fix(groq/chat/transformation.py): handle max_retries

litellm/llms/groq/chat/transformation.py

@@ -2,14 +2,10 @@
 Translate from OpenAI's `/v1/chat/completions` to Groq's `/v1/chat/completions`
 """
 
-from typing import Any, AsyncIterator, Iterator, List, Optional, Tuple, Union
+from typing import List, Optional, Tuple, Union
 
 from pydantic import BaseModel
 
-from litellm.llms.base_llm.chat.transformation import BaseLLMException
-from litellm.llms.openai.chat.gpt_transformation import (
-    OpenAIChatCompletionStreamingHandler,
-)
 from litellm.secret_managers.main import get_secret_str
 from litellm.types.llms.openai import (
     AllMessageValues,
@@ -17,15 +13,10 @@ from litellm.types.llms.openai import (
     ChatCompletionToolParam,
     ChatCompletionToolParamFunctionChunk,
 )
-from litellm.types.utils import ModelResponse, ModelResponseStream
 
 from ...openai.chat.gpt_transformation import OpenAIGPTConfig
 
 
-class GroqError(BaseLLMException):
-    pass
-
-
 class GroqChatConfig(OpenAIGPTConfig):
     frequency_penalty: Optional[int] = None
     function_call: Optional[Union[str, dict]] = None
@@ -66,6 +57,14 @@ class GroqChatConfig(OpenAIGPTConfig):
     def get_config(cls):
         return super().get_config()
 
+    def get_supported_openai_params(self, model: str) -> list:
+        base_params = super().get_supported_openai_params(model)
+        try:
+            base_params.remove("max_retries")
+        except ValueError:
+            pass
+        return base_params
+
     def _transform_messages(self, messages: List[AllMessageValues], model: str) -> List:
         for idx, message in enumerate(messages):
             """
@@ -164,39 +163,3 @@ class GroqChatConfig(OpenAIGPTConfig):
         return super().map_openai_params(
             non_default_params, optional_params, model, drop_params
         )
-
-    def get_model_response_iterator(
-        self,
-        streaming_response: Union[Iterator[str], AsyncIterator[str], ModelResponse],
-        sync_stream: bool,
-        json_mode: Optional[bool] = False,
-    ) -> Any:
-        return GroqChatCompletionStreamingHandler(
-            streaming_response=streaming_response,
-            sync_stream=sync_stream,
-            json_mode=json_mode,
-        )
-
-
-class GroqChatCompletionStreamingHandler(OpenAIChatCompletionStreamingHandler):
-    def chunk_parser(self, chunk: dict) -> ModelResponseStream:
-        try:
-            ## HANDLE ERROR IN CHUNK ##
-            if "error" in chunk:
-                error_chunk = chunk["error"]
-                raise GroqError(
-                    message="{}, Failed generation: {}".format(
-                        error_chunk["message"], error_chunk["failed_generation"]
-                    ),
-                    status_code=error_chunk["status_code"],
-                )
-
-            return super().chunk_parser(chunk)
-        except KeyError as e:
-            raise GroqError(
-                message=f"KeyError: {e}, Got unexpected response from Groq: {chunk}",
-                status_code=400,
-                headers={"Content-Type": "application/json"},
-            )
-        except Exception as e:
-            raise e