https://github.com/mohitsingla46/rag-ai-document_analyzer

AI PDF Analyzer: Chat with your PDFs! LLM-powered app for Q&A, retrieval, & document insights. Uses LangChain, LangGraph, Groq, Nomic Embeddings & MongoDB. Frontend included.
https://github.com/mohitsingla46/rag-ai-document_analyzer

ai-agents groq-api langchain-js llama3 mongodb-atlas nomic-embed-text retrieval-augmented-generation vector-database

Last synced: 3 months ago
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AI PDF Analyzer: Chat with your PDFs! LLM-powered app for Q&A, retrieval, & document insights. Uses LangChain, LangGraph, Groq, Nomic Embeddings & MongoDB. Frontend included.

• Host: GitHub
• URL: https://github.com/mohitsingla46/rag-ai-document_analyzer
• Owner: mohitsingla46
• Created: 2025-03-02T07:35:25.000Z (3 months ago)
• Default Branch: master
• Last Pushed: 2025-03-02T08:39:23.000Z (3 months ago)
• Last Synced: 2025-03-02T09:26:28.222Z (3 months ago)
• Topics: ai-agents, groq-api, langchain-js, llama3, mongodb-atlas, nomic-embed-text, retrieval-augmented-generation, vector-database
• Language: TypeScript
• Homepage: https://ai-document-analyzer.vercel.app/
• Size: 148 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# AI Document Analyzer

[![License](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE)

[![Build Status](https://img.shields.io/badge/build-passing-brightgreen.svg)](https://your-build-status-url.com)

**Chat with your PDFs!** This project provides a user-friendly application that lets you ask questions about your PDF documents and get AI-powered answers.

## Overview

The AI Document Analyzer is a full-stack application that utilizes the power of Large Language Models (LLMs), vector databases, and document retrieval to allow you to interact with your PDF content in a conversational way.  Whether you need to extract specific information, summarize key points, or understand complex data, this tool can help.

## Key Features

*   **Conversational Interaction:** Ask questions about your PDF and receive natural language responses.

*   **AI-Powered Insights:** Leverages LLMs for intelligent understanding and analysis of your document content.

*   **Document Retrieval:** Finds relevant information within your PDF to provide accurate answers.

*   **Stateful Conversations:** Remembers previous questions and responses for context-aware interactions.

*   **User Friendly**: A front end is present, for a better user experience.

*   **Persistent Data:** Stores conversation state and embeddings for a seamless experience across sessions.

## Technologies Used

*   **Large Language Models (LLMs):**  For natural language understanding and response generation.

*   **LangChain & LangGraph:** For orchestrating LLMs, retrieval, and tools in a modular way.

* **Groq**: For faster inference of LLM.

*   **Nomic Embeddings:** For creating vector representations of document content.

*   **MongoDB as a Vector Database:** For storing and efficiently querying vector embeddings.

* **Front end technologies**: The frontend use a framework such as Next.js (The React Framework) and is well structured.

## Getting Started

1.  **Prerequisites:**

    *   Node.js (version 20.x or higher)

    *   MongoDB (running instance, with connection details configured)

    *   A Google OAuth 2.0 Client ID (`GOOGLE_CLIENT_ID`) and Client Secret (`GOOGLE_CLIENT_SECRET`) for authentication.

    *   Groq API key (`GROQ_API_KEY`) for LLM.

    *   Nomic Embedding API key (`NOMIC_API_KEY`).

    *   `NEXTAUTH_URL` defined (e.g., `http://localhost:3000` or your deployed URL)

    *   `NEXTAUTH_SECRET` for secure authentication.

    *   `MONGODB_URI` for connecting to your MongoDB instance.

2.  **Installation:**

    ```bash

    git clone 

    cd 

    npm install # For dependencies.

    ```

3.  **Configuration:**

    *   Create a `.env` file in the project root directory.

    *   Set environment variables:

        ```

        GOOGLE_CLIENT_ID=

        GOOGLE_CLIENT_SECRET=

        NEXTAUTH_URL=http://localhost:3000 # Replace with your deployment url, if not local

        NEXTAUTH_SECRET=

        MONGODB_URI=mongodb+srv://:@.mongodb.net/?retryWrites=true&w=majority&appName= #Update username, password, cluster, and database name.

        GROQ_API_KEY=

        NOMIC_API_KEY=

        ```

4.  **Running the Application:**

    ```bash

    # In the root directory

    npm run dev

    ```

5. **Accessing the application**:

    - Go to your web navigator, and go to `localhost:3000`, or the port that you specified in the frontend application.

## Contact

For any questions or inquiries, please contact [[email protected]]([email protected]).