🧠 SAS.DetectionService — Event Detection Microservice

This service is responsible for detecting and locating real-world events (e.g., disasters, crimes, major happenings) from raw social media messages using an AI-powered processing pipeline. It is part of the SAS (Situational Awareness System) platform.

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📁 Project Structure

SAS.DetectionService/
├── assets/                     # Additional resources (e.g., models, configs)
├── src/
│   ├── app/
│   │   ├── core/               # Core logic (configs, models, services)
│   │   │   ├── configs/        # App configuration (env, constants)
│   │   │   ├── models/         # Pydantic data models
│   │   │   └── services/       # Application services (location inference, messaging, storage, etc.)
│   │   ├── detection/          # Event detection base components
│   │   ├── kafka/              # Kafka producer and consumer wrappers
│   │   ├── pipeline/           # Modular processing pipeline for event detection
│   │   │   ├── stages/         # Individual processing stages (locating, summarizing, publishing)
│   │   │   ├── pipeline.py     # Pipeline runner
│   │   │   └── registry.py     # Stage registry and configuration
│   │   ├── main.py             # Entry point
│   │   └── __init__.py
│   └── tests/                  # Unit and integration tests
├── .env                        # Environment variables (DO NOT COMMIT SECRETS)
├── .gitignore
├── Dockerfile                  # Container configuration
├── Jenkinsfile                 # CI/CD build instructions
├── Makefile                    # Task shortcuts (build, test, etc.)
├── README.md
└── requirements.txt            # Python dependencies

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🚀 Features

• ✅ Kafka Integration for scalable messaging
• 🧩 Modular Pipeline Architecture using dynamically registered stages
• 🌍 Location Inference from text using NLP
• 🧵 Event Summarization & Deduplication
• 📤 Publishing Detected Events to downstream services or databases
• 🔧 Easily extendable with new stages, models, or event types

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🛠️ Setup & Development

1. Clone and enter the project

git clone https://github.com/HasanKhadd0ur/SAS.DetectionService.git
cd SAS.DetectionService

2. Create and activate a virtual environment

python -m venv venv
source venv/bin/activate  # On Windows use: venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

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🧪 Running the Service

python src/app/main.py

The service will start consuming messages from the Kafka topic, apply the event detection pipeline, and publish the results.

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🧪 Testing

pytest src/tests/

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🤖 CI/CD

This project uses Jenkins for automated build and testing. See Jenkinsfile for pipeline stages.

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📄 License

MIT License. See LICENSE (to be added).

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👨‍💻 Author

Hasan Khaddour — @HasanKhadd0ur