Build a Scalable RAG Chatbot for Private Dataset InteractionsBuild a Scalable RAG Chatbot for Private Dataset Interactions
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
Built a highly scalable Retrieval-Augmented Generation (RAG) chatbot designed to interact with private datasets/PDFs. Unlike standard LLMs, this system minimizes hallucinations by retrieving real-time context from a local knowledge base before generating responses.
Key Features:
Semantic Search: Implemented Vector Embeddings to perform high-speed similarity searches across thousands of document chunks.
Smart Retrieval: Integrated a retrieval pipeline using LangChain to fetch the most relevant context for user queries.
Source Citation: Configured the bot to provide source references from documents, ensuring data transparency and accuracy.
Optimized Performance: Used FAISS/Chromadb for efficient vector storage and retrieval.
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