document-qa

neel1996/supesquire

Document Q&A chatbot

tmori/generative-agents

This Repositry is an experiment with an agent that searches documents and asks questions repeatedly in response to the main question. It automatically determines the optimal answer from the current documents or recognizes when there is no answer.

hardikjp7/DeepSeek-R1-RAG-for-Document-QA

🐋 DeepSeek-R1: Retrieval-Augmented Generation for Document Q&A 📄

byerlikaya/SmartRAG

⚡ Production-ready .NET Standard 2.1 RAG library with 🤖 multi-AI provider support, 🏢 enterprise vector storage, 📄 intelligent document processing, and 🗄️ multi-database query coordination. 🌍 Cross-platform compatible.

javcanti/ContextAgent

ContextAgent is a production-ready AI assistant backend with RAG, LangChain, and FastAPI. It ingests documents, uses OpenAI embeddings, and stores vectors in ChromaDB 🐙

manhowong/LLM-Chatbot-for-QA

An LLM-powered Slack bot built with Langchain.

chussboi96/RAG-PDF-phi-3-chatbot

RAG chatbot designed for domain-specific queries using Ollama, Langchain, phi-3 and Faiss

dronefreak/local_rag_pipeline

An advanced, fully local, and GPU-accelerated RAG pipeline. Features a sophisticated LLM-based preprocessing engine, state-of-the-art Parent Document Retriever with RAG Fusion, and a modular, Hydra-configurable architecture. Built with LangChain, Ollama, and ChromaDB for 100% private, high-performance document Q&A.

Jaolmos/documentmentor-rag

Sistema RAG (Retrieval Augmented Generation) para asistencia de documentación técnica en español utilizando LangChain, OpenAI Y Streamlit para la interfaz visual

sonwanesuresh95/askdoc-local

⚡️ Local RAG API using FastAPI + LangChain + Ollama | Upload PDFs, DOCX, CSVs, XLSX and ask questions using your own documents — fully offline!

webcodelabb/ContextAgent

AI assistant backend for document-based question answering using RAG (LangChain, OpenAI, FastAPI, ChromaDB). Features modular architecture, multi-tool agents, conversational memory, semantic search, PDF/Docx/Markdown processing, and production-ready deployment with Docker.

AbhishekGadagin/document-qa-system

AI-powered document Q&A system with vector search

Deepak4Siriboyina/smartdoc-assistant

hishamzargar/DocumentAgent

AI agent API (Python/FastAPI) to upload documents (PDF/TXT) and answer questions using RAG with Azure OpenAI and LangChain.

Md-Emon-Hasan/AutoDocThinker

Agentic AI system that allows users to upload documents (PDFs, DOCX, etc.) and natural language questions. It uses LLM-based RAG to extract relevant information. The architecture includes multi-agent components such as document retrievers, summarizers, web searchers, and tool routers — enabling dynamic reasoning and accurate responses.

Pranav-here/Healthcare-Chatbot

Sub-second RAG-based chatbot for medical Q&A over 10+ textbooks with source-cited responses.

sayan-dg/ask-knowledge-base

A Document QA chatbot using LangChain, Pinecone for vector storage, and Amazon Bedrock (mistral.mixtral-8x7b-instruct for LLM and titan-embed-text for embeddings). Built with a Streamlit frontend for document uploads and contextual question answering.

SNEAKO7/commission-dashboard-assistant-RAG-

AI-powered commission plan assistant featuring advanced RAG pipeline, Model Context Protocol (MCP) PostgreSQL server integration, multi-format document processing, and secure SELECT-only database operations. Guided 3-phase plan creation with conversational interface.

Espacio-root/llm-notebooks

This repository acts as an archive of the owners experience working with large language models neatly presented within jupyter notebooks

harimkang/docsense

An intelligent document assistant powered by Open-Source Large Language Models

yash-learnerr/pdf-chat-assistant

Build a powerful PDF Chat Assistant using Node.js, LangChain, and Google Gemini. Upload PDFs, extract content, and interact with them using natural language queries powered by Gemini LLM. Ideal for document Q&A, contract analysis, resume review, and more.

Ashprogrammer29/AI-Powered-PDF-Context-Retrieval-Chatbot-RAG

AI-Powered PDF Context Retrieval Chatbot (RAG) is a smart chatbot that lets you upload PDFs and ask questions about their content. Using advanced AI and semantic search, it finds and summarizes answers directly from your documents—ideal for legal, academic, business, and support tasks.

BrijeshRakhasiya/Generative-AI

A modular Generative AI showcase featuring chatbot agents, RAG pipelines, multi-search agent orchestration, document Q&A, and creative GenAI tools. Built with Streamlit and powered by OpenAI, Gemini, and LangChain, this repo offers hands-on demos for agentic reasoning, retrieval, and multimodal generation.

Danni-Ke/MemoOrb

Personal Book RAG Assistant: A lightweight, RAG-based Q&A system for personal reading notes and documents. Supports multi-format ingestion (.md, .txt, .epub, .pdf, .html, .doc) with conversational memory and citation-based answers.

galezra/ragbox

🔒 Local AI Agent - Offline RAG system for secure document Q&A with no external APIs

Garbii1/personal-data-assistant-chatbot

Create your own Retrieval-Augmented Generation (RAG) chatbot for PDFs. This project uses LangChain, Flask, and an LLM (IBM WatsonX/Hugging Face) to build a conversational AI that understands your documents.

hari7261/Document-Q-A-LLM

A document question-answering system that allows users to upload files (PDFs, DOCs, TXTs) and ask questions about their content using RAG (Retrieval-Augmented Generation) with ChromaDB and Gemma.

JaimeLucena/rag-pdf-python

AI-powered document Q&A using RAG, FastAPI, Streamlit, and OpenAI. Upload PDFs and ask questions about their content.

mateusz29/chat-with-documents

Ask questions and get answers from your PDFs. A RAG system powered by OpenAI, LangChain, and Chroma vector database.

ObinnaOkoye89/car-manual-rag-chatbot

RAG chatbot using car manual data to answer MG ZS warnings via GPT-4o and LangChain.

rmehmood786/genai-knowledge-assistant

🧠 Offline RAG App using LangChain, FAISS, and HuggingFace. A lightweight AI assistant that lets you chat with your own documents without any API costs.

sabry-awad97/ai-knowledge-assistant-python

🤖 Production-ready RAG system with Docker AI local embeddings & Gemini 2.5. Enterprise document Q&A with role-based access, semantic search, and SOLID architecture. FastAPI + PostgreSQL + Weaviate. Free, private, offline-capable.

SayamAlt/Multi-Domain-AI-Chatbot-using-Langchain

Successfully developed a Multi-Domain AI Personal Assistant using LangChain, OpenAI, and Streamlit. The application seamlessly integrates multiple specialized capabilities, including document-based question answering (QA), Python code execution, debugging, explanation and optimization, web search, latest news retrieval, and currency conversion.

shreyashlodhi/ai-research-assistant

An intelligent, domain-specific Medical Assistant Chatbot built with a full-stack Retrieval-Augmented Generation (RAG) pipeline. This application answers complex medical queries by retrieving and synthesizing information directly from trusted PDF documents , ensuring accurate and context-aware responses powered by state-of-the-art LLMs.

Sourav01112/voice-rag-pdf-assistant

Voice-enabled RAG assistant that processes PDFs with Ollama, stores embeddings in ChromaDB, and provides spoken answers via ElevenLabs TTS for hands-free document Q&A