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Insight Engine (Intelligent Meeting Insights Platform)\n\n**Insight Engine** is an AI-powered platform designed to perform deep analysis on meeting transcripts, extract action items, summarize discussions, and provide intelligent insights using advanced NLP.\n\n## 🚀 Key Features\n\n### 🧠 Core AI \u0026 NLP (`app/nlp_analyzer.py`)\n*   **Meeting Summarization**: Automatically generates concise summaries of long discussions.\n*   **Action Item Extraction**: Identifies and assigns tasks, owners, and due dates from transcript text.\n*   **Key Topic Detection**: Extracts valid topics and decision points.\n*   **Speech-to-Text**: Integrated audio processing for meeting recordings.\n\n### 🔒 Security \u0026 Auth (`app/auth.py`, `app/password_policy.py`)\n*   **Robust Authentication**: JWT-based auth with refresh tokens.\n*   **Advanced Password Policy**: Enforces minimum entropy, checks **Have I Been Pwned** (HIBP) for breached passwords, and prevents common weak passwords.\n*   **Brute Force Protection**: Rate limiting and lockout mechanisms.\n*   **Secrets Management**: Production-ready secrets loading from:\n    *   Environment Variables (`.env`)\n    *   AWS Secrets Manager\n    *   Azure Key Vault\n    *   HashiCorp Vault\n\n### 💻 Modern Frontend (`frontend/`)\n*   Built with **React 18** and **Vite**.\n*   **TailwindCSS** for styling.\n*   **Recharts** for data visualization.\n*   **Playwright** for End-to-End (E2E) testing.\n\n### ⚙️ Backend Architecture\n*   **FastAPI**: High-performance async Python framework.\n*   **MongoDB (Motor)**: Async database driver for scalable data storage.\n*   **OpenAI Integration**: Leverages LLMs for semantic analysis.\n\n## 🛠️ Tech Stack\n\n| Component | Technology |\n| :--- | :--- |\n| **Backend** | Python 3.x, FastAPI, Uvicorn |\n| **Database** | MongoDB, Motor (Async) |\n| **AI/ML** | OpenAI API, Faster-Whisper, Vosk |\n| **Frontend** | React, Vite, TailwindCSS |\n| **Testing** | Pytest, Playwright |\n| **Security** | Python-Jose, Passlib, Bcrypt |\n\n## 📦 Installation \u0026 Setup\n\n### Prerequisites\n*   Python 3.8+\n*   Node.js 18+\n*   MongoDB instance\n\n### 1. Backend Setup\n```bash\n# Create virtual environment\npython -m venv venv\nsource venv/bin/activate  # or venv\\Scripts\\activate on Windows\n\n# Install dependencies\npip install -r requirements.txt\n\n# Configure environment\ncp .env.sample .env\n# Edit .env with your keys (OPENAI_API_KEY, SECRET_KEY, MONGO_URI)\n\n# Run server\npython main.py\n```\n\n### 2. Frontend Setup\n```bash\ncd frontend\nnpm install\nnpm run dev\n```\n\n## 🧪 Testing\n```bash\n# Backend Tests\npytest tests/\n\n# Frontend E2E Tests\ncd frontend\nnpx playwright test\n```\n\n## 📂 Project Structure\n*   `app/`: Core backend logic (API, Auth, NLP).\n*   `frontend/`: React application.\n*   `tools/`: Admin utilities (Backups, PDF extraction).\n*   `tests/`: Integration and unit tests (ignored in git).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fysocrius%2Finsight-engine","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fysocrius%2Finsight-engine","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fysocrius%2Finsight-engine/lists"}