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(sap) run black formater

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This commit is contained in:
Vasilisa Parshikova 2026-03-13 15:48:48 +04:00
parent a105cb336d
commit 4c816c53ad
5 changed files with 127 additions and 77 deletions
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7
litellm/llms/sap/chat/handler.py
View file

@ -251,11 +251,8 @@ class AsyncSAPStreamIterator:
# -------------------------------
class GenAIHubOrchestration(BaseLLMHTTPHandler):
def _add_stream_param_to_request_body(
self,
data: dict,
provider_config: BaseConfig,
fake_stream: bool
):
self, data: dict, provider_config: BaseConfig, fake_stream: bool
):
if data.get("config", {}).get("stream", None) is not None:
data["config"]["stream"]["enabled"] = True
else:

77
litellm/llms/sap/chat/models.py
View file

@ -1,6 +1,6 @@
from typing import Union, Literal, Optional
from enum import Enum
import warnings
import warnings
from pydantic import BaseModel, Field, field_validator, model_validator
@ -9,16 +9,16 @@ def validate_different_content(v: Union[str, dict, list]) -> str:
if v in ((), {}, []):
return ""
elif isinstance(v, dict) and "text" in v:
return v['text']
return v["text"]
elif isinstance(v, list):
new_v = []
for item in v:
if isinstance(item, dict) and "text" in item:
if item['text']:
new_v.append(item['text'])
if item["text"]:
new_v.append(item["text"])
elif isinstance(item, str):
new_v.append(item)
return '\n'.join(new_v)
return "\n".join(new_v)
elif isinstance(v, str):
return v
raise ValueError("Content must be a string")
@ -82,7 +82,9 @@ class SAPMessage(BaseModel):
role: Literal["system", "developer"] = "system"
content: str
_content_validator = field_validator("content", mode="before")(validate_different_content)
_content_validator = field_validator("content", mode="before")(
validate_different_content
)
class SAPUserMessage(BaseModel):
@ -98,8 +100,9 @@ class SAPAssistantMessage(BaseModel):
refusal: str = ""
tool_calls: list[MessageToolCall] = []
_content_validator = field_validator("content", mode="before")(validate_different_content)
_content_validator = field_validator("content", mode="before")(
validate_different_content
)
class SAPToolChatMessage(BaseModel):
@ -107,7 +110,9 @@ class SAPToolChatMessage(BaseModel):
tool_call_id: str
content: str
_content_validator = field_validator("content", mode="before")(validate_different_content)
_content_validator = field_validator("content", mode="before")(
validate_different_content
)
ChatMessage = Union[SAPUserMessage, SAPAssistantMessage, SAPToolChatMessage, SAPMessage]
@ -135,14 +140,14 @@ class KeyValueListPair(BaseModel):
class DocumentMetadataKeyValueListPairs(KeyValueListPair):
select_mode: Optional[list[Literal['ignoreIfKeyAbsent']]] = None
select_mode: Optional[list[Literal["ignoreIfKeyAbsent"]]] = None
class GroundingSearchConfig(BaseModel):
max_chunk_count: Optional[int] = Field(default=None, ge=0)
max_document_count: Optional[int] = Field(default=None, ge=0)
@model_validator(mode='after')
@model_validator(mode="after")
def validate_max_chunk_count_and_max_document_count(self):
if self.max_chunk_count is not None and self.max_document_count is not None:
raise ValueError("Cannot specify both maxChunkCount and maxDocumentCount.")
@ -153,7 +158,7 @@ class DocumentGroundingFilter(BaseModel):
id_: Optional[str] = Field(default=None, alias="id")
data_repository_type: Literal["vector", "help.sap.com"]
search_config: Optional[GroundingSearchConfig] = None
data_repositories: Optional[list[str]]= None
data_repositories: Optional[list[str]] = None
data_repository_metadata: Optional[list[KeyValueListPair]] = None
document_metadata: Optional[list[DocumentMetadataKeyValueListPairs]] = None
chunk_metadata: Optional[list[KeyValueListPair]] = None
@ -171,7 +176,9 @@ class DocumentGroundingConfig(BaseModel):
class GroundingModuleConfig(BaseModel):
type_: Literal["document_grounding_service"] = Field(default="document_grounding_service", alias="type")
type_: Literal["document_grounding_service"] = Field(
default="document_grounding_service", alias="type"
)
config: DocumentGroundingConfig
@ -284,6 +291,7 @@ class DPIMethodConstant(BaseModel):
"""
Replaces the entity with the specified value followed by an incrementing number
"""
method: Literal["constant"] = "constant"
value: str
@ -292,6 +300,7 @@ class DPIMethodFabricatedData(BaseModel):
"""
Replaces the entity with a randomly generated value appropriate to its type.
"""
method: Literal["fabricated_data"] = "fabricated_data"
@ -300,6 +309,7 @@ class DPICustomEntity(BaseModel):
regex: Regular expression to match the entity
replacement_strategy: Replacement strategy to be used for the entity
"""
regex: str
replacement_strategy: DPIMethodConstant
@ -309,8 +319,11 @@ class DPIStandardEntity(BaseModel):
type: Standard entity type to be masked
replacement_strategy: Replacement strategy to be used for the entity
"""
type_: SAPMaskingProfileEntity = Field(..., alias="type")
replacement_strategy: Optional[Union[DPIMethodConstant, DPIMethodFabricatedData]] = None
replacement_strategy: Optional[
Union[DPIMethodConstant, DPIMethodFabricatedData]
] = None
class MaskGroundingInput(BaseModel):
@ -318,6 +331,7 @@ class MaskGroundingInput(BaseModel):
Controls whether the input to the grounding module will be masked with the configuration
supplied in the masking module
"""
enabled: bool = False
@ -338,6 +352,7 @@ class MaskingProviderConfig(BaseModel):
mask_grounding_input: A flag indicating whether to mask input to the grounding module.
"""
type_: str = Field(default="sap_data_privacy_integration", alias="type")
method: Literal["anonymization", "pseudonymization"]
entities: list[Union[DPIStandardEntity, DPICustomEntity]]
@ -355,12 +370,14 @@ class MaskingModuleConfig(BaseModel):
IMPORTANT: use exactly one of the parameters to set the list of masking provider configurations.
DEPRECATED: parameter 'masking_providers' will be removed Sept 15, 2026. Use 'providers' instead.
"""
providers: Optional[list[MaskingProviderConfig]] = Field(min_length=1, default=None)
masking_providers: Optional[list[MaskingProviderConfig]] = Field(min_length=1, default=None)
masking_providers: Optional[list[MaskingProviderConfig]] = Field(
min_length=1, default=None
)
@model_validator(mode="after")
def enforce_exactly_one_provider_list(self):
has_providers = self.providers is not None
has_masking_providers = self.masking_providers is not None
@ -443,7 +460,8 @@ class AzureContentSafetyInput(AzureContentFilter):
self_harm: Threshold for self-harm content.
prompt_shield: A flag to use prompt shield
"""
"""
prompt_shield: Optional[bool] = False
@ -539,29 +557,34 @@ class FilteringStreamOptions(BaseModel):
overlap: Number of characters that should be additionally sent to content filtering services
from previous chunks as additional context.
"""
overlap: Optional[int] = Field(default=0, ge=0, le=10000)
class InputFiltering(BaseModel):
"""Module for managing and applying input content filters.
Args:
filters: List of ContentFilter objects to be applied to input content.
Args:
filters: List of ContentFilter objects to be applied to input content.
"""
filters: list[Union[AzureContentSafetyInputFilterConfig, LlamaGuard38bFilterConfig]] = Field(min_length=1)
filters: list[
Union[AzureContentSafetyInputFilterConfig, LlamaGuard38bFilterConfig]
] = Field(min_length=1)
class OutputFiltering(BaseModel):
"""Module for managing and applying output content filters.
Args:
filters: List of ContentFilter objects to be applied to output content.
Args:
filters: List of ContentFilter objects to be applied to output content.
stream_options: Module-specific streaming options.
stream_options: Module-specific streaming options.
"""
filters: list[
Union[AzureContentSafetyOutputFilterConfig, LlamaGuard38bFilterConfig]] = Field(min_length=1)
Union[AzureContentSafetyOutputFilterConfig, LlamaGuard38bFilterConfig]
] = Field(min_length=1)
stream_options: Optional[FilteringStreamOptions] = None
@ -573,6 +596,7 @@ class FilteringModuleConfig(BaseModel):
output: Module for filtering and validating output content after generation.
"""
input: Optional[InputFiltering] = None
output: Optional[OutputFiltering] = None
@ -598,6 +622,7 @@ class SAPDocumentTranslationApplyToSelector(BaseModel):
targets the value of "user_input" in placeholder_values specified in the request payload;
and considers the value to be in German.
"""
category: Literal["placeholders", "template_roles"]
items: list[str]
source_language: str
@ -612,6 +637,7 @@ class InputTranslationConfig(BaseModel):
target_language: Language to which the text should be translated. Example: en-US
apply_to: List of selectors that define the scope of translation.
"""
source_language: Optional[str] = None
target_language: str
apply_to: Optional[list[SAPDocumentTranslationApplyToSelector]] = None
@ -633,6 +659,7 @@ class SAPDocumentTranslationInput(BaseModel):
config: Configuration object for the translation module.
"""
type_: str = Field(default="sap_document_translation", alias="type")
translate_messages_history: Optional[bool] = None
config: InputTranslationConfig
@ -647,6 +674,7 @@ class SAPDocumentTranslationOutput(BaseModel):
config: Configuration object for the translation module.
"""
type_: str = Field(default="sap_document_translation", alias="type")
config: OutputTranslationConfig
@ -660,6 +688,7 @@ class TranslationModuleConfig(BaseModel):
output: Configuration for output translation
"""
input: Optional[SAPDocumentTranslationInput] = None
output: Optional[SAPDocumentTranslationOutput] = None

94
litellm/llms/sap/chat/transformation.py
View file

@ -1,7 +1,17 @@
"""
Translate from OpenAI's `/v1/chat/completions` to SAP Generative AI Hub's Orchestration Service`v2/completion`
"""
from typing import List, Optional, Union, Dict, Tuple, Any, TYPE_CHECKING, Iterator, AsyncIterator
from typing import (
List,
Optional,
Union,
Dict,
Tuple,
Any,
TYPE_CHECKING,
Iterator,
AsyncIterator,
)
from functools import cached_property
import litellm
import httpx
@ -21,7 +31,12 @@ else:
from ..credentials import get_token_creator
from .models import ResponseFormatJSONSchema, ResponseFormat, OrchestrationRequest
from .handler import GenAIHubOrchestrationError, AsyncSAPStreamIterator, SAPStreamIterator
from .handler import (
GenAIHubOrchestrationError,
AsyncSAPStreamIterator,
SAPStreamIterator,
)
def validate_dict(data: dict, model) -> dict:
return model(**data).model_dump(by_alias=True, exclude_unset=True)
@ -69,16 +84,15 @@ class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
def run_env_setup(self, service_key: Optional[str] = None) -> None:
try:
self.token_creator, self._base_url, self._resource_group = get_token_creator(service_key) # type: ignore
self.token_creator, self._base_url, self._resource_group = get_token_creator(service_key) # type: ignore
except ValueError as err:
raise GenAIHubOrchestrationError(status_code=400, message=err.args[0])
@property
def headers(self) -> Dict[str, str]:
if self.token_creator is None:
self.run_env_setup()
access_token = self.token_creator() # type: ignore
access_token = self.token_creator() # type: ignore
return {
"Authorization": access_token,
"AI-Resource-Group": self.resource_group,
@ -90,14 +104,13 @@ class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
def base_url(self) -> str:
if self._base_url is None:
self.run_env_setup()
return self._base_url # type: ignore
return self._base_url # type: ignore
@property
def resource_group(self) -> str:
if self._resource_group is None:
self.run_env_setup()
return self._resource_group # type: ignore
return self._resource_group # type: ignore
@cached_property
def deployment_url(self) -> str:
@ -161,7 +174,6 @@ class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
params.remove("tool_choice")
return params
def validate_environment(
self,
headers: dict,
@ -177,13 +189,13 @@ class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
return self.headers
def get_complete_url(
self,
api_base: Optional[str],
api_key: Optional[str],
model: str,
optional_params: dict,
litellm_params: dict,
stream: Optional[bool] = None,
self,
api_base: Optional[str],
api_key: Optional[str],
model: str,
optional_params: dict,
litellm_params: dict,
stream: Optional[bool] = None,
):
api_base_ = f"{self.deployment_url}/v2/completion"
return api_base_
@ -191,7 +203,7 @@ class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
def transform_request(
self,
model: str,
messages: List[Dict[str, str]], # type: ignore
messages: List[Dict[str, str]], # type: ignore
optional_params: dict,
litellm_params: dict,
headers: dict,
@ -220,7 +232,9 @@ class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
resp_type = response_format.get("type", None)
if resp_type:
if resp_type == "json_schema":
response_format = validate_dict(response_format, ResponseFormatJSONSchema)
response_format = validate_dict(
response_format, ResponseFormatJSONSchema
)
else:
response_format = validate_dict(response_format, ResponseFormat)
response_format = {"response_format": response_format}
@ -228,7 +242,9 @@ class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
response_format = {}
placeholder_defaults = params.pop("placeholder_defaults", {})
placeholder_defaults = {"defaults": placeholder_defaults} if placeholder_defaults else {}
placeholder_defaults = (
{"defaults": placeholder_defaults} if placeholder_defaults else {}
)
optional_modules = {}
optional_modules_lst = ["grounding", "masking", "filtering", "translation"]
@ -265,7 +281,9 @@ class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
stream_config["delimiters"] = stream_options.get("delimiters")
placeholder_values = optional_params.pop("placeholder_values", {})
placeholder_values = {"placeholder_values": placeholder_values} if placeholder_values else {}
placeholder_values = (
{"placeholder_values": placeholder_values} if placeholder_values else {}
)
fallback_modules = optional_params.pop("fallback_sap_modules", [])
@ -304,7 +322,7 @@ class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
request_body = {
"config": {
"modules": modules_payload,
**({"stream": stream_config} if stream_config else {})
**({"stream": stream_config} if stream_config else {}),
},
**placeholder_values,
}
@ -314,18 +332,18 @@ class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
return body
def transform_response(
self,
model: str,
raw_response: httpx.Response,
model_response: ModelResponse,
logging_obj: LiteLLMLoggingObj,
request_data: dict,
messages: List[AllMessageValues],
optional_params: dict,
litellm_params: dict,
encoding: Any,
api_key: Optional[str] = None,
json_mode: Optional[bool] = None,
self,
model: str,
raw_response: httpx.Response,
model_response: ModelResponse,
logging_obj: LiteLLMLoggingObj,
request_data: dict,
messages: List[AllMessageValues],
optional_params: dict,
litellm_params: dict,
encoding: Any,
api_key: Optional[str] = None,
json_mode: Optional[bool] = None,
) -> ModelResponse:
logging_obj.post_call(
input=messages,
@ -359,17 +377,17 @@ class GenAIHubOrchestrationConfig(OpenAIGPTConfig):
if choice.message and choice.message.content:
content = choice.message.content.strip()
# Match ```json ... ``` or ``` ... ```
match = re.match(r'^```(?:json)?\s*\n?(.*?)\n?```$', content, re.DOTALL)
match = re.match(r"^```(?:json)?\s*\n?(.*?)\n?```$", content, re.DOTALL)
if match:
choice.message.content = match.group(1).strip()
return response
def get_model_response_iterator(
self,
streaming_response: Union[Iterator[str], AsyncIterator[str], "ModelResponse"],
sync_stream: bool,
json_mode: Optional[bool] = False,
self,
streaming_response: Union[Iterator[str], AsyncIterator[str], "ModelResponse"],
sync_stream: bool,
json_mode: Optional[bool] = False,
):
if sync_stream:
return SAPStreamIterator(response=streaming_response) # type: ignore

15
litellm/llms/sap/credentials.py
View file

@ -180,7 +180,9 @@ def _resolve_value(
return cred.default
def fetch_credentials(service_key: Optional[str] = None, profile: Optional[str] = None, **kwargs) -> Dict[str, str]:
def fetch_credentials(
service_key: Optional[str] = None, profile: Optional[str] = None, **kwargs
) -> Dict[str, str]:
"""
Resolution order per key:
kwargs
@ -196,8 +198,11 @@ def fetch_credentials(service_key: Optional[str] = None, profile: Optional[str]
if not config:
# Prefer AICORE_SERVICE_KEY if present; otherwise fall back to the VCAP service.
service_like = service_key or sap_service_key or _load_json_env(SERVICE_KEY_ENV_VAR) or _get_vcap_service(
VCAP_AICORE_SERVICE_NAME
service_like = (
service_key
or sap_service_key
or _load_json_env(SERVICE_KEY_ENV_VAR)
or _get_vcap_service(VCAP_AICORE_SERVICE_NAME)
)
out: Dict[str, str] = {}
@ -241,7 +246,9 @@ def get_token_creator(
"""
# Resolve credentials using your helper
credentials: Dict[str, str] = fetch_credentials(service_key=service_key, profile=profile, **overrides)
credentials: Dict[str, str] = fetch_credentials(
service_key=service_key, profile=profile, **overrides
)
auth_url = credentials.get("auth_url")
client_id = credentials.get("client_id")

11
litellm/llms/sap/embed/transformation.py
View file

@ -52,9 +52,11 @@ class EmbeddingModel(BaseModel):
timeout: Optional[int] = Field(default=None, ge=1, le=600)
max_retries: Optional[int] = Field(default=None, ge=0, le=5)
class EmbeddingsModelConfig(BaseModel):
model: EmbeddingModel
class EmbeddingsModules(BaseModel):
embeddings: EmbeddingsModelConfig
masking: Optional[MaskingModuleConfig] = None
@ -64,9 +66,11 @@ class EmbeddingInput(BaseModel):
text: Union[str, List[str]]
type: Optional[Literal["text", "document", "query"]] = None
class EmbeddingConfig(BaseModel):
modules: EmbeddingsModules
class EmbeddingRequest(BaseModel):
config: EmbeddingConfig
input: EmbeddingInput
@ -170,12 +174,7 @@ class GenAIHubEmbeddingConfig(BaseEmbeddingConfig):
masking = optional_params.get("masking")
masking = {"masking": masking} if masking is not None else {}
body = {
"config": {
"modules": {
"embeddings": {"model": model_dict},
**masking
}
},
"config": {"modules": {"embeddings": {"model": model_dict}, **masking}},
"input": input_dict,
}
body = validate_dict(body, EmbeddingRequest)