Creating a Tavus example using the DailyTransport.

examples/foundational/21b-tavus-layer-daily-transport.py

@@ -7,9 +7,9 @@
 import asyncio
 import os
 import sys
-from typing import Any, Mapping
 
 import aiohttp
+from daily_runner import configure
 from dotenv import load_dotenv
 from loguru import logger
 
@@ -20,7 +20,7 @@ from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
-from pipecat.services.openai.llm import OpenAILLMService
+from pipecat.services.google.llm import GoogleLLMService
 from pipecat.services.tavus.video import TavusVideoService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
@@ -32,23 +32,20 @@ logger.add(sys.stderr, level="DEBUG")
 
 async def main():
     async with aiohttp.ClientSession() as session:
-        tavus = TavusVideoService(
-            api_key=os.getenv("TAVUS_API_KEY"),
-            replica_id=os.getenv("TAVUS_REPLICA_ID"),
-            session=session,
-        )
-
-        # get persona, look up persona_name, set this as the bot name to ignore
-        persona_name = await tavus.get_persona_name()
-        room_url = await tavus.initialize()
+        (room_url, token) = await configure(session)
 
         transport = DailyTransport(
-            room_url=room_url,
-            token=None,
-            bot_name="Pipecat bot",
-            params=DailyParams(
+            room_url,
+            token,
+            "Pipecat bot",
+            DailyParams(
                 audio_in_enabled=True,
+                audio_out_enabled=True,
+                video_out_enabled=True,
+                video_out_is_live=True,
                 vad_analyzer=SileroVADAnalyzer(),
+                video_out_width=1280,
+                video_out_height=720,
             ),
         )
 
@@ -59,7 +56,13 @@ async def main():
             voice_id="a167e0f3-df7e-4d52-a9c3-f949145efdab",
         )
 
-        llm = OpenAILLMService(model="gpt-4o-mini")
+        llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"))
+
+        tavus = TavusVideoService(
+            api_key=os.getenv("TAVUS_API_KEY"),
+            replica_id=os.getenv("TAVUS_REPLICA_ID"),
+            session=session,
+        )
 
         messages = [
             {
@@ -87,10 +90,8 @@ async def main():
         task = PipelineTask(
             pipeline,
             params=PipelineParams(
-                # We just use 16000 because that's what Tavus is expecting and
-                # we avoid resampling.
                 audio_in_sample_rate=16000,
-                audio_out_sample_rate=16000,
+                audio_out_sample_rate=24000,
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,
@@ -98,33 +99,22 @@ async def main():
             ),
         )
 
-        @transport.event_handler("on_participant_joined")
-        async def on_participant_joined(
-            transport: DailyTransport, participant: Mapping[str, Any]
-        ) -> None:
-            # Ignore the Tavus replica's microphone
-            if participant.get("info", {}).get("userName", "") == persona_name:
-                logger.debug(f"Ignoring {participant['id']}'s microphone")
-                await transport.update_subscriptions(
-                    participant_settings={
-                        participant["id"]: {
-                            "media": {"microphone": "unsubscribed"},
-                        }
-                    }
-                )
-
-            if participant.get("info", {}).get("userName", "") != persona_name:
-                # 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()])
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            # Kick off the conversation.
+            messages.append(
+                {
+                    "role": "system",
+                    "content": "Start by greeting the user and ask how you can help.",
+                }
+            )
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
 
         @transport.event_handler("on_participant_left")
         async def on_participant_left(transport, participant, reason):
             await task.cancel()
 
-        runner = PipelineRunner()
+        runner = PipelineRunner(handle_sigint=False)
 
         await runner.run(task)