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Chat with Data is an AI-powered platform where users can upload PDF documents, process them through an AI workflow, and engage in conversations about the content via a chat interface. Built with Langchain, Next.js, Vercel AI SDK, Supabase, and Vercel Blob Storage.

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Chat with Docs

Chat with Docs is an AI-powered document processing and conversation platform where users can upload PDF documents, have them processed through an AI workflow, and engage in conversations about the content of the documents through a chat interface.

Chat with Data Preview

RAG WORKFLOW

RAG Workflow

Features

  • Document Processing: Upload PDF documents which are processed using an AI workflow.
  • AI Workflow: Utilizes Langchain for document analysis and Next.js with Vercel AI SDK for document handling.
  • Vector Embeddings: Extracts vector embeddings of documents and stores them in Supabase Vector Store.
  • Chat Interface: Enables users to discuss document contents via a chat interface.
  • Document Preview: Provides a preview of the uploaded document within the chat interface.
  • Scalable Storage: Uses Vercel Blob Storage for managing document files securely.
  • Export Chat as Detailed PDF: Users can export their chat history, including AI analysis and document excerpts, into a PDF for offline viewing.
  • Fork Chat: Allows users to fork a conversation from shared chat.

Tech Stack

  • Langchain: Powers the AI workflow for document processing.
  • Next.js: Frontend framework for building the web application.
  • Vercel: Hosts the application and utilizes Vercel Blob Storage.
  • AI SDK: Integrates AI capabilities for document analysis.
  • Supabase: Stores vector embeddings of documents in Supabase Vector Store.
  • Gemini: Possibly used for enhancing chat functionalities or backend operations.

Installation and Setup

  1. Clone the repository

    git clone https://github.com/your-username/chat-with-docs.git
    cd chat-with-docs
  2. Install dependencies

    npm install
  3. Set up environment variables

    Create a .env file in the root directory and add the following:

    BLOB_READ_WRITE_TOKEN="your-vercel-blob-read-write-token"
    GOOGLE_API_KEY="your-google-api-key"
    SUPABASE_PRIVATE_KEY="your-supabase-private-key"
    SUPABASE_URL="https://your-supabase-url.co"
    NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY="your-clerk-publishable-key"
    CLERK_SECRET_KEY="your-clerk-secret-key"
    MONGODB_URL="mongodb+srv://username:password@your-mongodb-url"
    NEXT_PUBLIC_CLERK_SIGN_IN_URL="/sign-in"
    NEXT_PUBLIC_CLERK_SIGN_UP_URL="/sign-up"
    NEXT_PUBLIC_CLERK_AFTER_SIGN_IN_URL="/"
    NEXT_PUBLIC_CLERK_AFTER_SIGN_UP_URL="/"
    NEXT_PUBLIC_BLOB_READ_WRITE_TOKEN="your-nextjs-blob-read-write-token"
    # NEXT_CLERK_WEBHOOK_SECRET="your-clerk-webhook-secret"
    
  4. Start the application

    npm run dev
  5. Open your browser

    Visit http://localhost:3000 to see the application running.

Deployment

The application is deployed and accessible at Deployment Link.

About

Chat with Data is an AI-powered platform where users can upload PDF documents, process them through an AI workflow, and engage in conversations about the content via a chat interface. Built with Langchain, Next.js, Vercel AI SDK, Supabase, and Vercel Blob Storage.

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