chore: initial snapshot for gitea/github upload

llm-gateway-competitors/litellm-wheel-src/litellm/llms/vertex_ai/google_genai/transformation.py

@@ -0,0 +1,100 @@
+"""
+Transformation for Calling Google models in their native format.
+"""
+
+from typing import Any, Dict, Literal, Optional, Union
+
+from litellm.llms.gemini.google_genai.transformation import GoogleGenAIConfig
+from litellm.types.router import GenericLiteLLMParams
+
+
+class VertexAIGoogleGenAIConfig(GoogleGenAIConfig):
+    """
+    Configuration for calling Google models in their native format.
+    """
+
+    HEADER_NAME = "Authorization"
+    BEARER_PREFIX = "Bearer"
+
+    @property
+    def custom_llm_provider(self) -> Literal["gemini", "vertex_ai"]:
+        return "vertex_ai"
+
+    def validate_environment(
+        self,
+        api_key: Optional[str],
+        headers: Optional[dict],
+        model: str,
+        litellm_params: Optional[Union[GenericLiteLLMParams, dict]],
+    ) -> dict:
+        default_headers = {
+            "Content-Type": "application/json",
+        }
+
+        if api_key is not None:
+            default_headers[self.HEADER_NAME] = f"{self.BEARER_PREFIX} {api_key}"
+        if headers is not None:
+            default_headers.update(headers)
+
+        return default_headers
+
+    def _camel_to_snake(self, camel_str: str) -> str:
+        """Convert camelCase to snake_case"""
+        import re
+
+        return re.sub(r"(?<!^)(?=[A-Z])", "_", camel_str).lower()
+
+    def map_generate_content_optional_params(
+        self,
+        generate_content_config_dict,
+        model: str,
+    ):
+        """
+        Map Google GenAI parameters to provider-specific format.
+
+        Args:
+            generate_content_optional_params: Optional parameters for generate content
+            model: The model name
+
+        Returns:
+            Mapped parameters for the provider
+        """
+
+        _generate_content_config_dict: Dict = {}
+
+        for param, value in generate_content_config_dict.items():
+            camel_case_key = self._camel_to_snake(param)
+            _generate_content_config_dict[camel_case_key] = value
+        return _generate_content_config_dict
+
+    def transform_generate_content_request(
+        self,
+        model: str,
+        contents: Any,
+        tools: Optional[Any],
+        generate_content_config_dict: Dict,
+        system_instruction: Optional[Any] = None,
+    ) -> dict:
+        """
+        Transform the generate content request for Vertex AI.
+        Since Vertex AI natively supports Google GenAI format, we can pass most fields directly.
+        """
+        # Build the request in Google GenAI format that Vertex AI expects
+        result = {
+            "model": model,
+            "contents": contents,
+        }
+
+        # Add tools if provided
+        if tools:
+            result["tools"] = tools
+
+        # Add systemInstruction if provided
+        if system_instruction:
+            result["systemInstruction"] = system_instruction
+
+        # Handle generationConfig - Vertex AI expects it in the same format
+        if generate_content_config_dict:
+            result["generationConfig"] = generate_content_config_dict
+
+        return result