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EuroSwarm Parliament - European Parliament Simulation

A comprehensive simulation of the European Parliament with 717 MEPs (Members of European Parliament) based on real EU data, featuring full democratic functionality including bill introduction, committee work, parliamentary debates, and democratic voting mechanisms.

Overview

The EuroSwarm Parliament transforms the basic senator simulation into a full-fledged European Parliament with democratic capabilities. Unlike the original senator simulation that only allowed simple "Aye/Nay" voting, this system provides:

Democratic Discussion: Full parliamentary debates with diverse perspectives
Committee Work: Specialized committee hearings and analysis
Bill Processing: Complete legislative workflow from introduction to final vote
Political Group Coordination: Realistic political group dynamics
Real MEP Data: Based on actual EU.xml data with 700 real MEPs
Board of Directors Pattern: Advanced democratic decision-making using the Board of Directors swarm

Key Features

Democratic Functionality

Bill Introduction: MEPs can introduce bills with sponsors and co-sponsors
Committee Hearings: Specialized committee analysis and recommendations
Parliamentary Debates: Multi-perspective discussions with diverse participants
Democratic Voting: Comprehensive voting with individual reasoning and political group analysis
Amendment Process: Support for bill amendments and modifications

Realistic Parliament Structure

717 MEPs: Based on real EU.xml data with actual MEP names and affiliations
Political Groups: All major European political groups represented
Committee System: 16 specialized committees with chairs and members
Leadership Positions: President, Vice Presidents, Committee Chairs
Country Representation: All EU member states represented

Advanced AI Agents

Individual MEP Agents: Each MEP has a unique AI agent with:
- Political group alignment
- National party affiliation
- Committee memberships
- Areas of expertise
- Country-specific interests
Democratic Decision-Making: Board of Directors pattern for consensus building
Contextual Responses: MEPs respond based on their political positions and expertise

Architecture

Core Components

1. ParliamentaryMember

Represents individual MEPs with:

Personal information (name, country, political group)
Parliamentary role and committee memberships
Areas of expertise and voting weight
AI agent for decision-making

2. ParliamentaryBill

Represents legislative proposals with:

Title, description, and legislative procedure type
Committee assignment and sponsorship
Status tracking and amendment support

3. ParliamentaryCommittee

Represents parliamentary committees with:

Chair and vice-chair positions
Member lists and responsibilities
Current bills under consideration

4. ParliamentaryVote

Represents voting sessions with:

Individual MEP votes and reasoning
Political group analysis
Final results and statistics

Democratic Decision-Making

The system uses the Board of Directors pattern for democratic decision-making:

Political Group Leaders: Each political group has a representative on the democratic council
Weighted Voting: Voting weights based on group size
Consensus Building: Multi-round discussions to reach consensus
Individual Voting: MEPs vote individually after considering the democratic council's analysis

Political Groups

The simulation includes all major European political groups:

Group of the European People's Party (Christian Democrats) - EPP
Group of the Progressive Alliance of Socialists and Democrats - S&D
Renew Europe Group - RE
Group of the Greens/European Free Alliance - Greens/EFA
European Conservatives and Reformists Group - ECR
The Left group in the European Parliament - GUE/NGL
Patriots for Europe Group - Patriots
Europe of Sovereign Nations Group - ESN
Non-attached Members - NI

Committees

16 specialized committees covering all major policy areas:

Agriculture and Rural Development
Budgetary Control
Civil Liberties, Justice and Home Affairs
Development
Economic and Monetary Affairs
Employment and Social Affairs
Environment, Public Health and Food Safety
Foreign Affairs
Industry, Research and Energy
Internal Market and Consumer Protection
International Trade
Legal Affairs
Petitions
Regional Development
Security and Defence
Transport and Tourism

Usage

Basic Initialization

from euroswarm_parliament import EuroSwarmParliament, VoteType

# Initialize parliament
parliament = EuroSwarmParliament(
    eu_data_file="EU.xml",
    parliament_size=None,  # Use all MEPs from EU.xml (718)
    enable_democratic_discussion=True,
    enable_committee_work=True,
    enable_amendment_process=True,
    verbose=False
)

Bill Introduction and Processing

# Introduce a bill
bill = parliament.introduce_bill(
    title="European Climate Law",
    description="Framework for achieving climate neutrality by 2050",
    bill_type=VoteType.ORDINARY_LEGISLATIVE_PROCEDURE,
    committee="Environment, Public Health and Food Safety",
    sponsor="Philippe Lamberts"
)

# Conduct committee hearing
hearing = parliament.conduct_committee_hearing(
    committee=bill.committee,
    bill=bill
)

# Conduct parliamentary debate
debate = parliament.conduct_parliamentary_debate(
    bill=bill,
    max_speakers=20
)

# Conduct democratic vote
vote = parliament.conduct_democratic_vote(bill)

Complete Democratic Session

# Run a complete parliamentary session
session = parliament.run_democratic_session(
    bill_title="Artificial Intelligence Act",
    bill_description="Comprehensive regulation of AI systems in the EU",
    bill_type=VoteType.ORDINARY_LEGISLATIVE_PROCEDURE,
    committee="Internal Market and Consumer Protection"
)

print(f"Final Outcome: {session['session_summary']['final_outcome']}")

Individual MEP Interaction

# Get specific MEP
mep = parliament.get_mep("Valérie Hayer")

# Ask for position on policy
response = mep.agent.run("What is your position on digital privacy regulation?")
print(f"{mep.full_name}: {response}")

Political Analysis

# Get parliament composition
composition = parliament.get_parliament_composition()

# Analyze political groups
for group_name, stats in composition['political_groups'].items():
    print(f"{group_name}: {stats['count']} MEPs ({stats['percentage']:.1f}%)")

# Get country representation
country_members = parliament.get_country_members("Germany")
print(f"German MEPs: {len(country_members)}")

Democratic Features

1. Democratic Discussion

Multi-Perspective Debates: MEPs from different political groups and countries
Expertise-Based Input: MEPs contribute based on their areas of expertise
Constructive Dialogue: Respectful debate with evidence-based arguments

2. Committee Work

Specialized Analysis: Committees provide detailed technical analysis
Expert Recommendations: Committee members offer specialized insights
Stakeholder Consideration: Multiple perspectives on policy impacts

3. Democratic Voting

Individual Reasoning: Each MEP provides reasoning for their vote
Political Group Analysis: Voting patterns by political affiliation
Transparent Process: Full visibility into decision-making process

4. Consensus Building

Board of Directors Pattern: Advanced democratic decision-making
Weighted Representation: Political groups weighted by size
Multi-Round Discussion: Iterative process to reach consensus

🔧 Configuration

Parliament Settings

parliament = EuroSwarmParliament(
    eu_data_file="EU.xml",              # Path to EU data file
    parliament_size=None,                # Use all MEPs from EU.xml (717)
    enable_democratic_discussion=True,   # Enable democratic features
    enable_committee_work=True,          # Enable committee system
    enable_amendment_process=True,       # Enable bill amendments
    verbose=False                        # Enable detailed logging
)

MEP Agent Configuration

Each MEP agent is configured with:

System Prompt: Comprehensive political background and principles
Model: GPT-4o-mini for consistent responses
Max Loops: 3 iterations for thorough analysis
Expertise Areas: Based on political group and country

📊 Data Sources

EU.xml File

The simulation uses real EU data from the EU.xml file containing:

MEP Names: Full names of all 700 MEPs
Countries: Country representation
Political Groups: European political group affiliations
National Parties: National political party memberships
MEP IDs: Unique identifiers for each MEP

Fallback System

If EU.xml cannot be loaded, the system creates representative fallback MEPs:

Sample MEPs: Representative selection from major political groups
Realistic Data: Based on actual European Parliament composition
Full Functionality: All democratic features remain available

🎮 Example Scenarios

Scenario 1: Climate Policy Debate

# Climate change legislation with diverse perspectives
session = parliament.run_democratic_session(
    bill_title="European Climate Law",
    bill_description="Carbon neutrality framework for 2050",
    committee="Environment, Public Health and Food Safety"
)

Scenario 2: Digital Regulation

# Digital services regulation with technical analysis
session = parliament.run_democratic_session(
    bill_title="Digital Services Act",
    bill_description="Online platform regulation",
    committee="Internal Market and Consumer Protection"
)

# Minimum wage directive with social considerations
session = parliament.run_democratic_session(
    bill_title="European Minimum Wage Directive",
    bill_description="Framework for adequate minimum wages",
    committee="Employment and Social Affairs"
)

🔮 Future Enhancements

Planned Optimizations

Performance Optimization: Parallel processing for large-scale voting
Advanced NLP: Better analysis of debate transcripts and reasoning
Real-time Updates: Dynamic parliament composition updates
Historical Analysis: Track voting patterns and political evolution
External Integration: Connect with real EU data sources

Potential Features

Amendment System: Full amendment proposal and voting
Lobbying Simulation: Interest group influence on MEPs
Media Integration: Public opinion and media coverage
International Relations: Interaction with other EU institutions
Budget Simulation: Financial impact analysis of legislation

📝 Requirements

Dependencies

swarms: Core swarm framework
loguru: Advanced logging
xml.etree.ElementTree: XML parsing for EU data
dataclasses: Data structure support
typing: Type hints
datetime: Date and time handling

Data Files

EU.xml: European Parliament member data (included)

🏃‍♂️ Quick Start

Install Dependencies:
```
pip install swarms loguru
```
Run Example:
```
python euroswarm_parliament_example.py
```

Create Custom Session:

from euroswarm_parliament import EuroSwarmParliament, VoteType

parliament = EuroSwarmParliament()
session = parliament.run_democratic_session(
    bill_title="Your Bill Title",
    bill_description="Your bill description",
    committee="Relevant Committee"
)

🤝 Contributing

The EuroSwarm Parliament is designed to be extensible and customizable. Contributions are welcome for:

New Democratic Features: Additional parliamentary procedures
Performance Optimizations: Faster processing for large parliaments
Data Integration: Additional EU data sources
Analysis Tools: Advanced political analysis features
Documentation: Improved documentation and examples

📄 License

This project is part of the Swarms Democracy framework and follows the same licensing terms.

🏛️ Acknowledgments

European Parliament: For the democratic structure and procedures
EU Data: For providing comprehensive MEP information
Swarms Framework: For the underlying multi-agent architecture
Board of Directors Pattern: For advanced democratic decision-making

The EuroSwarm Parliament represents a significant advancement in democratic simulation, providing a realistic and comprehensive model of European parliamentary democracy with full AI-powered MEP representation and democratic decision-making processes.

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