Agents

from swarms import Agent

# Initialize a basic agent
agent = Agent(
    model_name="gpt-4o-mini",
    max_loops=1,
    interactive=True,
)

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

from swarms import Agent

# Create a production-ready agent
agent = Agent(
    # Identity
    agent_name="Financial-Analyst",
    agent_description="Expert in financial analysis and market research",
    
    # LLM Configuration
    model_name="gpt-4o-mini",
    max_tokens=4096,
    temperature=0.5,
    
    # Execution Control
    max_loops=5,
    dynamic_loops=True,
    stopping_token="<DONE>",
    
    # System Behavior
    system_prompt="""You are a financial analyst with expertise in market research.
    Your role is to analyze financial data and provide actionable insights.
    Always cite your sources and provide confidence levels for predictions.""",
    
    # Memory & Context
    context_length=16000,
    dynamic_context_window=True,
    return_history=True,
    
    # Tools (if applicable)
    tools=[search_tool, calculator_tool],
    
    # Output Control
    streaming_on=True,
    verbose=True,
)

# Execute a complex task
result = agent.run(
    "Analyze the current state of the renewable energy market and provide investment recommendations"
)

agent = Agent(
    model_name="gpt-4o-mini",
    max_loops="auto",  # Agent will determine when to stop
)

agent = Agent(
    model_name="gpt-4o",
    multi_modal=True,
)

response = agent.run(
    task="Analyze this chart",
    img="/path/to/chart.png"
)

def streaming_callback(chunk: str):
    print(chunk, end="", flush=True)

agent = Agent(
    model_name="gpt-4o-mini",
    streaming_callback=streaming_callback,
)

response = agent.run("Tell me a story")

from swarms.memory import ChromaDB

memory = ChromaDB()

agent = Agent(
    model_name="gpt-4o-mini",
    long_term_memory=memory,
)