Updates to cloud examples: cloud-simple so it can be deployed and use Krisp

examples/quickstart/cloud-multi-bot.py

@@ -14,6 +14,7 @@ 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.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
 from pipecat.runner.cloud import SmallWebRTCSessionArguments
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
@@ -53,9 +54,12 @@ async def run_bot(transport):
     context = OpenAILLMContext(messages)
     context_aggregator = llm.create_context_aggregator(context)
 
+    rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
+
     pipeline = Pipeline(
         [
             transport.input(),
+            rtvi,
             stt,
             context_aggregator.user(),
             llm,
@@ -71,6 +75,7 @@ async def run_bot(transport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        observers=[RTVIObserver(rtvi)],
     )
 
     @transport.event_handler("on_client_connected")

examples/quickstart/cloud-simple-bot.py

@@ -5,6 +5,8 @@
 #
 
 import os
+from dataclasses import dataclass
+from typing import Any, Optional
 
 from dotenv import load_dotenv
 from loguru import logger
@@ -14,7 +16,9 @@ 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.runner.cloud import SmallWebRTCSessionArguments
+
+# from pipecat.runner.cloud import SmallWebRTCSessionArguments # Need a release of Pipecat to use this
+from pipecat.processors.frameworks.rtvi import RTVIConfig, RTVIObserver, RTVIProcessor
 from pipecat.services.cartesia.tts import CartesiaTTSService
 from pipecat.services.deepgram.stt import DeepgramSTTService
 from pipecat.services.openai.llm import OpenAILLMService
@@ -30,6 +34,26 @@ except ImportError:
 load_dotenv(override=True)
 
 
+# For now, we'll just define SmallWebRTCSessionArguments here directly since Pipecat
+# isn't released with the pipecat.runner.cloud module yet.
+# This saves us from having to build a Docker container from my branch or main to
+# deploy to PCC.
+@dataclass
+class SmallWebRTCSessionArguments:
+    """Small WebRTC session arguments for local development.
+
+    This will be replaced by pipecatcloud.agent.SmallWebRTCSessionArguments
+    when WebRTC support is added to Pipecat Cloud.
+    """
+
+    webrtc_connection: Any
+    session_id: Optional[str] = None
+
+
+# Check if we're running locally
+IS_LOCAL_RUN = os.environ.get("LOCAL_RUN", "0") == "1"
+
+
 async def run_bot(transport):
     """Main bot logic that works with any transport."""
     logger.info(f"Starting bot")
@@ -53,9 +77,12 @@ async def run_bot(transport):
     context = OpenAILLMContext(messages)
     context_aggregator = llm.create_context_aggregator(context)
 
+    rtvi = RTVIProcessor(config=RTVIConfig(config=[]))
+
     pipeline = Pipeline(
         [
             transport.input(),
+            rtvi,
             stt,
             context_aggregator.user(),
             llm,
@@ -71,6 +98,7 @@ async def run_bot(transport):
             enable_metrics=True,
             enable_usage_metrics=True,
         ),
+        observers=[RTVIObserver(rtvi)],
     )
 
     @transport.event_handler("on_client_connected")
@@ -94,12 +122,18 @@ async def bot(session_args: DailySessionArguments | SmallWebRTCSessionArguments)
     if isinstance(session_args, DailySessionArguments):
         from pipecat.transports.services.daily import DailyParams, DailyTransport
 
+        if not IS_LOCAL_RUN:
+            from pipecat.audio.filters.krisp_filter import KrispFilter
+
         transport = DailyTransport(
             session_args.room_url,
             session_args.token,
             "Pipecat Bot",
             params=DailyParams(
                 audio_in_enabled=True,
+                audio_in_filter=None
+                if IS_LOCAL_RUN
+                else KrispFilter(),  # Only use Krisp in production
                 audio_out_enabled=True,
                 vad_analyzer=SileroVADAnalyzer(),
             ),

examples/quickstart/pcc-deploy.toml

@@ -2,6 +2,7 @@ agent_name = "cloud-simple-bot"
 image = "your_dockerhub_username/cloud-simple-bot:0.1"
 image_credentials = "dockerhub-access"
 secret_set = "cloud-simple-bot-secrets"
+enable_krisp = true
 
 [scaling]
 	min_agents = 0