Applications
- FromPakistan
- Member sinceNov 2023
- Avg. response time1 hour
Languages
Urdu, English, Hindi
I am an AI/ML Engineer specializing in RAG chatbots, Generative AI, LLM applications, and Machine Learning. I build intelligent AI assistants and document-based chatbots using Python, LangChain, LangGraph, Hugging Face, and ChromaDB. My skills include semantic search, hybrid retrieval, prompt engineering, and LLM integration. I also develop and deploy AI applications using FastAPI and Docker, helping businesses automate workflows with practical, reliable AI solutions.
My Portfolio
FAQ
What do you need to start building my RAG chatbot?
I need your project requirements, documents (PDF, DOCX, TXT, etc.), preferred AI model, and any specific features you want in your chatbot.
Can you build a chatbot that answers questions from PDF documents?
Yes! I can build a PDF-based RAG chatbot that processes your documents, retrieves relevant information, and generates context-aware answers.
Which AI models do you support?
I can integrate models from OpenAI, Google Gemini, Anthropic Claude, DeepSeek, and open-source models, depending on your requirements and API access.
Which vector databases do you work with?
I work with ChromaDB and FAISS for storing and retrieving document embeddings. I can recommend a suitable solution based on your project.
Do you support custom embedding models?
Yes! I can integrate suitable embedding models from Hugging Face and other supported providers to improve semantic search and document retrieval.
Can you integrate the chatbot into my website or application?
Yes! I can develop API-based chatbot backends using Python and FastAPI and help integrate them into your website or application.
Will I receive the complete source code?
Yes! The source code is included in the packages, along with the project files and setup instructions.
Can you build a custom RAG chatbot with hybrid search?
Yes! I can implement semantic search, keyword-based retrieval (BM25), and hybrid search with Reciprocal Rank Fusion (RRF), depending on your project requirements.
