函数调用
函数调用允许模型为你定义的函数生成结构化参数。模型本身不会直接执行函数，而是输出 JSON，你可以在代码中据此调用该函数。
工作原理
- 定义工具 — 在请求中提供函数 schema
- 模型决策 — 模型决定是否调用一个或多个工具
- 由你执行 — 解析模型的工具调用并运行实际函数
- 返回结果 — 将函数输出回传给模型
- 模型响应 — 模型基于工具结果生成最终回答
定义工具
from openai import OpenAI
client = OpenAI(
base_url="https://openapi.linkwo.ai/v1",
api_key="YOUR_API_KEY"
)
tools = [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get the current weather for a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "City name, e.g., Beijing"
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"],
"description": "Temperature unit"
}
},
"required": ["location"]
}
}
}
]完整示例
import json
response = client.chat.completions.create(
model="deepseek/deepseek-v4-pro",
messages=[{"role": "user", "content": "What's the weather like in Shanghai?"}],
tools=tools,
tool_choice="auto"
)
message = response.choices[0].message
if message.tool_calls:
for tool_call in message.tool_calls:
function_name = tool_call.function.name
function_args = json.loads(tool_call.function.arguments)
# Execute the function
if function_name == "get_weather":
result = get_weather(**function_args)
# Send result back to the model
response = client.chat.completions.create(
model="deepseek/deepseek-v4-pro",
messages=[
{"role": "user", "content": "What's the weather like in Shanghai?"},
message,
{
"role": "tool",
"tool_call_id": tool_call.id,
"content": str(result)
}
]
)
print(response.choices[0].message.content)工具选择
| 值 | 说明 |
|---|---|
auto | 由模型决定是否调用工具（默认） |
none | 模型不会调用任何工具 |
required | 模型必须至少调用一个工具 |
{"type": "function", "function": {"name": "..."}} | 强制调用指定函数 |
多个工具
你可以在单次请求中定义多个工具：
tools = [
{
"type": "function",
"function": {
"name": "search_products",
"description": "Search the product catalog",
"parameters": {
"type": "object",
"properties": {
"query": {"type": "string"},
"category": {"type": "string"},
"max_price": {"type": "number"}
},
"required": ["query"]
}
}
},
{
"type": "function",
"function": {
"name": "place_order",
"description": "Place an order for a product",
"parameters": {
"type": "object",
"properties": {
"product_id": {"type": "string"},
"quantity": {"type": "integer"}
},
"required": ["product_id", "quantity"]
}
}
}
]最佳实践
- 编写清晰的描述 — 模型依赖函数和参数的描述来决定何时以及如何调用它们
- 为受限值使用 enum — 尽可能用
enum限定参数取值 - 标注必填字段 — 始终将必要参数标记为
required - 优雅地处理错误 — 将错误信息作为工具结果返回，便于模型自我纠正
- 控制工具数量 — 工具过多会让模型困惑，请保持聚焦
并行工具调用
部分模型支持在单次响应中调用多个工具。可遍历 message.tool_calls 来处理：
if message.tool_calls:
tool_results = []
for tool_call in message.tool_calls:
result = execute_function(tool_call.function.name, json.loads(tool_call.function.arguments))
tool_results.append({
"role": "tool",
"tool_call_id": tool_call.id,
"content": str(result)
})