{"id":25926856,"url":"https://github.com/mohiteamit/ai-pdf-summarizer","last_synced_at":"2026-04-28T16:36:56.842Z","repository":{"id":280259394,"uuid":"941259770","full_name":"mohiteamit/ai-pdf-summarizer","owner":"mohiteamit","description":"AI-Powered PDF Summarizer: Upload PDFs, extract insights, generate customizable summaries with GPT-4. 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The application provides options for brief, detailed, and technical summaries and offers both a web interface and an API for integration.\n\n## Key Highlights\n\n1️⃣ **Versatile PDF Summarization**: Supports all types of PDF documents, including research papers, reports, and business documents. 2️⃣ **Customizable Summaries**: Generate brief, detailed, or technical summaries based on your needs. 3️⃣ **User-Friendly Interface**: Streamlit-powered web app for seamless interaction. 4️⃣ **API Integration**: FastAPI endpoint for programmatic access to summarization. 5️⃣ **Downloadable Output**: Save summaries as text files directly from the app. 6️⃣ **Containerized Deployment**: Fully dockerized for easy setup and deployment.\n\n## Features\n\n1️⃣ **PDF Upload and Parsing**: Upload PDF files and automatically extract text content. 2️⃣ **Customizable Summaries**: Choose between brief, detailed, and technical summary types. 3️⃣ **Streamlit Interface**: User-friendly web app for uploading files and viewing summaries. 4️⃣ **API Endpoint**: FastAPI endpoint for programmatic access to the summarization service. 5️⃣ **Downloadable Summaries**: Option to download summaries as text files.\n\n## Technology Stack\n\n- **Python 3.12**\n- **Streamlit**: Frontend for web app\n- **FastAPI**: API for backend integration\n- **OpenAI API**: GPT-4 for summarization\n- **PyMuPDF (fitz)**: PDF parsing\n- **Docker**: Containerization\n\n## Installation\n\n1. **Clone the repository:**\n\n```bash\ngit clone https://github.com/yourusername/ai-powered-pdf-summarizer.git\ncd ai-powered-pdf-summarizer\n```\n\n2. **Create a virtual environment and activate it:**\n\n```bash\npython3.12 -m venv venv\nsource venv/bin/activate  # On Windows use: venv\\Scripts\\activate\n```\n\n3. **Install dependencies:**\n\n```bash\npip install -r requirements.txt\n```\n\n4. **Set up the environment variables:** Create a `.env` file with the following content:\n\n```env\nOPENAI_API_KEY=your_openai_api_key_here\n```\n\n## Usage\n\n### **Streamlit App**\n\n```bash\nstreamlit run app/main.py\n```\n\nAccess the app at `http://localhost:8501`\n\n### **API Server**\n\n```bash\nuvicorn api.api:app --reload\n```\n\nAccess the API at `http://localhost:8000/summarize`\n\n## Docker\n\n```bash\ndocker build -t ai-pdf-summarizer .\ndocker run -p 8000:8000 ai-pdf-summarizer\n```\n\n## Testing\n\n```bash\npytest tests/\n```\n\n## License\n\nThis project is licensed under the MIT License.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmohiteamit%2Fai-pdf-summarizer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmohiteamit%2Fai-pdf-summarizer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmohiteamit%2Fai-pdf-summarizer/lists"}