chore: initial snapshot for gitea/github upload

llm-gateway-competitors/litellm-wheel-src/litellm/llms/base_llm/image_variations/transformation.py

@@ -0,0 +1,134 @@
+from abc import ABC, abstractmethod
+from typing import TYPE_CHECKING, Any, List, Optional
+
+import httpx
+from aiohttp import ClientResponse
+
+from litellm.llms.base_llm.chat.transformation import BaseConfig
+from litellm.types.llms.openai import (
+    AllMessageValues,
+    OpenAIImageVariationOptionalParams,
+)
+from litellm.types.utils import (
+    FileTypes,
+    HttpHandlerRequestFields,
+    ImageResponse,
+    ModelResponse,
+)
+
+if TYPE_CHECKING:
+    from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+
+    LiteLLMLoggingObj = _LiteLLMLoggingObj
+else:
+    LiteLLMLoggingObj = Any
+
+
+class BaseImageVariationConfig(BaseConfig, ABC):
+    @abstractmethod
+    def get_supported_openai_params(
+        self, model: str
+    ) -> List[OpenAIImageVariationOptionalParams]:
+        pass
+
+    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,
+    ) -> str:
+        """
+        OPTIONAL
+
+        Get the complete url for the request
+
+        Some providers need `model` in `api_base`
+        """
+        return api_base or ""
+
+    @abstractmethod
+    def transform_request_image_variation(
+        self,
+        model: Optional[str],
+        image: FileTypes,
+        optional_params: dict,
+        headers: dict,
+    ) -> HttpHandlerRequestFields:
+        pass
+
+    def validate_environment(
+        self,
+        headers: dict,
+        model: str,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        litellm_params: dict,
+        api_key: Optional[str] = None,
+        api_base: Optional[str] = None,
+    ) -> dict:
+        return {}
+
+    @abstractmethod
+    async def async_transform_response_image_variation(
+        self,
+        model: Optional[str],
+        raw_response: ClientResponse,
+        model_response: ImageResponse,
+        logging_obj: LiteLLMLoggingObj,
+        request_data: dict,
+        image: FileTypes,
+        optional_params: dict,
+        litellm_params: dict,
+        encoding: Any,
+        api_key: Optional[str] = None,
+    ) -> ImageResponse:
+        pass
+
+    @abstractmethod
+    def transform_response_image_variation(
+        self,
+        model: Optional[str],
+        raw_response: httpx.Response,
+        model_response: ImageResponse,
+        logging_obj: LiteLLMLoggingObj,
+        request_data: dict,
+        image: FileTypes,
+        optional_params: dict,
+        litellm_params: dict,
+        encoding: Any,
+        api_key: Optional[str] = None,
+    ) -> ImageResponse:
+        pass
+
+    def transform_request(
+        self,
+        model: str,
+        messages: List[AllMessageValues],
+        optional_params: dict,
+        litellm_params: dict,
+        headers: dict,
+    ) -> dict:
+        raise NotImplementedError(
+            "ImageVariationConfig implementa 'transform_request_image_variation' for image variation models"
+        )
+
+    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,
+    ) -> ModelResponse:
+        raise NotImplementedError(
+            "ImageVariationConfig implements 'transform_response_image_variation' for image variation models"
+        )