fixes based on markbackman review

examples/foundational/07ae-interruptible-hume.py

@@ -7,22 +7,21 @@
 import os
 
 from dotenv import load_dotenv
-from loguru import logger
 
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.frames.frames import StartFrame
+from pipecat.frames.frames import LLMRunFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.llm_response_universal import LLMContextAggregatorPair
 from pipecat.runner.types import RunnerArguments
 from pipecat.runner.utils import create_transport
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.hume.tts import HUME_SAMPLE_RATE, HumeTTSService
 from pipecat.services.openai.llm import OpenAILLMService
 from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
-from pipecat.transports.services.daily import DailyParams
+from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
 
 load_dotenv(override=True)
 
@@ -40,12 +39,7 @@ transport_params = {
         audio_out_enabled=True,
         vad_analyzer=SileroVADAnalyzer(),
     ),
-    "webrtc": lambda: TransportParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-        vad_analyzer=SileroVADAnalyzer(),
-        audio_out_sample_rate=HUME_SAMPLE_RATE,
-    ),
+    "webrtc": lambda: TransportParams(),
 }
 
 
@@ -69,8 +63,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         },
     ]
 
-    context = OpenAILLMContext(messages)
-    context_aggregator = llm.create_context_aggregator(context)
+    context = LLMContext(messages)
+    context_aggregator = LLMContextAggregatorPair(context)
 
     pipeline = Pipeline(
         [
@@ -89,6 +83,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         params=PipelineParams(
             enable_metrics=True,
             enable_usage_metrics=True,
+            audio_out_sample_rate=HUME_SAMPLE_RATE,
         ),
         idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
     )
@@ -98,7 +93,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
         logger.info(f"Client connected")
         # Kick off the conversation.
         messages.append({"role": "system", "content": "Please introduce yourself to the user."})
-        await task.queue_frames([context_aggregator.user().get_context_frame()])
+        await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(transport, client):
@@ -112,7 +107,6 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
 
 async def bot(runner_args: RunnerArguments):
     """Main bot entry point compatible with Pipecat Cloud."""
-    runner_args.transport = "webrtc"
     transport = await create_transport(runner_args, transport_params)
 
     await run_bot(transport, runner_args)