fix(factory.py): mistral message input fix

litellm/llms/openai.py

@@ -222,6 +222,7 @@ class OpenAIChatCompletion(BaseLLM):
         custom_prompt_dict: dict = {},
         client=None,
         organization: Optional[str] = None,
+        custom_llm_provider: Optional[str] = None,
     ):
         super().completion()
         exception_mapping_worked = False
@@ -236,6 +237,14 @@ class OpenAIChatCompletion(BaseLLM):
                     status_code=422, message=f"Timeout needs to be a float"
                 )
 
+            if custom_llm_provider == "mistral":
+                # check if message content passed in as list, and not string
+                messages = prompt_factory(
+                    model=model,
+                    messages=messages,
+                    custom_llm_provider=custom_llm_provider,
+                )
+
             for _ in range(
                 2
             ):  # if call fails due to alternating messages, retry with reformatted message
@@ -325,12 +334,13 @@ class OpenAIChatCompletion(BaseLLM):
                             model_response_object=model_response,
                         )
                 except Exception as e:
-                    if "Conversation roles must alternate user/assistant" in str(
-                        e
-                    ) or "user and assistant roles should be alternating" in str(e):
+                    if (
+                        "Conversation roles must alternate user/assistant" in str(e)
+                        or "user and assistant roles should be alternating" in str(e)
+                    ) and messages is not None:
                         # reformat messages to ensure user/assistant are alternating, if there's either 2 consecutive 'user' messages or 2 consecutive 'assistant' message, add a blank 'user' or 'assistant' message to ensure compatibility
                         new_messages = []
-                        for i in range(len(messages) - 1):
+                        for i in range(len(messages) - 1):  # type: ignore
                             new_messages.append(messages[i])
                             if messages[i]["role"] == messages[i + 1]["role"]:
                                 if messages[i]["role"] == "user":
@@ -341,7 +351,9 @@ class OpenAIChatCompletion(BaseLLM):
                                     new_messages.append({"role": "user", "content": ""})
                         new_messages.append(messages[-1])
                         messages = new_messages
-                    elif "Last message must have role `user`" in str(e):
+                    elif (
+                        "Last message must have role `user`" in str(e)
+                    ) and messages is not None:
                         new_messages = messages
                         new_messages.append({"role": "user", "content": ""})
                         messages = new_messages

litellm/llms/prompt_templates/factory.py

@@ -116,6 +116,28 @@ 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:
+        texts = ""
+        if 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"]
+        new_m = {"role": m["role"], "content": texts}
+        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 = ""
@@ -612,6 +634,8 @@ def prompt_factory(
             return _gemini_vision_convert_messages(messages=messages)
         else:
             return gemini_text_image_pt(messages=messages)
+    elif custom_llm_provider == "mistral":
+        return mistral_api_pt(messages=messages)
     try:
         if "meta-llama/llama-2" in model and "chat" in model:
             return llama_2_chat_pt(messages=messages)

litellm/main.py

@@ -846,6 +846,7 @@ def completion(
                     custom_prompt_dict=custom_prompt_dict,
                     client=client,  # pass AsyncOpenAI, OpenAI client
                     organization=organization,
+                    custom_llm_provider=custom_llm_provider,
                 )
             except Exception as e:
                 ## LOGGING - log the original exception returned

litellm/tests/test_completion.py

@@ -110,6 +110,29 @@ def test_completion_mistral_api():
 # test_completion_mistral_api()
 
 
+def test_completion_mistral_api_modified_input():
+    try:
+        litellm.set_verbose = True
+        response = completion(
+            model="mistral/mistral-tiny",
+            max_tokens=5,
+            messages=[
+                {
+                    "role": "user",
+                    "content": [{"type": "text", "text": "Hey, how's it going?"}],
+                }
+            ],
+        )
+        # Add any assertions here to check the response
+        print(response)
+
+        cost = litellm.completion_cost(completion_response=response)
+        print("cost to make mistral completion=", cost)
+        assert cost > 0.0
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
+
+
 def test_completion_claude2_1():
     try:
         print("claude2.1 test request")