Bedrock pixtral fix

litellm/llms/bedrock/chat/invoke_transformations/amazon_mistral_transformation.py

@@ -1,10 +1,14 @@
 import types
-from typing import List, Optional
+from typing import List, Optional, TYPE_CHECKING
 
 from litellm.llms.base_llm.chat.transformation import BaseConfig
 from litellm.llms.bedrock.chat.invoke_transformations.base_invoke_transformation import (
     AmazonInvokeConfig,
 )
+from litellm.llms.bedrock.common_utils import BedrockError
+
+if TYPE_CHECKING:
+    from litellm.types.utils import ModelResponse
 
 
 class AmazonMistralConfig(AmazonInvokeConfig, BaseConfig):
@@ -81,3 +85,27 @@ def map_openai_params(
             if k == "stream":
                 optional_params["stream"] = v
         return optional_params
+
+    @staticmethod
+    def get_outputText(completion_response: dict, model_response: "ModelResponse") -> str:
+        """This function extracts the output text from a bedrock mistral completion.
+        As a side effect, it updates the finish reason for a model response.
+
+        Args:
+            completion_response: JSON from the completion.
+            model_response: ModelResponse
+
+        Returns:
+            A string with the response of the LLM
+
+        """
+        if "choices" in completion_response:
+            outputText = completion_response["choices"][0]["message"]["content"]
+            model_response.choices[0].finish_reason = completion_response["choices"][0]["finish_reason"]
+        elif "outputs" in completion_response:
+            outputText = completion_response["outputs"][0]["text"]
+            model_response.choices[0].finish_reason = completion_response["outputs"][0]["stop_reason"]
+        else:
+            raise BedrockError(message="Unexpected mistral completion response", status_code=400)
+
+        return outputText

litellm/llms/bedrock/chat/invoke_transformations/base_invoke_transformation.py

@@ -366,10 +366,7 @@ def transform_response(  # noqa: PLR0915
             elif provider == "meta" or provider == "llama" or provider == "deepseek_r1":
                 outputText = completion_response["generation"]
             elif provider == "mistral":
-                outputText = completion_response["outputs"][0]["text"]
-                model_response.choices[0].finish_reason = completion_response[
-                    "outputs"
-                ][0]["stop_reason"]
+                outputText = litellm.AmazonMistralConfig.get_outputText(completion_response, model_response)
             else:  # amazon titan
                 outputText = completion_response.get("results")[0].get("outputText")
         except Exception as e:

tests/litellm/llms/bedrock/chat/test_mistral_config.py

@@ -0,0 +1,30 @@
+
+
+from litellm.llms.bedrock.chat.invoke_transformations.amazon_mistral_transformation import AmazonMistralConfig
+from litellm.types.utils import ModelResponse
+
+
+def test_mistral_get_outputText():
+    # Set initial model response with arbitrary finish reason
+    model_response = ModelResponse()
+    model_response.choices[0].finish_reason = "None"
+
+    # Models like pixtral will return a completion with the openai format.
+    mock_json_with_choices = {"choices": [{"message": {"content": "Hello!"}, "finish_reason": "stop"}]}
+
+    outputText = AmazonMistralConfig.get_outputText(
+        completion_response=mock_json_with_choices, model_response=model_response
+    )
+
+    assert outputText == "Hello!"
+    assert model_response.choices[0].finish_reason == "stop"
+
+    # Other models might return a completion behind "outputs"
+    mock_json_with_output = {"outputs": [{"text": "Hi!", "stop_reason": "finish"}]}
+
+    outputText = AmazonMistralConfig.get_outputText(
+        completion_response=mock_json_with_output, model_response=model_response
+    )
+
+    assert outputText == "Hi!"
+    assert model_response.choices[0].finish_reason == "finish"