{"repo":"eltatata/Nextjs-langchain-retrievalQA","free":true,"listed":false,"github":"https://github.com/eltatata/Nextjs-langchain-retrievalQA","clone":"git clone https://github.com/eltatata/Nextjs-langchain-retrievalQA.git","description":"A chatbot created with Next.js and AI SDK, using Langchain with RetrievalQA to provide information from a PDF loaded into a vector store in MongoDB.","language":"TypeScript","stars":10,"topics":["langchain","mogodb","vercel-ai-sdk","openai","nextjs","tailwindcss"],"license":null,"category":"ai-agents","readme_excerpt":"Felipe — AI-Powered Assistant for Data Structures Felipe is a lightweight AI assistant built with RAG (Retrieval-Augmented Generation) to help users ask questions and retrieve relevant information specifically about data structures . --- 🚀 Features - 💬 Ask natural language questions about data structures. - 📄 Information is retrieved from a structured PDF source . - ⚙️ Built using LangChain , Next.js , and Vercel AI SDK . - 🧠 MongoDB is used as the vector store for efficient semantic search. --- 📸 Demo --- 📘 Source Material All responses are based on a curated PDF about data structures. 👉 Download the PDF --- 🛠️ Tech Stack - LangChain - Next.js - Tailwind - Vercel AI SDK - MongoDB Vector Store - Vercel --- 📦 Installation bash Clone the repo git clone https://github.com/eltatata/Nextjs-langchain-retrievalQA cd Nextjs-langchain-retrievalQA Install dependencies npm install Create your .env file based on .env.example and configure your keys cp .env.example .env Run the development server npm run dev","default_branch":null,"files":null,"tree":[],"storefront":"/r/eltatata","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/eltatata/Nextjs-langchain-retrievalQA/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}