testing vad-gated-pipeline

examples/fast-chatbot/bot.py

@@ -18,7 +18,7 @@ from pydantic import BaseModel, ValidationError
 from pipecat.vad.vad_analyzer import VADParams
 from pipecat.vad.silero import SileroVADAnalyzer
 from pipecat.transports.services.daily import DailyParams, DailyTransport
-from pipecat.services.openai import OpenAILLMService
+from pipecat.services.openai import OpenAILLMService, OpenAILLMContext
 from pipecat.services.deepgram import DeepgramSTTService
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.pipeline.runner import PipelineRunner
@@ -30,11 +30,19 @@ from pipecat.processors.aggregators.llm_response import (
 )
 
 from helpers import (
+    GreedyLLMAggregator,
     ClearableDeepgramTTSService,
+    VADGate,
     AudioVolumeTimer,
     TranscriptionTimingLogger
 )
 
+# from helpers import (
+#     ClearableDeepgramTTSService,
+#     AudioVolumeTimer,
+#     TranscriptionTimingLogger
+# )
+
 
 from dotenv import load_dotenv
 load_dotenv(override=True)
@@ -105,22 +113,41 @@ async def main(settings: BotSettings):
             },
         ]
 
+        # avt = AudioVolumeTimer()
+        # tl = TranscriptionTimingLogger(avt)
+
+        # tma_in = LLMUserResponseAggregator(messages)
+        # tma_out = LLMAssistantResponseAggregator(messages)
+
+        # pipeline = Pipeline([
+        #     transport.input(),   # Transport user input
+        #     avt,                 # Audio volume timer
+        #     stt,                 # Speech-to-text
+        #     tl,                  # Transcription timing logger
+        #     tma_in,              # User responses
+        #     llm,                 # LLM
+        #     tts,                 # TTS
+        #     transport.output(),  # Transport bot output
+        #     tma_out,             # Assistant spoken responses
+        # ])
+
+        ctx = OpenAILLMContext()
+        greedy = GreedyLLMAggregator(name="greedy", context=ctx)
+        gate = VADGate(name="gate", vad_analyzer=transport.input().vad_analyzer(), context=ctx)
         avt = AudioVolumeTimer()
         tl = TranscriptionTimingLogger(avt)
 
-        tma_in = LLMUserResponseAggregator(messages)
-        tma_out = LLMAssistantResponseAggregator(messages)
-
         pipeline = Pipeline([
             transport.input(),   # Transport user input
-            avt,                 # Audio volume timer
-            stt,                 # Speech-to-text
-            tl,                  # Transcription timing logger
-            tma_in,              # User responses
+            avt,
+            stt,
+            tl,
+            greedy,
             llm,                 # LLM
             tts,                 # TTS
+            gate,
             transport.output(),  # Transport bot output
-            tma_out,             # Assistant spoken responses
+            # FrameLogger()
         ])
 
         task = PipelineTask(
@@ -159,6 +186,7 @@ if __name__ == "__main__":
 
     try:
         settings = BotSettings.model_validate_json(args.settings)
+        # print(f"settings: {settings.json()}")
         asyncio.run(main(settings))
     except ValidationError as e:
         print(e)