LLM agent that can use external tools

import requests
import wolframalpha

def weather_lookup(location):
    api_key = "your_weather_api_key"
    url = f"http://api.weatherapi.com/v1/current.json?key={api_key}&q={location}"
    response = requests.get(url)
    data = response.json()
    return f"The current temperature in {location} is {data['current']['temp_c']}°C"

def wolfram_query(query):
    client = wolframalpha.Client("your_wolfram_alpha_app_id")
    res = client.query(query)
    return next(res.results).text

tools = {
    "weather_lookup": weather_lookup,
    "wolfram_query": wolfram_query
}

def tool_using_agent(user_input):
    tool_selection_prompt = f"""
    Based on the user's input, determine if a tool should be used to answer the question.
    Available tools: {', '.join(tools.keys())}

    User input: {user_input}

    If a tool should be used, respond with the tool name and the parameter to pass to the tool.
    If no tool is needed, respond with "No tool needed."

    Response:
    """

    tool_decision = llm.generate(tool_selection_prompt)

    if tool_decision.startswith("No tool needed"):
        return llm.generate(f"User: {user_input}\nAssistant:")
    else:
        tool_name, parameter = tool_decision.split(', ')
        tool_result = tools[tool_name](parameter)

        final_response_prompt = f"""
        User asked: {user_input}
        Tool used: {tool_name}
        Tool result: {tool_result}

        Please provide a natural language response to the user based on this information:
        """

        return llm.generate(final_response_prompt)

# Usage
print(tool_using_agent("What's the weather like in New York?"))
print(tool_using_agent("What's the square root of 256?"))