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Improve groq OpenAI API compatibility

Browse source 
This doesn't get Groq to 100% on the OpenAI API verification tests,
but it does get it to 88.2% when Llama Stack is in the middle,
compared to the 61.8% results for using an OpenAI client against Groq
directly.

The groq provider doesn't use litellm under the covers in its
openai_chat_completion endpoint, and instead directly uses an
AsyncOpenAI client with some special handling to improve conformance
of responses for response_format usage and tool calling.

Signed-off-by: Ben Browning <bbrownin@redhat.com>
This commit is contained in:
Ben Browning 2025-04-13 13:35:53 -04:00
parent 657bb12e85
commit 8a1c0a1008
16 changed files with 418 additions and 45 deletions
Download patch file Download diff file Expand all files Collapse all files

81
docs/_static/llama-stack-spec.html vendored
View file

@ -8923,6 +8923,9 @@
"OpenAIChatCompletionToolCall": {
"type": "object",
"properties": {
"index": {
"type": "integer"
},
"id": {
"type": "string"
},
@ -8937,9 +8940,7 @@
},
"additionalProperties": false,
"required": [
"id",
"type",
"function"
"type"
],
"title": "OpenAIChatCompletionToolCall"
},
@ -8954,10 +8955,6 @@
}
},
"additionalProperties": false,
"required": [
"name",
"arguments"
],
"title": "OpenAIChatCompletionToolCallFunction"
},
"OpenAIDeveloperMessageParam": {
@ -9563,7 +9560,7 @@
"choices": {
"type": "array",
"items": {
"$ref": "#/components/schemas/OpenAIChoice"
"$ref": "#/components/schemas/OpenAIChunkChoice"
},
"description": "List of choices"
},
@ -9605,10 +9602,12 @@
"description": "The reason the model stopped generating"
},
"index": {
"type": "integer"
"type": "integer",
"description": "The index of the choice"
},
"logprobs": {
"$ref": "#/components/schemas/OpenAIChoiceLogprobs"
"$ref": "#/components/schemas/OpenAIChoiceLogprobs",
"description": "(Optional) The log probabilities for the tokens in the message"
}
},
"additionalProperties": false,
@ -9620,6 +9619,33 @@
"title": "OpenAIChoice",
"description": "A choice from an OpenAI-compatible chat completion response."
},
"OpenAIChoiceDelta": {
"type": "object",
"properties": {
"content": {
"type": "string",
"description": "(Optional) The content of the delta"
},
"refusal": {
"type": "string",
"description": "(Optional) The refusal of the delta"
},
"role": {
"type": "string",
"description": "(Optional) The role of the delta"
},
"tool_calls": {
"type": "array",
"items": {
"$ref": "#/components/schemas/OpenAIChatCompletionToolCall"
},
"description": "(Optional) The tool calls of the delta"
}
},
"additionalProperties": false,
"title": "OpenAIChoiceDelta",
"description": "A delta from an OpenAI-compatible chat completion streaming response."
},
"OpenAIChoiceLogprobs": {
"type": "object",
"properties": {
@ -9627,19 +9653,50 @@
"type": "array",
"items": {
"$ref": "#/components/schemas/OpenAITokenLogProb"
}
},
"description": "(Optional) The log probabilities for the tokens in the message"
},
"refusal": {
"type": "array",
"items": {
"$ref": "#/components/schemas/OpenAITokenLogProb"
}
},
"description": "(Optional) The log probabilities for the tokens in the message"
}
},
"additionalProperties": false,
"title": "OpenAIChoiceLogprobs",
"description": "The log probabilities for the tokens in the message from an OpenAI-compatible chat completion response."
},
"OpenAIChunkChoice": {
"type": "object",
"properties": {
"delta": {
"$ref": "#/components/schemas/OpenAIChoiceDelta",
"description": "The delta from the chunk"
},
"finish_reason": {
"type": "string",
"description": "The reason the model stopped generating"
},
"index": {
"type": "integer",
"description": "The index of the choice"
},
"logprobs": {
"$ref": "#/components/schemas/OpenAIChoiceLogprobs",
"description": "(Optional) The log probabilities for the tokens in the message"
}
},
"additionalProperties": false,
"required": [
"delta",
"finish_reason",
"index"
],
"title": "OpenAIChunkChoice",
"description": "A chunk choice from an OpenAI-compatible chat completion streaming response."
},
"OpenAITokenLogProb": {
"type": "object",
"properties": {

61
docs/_static/llama-stack-spec.yaml vendored
View file

@ -6127,6 +6127,8 @@ components:
OpenAIChatCompletionToolCall:
type: object
properties:
index:
type: integer
id:
type: string
type:
@ -6137,9 +6139,7 @@ components:
$ref: '#/components/schemas/OpenAIChatCompletionToolCallFunction'
additionalProperties: false
required:
- id
- type
- function
title: OpenAIChatCompletionToolCall
OpenAIChatCompletionToolCallFunction:
type: object
@ -6149,9 +6149,6 @@ components:
arguments:
type: string
additionalProperties: false
required:
- name
- arguments
title: OpenAIChatCompletionToolCallFunction
OpenAIDeveloperMessageParam:
type: object
@ -6550,7 +6547,7 @@ components:
choices:
type: array
items:
$ref: '#/components/schemas/OpenAIChoice'
$ref: '#/components/schemas/OpenAIChunkChoice'
description: List of choices
object:
type: string
@ -6587,8 +6584,11 @@ components:
description: The reason the model stopped generating
index:
type: integer
description: The index of the choice
logprobs:
$ref: '#/components/schemas/OpenAIChoiceLogprobs'
description: >-
(Optional) The log probabilities for the tokens in the message
additionalProperties: false
required:
- message
@ -6597,6 +6597,27 @@ components:
title: OpenAIChoice
description: >-
A choice from an OpenAI-compatible chat completion response.
OpenAIChoiceDelta:
type: object
properties:
content:
type: string
description: (Optional) The content of the delta
refusal:
type: string
description: (Optional) The refusal of the delta
role:
type: string
description: (Optional) The role of the delta
tool_calls:
type: array
items:
$ref: '#/components/schemas/OpenAIChatCompletionToolCall'
description: (Optional) The tool calls of the delta
additionalProperties: false
title: OpenAIChoiceDelta
description: >-
A delta from an OpenAI-compatible chat completion streaming response.
OpenAIChoiceLogprobs:
type: object
properties:
@ -6604,15 +6625,43 @@ components:
type: array
items:
$ref: '#/components/schemas/OpenAITokenLogProb'
description: >-
(Optional) The log probabilities for the tokens in the message
refusal:
type: array
items:
$ref: '#/components/schemas/OpenAITokenLogProb'
description: >-
(Optional) The log probabilities for the tokens in the message
additionalProperties: false
title: OpenAIChoiceLogprobs
description: >-
The log probabilities for the tokens in the message from an OpenAI-compatible
chat completion response.
OpenAIChunkChoice:
type: object
properties:
delta:
$ref: '#/components/schemas/OpenAIChoiceDelta'
description: The delta from the chunk
finish_reason:
type: string
description: The reason the model stopped generating
index:
type: integer
description: The index of the choice
logprobs:
$ref: '#/components/schemas/OpenAIChoiceLogprobs'
description: >-
(Optional) The log probabilities for the tokens in the message
additionalProperties: false
required:
- delta
- finish_reason
- index
title: OpenAIChunkChoice
description: >-
A chunk choice from an OpenAI-compatible chat completion streaming response.
OpenAITokenLogProb:
type: object
properties:

2
docs/source/distributions/self_hosted_distro/groq.md
View file

@ -43,7 +43,9 @@ The following models are available by default:
- `groq/llama-3.3-70b-versatile (aliases: meta-llama/Llama-3.3-70B-Instruct)`
- `groq/llama-3.2-3b-preview (aliases: meta-llama/Llama-3.2-3B-Instruct)`
- `groq/llama-4-scout-17b-16e-instruct (aliases: meta-llama/Llama-4-Scout-17B-16E-Instruct)`
- `groq/meta-llama/llama-4-scout-17b-16e-instruct (aliases: meta-llama/Llama-4-Scout-17B-16E-Instruct)`
- `groq/llama-4-maverick-17b-128e-instruct (aliases: meta-llama/Llama-4-Maverick-17B-128E-Instruct)`
- `groq/meta-llama/llama-4-maverick-17b-128e-instruct (aliases: meta-llama/Llama-4-Maverick-17B-128E-Instruct)`
### Prerequisite: API Keys

51
llama_stack/apis/inference/inference.py
View file

@ -503,15 +503,16 @@ class OpenAISystemMessageParam(BaseModel):
@json_schema_type
class OpenAIChatCompletionToolCallFunction(BaseModel):
name: str
arguments: str
name: Optional[str] = None
arguments: Optional[str] = None
@json_schema_type
class OpenAIChatCompletionToolCall(BaseModel):
id: str
index: Optional[int] = None
id: Optional[str] = None
type: Literal["function"] = "function"
function: OpenAIChatCompletionToolCallFunction
function: Optional[OpenAIChatCompletionToolCallFunction] = None
@json_schema_type
@ -645,22 +646,54 @@ class OpenAITokenLogProb(BaseModel):
class OpenAIChoiceLogprobs(BaseModel):
"""The log probabilities for the tokens in the message from an OpenAI-compatible chat completion response.
:content: (Optional) The log probabilities for the tokens in the message
:refusal: (Optional) The log probabilities for the tokens in the message
:param content: (Optional) The log probabilities for the tokens in the message
:param refusal: (Optional) The log probabilities for the tokens in the message
"""
content: Optional[List[OpenAITokenLogProb]] = None
refusal: Optional[List[OpenAITokenLogProb]] = None
@json_schema_type
class OpenAIChoiceDelta(BaseModel):
"""A delta from an OpenAI-compatible chat completion streaming response.
:param content: (Optional) The content of the delta
:param refusal: (Optional) The refusal of the delta
:param role: (Optional) The role of the delta
:param tool_calls: (Optional) The tool calls of the delta
"""
content: Optional[str] = None
refusal: Optional[str] = None
role: Optional[str] = None
tool_calls: Optional[List[OpenAIChatCompletionToolCall]] = None
@json_schema_type
class OpenAIChunkChoice(BaseModel):
"""A chunk choice from an OpenAI-compatible chat completion streaming response.
:param delta: The delta from the chunk
:param finish_reason: The reason the model stopped generating
:param index: The index of the choice
:param logprobs: (Optional) The log probabilities for the tokens in the message
"""
delta: OpenAIChoiceDelta
finish_reason: str
index: int
logprobs: Optional[OpenAIChoiceLogprobs] = None
@json_schema_type
class OpenAIChoice(BaseModel):
"""A choice from an OpenAI-compatible chat completion response.
:param message: The message from the model
:param finish_reason: The reason the model stopped generating
:index: The index of the choice
:logprobs: (Optional) The log probabilities for the tokens in the message
:param index: The index of the choice
:param logprobs: (Optional) The log probabilities for the tokens in the message
"""
message: OpenAIMessageParam
@ -699,7 +732,7 @@ class OpenAIChatCompletionChunk(BaseModel):
"""
id: str
choices: List[OpenAIChoice]
choices: List[OpenAIChunkChoice]
object: Literal["chat.completion.chunk"] = "chat.completion.chunk"
created: int
model: str

136
llama_stack/providers/remote/inference/groq/groq.py
View file

@ -4,8 +4,24 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import Any, AsyncIterator, Dict, List, Optional, Union
from openai import AsyncOpenAI
from llama_stack.apis.inference.inference import (
OpenAIChatCompletion,
OpenAIChatCompletionChunk,
OpenAIChoiceDelta,
OpenAIChunkChoice,
OpenAIMessageParam,
OpenAIResponseFormatParam,
OpenAISystemMessageParam,
)
from llama_stack.providers.remote.inference.groq.config import GroqConfig
from llama_stack.providers.utils.inference.litellm_openai_mixin import LiteLLMOpenAIMixin
from llama_stack.providers.utils.inference.openai_compat import (
prepare_openai_completion_params,
)
from .models import MODEL_ENTRIES
@ -21,9 +37,129 @@ class GroqInferenceAdapter(LiteLLMOpenAIMixin):
provider_data_api_key_field="groq_api_key",
)
self.config = config
self._openai_client = None
async def initialize(self):
await super().initialize()
async def shutdown(self):
await super().shutdown()
if self._openai_client:
await self._openai_client.close()
self._openai_client = None
def _get_openai_client(self) -> AsyncOpenAI:
if not self._openai_client:
self._openai_client = AsyncOpenAI(
base_url=f"{self.config.url}/openai/v1",
api_key=self.config.api_key,
)
return self._openai_client
async def openai_chat_completion(
self,
model: str,
messages: List[OpenAIMessageParam],
frequency_penalty: Optional[float] = None,
function_call: Optional[Union[str, Dict[str, Any]]] = None,
functions: Optional[List[Dict[str, Any]]] = None,
logit_bias: Optional[Dict[str, float]] = None,
logprobs: Optional[bool] = None,
max_completion_tokens: Optional[int] = None,
max_tokens: Optional[int] = None,
n: Optional[int] = None,
parallel_tool_calls: Optional[bool] = None,
presence_penalty: Optional[float] = None,
response_format: Optional[OpenAIResponseFormatParam] = None,
seed: Optional[int] = None,
stop: Optional[Union[str, List[str]]] = None,
stream: Optional[bool] = None,
stream_options: Optional[Dict[str, Any]] = None,
temperature: Optional[float] = None,
tool_choice: Optional[Union[str, Dict[str, Any]]] = None,
tools: Optional[List[Dict[str, Any]]] = None,
top_logprobs: Optional[int] = None,
top_p: Optional[float] = None,
user: Optional[str] = None,
) -> Union[OpenAIChatCompletion, AsyncIterator[OpenAIChatCompletionChunk]]:
model_obj = await self.model_store.get_model(model)
# Groq does not support json_schema response format, so we need to convert it to json_object
if response_format and response_format.type == "json_schema":
response_format.type = "json_object"
schema = response_format.json_schema.get("schema", {})
response_format.json_schema = None
json_instructions = f"\nYour response should be a JSON object that matches the following schema: {schema}"
if messages and messages[0].role == "system":
messages[0].content = messages[0].content + json_instructions
else:
messages.insert(0, OpenAISystemMessageParam(content=json_instructions))
# Groq returns a 400 error if tools are provided but none are called
# So, set tool_choice to "required" to attempt to force a call
if tools and (not tool_choice or tool_choice == "auto"):
tool_choice = "required"
params = await prepare_openai_completion_params(
model=model_obj.provider_resource_id.replace("groq/", ""),
messages=messages,
frequency_penalty=frequency_penalty,
function_call=function_call,
functions=functions,
logit_bias=logit_bias,
logprobs=logprobs,
max_completion_tokens=max_completion_tokens,
max_tokens=max_tokens,
n=n,
parallel_tool_calls=parallel_tool_calls,
presence_penalty=presence_penalty,
response_format=response_format,
seed=seed,
stop=stop,
stream=stream,
stream_options=stream_options,
temperature=temperature,
tool_choice=tool_choice,
tools=tools,
top_logprobs=top_logprobs,
top_p=top_p,
user=user,
)
# Groq does not support streaming requests that set response_format
fake_stream = False
if stream and response_format:
params["stream"] = False
fake_stream = True
response = await self._get_openai_client().chat.completions.create(**params)
if fake_stream:
chunk_choices = []
for choice in response.choices:
delta = OpenAIChoiceDelta(
content=choice.message.content,
role=choice.message.role,
tool_calls=choice.message.tool_calls,
)
chunk_choice = OpenAIChunkChoice(
delta=delta,
finish_reason=choice.finish_reason,
index=choice.index,
logprobs=None,
)
chunk_choices.append(chunk_choice)
chunk = OpenAIChatCompletionChunk(
id=response.id,
choices=chunk_choices,
object="chat.completion.chunk",
created=response.created,
model=response.model,
)
async def _fake_stream_generator():
yield chunk
return _fake_stream_generator()
else:
return response

8
llama_stack/providers/remote/inference/groq/models.py
View file

@ -39,8 +39,16 @@ MODEL_ENTRIES = [
"groq/llama-4-scout-17b-16e-instruct",
CoreModelId.llama4_scout_17b_16e_instruct.value,
),
build_hf_repo_model_entry(
"groq/meta-llama/llama-4-scout-17b-16e-instruct",
CoreModelId.llama4_scout_17b_16e_instruct.value,
),
build_hf_repo_model_entry(
"groq/llama-4-maverick-17b-128e-instruct",
CoreModelId.llama4_maverick_17b_128e_instruct.value,
),
build_hf_repo_model_entry(
"groq/meta-llama/llama-4-maverick-17b-128e-instruct",
CoreModelId.llama4_maverick_17b_128e_instruct.value,
),
]

4
llama_stack/providers/utils/inference/litellm_openai_mixin.py
View file

@ -298,7 +298,7 @@ class LiteLLMOpenAIMixin(
guided_choice=guided_choice,
prompt_logprobs=prompt_logprobs,
)
return litellm.text_completion(**params)
return await litellm.atext_completion(**params)
async def openai_chat_completion(
self,
@ -352,7 +352,7 @@ class LiteLLMOpenAIMixin(
top_p=top_p,
user=user,
)
return litellm.completion(**params)
return await litellm.acompletion(**params)
async def batch_completion(
self,

9
llama_stack/providers/utils/inference/openai_compat.py
View file

@ -1354,14 +1354,7 @@ class OpenAIChatCompletionToLlamaStackMixin:
i = 0
async for chunk in response:
event = chunk.event
if event.stop_reason == StopReason.end_of_turn:
finish_reason = "stop"
elif event.stop_reason == StopReason.end_of_message:
finish_reason = "eos"
elif event.stop_reason == StopReason.out_of_tokens:
finish_reason = "length"
else:
finish_reason = None
finish_reason = _convert_stop_reason_to_openai_finish_reason(event.stop_reason)
if isinstance(event.delta, TextDelta):
text_delta = event.delta.text

20
llama_stack/templates/dev/run.yaml
View file

@ -386,6 +386,16 @@ models:
provider_id: groq
provider_model_id: groq/llama-4-scout-17b-16e-instruct
model_type: llm
- metadata: {}
model_id: groq/meta-llama/llama-4-scout-17b-16e-instruct
provider_id: groq
provider_model_id: groq/meta-llama/llama-4-scout-17b-16e-instruct
model_type: llm
- metadata: {}
model_id: meta-llama/Llama-4-Scout-17B-16E-Instruct
provider_id: groq
provider_model_id: groq/meta-llama/llama-4-scout-17b-16e-instruct
model_type: llm
- metadata: {}
model_id: groq/llama-4-maverick-17b-128e-instruct
provider_id: groq
@ -396,6 +406,16 @@ models:
provider_id: groq
provider_model_id: groq/llama-4-maverick-17b-128e-instruct
model_type: llm
- metadata: {}
model_id: groq/meta-llama/llama-4-maverick-17b-128e-instruct
provider_id: groq
provider_model_id: groq/meta-llama/llama-4-maverick-17b-128e-instruct
model_type: llm
- metadata: {}
model_id: meta-llama/Llama-4-Maverick-17B-128E-Instruct
provider_id: groq
provider_model_id: groq/meta-llama/llama-4-maverick-17b-128e-instruct
model_type: llm
- metadata:
embedding_dimension: 384
model_id: all-MiniLM-L6-v2

20
llama_stack/templates/groq/run.yaml
View file

@ -158,6 +158,16 @@ models:
provider_id: groq
provider_model_id: groq/llama-4-scout-17b-16e-instruct
model_type: llm
- metadata: {}
model_id: groq/meta-llama/llama-4-scout-17b-16e-instruct
provider_id: groq
provider_model_id: groq/meta-llama/llama-4-scout-17b-16e-instruct
model_type: llm
- metadata: {}
model_id: meta-llama/Llama-4-Scout-17B-16E-Instruct
provider_id: groq
provider_model_id: groq/meta-llama/llama-4-scout-17b-16e-instruct
model_type: llm
- metadata: {}
model_id: groq/llama-4-maverick-17b-128e-instruct
provider_id: groq
@ -168,6 +178,16 @@ models:
provider_id: groq
provider_model_id: groq/llama-4-maverick-17b-128e-instruct
model_type: llm
- metadata: {}
model_id: groq/meta-llama/llama-4-maverick-17b-128e-instruct
provider_id: groq
provider_model_id: groq/meta-llama/llama-4-maverick-17b-128e-instruct
model_type: llm
- metadata: {}
model_id: meta-llama/Llama-4-Maverick-17B-128E-Instruct
provider_id: groq
provider_model_id: groq/meta-llama/llama-4-maverick-17b-128e-instruct
model_type: llm
- metadata:
embedding_dimension: 384
model_id: all-MiniLM-L6-v2

20
llama_stack/templates/verification/run.yaml
View file

@ -474,6 +474,16 @@ models:
provider_id: groq-openai-compat
provider_model_id: groq/llama-4-scout-17b-16e-instruct
model_type: llm
- metadata: {}
model_id: groq/meta-llama/llama-4-scout-17b-16e-instruct
provider_id: groq-openai-compat
provider_model_id: groq/meta-llama/llama-4-scout-17b-16e-instruct
model_type: llm
- metadata: {}
model_id: meta-llama/Llama-4-Scout-17B-16E-Instruct
provider_id: groq-openai-compat
provider_model_id: groq/meta-llama/llama-4-scout-17b-16e-instruct
model_type: llm
- metadata: {}
model_id: groq/llama-4-maverick-17b-128e-instruct
provider_id: groq-openai-compat
@ -484,6 +494,16 @@ models:
provider_id: groq-openai-compat
provider_model_id: groq/llama-4-maverick-17b-128e-instruct
model_type: llm
- metadata: {}
model_id: groq/meta-llama/llama-4-maverick-17b-128e-instruct
provider_id: groq-openai-compat
provider_model_id: groq/meta-llama/llama-4-maverick-17b-128e-instruct
model_type: llm
- metadata: {}
model_id: meta-llama/Llama-4-Maverick-17B-128E-Instruct
provider_id: groq-openai-compat
provider_model_id: groq/meta-llama/llama-4-maverick-17b-128e-instruct
model_type: llm
- metadata: {}
model_id: Meta-Llama-3.1-8B-Instruct
provider_id: sambanova-openai-compat

14
tests/verifications/conf/groq-llama-stack.yaml Normal file
View file

@ -0,0 +1,14 @@
base_url: http://localhost:8321/v1/openai/v1
api_key_var: GROQ_API_KEY
models:
- groq/llama-3.3-70b-versatile
- groq/llama-4-scout-17b-16e-instruct
- groq/llama-4-maverick-17b-128e-instruct
model_display_names:
groq/llama-3.3-70b-versatile: Llama-3.3-70B-Instruct
groq/llama-4-scout-17b-16e-instruct: Llama-4-Scout-Instruct
groq/llama-4-maverick-17b-128e-instruct: Llama-4-Maverick-Instruct
test_exclusions:
groq/llama-3.3-70b-versatile:
- test_chat_non_streaming_image
- test_chat_streaming_image

8
tests/verifications/conf/groq.yaml
View file

@ -2,12 +2,12 @@ base_url: https://api.groq.com/openai/v1
api_key_var: GROQ_API_KEY
models:
- llama-3.3-70b-versatile
- llama-4-scout-17b-16e-instruct
- llama-4-maverick-17b-128e-instruct
- meta-llama/llama-4-scout-17b-16e-instruct
- meta-llama/llama-4-maverick-17b-128e-instruct
model_display_names:
llama-3.3-70b-versatile: Llama-3.3-70B-Instruct
llama-4-scout-17b-16e-instruct: Llama-4-Scout-Instruct
llama-4-maverick-17b-128e-instruct: Llama-4-Maverick-Instruct
meta-llama/llama-4-scout-17b-16e-instruct: Llama-4-Scout-Instruct
meta-llama/llama-4-maverick-17b-128e-instruct: Llama-4-Maverick-Instruct
test_exclusions:
llama-3.3-70b-versatile:
- test_chat_non_streaming_image

8
tests/verifications/conf/openai-llama-stack.yaml
View file

@ -1,9 +1,9 @@
base_url: http://localhost:8321/v1/openai/v1
api_key_var: OPENAI_API_KEY
models:
- gpt-4o
- gpt-4o-mini
- openai/gpt-4o
- openai/gpt-4o-mini
model_display_names:
gpt-4o: gpt-4o
gpt-4o-mini: gpt-4o-mini
openai/gpt-4o: gpt-4o
openai/gpt-4o-mini: gpt-4o-mini
test_exclusions: {}

1
tests/verifications/generate_report.py
View file

@ -75,6 +75,7 @@ PROVIDER_ORDER = [
"openai",
"together-llama-stack",
"fireworks-llama-stack",
"groq-llama-stack",
"openai-llama-stack",
]

20
tests/verifications/openai-api-verification-run.yaml
View file

@ -17,6 +17,11 @@ providers:
config:
url: https://api.fireworks.ai/inference/v1
api_key: ${env.FIREWORKS_API_KEY}
- provider_id: groq
provider_type: remote::groq
config:
url: https://api.groq.com
api_key: ${env.GROQ_API_KEY}
- provider_id: openai
provider_type: remote::openai
config:
@ -98,6 +103,21 @@ models:
provider_id: fireworks
provider_model_id: accounts/fireworks/models/llama4-maverick-instruct-basic
model_type: llm
- metadata: {}
model_id: groq/llama-3.3-70b-versatile
provider_id: groq
provider_model_id: groq/llama-3.3-70b-versatile
model_type: llm
- metadata: {}
model_id: groq/llama-4-scout-17b-16e-instruct
provider_id: groq
provider_model_id: groq/meta-llama/llama-4-scout-17b-16e-instruct
model_type: llm
- metadata: {}
model_id: groq/llama-4-maverick-17b-128e-instruct
provider_id: groq
provider_model_id: groq/meta-llama/llama-4-maverick-17b-128e-instruct
model_type: llm
- metadata: {}
model_id: openai/gpt-4o
provider_id: openai