chore: initial public snapshot for github upload

llm-gateway-competitors/litellm-wheel-src/litellm/llms/databricks/responses/transformation.py

@@ -0,0 +1,104 @@
+"""
+Databricks Responses API configuration.
+
+Inherits from OpenAIResponsesAPIConfig since Databricks' Responses API
+is compatible with OpenAI's for GPT models.
+
+Reference: https://docs.databricks.com/aws/en/machine-learning/foundation-model-apis/api-reference
+"""
+
+import os
+from typing import TYPE_CHECKING, Any, Dict, Optional, Union
+
+from litellm.llms.databricks.common_utils import DatabricksBase
+from litellm.llms.openai.responses.transformation import OpenAIResponsesAPIConfig
+from litellm.types.llms.openai import ResponseInputParam
+from litellm.types.router import GenericLiteLLMParams
+from litellm.types.utils import LlmProviders
+
+if TYPE_CHECKING:
+    from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+
+    LiteLLMLoggingObj = _LiteLLMLoggingObj
+else:
+    LiteLLMLoggingObj = Any
+
+
+class DatabricksResponsesAPIConfig(DatabricksBase, OpenAIResponsesAPIConfig):
+    """
+    Configuration for Databricks Responses API.
+
+    Inherits from OpenAIResponsesAPIConfig since Databricks' Responses API
+    is largely compatible with OpenAI's for GPT models.
+
+    Note: The Responses API on Databricks is only compatible with OpenAI GPT models.
+    """
+
+    @property
+    def custom_llm_provider(self) -> LlmProviders:
+        return LlmProviders.DATABRICKS
+
+    def validate_environment(
+        self,
+        headers: dict,
+        model: str,
+        litellm_params: Optional[GenericLiteLLMParams],
+    ) -> dict:
+        litellm_params = litellm_params or GenericLiteLLMParams()
+        api_key = litellm_params.api_key or os.getenv("DATABRICKS_API_KEY")
+        api_base = litellm_params.api_base or os.getenv("DATABRICKS_API_BASE")
+
+        # Reuse Databricks auth logic (OAuth M2M, PAT, SDK fallback).
+        # custom_endpoint=False allows SDK auth fallback; the appended
+        # /chat/completions suffix is harmless since we discard api_base
+        # here and build the URL separately in get_complete_url().
+        _, headers = self.databricks_validate_environment(
+            api_key=api_key,
+            api_base=api_base,
+            endpoint_type="chat_completions",
+            custom_endpoint=False,
+            headers=headers,
+        )
+
+        headers["Content-Type"] = "application/json"
+        return headers
+
+    def get_complete_url(
+        self,
+        api_base: Optional[str],
+        litellm_params: dict,
+    ) -> str:
+        api_base = api_base or os.getenv("DATABRICKS_API_BASE")
+        api_base = self._get_api_base(api_base)
+        api_base = api_base.rstrip("/")
+        return f"{api_base}/responses"
+
+    def transform_responses_api_request(
+        self,
+        model: str,
+        input: Union[str, ResponseInputParam],
+        response_api_optional_request_params: Dict,
+        litellm_params: GenericLiteLLMParams,
+        headers: dict,
+    ) -> Dict:
+        """
+        Transform request for Databricks Responses API.
+
+        Strips the 'databricks/' prefix from model name if present,
+        then delegates to OpenAI's transformation.
+        """
+        # Strip provider prefix if present (e.g., "databricks/databricks-gpt-5-nano" -> "databricks-gpt-5-nano")
+        if model.startswith("databricks/"):
+            model = model[len("databricks/") :]
+
+        return super().transform_responses_api_request(
+            model=model,
+            input=input,
+            response_api_optional_request_params=response_api_optional_request_params,
+            litellm_params=litellm_params,
+            headers=headers,
+        )
+
+    def supports_native_websocket(self) -> bool:
+        """Databricks does not support native WebSocket for Responses API"""
+        return False