I'm converting the Swagger for Azure OpenAI API Version 2023-07-01-preview from json to yaml
My Swagger looks like this
openapi: 3.0.1
info:
title: OpenAI Models API
description: ''
version: '123'
servers:
- url: https://def.com/openai
paths:
/gpt-35-turbo/chat/completions:
post:
tags:
- openai
summary: Creates a completion for the chat message
description: gpt-35-turbo-chat-completion
operationId: GPT_35_Turbo_ChatCompletions_Create
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/createChatCompletionRequest'
responses:
'200':
description: OK
content:
application/json:
schema:
$ref: '#/components/schemas/createChatCompletionResponse'
headers:
apim-request-id:
description: Request ID for troubleshooting purposes
schema:
type: string
default:
description: Service unavailable
content:
application/json:
schema:
$ref: '#/components/schemas/errorResponse'
headers:
apim-request-id:
description: Request ID for troubleshooting purposes
schema:
type: string
components:
schemas:
errorResponse:
type: object
properties:
error:
$ref: '#/components/schemas/error'
errorBase:
type: object
properties:
code:
type: string
message:
type: string
error:
type: object
allOf:
- $ref: '#/components/schemas/errorBase'
properties:
code:
type: string
message:
type: string
param:
type: string
type:
type: string
inner_error:
$ref: '#/components/schemas/innerError'
innerError:
description: Inner error with additional details.
type: object
properties:
code:
$ref: '#/components/schemas/innerErrorCode'
content_filter_results:
$ref: '#/components/schemas/contentFilterResults'
innerErrorCode:
description: Error codes for the inner error object.
enum:
- ResponsibleAIPolicyViolation
type: string
x-ms-enum:
name: InnerErrorCode
modelAsString: true
values:
- value: ResponsibleAIPolicyViolation
description: The prompt violated one of more content filter rules.
contentFilterResult:
type: object
properties:
severity:
type: string
enum:
- safe
- low
- medium
- high
x-ms-enum:
name: ContentFilterSeverity
modelAsString: true
values:
- value: safe
description: >-
General content or related content in generic or non-harmful
contexts.
- value: low
description: Harmful content at a low intensity and risk level.
- value: medium
description: Harmful content at a medium intensity and risk level.
- value: high
description: Harmful content at a high intensity and risk level.
filtered:
type: boolean
required:
- severity
- filtered
contentFilterResults:
type: object
description: >-
Information about the content filtering category (hate, sexual,
violence, self_harm), if it has been detected, as well as the severity
level (very_low, low, medium, high-scale that determines the intensity
and risk level of harmful content) and if it has been filtered or not.
properties:
sexual:
$ref: '#/components/schemas/contentFilterResult'
violence:
$ref: '#/components/schemas/contentFilterResult'
hate:
$ref: '#/components/schemas/contentFilterResult'
self_harm:
$ref: '#/components/schemas/contentFilterResult'
error:
$ref: '#/components/schemas/errorBase'
promptFilterResult:
type: object
description: Content filtering results for a single prompt in the request.
properties:
prompt_index:
type: integer
content_filter_results:
$ref: '#/components/schemas/contentFilterResults'
promptFilterResults:
type: array
description: >-
Content filtering results for zero or more prompts in the request. In a
streaming request, results for different prompts may arrive at different
times or in different orders.
items:
$ref: '#/components/schemas/promptFilterResult'
createChatCompletionRequest:
type: object
allOf:
- $ref: '#/components/schemas/chatCompletionsRequestCommon'
- properties:
messages:
description: >-
A list of messages comprising the conversation so far. [Example
Python
code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb).
type: array
minItems: 1
items:
$ref: '#/components/schemas/chatCompletionRequestMessage'
functions:
description: A list of functions the model may generate JSON inputs for.
type: array
minItems: 1
items:
$ref: '#/components/schemas/chatCompletionFunctions'
function_call:
description: >-
Controls how the model responds to function calls. "none" means
the model does not call a function, and responds to the
end-user. "auto" means the model can pick between an end-user or
calling a function. Specifying a particular function via
`{"name":\ "my_function"}` forces the model to call that
function. "none" is the default when no functions are present.
"auto" is the default if functions are present.
oneOf:
- type: string
enum:
- none
- auto
- type: object
properties:
name:
type: string
description: The name of the function to call.
required:
- name
'n':
type: integer
minimum: 1
maximum: 128
default: 1
example: 1
nullable: true
description: >-
How many chat completion choices to generate for each input
message.
required:
- messages
chatCompletionsRequestCommon:
type: object
properties:
temperature:
description: >-
What sampling temperature to use, between 0 and 2. Higher values
like 0.8 will make the output more random, while lower values like
0.2 will make it more focused and deterministic.
We generally recommend altering this or `top_p` but not both.
type: number
minimum: 0
maximum: 2
default: 1
example: 1
nullable: true
top_p:
description: >-
An alternative to sampling with temperature, called nucleus
sampling, where the model considers the results of the tokens with
top_p probability mass. So 0.1 means only the tokens comprising the
top 10% probability mass are considered.
We generally recommend altering this or `temperature` but not both.
type: number
minimum: 0
maximum: 1
default: 1
example: 1
nullable: true
stop:
description: Up to 4 sequences where the API will stop generating further tokens.
oneOf:
- type: string
nullable: true
- type: array
items:
type: string
nullable: false
minItems: 1
maxItems: 4
description: Array minimum size of 1 and maximum of 4
default: null
max_tokens:
description: >-
The maximum number of tokens allowed for the generated answer. By
default, the number of tokens the model can return will be (4096 -
prompt tokens).
type: integer
default: 4096
presence_penalty:
description: >-
Number between -2.0 and 2.0. Positive values penalize new tokens
based on whether they appear in the text so far, increasing the
model's likelihood to talk about new topics.
type: number
default: 0
minimum: -2
maximum: 2
frequency_penalty:
description: >-
Number between -2.0 and 2.0. Positive values penalize new tokens
based on their existing frequency in the text so far, decreasing the
model's likelihood to repeat the same line verbatim.
type: number
default: 0
minimum: -2
maximum: 2
logit_bias:
description: >-
Modify the likelihood of specified tokens appearing in the
completion. Accepts a json object that maps tokens (specified by
their token ID in the tokenizer) to an associated bias value from
-100 to 100. Mathematically, the bias is added to the logits
generated by the model prior to sampling. The exact effect will vary
per model, but values between -1 and 1 should decrease or increase
likelihood of selection; values like -100 or 100 should result in a
ban or exclusive selection of the relevant token.
type: object
nullable: true
user:
description: >-
A unique identifier representing your end-user, which can help Azure
OpenAI to monitor and detect abuse.
type: string
example: user-1234
nullable: false
chatCompletionRequestMessage:
type: object
properties:
role:
type: string
enum:
- system
- user
- assistant
- function
description: >-
The role of the messages author. One of `system`, `user`,
`assistant`, or `function`.
content:
type: string
description: >-
The contents of the message. `content` is required for all messages
except assistant messages with function calls.
name:
type: string
description: >-
The name of the author of this message. `name` is required if role
is `function`, and it should be the name of the function whose
response is in the `content`. May contain a-z, A-Z, 0-9, and
underscores, with a maximum length of 64 characters.
function_call:
type: object
description: >-
The name and arguments of a function that should be called, as
generated by the model.
properties:
name:
type: string
description: The name of the function to call.
arguments:
type: string
description: >-
The arguments to call the function with, as generated by the
model in JSON format. Note that the model does not always
generate valid JSON, and may hallucinate parameters not defined
by your function schema. Validate the arguments in your code
before calling your function.
required:
- role
createChatCompletionResponse:
type: object
allOf:
- $ref: '#/components/schemas/chatCompletionsResponseCommon'
- properties:
prompt_filter_results:
$ref: '#/components/schemas/promptFilterResults'
choices:
type: array
items:
type: object
allOf:
- $ref: '#/components/schemas/chatCompletionChoiceCommon'
- properties:
message:
$ref: '#/components/schemas/chatCompletionResponseMessage'
content_filter_results:
$ref: '#/components/schemas/contentFilterResults'
required:
- id
- object
- created
- model
- choices
chatCompletionFunctions:
type: object
properties:
name:
type: string
description: >-
The name of the function to be called. Must be a-z, A-Z, 0-9, or
contain underscores and dashes, with a maximum length of 64.
description:
type: string
description: The description of what the function does.
parameters:
$ref: '#/components/schemas/chatCompletionFunctionParameters'
required:
- name
chatCompletionFunctionParameters:
type: object
description: >-
The parameters the functions accepts, described as a JSON Schema object.
See the [guide](/docs/guides/gpt/function-calling) for examples, and the
[JSON Schema
reference](https://json-schema.org/understanding-json-schema/) for
documentation about the format.
additionalProperties: true
chatCompletionsResponseCommon:
type: object
properties:
id:
type: string
object:
type: string
created:
type: integer
format: unixtime
model:
type: string
usage:
type: object
properties:
prompt_tokens:
type: integer
completion_tokens:
type: integer
total_tokens:
type: integer
required:
- prompt_tokens
- completion_tokens
- total_tokens
required:
- id
- object
- created
- model
chatCompletionChoiceCommon:
type: object
properties:
index:
type: integer
finish_reason:
type: string
chatCompletionResponseMessage:
type: object
properties:
role:
type: string
enum:
- system
- user
- assistant
- function
description: The role of the author of this message.
content:
type: string
description: The contents of the message.
function_call:
type: object
description: >-
The name and arguments of a function that should be called, as
generated by the model.
properties:
name:
type: string
description: The name of the function to call.
arguments:
type: string
description: >-
The arguments to call the function with, as generated by the
model in JSON format. Note that the model does not always
generate valid JSON, and may hallucinate parameters not defined
by your function schema. Validate the arguments in your code
before calling your function.
required:
- role
securitySchemes:
apiKeyHeader:
type: apiKey
name: Ocp-Apim-Subscription-Key
in: header
apiKeyQuery:
type: apiKey
name: subscription-key
in: query
security:
- apiKeyHeader: [ ]
- apiKeyQuery: [ ]
I used this in azure apim and validating the content like this
<validate-content unspecified-content-type-action="ignore" max-size="102400" size-exceeded-action="detect" errors-variable-name="requestBodyValidation">
<content type="application/json" validate-as="json" action="prevent" allow-additional-properties="false" />
</validate-content>
Now I tried to give the request like the actual property
{
"messages": [
{
"role": "user",
"content": "Find beachfront hotels in San Diego for less than $300 a month with free breakfast."
}
],
"temperature": 1,
"top_p": 1,
"stop": "",
"max_tokens": 2000,
"presence_penalty": 0,
"frequency_penalty": 0,
"logit_bias": {},
"user": "user-1234",
"n": 1,
"function_call" : "auto",
"functions" : [
{
"name": "search_hotels",
"description": "Retrieves hotels from the search index based on the parameters provided",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The location of the hotel (i.e. Seattle, WA)"
},
"max_price": {
"type": "number",
"description": "The maximum price for the hotel"
},
"features": {
"type": "string",
"description": "A comma separated list of features (i.e. beachfront, free wifi, etc.)"
}
},
"required": ["location"]
}
}
]
}
And the APIM is giving the error like
{
"statusCode": 400,
"message": "Body of the request does not conform to the definition which is associated with the content type application/json. JSON does not match all schemas from 'allOf'. Invalid schema indexes: 0, 1. Line: 42, Position: 1"
}
But the same request is working when I directly hit the azure openai.
What could be the possible issue here ?
I believe your problem is this line allow-additional-properties="false"
allow-additional-properties Boolean. For a JSON schema, specifies whether to implement a runtime override of the additionalProperties value configured in the schema:
If the attribute isn't specified, the policy validates additional properties according to configuration of the additionalProperties field in the schema.
source: https://learn.microsoft.com/en-us/azure/api-management/validate-content-policy#content-attributes
This property overrides your JSON Schema. Even though your allOf definition does not use additionalProperties: false, apim will inject this constraint to the root schema, which translates to
{
"type": "object",
"additionalProperties": false,
"allOf": [{...}, {...}]
}
This schema doesn't allow any properties to be validated because no properties are defined at the root.
The only valid schemas in this situation would be
{}
OR
true
There are a few ways to tackle this but IMHO, the best option is to use the schema definition, rather than the apim attribute because you're introducing constraints on the schema where they are not defined. If someone else were to review the schema, they would run into the same issue you are having.
This is where it may get tricky for you depending on which version of JSON Schema is supported in APIM and which version you are using.
Draft-04 - 07 requires some massaging to the schema, in most circumstances, to achieve the desired behavior of using allOf with additionalProperties": false
additionalProperties{
"$schema": "http://json-schema.org/draft-07/schema#",
"type": "object",
"additionalProperties": false,
"properties": {
"messages": {},
"temperature": {},
"top_p": {},
"stop": {},
"max_tokens": {},
"presence_penalty": {},
"frequency_penalty": {},
"logit_bias": {},
"user": { },
"n": { },
"function_call": { },
"functions": { }
},
"allOf": [
{
"type": "object",
"properties": {
"temperature": {},
"top_p": {},
"stop": {},
"max_tokens": {},
"presence_penalty": {},
"frequency_penalty": {},
"logit_bias": {},
"user": {}
}
},
{
"type": "object",
"properties": {
"messages": {},
"n": {},
"function_call": {},
"functions": {}
}
}
]
}
If you're using JSON Schema draft 2019-09 or later, you can use the newer keyword unevaluatedProperties which performs the behavior described above, automatically.
{
"$schema": "https://json-schema.org/draft/2019-09/schema",
"type": "object",
"unevaluatedProperties": false,
"allOf": [
{
"type": "object",
"properties": {
"temperature": {},
"top_p": {},
"stop": {},
"max_tokens": {},
"presence_penalty": {},
"frequency_penalty": {},
"logit_bias": {},
"user": {}
}
},
{
"type": "object",
"properties": {
"messages": {},
"n": {},
"function_call": {},
"functions": {}
}
}
]
}
This example fails:
{
"messages": [
{
"role": "user",
"content": "Find beachfront hotels in San Diego for less than $300 a month with free breakfast."
}
],
"stackOverflow": -1
}
Invalid
# fails schema constraint https://json-schema.hyperjump.io/schema#/unevaluatedProperties
#/stackOverflow fails schema constraint https://json-schema.hyperjump.io/schema#/unevaluatedProperties