Enable async tool cancellation feature.

examples/function-calling/function-calling-anthropic-async-stream.py

@@ -118,6 +118,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     llm = AnthropicLLMService(
         api_key=os.getenv("ANTHROPIC_API_KEY"),
+        enable_async_tool_cancellation=True,
         settings=AnthropicLLMService.Settings(
             system_instruction=(
                 "You are a helpful assistant in a voice conversation. "
@@ -139,9 +140,10 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         timeout_secs=30,
     )
 
-    @llm.event_handler("on_function_calls_started")
-    async def on_function_calls_started(service, function_calls):
-        await tts.queue_frame(TTSSpeakFrame("Sure, tracking your location now."))
+    @llm.event_handler("on_function_calls_cancelled")
+    async def on_function_calls_cancelled(service, function_calls):
+        for item in function_calls:
+            logger.info(f"Function call cancelled: {item.function_name} [{item.tool_call_id}]")
 
     location_function = FunctionSchema(
         name="track_current_location",

examples/function-calling/function-calling-anthropic-async.py

@@ -77,6 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     llm = AnthropicLLMService(
         api_key=os.getenv("ANTHROPIC_API_KEY"),
+        enable_async_tool_cancellation=True,
         settings=AnthropicLLMService.Settings(
             system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
         ),
@@ -92,6 +93,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     )
     llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
 
+    @llm.event_handler("on_function_calls_cancelled")
+    async def on_function_calls_cancelled(service, function_calls):
+        for item in function_calls:
+            logger.info(f"Function call cancelled: {item.function_name} [{item.tool_call_id}]")
+
     weather_function = FunctionSchema(
         name="get_current_weather",
         description="Get the current weather",

examples/function-calling/function-calling-google-async-stream.py

@@ -118,6 +118,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     llm = GoogleLLMService(
         api_key=os.getenv("GOOGLE_API_KEY"),
+        enable_async_tool_cancellation=True,
         settings=GoogleLLMService.Settings(
             system_instruction=(
                 "You are a helpful assistant in a voice conversation. "
@@ -143,6 +144,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_function_calls_started(service, function_calls):
         await tts.queue_frame(TTSSpeakFrame("Sure, tracking your location now."))
 
+    @llm.event_handler("on_function_calls_cancelled")
+    async def on_function_calls_cancelled(service, function_calls):
+        for item in function_calls:
+            logger.info(f"Function call cancelled: {item.function_name} [{item.tool_call_id}]")
+
     location_function = FunctionSchema(
         name="track_current_location",
         description="Start tracking the user's current GPS location, reporting position updates until the user reaches their destination.",

examples/function-calling/function-calling-google-async.py

@@ -128,6 +128,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     llm = GoogleLLMService(
         api_key=os.getenv("GOOGLE_API_KEY"),
+        enable_async_tool_cancellation=True,
         settings=GoogleLLMService.Settings(
             system_instruction=system_prompt,
         ),
@@ -140,6 +141,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_function_calls_started(service, function_calls):
         await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
 
+    @llm.event_handler("on_function_calls_cancelled")
+    async def on_function_calls_cancelled(service, function_calls):
+        for item in function_calls:
+            logger.info(f"Function call cancelled: {item.function_name} [{item.tool_call_id}]")
+
     weather_function = FunctionSchema(
         name="get_weather",
         description="Get the current weather",

examples/function-calling/function-calling-openai-async-stream.py

@@ -118,6 +118,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     llm = OpenAILLMService(
         api_key=os.getenv("OPENAI_API_KEY"),
+        enable_async_tool_cancellation=True,
         settings=OpenAILLMService.Settings(
             system_instruction=(
                 "You are a helpful assistant in a voice conversation. "
@@ -143,6 +144,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_function_calls_started(service, function_calls):
         await tts.queue_frame(TTSSpeakFrame("Sure, tracking your location now."))
 
+    @llm.event_handler("on_function_calls_cancelled")
+    async def on_function_calls_cancelled(service, function_calls):
+        for item in function_calls:
+            logger.info(f"Function call cancelled: {item.function_name} [{item.tool_call_id}]")
+
     location_function = FunctionSchema(
         name="track_current_location",
         description="Start tracking the user's current GPS location, reporting position updates until the user reaches their destination.",
@@ -181,6 +187,9 @@ async def on_function_calls_started(service, function_calls):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
         await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")

examples/function-calling/function-calling-openai-async.py

@@ -87,6 +87,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     llm = OpenAILLMService(
         api_key=os.getenv("OPENAI_API_KEY"),
+        enable_async_tool_cancellation=True,
         settings=OpenAILLMService.Settings(
             system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
         ),
@@ -106,6 +107,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_function_calls_started(service, function_calls):
         await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
 
+    @llm.event_handler("on_function_calls_cancelled")
+    async def on_function_calls_cancelled(service, function_calls):
+        for item in function_calls:
+            logger.info(f"Function call cancelled: {item.function_name} [{item.tool_call_id}]")
+
     weather_function = FunctionSchema(
         name="get_current_weather",
         description="Get the current weather",
@@ -165,6 +171,9 @@ async def on_function_calls_started(service, function_calls):
     async def on_client_connected(transport, client):
         logger.info(f"Client connected")
         # Kick off the conversation.
+        context.add_message(
+            {"role": "developer", "content": "Please introduce yourself to the user."}
+        )
         await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")

examples/function-calling/function-calling-openai-responses-async-stream.py

@@ -118,6 +118,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     llm = OpenAIResponsesLLMService(
         api_key=os.getenv("OPENAI_API_KEY"),
+        enable_async_tool_cancellation=True,
         settings=OpenAIResponsesLLMService.Settings(
             system_instruction=(
                 "You are a helpful assistant in a voice conversation. "
@@ -143,6 +144,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
     async def on_function_calls_started(service, function_calls):
         await tts.queue_frame(TTSSpeakFrame("Sure, tracking your location now."))
 
+    @llm.event_handler("on_function_calls_cancelled")
+    async def on_function_calls_cancelled(service, function_calls):
+        for item in function_calls:
+            logger.info(f"Function call cancelled: {item.function_name} [{item.tool_call_id}]")
+
     location_function = FunctionSchema(
         name="track_current_location",
         description="Track the device's current GPS location during a road trip, reporting position updates as the vehicle moves through cities until it reaches the final destination.",

examples/function-calling/function-calling-openai-responses-async.py

@@ -77,6 +77,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
     llm = OpenAIResponsesLLMService(
         api_key=os.getenv("OPENAI_API_KEY"),
+        enable_async_tool_cancellation=True,
         settings=OpenAIResponsesLLMService.Settings(
             system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
         ),
@@ -104,6 +105,11 @@ async def on_function_calls_started(service, function_calls):
         # matching, forcing a full context resend.
         await tts.queue_frame(TTSSpeakFrame("Let me check on that.", append_to_context=False))
 
+    @llm.event_handler("on_function_calls_cancelled")
+    async def on_function_calls_cancelled(service, function_calls):
+        for item in function_calls:
+            logger.info(f"Function call cancelled: {item.function_name} [{item.tool_call_id}]")
+
     weather_function = FunctionSchema(
         name="get_current_weather",
         description="Get the current weather",

src/pipecat/adapters/base_llm_adapter.py

@@ -10,11 +10,13 @@
 adapters that handle tool format conversion and standardization.
 """
 
+import warnings
 from abc import ABC, abstractmethod
 from typing import Any, Dict, Generic, List, Optional, TypeVar
 
 from loguru import logger
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
 from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.processors.aggregators.llm_context import (
     LLMContext,
@@ -48,6 +50,21 @@ class BaseLLMAdapter(ABC, Generic[TLLMInvocationParams]):
     def __init__(self):
         """Initialize the adapter."""
         self._warned_system_instruction = False
+        self._builtin_tools: Dict[str, FunctionSchema] = {}
+
+    @property
+    def builtin_tools(self) -> Dict[str, FunctionSchema]:
+        """Built-in tools automatically merged into every inference request.
+
+        Keyed by tool name for O(1) lookup, insertion, and removal.  The
+        service injects tools here so they are sent transparently on every
+        inference request without the user having to add them to their
+        ``ToolsSchema``.
+
+        Returns:
+            Mutable dict mapping tool name to ``FunctionSchema``.
+        """
+        return self._builtin_tools
 
     @property
     @abstractmethod
@@ -122,15 +139,41 @@ def get_messages(self, context: LLMContext) -> List[LLMContextMessage]:
     def from_standard_tools(self, tools: Any) -> List[Any] | NotGiven:
         """Convert tools from standard format to provider format.
 
+        Built-in tools are automatically merged into the schema before conversion so that every
+        inference request receives them without the user having to declare them explicitly.
+
         Args:
             tools: Tools in standard format or provider-specific format.
 
         Returns:
             List of tools converted to provider format, or original tools
             if not in standard format.
         """
+        if self._builtin_tools:
+            if isinstance(tools, ToolsSchema):
+                tools = ToolsSchema(
+                    standard_tools=tools.standard_tools + list(self._builtin_tools.values()),
+                    custom_tools=tools.custom_tools,
+                )
+            else:
+                # User supplied tools in a legacy/provider-specific format.
+                # Built-in tools cannot be safely merged, so they will not be injected.
+                # Migrate to ToolsSchema to enable built-in tool support; use custom_tools
+                # as an escape hatch for any provider-specific tools that don't fit the
+                # standard schema.
+                if tools is not None:
+                    warnings.warn(
+                        "Built-in tools (e.g. async tool cancellation) could not be injected "
+                        "because the supplied tools are not a ToolsSchema instance. "
+                        "Migrate to ToolsSchema to enable built-in tool support. "
+                        "Use ToolsSchema(custom_tools=...) as an escape hatch for any "
+                        "provider-specific tools that don't fit the standard schema.",
+                        DeprecationWarning,
+                        stacklevel=2,
+                    )
+                # Fall through and return the original tools unchanged.
+
         if isinstance(tools, ToolsSchema):
-            logger.debug(f"Retrieving the tools using the adapter: {type(self)}")
             return self.to_provider_tools_format(tools)
         # Fallback to return the same tools in case they are not in a standard format
         return tools