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chatbot

A production-ready Retrieval-Augmented Generation (RAG) chatbot built with Streamlit, LangChain, Google Gemini, and ChromaDB. Upload PDFs and ask questions — the system retrieves relevant document chunks and answers using Gemini's LLM.

AI-powered decision simulation platform — multi-expert adversarial debate with real-time streaming, structured scoring, and AI-synthesised verdicts. Built for the Swecha Internship Hackathon.

AI-powered open-source repository onboarding assistant that analyzes GitHub repositories and provides onboarding guidance using Gemini and Ollama.

RAG Chatbot using LangChain, FAISS, Gemini and local LLM support.

Fully offline document Q&A system using PyMuPDF4LLM, Ollama, and llama.cpp. Dual LLM backend with pre-commit quality gates.

RAG Chatbot built using LangChain, FAISS, Groq LLM, and Flask. Supports PDF document ingestion and intelligent question answering through Retrieval-Augmented Generation.

AI-powered PDF Chatbot using Retrieval Augmented Generation (RAG), FAISS, and OpenAI APIs.

Local-first RAG chatbot for university documents using PyMuPDF4LLM, FAISS, Groq and Llama.cpp.

Local PDF RAG system using TinyLlama, FAISS, Streamlit, and Sentence Transformers.

Local-First PDF Q&A Assistant built using PyMuPDF4LLM and Llama.cpp. Supports PDF upload, document retrieval, and question answering using a local language model.

Production-ready RAG chatbot built with Streamlit, LangChain, FAISS, and local LLM support. Features document Q&A, PDF processing, and AGPLv3 compliance.

Local PDF Question Answering System using TinyLlama, Llama.cpp, Streamlit, and Retrieval-Augmented Generation (RAG).

Multimodal Retrieval-Augmented Generation (RAG) application built with Streamlit, LangChain and ChromaDB for intelligent document question answering.

A dual-mode RAG (Retrieval-Augmented Generation) chatbot. Mode 1 uses hybrid search (pgvector + BM25) with Ollama for fully local, free LLM inference. Mode 2 uses a lightweight Find-Retrieve-Answer workflow with PyMuPDF4LLM and llama.cpp for structured PDF Q&A with zero embeddings or vector database.

GRAM Connect is a platform that helps citizens identify and apply for eligible government welfare schemes based on their profile, location, income, and category. It provides scheme recommendations, eligibility checking, and awareness of government benefits.

Local Streamlit RAG research assistant for querying uploaded and preloaded documents with Ollama, LangChain, and ChromaDB.

RAG PDF chatbot using Streamlit, LangChain, FAISS, HuggingFace embeddings, and Gemini API.

Local-First Document Q&A with RAG using Ollama — Find-Retrieve-Answer pattern

CineRAG is a Retrieval-Augmented Generation (RAG) application designed to answer cinema-related queries. The platform currently focuses on the Telugu film industry, providing responses based on information stored in a local knowledge repository.

Lightweight local RAG document chatbot with multilingual support (en/hi/te).