fix mistral ai llm issue

semantic_router/encoders/mistral.py

@@ -25,7 +25,7 @@ class MistralEncoder(BaseEncoder):
         if name is None:
             name = EncoderDefault.MISTRAL.value["embedding_model"]
         super().__init__(name=name, score_threshold=score_threshold)
-           self._client, self._mistralai = self._initialize_client(mistralai_api_key)
+        self._client, self._mistralai = self._initialize_client(mistralai_api_key)
 
     def _initialize_client(self, api_key):
         try:
@@ -67,7 +67,9 @@ class MistralEncoder(BaseEncoder):
 
         if (
             not embeds
-            or not isinstance(embeds, self._mistralai.models.embeddings.EmbeddingResponse)
+            or not isinstance(
+                embeds, self._mistralai.models.embeddings.EmbeddingResponse
+            )
             or not embeds.data
         ):
             raise ValueError(f"No embeddings returned from MistralAI: {error_message}")

semantic_router/llms/mistral.py

@@ -14,6 +14,7 @@ class MistralAILLM(BaseLLM):
     _client: Any = PrivateAttr()
     temperature: Optional[float]
     max_tokens: Optional[int]
+    _mistralai: Any = PrivateAttr()
 
     def __init__(
         self,
@@ -25,12 +26,13 @@ class MistralAILLM(BaseLLM):
         if name is None:
             name = EncoderDefault.MISTRAL.value["language_model"]
         super().__init__(name=name)
-        self._client = self._initialize_client(mistralai_api_key)
+        self._client, self._mistralai = self._initialize_client(mistralai_api_key)
         self.temperature = temperature
         self.max_tokens = max_tokens
 
     def _initialize_client(self, api_key):
         try:
+            import mistralai
             from mistralai.client import MistralClient
         except ImportError:
             raise ImportError(
@@ -47,15 +49,22 @@ class MistralAILLM(BaseLLM):
             raise ValueError(
                 f"MistralAI API client failed to initialize. Error: {e}"
             ) from e
-        return client
+        return client, mistralai
 
     def __call__(self, messages: List[Message]) -> str:
         if self._client is None:
             raise ValueError("MistralAI client is not initialized.")
+
+        chat_messages = [
+            self._mistralai.models.chat_completion.ChatMessage(
+                role=m.role, content=m.content
+            )
+            for m in messages
+        ]
         try:
             completion = self._client.chat(
                 model=self.name,
-                messages=[m.to_mistral() for m in messages],
+                messages=chat_messages,
                 temperature=self.temperature,
                 max_tokens=self.max_tokens,
             )