Add additional function call for testing to 14e, 14r, 19, 19a, 26b

examples/foundational/14e-function-calling-gemini.py

@@ -39,6 +39,10 @@ async def get_weather(params: FunctionCallParams):
     await params.result_callback(f"The weather in {location} is currently 72 degrees and sunny.")
 
 
+async def fetch_restaurant_recommendation(params: FunctionCallParams):
+    await params.result_callback({"name": "The Golden Dragon"})
+
+
 async def get_image(params: FunctionCallParams):
     question = params.arguments["question"]
     logger.debug(f"Requesting image with user_id={client_id}, question={question}")
@@ -92,6 +96,7 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash-001")
     llm.register_function("get_weather", get_weather)
     llm.register_function("get_image", get_image)
+    llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
 
     @llm.event_handler("on_function_calls_started")
     async def on_function_calls_started(service, function_calls):
@@ -113,6 +118,17 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         },
         required=["location", "format"],
     )
+    restaurant_function = FunctionSchema(
+        name="get_restaurant_recommendation",
+        description="Get a restaurant recommendation",
+        properties={
+            "location": {
+                "type": "string",
+                "description": "The city and state, e.g. San Francisco, CA",
+            },
+        },
+        required=["location"],
+    )
     get_image_function = FunctionSchema(
         name="get_image",
         description="Get an image from the video stream.",
@@ -124,14 +140,14 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         },
         required=["question"],
     )
-    tools = ToolsSchema(standard_tools=[weather_function, get_image_function])
+    tools = ToolsSchema(standard_tools=[weather_function, get_image_function, restaurant_function])
 
     system_prompt = """\
 You are a helpful assistant who converses with a user and answers questions. Respond concisely to general questions.
 
 Your response will be turned into speech so use only simple words and punctuation.
 
-You have access to two tools: get_weather and get_image.
+You have access to three tools: get_weather, get_restaurant_recommendation, and get_image.
 
 You can respond to questions about the weather using the get_weather tool.
 

examples/foundational/14r-function-calling-aws.py

@@ -32,6 +32,10 @@ async def fetch_weather_from_api(params: FunctionCallParams):
     await params.result_callback({"conditions": "nice", "temperature": "75"})
 
 
+async def fetch_restaurant_recommendation(params: FunctionCallParams):
+    await params.result_callback({"name": "The Golden Dragon"})
+
+
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
 # instantiated. The function will be called when the desired transport gets
 # selected.
@@ -74,6 +78,7 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     # You can also register a function_name of None to get all functions
     # sent to the same callback with an additional function_name parameter.
     llm.register_function("get_current_weather", fetch_weather_from_api)
+    llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
 
     weather_function = FunctionSchema(
         name="get_current_weather",
@@ -91,7 +96,18 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         },
         required=["location", "format"],
     )
-    tools = ToolsSchema(standard_tools=[weather_function])
+    restaurant_function = FunctionSchema(
+        name="get_restaurant_recommendation",
+        description="Get a restaurant recommendation",
+        properties={
+            "location": {
+                "type": "string",
+                "description": "The city and state, e.g. San Francisco, CA",
+            },
+        },
+        required=["location"],
+    )
+    tools = ToolsSchema(standard_tools=[weather_function, restaurant_function])
 
     messages = [
         {

examples/foundational/19-openai-realtime-beta.py

@@ -45,6 +45,10 @@ async def fetch_weather_from_api(params: FunctionCallParams):
     )
 
 
+async def fetch_restaurant_recommendation(params: FunctionCallParams):
+    await params.result_callback({"name": "The Golden Dragon"})
+
+
 weather_function = FunctionSchema(
     name="get_current_weather",
     description="Get the current weather",
@@ -62,8 +66,20 @@ weather_function = FunctionSchema(
     required=["location", "format"],
 )
 
+restaurant_function = FunctionSchema(
+    name="get_restaurant_recommendation",
+    description="Get a restaurant recommendation",
+    properties={
+        "location": {
+            "type": "string",
+            "description": "The city and state, e.g. San Francisco, CA",
+        },
+    },
+    required=["location"],
+)
+
 # Create tools schema
-tools = ToolsSchema(standard_tools=[weather_function])
+tools = ToolsSchema(standard_tools=[weather_function, restaurant_function])
 
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
@@ -100,7 +116,7 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         # turn_detection=False,
         input_audio_noise_reduction=InputAudioNoiseReduction(type="near_field"),
         # tools=tools,
-        instructions="""Your knowledge cutoff is 2023-10. You are a helpful and friendly AI.
+        instructions="""You are a helpful and friendly AI.
 
 Act like a human, but remember that you aren't a human and that you can't do human
 things in the real world. Your voice and personality should be warm and engaging, with a lively and
@@ -113,6 +129,10 @@ even if you're asked about them.
 You are participating in a voice conversation. Keep your responses concise, short, and to the point
 unless specifically asked to elaborate on a topic.
 
+You have access to the following tools:
+- get_current_weather: Get the current weather for a given location.
+- get_restaurant_recommendation: Get a restaurant recommendation for a given location.
+
 Remember, your responses should be short. Just one or two sentences, usually.""",
     )
 
@@ -125,6 +145,7 @@ Remember, your responses should be short. Just one or two sentences, usually."""
     # you can either register a single function for all function calls, or specific functions
     # llm.register_function(None, fetch_weather_from_api)
     llm.register_function("get_current_weather", fetch_weather_from_api)
+    llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
 
     # Create a standard OpenAI LLM context object using the normal messages format. The
     # OpenAIRealtimeBetaLLMService will convert this internally to messages that the

examples/foundational/19a-azure-realtime-beta.py

@@ -43,6 +43,10 @@ async def fetch_weather_from_api(params: FunctionCallParams):
     )
 
 
+async def fetch_restaurant_recommendation(params: FunctionCallParams):
+    await params.result_callback({"name": "The Golden Dragon"})
+
+
 # Define weather function using standardized schema
 weather_function = FunctionSchema(
     name="get_current_weather",
@@ -61,8 +65,20 @@ weather_function = FunctionSchema(
     required=["location", "format"],
 )
 
+restaurant_function = FunctionSchema(
+    name="get_restaurant_recommendation",
+    description="Get a restaurant recommendation",
+    properties={
+        "location": {
+            "type": "string",
+            "description": "The city and state, e.g. San Francisco, CA",
+        },
+    },
+    required=["location"],
+)
+
 # Create tools schema
-tools = ToolsSchema(standard_tools=[weather_function])
+tools = ToolsSchema(standard_tools=[weather_function, restaurant_function])
 
 
 # We store functions so objects (e.g. SileroVADAnalyzer) don't get
@@ -98,7 +114,7 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         # Or set to False to disable openai turn detection and use transport VAD
         # turn_detection=False,
         # tools=tools,
-        instructions="""Your knowledge cutoff is 2023-10. You are a helpful and friendly AI.
+        instructions="""You are a helpful and friendly AI.
 
 Act like a human, but remember that you aren't a human and that you can't do human
 things in the real world. Your voice and personality should be warm and engaging, with a lively and
@@ -111,6 +127,10 @@ even if you're asked about them.
 You are participating in a voice conversation. Keep your responses concise, short, and to the point
 unless specifically asked to elaborate on a topic.
 
+You have access to the following tools:
+- get_current_weather: Get the current weather for a given location.
+- get_restaurant_recommendation: Get a restaurant recommendation for a given location.
+
 Remember, your responses should be short. Just one or two sentences, usually.""",
     )
 
@@ -124,6 +144,7 @@ Remember, your responses should be short. Just one or two sentences, usually."""
     # you can either register a single function for all function calls, or specific functions
     # llm.register_function(None, fetch_weather_from_api)
     llm.register_function("get_current_weather", fetch_weather_from_api)
+    llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
 
     # Create a standard OpenAI LLM context object using the normal messages format. The
     # OpenAIRealtimeBetaLLMService will convert this internally to messages that the

examples/foundational/26b-gemini-multimodal-live-function-calling.py

@@ -40,11 +40,17 @@ async def fetch_weather_from_api(params: FunctionCallParams):
     )
 
 
+async def fetch_restaurant_recommendation(params: FunctionCallParams):
+    await params.result_callback({"name": "The Golden Dragon"})
+
+
 system_instruction = """
 You are a helpful assistant who can answer questions and use tools.
 
-You have a tool called "get_current_weather" that can be used to get the current weather. If the user asks
-for the weather, call this function.
+You have three tools available to you:
+1. get_current_weather: Use this tool to get the current weather in a specific location.
+2. get_restaurant_recommendation: Use this tool to get a restaurant recommendation in a specific location.
+3. google_search: Use this tool to search the web for information.
 """
 
 
@@ -101,9 +107,21 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
         },
         required=["location", "format"],
     )
+    restaurant_function = FunctionSchema(
+        name="get_restaurant_recommendation",
+        description="Get a restaurant recommendation",
+        properties={
+            "location": {
+                "type": "string",
+                "description": "The city and state, e.g. San Francisco, CA",
+            },
+        },
+        required=["location"],
+    )
     search_tool = {"google_search": {}}
     tools = ToolsSchema(
-        standard_tools=[weather_function], custom_tools={AdapterType.GEMINI: [search_tool]}
+        standard_tools=[weather_function, restaurant_function],
+        custom_tools={AdapterType.GEMINI: [search_tool]},
     )
 
     llm = GeminiMultimodalLiveLLMService(
@@ -113,6 +131,7 @@ async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_si
     )
 
     llm.register_function("get_current_weather", fetch_weather_from_api)
+    llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
 
     context = OpenAILLMContext(
         [{"role": "user", "content": "Say hello."}],