chore: initial public snapshot for github upload

llm-gateway-competitors/litellm-wheel-src/litellm/llms/hosted_vllm/embedding/README.md

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+No transformation is required for hosted_vllm embedding.
+
+VLLM is a superset of OpenAI's `embedding` endpoint.
+
+To pass provider-specific parameters, see [this](https://docs.litellm.ai/docs/completion/provider_specific_params)

llm-gateway-competitors/litellm-wheel-src/litellm/llms/hosted_vllm/embedding/transformation.py

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+"""
+Hosted VLLM Embedding API Configuration.
+
+This module provides the configuration for hosted VLLM's Embedding API.
+VLLM is OpenAI-compatible and supports embeddings via the /v1/embeddings endpoint.
+
+Docs: https://docs.vllm.ai/en/latest/serving/openai_compatible_server.html
+"""
+
+from typing import TYPE_CHECKING, Any, List, Optional, Union
+
+import httpx
+
+from litellm.llms.base_llm.chat.transformation import BaseLLMException
+from litellm.llms.base_llm.embedding.transformation import BaseEmbeddingConfig
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import AllEmbeddingInputValues, AllMessageValues
+from litellm.types.utils import EmbeddingResponse
+from litellm.utils import convert_to_model_response_object
+
+if TYPE_CHECKING:
+    from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+
+    LiteLLMLoggingObj = _LiteLLMLoggingObj
+else:
+    LiteLLMLoggingObj = Any
+
+
+class HostedVLLMEmbeddingError(BaseLLMException):
+    """Exception class for Hosted VLLM Embedding errors."""
+
+    pass
+
+
+class HostedVLLMEmbeddingConfig(BaseEmbeddingConfig):
+    """
+    Configuration for Hosted VLLM's Embedding API.
+
+    Reference: https://docs.vllm.ai/en/latest/serving/openai_compatible_server.html
+    """
+
+    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:
+        """
+        Validate environment and set up headers for Hosted VLLM API.
+        """
+        if api_key is None:
+            api_key = get_secret_str("HOSTED_VLLM_API_KEY") or "fake-api-key"
+
+        default_headers = {
+            "Content-Type": "application/json",
+        }
+
+        # Only add Authorization header if api_key is not "fake-api-key"
+        if api_key and api_key != "fake-api-key":
+            default_headers["Authorization"] = f"Bearer {api_key}"
+
+        # Merge with existing headers (user's headers take priority)
+        return {**default_headers, **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,
+    ) -> str:
+        """
+        Get the complete URL for Hosted VLLM Embedding API endpoint.
+        """
+        if api_base is None:
+            api_base = get_secret_str("HOSTED_VLLM_API_BASE")
+            if api_base is None:
+                raise ValueError("api_base is required for hosted_vllm embeddings")
+
+        # Remove trailing slashes
+        api_base = api_base.rstrip("/")
+
+        # Ensure the URL ends with /embeddings
+        if not api_base.endswith("/embeddings"):
+            api_base = f"{api_base}/embeddings"
+
+        return api_base
+
+    def transform_embedding_request(
+        self,
+        model: str,
+        input: AllEmbeddingInputValues,
+        optional_params: dict,
+        headers: dict,
+    ) -> dict:
+        """
+        Transform embedding request to Hosted VLLM format (OpenAI-compatible).
+        """
+        # Ensure input is a list
+        if isinstance(input, str):
+            input = [input]
+
+        # Strip 'hosted_vllm/' prefix if present
+        if model.startswith("hosted_vllm/"):
+            model = model.replace("hosted_vllm/", "", 1)
+
+        return {
+            "model": model,
+            "input": input,
+            **optional_params,
+        }
+
+    def transform_embedding_response(
+        self,
+        model: str,
+        raw_response: httpx.Response,
+        model_response: EmbeddingResponse,
+        logging_obj: LiteLLMLoggingObj,
+        api_key: Optional[str],
+        request_data: dict,
+        optional_params: dict,
+        litellm_params: dict,
+    ) -> EmbeddingResponse:
+        """
+        Transform embedding response from Hosted VLLM format (OpenAI-compatible).
+        """
+        logging_obj.post_call(original_response=raw_response.text)
+
+        # VLLM returns standard OpenAI-compatible embedding response
+        response_json = raw_response.json()
+
+        return convert_to_model_response_object(
+            response_object=response_json,
+            model_response_object=model_response,
+            response_type="embedding",
+        )
+
+    def get_supported_openai_params(self, model: str) -> list:
+        """
+        Get list of supported OpenAI parameters for Hosted VLLM embeddings.
+        """
+        return [
+            "timeout",
+            "dimensions",
+            "encoding_format",
+            "user",
+        ]
+
+    def map_openai_params(
+        self,
+        non_default_params: dict,
+        optional_params: dict,
+        model: str,
+        drop_params: bool,
+    ) -> dict:
+        """
+        Map OpenAI parameters to Hosted VLLM format.
+        """
+        for param, value in non_default_params.items():
+            if param in self.get_supported_openai_params(model):
+                optional_params[param] = value
+        return optional_params
+
+    def get_error_class(
+        self, error_message: str, status_code: int, headers: Union[dict, httpx.Headers]
+    ) -> BaseLLMException:
+        """
+        Get the error class for Hosted VLLM errors.
+        """
+        return HostedVLLMEmbeddingError(
+            message=error_message,
+            status_code=status_code,
+            headers=headers,
+        )