feat: GenAI - Allowed callable functions to return values directly in…

… Automatic Function Calling

PiperOrigin-RevId: 640574734

tests/unit/vertexai/test_generative_models.py

@@ -950,7 +950,7 @@ def test_generate_content_vertex_rag_retriever(self):
         attribute="generate_content",
         new=mock_generate_content,
     )
-    def test_chat_automatic_function_calling(self):
+    def test_chat_automatic_function_calling_with_function_returning_dict(self):
         generative_models = preview_generative_models
         get_current_weather_func = generative_models.FunctionDeclaration.from_func(
             get_current_weather
@@ -984,6 +984,51 @@ def test_chat_automatic_function_calling(self):
             chat2.send_message("What is the weather like in Boston?")
         assert err.match("Exceeded the maximum")
 
+    @mock.patch.object(
+        target=prediction_service.PredictionServiceClient,
+        attribute="generate_content",
+        new=mock_generate_content,
+    )
+    def test_chat_automatic_function_calling_with_function_returning_value(self):
+        # Define a new function that returns a value instead of a dict.
+        def get_current_weather(location: str):
+            """Gets weather in the specified location.
+
+            Args:
+                location: The location for which to get the weather.
+
+            Returns:
+                The weather information as a str.
+            """
+            if location == "Boston":
+                return "Super nice, but maybe a bit hot."
+            return "Unavailable"
+
+        generative_models = preview_generative_models
+        get_current_weather_func = generative_models.FunctionDeclaration.from_func(
+            get_current_weather
+        )
+        weather_tool = generative_models.Tool(
+            function_declarations=[get_current_weather_func],
+        )
+
+        model = generative_models.GenerativeModel(
+            "gemini-pro",
+            # Specifying the tools once to avoid specifying them in every request
+            tools=[weather_tool],
+        )
+        afc_responder = generative_models.AutomaticFunctionCallingResponder(
+            max_automatic_function_calls=5,
+        )
+        chat = model.start_chat(responder=afc_responder)
+
+        response1 = chat.send_message("What is the weather like in Boston?")
+        assert response1.text.startswith("The weather in Boston is")
+        assert "nice" in response1.text
+        assert len(chat.history) == 4
+        assert chat.history[-3].parts[0].function_call
+        assert chat.history[-2].parts[0].function_response
+
 
 EXPECTED_SCHEMA_FOR_GET_CURRENT_WEATHER = {
     "title": "get_current_weather",

vertexai/generative_models/_generative_models.py

@@ -15,6 +15,7 @@
 """Classes for working with generative models."""
 # pylint: disable=bad-continuation, line-too-long, protected-access
 
+from collections.abc import Mapping
 import copy
 import io
 import json
@@ -2422,6 +2423,10 @@ def respond_to_model_response(
                     # due to: AttributeError: type object 'MapComposite' has no attribute 'to_dict'
                     function_args = type(function_call).to_dict(function_call)["args"]
                     function_call_result = callable_function._function(**function_args)
+                    if not isinstance(function_call_result, Mapping):
+                        # If the function returns a single value, wrap it in the
+                        # format that Part.from_function_response can accept.
+                        function_call_result = {"result": function_call_result}
                 except Exception as ex:
                     raise RuntimeError(
                         f"""Error raised when calling function "{function_call.name}" as requested by the model."""