Contents

Welcome to Agent Party

This guide will help you get started with Agent Party, the enterprise platform for AI agent collaboration. Whether you’re a developer, organization, or AI enthusiast, we’ll walk you through the steps to begin using the platform.

For Developers

1. Clone the Repository

Start by cloning the Agent Party repository:

git clone https://github.com/agent-party/agent-party.git
cd agent-party

2. Install Dependencies

Agent Party uses Poetry for dependency management:

# Install Poetry if you don't have it
curl -sSL https://install.python-poetry.org | python3 -

# Install dependencies
poetry install

3. Set Up the Environment

Create a .env file with necessary configuration:

cp .env.example .env
# Edit .env with your settings

Key configuration items:

  • Database connection strings
  • API keys for language models
  • Storage credentials
  • Kafka connection details

4. Run the Dev Environment

Start the development environment using Docker Compose:

docker-compose up -d

This will start:

  • Neo4j database
  • Kafka and Zookeeper
  • Redis
  • MinIO object storage

5. Run the Application

Start the Agent Party application:

poetry run python -m agent_party

The API will be available at http://localhost:8000 and the web UI at http://localhost:8000/ui.

6. Try the Quickstart Example

Explore the quickstart example to see Agent Party in action:

poetry run python examples/quickstart.py

This example demonstrates:

  • Agent registration
  • Team formation
  • Task execution
  • Result visualization

For Organizations

If you’re evaluating Agent Party for your organization, follow these steps:

1. Assess Your Requirements

Consider your specific needs:

  • What kind of AI collaboration do you need?
  • What existing tools need integration?
  • What security and compliance requirements do you have?
  • What is your expected scale?

2. Explore the Enterprise Evaluation Guide

Download our Enterprise Evaluation Guide for a comprehensive assessment framework, including:

  • Technical requirements
  • Security checklist
  • Integration points
  • ROI calculator
  • Implementation timeline

3. Schedule a Demo

Contact our team to schedule a personalized demo tailored to your use case.

4. Plan Your Implementation

Review our implementation resources:

5. Explore Success Stories

Learn from organizations already using Agent Party:

Core Components Walkthrough

To understand the platform better, let’s walk through its core components:

Doorman (Trust & Access Control)

The security gateway managing identity, permissions, and trust.

Getting Started with Doorman:

from agent_party.components import Doorman

# Initialize with your authentication settings
doorman = Doorman(
    auth_provider="oauth",
    auth_config={
        "client_id": "your-client-id",
        "client_secret": "your-client-secret",
        "redirect_uri": "https://your-app.com/callback"
    }
)

# Verify and decode tokens
user_info = doorman.authenticate_token(token)

# Check permissions
if doorman.authorize(user_id, "team:create"):
    # User is authorized to create teams
    ...

DJ (Intelligent Orchestration)

The coordination engine that routes requests and manages workflows.

Getting Started with DJ:

from agent_party.components import DJ

# Initialize the DJ component
dj = DJ()

# Get team recommendations for a task
recommended_team = await dj.recommend_team(
    task_id="task-123",
    required_capabilities=["research", "writing", "data_analysis"],
    max_team_size=3
)

# Print recommended team
for agent in recommended_team:
    print(f"Agent: {agent['name']}, Role: {agent['role']}")

Bartender (User Interface)

The human-facing layer making AI collaboration intuitive.

Getting Started with Bartender:

from agent_party.components import Bartender

# Initialize the Bartender
bartender = Bartender()

# Create a team for a task
team_id = await bartender.create_team(
    task_id="task-123",
    team_name="Research Team",
    agents=recommended_team
)

# Submit a task to the team
response = await bartender.submit_task(
    team_id=team_id,
    instructions="Research the impact of AI on healthcare and provide a summary",
    format="markdown"
)

# Display the team's response
print(response.result)

Key Workflows

Creating an Agent

from agent_party.agent import AgentFactory

# Create an agent factory
factory = AgentFactory()

# Create a specialized agent
agent_id = await factory.create_agent(
    template_id="researcher-template",
    name="Healthcare Researcher",
    parameters={
        "expertise": ["medical_research", "clinical_trials", "healthcare_policy"],
        "communication_style": "detailed",
        "research_depth": "thorough"
    }
)

print(f"Created agent with ID: {agent_id}")

Forming a Team

from agent_party.team import TeamFormation

# Initialize team formation service
team_formation = TeamFormation()

# Form a team based on task requirements
team = await team_formation.form_team(
    task_description="Analyze clinical trial data and prepare a research report",
    required_capabilities=[
        {"name": "data_analysis", "importance": 0.9},
        {"name": "medical_knowledge", "importance": 0.8},
        {"name": "report_writing", "importance": 0.7}
    ],
    max_team_size=3
)

print(f"Team formed with {len(team.agents)} agents")

Executing a Task

from agent_party.task import TaskExecution

# Initialize task execution service
task_execution = TaskExecution()

# Execute a task with a team
task_result = await task_execution.execute_task(
    team_id=team.id,
    instructions="Analyze the attached clinical trial data and provide a detailed report on efficacy and safety findings",
    attachments=["clinical_trial_data.csv"],
    output_format="markdown"
)

print(f"Task completed with status: {task_result.status}")
print(f"Output: {task_result.output}")

Next Steps

After getting started, explore these resources to deepen your understanding:

  1. Architecture Documentation
  2. Agent System Reference
  3. Team Formation Guide
  4. API Reference
  5. Contribution Guidelines

Community Resources

Join the Agent Party community:

Support

If you need help: