refactor: (GenAI) Reorganized Function calling Samples (Group A) (GoogleCloudPlatform#12591)

* New files for Function Calling folder

* Marks old files to be deleted

* Renamed tests

* Fix comments

* Update comments

* Rewrite tests

* Changed comments -> JSON schema format

Author: Thoughtseize1

generative_ai/chat_completions/chat_completions_function_calling_basic.py

@@ -11,6 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+# TODO: Delete this file after approval generative_ai/function_calling/chat_function_calling_basic.py
 
 
 def generate_text(project_id: str, location: str = "us-central1") -> object:

generative_ai/chat_completions/chat_completions_function_calling_config.py

@@ -11,6 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+# TODO: Delete this file after approval generative_ai/function_calling/chat_function_calling_config.py
 
 
 def generate_text(project_id: str, location: str = "us-central1") -> object:

generative_ai/chat_completions/chat_completions_test.py

@@ -47,13 +47,15 @@ def test_non_streaming_image() -> None:
     assert response
 
 
+# TODO: Delete this test after approval /function_calling/chat_function_calling_test.py::test_function_calling_basic
 def test_function_calling_basic() -> None:
     response = chat_completions_function_calling_basic.generate_text(
         PROJECT_ID, LOCATION
     )
     assert response
 
 
+# TODO: Delete this test after approval /function_calling/chat_function_calling_test.py::test_function_calling_config
 def test_function_calling_config() -> None:
     response = chat_completions_function_calling_config.generate_text(
         PROJECT_ID, LOCATION

generative_ai/function_calling.py

@@ -11,6 +11,8 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+# TODO: Delete this file after approval function_calling/basic_example.py AND function_calling/advanced_example.py
+
 import os
 
 from vertexai.generative_models import GenerationResponse
@@ -178,3 +180,7 @@ def generate_function_call_advanced() -> GenerationResponse:
     print(response.candidates[0].function_calls)
     # [END generativeaionvertexai_gemini_function_calling_advanced]
     return response
+
+
+if __name__ == "__main__":
+    generate_function_call_advanced()

generative_ai/function_calling/advanced_example.py

@@ -0,0 +1,104 @@
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+from vertexai.generative_models import GenerationResponse
+
+PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
+
+
+def generate_function_call_advanced() -> GenerationResponse:
+    # [START generativeaionvertexai_gemini_function_calling_advanced]
+    import vertexai
+    from vertexai.preview.generative_models import (
+        FunctionDeclaration,
+        GenerativeModel,
+        Tool,
+        ToolConfig,
+    )
+
+    # TODO(developer): Update & uncomment below line
+    # PROJECT_ID = "your-project-id"
+
+    # Initialize Vertex AI
+    vertexai.init(project=PROJECT_ID, location="us-central1")
+
+    # Specify a function declaration and parameters for an API request
+    get_product_sku_func = FunctionDeclaration(
+        name="get_product_sku",
+        description="Get the available inventory for a Google products, e.g: Pixel phones, Pixel Watches, Google Home etc",
+        # Function parameters are specified in JSON schema format
+        parameters={
+            "type": "object",
+            "properties": {
+                "product_name": {"type": "string", "description": "Product name"}
+            },
+        },
+    )
+
+    # Specify another function declaration and parameters for an API request
+    get_store_location_func = FunctionDeclaration(
+        name="get_store_location",
+        description="Get the location of the closest store",
+        # Function parameters are specified in JSON schema format
+        parameters={
+            "type": "object",
+            "properties": {"location": {"type": "string", "description": "Location"}},
+        },
+    )
+
+    # Define a tool that includes the above functions
+    retail_tool = Tool(
+        function_declarations=[
+            get_product_sku_func,
+            get_store_location_func,
+        ],
+    )
+
+    # Define a tool config for the above functions
+    retail_tool_config = ToolConfig(
+        function_calling_config=ToolConfig.FunctionCallingConfig(
+            # ANY mode forces the model to predict a function call
+            mode=ToolConfig.FunctionCallingConfig.Mode.ANY,
+            # List of functions that can be returned when the mode is ANY.
+            # If the list is empty, any declared function can be returned.
+            allowed_function_names=["get_product_sku"],
+        )
+    )
+
+    model = GenerativeModel(
+        model_name="gemini-1.5-flash-001",
+        tools=[retail_tool],
+        tool_config=retail_tool_config,
+    )
+    response = model.generate_content(
+        "Do you have the Pixel 8 Pro 128GB in stock?",
+    )
+
+    print(response.candidates[0].function_calls)
+    # Example response:
+    # [
+    # name: "get_product_sku"
+    # args {
+    #   fields { key: "product_name" value { string_value: "Pixel 8 Pro 128GB" }}
+    #   }
+    # ]
+
+    # [END generativeaionvertexai_gemini_function_calling_advanced]
+    return response
+
+
+if __name__ == "__main__":
+    generate_function_call_advanced()

generative_ai/function_calling/basic_example.py

@@ -0,0 +1,119 @@
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+from vertexai.generative_models import GenerationResponse
+
+PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
+
+
+def generate_function_call() -> GenerationResponse:
+    # [START generativeaionvertexai_gemini_function_calling]
+    import vertexai
+    from vertexai.generative_models import (
+        Content,
+        FunctionDeclaration,
+        GenerationConfig,
+        GenerativeModel,
+        Part,
+        Tool,
+    )
+
+    # TODO(developer): Update & uncomment below line
+    # PROJECT_ID = "your-project-id"
+
+    # Initialize Vertex AI
+    vertexai.init(project=PROJECT_ID, location="us-central1")
+
+    # Initialize Gemini model
+    model = GenerativeModel("gemini-1.5-flash-001")
+
+    # Define the user's prompt in a Content object that we can reuse in model calls
+    user_prompt_content = Content(
+        role="user",
+        parts=[
+            Part.from_text("What is the weather like in Boston?"),
+        ],
+    )
+
+    # Specify a function declaration and parameters for an API request
+    function_name = "get_current_weather"
+    get_current_weather_func = FunctionDeclaration(
+        name=function_name,
+        description="Get the current weather in a given location",
+        # Function parameters are specified in JSON schema format
+        parameters={
+            "type": "object",
+            "properties": {"location": {"type": "string", "description": "Location"}},
+        },
+    )
+
+    # Define a tool that includes the above get_current_weather_func
+    weather_tool = Tool(
+        function_declarations=[get_current_weather_func],
+    )
+
+    # Send the prompt and instruct the model to generate content using the Tool that you just created
+    response = model.generate_content(
+        user_prompt_content,
+        generation_config=GenerationConfig(temperature=0),
+        tools=[weather_tool],
+    )
+    function_call = response.candidates[0].function_calls[0]
+    print(function_call)
+
+    # Check the function name that the model responded with, and make an API call to an external system
+    if function_call.name == function_name:
+        # Extract the arguments to use in your API call
+        location = function_call.args["location"]  # noqa: F841
+
+        # Here you can use your preferred method to make an API request to fetch the current weather, for example:
+        # api_response = requests.post(weather_api_url, data={"location": location})
+
+        # In this example, we'll use synthetic data to simulate a response payload from an external API
+        api_response = """{ "location": "Boston, MA", "temperature": 38, "description": "Partly Cloudy",
+                        "icon": "partly-cloudy", "humidity": 65, "wind": { "speed": 10, "direction": "NW" } }"""
+
+    # Return the API response to Gemini so it can generate a model response or request another function call
+    response = model.generate_content(
+        [
+            user_prompt_content,  # User prompt
+            response.candidates[0].content,  # Function call response
+            Content(
+                parts=[
+                    Part.from_function_response(
+                        name=function_name,
+                        response={
+                            "content": api_response,  # Return the API response to Gemini
+                        },
+                    ),
+                ],
+            ),
+        ],
+        tools=[weather_tool],
+    )
+
+    # Get the model response
+    print(response.text)
+    # Example response:
+    # The weather in Boston is partly cloudy with a temperature of 38 degrees Fahrenheit.
+    # The humidity is 65% and the wind is blowing from the northwest at 10 mph.
+
+    # [END generativeaionvertexai_gemini_function_calling]
+    return response
+
+
+if __name__ == "__main__":
+    generate_function_call()