TextGuard AI

TextGuard AI is a powerful text classification and spam detection API that uses advanced AI models to analyze and classify text content. It provides a simple REST API interface for both single text analysis and batch processing.

Features

• Text classification and spam detection
• Batch processing support
• Tiered API access (Free, Basic, Premium)
• Rate limiting and usage tracking
• Detailed analysis with confidence scores
• Easy integration with existing applications

Installation

1. Clone the repository:

git clone https://github.com/yourusername/textguard-ai.git
cd textguard-ai

2. Install dependencies:

pip install -r requirements.txt

3. Set up environment variables: Create a .env file in the root directory with the following variables:

DEEPSEEK_API_KEY=your_deepseek_api_key_here
FREE_API_KEY=free_key
BASIC_API_KEY=basic_key
PREMIUM_API_KEY=premium_key

Usage

1. Start the server:

python -m src.api.main

2. The API will be available at http://localhost:8000

API Endpoints

• GET /: Root endpoint with API information
• GET /health: Health check endpoint
• GET /tools: List available tools and their parameters
• POST /classify: Classify a single text
• POST /batch_classify: Classify multiple texts
• GET /usage: Get usage statistics

Example Requests

1. Single Text Classification:

curl -X POST "http://localhost:8000/classify" \
     -H "X-API-Key: your_api_key" \
     -H "Content-Type: application/json" \
     -d '{"text": "Your text here", "analysis_type": "spam"}'

2. Batch Classification:

curl -X POST "http://localhost:8000/batch_classify" \
     -H "X-API-Key: your_api_key" \
     -H "Content-Type: application/json" \
     -d '{"texts": ["Text 1", "Text 2"], "analysis_type": "spam"}'

API Tiers

Free Tier

• 100 requests per day
• Maximum batch size: 10 texts
• Basic analysis

Basic Tier

• 1,000 requests per day
• Maximum batch size: 50 texts
• Detailed analysis

Premium Tier

• 10,000 requests per day
• Maximum batch size: 100 texts
• Advanced analysis with priority processing

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.