Structured Output

Some of our models are compatible with OpenAI structured output, so they support using the OpenAI SDK to utilize this capability.

Currently supported models include:

• inf-chat-int-v1

Example

Input Python class, output Python object

from pydantic import BaseModel
from openai import OpenAI
import os

client = OpenAI(
    base_url="https://api.infly.cn/v1",
    api_key=os.getenv("INF_OPENAPI_API_KEY"),
)

class Weather(BaseModel):
    location: str
    weather_state: str
    temperature: int

completion = client.beta.chat.completions.parse(
    model="inf-chat-int-v1",
    messages=[
        {"role": "system", "content": "Extract the weather from the following text"},
        {"role": "user", "content": "The weather in Xuhui, Shanghai is sunny today, with a temperature of 25 degrees"},
    ],
    response_format=Weather,
)

weather = completion.choices[0].message.parsed

print(weather)

# This will print
# Weather(location='Xuhui, Shanghai', weather_state='sunny', temperature=25)

Input JSON schema, output JSON

JSON Schema is a powerful standard for defining and validating JSON data structures.

import os
from openai import OpenAI
from pydantic import BaseModel


client = OpenAI(
    base_url="https://api.infly.cn/v1",
    api_key=os.getenv("INF_OPENAPI_API_KEY"),
)


weather_json_schema = {
    "type": "object",
    "properties": {
        "location": {"type": "string"},
        "weather_state": {"type": "string"},
        "temperature": {"type": "integer"},
    },
    "required": ["location", "weather_state", "temperature"],
    "additionalProperties": False,
}

# or 

class Weather(BaseModel):
    location: str
    weather_state: str
    temperature: int


weather_json_schema = Weather.model_json_schema()


completion = client.chat.completions.create(
    model="inf-chat-int-v1",
    messages=[
        {"role": "system", "content": "Extract the weather from the following text"},
        {"role": "user", "content": "It is sunny in Xuhui Riverside, Shanghai today, with a temperature of 25 degrees"},
    ],
    response_format={
            "type": "json_schema",
            "json_schema": {
                "name": "Weather",
                "schema": weather_json_schema,
            }
        }
)

print(completion.choices[0].message.content)

# Will print:
# {"location": "Xuhui Riverside, Shanghai", "weather_state": "sunny", "temperature": 25}

Stream Mode

import os
from openai import OpenAI
from pydantic import BaseModel


client = OpenAI(
    base_url="https://api.infly.cn/v1",
    api_key=os.getenv("INF_OPENAPI_API_KEY"),
)

class Weather(BaseModel):
    location: str
    weather_state: str
    temperature: int

completion = client.chat.completions.create(
    model="inf-chat-int-v1",
    stream=True,
    messages=[
        {"role": "system", "content": "Extract the weather from the following text"},
        {"role": "user", "content": "It is sunny in Xuhui Riverside, Shanghai today, with a temperature of 25 degrees"},
    ],
    response_format={
        "type": "json_schema",
        "json_schema": {
            "name": "Weather",
            "schema": Weather.model_json_schema()
        }
    }
)

final_json = ""
for chunk in completion:
    if chunk.choices:
        final_json += chunk.choices[0].delta.content or ""

print(final_json)

# Will print:
# {"location": "Xuhui Riverside, Shanghai", "weather_state": "sunny", "temperature": 25}