Merge branch 'main' into nvidia-e2e-notebook

This commit is contained in:
Jash Gulabrai 2025-04-15 08:38:41 -04:00
commit 7cdd2a0410
264 changed files with 229042 additions and 8445 deletions

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@ -5,7 +5,7 @@
# the root directory of this source tree.
from llama_stack.apis.models import ModelType
from llama_stack.models.llama.datatypes import CoreModelId
from llama_stack.models.llama.sku_types import CoreModelId
from llama_stack.providers.utils.inference.model_registry import (
ProviderModelEntry,
build_hf_repo_model_entry,

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@ -7,7 +7,7 @@
import logging
import warnings
from functools import lru_cache
from typing import AsyncIterator, List, Optional, Union
from typing import Any, AsyncIterator, Dict, List, Optional, Union
from openai import APIConnectionError, AsyncOpenAI, BadRequestError
@ -29,21 +29,27 @@ from llama_stack.apis.inference import (
LogProbConfig,
Message,
ResponseFormat,
SamplingParams,
TextTruncation,
ToolChoice,
ToolConfig,
)
from llama_stack.models.llama.datatypes import (
SamplingParams,
ToolDefinition,
ToolPromptFormat,
)
from llama_stack.apis.inference.inference import (
OpenAIChatCompletion,
OpenAIChatCompletionChunk,
OpenAICompletion,
OpenAIMessageParam,
OpenAIResponseFormatParam,
)
from llama_stack.models.llama.datatypes import ToolPromptFormat
from llama_stack.providers.utils.inference.model_registry import (
ModelRegistryHelper,
)
from llama_stack.providers.utils.inference.openai_compat import (
convert_openai_chat_completion_choice,
convert_openai_chat_completion_stream,
prepare_openai_completion_params,
)
from llama_stack.providers.utils.inference.prompt_adapter import content_has_media
@ -265,3 +271,111 @@ class NVIDIAInferenceAdapter(Inference, ModelRegistryHelper):
else:
# we pass n=1 to get only one completion
return convert_openai_chat_completion_choice(response.choices[0])
async def openai_completion(
self,
model: str,
prompt: Union[str, List[str], List[int], List[List[int]]],
best_of: Optional[int] = None,
echo: Optional[bool] = None,
frequency_penalty: Optional[float] = None,
logit_bias: Optional[Dict[str, float]] = None,
logprobs: Optional[bool] = None,
max_tokens: Optional[int] = None,
n: Optional[int] = None,
presence_penalty: Optional[float] = 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,
top_p: Optional[float] = None,
user: Optional[str] = None,
guided_choice: Optional[List[str]] = None,
prompt_logprobs: Optional[int] = None,
) -> OpenAICompletion:
provider_model_id = self.get_provider_model_id(model)
params = await prepare_openai_completion_params(
model=provider_model_id,
prompt=prompt,
best_of=best_of,
echo=echo,
frequency_penalty=frequency_penalty,
logit_bias=logit_bias,
logprobs=logprobs,
max_tokens=max_tokens,
n=n,
presence_penalty=presence_penalty,
seed=seed,
stop=stop,
stream=stream,
stream_options=stream_options,
temperature=temperature,
top_p=top_p,
user=user,
)
try:
return await self._get_client(provider_model_id).completions.create(**params)
except APIConnectionError as e:
raise ConnectionError(f"Failed to connect to NVIDIA NIM at {self._config.url}: {e}") from e
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]]:
provider_model_id = self.get_provider_model_id(model)
params = await prepare_openai_completion_params(
model=provider_model_id,
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,
)
try:
return await self._get_client(provider_model_id).chat.completions.create(**params)
except APIConnectionError as e:
raise ConnectionError(f"Failed to connect to NVIDIA NIM at {self._config.url}: {e}") from e

View file

@ -19,11 +19,9 @@ from llama_stack.apis.inference import (
CompletionRequest,
CompletionResponse,
CompletionResponseStreamChunk,
GreedySamplingStrategy,
JsonSchemaResponseFormat,
TokenLogProbs,
)
from llama_stack.models.llama.datatypes import (
GreedySamplingStrategy,
TopKSamplingStrategy,
TopPSamplingStrategy,
)