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pre-commit issues fix
This commit is contained in:
Sajikumar JS
parent
34a3f1a749
commit
efe5b124f3
7 changed files with 207 additions and 31 deletions
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@ -5,10 +5,11 @@
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# the root directory of this source tree.
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import os
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from typing import Optional, Dict, Any
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from typing import Any, Dict, Optional
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from pydantic import BaseModel, Field, SecretStr
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from llama_stack.schema_utils import json_schema_type
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from pydantic import BaseModel, Field, SecretStr
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class WatsonXProviderDataValidator(BaseModel):
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@ -19,7 +20,6 @@ class WatsonXProviderDataValidator(BaseModel):
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@json_schema_type
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class WatsonXConfig(BaseModel):
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url: str = Field(
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default_factory=lambda: os.getenv("WATSONX_BASE_URL", "https://us-south.ml.cloud.ibm.com"),
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description="A base url for accessing the Watsonx.ai",
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@ -42,5 +42,5 @@ class WatsonXConfig(BaseModel):
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return {
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"url": "${env.WATSONX_BASE_URL:https://us-south.ml.cloud.ibm.com}",
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"api_key": "${env.WATSONX_API_KEY:}",
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"project_id": "${env.WATSONX_PROJECT_ID:}"
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}
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"project_id": "${env.WATSONX_PROJECT_ID:}",
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}
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@ -43,7 +43,5 @@ MODEL_ENTRIES = [
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build_hf_repo_model_entry(
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"meta-llama/llama-guard-3-11b-vision",
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CoreModelId.llama_guard_3_11b_vision.value,
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)
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),
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]
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@ -6,8 +6,10 @@
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from typing import AsyncGenerator, List, Optional, Union
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from ibm_watson_machine_learning.foundation_models import Model
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from ibm_watson_machine_learning.metanames import GenTextParamsMetaNames as GenParams
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from llama_stack.apis.common.content_types import InterleavedContent, InterleavedContentItem
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from llama_stack.providers.utils.inference.model_registry import ModelRegistryHelper
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from llama_stack.apis.inference import (
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ChatCompletionRequest,
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ChatCompletionResponse,
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@ -18,7 +20,6 @@ from llama_stack.apis.inference import (
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LogProbConfig,
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Message,
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ResponseFormat,
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ResponseFormatType,
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SamplingParams,
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TextTruncation,
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ToolChoice,
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@ -26,6 +27,7 @@ from llama_stack.apis.inference import (
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ToolDefinition,
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ToolPromptFormat,
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)
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from llama_stack.providers.utils.inference.model_registry import ModelRegistryHelper
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from llama_stack.providers.utils.inference.openai_compat import (
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OpenAICompatCompletionChoice,
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OpenAICompatCompletionResponse,
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@ -41,14 +43,9 @@ from llama_stack.providers.utils.inference.prompt_adapter import (
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)
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from . import WatsonXConfig
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from ibm_watson_machine_learning.foundation_models import Model
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from ibm_watson_machine_learning.metanames import GenTextParamsMetaNames as GenParams
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from .models import MODEL_ENTRIES
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class WatsonXInferenceAdapter(Inference, ModelRegistryHelper):
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def __init__(self, config: WatsonXConfig) -> None:
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ModelRegistryHelper.__init__(self, MODEL_ENTRIES)
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@ -94,12 +91,9 @@ class WatsonXInferenceAdapter(Inference, ModelRegistryHelper):
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config_api_key = self._config.api_key.get_secret_value() if self._config.api_key else None
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config_url = self._config.url
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project_id = self._config.project_id
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credentials = {
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"url": config_url,
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"apikey": config_api_key
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}
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credentials = {"url": config_url, "apikey": config_api_key}
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return Model(model_id=model_id,credentials=credentials, project_id=project_id)
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return Model(model_id=model_id, credentials=credentials, project_id=project_id)
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async def _nonstream_completion(self, request: CompletionRequest) -> ChatCompletionResponse:
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params = await self._get_params(request)
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@ -186,6 +180,7 @@ class WatsonXInferenceAdapter(Inference, ModelRegistryHelper):
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async def _stream_chat_completion(self, request: ChatCompletionRequest) -> AsyncGenerator:
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params = await self._get_params(request)
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model_id = request.model
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# if we shift to TogetherAsyncClient, we won't need this wrapper
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async def _to_async_generator():
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s = self._get_client(model_id).generate_text_stream(**params)
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@ -225,19 +220,29 @@ class WatsonXInferenceAdapter(Inference, ModelRegistryHelper):
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if request.sampling_params.additional_params.get("temperature"):
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input_dict["params"][GenParams.TEMPERATURE] = request.sampling_params.additional_params["temperature"]
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if request.sampling_params.additional_params.get("length_penalty"):
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input_dict["params"][GenParams.LENGTH_PENALTY] = request.sampling_params.additional_params["length_penalty"]
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input_dict["params"][GenParams.LENGTH_PENALTY] = request.sampling_params.additional_params[
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"length_penalty"
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]
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if request.sampling_params.additional_params.get("random_seed"):
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input_dict["params"][GenParams.RANDOM_SEED] = request.sampling_params.additional_params["random_seed"]
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if request.sampling_params.additional_params.get("min_new_tokens"):
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input_dict["params"][GenParams.MIN_NEW_TOKENS] = request.sampling_params.additional_params["min_new_tokens"]
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input_dict["params"][GenParams.MIN_NEW_TOKENS] = request.sampling_params.additional_params[
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"min_new_tokens"
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]
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if request.sampling_params.additional_params.get("stop_sequences"):
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input_dict["params"][GenParams.STOP_SEQUENCES] = request.sampling_params.additional_params["stop_sequences"]
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input_dict["params"][GenParams.STOP_SEQUENCES] = request.sampling_params.additional_params[
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"stop_sequences"
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]
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if request.sampling_params.additional_params.get("time_limit"):
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input_dict["params"][GenParams.TIME_LIMIT] = request.sampling_params.additional_params["time_limit"]
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if request.sampling_params.additional_params.get("truncate_input_tokens"):
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input_dict["params"][GenParams.TRUNCATE_INPUT_TOKENS] = request.sampling_params.additional_params["truncate_input_tokens"]
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input_dict["params"][GenParams.TRUNCATE_INPUT_TOKENS] = request.sampling_params.additional_params[
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"truncate_input_tokens"
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]
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if request.sampling_params.additional_params.get("return_options"):
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input_dict["params"][GenParams.RETURN_OPTIONS] = request.sampling_params.additional_params["return_options"]
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input_dict["params"][GenParams.RETURN_OPTIONS] = request.sampling_params.additional_params[
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"return_options"
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]
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params = {
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**input_dict,
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