Legal Risk Analyzer for Tweets

🛡️ Not Legal Advice — This Streamlit app estimates the legal risk of a tweet for a given country, using a multi-agent CrewAI workflow. It collects statutes, codes and regulations, evaluates your tweet against hate-speech, defamation, incitement, and other categories, then surfaces a risk score and detailed breakdown.

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🚀 Features

• Multi-Agent Architecture

  • CountryLegalDataCollector: Scrapes official legal sources for a given country
  • LegalDataAggregator: Parses and structures statutes by category with citations
  • DynamicRiskEvaluationAgent: Scores your tweet against each legal category
  • ReportGenerator: Compiles a human-friendly summary, per-category details, and full JSON

• Interactive Streamlit UI

  • Enter your Country (e.g. US, UK, Germany)
  • Paste your Tweet text
  • Get an Overall Risk percentage, a clickable breakdown panel, and raw JSON

• Polished UX

  • Full-screen prison-bars background
  • Semi-transparent content container for legibility
  • Centered layout for any screen size

• Deployment-Ready

  • 📦 Dockerfile for containerized builds
  • ☁️ Streamlit Community Cloud instructions

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🔧 Project Structure

tweet_legal_risk/
├── app.py                  # Streamlit front-end & Crew kickoff
├── collector.py            # CountryLegalDataCollector agent
├── aggregator.py           # LegalDataAggregator agent
├── evaluator.py            # DynamicRiskEvaluationAgent
├── reporter.py             # ReportGenerator
├── requirements.txt        # Python dependencies
├── Dockerfile              # Container build instructions
├── .dockerignore
└── background.png          # Jail-bars background image

Main page.

The analysis structure.

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💻 Local Setup

1. Clone & cd

   git clone https://github.com/<your-username>/tweet-legal-risk.git
   cd tweet-legal-risk

Create & activate venv

python3.11 -m venv .venv
source .venv/bin/activate       # macOS/Linux
.\.venv\Scripts\Activate.ps1    # Windows PowerShell

Install dependencies

pip install --upgrade pip
pip install -r requirements.txt

Set your OpenAI key

export OPENAI_API_KEY="sk-..."

Run the app

python -m streamlit run app.py

Visit http://localhost:8501 in your browser.

🐳 Docker

Build and run in a container:

docker build -t tweet-legal-risk:latest .
docker run -d -p 8501:8501 --name tweet-risk-app tweet-legal-risk:latest

Open http://localhost:8501.

☁️ Deploy to Streamlit Community Cloud

Push your code to GitHub (public or private). Go to https://share.streamlit.io → New app → select your repo, branch main, and app.py. Under Settings → Secrets, add OPENAI_API_KEY. Click Deploy and share your public URL.

🎯 Usage

Enter a country code (e.g. US, germany). Paste any tweet text. Click Analyze Tweet. View your overall risk, expand categories for details, or inspect raw JSON.

⚖️ Disclaimer

This tool is not legal advice. It’s a demonstration of AI-driven risk estimation based on publicly available statutes. Always consult a qualified attorney for real legal guidance.

📄 License

This project is released under the MIT License.