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Production-grade ai-sentiment-platform component

Project description

AI Sentiment Analysis Platform

Python 3.11+ FastAPI Transformers License: MIT

A production-grade NLP platform for real-time and batch sentiment analysis. Powered by state-of-the-art transformer models (BERT, RoBERTa) and optimized for high-throughput enterprise use cases.

🚀 Features

  • Hybrid Analysis: Choice of lightweight VADER/TextBlob or heavy-duty Transformer models.
  • Async Processing: Celery-backed batch processing for large datasets.
  • RESTful API: Fast and well-documented API endpoints.
  • Observability: Prometheus metrics and structured logging.
  • Caching: Redis integration for frequent query results.
  • Scalability: Designed for horizontal scaling with Docker.

📁 Project Structure

ai-sentiment-analysis-platform/
├── src/
│   ├── api/          # FastAPI routes and middleware
│   ├── core/         # Model loading, Processing logic
│   ├── models/       # NLP model abstractions
│   ├── tasks/        # Celery worker tasks
│   └── main.py       # Application entrypoint
├── tests/            # Unit and integration tests
├── Dockerfile
├── docker-compose.yml
└── requirements.txt

🛠️ Quick Start

# Clone
git clone https://github.com/Shivay00001/ai-sentiment-analysis-platform.git

# Run with Docker
docker-compose up --build

📄 License

MIT License

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