fix(anthropic.py): fix tool calling + streaming issue

litellm/llms/anthropic.py

@@ -165,6 +165,9 @@ class AnthropicChatCompletion(BaseLLM):
         print_verbose,
         encoding,
     ) -> CustomStreamWrapper:
+        """
+        Return stream object for tool-calling + streaming
+        """
         ## LOGGING
         logging_obj.post_call(
             input=messages,
@@ -202,6 +205,18 @@ class AnthropicChatCompletion(BaseLLM):
                 message=str(completion_response["error"]),
                 status_code=response.status_code,
             )
+        _message = litellm.Message(
+            tool_calls=tool_calls,
+            content=text_content or None,
+        )
+        model_response.choices[0].message = _message  # type: ignore
+        model_response._hidden_params["original_response"] = completion_response[
+            "content"
+        ]  # allow user to access raw anthropic tool calling response
+
+        model_response.choices[0].finish_reason = map_finish_reason(
+            completion_response["stop_reason"]
+        )
 
         print_verbose("INSIDE ANTHROPIC STREAMING TOOL CALLING CONDITION BLOCK")
         # return an iterator
@@ -392,13 +407,27 @@ class AnthropicChatCompletion(BaseLLM):
         litellm_params=None,
         logger_fn=None,
         headers={},
-    ) -> ModelResponse:
+    ) -> Union[ModelResponse, CustomStreamWrapper]:
         self.async_handler = AsyncHTTPHandler(
             timeout=httpx.Timeout(timeout=600.0, connect=5.0)
         )
         response = await self.async_handler.post(
             api_base, headers=headers, data=json.dumps(data)
         )
+        if stream and _is_function_call:
+            return self.process_streaming_response(
+                model=model,
+                response=response,
+                model_response=model_response,
+                stream=stream,
+                logging_obj=logging_obj,
+                api_key=api_key,
+                data=data,
+                messages=messages,
+                print_verbose=print_verbose,
+                optional_params=optional_params,
+                encoding=encoding,
+            )
         return self.process_response(
             model=model,
             response=response,