Openai Function Calling Model Example

example.py

import json
import requests
import openai
from datetime import datetime
import inspect
import json
from typing import get_type_hints

# Set OpenAI API key
openai.api_key = 'sk-...'

# Function to convert a Python function to JSON representation
def to_json(func) -> str:
    json_representation = dict()
    json_representation['name'] = func.__name__  # Function name
    json_representation['description'] = func.__doc__.strip()  # Function description

    # Get function parameters and their type hints
    parameters = inspect.signature(func).parameters
    func_type_hints = get_type_hints(func)

    json_parameters = dict()
    json_parameters['type'] = 'object'
    json_parameters['properties'] = {}

    # Process each parameter
    for name, param in parameters.items():
        if name == 'return':
            continue

        param_info = {}

        # Parameter description from the default value
        param_info['description'] = inspect.signature(func).parameters[name].default

        param_annotation = func_type_hints.get(name)

        if param_annotation:
            # Convert parameter type hint to JSON type
            if param_annotation.__name__ == 'str':
                param_info['type'] = 'string'
            else:
                param_info['type'] = param_annotation.__name__

        if name == 'self':
            continue

        json_parameters['properties'][name] = param_info

    json_representation['parameters'] = json_parameters

    return json_representation

# Function to format a function call as a string
def format_call(function_call: dict) -> str:
    json_data: dict = json.loads(function_call.__str__())
    
    function_name: str = json_data["name"]
    args_json: str = json_data["arguments"]
    
    args_dict: dict = json.loads(args_json)
    args: str = ', '.join([f"{k}='{v}'" for k, v in args_dict.items()])

    return f"{function_name}({args})"

# Example conversation
prompt = 'whats the weather rn'
conversation = [
    {
        'role': 'assistant',
        'content': f'You are ChatGPT an Artificial Intelligence developed by OpenAI, respond in a concise way, date: {datetime.today().strftime("%Y/%m/%d %H:%M:%S")}, current location: New York, USA'
    },
    {
        'role': 'user',
        'content': prompt
    }
]

# Function to get current weather using OpenWeatherMap API
def get_current_weather(location: str = 'CityName, CountryCode') -> dict:
    """get weather in location"""

    # Make API request to get weather data
    weather_data = requests.get(f'https://openweathermap.org/data/2.5/weather?q={location}&appid=439d4b804bc8187953eb36d2a8c26a02').json()

    # Extract relevant weather information
    return json.dumps(separators=(',', ':'), obj={
        'description': weather_data['weather'][0]['description'],
        'temperature': weather_data['main']['temp'],
        'humidity': weather_data['main']['humidity'],
        # 'wind_speed': weather_data['wind']['speed'],
        # 'unit': 'celsius',
        # 'wind_speed_unit_pronunciation': 'meters per second'
    })

# Convert get_current_weather function to JSON representation
weather_function_json = to_json(get_current_weather)

# Use the Chat API to interact with the model
completion = openai.ChatCompletion.create(model='gpt-3.5-turbo-0613', 
                             messages=conversation, functions=[weather_function_json])

# Add the function call and its result to the conversation
conversation += [json.loads(completion.choices[0].message.__str__())]
conversation += [{
    'role': 'function',
    'name': completion.choices[0].message.function_call.name,
    'content': eval(format_call(completion.choices[0].message.function_call)),
}]

# Continue the conversation with the updated function call
completion = openai.ChatCompletion.create(model='gpt-3.5-turbo-0613', 
                             messages=conversation, functions=[weather_function_json])

# Print the generated response
print(completion.choices[0].message.content)

你是谁？

你好

你好

你是谁？

你好

您好