PDF RAG Chatbot with Hybrid Search and Llama 3.1PDF RAG Chatbot with Hybrid Search and Llama 3.1
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Back to feedPost
Aikaksh's avatar
Aikaksh Singh Routela
• Sep 30
PDF RAG Chatbot: Intelligent Document Q&A System
Built a production-ready Retrieval-Augmented Generation (RAG) system that allows users to upload PDF documents and ask complex questions, receiving accurate, context-aware answers instantly.
Engineering Challenges Solved:
Context Retrieval: Implemented a hybrid search system combining BM25 (keyword) and Vector Embeddings (semantic) using ChromaDB to ensure highly relevant document chunks are retrieved before passing them to the LLM.
LLM Integration: Connected the retrieval pipeline to Groq's Llama 3.1 API, achieving sub-second inference times while maintaining high answer relevancy.
Document Processing: Engineered a robust pipeline using pdfplumber to extract text from multi-page PDFs, with chunking and embedding strategies optimized for retrieval accuracy.
Tech Stack: Python, Flask, ChromaDB, Groq API (Llama 3.1), Sentence-Transformers, pdfplumber.
Completed work
AI DevelopmentAI Engineer Data Systems DesignGitPythonStreamlit
Post image
Back to feed
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started