(fix) OpenAI's optional messages[].name does not work with Mistral API (#6701)

* use helper for _transform_messages mistral

* add test_message_with_name to base LLMChat test

* fix linting

litellm/llms/mistral/mistral_chat_transformation.py

@@ -10,6 +10,7 @@ import types
 from typing import List, Literal, Optional, Tuple, Union
 
 from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import AllMessageValues
 
 
 class MistralConfig:
@@ -148,3 +149,59 @@ class MistralConfig:
             or get_secret_str("MISTRAL_API_KEY")
         )
         return api_base, dynamic_api_key
+
+    @classmethod
+    def _transform_messages(cls, messages: List[AllMessageValues]):
+        """
+        - handles scenario where content is list and not string
+        - content list is just text, and no images
+        - if image passed in, then just return as is (user-intended)
+        - if `name` is passed, then drop it for mistral API: https://github.com/BerriAI/litellm/issues/6696
+
+        Motivation: mistral api doesn't support content as a list
+        """
+        new_messages = []
+        for m in messages:
+            special_keys = ["role", "content", "tool_calls", "function_call"]
+            extra_args = {}
+            if isinstance(m, dict):
+                for k, v in m.items():
+                    if k not in special_keys:
+                        extra_args[k] = v
+            texts = ""
+            _content = m.get("content")
+            if _content is not None and isinstance(_content, list):
+                for c in _content:
+                    _text: Optional[str] = c.get("text")
+                    if c["type"] == "image_url":
+                        return messages
+                    elif c["type"] == "text" and isinstance(_text, str):
+                        texts += _text
+            elif _content is not None and isinstance(_content, str):
+                texts = _content
+
+            new_m = {"role": m["role"], "content": texts, **extra_args}
+
+            if m.get("tool_calls"):
+                new_m["tool_calls"] = m.get("tool_calls")
+
+            new_m = cls._handle_name_in_message(new_m)
+
+            new_messages.append(new_m)
+        return new_messages
+
+    @classmethod
+    def _handle_name_in_message(cls, message: dict) -> dict:
+        """
+        Mistral API only supports `name` in tool messages
+
+        If role == tool, then we keep `name`
+        Otherwise, we drop `name`
+        """
+        if message.get("name") is not None:
+            if message["role"] == "tool":
+                message["name"] = message.get("name")
+            else:
+                message.pop("name", None)
+
+        return message

litellm/llms/prompt_templates/factory.py

@@ -259,43 +259,6 @@ def mistral_instruct_pt(messages):
     return prompt
 
 
-def mistral_api_pt(messages):
-    """
-    - handles scenario where content is list and not string
-    - content list is just text, and no images
-    - if image passed in, then just return as is (user-intended)
-
-    Motivation: mistral api doesn't support content as a list
-    """
-    new_messages = []
-    for m in messages:
-        special_keys = ["role", "content", "tool_calls", "function_call"]
-        extra_args = {}
-        if isinstance(m, dict):
-            for k, v in m.items():
-                if k not in special_keys:
-                    extra_args[k] = v
-        texts = ""
-        if m.get("content", None) is not None and isinstance(m["content"], list):
-            for c in m["content"]:
-                if c["type"] == "image_url":
-                    return messages
-                elif c["type"] == "text" and isinstance(c["text"], str):
-                    texts += c["text"]
-        elif m.get("content", None) is not None and isinstance(m["content"], str):
-            texts = m["content"]
-
-        new_m = {"role": m["role"], "content": texts, **extra_args}
-
-        if new_m["role"] == "tool" and m.get("name"):
-            new_m["name"] = m["name"]
-        if m.get("tool_calls"):
-            new_m["tool_calls"] = m["tool_calls"]
-
-        new_messages.append(new_m)
-    return new_messages
-
-
 # Falcon prompt template - from https://github.com/lm-sys/FastChat/blob/main/fastchat/conversation.py#L110
 def falcon_instruct_pt(messages):
     prompt = ""
@@ -2853,7 +2816,7 @@ def prompt_factory(
         else:
             return gemini_text_image_pt(messages=messages)
     elif custom_llm_provider == "mistral":
-        return mistral_api_pt(messages=messages)
+        return litellm.MistralConfig._transform_messages(messages=messages)
     elif custom_llm_provider == "bedrock":
         if "amazon.titan-text" in model:
             return amazon_titan_pt(messages=messages)

tests/llm_translation/base_llm_unit_tests.py

@@ -45,6 +45,14 @@ class BaseLLMChatTest(ABC):
         )
         assert response is not None
 
+    def test_message_with_name(self):
+        base_completion_call_args = self.get_base_completion_call_args()
+        messages = [
+            {"role": "user", "content": "Hello", "name": "test_name"},
+        ]
+        response = litellm.completion(**base_completion_call_args, messages=messages)
+        assert response is not None
+
     @pytest.fixture
     def pdf_messages(self):
         import base64

tests/llm_translation/test_mistral_api.py

@@ -0,0 +1,34 @@
+import asyncio
+import os
+import sys
+import traceback
+
+from dotenv import load_dotenv
+
+import litellm.types
+import litellm.types.utils
+from litellm.llms.anthropic.chat import ModelResponseIterator
+
+load_dotenv()
+import io
+import os
+
+sys.path.insert(
+    0, os.path.abspath("../..")
+)  # Adds the parent directory to the system path
+from typing import Optional
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+import litellm
+
+from litellm.llms.anthropic.common_utils import process_anthropic_headers
+from httpx import Headers
+from base_llm_unit_tests import BaseLLMChatTest
+
+
+class TestMistralCompletion(BaseLLMChatTest):
+    def get_base_completion_call_args(self) -> dict:
+        litellm.set_verbose = True
+        return {"model": "mistral/mistral-small-latest"}