PulsePoint is an advanced Open-Source Intelligence (OSINT) search and analysis tool designed to automatically gather, analyze, and present relevant data from various sources, including Wikipedia, Google, News APIs, Wolfram Alpha, and Semantic Scholar. It employs AI-powered insights to extract key takeaways and perform sentiment analysis on the retrieved content.
- Automatically queries unused tags for continuous data discovery.
- Supports advanced search filtering (language, date ranges, and exclusions).
- Uses Gemini AI for summarization, cross-referencing, and tagging.
- Extracts key insights from aggregated data.
- Generates structured JSON responses for easier integration.
- Implements VADER sentiment analysis to determine the tone of articles.
- Helps categorize news and research papers based on positive, negative, or neutral sentiment.
- Built with Flask and SQLAlchemy for database management.
- Supports automatic search scheduling using APScheduler.
- Easily extendable with additional OSINT sources.
Other features and capability can be seen at this document
- Python 3.8+
- Flask
- SQLite (default database)
- API keys for:
# Clone the repository
git clone https://github.com/1999AZZAR/PulsePoint.git
cd PulsePoint
# Create a virtual environment
python3 -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Create .env file and add your API keys
echo "NEWSAPI_KEY=your_newsapi_key" >> .env
echo "GSE_API_KEY=your_google_search_api_key" >> .env
echo "GSE_ID=your_google_search_engine_id" >> .env
echo "WOLFRAM_ALPHA_APP_ID=your_wolframalpha_app_id" >> .env
echo "GEMINI_API_KEY=your_gemini_api_key" >> .env
# Run the application
python main.pyNavigate to http://localhost:5000/ in your browser to access the search interface.
- Enter your query and optionally configure advanced filters.
- Click Search, and the system will gather results from multiple OSINT sources.
- AI-generated summaries and insights will be displayed alongside the search results.
- Sentiment analysis will indicate the overall tone of the content.
You can interact with PulsePoint programmatically:
POST /searchParameters:
{
"query": "climate change",
"negative_query": "hoax, conspiracy",
"from_date": "2024-01-01",
"to_date": "2024-12-31",
"language": "en"
}Response:
{
"results": {
"wikipedia": [{ "title": "Climate Change", "snippet": "Climate change refers to...", "url": "https://en.wikipedia.org/..." }],
"news_everything": [...],
"semantic_scholar": [...]
},
"summary": "Climate change is a global issue caused by human activities...",
"insights": "The data suggests that carbon emissions are the primary driver of climate change...",
"cross_references": "Multiple sources confirm the impact of deforestation on rising temperatures...",
"tags": ["environment", "global warming", "carbon emissions"]
}PulsePoint/
│── main.py # Flask app initialization & scheduler
│── routes.py # API endpoints
│── models.py # Database models
│── osint_helper.py # OSINT query handling
│── completer.py # Search validation & re-processing
│── auto_search.py # Automated background searches
│── mig.py # missing value fixer
│── instance/
│ └── osint.db # the database (will auto generated if none)
│── templates/
│ └── index.html # Web interface (Frontend)
└── static/ # Static assets (CSS, JS, etc.)
We welcome contributions! To contribute:
- Fork the repository
- Create a feature branch (
git checkout -b feature-xyz) - Commit your changes (
git commit -m "Added feature XYZ") - Push to your branch (
git push origin feature-xyz) - Open a Pull Request
Developed with ❤️ by azzar and the open-source community.
- 📘 Documentation (todo)
- 🐞 Issue Tracker
- ✨ Feature Requests
