I will build a custom rag chatbot using langchain, llamaindex, and openai


About this gig
I build production-ready RAG (Retrieval-Augmented Generation) chatbots
that answer questions accurately using your own documents, databases,
or knowledge bases.
Whether you need a customer support bot, internal knowledge assistant,
or document Q&A system I deliver end-to-end pipelines that actually work.
What you get:
Custom RAG pipeline (LangChain / LlamaIndex)
Vector DB integration (Pinecone, ChromaDB, FAISS)
PDF, URL, CSV, database & Notion support
OpenAI, Claude, Mistral or open-source LLM
Voice input/output support (Whisper + TTS)
Clean REST API or Streamlit UI
AWS / Azure / HuggingFace deployment
I have built VoiceRAG a real-time voice-enabled RAG system and
production pipelines tested on financial datasets. I don't just
prototype, I build things that scale.
Tech: Python · LangChain · LlamaIndex · OpenAI · Pinecone ·
FastAPI · Streamlit · Docker · AWS · Azure
Get to know Taha Ahmad
AI System Engineer
- FromPakistan
- Member sinceOct 2023
- Avg. response time2 hours
Languages
English, French, Chinese
My Portfolio
FAQ
Q: What data sources can the chatbot connect to?
PDF, Word docs, CSVs, URLs, SQL databases, Notion, and more — basically any structured or unstructured data you have.
Q: Which LLM will you use?
GPT-4o by default, but I can integrate Claude, Gemini, Mistral, LLaMA, or any open-source model based on your preference or budget.
Q: Will I get the source code?
Yes, full source code with documentation is delivered with every package — no lock-in.
Q: Can you add voice input and output?
Yes, voice support using OpenAI Whisper (speech-to-text) and TTS (text-to-speech) is included in the Premium package.

