Sample agent with Huggingface Smolagent framework

ai_smol_agent.py

"""
This script builds an AI agent using SmolAgents, OpenAI GPT, and Serper.dev.
The agent performs a web search using the Serper.dev API and summarizes the results using GPT-4.
"""

# Import required libraries
from smolagents import tool, CodeAgent, LiteLLMModel, HfApiModel, TransformersModel
from smolagents.prompts import CODE_SYSTEM_PROMPT
import http.client
import json
import os
from dotenv import load_dotenv

# Load environment variables from .env file
load_dotenv()

# Define the Web Search Tool using @tool decorator
@tool
def web_search(query: str) -> list:
    """
    Performs a web search using Serper.dev and retrieves the complete results.

    Args:
        query: The search query to perform.

    Returns:
        list: A list of all results retrieved from the web search.
    """
    # Fetch the API key from environment variables
    api_key = os.getenv("SERPER_API_KEY")
    if not api_key:
        raise ValueError("SERPER_API_KEY is not set in the environment variables.")

    # Create the HTTP connection and send the POST request
    conn = http.client.HTTPSConnection("google.serper.dev")
    payload = json.dumps({"q": query})
    headers = {
        "X-API-KEY": api_key,
        "Content-Type": "application/json"
    }

    conn.request("POST", "/search", payload, headers)
    res = conn.getresponse()
    data = res.read()
    conn.close()

    # Parse and return the full search results
    response_json = json.loads(data.decode("utf-8"))
    results = response_json.get("organic", [])
    print("Full Results:", results)  # Debugging log
    return results

# Define the LLM Model
model = LiteLLMModel(
    model_id="gpt-4",                      # Specify the model to use
    api_base="https://api.openai.com/v1",  # OpenAI API endpoint
    api_key=os.getenv("OPENAI_API_KEY")    # OpenAI API key from environment variables
)

#model=HfApiModel(token="YOUR_HUGGINGFACEHUB_API_TOKEN"),        # Default model - Qwen/Qwen2.5-Coder-32B-Instruct   

#model = TransformersModel(model_id="HuggingFaceTB/SmolLM-135M-Instruct")

#model_id = "meta-llama/Llama-3.3-70B-Instruct" 
#model=HfApiModel(model_id=model_id, token="YOUR_HUGGINGFACEHUB_API_TOKEN"), #Pro Model

modified_system_prompt = CODE_SYSTEM_PROMPT + "\nChanges" # Change the system prompt here


# Create the CodeAgent with tools and model
agent = CodeAgent(
    tools= [web_search],  # Register the web_search tool
    model=model,
    #system_prompt=modified_system_prompt,
    verbose_level= 2
)

def main():
    """
    Main function to run the AI agent workflow.
    Accepts a user query, performs a web search, and summarizes the results.
    """
    import argparse

    # Set up argument parsing for user input
    parser = argparse.ArgumentParser(description="Run the AI Agent Workflow.")
    parser.add_argument("--query", type=str, help="Query for web search", required=True)
    args = parser.parse_args()

    # Fetch the query from command-line arguments
    query = args.query
    print(f"Running Agent with query: '{query}'")

    # Execute the agent to handle web search and summarization
    response = agent.run(f"Search the web for '{query}' and use the complete results and give detailed quick summary.")
    print("Final Output:")
    print(response)

if __name__ == "__main__":
    main()