forked from phoenix/litellm-mirror
docs(json_mode.md): add example of calling openai with pydantic model via litellm
This commit is contained in:
parent
9cf3d5f568
commit
0c88cc4153
1 changed files with 6 additions and 33 deletions
|
@ -71,12 +71,6 @@ response_format: { "type": "json_schema", "json_schema": … , "strict": true }
|
|||
|
||||
Works for OpenAI models
|
||||
|
||||
:::info
|
||||
|
||||
Support for passing in a pydantic object to litellm sdk will be [coming soon](https://github.com/BerriAI/litellm/issues/5074#issuecomment-2272355842)
|
||||
|
||||
:::
|
||||
|
||||
<Tabs>
|
||||
<TabItem value="sdk" label="SDK">
|
||||
|
||||
|
@ -89,36 +83,15 @@ os.environ["OPENAI_API_KEY"] = ""
|
|||
|
||||
messages = [{"role": "user", "content": "List 5 cookie recipes"}]
|
||||
|
||||
class CalendarEvent(BaseModel):
|
||||
name: str
|
||||
date: str
|
||||
participants: list[str]
|
||||
|
||||
resp = completion(
|
||||
model="gpt-4o-2024-08-06",
|
||||
messages=messages,
|
||||
response_format={
|
||||
"type": "json_schema",
|
||||
"json_schema": {
|
||||
"name": "math_reasoning",
|
||||
"schema": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"steps": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"explanation": { "type": "string" },
|
||||
"output": { "type": "string" }
|
||||
},
|
||||
"required": ["explanation", "output"],
|
||||
"additionalProperties": False
|
||||
}
|
||||
},
|
||||
"final_answer": { "type": "string" }
|
||||
},
|
||||
"required": ["steps", "final_answer"],
|
||||
"additionalProperties": False
|
||||
},
|
||||
"strict": True
|
||||
},
|
||||
}
|
||||
response_format=CalendarEvent
|
||||
)
|
||||
|
||||
print("Received={}".format(resp))
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue