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Building and Integrating Tools for Your Agent

In this section, we’ll grant Alfred access to the web, enabling him to find the latest news and global updates. Additionally, he’ll have access to weather data and Hugging Face hub model download statistics, so that he can make relevant conversation about fresh topics.

##
Give Your Agent Access to the Web

Remember that we want Alfred to establish his presence as a true renaissance host, with a deep knowledge of the world.

To do so, we need to make sure that Alfred has access to the latest news and information about the world.

Let’s start by creating a web search tool for Alfred!

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    from smolagents import DuckDuckGoSearchTool

    # Initialize the DuckDuckGo search tool
    search_tool = DuckDuckGoSearchTool()

    # Example usage
    results = search_tool("Who's the current President of France?")
    print(results)

Expected output:

    The current President of France in Emmanuel Macron.

##
Creating a Custom Tool for Weather Information to Schedule the Fireworks

The perfect gala would have fireworks over a clear sky, we need to make sure the fireworks are not cancelled due to bad weather.

Let’s create a custom tool that can be used to call an external weather API and get the weather information for a given location.

For the sake of simplicity, we're using a dummy weather API for this example. If you want to use a real weather API, you could implement a weather tool that uses the OpenWeatherMap API, like in Unit 1.
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    from smolagents import Tool
    import random

    class WeatherInfoTool(Tool):
        name = "weather_info"
        description = "Fetches dummy weather information for a given location."
        inputs = {
            "location": {
                "type": "string",
                "description": "The location to get weather information for."
            }
        }
        output_type = "string"

        def forward(self, location: str):
            # Dummy weather data
            weather_conditions = [
                {"condition": "Rainy", "temp_c": 15},
                {"condition": "Clear", "temp_c": 25},
                {"condition": "Windy", "temp_c": 20}
            ]
            # Randomly select a weather condition
            data = random.choice(weather_conditions)
            return f"Weather in {location}: {data['condition']}, {data['temp_c']}°C"

    # Initialize the tool
    weather_info_tool = WeatherInfoTool()

##
Creating a Hub Stats Tool for Influential AI Builders

In attendance at the gala are the who’s who of AI builders. Alfred wants to impress them by discussing their most popular models, datasets, and spaces. We’ll create a tool to fetch model statistics from the Hugging Face Hub based on a username.

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    from smolagents import Tool
    from huggingface_hub import list_models

    class HubStatsTool(Tool):
        name = "hub_stats"
        description = "Fetches the most downloaded model from a specific author on the Hugging Face Hub."
        inputs = {
            "author": {
                "type": "string",
                "description": "The username of the model author/organization to find models from."
            }
        }
        output_type = "string"

        def forward(self, author: str):
            try:
                # List models from the specified author, sorted by downloads
                models = list(list_models(author=author, sort="downloads", direction=-1, limit=1))

                if models:
                    model = models[0]
                    return f"The most downloaded model by {author} is {model.id} with {model.downloads:,} downloads."
                else:
                    return f"No models found for author {author}."
            except Exception as e:
                return f"Error fetching models for {author}: {str(e)}"

    # Initialize the tool
    hub_stats_tool = HubStatsTool()

    # Example usage
    print(hub_stats_tool("facebook")) # Example: Get the most downloaded model by Facebook

Expected output:

    The most downloaded model by facebook is facebook/esmfold_v1 with 12,544,550 downloads.

With the Hub Stats Tool, Alfred can now impress influential AI builders by discussing their most popular models.

##
Integrating Tools with Alfred

Now that we have all the tools, let’s integrate them into Alfred’s agent:

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    from smolagents import CodeAgent, InferenceClientModel

    # Initialize the Hugging Face model
    model = InferenceClientModel()

    # Create Alfred with all the tools
    alfred = CodeAgent(
        tools=[search_tool, weather_info_tool, hub_stats_tool],
        model=model
    )

    # Example query Alfred might receive during the gala
    response = alfred.run("What is Facebook and what's their most popular model?")

    print("🎩 Alfred's Response:")
    print(response)

Expected output:

    🎩 Alfred's Response:
    Facebook is a social networking website where users can connect, share information, and interact with others. The most downloaded model by Facebook on the Hugging Face Hub is ESMFold_v1.

##
Conclusion

By integrating these tools, Alfred is now equipped to handle a variety of tasks, from web searches to weather updates and model statistics. This ensures he remains the most informed and engaging host at the gala.

Try implementing a tool that can be used to get the latest news about a specific topic.

When you’re done, implement your custom tools in the `tools.py` file.

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