https://github.com/tutortoise/bilingual-abusive-detection-service
Text based content moderation service
https://github.com/tutortoise/bilingual-abusive-detection-service
tensorflow transformer
Last synced: 5 months ago
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Text based content moderation service
- Host: GitHub
- URL: https://github.com/tutortoise/bilingual-abusive-detection-service
- Owner: Tutortoise
- Created: 2024-12-02T19:14:18.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-12T00:47:57.000Z (over 1 year ago)
- Last Synced: 2025-04-30T15:27:24.440Z (about 1 year ago)
- Topics: tensorflow, transformer
- Language: Python
- Homepage:
- Size: 4.93 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Bilingual Abusive Text Detection Engine
A content moderation engine designed to maintain professional standards in our tutor-finding platform. Supports both English and Indonesian languages.
## Overview
This engine provides enterprise-grade content moderation capabilities:
- Real-time detection of inappropriate content
- Multilingual support (English and Indonesian)
- High-precision text classification
- Scalable architecture for production deployment
- Production-ready API endpoints
- Comprehensive batch processing capabilities
## Key Features
### Content Analysis
- Multi-language support (EN/ID)
- Character substitution detection
- Context-aware classification
- Pattern recognition for evasion attempts
- Real-time content validation
### Technical Capabilities
- Low-latency response times (<100ms)
- High-throughput batch processing
- Scalable worker configuration
- Configurable confidence thresholds
- Comprehensive logging and monitoring
## Technical Stack
- **Runtime**: Python 3.11+
- **Framework**: FastAPI
- **Server**: Granian (High-performance ASGI server)
- **ML Framework**: TensorFlow 2.x
- **Package Management**: UV
## Installation
### Using Docker (Recommended)
```bash
# Build the image
docker build -t abusive-detection:latest .
# Run the container
docker run -d -p 8000:8000 abusive-detection:latest
```
### Manual Installation
```bash
# Install dependencies
uv sync
# Start the server
granian web.main:app \
--host 0.0.0.0 \
--port 8000 \
--interface asgi \
--workers $(nproc)
```
## Configuration
### Environment Variables
| Variable | Description | Default |
| -------------------------- | -------------------- | --------- |
| `GRANIAN_HOST` | Server host | `0.0.0.0` |
| `GRANIAN_PORT` | Server port | `8000` |
| `GRANIAN_WORKERS_PER_CORE` | Workers per CPU core | `2` |
| `GRANIAN_MAX_WORKERS` | Maximum worker limit | `32` |
| `GRANIAN_LOG_LEVEL` | Logging verbosity | `info` |
## API Reference
### Single Text Analysis
```http
POST /predict
Content-Type: application/json
{
"text": "Content to analyze"
}
```
### Batch Analysis
```http
POST /predict_batch
Content-Type: application/json
{
"texts": [
"First content to analyze",
"Second content to analyze"
]
}
```
### Response Schema
```typescript
interface PredictionResponse {
text: string;
probability: float; // Range: 0-1
is_abusive: boolean;
confidence: float; // Range: 0-1
early_detection: boolean;
matched_words: string[];
}
```
### Example Response
```json
{
"text": "Sample text for analysis",
"probability": 0.12,
"is_abusive": false,
"confidence": 0.88,
"early_detection": false,
"matched_words": []
}
```
## Model Training
### Datasets
- **English**: [Hate Speech and Offensive Language Detection](https://www.kaggle.com/datasets/thedevastator/hate-speech-and-offensive-language-detection/data)
- **Indonesian**: [Indonesian Abusive and Hate Speech Twitter Text](https://www.kaggle.com/datasets/ilhamfp31/indonesian-abusive-and-hate-speech-twitter-text/data)
## Health Monitoring
```http
GET /health
```
Returns service health status and basic metrics.