smolagents

# agents/research.py — Agent that writes and executes Python code
from smolagents import CodeAgent, tool, HfApiModel, OpenAIServerModel

# Use any LLM as the engine
model = OpenAIServerModel(model_id="gpt-4o")
# Or local: HfApiModel(model_id="meta-llama/Llama-3.1-70B-Instruct")
# Or Anthropic: AnthropicServerModel(model_id="claude-sonnet-4-20250514")

@tool
def search_web(query: str) -> str:
    """Search the web for information.

    Args:
        query: Search query string
    """
    results = brave_search(query, count=5)
    return "\n".join([f"- {r['title']}: {r['description']}" for r in results])

@tool
def get_stock_price(symbol: str) -> dict:
    """Get current stock price and basic metrics.

    Args:
        symbol: Stock ticker symbol (e.g., AAPL, GOOGL)
    """
    data = yfinance.Ticker(symbol)
    return {
        "price": data.info["currentPrice"],
        "change": data.info["regularMarketChangePercent"],
        "market_cap": data.info["marketCap"],
        "pe_ratio": data.info.get("trailingPE"),
    }

@tool
def create_chart(data: dict, title: str) -> str:
    """Create a chart from data and save as image.

    Args:
        data: Dictionary with x and y values
        title: Chart title
    """
    import matplotlib.pyplot as plt
    plt.figure(figsize=(10, 6))
    plt.plot(data["x"], data["y"])
    plt.title(title)
    path = f"/tmp/{title.replace(' ', '_')}.png"
    plt.savefig(path)
    return f"Chart saved to {path}"

# Create agent
agent = CodeAgent(
    tools=[search_web, get_stock_price, create_chart],
    model=model,
    max_steps=10,
    additional_authorized_imports=["pandas", "numpy", "matplotlib"],
)

# Agent writes and executes Python code to solve the task
result = agent.run(
    "Compare AAPL and MSFT stock performance. "
    "Get their current prices, calculate the PE ratio difference, "
    "and create a comparison chart."
)
# Agent generates code like:
# aapl = get_stock_price("AAPL")
# msft = get_stock_price("MSFT")
# ... creates chart, returns analysis

from smolagents import CodeAgent, ManagedAgent

# Specialist agents
web_agent = CodeAgent(tools=[search_web], model=model)
data_agent = CodeAgent(tools=[get_stock_price, create_chart], model=model,
                        additional_authorized_imports=["pandas", "numpy", "matplotlib"])

# Manager agent delegates to specialists
managed_web = ManagedAgent(agent=web_agent, name="web_researcher",
    description="Searches the web for information")
managed_data = ManagedAgent(agent=data_agent, name="data_analyst",
    description="Analyzes financial data and creates charts")

manager = CodeAgent(
    tools=[],
    model=model,
    managed_agents=[managed_web, managed_data],
)

result = manager.run(
    "Research the latest AI chip market trends, "
    "then analyze NVDA and AMD stock data and create a comparison report."
)

from smolagents import load_tool

# Load tools from Hugging Face Hub
image_gen = load_tool("m-ric/text-to-image", trust_remote_code=True)
translator = load_tool("m-ric/translation", trust_remote_code=True)
speech = load_tool("m-ric/text-to-speech", trust_remote_code=True)

agent = CodeAgent(tools=[image_gen, translator, speech], model=model)

pip install smolagents