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Test fixes in openai_compat

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Swapna Lekkala 2025-09-17 16:50:46 -07:00
parent e56a3f266c
commit d60514b57b
7 changed files with 221 additions and 7 deletions
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83
docs/_static/llama-stack-spec.html vendored
View file

@ -6372,6 +6372,9 @@
"$ref": "#/components/schemas/TokenLogProbs"
},
"description": "Optional log probabilities for generated tokens"
},
"usage": {
"$ref": "#/components/schemas/UsageInfo"
}
},
"additionalProperties": false,
@ -6430,6 +6433,31 @@
"title": "TokenLogProbs",
"description": "Log probabilities for generated tokens."
},
"UsageInfo": {
"type": "object",
"properties": {
"completion_tokens": {
"type": "integer",
"description": "Number of tokens generated"
},
"prompt_tokens": {
"type": "integer",
"description": "Number of tokens in the prompt"
},
"total_tokens": {
"type": "integer",
"description": "Total number of tokens processed"
}
},
"additionalProperties": false,
"required": [
"completion_tokens",
"prompt_tokens",
"total_tokens"
],
"title": "UsageInfo",
"description": "Usage information for a model."
},
"BatchCompletionRequest": {
"type": "object",
"properties": {
@ -10939,6 +10967,31 @@
"title": "OpenAIChatCompletionToolCallFunction",
"description": "Function call details for OpenAI-compatible tool calls."
},
"OpenAIChatCompletionUsage": {
"type": "object",
"properties": {
"prompt_tokens": {
"type": "integer",
"description": "The number of tokens in the prompt"
},
"completion_tokens": {
"type": "integer",
"description": "The number of tokens in the completion"
},
"total_tokens": {
"type": "integer",
"description": "The total number of tokens used"
}
},
"additionalProperties": false,
"required": [
"prompt_tokens",
"completion_tokens",
"total_tokens"
],
"title": "OpenAIChatCompletionUsage",
"description": "Usage information for an OpenAI-compatible chat completion response."
},
"OpenAIChoice": {
"type": "object",
"properties": {
@ -11276,6 +11329,13 @@
"OpenAICompletionWithInputMessages": {
"type": "object",
"properties": {
"metrics": {
"type": "array",
"items": {
"$ref": "#/components/schemas/MetricInResponse"
},
"description": "(Optional) List of metrics associated with the API response"
},
"id": {
"type": "string",
"description": "The ID of the chat completion"
@ -11301,6 +11361,9 @@
"type": "string",
"description": "The model that was used to generate the chat completion"
},
"usage": {
"$ref": "#/components/schemas/OpenAIChatCompletionUsage"
},
"input_messages": {
"type": "array",
"items": {
@ -13062,6 +13125,13 @@
"items": {
"type": "object",
"properties": {
"metrics": {
"type": "array",
"items": {
"$ref": "#/components/schemas/MetricInResponse"
},
"description": "(Optional) List of metrics associated with the API response"
},
"id": {
"type": "string",
"description": "The ID of the chat completion"
@ -13087,6 +13157,9 @@
"type": "string",
"description": "The model that was used to generate the chat completion"
},
"usage": {
"$ref": "#/components/schemas/OpenAIChatCompletionUsage"
},
"input_messages": {
"type": "array",
"items": {
@ -14478,6 +14551,13 @@
"OpenAIChatCompletion": {
"type": "object",
"properties": {
"metrics": {
"type": "array",
"items": {
"$ref": "#/components/schemas/MetricInResponse"
},
"description": "(Optional) List of metrics associated with the API response"
},
"id": {
"type": "string",
"description": "The ID of the chat completion"
@ -14502,6 +14582,9 @@
"model": {
"type": "string",
"description": "The model that was used to generate the chat completion"
},
"usage": {
"$ref": "#/components/schemas/OpenAIChatCompletionUsage"
}
},
"additionalProperties": false,

65
docs/_static/llama-stack-spec.yaml vendored
View file

@ -4548,6 +4548,8 @@ components:
$ref: '#/components/schemas/TokenLogProbs'
description: >-
Optional log probabilities for generated tokens
usage:
$ref: '#/components/schemas/UsageInfo'
additionalProperties: false
required:
- completion_message
@ -4589,6 +4591,25 @@ components:
- logprobs_by_token
title: TokenLogProbs
description: Log probabilities for generated tokens.
UsageInfo:
type: object
properties:
completion_tokens:
type: integer
description: Number of tokens generated
prompt_tokens:
type: integer
description: Number of tokens in the prompt
total_tokens:
type: integer
description: Total number of tokens processed
additionalProperties: false
required:
- completion_tokens
- prompt_tokens
- total_tokens
title: UsageInfo
description: Usage information for a model.
BatchCompletionRequest:
type: object
properties:
@ -8103,6 +8124,26 @@ components:
title: OpenAIChatCompletionToolCallFunction
description: >-
Function call details for OpenAI-compatible tool calls.
OpenAIChatCompletionUsage:
type: object
properties:
prompt_tokens:
type: integer
description: The number of tokens in the prompt
completion_tokens:
type: integer
description: The number of tokens in the completion
total_tokens:
type: integer
description: The total number of tokens used
additionalProperties: false
required:
- prompt_tokens
- completion_tokens
- total_tokens
title: OpenAIChatCompletionUsage
description: >-
Usage information for an OpenAI-compatible chat completion response.
OpenAIChoice:
type: object
properties:
@ -8365,6 +8406,12 @@ components:
OpenAICompletionWithInputMessages:
type: object
properties:
metrics:
type: array
items:
$ref: '#/components/schemas/MetricInResponse'
description: >-
(Optional) List of metrics associated with the API response
id:
type: string
description: The ID of the chat completion
@ -8387,6 +8434,8 @@ components:
type: string
description: >-
The model that was used to generate the chat completion
usage:
$ref: '#/components/schemas/OpenAIChatCompletionUsage'
input_messages:
type: array
items:
@ -9682,6 +9731,12 @@ components:
items:
type: object
properties:
metrics:
type: array
items:
$ref: '#/components/schemas/MetricInResponse'
description: >-
(Optional) List of metrics associated with the API response
id:
type: string
description: The ID of the chat completion
@ -9704,6 +9759,8 @@ components:
type: string
description: >-
The model that was used to generate the chat completion
usage:
$ref: '#/components/schemas/OpenAIChatCompletionUsage'
input_messages:
type: array
items:
@ -10719,6 +10776,12 @@ components:
OpenAIChatCompletion:
type: object
properties:
metrics:
type: array
items:
$ref: '#/components/schemas/MetricInResponse'
description: >-
(Optional) List of metrics associated with the API response
id:
type: string
description: The ID of the chat completion
@ -10741,6 +10804,8 @@ components:
type: string
description: >-
The model that was used to generate the chat completion
usage:
$ref: '#/components/schemas/OpenAIChatCompletionUsage'
additionalProperties: false
required:
- id

32
llama_stack/apis/inference/inference.py
View file

@ -451,6 +451,20 @@ class ChatCompletionResponseStreamChunk(MetricResponseMixin):
event: ChatCompletionResponseEvent
@json_schema_type
class UsageInfo(BaseModel):
"""Usage information for a model.
:param completion_tokens: Number of tokens generated
:param prompt_tokens: Number of tokens in the prompt
:param total_tokens: Total number of tokens processed
"""
completion_tokens: int
prompt_tokens: int
total_tokens: int
@json_schema_type
class ChatCompletionResponse(MetricResponseMixin):
"""Response from a chat completion request.
@ -461,6 +475,7 @@ class ChatCompletionResponse(MetricResponseMixin):
completion_message: CompletionMessage
logprobs: list[TokenLogProbs] | None = None
usage: UsageInfo | None = None
@json_schema_type
@ -818,7 +833,21 @@ class OpenAIChoice(BaseModel):
@json_schema_type
class OpenAIChatCompletion(BaseModel):
class OpenAIChatCompletionUsage(BaseModel):
"""Usage information for an OpenAI-compatible chat completion response.
:param prompt_tokens: The number of tokens in the prompt
:param completion_tokens: The number of tokens in the completion
:param total_tokens: The total number of tokens used
"""
prompt_tokens: int
completion_tokens: int
total_tokens: int
@json_schema_type
class OpenAIChatCompletion(MetricResponseMixin):
"""Response from an OpenAI-compatible chat completion request.
:param id: The ID of the chat completion
@ -833,6 +862,7 @@ class OpenAIChatCompletion(BaseModel):
object: Literal["chat.completion"] = "chat.completion"
created: int
model: str
usage: OpenAIChatCompletionUsage | None = None
@json_schema_type

2
llama_stack/core/routers/inference.py
View file

@ -590,6 +590,7 @@ class InferenceRouter(Inference):
async def _nonstream_openai_chat_completion(self, provider: Inference, params: dict) -> OpenAIChatCompletion:
response = await provider.openai_chat_completion(**params)
for choice in response.choices:
# some providers return an empty list for no tool calls in non-streaming responses
# but the OpenAI API returns None. So, set tool_calls to None if it's empty
@ -739,7 +740,6 @@ class InferenceRouter(Inference):
id = None
created = None
choices_data: dict[int, dict[str, Any]] = {}
try:
async for chunk in response:
# Skip None chunks

6
llama_stack/providers/remote/inference/fireworks/fireworks.py
View file

@ -130,7 +130,7 @@ class FireworksInferenceAdapter(OpenAIMixin, ModelRegistryHelper, Inference, Nee
async def _stream_completion(self, request: CompletionRequest) -> AsyncGenerator:
params = await self._get_params(request)
stream = self.client.completions.create(**params)
stream = await self.client.completions.create(**params)
async for chunk in process_completion_stream_response(stream):
yield chunk
@ -208,9 +208,9 @@ class FireworksInferenceAdapter(OpenAIMixin, ModelRegistryHelper, Inference, Nee
params = await self._get_params(request)
if "messages" in params:
stream = self.client.chat.completions.create(**params)
stream = await self.client.chat.completions.create(**params)
else:
stream = self.client.completions.create(**params)
stream = await self.client.completions.create(**params)
async for chunk in process_chat_completion_stream_response(stream, request):
yield chunk

31
llama_stack/providers/utils/inference/openai_compat.py
View file

@ -31,6 +31,8 @@ from openai.types.chat import (
ChatCompletionContentPartTextParam as OpenAIChatCompletionContentPartTextParam,
)
from llama_stack.apis.inference.inference import UsageInfo
try:
from openai.types.chat import (
ChatCompletionMessageFunctionToolCall as OpenAIChatCompletionMessageFunctionToolCall,
@ -103,6 +105,7 @@ from llama_stack.apis.inference import (
JsonSchemaResponseFormat,
Message,
OpenAIChatCompletion,
OpenAIChatCompletionUsage,
OpenAICompletion,
OpenAICompletionChoice,
OpenAIEmbeddingData,
@ -277,6 +280,11 @@ def process_chat_completion_response(
request: ChatCompletionRequest,
) -> ChatCompletionResponse:
choice = response.choices[0]
usage = UsageInfo(
prompt_tokens=response.usage.prompt_tokens,
completion_tokens=response.usage.completion_tokens,
total_tokens=response.usage.total_tokens,
)
if choice.finish_reason == "tool_calls":
if not choice.message or not choice.message.tool_calls:
raise ValueError("Tool calls are not present in the response")
@ -290,6 +298,7 @@ def process_chat_completion_response(
content=json.dumps(tool_calls, default=lambda x: x.model_dump()),
),
logprobs=None,
usage=usage,
)
else:
# Otherwise, return tool calls as normal
@ -301,6 +310,7 @@ def process_chat_completion_response(
content="",
),
logprobs=None,
usage=usage,
)
# TODO: This does not work well with tool calls for vLLM remote provider
@ -335,6 +345,7 @@ def process_chat_completion_response(
tool_calls=raw_message.tool_calls,
),
logprobs=None,
usage=usage,
)
@ -646,7 +657,7 @@ async def convert_message_to_openai_dict_new(
arguments=json.dumps(tool.arguments),
),
type="function",
)
).model_dump()
for tool in message.tool_calls
]
params = {}
@ -657,6 +668,7 @@ async def convert_message_to_openai_dict_new(
content=await _convert_message_content(message.content),
**params,
)
elif isinstance(message, ToolResponseMessage):
out = OpenAIChatCompletionToolMessage(
role="tool",
@ -1375,6 +1387,7 @@ class OpenAIChatCompletionToLlamaStackMixin:
user: str | None = None,
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
messages = openai_messages_to_messages(messages)
response_format = _convert_openai_request_response_format(response_format)
sampling_params = _convert_openai_sampling_params(
max_tokens=max_tokens,
@ -1401,7 +1414,6 @@ class OpenAIChatCompletionToLlamaStackMixin:
tools=tools,
)
outstanding_responses.append(response)
if stream:
return OpenAIChatCompletionToLlamaStackMixin._process_stream_response(self, model, outstanding_responses)
@ -1476,12 +1488,22 @@ class OpenAIChatCompletionToLlamaStackMixin:
self, model: str, outstanding_responses: list[Awaitable[ChatCompletionResponse]]
) -> OpenAIChatCompletion:
choices = []
total_prompt_tokens = 0
total_completion_tokens = 0
total_tokens = 0
for outstanding_response in outstanding_responses:
response = await outstanding_response
completion_message = response.completion_message
message = await convert_message_to_openai_dict_new(completion_message)
finish_reason = _convert_stop_reason_to_openai_finish_reason(completion_message.stop_reason)
# Aggregate usage data
if response.usage:
total_prompt_tokens += response.usage.prompt_tokens
total_completion_tokens += response.usage.completion_tokens
total_tokens += response.usage.total_tokens
choice = OpenAIChatCompletionChoice(
index=len(choices),
message=message,
@ -1489,12 +1511,17 @@ class OpenAIChatCompletionToLlamaStackMixin:
)
choices.append(choice)
usage = OpenAIChatCompletionUsage(
prompt_tokens=total_prompt_tokens, completion_tokens=total_completion_tokens, total_tokens=total_tokens
)
return OpenAIChatCompletion(
id=f"chatcmpl-{uuid.uuid4()}",
choices=choices,
created=int(time.time()),
model=model,
object="chat.completion",
usage=usage,
)

9
tests/integration/suites.py
View file

@ -108,6 +108,15 @@ SETUP_DEFINITIONS: dict[str, Setup] = {
"embedding_model": "together/togethercomputer/m2-bert-80M-32k-retrieval",
},
),
"fireworks": Setup(
name="fireworks",
description="Fireworks provider with a text model",
defaults={
"text_model": "fireworks/accounts/fireworks/models/llama-v3p1-8b-instruct",
"vision_model": "fireworks/accounts/fireworks/models/llama-v3p2-90b-vision-instruct",
"embedding_model": "nomic-ai/nomic-embed-text-v1.5",
},
),
}