Support for passing in a ToolsSchema in lieu of a list of provider-specific dicts when updating OpenAIRealtimeLLMService using LLMUpdateSettingsFrame.

examples/foundational/19-openai-realtime.py

@@ -14,8 +14,14 @@ from loguru import logger
 
 from pipecat.adapters.schemas.function_schema import FunctionSchema
 from pipecat.adapters.schemas.tools_schema import ToolsSchema
+from pipecat.adapters.services.open_ai_realtime_adapter import OpenAIRealtimeLLMAdapter
 from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import LLMRunFrame, LLMSetToolsFrame, TranscriptionMessage
+from pipecat.frames.frames import (
+    LLMRunFrame,
+    LLMSetToolsFrame,
+    LLMUpdateSettingsFrame,
+    TranscriptionMessage,
+)
 from pipecat.observers.loggers.transcription_log_observer import TranscriptionLogObserver
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
@@ -148,6 +154,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
                 noise_reduction=InputAudioNoiseReduction(type="near_field"),
             )
         ),
+        # In this example we provide tools through the context, but you could
+        # alternatively provide them here.
         # tools=tools,
         instructions="""You are a helpful and friendly AI.
 
@@ -223,6 +231,10 @@ Remember, your responses should be short. Just one or two sentences, usually. Re
             standard_tools=[weather_function, restaurant_function, get_news_function]
         )
         await task.queue_frames([LLMSetToolsFrame(tools=new_tools)])
+        # Alternative pattern, useful if you're changing other session properties too
+        # await task.queue_frames(
+        #     [LLMUpdateSettingsFrame(settings=SessionProperties(tools=new_tools).model_dump())]
+        # )
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):