function-calling.py

import requests

def get_weather(latitude, longitude):
    response = requests.get(f"https://api.open-meteo.com/v1/forecast?latitude={latitude}&longitude={longitude}&current=temperature_2m,wind_speed_10m&hourly=temperature_2m,relative_humidity_2m,wind_speed_10m")
    data = response.json()
    return data['current']['temperature_2m']

from openai import OpenAI
import json

client = OpenAI()

tools = [{
    "type": "function",
    "name": "get_weather",
    "description": "Get current temperature for provided coordinates in celsius.",
    "parameters": {
        "type": "object",
        "properties": {
            "latitude": {"type": "number"},
            "longitude": {"type": "number"}
        },
        "required": ["latitude", "longitude"],
        "additionalProperties": False
    },
    "strict": True
}]

input_messages = [{"role": "user", "content": "What's the weather like in Paris today?"}]

print(f"1 -> Initial Input array {input_messages}")
response = client.responses.create(
    model="gpt-4o",
    input=input_messages,
    tools=tools,
)

# Model extracts the tool call.
tool_call = response.output[0]

# Invoke the tool
args = json.loads(tool_call.arguments)
result = get_weather(args["latitude"], args["longitude"])

# Add the reult of the tool call to input messages so that it can be passed back to the model.
input_messages.append(tool_call)                    
input_messages.append({                              
    "type": "function_call_output",
    "call_id": tool_call.call_id,
    "output": str(result)
})

response_2 = client.responses.create(
    model="gpt-4o",
    input=input_messages,
    tools=tools,
)

print(f"2 -> Invoke the model")
print(f"3 -> Model outputs function to invoke with parameter -> {tool_call}")
print(f"4 -> Invoke the function and get the output - {str(result)}")
print(f"5 -> Append the function call and result of the function to input messages - {input_messages}")
print(f"6 -> Call the model again - {response_2.output_text}")