AI宝库-ChatGPT插件能力

# 普通代码
# 注意新版的python SDK中openai函数已经发生了更新
# 历史版本
messages = [
    {"role": "user", "content": "Hello stone!"}
]
completion = openai.ChatCompletion.create(
    model="gpt-3.5-turbo",
    messages=messages
)

# 新版中
completion = openai.chat.completions.create(
    model="gpt-3.5-turbo",
    messages=[
        {"role": "user", "content": "Hello stone!"}
    ],
)

# Function calling
completion = openai.ChatCompletion.create(
  model="gpt-3.5-turbo",
  messages=messages,
  
  # 增加额外两个参数
  functions=functions,
  function_call="auto", # auto is default, but we'll be explicit
)

# 1.1 定义模拟获取天气的本地函数
def get_current_weather(location, unit):
    # 可以对接第三方应用系统的API
    return f"It's 0 {unit} in {location}"

  ChatCompletion(
  id='chatcmpl-8K54AkuSdoiwk8Jw2B8zcPs5VibAZ', 
  choices=[
    Choice(
      finish_reason='function_call', 
      index=0, 
      message=ChatCompletionMessage(
        content=None, role='assistant', 
        function_call=FunctionCall(
          arguments='{\n  "location": "Xian",\n  "unit": "celsius"\n}', 
          name='get_current_weather'
        ), 
        tool_calls=None
      ))
    ], 
    created=1699796726, 
    model='gpt-3.5-turbo-0613', 
    object='chat.completion', 
    system_fingerprint=None,
    usage=CompletionUsage(
      completion_tokens=25, 
      prompt_tokens=89, 
      total_tokens=114
    )
  )

ChatCompletionMessage(
    content='The weather in Xian today is 0 degrees Celsius.', 
    role='assistant', 
    function_call=None, 
    tool_calls=None
)

# function_calling.py
import openai
import json

openai.api_key = 'sk-xxxxxxxx' # 密钥

# 1. 定义函数
# 1.1 定义模拟获取天气的本地函数
def get_current_weather(location, unit):
    # Call the weather API
    return f"It's 0 {unit} in {location}"

# 1.2 定义函数字典方便调用
function_dict = {
    "get_current_weather": get_current_weather,
}

# 1.3 定义chat接口需要的函数
functions = [
    {
        "name": "get_current_weather",
        "description": "Get the current weather in a given location",
        "parameters": {
            "type": "object",
            "properties": {
                "location": {
                    "type": "string",
                    "description": "The city and state, e.g. ShaanXi, Xian",
                },
                "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
            },
            "required": ["location"],
        },
    }
]

# 2. 第一次调用chat接口，返回的是函数调用的提示
messages = [
    {"role": "user", "content": "What's the weather like in Xian today with celsius?"}]
completion = openai.chat.completions.create(
    model="gpt-3.5-turbo",
    messages=messages,
    functions=functions,
    function_call="auto",  # auto is default, but we'll be explicit
)
print(completion)

# 3. 从结果接口的结果中获取函数调用的参数 进行本地函数调用
# 3.1 获取函数调用的参数
response_message = completion.choices[0].message
function_name = response_message.function_call.name
function_args = json.loads(response_message.function_call.arguments)
# 3.2 调用本地函数
function_response = function_dict.get(function_name)(**function_args)
# 3.3 将本地函数的结果作为chat接口的输入
messages.append(response_message)
messages.append({
    "role": "function",
    "name": function_name,
    "content": function_response,
})

# 4. 第二次调用chat接口，返回的是chat的最终结果
completion_final = openai.chat.completions.create(
    model="gpt-3.5-turbo",
    messages=messages,
)

print(completion_final.choices[0].message)