fix function calling examples

examples/foundational/15-switch-voices.py

@@ -14,10 +14,6 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.parallel_pipeline import ParallelPipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_response import (
-    LLMAssistantContextAggregator,
-    LLMUserContextAggregator
-)
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.processors.filters.function_filter import FunctionFilter
 from pipecat.services.cartesia import CartesiaTTSService
@@ -40,10 +36,10 @@ logger.add(sys.stderr, level="DEBUG")
 current_voice = "News Lady"
 
 
-async def switch_voice(llm, args):
+async def switch_voice(function_name, tool_call_id, args, llm, context, result_callback):
     global current_voice
     current_voice = args["voice"]
-    return {"voice": f"You are now using your {current_voice} voice. Your responses should now be as if you were a {current_voice}."}
+    await result_callback({"voice": f"You are now using your {current_voice} voice. Your responses should now be as if you were a {current_voice}."})
 
 
 async def news_lady_filter(frame) -> bool:
@@ -119,12 +115,11 @@ async def main():
         ]
 
         context = OpenAILLMContext(messages, tools)
-        tma_in = LLMUserContextAggregator(context)
-        tma_out = LLMAssistantContextAggregator(context)
+        context_aggregator = llm.create_context_aggregator(context)
 
         pipeline = Pipeline([
             transport.input(),   # Transport user input
-            tma_in,              # User responses
+            context_aggregator.user(),  # User responses
             llm,                 # LLM
             ParallelPipeline(    # TTS (one of the following vocies)
                 [FunctionFilter(news_lady_filter), news_lady],            # News Lady voice
@@ -132,7 +127,7 @@ async def main():
                 [FunctionFilter(barbershop_man_filter), barbershop_man],  # Barbershop Man voice
             ),
             transport.output(),  # Transport bot output
-            tma_out              # Assistant spoken responses
+            context_aggregator.assistant(),  # Assistant spoken responses
         ])
 
         task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))