✅什么是Function Calling？
典型回答
**Function Calling都是一种让大模型会使用工具的方案。**如果一个大模型不会用工具，那就只能是一个简单的对话机器人，并且只能根据以往训练的数据进行对话。
如果你想让给大模型能够帮你联网查询、帮你操作本地文件、帮你调外部服务，都需要让他会用工具，而Function Call，MCP、A2A都是可以让大模型更好的使用工具的技术方案。
Function Call是Open AI提出的，最开始时只针对自家的GPT用的，他需要先通过结构化的方式定义出来有哪些工具。如：
import json
def get_current_temperature(location: str, unit: str = "celsius"):
"""Get current temperature at a location.
Args:
location: The location to get the temperature for, in the format "City, State, Country".
unit: The unit to return the temperature in. Defaults to "celsius". (choices: ["celsius", "fahrenheit"])
Returns:
the temperature, the location, and the unit in a dict
"""
return {
"temperature": 26.1,
"location": location,
"unit": unit,
}
def get_temperature_date(location: str, date: str, unit: str = "celsius"):
"""Get temperature at a location and date.
Args:
location: The location to get the temperature for, in the format "City, State, Country".
date: The date to get the temperature for, in the format "Year-Month-Day".
unit: The unit to return the temperature in. Defaults to "celsius". (choices: ["celsius", "fahrenheit"])
Returns:
the temperature, the location, the date and the unit in a dict
"""
return {
"temperature": 25.9,
"location": location,
"date": date,
"unit": unit,
}
def get_function_by_name(name):
if name == "get_current_temperature":
return get_current_temperature
if name == "get_temperature_date":
return get_temperature_date
TOOLS = [
{
"type": "function",
"function": {
"name": "get_current_temperature",
"description": "Get current temperature at a location.",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": 'The location to get the temperature for, in the format "City, State, Country".',
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"],
"description": 'The unit to return the temperature in. Defaults to "celsius".',
},
},
"required": ["location"],
},
},
},
{
"type": "function",
"function": {
"name": "get_temperature_date",
"description": "Get temperature at a location and date.",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": 'The location to get the temperature for, in the format "City, State, Country".',
},
"date": {
"type": "string",
"description": 'The date to get the temperature for, in the format "Year-Month-Day".',
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"],
"description": 'The unit to return the temperature in. Defaults to "celsius".',
},
},
"required": ["location", "date"],
},
},
},
]
MESSAGES = [
{"role": "system", "content": "You are Qwen, created by Alibaba Cloud. You are a helpful assistant.\n\nCurrent Date: 2024-09-30"},
{"role": "user", "content": "What's the temperature in San Francisco now? How about tomorrow?"},
]其中的TOOLS部分就是关于工具的定义，对于每个工具，它是一个具有两个字段的JSON object：
type：string，用于指定工具类型，目前仅"function"有效function：object，详细说明了如何使用该函数
对于每个function，它是一个具有三个字段的JSON object：
name：string 表示函数名称description：string 描述函数用途parameters：JSON Schema，用于指定函数接受的参数。请参阅链接文档以了解如何构建JSON Schema。值得注意的字段包括type、required和enum。
大多数框架使用“工具”格式，有些可能使用“函数”格式。根据命名，应该很明显应该使用哪一个。
定义好了工具之后，再向他提问的时候，将我们的prompts和上面定义的可用的工具都传给LLM，那么他就能根据用户的问题，选择工具去使用，更好的做回答了。