A TypeScript sample app for the Retrieval Augmented Generation pattern running on Azure, using Azure AI Search for retrieval and Azure OpenAI and LangChain large language models (LLMs) to power ChatGPT-style and Q&A experiences.

Q&A based on elasticsearch+langchain+chatglm2 ｜ 基于elasticsearch，langchain，chatglm2的自有知识库问答

A learning project for building local knowledge bases from PDFs using LangChain, supporting multiple LLMs (DeepSeek, OpenAI). Features include PDF processing, knowledge graph construction, and natural language Q&A interface.一个基于 LangChain 的学习项目，用于构建 PDF 本地知识库，支持多种大语言模型（DeepSeek、OpenAI）。功能包括 PDF 处理、知识图谱构建和自然语言问答界面。

AI Q&A Search Engine ➡️ 基于LangChain和SearXNG打造的开源AI搜索引擎

Notebook for my Youtube video on summarizing and querying multiple pdfs

langchain-chat is an AI-driven Q&A system that leverages OpenAI's GPT-4 model and FAISS for efficient document indexing. It loads and splits documents from websites or PDFs, remembers conversations, and provides accurate, context-aware answers based on the indexed data. Easy to set up and extend.

Python Streamlit web app allowing users to interact with their data from a CSV or XLSX file, utilizing OpenAI API and LangChain. It imports necessary libraries, handles API key loading, displays a user-friendly interface for file upload and data preview, creates a Pandas DF agent with OpenAI, and executes user queries.

Introduction to LLM App Development Workshop: PDF Q&A App using OpenAI, Langchain, and Chainlit

Groq API: Quick Guide with Examples Groq SDK, Langchain, LlamaIndex, OpenAI SDK, Vercel

LangChain / LangGraph Q&A 에이전트

📚 AI-powered research reading workbench. Project-based paper Q&A with Hybrid RAG, multi-agent workflows (ReAct/Plan-Act/RePlan), long-term memory, and traceable evidence. Built with LangChain + LangGraph + Streamlit.

Q&A Bot with Llama Index and LangChain

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Using langchain, deeplake and openai to create a Q&A on the Mojo lang programming manual

Build a Medical Q&A system using LangChain and Mistral 7B

A code sample that shows how to use 🦜️🔗langchain, 🦙llama_index and a hosted LLM endpoint to do a standard chat or Q&A about a pdf document

Knowledge base Q&A program using LangChain for retrieval-augmented prompting and PGVector as vector store.

AI-powered learning platform with 6 specialized agents for personalized education. Features adaptive roadmaps, quizzes, tutoring, RAG document Q&A, and learning style adaptation. Built with Phidata, Streamlit, and LangChain.

Evolving LangChain agent architectures using the Quality-Diversity (QD) algorithm.

- Full Q&A pipeline using LangChain framework, Qdrant as vector database and Azure Function with HttpTrigger. - Research papers that can be loaded into the vector database, and the Azure Functions processes the request using the retrieval and generation logic. - Can use in any other research paper from Arxiv.

Using Pinecone, LangChain + OpenAI for Generative Q&A with Retrieval Augmented Generation (RAG).

LLM Agents: Landing Page Generation for an E-commerce Platform Using CrewAI, Groq-LangChain and Qdrant

This project builds a custom question answering chatbot using Langchain and Google Gemini Language Model (LLM). It fine-tunes industrial data for accurate responses and integrates Streamlit for user interaction, aiming to enhance user experience.

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Build a Full stack Q&A Chatbot with Langchain, and LLM Models on Amazon Sagemaker

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A high-performance Q&A chatbot that uses the Groq API and Llama 3 for real-time, context-aware answers from multiple PDF documents. This project leverages LangChain for orchestration, FAISS for local vector search, and Streamlit for an interactive user interface. Ideal for efficient and private document analysis.

This repository is a Video Q&A site that uses LangChain, OpenAI, Google Gemini, and Redis to answer questions using videos for RAG.

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Simple LLM-enabled document Q&A app built using Langchain and Streamlit