chore: initial public snapshot for github upload

llm-gateway-competitors/litellm-wheel-src/litellm/llms/bedrock_mantle/chat/transformation.py

@@ -0,0 +1,80 @@
+"""
+Amazon Bedrock Mantle - OpenAI-compatible inference engine in Amazon Bedrock.
+
+API docs: https://docs.aws.amazon.com/bedrock/latest/userguide/bedrock-mantle.html
+
+Base URL: https://bedrock-mantle.{region}.api.aws/v1
+Auth: AWS Bedrock API key as Bearer token (set via BEDROCK_MANTLE_API_KEY env var)
+      or region-aware key via BEDROCK_MANTLE_{REGION}_API_KEY.
+"""
+
+from typing import Iterator, AsyncIterator, Any, Optional, Tuple, Union
+
+import litellm
+from litellm._logging import verbose_logger
+from litellm.secret_managers.main import get_secret_str
+
+from ...openai_like.chat.transformation import OpenAILikeChatConfig
+
+
+BEDROCK_MANTLE_DEFAULT_REGION = "us-east-1"
+
+
+class BedrockMantleChatConfig(OpenAILikeChatConfig):
+    """
+    Transformation config for Amazon Bedrock Mantle OpenAI-compatible API.
+    """
+
+    @property
+    def custom_llm_provider(self) -> Optional[str]:
+        return "bedrock_mantle"
+
+    @classmethod
+    def get_config(cls):
+        return super().get_config()
+
+    def _get_openai_compatible_provider_info(
+        self, api_base: Optional[str], api_key: Optional[str]
+    ) -> Tuple[Optional[str], Optional[str]]:
+        region = (
+            get_secret_str("BEDROCK_MANTLE_REGION")
+            or get_secret_str("AWS_REGION")
+            or BEDROCK_MANTLE_DEFAULT_REGION
+        )
+        api_base = (
+            api_base
+            or get_secret_str("BEDROCK_MANTLE_API_BASE")
+            or f"https://bedrock-mantle.{region}.api.aws/v1"
+        )
+        dynamic_api_key = api_key or get_secret_str("BEDROCK_MANTLE_API_KEY")
+        return api_base, dynamic_api_key
+
+    def get_supported_openai_params(self, model: str) -> list:
+        base_params = super().get_supported_openai_params(model)
+        try:
+            if litellm.supports_reasoning(
+                model=model, custom_llm_provider=self.custom_llm_provider
+            ):
+                if "reasoning_effort" not in base_params:
+                    base_params.append("reasoning_effort")
+        except Exception as e:
+            verbose_logger.debug(
+                f"BedrockMantleChatConfig: error checking reasoning support: {e}"
+            )
+        return base_params
+
+    def get_model_response_iterator(
+        self,
+        streaming_response: Union[Iterator[str], AsyncIterator[str], Any],
+        sync_stream: bool,
+        json_mode: Optional[bool] = False,
+    ) -> Any:
+        from litellm.llms.openai.chat.gpt_transformation import (
+            OpenAIChatCompletionStreamingHandler,
+        )
+
+        return OpenAIChatCompletionStreamingHandler(
+            streaming_response=streaming_response,
+            sync_stream=sync_stream,
+            json_mode=json_mode,
+        )