Creating Agents

from swarms import Agent

# Create a basic agent
agent = Agent(
    agent_name="my-agent",
    model_name="gpt-5.4",
    max_loops=1,
)

# Run the agent
response = agent.run("What are the key benefits of using a multi-agent system?")
print(response)

from swarms import Agent

agent = Agent(
    model_name="gpt-5.4",
    max_loops=1,
)

response = agent.run("Generate a report on the financials.")
print(response)

agent = Agent(
    agent_name="Financial-Analyst",
    agent_description="An expert financial analyst specializing in market analysis and reporting",
    model_name="claude-sonnet-4-6",
    max_loops=1,
    verbose=True,
)

SYSTEM_PROMPT = """
You are a senior financial analyst with expertise in:
- Financial statement analysis
- Market research and competitor analysis
- Investment recommendations
- Risk assessment

Provide detailed, data-driven insights with proper citations.
"""

agent = Agent(
    agent_name="Financial-Expert",
    system_prompt=SYSTEM_PROMPT,
    model_name="claude-sonnet-4-6",
    max_loops=1,
)

agent = Agent(
    agent_name="Assistant",
    model_name="gpt-5.4",
    max_loops=5,
    interactive=True,  # Enable interactive mode
    user_name="User",
    custom_exit_command="exit",
)

# Agent will prompt for user input in a loop
agent.run("Hello! How can I help you today?")

agent = Agent(
    agent_name="Research-Agent",
    model_name="claude-sonnet-4-6",
    max_loops="auto",  # Autonomous loop mode
    reasoning_prompt_on=True,
    dynamic_temperature_enabled=True,
    verbose=True,
)

response = agent.run(
    "Research the latest trends in AI and create a comprehensive report"
)

agent = Agent(
    agent_name="Reliable-Agent",
    fallback_models=[
        "claude-sonnet-4-6",           # Primary model
        "gpt-5.4",      # First fallback
        "gpt-3.5-turbo"     # Final fallback
    ],
    max_loops=1,
)

# Agent will automatically try fallback models if primary fails
response = agent.run("Generate a report")

import os

# Set your Swarms API key
os.environ["SWARMS_API_KEY"] = "your-api-key"

agent = Agent(
    model_name="claude-sonnet-4-6",
    marketplace_prompt_id="550e8400-e29b-41d4-a716-446655440000",  # UUID from marketplace
    max_loops=1,
)

# System prompt is automatically loaded from the marketplace
response = agent.run("Execute the marketplace prompt task")

# Good
agent = Agent(
    agent_name="Financial-Analyst",
    agent_description="Expert in financial analysis",
    model_name="claude-sonnet-4-6",
)

# Avoid
agent = Agent(model_name="claude-sonnet-4-6")  # Uses default name

# Good - Specific and detailed
system_prompt = """
You are a healthcare data analyst specializing in:
1. Patient data analysis
2. Medical coding (ICD-10, CPT)
3. HIPAA compliance
4. Clinical research metrics

Always maintain patient privacy and follow HIPAA guidelines.
"""

# Avoid - Too vague
system_prompt = "You are a helpful assistant."

# For simple tasks
agent = Agent(max_loops=1)  # Single response

# For multi-step reasoning
agent = Agent(max_loops=5)  # Fixed iterations

# For autonomous tasks
agent = Agent(max_loops="auto")  # Dynamic execution

agent = Agent(
    model_name="gpt-5.4",
    verbose=True,  # See detailed logs
    print_on=True,  # Print agent responses
)

agent = Agent(
    agent_name="Research-Agent",
    model_name="claude-sonnet-4-6",
    autosave=True,  # Automatically save state
    saved_state_path="./agent_states/",
)

import os

# Set API keys
os.environ["OPENAI_API_KEY"] = "your-api-key"
os.environ["WORKSPACE_DIR"] = "agent_workspace"

# Create agent
agent = Agent(
    model_name="claude-sonnet-4-6",
    max_loops=1,
)

research_agent = Agent(
    agent_name="Researcher",
    system_prompt="You are an expert researcher. Provide detailed, cited information.",
    model_name="claude-sonnet-4-6",
    max_loops=3,
    temperature=0.5,
    verbose=True,
)

writer_agent = Agent(
    agent_name="Writer",
    system_prompt="You are a professional writer. Create engaging, well-structured content.",
    model_name="claude-sonnet-4-6",
    max_loops=1,
    temperature=0.7,
)

code_agent = Agent(
    agent_name="Code-Generator",
    system_prompt="You are an expert software engineer. Write clean, documented code.",
    model_name="claude-sonnet-4-6",
    max_loops=2,
    temperature=0.3,  # Lower temperature for more deterministic output
)