refactor: fix linting error

litellm/llms/bedrock/chat/converse_transformation.py

@@ -339,6 +339,55 @@ class AmazonConverseConfig(BaseConfig):
             }
         }
 
+    def _handle_reasoning_effort_parameter(
+        self, model: str, reasoning_effort: str, optional_params: dict
+    ) -> None:
+        """
+        Handle the reasoning_effort parameter based on the model type.
+
+        Different model families handle reasoning effort differently:
+        - GPT-OSS models: Keep reasoning_effort as-is (passed to additionalModelRequestFields)
+        - Nova Lite 2 models: Transform to reasoningConfig structure
+        - Other models (Anthropic, etc.): Convert to thinking parameter
+
+        Args:
+            model: The model identifier
+            reasoning_effort: The reasoning effort value
+            optional_params: Dictionary of optional parameters to update in-place
+
+        Examples:
+            >>> config = AmazonConverseConfig()
+            >>> params = {}
+            >>> config._handle_reasoning_effort_parameter("gpt-oss-model", "high", params)
+            >>> params
+            {'reasoning_effort': 'high'}
+
+            >>> params = {}
+            >>> config._handle_reasoning_effort_parameter("amazon.nova-2-lite-v1:0", "high", params)
+            >>> params
+            {'reasoningConfig': {'type': 'enabled', 'maxReasoningEffort': 'high'}}
+
+            >>> params = {}
+            >>> config._handle_reasoning_effort_parameter("anthropic.claude-3", "high", params)
+            >>> params
+            {'thinking': {'type': 'enabled', 'budget_tokens': 10000}}
+        """
+        if "gpt-oss" in model:
+            # GPT-OSS models: keep reasoning_effort as-is
+            # It will be passed through to additionalModelRequestFields
+            optional_params["reasoning_effort"] = reasoning_effort
+        elif self._is_nova_lite_2_model(model):
+            # Nova Lite 2 models: transform to reasoningConfig
+            reasoning_config = self._transform_reasoning_effort_to_reasoning_config(
+                reasoning_effort
+            )
+            optional_params.update(reasoning_config)
+        else:
+            # Anthropic and other models: convert to thinking parameter
+            optional_params["thinking"] = AnthropicConfig._map_reasoning_effort(
+                reasoning_effort
+            )
+
     def get_supported_openai_params(self, model: str) -> List[str]:
         from litellm.utils import supports_function_calling
 
@@ -658,21 +707,9 @@ class AmazonConverseConfig(BaseConfig):
             if param == "thinking":
                 optional_params["thinking"] = value
             elif param == "reasoning_effort" and isinstance(value, str):
-                if "gpt-oss" in model:
-                    # GPT-OSS models: keep reasoning_effort as-is
-                    # It will be passed through to additionalModelRequestFields
-                    optional_params["reasoning_effort"] = value
-                elif self._is_nova_lite_2_model(model):
-                    # Nova Lite 2 models: transform to reasoningConfig
-                    reasoning_config = (
-                        self._transform_reasoning_effort_to_reasoning_config(value)
-                    )
-                    optional_params.update(reasoning_config)
-                else:
-                    # Anthropic and other models: convert to thinking parameter
-                    optional_params["thinking"] = AnthropicConfig._map_reasoning_effort(
-                        value
-                    )
+                self._handle_reasoning_effort_parameter(
+                    model=model, reasoning_effort=value, optional_params=optional_params
+                )
             if param == "requestMetadata":
                 if value is not None and isinstance(value, dict):
                     self._validate_request_metadata(value)  # type: ignore
@@ -695,10 +732,7 @@ class AmazonConverseConfig(BaseConfig):
             )
 
         final_is_thinking_enabled = self.is_thinking_enabled(optional_params)
-        if (
-            final_is_thinking_enabled
-            and "tool_choice" in optional_params
-        ):
+        if final_is_thinking_enabled and "tool_choice" in optional_params:
             tool_choice_block = optional_params["tool_choice"]
             if isinstance(tool_choice_block, dict):
                 if "any" in tool_choice_block or "tool" in tool_choice_block:
@@ -922,20 +956,22 @@ class AmazonConverseConfig(BaseConfig):
         inference_params = {
             k: v for k, v in inference_params.items() if k in total_supported_params
         }
-        
+
         # Only set the topK value in for models that support it
         additional_request_params.update(
             self._handle_top_k_value(model, inference_params)
         )
-        
+
         # Filter out internal/MCP-related parameters that shouldn't be sent to the API
         # These are LiteLLM internal parameters, not API parameters
         additional_request_params = filter_internal_params(additional_request_params)
-        
+
         # Filter out non-serializable objects (exceptions, callables, logging objects, etc.)
         # from additional_request_params to prevent JSON serialization errors
         # This filters: Exception objects, callable objects (functions), Logging objects, etc.
-        additional_request_params = filter_exceptions_from_params(additional_request_params)
+        additional_request_params = filter_exceptions_from_params(
+            additional_request_params
+        )
 
         return inference_params, additional_request_params, request_metadata
 
@@ -960,7 +996,10 @@ class AmazonConverseConfig(BaseConfig):
         if original_tools:
             for tool in original_tools:
                 tool_type = tool.get("type", "")
-                if tool_type in ("tool_search_tool_regex_20251119", "tool_search_tool_bm25_20251119"):
+                if tool_type in (
+                    "tool_search_tool_regex_20251119",
+                    "tool_search_tool_bm25_20251119",
+                ):
                     # Tool search not supported in Converse API - skip it
                     continue
                 filtered_tools.append(tool)

litellm/model_prices_and_context_window_backup.json

@@ -12532,6 +12532,7 @@
         "deprecation_date": "2026-01-15",
         "cache_read_input_token_cost": 7.5e-08,
         "input_cost_per_audio_token": 1e-06,
+        "input_cost_per_image_token": 3e-07,
         "input_cost_per_token": 3e-07,
         "litellm_provider": "vertex_ai-language-models",
         "max_audio_length_hours": 8.4,