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AI-Powered Document Search and Analysis

This is an AI-powered web application that allows users to upload documents, perform semantic searches using large language models (LLMs), and generate document summaries.

Features

  • Document Upload: Upload documents for search and analysis.
  • Semantic Search: Perform AI-based contextual searches using LLMs.
  • Text Summarization: Generate concise summaries of document content.
  • User Authentication: Secure login and registration with JWT tokens.

Tech Stack

  • Backend: Python (FastAPI)
  • Frontend: Svelte
  • Database: PostgreSQL
  • AI Libraries: LangChain, OpenAI
  • Containerization: Docker, Docker Compose

Installation

  1. Clone the repository:

    git clone https://github.com/Leg0shii/smart-documents.git
cd smart-documents

  2. Set up the environment variables in backend/.env:

    FRONTEND_PORT=5000
BACKEND_PORT=8000
SECRET_KEY=your_secret_key
OPENAI_API_KEY=your_openai_api_key
POSTGRES_USER=postgres
POSTGRES_PASSWORD=postgres
POSTGRES_DB=smart_documents
POSTGRES_HOST=db
POSTGRES_PORT=5432
DATABASE_URL=postgresql://${POSTGRES_USER}:${POSTGRES_PASSWORD}@${POSTGRES_HOST}:${POSTGRES_PORT}/${POSTGRES_DB}

  3. Run the application with Docker:

    docker-compose up --build

  4. Access the application:

    • Frontend: http://localhost:5000
    • Backend: http://localhost:8000

Usage

  • Register/Login: Create an account or log in.
  • Upload Documents: Upload your documents for search.
  • Perform Search: Use the search bar to find documents with custom top K results.
  • Get Summaries: Retrieve summaries of the search results.

Development

To run locally without Docker:

  • Backend:

    cd backend
pip install -r requirements.txt
uvicorn app.main:app --reload

  • Frontend:

    cd frontend
npm install
npm run dev

License

This project is licensed under the MIT License.