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chore: remove /v1/inference/completion and implementations

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Matthew Farrellee 2025-09-30 03:46:07 -04:00
parent 606f4cf281
commit 4b641d7127
78 changed files with 16143 additions and 17755 deletions
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57
llama_stack/providers/remote/inference/together/together.py
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@ -10,13 +10,9 @@ from openai import AsyncOpenAI
from together import AsyncTogether
from together.constants import BASE_URL
from llama_stack.apis.common.content_types import (
InterleavedContent,
)
from llama_stack.apis.inference import (
ChatCompletionRequest,
ChatCompletionResponse,
CompletionRequest,
Inference,
LogProbConfig,
Message,
@ -39,13 +35,10 @@ from llama_stack.providers.utils.inference.openai_compat import (
get_sampling_options,
process_chat_completion_response,
process_chat_completion_stream_response,
process_completion_response,
process_completion_stream_response,
)
from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
from llama_stack.providers.utils.inference.prompt_adapter import (
chat_completion_request_to_prompt,
completion_request_to_prompt,
request_has_media,
)
@ -81,31 +74,6 @@ class TogetherInferenceAdapter(OpenAIMixin, ModelRegistryHelper, Inference, Need
async def shutdown(self) -> None:
pass
async def completion(
self,
model_id: str,
content: InterleavedContent,
sampling_params: SamplingParams | None = None,
response_format: ResponseFormat | None = None,
stream: bool | None = False,
logprobs: LogProbConfig | None = None,
) -> AsyncGenerator:
if sampling_params is None:
sampling_params = SamplingParams()
model = await self.model_store.get_model(model_id)
request = CompletionRequest(
model=model.provider_resource_id,
content=content,
sampling_params=sampling_params,
response_format=response_format,
stream=stream,
logprobs=logprobs,
)
if stream:
return self._stream_completion(request)
else:
return await self._nonstream_completion(request)
def _get_client(self) -> AsyncTogether:
together_api_key = None
config_api_key = self.config.api_key.get_secret_value() if self.config.api_key else None
@ -127,19 +95,6 @@ class TogetherInferenceAdapter(OpenAIMixin, ModelRegistryHelper, Inference, Need
api_key=together_client.api_key,
)
async def _nonstream_completion(self, request: CompletionRequest) -> ChatCompletionResponse:
params = await self._get_params(request)
client = self._get_client()
r = await client.completions.create(**params)
return process_completion_response(r)
async def _stream_completion(self, request: CompletionRequest) -> AsyncGenerator:
params = await self._get_params(request)
client = self._get_client()
stream = await client.completions.create(**params)
async for chunk in process_completion_stream_response(stream):
yield chunk
def _build_options(
self,
sampling_params: SamplingParams | None,
@ -219,18 +174,14 @@ class TogetherInferenceAdapter(OpenAIMixin, ModelRegistryHelper, Inference, Need
async for chunk in process_chat_completion_stream_response(stream, request):
yield chunk
async def _get_params(self, request: ChatCompletionRequest | CompletionRequest) -> dict:
async def _get_params(self, request: ChatCompletionRequest) -> dict:
input_dict = {}
media_present = request_has_media(request)
llama_model = self.get_llama_model(request.model)
if isinstance(request, ChatCompletionRequest):
if media_present or not llama_model:
input_dict["messages"] = [await convert_message_to_openai_dict(m) for m in request.messages]
else:
input_dict["prompt"] = await chat_completion_request_to_prompt(request, llama_model)
if media_present or not llama_model:
input_dict["messages"] = [await convert_message_to_openai_dict(m) for m in request.messages]
else:
assert not media_present, "Together does not support media for Completion requests"
input_dict["prompt"] = await completion_request_to_prompt(request)
input_dict["prompt"] = await chat_completion_request_to_prompt(request, llama_model)
params = {
"model": request.model,