📄 PDF RAG Assistant

A minimal PDF-based RAG (Retrieval-Augmented Generation) assistant. Users can upload a PDF, preview it, and ask questions about its contents using an AI agent.

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Workflow

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🛠️ Tech Stack

• Next.js (App Router) – UI and backend routes
• LangChain – Document splitting, vector search, and LLM orchestration
• Qdrant – Vector database for semantic search
• OpenAI – Embedding model + LLM (e.g., gpt-4, gpt-3.5-turbo)

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✨ Features

• 📤 PDF Upload: Upload your own PDF documents
• 🧠 RAG-based QA: Ask questions and get answers from your document
• 👁️ PDF Preview: View the uploaded PDF side-by-side using an <iframe>
• 🔎 Chunking + Embedding: Uses RecursiveCharacterTextSplitter + text-embedding-3-small
• ⚡ Fast Search: Backed by Qdrant for quick vector retrieval

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📦 Local Setup

1. Clone the repo

git clone https://github.com/your-username/pdf-rag-assistant.git
cd pdf-rag-assistant

2.Install Dependencies

npm install

3.Configure environment

OPENAI_API_KEY=your-openai-key

4.Start the server

docker compose up -d
npm run dev

TODOS

1.Streaming for better UI experience. 2.User authentication 3.More Improved Prompting 4.User history