结构化输出

curl https://tokendog.io/v1/chat/completions \
  -H "Authorization: Bearer $TOKENDOG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model":"gpt-5",
    "messages":[{"role":"user","content":"提取：张三，28岁"}],
    "response_format":{"type":"json_schema","json_schema":{
      "name":"person","schema":{"type":"object",
        "properties":{"name":{"type":"string"},"age":{"type":"integer"}},
        "required":["name","age"],"additionalProperties":false}}}
  }'

from openai import OpenAI
client = OpenAI(base_url="https://tokendog.io/v1", api_key="YOUR_TOKENDOG_API_KEY")
resp = client.chat.completions.create(
    model="gpt-5",
    messages=[{"role":"user","content":"提取：张三，28岁"}],
    response_format={"type":"json_schema","json_schema":{
        "name":"person","schema":{"type":"object",
            "properties":{"name":{"type":"string"},"age":{"type":"integer"}},
            "required":["name","age"],"additionalProperties":False}}},
)
print(resp.choices[0].message.content)

import OpenAI from "openai";
const client = new OpenAI({ baseURL:"https://tokendog.io/v1", apiKey:"YOUR_TOKENDOG_API_KEY" });
const resp = await client.chat.completions.create({
  model:"gpt-5",
  messages:[{role:"user",content:"提取：张三，28岁"}],
  response_format:{type:"json_schema",json_schema:{
    name:"person",schema:{type:"object",
      properties:{name:{type:"string"},age:{type:"integer"}},
      required:["name","age"],additionalProperties:false}}},
});
console.log(resp.choices[0].message.content);