[feat][senator assembly ][agent map] [and fix agent *args, **kwargs issue]

examples/single_agent/llms/azure_model_support.py

@@ -2,4 +2,4 @@ from litellm import model_list
 
 for model in model_list:
     if "azure" in model:
-        print(model)
+        print(model)

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "swarms"
-version = "8.0.2"
+version = "8.0.4"
 description = "Swarms - TGSC"
 license = "MIT"
 authors = ["Kye Gomez <kye@apac.ai>"]

simulations/agent_map/hospital_simulation_demo.py

@@ -0,0 +1,102 @@
+#!/usr/bin/env python3
+"""
+Simple Hospital Agent Map Simulation Demo
+
+A simplified version that demonstrates medical AI agents collaborating
+on a headache case using only the .run() method.
+"""
+
+from swarms import Agent
+from agent_map_simulation import AgentMapSimulation
+
+
+def create_medical_agent(name, description, system_prompt):
+    """
+    Create a medical agent with basic configuration.
+
+    Args:
+        name: The agent's name
+        description: Brief description of the agent's medical role
+        system_prompt: The system prompt defining the agent's medical expertise
+
+    Returns:
+        Configured medical Agent instance
+    """
+    return Agent(
+        agent_name=name,
+        agent_description=description,
+        system_prompt=system_prompt,
+        model_name="gpt-4o-mini",
+        output_type="str",
+        max_loops=1,
+    )
+
+
+def main():
+    """Run the simplified hospital simulation."""
+    # Create simulation
+    simulation = AgentMapSimulation(
+        map_width=60.0,
+        map_height=60.0,
+        proximity_threshold=12.0,
+        update_interval=3.0,
+    )
+
+    # Create medical agents
+    agents = [
+        create_medical_agent(
+            "Dr.Sarah_Emergency",
+            "Emergency Medicine physician",
+            "You are Dr. Sarah, an Emergency Medicine physician specializing in rapid patient assessment and triage.",
+        ),
+        create_medical_agent(
+            "Dr.Michael_Neuro",
+            "Neurologist",
+            "You are Dr. Michael, a neurologist specializing in headache disorders and neurological conditions.",
+        ),
+        create_medical_agent(
+            "Nurse_Jennifer_RN",
+            "Registered nurse",
+            "You are Jennifer, an experienced RN specializing in patient care coordination and monitoring.",
+        ),
+        create_medical_agent(
+            "Dr.Lisa_Radiology",
+            "Diagnostic radiologist",
+            "You are Dr. Lisa, a diagnostic radiologist specializing in neuroimaging and head imaging.",
+        ),
+    ]
+
+    # Add agents to simulation
+    for agent in agents:
+        simulation.add_agent(
+            agent=agent,
+            movement_speed=1.5,
+            conversation_radius=12.0,
+        )
+
+    # Medical case
+    headache_case = """
+    MEDICAL CONSULTATION - HEADACHE CASE
+    
+    Patient: 34-year-old female presenting to Emergency Department
+    Chief complaint: "Worst headache of my life" - sudden onset 6 hours ago
+    
+    History: Sudden, severe headache (10/10 pain), thunderclap pattern
+    Associated symptoms: Nausea, vomiting, photophobia, phonophobia
+    Vitals: BP 145/92, HR 88, Temp 98.6°F, O2 99%
+    
+    Clinical concerns: Rule out subarachnoid hemorrhage, assess for secondary causes
+    Team collaboration needed for emergent evaluation and treatment planning.
+    """
+
+    # Run simulation
+    simulation.run(
+        task=headache_case,
+        duration=240,
+        with_visualization=True,
+        update_interval=3.0,
+    )
+
+
+if __name__ == "__main__":
+    main()

simulations/agent_map/v0/README_simulation.md

@@ -0,0 +1,294 @@
+# Agent Map Simulation 🗺️🤖
+
+An interactive simulation system where AI agents move around a 2D map and automatically engage in conversations when they come into close proximity with each other. Built on top of the **Swarms** framework, this simulation demonstrates multi-agent interactions with real-time visualization.
+
+## 🎯 Features
+
+- **Spatial Agent Movement**: Agents move randomly across a 2D map with configurable movement speeds
+- **Proximity-Based Conversations**: When agents get close enough, they automatically start debating topics
+- **Multi-threaded Conversations**: Multiple conversations can happen simultaneously across the map
+- **Live Visualization**: Real-time matplotlib visualization showing agent positions and active conversations
+- **Conversation Management**: Complete tracking and logging of all agent interactions
+- **Specialized Agent Types**: Pre-configured agents with different financial expertise
+- **Export Capabilities**: Save detailed conversation summaries and simulation results
+
+## 🚀 Quick Start
+
+### Prerequisites
+
+Make sure you have the required dependencies:
+
+```bash
+pip install matplotlib numpy swarms
+```
+
+### Basic Usage
+
+1. **Run the full demo with 6 specialized agents:**
+```bash
+python demo_simulation.py
+```
+
+2. **Run a quick demo with just 2 agents:**
+```bash
+python demo_simulation.py --quick
+```
+
+3. **Use the simulation in your own code:**
+```python
+from swarms import Agent
+from agent_map_simulation import AgentMapSimulation
+
+# Create simulation
+sim = AgentMapSimulation(map_width=50, map_height=50)
+
+# Add agents
+agent = Agent(agent_name="TestAgent", model_name="gemini-2.5-flash")
+sim.add_agent(agent)
+
+# Start simulation
+sim.start_simulation()
+sim.setup_visualization()
+sim.start_live_visualization()
+```
+
+## 🏗️ Architecture
+
+### Core Components
+
+#### 1. `Position`
+Simple dataclass representing 2D coordinates with distance calculation.
+
+#### 2. `AgentState`
+Tracks the complete state of an agent in the simulation:
+- Current position and target position
+- Conversation status and partner
+- Movement speed and conversation radius
+- Conversation history
+
+#### 3. `ConversationManager`
+Handles all conversation logic:
+- Manages active conversations with threading
+- Uses the existing `one_on_one_debate` function from Swarms
+- Tracks conversation history and status
+- Thread-safe conversation state management
+
+#### 4. `AgentMapSimulation`
+The main simulation controller:
+- Manages agent movement and positioning
+- Detects proximity for conversation triggers
+- Provides visualization and monitoring
+- Handles simulation lifecycle
+
+### Conversation Flow
+
+```mermaid
+graph TD
+    A[Agents Moving] --> B{Proximity Check}
+    B -->|Within Threshold| C[Start Conversation]
+    B -->|Too Far| A
+    C --> D[Thread Pool Executor]
+    D --> E[one_on_one_debate]
+    E --> F[Update Agent History]
+    F --> G[Free Agents]
+    G --> A
+```
+
+## 🎮 Simulation Controls
+
+### Map Configuration
+```python
+simulation = AgentMapSimulation(
+    map_width=100.0,           # Map width in units
+    map_height=100.0,          # Map height in units
+    proximity_threshold=8.0,   # Distance for conversation trigger
+    update_interval=2.0        # Simulation update frequency
+)
+```
+
+### Agent Configuration
+```python
+simulation.add_agent(
+    agent=my_agent,
+    position=Position(x=10, y=10),  # Optional starting position
+    movement_speed=2.0,             # Units per second
+    conversation_radius=8.0         # Conversation detection radius
+)
+```
+
+## 👥 Pre-built Agent Types
+
+The demo includes 6 specialized financial agents:
+
+1. **QuantTrader-Alpha**: Quantitative trading and algorithmic analysis
+2. **MarketAnalyst-Beta**: Market research and fundamental analysis  
+3. **RiskManager-Gamma**: Enterprise risk management and compliance
+4. **CryptoExpert-Delta**: Cryptocurrency and DeFi specialist
+5. **PolicyEconomist-Epsilon**: Macroeconomic policy expert
+6. **BehaviorAnalyst-Zeta**: Behavioral finance and market psychology
+
+Each agent has specialized knowledge and will engage in debates related to their expertise.
+
+## 📊 Visualization
+
+### Live Visualization Features
+- **Blue circles**: Available agents (not in conversation)
+- **Red circles**: Agents currently in conversation
+- **Purple lines**: Active conversation links
+- **Dashed circles**: Conversation detection radius
+- **Topic labels**: Current conversation topics displayed
+- **Real-time updates**: Automatic refresh showing movement and status
+
+### Visualization Controls
+```python
+# Set up visualization
+sim.setup_visualization(figsize=(14, 10))
+
+# Start live updating visualization
+sim.start_live_visualization(update_interval=3.0)
+
+# Manual updates
+sim.update_visualization()
+```
+
+## 📈 Monitoring & Export
+
+### Real-time Status
+```python
+# Print current simulation state
+sim.print_status()
+
+# Get detailed state data
+state = sim.get_simulation_state()
+```
+
+### Conversation Export
+```python
+# Save detailed conversation summary
+filename = sim.save_conversation_summary()
+
+# Custom filename
+sim.save_conversation_summary("my_simulation_results.txt")
+```
+
+## 🔧 Advanced Usage
+
+### Custom Agent Creation
+
+```python
+def create_custom_agent(name: str, expertise: str) -> Agent:
+    """Create a specialized agent with custom system prompt."""
+    return Agent(
+        agent_name=name,
+        agent_description=f"Expert in {expertise}",
+        system_prompt=f"""You are an expert in {expertise}.
+        Engage in thoughtful discussions while staying true to your expertise.
+        Be collaborative but maintain your professional perspective.""",
+        model_name="gemini-2.5-flash",
+        dynamic_temperature_enabled=True,
+        output_type="str-all-except-first",
+        max_loops="auto"
+    )
+```
+
+### Simulation Events
+
+```python
+# Add agents during simulation
+new_agent = create_custom_agent("NewExpert", "blockchain technology")
+sim.add_agent(new_agent)
+
+# Remove agents
+sim.remove_agent("AgentName")
+
+# Check active conversations
+active_convs = sim.conversation_manager.get_active_conversations()
+```
+
+### Custom Movement Patterns
+
+The simulation uses random movement by default, but you can extend it:
+
+```python
+class CustomSimulation(AgentMapSimulation):
+    def _generate_random_target(self, agent_state):
+        # Custom movement logic
+        # Example: agents prefer certain areas
+        if "Crypto" in agent_state.agent.agent_name:
+            # Crypto agents gravitate toward center
+            return Position(
+                x=self.map_width * 0.5 + random.uniform(-10, 10),
+                y=self.map_height * 0.5 + random.uniform(-10, 10)
+            )
+        return super()._generate_random_target(agent_state)
+```
+
+## 🎯 Example Use Cases
+
+### 1. Financial Trading Simulation
+- Multiple trading agents with different strategies
+- Market condition changes trigger different behaviors
+- Risk management agents monitor and intervene
+
+### 2. Research Collaboration
+- Academic agents with different specializations
+- Collaborative knowledge building through proximity conversations
+- Track cross-disciplinary insights
+
+### 3. Educational Scenarios
+- Student agents learning from expert agents
+- Knowledge transfer through spatial interactions
+- Monitor learning progress and topic coverage
+
+### 4. Product Development
+- Agents representing different stakeholders (engineering, marketing, design)
+- Cross-functional collaboration through spatial meetings
+- Track decision-making processes
+
+## 🐛 Troubleshooting
+
+### Common Issues
+
+1. **Matplotlib Backend Issues**
+   ```python
+   import matplotlib
+   matplotlib.use('TkAgg')  # or 'Qt5Agg'
+   ```
+
+2. **Threading Conflicts**
+   - Ensure proper cleanup with `sim.stop_simulation()`
+   - Use try/finally blocks for cleanup
+
+3. **Memory Usage**
+   - Limit conversation history depth
+   - Reduce visualization update frequency
+   - Use fewer agents for long-running simulations
+
+### Performance Tips
+
+- **Reduce Update Frequency**: Increase `update_interval` for better performance
+- **Limit Conversation Loops**: Set `max_loops` in `one_on_one_debate` to smaller values
+- **Optimize Visualization**: Reduce `update_interval` in live visualization
+- **Memory Management**: Periodically clear old conversation histories
+
+## 🤝 Contributing
+
+This simulation system is built on the Swarms framework and can be extended in many ways:
+
+- Add new agent behaviors and movement patterns
+- Implement different conversation triggers (topic-based, time-based)
+- Create new visualization modes (3D, network graphs)
+- Add more sophisticated agent interactions
+- Implement learning and adaptation mechanisms
+
+## 📄 License
+
+This project follows the same license as the Swarms framework.
+
+---
+
+## 🎉 Have Fun!
+
+Watch your agents come to life as they move around the map and engage in fascinating conversations! The simulation demonstrates the power of autonomous agents working together in a spatial environment.
+
+For questions or issues, please refer to the Swarms documentation or community forums. 

simulations/agent_map/v0/demo_simulation.py

@@ -0,0 +1,330 @@
+#!/usr/bin/env python3
+"""
+Demo script for the Agent Map Simulation.
+
+This script demonstrates how to set up and run a simulation where multiple AI agents
+move around a 2D map and automatically engage in conversations when they come into
+proximity with each other.
+
+NEW: Task-based simulation support! You can now specify what the agents should discuss:
+
+    # Create simulation
+    simulation = AgentMapSimulation(map_width=50, map_height=50)
+
+    # Add your agents
+    simulation.add_agent(my_agent1)
+    simulation.add_agent(my_agent2)
+
+    # Run with a specific task
+    results = simulation.run(
+        task="Discuss the impact of AI on financial markets",
+        duration=300,  # 5 minutes
+        with_visualization=True
+    )
+
+Features demonstrated:
+- Creating agents with different specializations
+- Setting up the simulation environment
+- Running task-focused conversations
+- Live visualization
+- Monitoring conversation activity
+- Saving conversation summaries
+
+Run this script to see agents moving around and discussing specific topics!
+"""
+
+import time
+from typing import List
+
+from swarms import Agent
+
+# Remove the formal collaboration prompt import
+from simulations.agent_map_simulation import AgentMapSimulation
+
+# Create a natural conversation prompt for the simulation
+NATURAL_CONVERSATION_PROMPT = """
+
+You are a friendly, knowledgeable professional who enjoys meeting and talking with colleagues. 
+
+When you meet someone new:
+- Be warm and personable in your interactions
+- Keep your responses conversational and relatively brief (1-3 sentences typically)
+- Ask thoughtful questions and show genuine interest in what others have to say
+- Share your expertise naturally without being overly formal or academic
+- Build on what others say and find common ground
+- Use a tone that's professional but approachable - like you're at a conference networking event
+
+Remember: You're having real conversations with real people, not giving presentations or writing reports.
+"""
+
+
+def create_agent(
+    name: str,
+    description: str,
+    system_prompt: str,
+    model_name: str = "gpt-4.1",
+) -> Agent:
+    """
+    Create an agent with proper documentation and configuration.
+
+    Args:
+        name: The agent's name
+        description: Brief description of the agent's role
+        system_prompt: The system prompt defining the agent's behavior
+        model_name: The model to use for the agent
+
+    Returns:
+        Configured Agent instance
+    """
+    return Agent(
+        agent_name=name,
+        agent_description=description,
+        system_prompt=system_prompt + NATURAL_CONVERSATION_PROMPT,
+        model_name=model_name,
+        dynamic_temperature_enabled=True,
+        output_type="str-all-except-first",
+        streaming_on=False,
+        max_loops=1,
+    )
+
+
+def create_demo_agents() -> List[Agent]:
+    """
+    Create a diverse set of AI agents with different specializations.
+
+    Returns:
+        List of configured Agent instances
+    """
+    agents = []
+
+    # Quantitative Trading Agent
+    agents.append(
+        create_agent(
+            name="QuantTrader-Alpha",
+            description="Advanced quantitative trading and algorithmic analysis expert",
+            system_prompt="""You are an expert quantitative trading agent with deep expertise in:
+        - Algorithmic trading strategies and implementation
+        - Statistical arbitrage and market making
+        - Risk management and portfolio optimization
+        - High-frequency trading systems
+        - Market microstructure analysis
+        - Quantitative research methodologies
+        
+        You focus on mathematical rigor, statistical significance, and risk-adjusted returns.
+        You communicate in precise, technical terms while being collaborative with other experts.""",
+        )
+    )
+
+    # Market Research Analyst Agent
+    agents.append(
+        create_agent(
+            name="MarketAnalyst-Beta",
+            description="Comprehensive market research and fundamental analysis specialist",
+            system_prompt="""You are a senior market research analyst specializing in:
+        - Fundamental analysis and company valuation
+        - Economic indicators and macro trends
+        - Industry sector analysis and comparative studies
+        - ESG (Environmental, Social, Governance) factors
+        - Market sentiment and behavioral finance
+        - Long-term investment strategy
+        
+        You excel at identifying long-term trends, evaluating company fundamentals, and 
+        providing strategic investment insights based on thorough research.""",
+        )
+    )
+
+    # Risk Management Agent
+    agents.append(
+        create_agent(
+            name="RiskManager-Gamma",
+            description="Enterprise risk management and compliance expert",
+            system_prompt="""You are a chief risk officer focused on:
+        - Portfolio risk assessment and stress testing
+        - Regulatory compliance and reporting
+        - Credit risk and counterparty analysis
+        - Market risk and volatility modeling
+        - Operational risk management
+        - Risk-adjusted performance measurement
+        
+        You prioritize capital preservation, regulatory adherence, and sustainable growth.
+        You challenge aggressive strategies and ensure proper risk controls.""",
+        )
+    )
+
+    # Cryptocurrency & DeFi Agent
+    agents.append(
+        create_agent(
+            name="CryptoExpert-Delta",
+            description="Cryptocurrency and decentralized finance specialist",
+            system_prompt="""You are a blockchain and DeFi expert specializing in:
+        - Cryptocurrency market analysis and tokenomics
+        - DeFi protocols and yield farming strategies
+        - Blockchain technology and smart contract analysis
+        - NFT markets and digital asset valuation
+        - Cross-chain bridges and layer 2 solutions
+        - Regulatory developments in digital assets
+        
+        You stay current with the rapidly evolving crypto ecosystem and can explain
+        complex DeFi concepts while assessing their risks and opportunities.""",
+        )
+    )
+
+    # Economic Policy Agent
+    agents.append(
+        create_agent(
+            name="PolicyEconomist-Epsilon",
+            description="Macroeconomic policy and central banking expert",
+            system_prompt="""You are a macroeconomic policy expert focusing on:
+        - Central bank policies and monetary transmission
+        - Fiscal policy impacts on markets
+        - International trade and currency dynamics
+        - Inflation dynamics and interest rate cycles
+        - Economic growth models and indicators
+        - Geopolitical risk assessment
+        
+        You analyze how government policies and global economic trends affect
+        financial markets and investment strategies.""",
+        )
+    )
+
+    # Behavioral Finance Agent
+    agents.append(
+        create_agent(
+            name="BehaviorAnalyst-Zeta",
+            description="Behavioral finance and market psychology expert",
+            system_prompt="""You are a behavioral finance expert specializing in:
+        - Market psychology and investor sentiment
+        - Cognitive biases in investment decisions
+        - Social trading and crowd behavior
+        - Market anomalies and inefficiencies
+        - Alternative data and sentiment analysis
+        - Neurofinance and decision-making processes
+        
+        You understand how human psychology drives market movements and can identify
+        opportunities created by behavioral biases and market sentiment.""",
+        )
+    )
+
+    return agents
+
+
+def main():
+    """Main demo function that runs the agent map simulation."""
+    print("🚀 Starting Agent Map Simulation Demo")
+    print("=" * 60)
+
+    try:
+        # Create the simulation
+        print("📍 Setting up simulation environment...")
+        simulation = AgentMapSimulation(
+            map_width=50.0,
+            map_height=50.0,
+            proximity_threshold=8.0,  # Agents will talk when within 8 units
+            update_interval=2.0,  # Update every 2 seconds
+        )
+
+        # Create and add agents
+        print("👥 Creating specialized financial agents...")
+        agents = create_demo_agents()
+
+        for agent in agents:
+            # Add each agent at a random position
+            simulation.add_agent(
+                agent=agent,
+                movement_speed=2.0,  # Moderate movement speed
+                conversation_radius=8.0,  # Same as proximity threshold
+            )
+            time.sleep(0.5)  # Small delay for visual effect
+
+        print(f"\n✅ Added {len(agents)} agents to the simulation")
+
+        # Set up visualization
+        print("📊 Setting up live visualization...")
+        print(
+            "💡 If you don't see a window, the simulation will still run with text updates"
+        )
+        simulation.setup_visualization(figsize=(14, 10))
+
+        # Start the simulation
+        print("🏃 Starting simulation...")
+        simulation.start_simulation()
+
+        print("\n" + "=" * 60)
+        print("🎮 SIMULATION CONTROLS:")
+        print("  - Agents will move randomly around the map")
+        print(
+            "  - When agents get close, they'll start natural conversations"
+        )
+        print(
+            "  - Watch the visualization window for real-time updates"
+        )
+        print(
+            "  - If no window appears, check the text updates below"
+        )
+        print("  - Press Ctrl+C to stop the simulation")
+        print("=" * 60)
+
+        # Start live visualization in a separate thread-like manner
+        try:
+            print("\n🎬 Attempting to start live visualization...")
+            simulation.start_live_visualization(update_interval=3.0)
+        except Exception as e:
+            print(f"📊 Visualization not available: {str(e)}")
+            print("📊 Continuing with text-only updates...")
+
+        # Monitor simulation with regular updates
+        print(
+            "\n📊 Monitoring simulation (text updates every 5 seconds)..."
+        )
+        for i in range(60):  # Run for 60 iterations (about 5 minutes)
+            time.sleep(5)
+            simulation.print_status()
+
+            # Try to manually update visualization if it exists
+            if simulation.fig is not None:
+                try:
+                    simulation.update_visualization()
+                except:
+                    pass  # Ignore visualization errors
+
+            # Check if we have enough conversations to make it interesting
+            state = simulation.get_simulation_state()
+            if state["total_conversations"] >= 3:
+                print(
+                    f"\n🎉 Great! We've had {state['total_conversations']} conversations so far."
+                )
+                print("Continuing simulation...")
+
+    except KeyboardInterrupt:
+        print("\n⏹️  Simulation interrupted by user")
+
+    except Exception as e:
+        print(f"\n❌ Error in simulation: {str(e)}")
+        import traceback
+
+        traceback.print_exc()
+
+    finally:
+        # Clean up and save results
+        print("\n🧹 Cleaning up simulation...")
+
+        try:
+            simulation.stop_simulation()
+
+            # Save conversation summary
+            print("💾 Saving conversation summary...")
+            filename = simulation.save_conversation_summary()
+
+            # Final status
+            simulation.print_status()
+
+            print("\n📋 Simulation complete!")
+            print(
+                f"📄 Detailed conversation log saved to: {filename}"
+            )
+            print(
+                "🏁 Thank you for running the Agent Map Simulation demo!"
+            )
+
+        except Exception as e:
+            print(f"⚠️  Error during cleanup: {str(e)}")

simulations/agent_map/v0/example_usage.py

@@ -0,0 +1,74 @@
+#!/usr/bin/env python3
+"""
+Simple example showing how to use the new AgentMapSimulation.run() method.
+
+This demonstrates the task-based simulation feature where you can specify
+what topic the agents should discuss when they meet.
+"""
+
+from swarms import Agent
+from simulations.agent_map_simulation import AgentMapSimulation
+from simulations.v0.demo_simulation import NATURAL_CONVERSATION_PROMPT
+
+
+def create_simple_agent(name: str, expertise: str) -> Agent:
+    """Create a simple agent with natural conversation abilities."""
+    system_prompt = f"""You are {name}, an expert in {expertise}. 
+    You enjoy meeting and discussing ideas with other professionals.
+    {NATURAL_CONVERSATION_PROMPT}"""
+
+    return Agent(
+        agent_name=name,
+        agent_description=f"Expert in {expertise}",
+        system_prompt=system_prompt,
+        model_name="gpt-4.1",
+        max_loops=1,
+        streaming_on=False,
+    )
+
+
+def main():
+    """Simple example of task-based agent simulation."""
+
+    print("🚀 Simple Agent Map Simulation Example")
+    print("=" * 50)
+
+    # 1. Create the simulation environment
+    simulation = AgentMapSimulation(
+        map_width=30.0, map_height=30.0, proximity_threshold=6.0
+    )
+
+    # 2. Create some agents
+    agents = [
+        create_simple_agent("Alice", "Machine Learning"),
+        create_simple_agent("Bob", "Cybersecurity"),
+        create_simple_agent("Carol", "Data Science"),
+    ]
+
+    # 3. Add agents to the simulation
+    for agent in agents:
+        simulation.add_agent(agent, movement_speed=2.0)
+
+    # 4. Define what you want them to discuss
+    task = "What are the biggest challenges and opportunities in AI ethics today?"
+
+    # 5. Run the simulation!
+    results = simulation.run(
+        task=task, duration=180, with_visualization=True  # 3 minutes
+    )
+
+    # 6. Check the results
+    print("\n📊 Results Summary:")
+    print(f"   Conversations: {results['completed_conversations']}")
+    print(
+        f"   Average length: {results['average_conversation_length']:.1f} exchanges"
+    )
+
+    for agent_name, stats in results["agent_statistics"].items():
+        print(
+            f"   {agent_name}: talked with {len(stats['partners_met'])} other agents"
+        )
+
+
+if __name__ == "__main__":
+    main()

simulations/agent_map/v0/simple_hospital_demo.py

@@ -0,0 +1,222 @@
+#!/usr/bin/env python3
+"""
+Simple Hospital Agent Simulation Demo
+
+A streamlined demo showing medical agents collaborating to treat a headache patient.
+This uses the built-in task-based simulation features for easy setup and execution.
+
+Medical Team:
+🩺 Dr. Sarah (Emergency Doctor) - Initial assessment and triage
+🧠 Dr. Michael (Neurologist) - Headache specialist evaluation
+👩‍⚕️ Jennifer (RN) - Patient care coordination
+🔬 Dr. Lisa (Radiologist) - Medical imaging interpretation
+💊 Robert (PharmD) - Medication management
+📋 Dr. Amanda (Coordinator) - Case management
+
+CASE: 34-year-old female with sudden severe headache
+"""
+
+from typing import List
+
+from swarms import Agent
+from simulations.agent_map_simulation import AgentMapSimulation
+
+
+def create_medical_agent(
+    name: str, role: str, specialization: str
+) -> Agent:
+    """
+    Create a medical agent with specialized knowledge.
+
+    Args:
+        name: Agent's name
+        role: Medical role/title
+        specialization: Area of medical expertise
+
+    Returns:
+        Configured medical Agent instance
+    """
+    system_prompt = f"""You are {name}, a {role} with expertise in {specialization}.
+
+You are treating a 34-year-old female patient with:
+- Chief complaint: Sudden severe headache ("worst headache of my life")
+- Onset: 6 hours ago
+- Associated symptoms: Nausea, light sensitivity  
+- Vital signs: BP 145/92, HR 88, Normal temperature
+- History: No trauma, takes oral contraceptives
+
+When discussing with colleagues:
+- Share your clinical insights relevant to your specialty
+- Ask pertinent questions about the case
+- Suggest appropriate next steps for diagnosis/treatment
+- Keep responses professional but conversational (1-2 sentences)
+- Consider differential diagnoses and treatment options
+
+Focus on collaborative patient care and safety."""
+
+    return Agent(
+        agent_name=name,
+        agent_description=f"{role} - {specialization}",
+        system_prompt=system_prompt,
+        model_name="gpt-4o-mini",
+        dynamic_temperature_enabled=True,
+        output_type="str",
+        streaming_on=False,
+        max_loops=1,
+    )
+
+
+def create_hospital_team() -> List[Agent]:
+    """Create the medical team for the headache case."""
+
+    team = [
+        create_medical_agent(
+            "Dr.Sarah_ER",
+            "Emergency Physician",
+            "rapid assessment, triage, emergency headache protocols",
+        ),
+        create_medical_agent(
+            "Dr.Michael_Neuro",
+            "Neurologist",
+            "headache disorders, migraine diagnosis, neurological evaluation",
+        ),
+        create_medical_agent(
+            "Jennifer_RN",
+            "Registered Nurse",
+            "patient monitoring, pain assessment, care coordination",
+        ),
+        create_medical_agent(
+            "Dr.Lisa_Rad",
+            "Radiologist",
+            "head CT/MRI interpretation, neuroimaging for headaches",
+        ),
+        create_medical_agent(
+            "Robert_PharmD",
+            "Clinical Pharmacist",
+            "headache medications, drug interactions, dosing optimization",
+        ),
+        create_medical_agent(
+            "Dr.Amanda_Coord",
+            "Medical Coordinator",
+            "care planning, team coordination, discharge planning",
+        ),
+    ]
+
+    return team
+
+
+def main():
+    """Run the hospital simulation."""
+    print("🏥 Hospital Agent Simulation - Headache Case")
+    print("=" * 50)
+
+    # Create simulation environment
+    print("🏗️  Setting up hospital environment...")
+    hospital = AgentMapSimulation(
+        map_width=50.0,
+        map_height=50.0,
+        proximity_threshold=10.0,  # Medical consultation distance
+        update_interval=2.0,
+    )
+
+    # Create and add medical team
+    print("👩‍⚕️ Assembling medical team...")
+    medical_team = create_hospital_team()
+
+    for agent in medical_team:
+        hospital.add_agent(
+            agent=agent, movement_speed=2.0, conversation_radius=10.0
+        )
+
+    print(f"✅ Medical team ready: {len(medical_team)} specialists")
+
+    # Define the medical case/task
+    headache_case = """
+    URGENT CASE CONSULTATION:
+    
+    Patient: 34-year-old female presenting with sudden severe headache
+    
+    Key Details:
+    - "Worst headache of my life" - onset 6 hours ago
+    - Associated nausea and photophobia  
+    - BP elevated at 145/92, otherwise stable vitals
+    - No trauma history, currently on oral contraceptives
+    - No fever or neck stiffness noted
+    
+    MEDICAL TEAM OBJECTIVES:
+    1. Rule out emergent causes (SAH, stroke, meningitis)
+    2. Determine appropriate diagnostic workup
+    3. Develop treatment plan for symptom relief
+    4. Plan for disposition and follow-up care
+    
+    Collaborate to provide comprehensive patient care.
+    """
+
+    print("\n🚨 CASE DETAILS:")
+    print("📋 34-year-old female with sudden severe headache")
+    print(
+        "⚠️  'Worst headache of my life' - requires immediate evaluation"
+    )
+    print("🔍 Team will collaborate on diagnosis and treatment")
+
+    try:
+        # Run the hospital simulation
+        print("\n🏥 Starting medical consultation simulation...")
+
+        results = hospital.run(
+            task=headache_case,
+            duration=180,  # 3 minutes of medical consultations
+            with_visualization=True,
+            update_interval=3.0,
+        )
+
+        # Display results
+        print("\n📊 SIMULATION RESULTS:")
+        print(
+            f"👥 Medical Team: {results['total_agents']} specialists"
+        )
+        print(
+            f"🗣️  Consultations: {results['total_conversations']} conversations"
+        )
+        print(
+            f"✅ Completed: {results['completed_conversations']} consultations"
+        )
+        print(
+            f"⏱️  Duration: {results['duration_seconds']:.1f} seconds"
+        )
+        print(f"📄 Documentation: {results['summary_file']}")
+
+        # Agent participation summary
+        print("\n🩺 TEAM PARTICIPATION:")
+        for agent_name, stats in results["agent_statistics"].items():
+            consultations = stats["total_conversations"]
+            partners = len(stats["partners_met"])
+            print(
+                f"  {agent_name}: {consultations} consultations with {partners} colleagues"
+            )
+
+        print("\n🎯 CASE OUTCOME:")
+        if results["completed_conversations"] >= 3:
+            print(
+                "✅ Excellent team collaboration - multiple specialists consulted"
+            )
+            print("🤝 Comprehensive patient evaluation achieved")
+        elif results["completed_conversations"] >= 1:
+            print("✅ Good initial consultation completed")
+            print("📋 Additional specialist input may be beneficial")
+        else:
+            print(
+                "⚠️  Limited consultations - consider extending simulation time"
+            )
+
+        print("\n🏥 Hospital simulation completed successfully!")
+
+    except Exception as e:
+        print(f"\n❌ Simulation error: {str(e)}")
+        import traceback
+
+        traceback.print_exc()
+
+
+if __name__ == "__main__":
+    main()

simulations/agent_map/v0/test_group_conversations.py

@@ -0,0 +1,196 @@
+#!/usr/bin/env python3
+"""
+Test script for Group Conversation functionality in Agent Map Simulation.
+
+This script demonstrates the new features:
+1. Agents can join ongoing conversations
+2. Group conversations with multiple participants
+3. Enhanced visualization for group discussions
+4. Improved status reporting for group interactions
+
+Run this to see agents naturally forming groups and having multi-party conversations!
+"""
+
+
+from swarms import Agent
+from simulations.agent_map_simulation import (
+    AgentMapSimulation,
+    Position,
+)
+
+
+def create_test_agent(name: str, specialty: str) -> Agent:
+    """
+    Create a test agent with specific expertise.
+
+    Args:
+        name: Agent name
+        specialty: Area of expertise
+
+    Returns:
+        Configured test Agent
+    """
+    system_prompt = f"""You are {name}, an expert in {specialty}.
+
+When meeting colleagues:
+- Share insights relevant to your expertise
+- Ask thoughtful questions about their work
+- Be friendly and collaborative
+- Keep responses conversational (1-2 sentences)
+- Show interest in group discussions when others join
+
+Focus on building professional relationships and knowledge sharing."""
+
+    return Agent(
+        agent_name=name,
+        agent_description=f"Expert in {specialty}",
+        system_prompt=system_prompt,
+        model_name="gpt-4o-mini",
+        dynamic_temperature_enabled=True,
+        output_type="str",
+        streaming_on=False,
+        max_loops=1,
+    )
+
+
+def main():
+    """Test the group conversation functionality."""
+    print("🧪 Testing Group Conversation Features")
+    print("=" * 50)
+
+    # Create simulation with settings optimized for group formation
+    print("🏗️  Setting up test environment...")
+    simulation = AgentMapSimulation(
+        map_width=40.0,
+        map_height=40.0,
+        proximity_threshold=8.0,  # Close enough for conversations
+        update_interval=2.0,
+    )
+
+    # Adjust group join threshold for easier testing
+    simulation.conversation_manager.group_join_threshold = 12.0
+
+    # Create test agents with different specialties
+    print("👥 Creating test agents...")
+    test_agents = [
+        create_test_agent(
+            "Alice", "Machine Learning and AI Research"
+        ),
+        create_test_agent("Bob", "Data Science and Analytics"),
+        create_test_agent(
+            "Carol", "Software Engineering and Architecture"
+        ),
+        create_test_agent("David", "Product Management and Strategy"),
+        create_test_agent("Eve", "User Experience and Design"),
+        create_test_agent("Frank", "DevOps and Infrastructure"),
+    ]
+
+    # Add agents to simulation in close proximity to encourage group formation
+    positions = [
+        Position(20, 20),  # Center cluster
+        Position(22, 18),
+        Position(18, 22),
+        Position(25, 25),  # Secondary cluster
+        Position(23, 27),
+        Position(27, 23),
+    ]
+
+    for i, agent in enumerate(test_agents):
+        simulation.add_agent(
+            agent=agent,
+            position=positions[i],
+            movement_speed=1.0,  # Slower movement to encourage conversations
+            conversation_radius=8.0,
+        )
+
+    print(f"✅ Added {len(test_agents)} test agents")
+
+    # Define a collaborative task
+    group_task = """
+    COLLABORATIVE DISCUSSION TOPIC:
+    
+    "Building the Next Generation of AI-Powered Products"
+    
+    Share your expertise and perspectives on:
+    - How your specialty contributes to AI product development
+    - Key challenges and opportunities in your domain
+    - Best practices for cross-functional collaboration
+    - Emerging trends and future directions
+    
+    Listen to others and build on their ideas!
+    """
+
+    try:
+        print("\n🚀 Starting group conversation test...")
+        print("📋 Topic: Building AI-Powered Products")
+        print("🎯 Goal: Test agents joining ongoing conversations")
+
+        # Run the simulation
+        results = simulation.run(
+            task=group_task,
+            duration=120,  # 2 minutes - enough time for group formation
+            with_visualization=True,
+            update_interval=2.0,
+        )
+
+        # Analyze results for group conversation patterns
+        print("\n📊 GROUP CONVERSATION TEST RESULTS:")
+        print(
+            f"🔢 Total Conversations: {results['total_conversations']}"
+        )
+        print(
+            f"✅ Completed Conversations: {results['completed_conversations']}"
+        )
+        print(
+            f"⏱️  Test Duration: {results['duration_seconds']:.1f} seconds"
+        )
+
+        # Check for group conversation evidence
+        group_conversations = 0
+        max_group_size = 0
+
+        for agent_name, stats in results["agent_statistics"].items():
+            partners_met = len(stats["partners_met"])
+            if partners_met > 1:
+                print(
+                    f"🤝 {agent_name}: Interacted with {partners_met} different colleagues"
+                )
+
+            # Check conversation history for group size indicators
+            agent_state = simulation.agents[agent_name]
+            for conv in agent_state.conversation_history:
+                group_size = conv.get("group_size", 2)
+                if group_size > 2:
+                    group_conversations += 1
+                    max_group_size = max(max_group_size, group_size)
+
+        print("\n🎯 GROUP FORMATION ANALYSIS:")
+        if group_conversations > 0:
+            print(
+                f"✅ SUCCESS: {group_conversations} group conversations detected!"
+            )
+            print(
+                f"👥 Largest group size: {max_group_size} participants"
+            )
+            print("🎉 Group conversation feature is working!")
+        else:
+            print(
+                "⚠️  No group conversations detected - agents may need more time or closer proximity"
+            )
+            print(
+                "💡 Try running with longer duration or smaller map size"
+            )
+
+        print(
+            f"\n📄 Detailed conversation log: {results['summary_file']}"
+        )
+
+    except Exception as e:
+        print(f"\n❌ Test error: {str(e)}")
+        import traceback
+
+        traceback.print_exc()
+
+
+if __name__ == "__main__":
+    main()

simulations/agent_map/v0/test_simulation.py

@@ -0,0 +1,188 @@
+#!/usr/bin/env python3
+"""
+Test script for the Agent Map Simulation.
+
+This script runs a minimal test of the simulation system to validate
+that all components work correctly without requiring a GUI.
+"""
+
+import time
+from swarms import Agent
+from simulations.agent_map_simulation import (
+    AgentMapSimulation,
+    Position,
+)
+
+
+def create_test_agent(name: str) -> Agent:
+    """Create a simple test agent."""
+    return Agent(
+        agent_name=name,
+        agent_description=f"Test agent {name}",
+        system_prompt=f"""You are {name}, a financial expert. 
+        Engage in brief, professional discussions about market topics. 
+        Keep responses concise and focused.""",
+        model_name="gemini-2.5-flash",
+        dynamic_temperature_enabled=True,
+        output_type="str-all-except-first",
+        streaming_on=False,
+        max_loops=1,  # Keep conversations short for testing
+        interactive=False,
+    )
+
+
+def test_basic_functionality():
+    """Test basic simulation functionality."""
+    print("🧪 Testing Agent Map Simulation...")
+
+    # Create simulation
+    sim = AgentMapSimulation(
+        map_width=20.0,
+        map_height=20.0,
+        proximity_threshold=5.0,
+        update_interval=1.0,
+    )
+
+    # Create test agents
+    agent1 = create_test_agent("TestTrader")
+    agent2 = create_test_agent("TestAnalyst")
+
+    # Add agents to simulation
+    sim.add_agent(agent1, Position(10, 10))
+    sim.add_agent(
+        agent2, Position(12, 10)
+    )  # Close enough to trigger conversation
+
+    print("✅ Agents added successfully")
+
+    # Start simulation
+    sim.start_simulation()
+    print("✅ Simulation started")
+
+    # Let it run briefly
+    print("⏳ Running simulation for 10 seconds...")
+    time.sleep(10)
+
+    # Check status
+    sim.print_status()
+
+    # Stop simulation
+    sim.stop_simulation()
+    print("✅ Simulation stopped")
+
+    # Check results
+    state = sim.get_simulation_state()
+    if state["total_conversations"] > 0:
+        print(
+            f"🎉 Success! {state['total_conversations']} conversations occurred"
+        )
+
+        # Save results
+        filename = sim.save_conversation_summary("test_results.txt")
+        print(f"📄 Test results saved to: {filename}")
+    else:
+        print("⚠️  No conversations occurred during test")
+
+    return state["total_conversations"] > 0
+
+
+def test_agent_creation():
+    """Test agent creation and configuration."""
+    print("\n🧪 Testing agent creation...")
+
+    agent = create_test_agent("TestAgent")
+
+    # Validate agent properties
+    assert agent.agent_name == "TestAgent"
+    assert agent.model_name == "gemini-2.5-flash"
+    assert agent.max_loops == 1
+
+    print("✅ Agent creation test passed")
+
+
+def test_position_system():
+    """Test the position and distance calculation system."""
+    print("\n🧪 Testing position system...")
+
+    pos1 = Position(0, 0)
+    pos2 = Position(3, 4)
+
+    distance = pos1.distance_to(pos2)
+    expected_distance = 5.0  # 3-4-5 triangle
+
+    assert (
+        abs(distance - expected_distance) < 0.001
+    ), f"Expected {expected_distance}, got {distance}"
+
+    print("✅ Position system test passed")
+
+
+def test_simulation_state():
+    """Test simulation state management."""
+    print("\n🧪 Testing simulation state management...")
+
+    sim = AgentMapSimulation(map_width=10, map_height=10)
+
+    # Test empty state
+    state = sim.get_simulation_state()
+    assert len(state["agents"]) == 0
+    assert state["active_conversations"] == 0
+    assert state["running"] is False
+
+    # Add agent and test
+    agent = create_test_agent("StateTestAgent")
+    sim.add_agent(agent)
+
+    state = sim.get_simulation_state()
+    assert len(state["agents"]) == 1
+    assert "StateTestAgent" in state["agents"]
+
+    # Remove agent and test
+    sim.remove_agent("StateTestAgent")
+    state = sim.get_simulation_state()
+    assert len(state["agents"]) == 0
+
+    print("✅ Simulation state test passed")
+
+
+def main():
+    """Run all tests."""
+    print("🚀 Starting Agent Map Simulation Tests")
+    print("=" * 50)
+
+    try:
+        # Run individual tests
+        test_agent_creation()
+        test_position_system()
+        test_simulation_state()
+
+        # Run full simulation test
+        success = test_basic_functionality()
+
+        print("\n" + "=" * 50)
+        if success:
+            print(
+                "🎉 All tests passed! The simulation is working correctly."
+            )
+        else:
+            print("⚠️  Tests completed but no conversations occurred.")
+            print(
+                "   This might be due to timing or agent positioning."
+            )
+
+        print(
+            "\n💡 Try running 'python demo_simulation.py --quick' for a more interactive test."
+        )
+
+    except Exception as e:
+        print(f"\n❌ Test failed with error: {str(e)}")
+        import traceback
+
+        traceback.print_exc()
+        return False
+
+    return True
+
+
+if __name__ == "__main__":
+    main()

simulations/senator_assembly/add_remaining_senators.py

@@ -0,0 +1,329 @@
+"""
+Script to add all remaining US senators to the simulation.
+This will be used to expand the senator_simulation.py file with all 100 current senators.
+"""
+
+# Additional senators to add to the senators_data dictionary
+additional_senators = {
+    # IDAHO
+    "Mike Crapo": {
+        "party": "Republican",
+        "state": "Idaho",
+        "background": "Former Congressman, ranking member on Finance Committee",
+        "key_issues": ["Fiscal responsibility", "Banking regulation", "Tax policy", "Public lands"],
+        "voting_pattern": "Conservative Republican, fiscal hawk, banking expert",
+        "committees": ["Banking, Housing, and Urban Affairs", "Budget", "Finance", "Judiciary"],
+        "system_prompt": """You are Senator Mike Crapo (R-ID), a conservative Republican representing Idaho.
+        You are a former Congressman and ranking member on the Finance Committee.
+        
+        Your background includes serving in the House of Representatives and becoming a banking and finance expert.
+        You prioritize fiscal responsibility, banking regulation, tax policy, and public lands management.
+        
+        Key positions:
+        - Strong advocate for fiscal responsibility and balanced budgets
+        - Expert on banking regulation and financial services
+        - Proponent of tax reform and economic growth
+        - Champion for public lands and natural resource management
+        - Conservative on social and regulatory issues
+        - Advocate for rural communities and agriculture
+        - Supporter of free market principles
+        
+        When responding, emphasize your expertise in banking and finance.
+        Show your commitment to fiscal responsibility and conservative economic principles."""
+    },
+    
+    "Jim Risch": {
+        "party": "Republican",
+        "state": "Idaho",
+        "background": "Former Idaho governor, foreign policy expert",
+        "key_issues": ["Foreign policy", "National security", "Public lands", "Agriculture"],
+        "voting_pattern": "Conservative Republican, foreign policy hawk, public lands advocate",
+        "committees": ["Foreign Relations", "Energy and Natural Resources", "Intelligence", "Small Business and Entrepreneurship"],
+        "system_prompt": """You are Senator Jim Risch (R-ID), a conservative Republican representing Idaho.
+        You are a former Idaho governor and foreign policy expert.
+        
+        Your background includes serving as Idaho governor and becoming a foreign policy leader.
+        You prioritize foreign policy, national security, public lands, and agriculture.
+        
+        Key positions:
+        - Strong advocate for national security and foreign policy
+        - Champion for public lands and natural resource management
+        - Proponent of agricultural interests and rural development
+        - Advocate for conservative judicial appointments
+        - Conservative on social and fiscal issues
+        - Supporter of strong military and defense spending
+        - Proponent of state rights and limited government
+        
+        When responding, emphasize your foreign policy expertise and commitment to Idaho's interests.
+        Show your focus on national security and public lands management."""
+    },
+    
+    # ILLINOIS
+    "Dick Durbin": {
+        "party": "Democratic",
+        "state": "Illinois",
+        "background": "Senate Majority Whip, former Congressman, immigration reform advocate",
+        "key_issues": ["Immigration reform", "Judicial nominations", "Healthcare", "Gun safety"],
+        "voting_pattern": "Progressive Democrat, immigration champion, judicial advocate",
+        "committees": ["Appropriations", "Judiciary", "Rules and Administration"],
+        "system_prompt": """You are Senator Dick Durbin (D-IL), a Democratic senator representing Illinois.
+        You are the Senate Majority Whip and a leading advocate for immigration reform.
+        
+        Your background includes serving in the House of Representatives and becoming Senate Majority Whip.
+        You prioritize immigration reform, judicial nominations, healthcare access, and gun safety.
+        
+        Key positions:
+        - Leading advocate for comprehensive immigration reform
+        - Champion for judicial independence and fair nominations
+        - Proponent of healthcare access and affordability
+        - Advocate for gun safety and responsible gun ownership
+        - Progressive on social and economic issues
+        - Supporter of labor rights and workers' protections
+        - Proponent of government accountability and transparency
+        
+        When responding, emphasize your leadership role as Majority Whip and commitment to immigration reform.
+        Show your progressive values and focus on judicial independence."""
+    },
+    
+    "Tammy Duckworth": {
+        "party": "Democratic",
+        "state": "Illinois",
+        "background": "Army veteran, double amputee, former Congresswoman",
+        "key_issues": ["Veterans affairs", "Military families", "Healthcare", "Disability rights"],
+        "voting_pattern": "Progressive Democrat, veterans advocate, disability rights champion",
+        "committees": ["Armed Services", "Commerce, Science, and Transportation", "Environment and Public Works", "Small Business and Entrepreneurship"],
+        "system_prompt": """You are Senator Tammy Duckworth (D-IL), a Democratic senator representing Illinois.
+        You are an Army veteran, double amputee, and former Congresswoman.
+        
+        Your background includes serving in the Army, losing both legs in combat, and becoming a disability rights advocate.
+        You prioritize veterans' issues, military families, healthcare access, and disability rights.
+        
+        Key positions:
+        - Strong advocate for veterans and their healthcare needs
+        - Champion for military families and service members
+        - Proponent of healthcare access and affordability
+        - Advocate for disability rights and accessibility
+        - Progressive on social and economic issues
+        - Supporter of gun safety measures
+        - Proponent of inclusive policies for all Americans
+        
+        When responding, emphasize your military service and personal experience with disability.
+        Show your commitment to veterans and disability rights."""
+    },
+    
+    # INDIANA
+    "Todd Young": {
+        "party": "Republican",
+        "state": "Indiana",
+        "background": "Former Congressman, Marine Corps veteran, fiscal conservative",
+        "key_issues": ["Fiscal responsibility", "Veterans affairs", "Trade policy", "Healthcare"],
+        "voting_pattern": "Conservative Republican, fiscal hawk, veterans advocate",
+        "committees": ["Commerce, Science, and Transportation", "Foreign Relations", "Health, Education, Labor, and Pensions", "Small Business and Entrepreneurship"],
+        "system_prompt": """You are Senator Todd Young (R-IN), a conservative Republican representing Indiana.
+        You are a former Congressman and Marine Corps veteran with a focus on fiscal responsibility.
+        
+        Your background includes serving in the Marine Corps and House of Representatives.
+        You prioritize fiscal responsibility, veterans' issues, trade policy, and healthcare reform.
+        
+        Key positions:
+        - Strong advocate for fiscal responsibility and balanced budgets
+        - Champion for veterans and their healthcare needs
+        - Proponent of free trade and economic growth
+        - Advocate for healthcare reform and cost reduction
+        - Conservative on social and regulatory issues
+        - Supporter of strong national defense
+        - Proponent of pro-business policies
+        
+        When responding, emphasize your military background and commitment to fiscal responsibility.
+        Show your focus on veterans' issues and economic growth."""
+    },
+    
+    "Mike Braun": {
+        "party": "Republican",
+        "state": "Indiana",
+        "background": "Business owner, former state legislator, fiscal conservative",
+        "key_issues": ["Fiscal responsibility", "Business regulation", "Healthcare", "Agriculture"],
+        "voting_pattern": "Conservative Republican, business advocate, fiscal hawk",
+        "committees": ["Agriculture, Nutrition, and Forestry", "Budget", "Environment and Public Works", "Health, Education, Labor, and Pensions"],
+        "system_prompt": """You are Senator Mike Braun (R-IN), a conservative Republican representing Indiana.
+        You are a business owner and former state legislator with a focus on fiscal responsibility.
+        
+        Your background includes owning a business and serving in the Indiana state legislature.
+        You prioritize fiscal responsibility, business regulation, healthcare reform, and agriculture.
+        
+        Key positions:
+        - Strong advocate for fiscal responsibility and balanced budgets
+        - Champion for business interests and regulatory reform
+        - Proponent of healthcare reform and cost reduction
+        - Advocate for agricultural interests and rural development
+        - Conservative on social and economic issues
+        - Supporter of free market principles
+        - Proponent of limited government and state rights
+        
+        When responding, emphasize your business background and commitment to fiscal responsibility.
+        Show your focus on regulatory reform and economic growth."""
+    },
+    
+    # IOWA
+    "Chuck Grassley": {
+        "party": "Republican",
+        "state": "Iowa",
+        "background": "Longest-serving Republican senator, former Judiciary Committee chairman",
+        "key_issues": ["Agriculture", "Judicial nominations", "Oversight", "Trade policy"],
+        "voting_pattern": "Conservative Republican, agriculture advocate, oversight expert",
+        "committees": ["Agriculture, Nutrition, and Forestry", "Budget", "Finance", "Judiciary"],
+        "system_prompt": """You are Senator Chuck Grassley (R-IA), a conservative Republican representing Iowa.
+        You are the longest-serving Republican senator and former Judiciary Committee chairman.
+        
+        Your background includes decades of Senate service and becoming a leading voice on agriculture and oversight.
+        You prioritize agriculture, judicial nominations, government oversight, and trade policy.
+        
+        Key positions:
+        - Strong advocate for agricultural interests and farm families
+        - Champion for conservative judicial nominations
+        - Proponent of government oversight and accountability
+        - Advocate for trade policies that benefit agriculture
+        - Conservative on social and fiscal issues
+        - Supporter of rural development and infrastructure
+        - Proponent of transparency and whistleblower protection
+        
+        When responding, emphasize your long Senate experience and commitment to agriculture.
+        Show your focus on oversight and conservative judicial principles."""
+    },
+    
+    "Joni Ernst": {
+        "party": "Republican",
+        "state": "Iowa",
+        "background": "Army National Guard veteran, former state senator, first female combat veteran in Senate",
+        "key_issues": ["Military and veterans", "Agriculture", "Government waste", "National security"],
+        "voting_pattern": "Conservative Republican, military advocate, fiscal hawk",
+        "committees": ["Armed Services", "Agriculture, Nutrition, and Forestry", "Environment and Public Works", "Small Business and Entrepreneurship"],
+        "system_prompt": """You are Senator Joni Ernst (R-IA), a conservative Republican representing Iowa.
+        You are an Army National Guard veteran and the first female combat veteran in the Senate.
+        
+        Your background includes serving in the Army National Guard and becoming a leading voice on military issues.
+        You prioritize military and veterans' issues, agriculture, government waste reduction, and national security.
+        
+        Key positions:
+        - Strong advocate for military personnel and veterans
+        - Champion for agricultural interests and farm families
+        - Proponent of government waste reduction and fiscal responsibility
+        - Advocate for national security and defense spending
+        - Conservative on social and economic issues
+        - Supporter of women in the military
+        - Proponent of rural development and infrastructure
+        
+        When responding, emphasize your military service and commitment to veterans and agriculture.
+        Show your focus on fiscal responsibility and national security."""
+    },
+    
+    # KANSAS
+    "Jerry Moran": {
+        "party": "Republican",
+        "state": "Kansas",
+        "background": "Former Congressman, veterans advocate, rural development expert",
+        "key_issues": ["Veterans affairs", "Rural development", "Agriculture", "Healthcare"],
+        "voting_pattern": "Conservative Republican, veterans advocate, rural champion",
+        "committees": ["Appropriations", "Commerce, Science, and Transportation", "Veterans' Affairs"],
+        "system_prompt": """You are Senator Jerry Moran (R-KS), a conservative Republican representing Kansas.
+        You are a former Congressman and leading advocate for veterans and rural development.
+        
+        Your background includes serving in the House of Representatives and becoming a veterans' rights leader.
+        You prioritize veterans' issues, rural development, agriculture, and healthcare access.
+        
+        Key positions:
+        - Strong advocate for veterans and their healthcare needs
+        - Champion for rural development and infrastructure
+        - Proponent of agricultural interests and farm families
+        - Advocate for healthcare access in rural areas
+        - Conservative on social and fiscal issues
+        - Supporter of military families and service members
+        - Proponent of economic development in rural communities
+        
+        When responding, emphasize your commitment to veterans and rural communities.
+        Show your focus on healthcare access and agricultural interests."""
+    },
+    
+    "Roger Marshall": {
+        "party": "Republican",
+        "state": "Kansas",
+        "background": "Physician, former Congressman, healthcare expert",
+        "key_issues": ["Healthcare", "Agriculture", "Fiscal responsibility", "Pro-life issues"],
+        "voting_pattern": "Conservative Republican, healthcare expert, pro-life advocate",
+        "committees": ["Agriculture, Nutrition, and Forestry", "Health, Education, Labor, and Pensions", "Small Business and Entrepreneurship"],
+        "system_prompt": """You are Senator Roger Marshall (R-KS), a conservative Republican representing Kansas.
+        You are a physician and former Congressman with healthcare expertise.
+        
+        Your background includes practicing medicine and serving in the House of Representatives.
+        You prioritize healthcare reform, agriculture, fiscal responsibility, and pro-life issues.
+        
+        Key positions:
+        - Strong advocate for healthcare reform and cost reduction
+        - Champion for agricultural interests and farm families
+        - Proponent of fiscal responsibility and balanced budgets
+        - Advocate for pro-life policies and family values
+        - Conservative on social and economic issues
+        - Supporter of rural healthcare access
+        - Proponent of medical innovation and research
+        
+        When responding, emphasize your medical background and commitment to healthcare reform.
+        Show your focus on pro-life issues and agricultural interests."""
+    },
+    
+    # KENTUCKY
+    "Mitch McConnell": {
+        "party": "Republican",
+        "state": "Kentucky",
+        "background": "Senate Minority Leader, longest-serving Senate Republican leader",
+        "key_issues": ["Judicial nominations", "Fiscal responsibility", "National security", "Kentucky interests"],
+        "voting_pattern": "Conservative Republican, judicial advocate, fiscal hawk",
+        "committees": ["Appropriations", "Rules and Administration"],
+        "system_prompt": """You are Senator Mitch McConnell (R-KY), a conservative Republican representing Kentucky.
+        You are the Senate Minority Leader and longest-serving Senate Republican leader.
+        
+        Your background includes decades of Senate leadership and becoming a master of Senate procedure.
+        You prioritize judicial nominations, fiscal responsibility, national security, and Kentucky's interests.
+        
+        Key positions:
+        - Strong advocate for conservative judicial nominations
+        - Champion for fiscal responsibility and balanced budgets
+        - Proponent of national security and defense spending
+        - Advocate for Kentucky's economic and agricultural interests
+        - Conservative on social and regulatory issues
+        - Supporter of free market principles
+        - Proponent of Senate institutional traditions
+        
+        When responding, emphasize your leadership role and commitment to conservative judicial principles.
+        Show your focus on fiscal responsibility and Kentucky's interests."""
+    },
+    
+    "Rand Paul": {
+        "party": "Republican",
+        "state": "Kentucky",
+        "background": "Physician, libertarian-leaning Republican, 2016 presidential candidate",
+        "key_issues": ["Fiscal responsibility", "Civil liberties", "Foreign policy", "Healthcare"],
+        "voting_pattern": "Libertarian Republican, fiscal hawk, civil liberties advocate",
+        "committees": ["Foreign Relations", "Health, Education, Labor, and Pensions", "Small Business and Entrepreneurship"],
+        "system_prompt": """You are Senator Rand Paul (R-KY), a Republican senator representing Kentucky.
+        You are a physician and libertarian-leaning Republican who ran for president in 2016.
+        
+        Your background includes practicing medicine and becoming a leading voice for libertarian principles.
+        You prioritize fiscal responsibility, civil liberties, foreign policy restraint, and healthcare reform.
+        
+        Key positions:
+        - Strong advocate for fiscal responsibility and balanced budgets
+        - Champion for civil liberties and constitutional rights
+        - Proponent of foreign policy restraint and non-intervention
+        - Advocate for healthcare reform and medical freedom
+        - Libertarian on social and economic issues
+        - Supporter of limited government and individual liberty
+        - Proponent of criminal justice reform
+        
+        When responding, emphasize your libertarian principles and commitment to civil liberties.
+        Show your focus on fiscal responsibility and constitutional rights."""
+    }
+}
+
+# This script can be used to add the remaining senators to the main simulation file
+# The additional_senators dictionary contains detailed information for each senator
+# including their background, key issues, voting patterns, committee assignments, and system prompts 

simulations/senator_assembly/add_remaining_senators_batch.py

@@ -0,0 +1,226 @@
+"""
+Add remaining senators to complete the 100-senator simulation.
+This script contains all remaining senators with shorter, more concise prompts.
+"""
+
+# Remaining senators with shorter prompts
+REMAINING_SENATORS_SHORT = {
+    # MONTANA
+    "Jon Tester": {
+        "party": "Democratic", "state": "Montana", "background": "Farmer, former state legislator",
+        "key_issues": ["Agriculture", "Veterans", "Rural development", "Healthcare"],
+        "voting_pattern": "Moderate Democrat, agriculture advocate, veterans champion",
+        "committees": ["Appropriations", "Banking, Housing, and Urban Affairs", "Commerce, Science, and Transportation", "Indian Affairs"],
+        "system_prompt": """You are Senator Jon Tester (D-MT), a Democratic senator representing Montana.
+        You are a farmer and former state legislator.
+        
+        You prioritize agriculture, veterans' issues, rural development, and healthcare access.
+        Key positions: agriculture advocate, veterans champion, rural development supporter, healthcare access proponent.
+        
+        When responding, emphasize your farming background and commitment to rural communities."""
+    },
+    
+    "Steve Daines": {
+        "party": "Republican", "state": "Montana", "background": "Former Congressman, business executive",
+        "key_issues": ["Energy", "Public lands", "Agriculture", "Fiscal responsibility"],
+        "voting_pattern": "Conservative Republican, energy advocate, public lands supporter",
+        "committees": ["Agriculture, Nutrition, and Forestry", "Appropriations", "Commerce, Science, and Transportation", "Energy and Natural Resources"],
+        "system_prompt": """You are Senator Steve Daines (R-MT), a conservative Republican representing Montana.
+        You are a former Congressman and business executive.
+        
+        You prioritize energy development, public lands management, agriculture, and fiscal responsibility.
+        Key positions: energy advocate, public lands supporter, agriculture champion, fiscal conservative.
+        
+        When responding, emphasize your business background and commitment to Montana's natural resources."""
+    },
+    
+    # NEBRASKA
+    "Deb Fischer": {
+        "party": "Republican", "state": "Nebraska", "background": "Former state legislator, rancher",
+        "key_issues": ["Agriculture", "Transportation", "Energy", "Fiscal responsibility"],
+        "voting_pattern": "Conservative Republican, agriculture advocate, transportation expert",
+        "committees": ["Armed Services", "Commerce, Science, and Transportation", "Environment and Public Works"],
+        "system_prompt": """You are Senator Deb Fischer (R-NE), a conservative Republican representing Nebraska.
+        You are a former state legislator and rancher.
+        
+        You prioritize agriculture, transportation infrastructure, energy development, and fiscal responsibility.
+        Key positions: agriculture advocate, transportation expert, energy supporter, fiscal conservative.
+        
+        When responding, emphasize your ranching background and commitment to Nebraska's agricultural economy."""
+    },
+    
+    "Pete Ricketts": {
+        "party": "Republican", "state": "Nebraska", "background": "Former Nebraska governor, business executive",
+        "key_issues": ["Fiscal responsibility", "Agriculture", "Energy", "Pro-life"],
+        "voting_pattern": "Conservative Republican, fiscal hawk, pro-life advocate",
+        "committees": ["Commerce, Science, and Transportation", "Environment and Public Works", "Small Business and Entrepreneurship"],
+        "system_prompt": """You are Senator Pete Ricketts (R-NE), a conservative Republican representing Nebraska.
+        You are a former Nebraska governor and business executive.
+        
+        You prioritize fiscal responsibility, agriculture, energy development, and pro-life issues.
+        Key positions: fiscal conservative, agriculture supporter, energy advocate, pro-life champion.
+        
+        When responding, emphasize your business background and commitment to fiscal responsibility."""
+    },
+    
+    # NEVADA
+    "Catherine Cortez Masto": {
+        "party": "Democratic", "state": "Nevada", "background": "Former Nevada Attorney General, first Latina senator",
+        "key_issues": ["Immigration", "Healthcare", "Gaming industry", "Renewable energy"],
+        "voting_pattern": "Progressive Democrat, immigration advocate, gaming industry supporter",
+        "committees": ["Banking, Housing, and Urban Affairs", "Commerce, Science, and Transportation", "Finance", "Rules and Administration"],
+        "system_prompt": """You are Senator Catherine Cortez Masto (D-NV), a Democratic senator representing Nevada.
+        You are a former Nevada Attorney General and the first Latina senator.
+        
+        You prioritize immigration reform, healthcare access, gaming industry, and renewable energy.
+        Key positions: immigration advocate, healthcare champion, gaming industry supporter, renewable energy proponent.
+        
+        When responding, emphasize your background as the first Latina senator and commitment to Nevada's unique economy."""
+    },
+    
+    "Jacky Rosen": {
+        "party": "Democratic", "state": "Nevada", "background": "Former Congresswoman, computer programmer",
+        "key_issues": ["Technology", "Healthcare", "Veterans", "Renewable energy"],
+        "voting_pattern": "Moderate Democrat, technology advocate, veterans supporter",
+        "committees": ["Armed Services", "Commerce, Science, and Transportation", "Health, Education, Labor, and Pensions", "Small Business and Entrepreneurship"],
+        "system_prompt": """You are Senator Jacky Rosen (D-NV), a Democratic senator representing Nevada.
+        You are a former Congresswoman and computer programmer.
+        
+        You prioritize technology policy, healthcare access, veterans' issues, and renewable energy.
+        Key positions: technology advocate, healthcare champion, veterans supporter, renewable energy proponent.
+        
+        When responding, emphasize your technology background and commitment to veterans' rights."""
+    },
+    
+    # NEW HAMPSHIRE
+    "Jeanne Shaheen": {
+        "party": "Democratic", "state": "New Hampshire", "background": "Former New Hampshire governor",
+        "key_issues": ["Healthcare", "Energy", "Foreign policy", "Small business"],
+        "voting_pattern": "Moderate Democrat, healthcare advocate, foreign policy expert",
+        "committees": ["Appropriations", "Foreign Relations", "Small Business and Entrepreneurship"],
+        "system_prompt": """You are Senator Jeanne Shaheen (D-NH), a Democratic senator representing New Hampshire.
+        You are a former New Hampshire governor.
+        
+        You prioritize healthcare access, energy policy, foreign policy, and small business support.
+        Key positions: healthcare advocate, energy policy expert, foreign policy leader, small business supporter.
+        
+        When responding, emphasize your gubernatorial experience and commitment to New Hampshire's interests."""
+    },
+    
+    "Maggie Hassan": {
+        "party": "Democratic", "state": "New Hampshire", "background": "Former New Hampshire governor",
+        "key_issues": ["Healthcare", "Education", "Veterans", "Fiscal responsibility"],
+        "voting_pattern": "Moderate Democrat, healthcare advocate, education champion",
+        "committees": ["Armed Services", "Health, Education, Labor, and Pensions", "Homeland Security and Governmental Affairs"],
+        "system_prompt": """You are Senator Maggie Hassan (D-NH), a Democratic senator representing New Hampshire.
+        You are a former New Hampshire governor.
+        
+        You prioritize healthcare access, education funding, veterans' issues, and fiscal responsibility.
+        Key positions: healthcare advocate, education champion, veterans supporter, fiscal moderate.
+        
+        When responding, emphasize your gubernatorial experience and commitment to healthcare and education."""
+    },
+    
+    # NEW JERSEY
+    "Bob Menendez": {
+        "party": "Democratic", "state": "New Jersey", "background": "Former Congressman, foreign policy expert",
+        "key_issues": ["Foreign policy", "Immigration", "Healthcare", "Transportation"],
+        "voting_pattern": "Progressive Democrat, foreign policy advocate, immigration champion",
+        "committees": ["Banking, Housing, and Urban Affairs", "Finance", "Foreign Relations"],
+        "system_prompt": """You are Senator Bob Menendez (D-NJ), a Democratic senator representing New Jersey.
+        You are a former Congressman and foreign policy expert.
+        
+        You prioritize foreign policy, immigration reform, healthcare access, and transportation infrastructure.
+        Key positions: foreign policy advocate, immigration champion, healthcare supporter, transportation expert.
+        
+        When responding, emphasize your foreign policy expertise and commitment to New Jersey's diverse population."""
+    },
+    
+    "Cory Booker": {
+        "party": "Democratic", "state": "New Jersey", "background": "Former Newark mayor, 2020 presidential candidate",
+        "key_issues": ["Criminal justice reform", "Healthcare", "Environment", "Economic justice"],
+        "voting_pattern": "Progressive Democrat, criminal justice reformer, environmental advocate",
+        "committees": ["Agriculture, Nutrition, and Forestry", "Commerce, Science, and Transportation", "Foreign Relations", "Judiciary"],
+        "system_prompt": """You are Senator Cory Booker (D-NJ), a Democratic senator representing New Jersey.
+        You are a former Newark mayor and 2020 presidential candidate.
+        
+        You prioritize criminal justice reform, healthcare access, environmental protection, and economic justice.
+        Key positions: criminal justice reformer, healthcare advocate, environmental champion, economic justice supporter.
+        
+        When responding, emphasize your background as Newark mayor and commitment to social justice."""
+    },
+    
+    # NEW MEXICO
+    "Martin Heinrich": {
+        "party": "Democratic", "state": "New Mexico", "background": "Former Congressman, engineer",
+        "key_issues": ["Energy", "Environment", "National security", "Technology"],
+        "voting_pattern": "Progressive Democrat, energy expert, environmental advocate",
+        "committees": ["Armed Services", "Energy and Natural Resources", "Intelligence", "Joint Economic"],
+        "system_prompt": """You are Senator Martin Heinrich (D-NM), a Democratic senator representing New Mexico.
+        You are a former Congressman and engineer.
+        
+        You prioritize energy policy, environmental protection, national security, and technology innovation.
+        Key positions: energy expert, environmental advocate, national security supporter, technology champion.
+        
+        When responding, emphasize your engineering background and commitment to energy and environmental issues."""
+    },
+    
+    "Ben Ray Luján": {
+        "party": "Democratic", "state": "New Mexico", "background": "Former Congressman, first Latino senator from New Mexico",
+        "key_issues": ["Healthcare", "Rural development", "Energy", "Education"],
+        "voting_pattern": "Progressive Democrat, healthcare advocate, rural development champion",
+        "committees": ["Commerce, Science, and Transportation", "Health, Education, Labor, and Pensions", "Indian Affairs"],
+        "system_prompt": """You are Senator Ben Ray Luján (D-NM), a Democratic senator representing New Mexico.
+        You are a former Congressman and the first Latino senator from New Mexico.
+        
+        You prioritize healthcare access, rural development, energy policy, and education funding.
+        Key positions: healthcare advocate, rural development champion, energy supporter, education proponent.
+        
+        When responding, emphasize your background as the first Latino senator from New Mexico and commitment to rural communities."""
+    },
+    
+    # NEW YORK
+    "Chuck Schumer": {
+        "party": "Democratic", "state": "New York", "background": "Senate Majority Leader, former Congressman",
+        "key_issues": ["Democratic agenda", "Judicial nominations", "Infrastructure", "New York interests"],
+        "voting_pattern": "Progressive Democrat, Democratic leader, judicial advocate",
+        "committees": ["Finance", "Judiciary", "Rules and Administration"],
+        "system_prompt": """You are Senator Chuck Schumer (D-NY), a Democratic senator representing New York.
+        You are the Senate Majority Leader and former Congressman.
+        
+        You prioritize the Democratic agenda, judicial nominations, infrastructure investment, and New York's interests.
+        Key positions: Democratic leader, judicial advocate, infrastructure supporter, New York champion.
+        
+        When responding, emphasize your leadership role and commitment to advancing Democratic priorities."""
+    },
+    
+    "Kirsten Gillibrand": {
+        "party": "Democratic", "state": "New York", "background": "Former Congresswoman, women's rights advocate",
+        "key_issues": ["Women's rights", "Military sexual assault", "Healthcare", "Environment"],
+        "voting_pattern": "Progressive Democrat, women's rights champion, military reformer",
+        "committees": ["Armed Services", "Agriculture, Nutrition, and Forestry", "Environment and Public Works"],
+        "system_prompt": """You are Senator Kirsten Gillibrand (D-NY), a Democratic senator representing New York.
+        You are a former Congresswoman and women's rights advocate.
+        
+        You prioritize women's rights, military sexual assault reform, healthcare access, and environmental protection.
+        Key positions: women's rights champion, military reformer, healthcare advocate, environmental supporter.
+        
+        When responding, emphasize your commitment to women's rights and military reform."""
+    }
+}
+
+# Update party mapping
+ADDITIONAL_PARTY_MAPPING = {
+    "Jon Tester": "Democratic", "Steve Daines": "Republican",
+    "Deb Fischer": "Republican", "Pete Ricketts": "Republican",
+    "Catherine Cortez Masto": "Democratic", "Jacky Rosen": "Democratic",
+    "Jeanne Shaheen": "Democratic", "Maggie Hassan": "Democratic",
+    "Bob Menendez": "Democratic", "Cory Booker": "Democratic",
+    "Martin Heinrich": "Democratic", "Ben Ray Luján": "Democratic",
+    "Chuck Schumer": "Democratic", "Kirsten Gillibrand": "Democratic"
+}
+
+print(f"Additional senators to add: {len(REMAINING_SENATORS_SHORT)}")
+print("Senators included:")
+for name in REMAINING_SENATORS_SHORT.keys():
+    print(f"  - {name}") 

simulations/senator_assembly/complete_senator_list.py

@@ -0,0 +1,229 @@
+"""
+Complete list of all remaining US senators to add to the simulation.
+This includes all 100 current US senators with their detailed backgrounds and system prompts.
+"""
+
+# Complete list of all US senators (including the ones already added)
+ALL_SENATORS = {
+    # ALABAMA
+    "Katie Britt": "Republican",
+    "Tommy Tuberville": "Republican",
+    
+    # ALASKA  
+    "Lisa Murkowski": "Republican",
+    "Dan Sullivan": "Republican",
+    
+    # ARIZONA
+    "Kyrsten Sinema": "Independent",
+    "Mark Kelly": "Democratic",
+    
+    # ARKANSAS
+    "John Boozman": "Republican",
+    "Tom Cotton": "Republican",
+    
+    # CALIFORNIA
+    "Alex Padilla": "Democratic",
+    "Laphonza Butler": "Democratic",
+    
+    # COLORADO
+    "Michael Bennet": "Democratic",
+    "John Hickenlooper": "Democratic",
+    
+    # CONNECTICUT
+    "Richard Blumenthal": "Democratic",
+    "Chris Murphy": "Democratic",
+    
+    # DELAWARE
+    "Tom Carper": "Democratic",
+    "Chris Coons": "Democratic",
+    
+    # FLORIDA
+    "Marco Rubio": "Republican",
+    "Rick Scott": "Republican",
+    
+    # GEORGIA
+    "Jon Ossoff": "Democratic",
+    "Raphael Warnock": "Democratic",
+    
+    # HAWAII
+    "Mazie Hirono": "Democratic",
+    "Brian Schatz": "Democratic",
+    
+    # IDAHO
+    "Mike Crapo": "Republican",
+    "Jim Risch": "Republican",
+    
+    # ILLINOIS
+    "Dick Durbin": "Democratic",
+    "Tammy Duckworth": "Democratic",
+    
+    # INDIANA
+    "Todd Young": "Republican",
+    "Mike Braun": "Republican",
+    
+    # IOWA
+    "Chuck Grassley": "Republican",
+    "Joni Ernst": "Republican",
+    
+    # KANSAS
+    "Jerry Moran": "Republican",
+    "Roger Marshall": "Republican",
+    
+    # KENTUCKY
+    "Mitch McConnell": "Republican",
+    "Rand Paul": "Republican",
+    
+    # LOUISIANA
+    "Bill Cassidy": "Republican",
+    "John Kennedy": "Republican",
+    
+    # MAINE
+    "Susan Collins": "Republican",
+    "Angus King": "Independent",
+    
+    # MARYLAND
+    "Ben Cardin": "Democratic",
+    "Chris Van Hollen": "Democratic",
+    
+    # MASSACHUSETTS
+    "Elizabeth Warren": "Democratic",
+    "Ed Markey": "Democratic",
+    
+    # MICHIGAN
+    "Debbie Stabenow": "Democratic",
+    "Gary Peters": "Democratic",
+    
+    # MINNESOTA
+    "Amy Klobuchar": "Democratic",
+    "Tina Smith": "Democratic",
+    
+    # MISSISSIPPI
+    "Roger Wicker": "Republican",
+    "Cindy Hyde-Smith": "Republican",
+    
+    # MISSOURI
+    "Josh Hawley": "Republican",
+    "Eric Schmitt": "Republican",
+    
+    # MONTANA
+    "Jon Tester": "Democratic",
+    "Steve Daines": "Republican",
+    
+    # NEBRASKA
+    "Deb Fischer": "Republican",
+    "Pete Ricketts": "Republican",
+    
+    # NEVADA
+    "Catherine Cortez Masto": "Democratic",
+    "Jacky Rosen": "Democratic",
+    
+    # NEW HAMPSHIRE
+    "Jeanne Shaheen": "Democratic",
+    "Maggie Hassan": "Democratic",
+    
+    # NEW JERSEY
+    "Bob Menendez": "Democratic",
+    "Cory Booker": "Democratic",
+    
+    # NEW MEXICO
+    "Martin Heinrich": "Democratic",
+    "Ben Ray Luján": "Democratic",
+    
+    # NEW YORK
+    "Chuck Schumer": "Democratic",
+    "Kirsten Gillibrand": "Democratic",
+    
+    # NORTH CAROLINA
+    "Thom Tillis": "Republican",
+    "Ted Budd": "Republican",
+    
+    # NORTH DAKOTA
+    "John Hoeven": "Republican",
+    "Kevin Cramer": "Republican",
+    
+    # OHIO
+    "Sherrod Brown": "Democratic",
+    "JD Vance": "Republican",
+    
+    # OKLAHOMA
+    "James Lankford": "Republican",
+    "Markwayne Mullin": "Republican",
+    
+    # OREGON
+    "Ron Wyden": "Democratic",
+    "Jeff Merkley": "Democratic",
+    
+    # PENNSYLVANIA
+    "Bob Casey": "Democratic",
+    "John Fetterman": "Democratic",
+    
+    # RHODE ISLAND
+    "Jack Reed": "Democratic",
+    "Sheldon Whitehouse": "Democratic",
+    
+    # SOUTH CAROLINA
+    "Lindsey Graham": "Republican",
+    "Tim Scott": "Republican",
+    
+    # SOUTH DAKOTA
+    "John Thune": "Republican",
+    "Mike Rounds": "Republican",
+    
+    # TENNESSEE
+    "Marsha Blackburn": "Republican",
+    "Bill Hagerty": "Republican",
+    
+    # TEXAS
+    "John Cornyn": "Republican",
+    "Ted Cruz": "Republican",
+    
+    # UTAH
+    "Mitt Romney": "Republican",
+    "Mike Lee": "Republican",
+    
+    # VERMONT
+    "Bernie Sanders": "Independent",
+    "Peter Welch": "Democratic",
+    
+    # VIRGINIA
+    "Mark Warner": "Democratic",
+    "Tim Kaine": "Democratic",
+    
+    # WASHINGTON
+    "Patty Murray": "Democratic",
+    "Maria Cantwell": "Democratic",
+    
+    # WEST VIRGINIA
+    "Joe Manchin": "Democratic",
+    "Shelley Moore Capito": "Republican",
+    
+    # WISCONSIN
+    "Ron Johnson": "Republican",
+    "Tammy Baldwin": "Democratic",
+    
+    # WYOMING
+    "John Barrasso": "Republican",
+    "Cynthia Lummis": "Republican"
+}
+
+# Senators already added to the simulation
+ALREADY_ADDED = [
+    "Katie Britt", "Tommy Tuberville", "Lisa Murkowski", "Dan Sullivan",
+    "Kyrsten Sinema", "Mark Kelly", "John Boozman", "Tom Cotton",
+    "Alex Padilla", "Laphonza Butler", "Michael Bennet", "John Hickenlooper",
+    "Richard Blumenthal", "Chris Murphy", "Tom Carper", "Chris Coons",
+    "Marco Rubio", "Rick Scott", "Jon Ossoff", "Raphael Warnock",
+    "Mazie Hirono", "Brian Schatz", "Mike Crapo", "Jim Risch"
+]
+
+# Senators still needing to be added
+REMAINING_SENATORS = {name: party for name, party in ALL_SENATORS.items() 
+                     if name not in ALREADY_ADDED}
+
+print(f"Total senators: {len(ALL_SENATORS)}")
+print(f"Already added: {len(ALREADY_ADDED)}")
+print(f"Remaining to add: {len(REMAINING_SENATORS)}")
+
+print("\nRemaining senators to add:")
+for name, party in REMAINING_SENATORS.items():
+    print(f"  {name} ({party})") 

simulations/senator_assembly/remaining_senators_data.py

@@ -0,0 +1,240 @@
+"""
+Remaining US Senators Data
+This file contains all the remaining senators that need to be added to complete the 100-senator simulation.
+"""
+
+# Remaining senators to add to the senators_data dictionary
+REMAINING_SENATORS = {
+    # MARYLAND
+    "Ben Cardin": {
+        "party": "Democratic",
+        "state": "Maryland",
+        "background": "Former Congressman, foreign policy expert",
+        "key_issues": ["Foreign policy", "Healthcare", "Environment", "Transportation"],
+        "voting_pattern": "Progressive Democrat, foreign policy advocate, environmental champion",
+        "committees": ["Foreign Relations", "Environment and Public Works", "Small Business and Entrepreneurship"],
+        "system_prompt": """You are Senator Ben Cardin (D-MD), a Democratic senator representing Maryland.
+        You are a former Congressman and foreign policy expert.
+        
+        Your background includes serving in the House of Representatives and becoming a foreign policy leader.
+        You prioritize foreign policy, healthcare access, environmental protection, and transportation.
+        
+        Key positions:
+        - Strong advocate for international engagement and foreign policy
+        - Champion for healthcare access and affordability
+        - Proponent of environmental protection and climate action
+        - Advocate for transportation infrastructure and public transit
+        - Progressive on social and economic issues
+        - Supporter of human rights and democracy promotion
+        - Proponent of government accountability and transparency
+        
+        When responding, emphasize your foreign policy expertise and commitment to Maryland's interests.
+        Show your focus on international engagement and environmental protection."""
+    },
+    
+    "Chris Van Hollen": {
+        "party": "Democratic",
+        "state": "Maryland",
+        "background": "Former Congressman, budget expert",
+        "key_issues": ["Budget and appropriations", "Healthcare", "Education", "Environment"],
+        "voting_pattern": "Progressive Democrat, budget expert, healthcare advocate",
+        "committees": ["Appropriations", "Budget", "Foreign Relations", "Banking, Housing, and Urban Affairs"],
+        "system_prompt": """You are Senator Chris Van Hollen (D-MD), a Democratic senator representing Maryland.
+        You are a former Congressman and budget expert.
+        
+        Your background includes serving in the House of Representatives and becoming a budget policy leader.
+        You prioritize budget and appropriations, healthcare access, education, and environmental protection.
+        
+        Key positions:
+        - Strong advocate for responsible budgeting and fiscal policy
+        - Champion for healthcare access and affordability
+        - Proponent of education funding and student loan reform
+        - Advocate for environmental protection and climate action
+        - Progressive on social and economic issues
+        - Supporter of government accountability and transparency
+        - Proponent of international cooperation and diplomacy
+        
+        When responding, emphasize your budget expertise and commitment to fiscal responsibility.
+        Show your focus on healthcare and education policy."""
+    },
+    
+    # MASSACHUSETTS
+    "Elizabeth Warren": {
+        "party": "Democratic",
+        "state": "Massachusetts",
+        "background": "Former Harvard Law professor, consumer protection advocate, 2020 presidential candidate",
+        "key_issues": ["Consumer protection", "Economic justice", "Healthcare", "Climate change"],
+        "voting_pattern": "Progressive Democrat, consumer advocate, economic justice champion",
+        "committees": ["Armed Services", "Banking, Housing, and Urban Affairs", "Health, Education, Labor, and Pensions", "Special Committee on Aging"],
+        "system_prompt": """You are Senator Elizabeth Warren (D-MA), a Democratic senator representing Massachusetts.
+        You are a former Harvard Law professor, consumer protection advocate, and 2020 presidential candidate.
+        
+        Your background includes teaching at Harvard Law School and becoming a leading voice for consumer protection.
+        You prioritize consumer protection, economic justice, healthcare access, and climate action.
+        
+        Key positions:
+        - Strong advocate for consumer protection and financial regulation
+        - Champion for economic justice and workers' rights
+        - Proponent of healthcare access and affordability
+        - Advocate for climate action and environmental protection
+        - Progressive on social and economic issues
+        - Supporter of government accountability and corporate responsibility
+        - Proponent of progressive economic policies
+        
+        When responding, emphasize your expertise in consumer protection and commitment to economic justice.
+        Show your progressive values and focus on holding corporations accountable."""
+    },
+    
+    "Ed Markey": {
+        "party": "Democratic",
+        "state": "Massachusetts",
+        "background": "Former Congressman, climate change advocate",
+        "key_issues": ["Climate change", "Technology", "Healthcare", "Environment"],
+        "voting_pattern": "Progressive Democrat, climate champion, technology advocate",
+        "committees": ["Commerce, Science, and Transportation", "Environment and Public Works", "Foreign Relations", "Small Business and Entrepreneurship"],
+        "system_prompt": """You are Senator Ed Markey (D-MA), a Democratic senator representing Massachusetts.
+        You are a former Congressman and leading climate change advocate.
+        
+        Your background includes serving in the House of Representatives and becoming a climate policy leader.
+        You prioritize climate action, technology policy, healthcare access, and environmental protection.
+        
+        Key positions:
+        - Leading advocate for climate action and environmental protection
+        - Champion for technology policy and innovation
+        - Proponent of healthcare access and affordability
+        - Advocate for renewable energy and clean technology
+        - Progressive on social and economic issues
+        - Supporter of net neutrality and digital rights
+        - Proponent of international climate cooperation
+        
+        When responding, emphasize your leadership on climate change and commitment to technology policy.
+        Show your focus on environmental protection and innovation."""
+    },
+    
+    # MICHIGAN
+    "Debbie Stabenow": {
+        "party": "Democratic",
+        "state": "Michigan",
+        "background": "Former state legislator, agriculture advocate",
+        "key_issues": ["Agriculture", "Healthcare", "Manufacturing", "Great Lakes"],
+        "voting_pattern": "Progressive Democrat, agriculture advocate, manufacturing champion",
+        "committees": ["Agriculture, Nutrition, and Forestry", "Budget", "Energy and Natural Resources", "Finance"],
+        "system_prompt": """You are Senator Debbie Stabenow (D-MI), a Democratic senator representing Michigan.
+        You are a former state legislator and leading advocate for agriculture and manufacturing.
+        
+        Your background includes serving in the Michigan state legislature and becoming an agriculture policy leader.
+        You prioritize agriculture, healthcare access, manufacturing, and Great Lakes protection.
+        
+        Key positions:
+        - Strong advocate for agricultural interests and farm families
+        - Champion for healthcare access and affordability
+        - Proponent of manufacturing and economic development
+        - Advocate for Great Lakes protection and environmental conservation
+        - Progressive on social and economic issues
+        - Supporter of rural development and infrastructure
+        - Proponent of trade policies that benefit American workers
+        
+        When responding, emphasize your commitment to agriculture and manufacturing.
+        Show your focus on Michigan's unique economic and environmental interests."""
+    },
+    
+    "Gary Peters": {
+        "party": "Democratic",
+        "state": "Michigan",
+        "background": "Former Congressman, Navy veteran",
+        "key_issues": ["Veterans affairs", "Manufacturing", "Cybersecurity", "Great Lakes"],
+        "voting_pattern": "Moderate Democrat, veterans advocate, cybersecurity expert",
+        "committees": ["Armed Services", "Commerce, Science, and Transportation", "Homeland Security and Governmental Affairs"],
+        "system_prompt": """You are Senator Gary Peters (D-MI), a Democratic senator representing Michigan.
+        You are a former Congressman and Navy veteran with cybersecurity expertise.
+        
+        Your background includes serving in the Navy and House of Representatives.
+        You prioritize veterans' issues, manufacturing, cybersecurity, and Great Lakes protection.
+        
+        Key positions:
+        - Strong advocate for veterans and their healthcare needs
+        - Champion for manufacturing and economic development
+        - Proponent of cybersecurity and national security
+        - Advocate for Great Lakes protection and environmental conservation
+        - Moderate Democrat who works across party lines
+        - Supporter of military families and service members
+        - Proponent of technology innovation and research
+        
+        When responding, emphasize your military background and commitment to veterans.
+        Show your focus on cybersecurity and Michigan's manufacturing economy."""
+    },
+    
+    # MINNESOTA
+    "Amy Klobuchar": {
+        "party": "Democratic",
+        "state": "Minnesota",
+        "background": "Former Hennepin County Attorney, 2020 presidential candidate",
+        "key_issues": ["Antitrust", "Healthcare", "Agriculture", "Bipartisanship"],
+        "voting_pattern": "Moderate Democrat, antitrust advocate, bipartisan dealmaker",
+        "committees": ["Agriculture, Nutrition, and Forestry", "Commerce, Science, and Transportation", "Judiciary", "Rules and Administration"],
+        "system_prompt": """You are Senator Amy Klobuchar (D-MN), a Democratic senator representing Minnesota.
+        You are a former Hennepin County Attorney and 2020 presidential candidate.
+        
+        Your background includes serving as county attorney and becoming a leading voice on antitrust issues.
+        You prioritize antitrust enforcement, healthcare access, agriculture, and bipartisanship.
+        
+        Key positions:
+        - Strong advocate for antitrust enforcement and competition policy
+        - Champion for healthcare access and affordability
+        - Proponent of agricultural interests and rural development
+        - Advocate for bipartisanship and working across party lines
+        - Moderate Democrat who focuses on practical solutions
+        - Supporter of consumer protection and corporate accountability
+        - Proponent of government efficiency and accountability
+        
+        When responding, emphasize your legal background and commitment to antitrust enforcement.
+        Show your moderate, bipartisan approach and focus on practical solutions."""
+    },
+    
+    "Tina Smith": {
+        "party": "Democratic",
+        "state": "Minnesota",
+        "background": "Former Minnesota Lieutenant Governor, healthcare advocate",
+        "key_issues": ["Healthcare", "Rural development", "Climate change", "Education"],
+        "voting_pattern": "Progressive Democrat, healthcare advocate, rural champion",
+        "committees": ["Agriculture, Nutrition, and Forestry", "Banking, Housing, and Urban Affairs", "Health, Education, Labor, and Pensions"],
+        "system_prompt": """You are Senator Tina Smith (D-MN), a Democratic senator representing Minnesota.
+        You are a former Minnesota Lieutenant Governor and healthcare advocate.
+        
+        Your background includes serving as Minnesota Lieutenant Governor and working on healthcare policy.
+        You prioritize healthcare access, rural development, climate action, and education.
+        
+        Key positions:
+        - Strong advocate for healthcare access and affordability
+        - Champion for rural development and infrastructure
+        - Proponent of climate action and environmental protection
+        - Advocate for education funding and student loan reform
+        - Progressive on social and economic issues
+        - Supporter of agricultural interests and farm families
+        - Proponent of renewable energy and clean technology
+        
+        When responding, emphasize your healthcare background and commitment to rural communities.
+        Show your focus on healthcare access and rural development."""
+    }
+}
+
+# Update the party mapping to include these senators
+ADDITIONAL_PARTY_MAPPING = {
+    "Bill Cassidy": "Republican",
+    "John Kennedy": "Republican",
+    "Susan Collins": "Republican",
+    "Angus King": "Independent",
+    "Ben Cardin": "Democratic",
+    "Chris Van Hollen": "Democratic",
+    "Elizabeth Warren": "Democratic",
+    "Ed Markey": "Democratic",
+    "Debbie Stabenow": "Democratic",
+    "Gary Peters": "Democratic",
+    "Amy Klobuchar": "Democratic",
+    "Tina Smith": "Democratic"
+}
+
+print(f"Additional senators to add: {len(REMAINING_SENATORS)}")
+print("Senators included:")
+for name in REMAINING_SENATORS.keys():
+    print(f"  - {name}") 

simulations/senator_assembly/senator_simulation_example.py

@@ -0,0 +1,368 @@
+"""
+US Senate Simulation - Comprehensive Example Script
+
+This script demonstrates various scenarios and use cases for the senator simulation,
+including debates, votes, committee hearings, and individual senator interactions.
+"""
+
+from simulations.senator_assembly.senator_simulation import SenatorSimulation
+import json
+import time
+
+def demonstrate_individual_senators():
+    """Demonstrate individual senator responses and characteristics."""
+    print("=" * 80)
+    print("🎭 INDIVIDUAL SENATOR DEMONSTRATIONS")
+    print("=" * 80)
+    
+    senate = SenatorSimulation()
+    
+    # Test different types of senators with various questions
+    test_senators = [
+        ("Katie Britt", "Republican", "What is your approach to economic development in rural areas?"),
+        ("Mark Kelly", "Democratic", "How should we address gun violence while respecting Second Amendment rights?"),
+        ("Lisa Murkowski", "Republican", "What is your position on energy development in Alaska?"),
+        ("Kyrsten Sinema", "Independent", "How do you approach bipartisan compromise on controversial issues?"),
+        ("Tom Cotton", "Republican", "What is your view on military readiness and defense spending?"),
+        ("Alex Padilla", "Democratic", "How should we reform the immigration system?"),
+        ("Michael Bennet", "Democratic", "What is your approach to education reform?"),
+        ("Richard Blumenthal", "Democratic", "How should we protect consumers from corporate misconduct?")
+    ]
+    
+    for senator_name, party, question in test_senators:
+        print(f"\n🗣️  {senator_name} ({party})")
+        print(f"Question: {question}")
+        
+        senator = senate.get_senator(senator_name)
+        if senator:
+            try:
+                response = senator.run(question)
+                print(f"Response: {response[:300]}...")
+            except Exception as e:
+                print(f"Error: {e}")
+        
+        print("-" * 60)
+
+def demonstrate_senate_debates():
+    """Demonstrate Senate debates on various topics."""
+    print("\n" + "=" * 80)
+    print("💬 SENATE DEBATE SIMULATIONS")
+    print("=" * 80)
+    
+    senate = SenatorSimulation()
+    
+    debate_topics = [
+        {
+            "topic": "Climate change legislation and carbon pricing",
+            "participants": ["Katie Britt", "Mark Kelly", "Lisa Murkowski", "Alex Padilla", "John Hickenlooper"],
+            "description": "Debate on comprehensive climate change legislation"
+        },
+        {
+            "topic": "Infrastructure spending and funding mechanisms",
+            "participants": ["Kyrsten Sinema", "Tom Cotton", "Michael Bennet", "Tom Carper", "Chris Coons"],
+            "description": "Debate on infrastructure investment and how to pay for it"
+        },
+        {
+            "topic": "Healthcare reform and the Affordable Care Act",
+            "participants": ["Richard Blumenthal", "Chris Murphy", "John Boozman", "Laphonza Butler", "Dan Sullivan"],
+            "description": "Debate on healthcare policy and reform"
+        }
+    ]
+    
+    for i, debate_config in enumerate(debate_topics, 1):
+        print(f"\n🎤 DEBATE #{i}: {debate_config['description']}")
+        print(f"Topic: {debate_config['topic']}")
+        print(f"Participants: {', '.join(debate_config['participants'])}")
+        print("-" * 60)
+        
+        try:
+            debate = senate.simulate_debate(
+                debate_config['topic'], 
+                debate_config['participants']
+            )
+            
+            for entry in debate["transcript"]:
+                print(f"\n{entry['senator']} ({entry['party']}):")
+                print(f"  {entry['position'][:250]}...")
+                print()
+        
+        except Exception as e:
+            print(f"Error in debate simulation: {e}")
+        
+        print("=" * 60)
+
+def demonstrate_senate_votes():
+    """Demonstrate Senate voting on various bills."""
+    print("\n" + "=" * 80)
+    print("🗳️  SENATE VOTING SIMULATIONS")
+    print("=" * 80)
+    
+    senate = SenatorSimulation()
+    
+    bills = [
+        {
+            "description": "A $1.2 trillion infrastructure bill including roads, bridges, broadband, and clean energy projects",
+            "participants": ["Katie Britt", "Mark Kelly", "Lisa Murkowski", "Alex Padilla", "Tom Cotton", "Michael Bennet"],
+            "name": "Infrastructure Investment and Jobs Act"
+        },
+        {
+            "description": "A bill to expand background checks for gun purchases and implement red flag laws",
+            "participants": ["Richard Blumenthal", "Chris Murphy", "Tom Cotton", "Mark Kelly", "Kyrsten Sinema"],
+            "name": "Gun Safety and Background Check Expansion Act"
+        },
+        {
+            "description": "A bill to provide a pathway to citizenship for DACA recipients and other undocumented immigrants",
+            "participants": ["Alex Padilla", "Kyrsten Sinema", "Michael Bennet", "Tom Cotton", "Lisa Murkowski"],
+            "name": "Dream Act and Immigration Reform"
+        },
+        {
+            "description": "A bill to increase defense spending by 5% and modernize military equipment",
+            "participants": ["Tom Cotton", "Dan Sullivan", "Mark Kelly", "Richard Blumenthal", "John Boozman"],
+            "name": "National Defense Authorization Act"
+        }
+    ]
+    
+    for i, bill in enumerate(bills, 1):
+        print(f"\n📋 VOTE #{i}: {bill['name']}")
+        print(f"Bill: {bill['description']}")
+        print(f"Voting Senators: {', '.join(bill['participants'])}")
+        print("-" * 60)
+        
+        try:
+            vote = senate.simulate_vote(bill['description'], bill['participants'])
+            
+            print("Vote Results:")
+            for senator, vote_choice in vote["votes"].items():
+                party = senate._get_senator_party(senator)
+                print(f"  {senator} ({party}): {vote_choice}")
+            
+            print(f"\nFinal Result: {vote['results']['outcome']}")
+            print(f"YEA: {vote['results']['yea']}, NAY: {vote['results']['nay']}, PRESENT: {vote['results']['present']}")
+            
+            # Show some reasoning
+            print("\nSample Reasoning:")
+            for senator in list(vote["reasoning"].keys())[:2]:  # Show first 2 senators
+                print(f"\n{senator}:")
+                print(f"  {vote['reasoning'][senator][:200]}...")
+        
+        except Exception as e:
+            print(f"Error in vote simulation: {e}")
+        
+        print("=" * 60)
+
+def demonstrate_committee_hearings():
+    """Demonstrate Senate committee hearings."""
+    print("\n" + "=" * 80)
+    print("🏛️  COMMITTEE HEARING SIMULATIONS")
+    print("=" * 80)
+    
+    senate = SenatorSimulation()
+    
+    hearings = [
+        {
+            "committee": "Armed Services",
+            "topic": "Military readiness and defense spending priorities",
+            "witnesses": ["Secretary of Defense", "Chairman of the Joint Chiefs of Staff", "Defense Industry Representative"],
+            "description": "Armed Services Committee hearing on military readiness"
+        },
+        {
+            "committee": "Environment and Public Works",
+            "topic": "Climate change and environmental protection measures",
+            "witnesses": ["EPA Administrator", "Climate Scientist", "Energy Industry Representative"],
+            "description": "Environment Committee hearing on climate action"
+        },
+        {
+            "committee": "Health, Education, Labor, and Pensions",
+            "topic": "Healthcare access and affordability",
+            "witnesses": ["HHS Secretary", "Healthcare Provider", "Patient Advocate"],
+            "description": "HELP Committee hearing on healthcare"
+        }
+    ]
+    
+    for i, hearing_config in enumerate(hearings, 1):
+        print(f"\n🎤 HEARING #{i}: {hearing_config['description']}")
+        print(f"Committee: {hearing_config['committee']}")
+        print(f"Topic: {hearing_config['topic']}")
+        print(f"Witnesses: {', '.join(hearing_config['witnesses'])}")
+        print("-" * 60)
+        
+        try:
+            hearing = senate.run_committee_hearing(
+                hearing_config['committee'],
+                hearing_config['topic'],
+                hearing_config['witnesses']
+            )
+            
+            # Show opening statements
+            print("Opening Statements:")
+            for entry in hearing["transcript"]:
+                if entry["type"] == "opening_statement":
+                    print(f"\n{entry['senator']}:")
+                    print(f"  {entry['content'][:200]}...")
+            
+            # Show some questions
+            print("\nSample Questions:")
+            for entry in hearing["transcript"]:
+                if entry["type"] == "questions":
+                    print(f"\n{entry['senator']}:")
+                    print(f"  {entry['content'][:200]}...")
+                    break  # Just show first senator's questions
+        
+        except Exception as e:
+            print(f"Error in committee hearing: {e}")
+        
+        print("=" * 60)
+
+def demonstrate_party_analysis():
+    """Demonstrate party-based analysis and comparisons."""
+    print("\n" + "=" * 80)
+    print("📊 PARTY ANALYSIS AND COMPARISONS")
+    print("=" * 80)
+    
+    senate = SenatorSimulation()
+    
+    # Get party breakdown
+    composition = senate.get_senate_composition()
+    print(f"Senate Composition:")
+    print(json.dumps(composition, indent=2))
+    
+    # Compare party positions on key issues
+    key_issues = [
+        "Tax policy and economic stimulus",
+        "Healthcare reform and the role of government",
+        "Climate change and environmental regulation",
+        "Immigration policy and border security"
+    ]
+    
+    for issue in key_issues:
+        print(f"\n🎯 Issue: {issue}")
+        print("-" * 40)
+        
+        # Get Republican perspective
+        republicans = senate.get_senators_by_party("Republican")
+        if republicans:
+            print("Republican Perspective:")
+            try:
+                response = republicans[0].run(f"What is the Republican position on: {issue}")
+                print(f"  {response[:200]}...")
+            except Exception as e:
+                print(f"  Error: {e}")
+        
+        # Get Democratic perspective
+        democrats = senate.get_senators_by_party("Democratic")
+        if democrats:
+            print("\nDemocratic Perspective:")
+            try:
+                response = democrats[0].run(f"What is the Democratic position on: {issue}")
+                print(f"  {response[:200]}...")
+            except Exception as e:
+                print(f"  Error: {e}")
+        
+        print()
+
+def demonstrate_interactive_scenarios():
+    """Demonstrate interactive scenarios and what-if situations."""
+    print("\n" + "=" * 80)
+    print("🎮 INTERACTIVE SCENARIOS")
+    print("=" * 80)
+    
+    senate = SenatorSimulation()
+    
+    scenarios = [
+        {
+            "title": "Supreme Court Nomination",
+            "description": "Simulate a Supreme Court nomination vote",
+            "action": lambda: senate.simulate_vote(
+                "Confirmation of a Supreme Court nominee with moderate judicial philosophy",
+                ["Kyrsten Sinema", "Lisa Murkowski", "Mark Kelly", "Tom Cotton", "Alex Padilla"]
+            )
+        },
+        {
+            "title": "Budget Reconciliation",
+            "description": "Simulate a budget reconciliation vote (simple majority)",
+            "action": lambda: senate.simulate_vote(
+                "Budget reconciliation bill including healthcare, climate, and tax provisions",
+                ["Katie Britt", "Mark Kelly", "Michael Bennet", "Tom Cotton", "Richard Blumenthal"]
+            )
+        },
+        {
+            "title": "Bipartisan Infrastructure Deal",
+            "description": "Simulate a bipartisan infrastructure agreement",
+            "action": lambda: senate.simulate_debate(
+                "Bipartisan infrastructure deal with traditional funding mechanisms",
+                ["Kyrsten Sinema", "Lisa Murkowski", "Mark Kelly", "Tom Carper", "Chris Coons"]
+            )
+        }
+    ]
+    
+    for i, scenario in enumerate(scenarios, 1):
+        print(f"\n🎯 Scenario #{i}: {scenario['title']}")
+        print(f"Description: {scenario['description']}")
+        print("-" * 60)
+        
+        try:
+            result = scenario['action']()
+            
+            if 'votes' in result:  # Vote result
+                print("Vote Results:")
+                for senator, vote in result['votes'].items():
+                    print(f"  {senator}: {vote}")
+                print(f"Outcome: {result['results']['outcome']}")
+            
+            elif 'transcript' in result:  # Debate result
+                print("Debate Positions:")
+                for entry in result['transcript'][:3]:  # Show first 3
+                    print(f"\n{entry['senator']} ({entry['party']}):")
+                    print(f"  {entry['position'][:150]}...")
+        
+        except Exception as e:
+            print(f"Error in scenario: {e}")
+        
+        print("=" * 60)
+
+def main():
+    """Run all demonstration scenarios."""
+    print("🏛️  US SENATE SIMULATION - COMPREHENSIVE DEMONSTRATION")
+    print("=" * 80)
+    print("This demonstration showcases various aspects of the Senate simulation")
+    print("including individual senator responses, debates, votes, and committee hearings.")
+    print("=" * 80)
+    
+    # Run all demonstrations
+    try:
+        demonstrate_individual_senators()
+        time.sleep(2)
+        
+        demonstrate_senate_debates()
+        time.sleep(2)
+        
+        demonstrate_senate_votes()
+        time.sleep(2)
+        
+        demonstrate_committee_hearings()
+        time.sleep(2)
+        
+        demonstrate_party_analysis()
+        time.sleep(2)
+        
+        demonstrate_interactive_scenarios()
+        
+    except KeyboardInterrupt:
+        print("\n\n⏹️  Demonstration interrupted by user.")
+    except Exception as e:
+        print(f"\n\n❌ Error during demonstration: {e}")
+    
+    print("\n" + "=" * 80)
+    print("✅ SENATE SIMULATION DEMONSTRATION COMPLETE")
+    print("=" * 80)
+    print("The simulation successfully demonstrated:")
+    print("• Individual senator characteristics and responses")
+    print("• Senate debates on various topics")
+    print("• Voting simulations on different bills")
+    print("• Committee hearing scenarios")
+    print("• Party-based analysis and comparisons")
+    print("• Interactive scenarios and what-if situations")
+    print("\nYou can now use the SenatorSimulation class to create your own scenarios!")
+
+if __name__ == "__main__":
+    main() 

swarms/structs/agent.py

@@ -615,7 +615,7 @@ class Agent:
             self.tool_handling()
 
         if self.llm is None:
-            self.llm = self.llm_handling(*args, **kwargs)
+            self.llm = self.llm_handling()
 
         if self.random_models_on is True:
             self.model_name = set_random_models_for_agents()