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chatbot

EndGame RAGHub is a scalable multimodal Retrieval-Augmented Generation platform supporting document, image, audio, and video understanding using FastAPI, Qdrant, LangGraph, and modern open-source AI infrastructure.

CivicTruth is a Retrieval-Augmented Generation (RAG) platform that enables transparent, citation-backed question answering over legislative and policy documents.

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

A Retrieval-Augmented Generation (RAG) chatbot built with Streamlit, LangChain, FAISS, and sentence-transformers. Upload PDFs and ask questions using Gemini or local Llama.cpp LLMs.

Lightweight local-first RAG chatbot built with Streamlit, Ollama, ChromaDB, SQLite, and local quality checks.

Smart Cab Finder is an AI-powered ride comparison platform that helps users compare fares, estimated arrival times, and ride options across multiple cab providers. The application includes an intelligent AI assistant for ride recommendations, supports Bring Your Own Key (BYOK) integrations, and is designed to support local AI inference through Ollama. To improve accessibility, the platform provides multilingual support in English, Hindi, and Telugu. Built using Python and Flask, the project follows secure development practices with automated testing, CI/CD pipelines, security scanning, and compliance-driven documentation.

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.

Bank Customer Churn Analysis is a data analytics and machine learning project designed to identify customers who are likely to leave a bank's services. Customer churn is a major challenge for banks, as retaining existing customers is more cost-effective than acquiring new ones. This project analyzes customer demographics, account details, transaction behavior, and banking activity to uncover patterns that contribute to customer attrition.

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

AI-powered legal document analyzer for India. Upload any contract or agreement — LegalLens finds hidden clauses, checks against 73 Indian laws, and explains everything in plain language.

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.

StudentAI - AI-powered RAG chatbot for document analysis and question answering using FastAPI, React, Ollama and Retrieval-Augmented Generation (RAG).

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.