Merge pull request #3079 from pipecat-ai/vp-add-exact-model-version-function

set full model name for base openai models

src/pipecat/services/openai/base_llm.py

@@ -133,6 +133,7 @@ class BaseOpenAILLMService(LLMService):
         self._retry_timeout_secs = retry_timeout_secs
         self._retry_on_timeout = retry_on_timeout
         self.set_model_name(model)
+        self._full_model_name: str = ""
         self._client = self.create_client(
             api_key=api_key,
             base_url=base_url,
@@ -185,6 +186,22 @@ class BaseOpenAILLMService(LLMService):
         """
         return True
 
+    def set_full_model_name(self, full_model_name: str):
+        """Set the full AI model name.
+
+        Args:
+            full_model_name: The full name of the AI model to use.
+        """
+        self._full_model_name = full_model_name
+
+    def get_full_model_name(self):
+        """Get the current full model name.
+
+        Returns:
+            The full name of the AI model being used.
+        """
+        return self._full_model_name
+
     async def get_chat_completions(
         self, params_from_context: OpenAILLMInvocationParams
     ) -> AsyncStream[ChatCompletionChunk]:
@@ -360,6 +377,9 @@ class BaseOpenAILLMService(LLMService):
                 )
                 await self.start_llm_usage_metrics(tokens)
 
+            if chunk.model and self.get_full_model_name() != chunk.model:
+                self.set_full_model_name(chunk.model)
+
             if chunk.choices is None or len(chunk.choices) == 0:
                 continue
 

src/pipecat/utils/tracing/service_decorators.py

@@ -483,7 +483,9 @@ def traced_llm(func: Optional[Callable] = None, *, name: Optional[str] = None) -
                             # Add all available attributes to the span
                             attribute_kwargs = {
                                 "service_name": service_class_name,
-                                "model": getattr(self, "model_name", "unknown"),
+                                "model": getattr(
+                                    self, getattr(self, "_full_model_name", "model_name"), "unknown"
+                                ),
                                 "stream": True,  # Most LLM services use streaming
                                 "parameters": params,
                             }