attempt at 2 pipelines

BaseInputTransport: remove VAD logging

.gitignore

@@ -32,6 +32,21 @@ fly.toml
 
 # Example files
 pipecat/examples/twilio-chatbot/templates/streams.xml
+pipecat/examples/bot-ready-signalling/client/react-native/node_modules/
+pipecat/examples/bot-ready-signalling/client/react-native/.expo/
+pipecat/examples/bot-ready-signalling/client/react-native/dist/
+pipecat/examples/bot-ready-signalling/client/react-native/npm-debug.*
+pipecat/examples/bot-ready-signalling/client/react-native/*.jks
+pipecat/examples/bot-ready-signalling/client/react-native/*.p8
+pipecat/examples/bot-ready-signalling/client/react-native/*.p12
+pipecat/examples/bot-ready-signalling/client/react-native/*.key
+pipecat/examples/bot-ready-signalling/client/react-native/*.mobileprovision
+pipecat/examples/bot-ready-signalling/client/react-native/*.orig.*
+pipecat/examples/bot-ready-signalling/client/react-native/web-build/
+
+# macOS
+.DS_Store
+
 
 # Documentation
 docs/api/_build/

CHANGELOG.md

@@ -5,6 +5,44 @@ All notable changes to **Pipecat** will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## Unreleased
+
+### Added
+
+- Added `room_url` property to `DailyTransport`.
+
+- Added `addons` argument to `DeepgramSTTService`.
+
+- Added `exponential_backoff_time()` to `utils.network` module.
+
+### Changed
+
+- `DeepgramSTTService` now uses the new `nova-3` model by default. If you want
+  to use the previous model you can pass `LiveOptions(model="nova-2-general")`.
+  (see https://deepgram.com/learn/introducing-nova-3-speech-to-text-api)
+
+```python
+stt = DeepgramSTTService(..., live_options=LiveOptions(model="nova-2-general"))
+```
+
+### Fixed
+
+- Fixed a `FishAudioTTSService` issue where `TTSStoppedFrame` was not being
+  pushed.
+
+- Fixed an issue that `start_callback` was not invoked for some LLM services.
+
+- Fixed an issue that would cause `DeepgramSTTService` to stop working after an
+  error occurred (e.g. sudden network loss). If the network recovered we would
+  not reconnect.
+
+- Fixed a `STTMuteFilter` issue that would not mute user audio frames causing
+  transcriptions to be generated by the STT service.
+
+### Other
+
+- Added Gemini support to `examples/phone-chatbot`.
+
 ## [0.0.57] - 2025-02-14
 
 ### Added

examples/bot-ready-signalling/client/react-native/.nvmrc

@@ -0,0 +1 @@
+22.14

examples/bot-ready-signalling/client/react-native/README.md

@@ -0,0 +1,60 @@
+# React Native Implementation
+
+Basic implementation using the [Pipecat React Native SDK](https://docs.pipecat.ai/client/react-native/introduction).
+
+## Usage
+
+### Expo requirements
+
+This project cannot be used with an [Expo Go](https://docs.expo.dev/workflow/expo-go/) app because [it requires custom native code](https://docs.expo.io/workflow/customizing/).
+
+When a project requires custom native code or a config plugin, we need to transition from using [Expo Go](https://docs.expo.dev/workflow/expo-go/) 
+to a [development build](https://docs.expo.dev/development/introduction/).
+
+More details about the custom native code used by this demo can be found in [rn-daily-js-expo-config-plugin](https://github.com/daily-co/rn-daily-js-expo-config-plugin).
+
+### Building remotely
+
+If you do not have experience with Xcode and Android Studio builds or do not have them installed locally on your computer, you will need to follow [this guide from Expo to use EAS Build](https://docs.expo.dev/development/create-development-builds/#create-and-install-eas-build).
+
+### Building locally
+
+You will need to have installed locally on your computer:
+- [Xcode](https://developer.apple.com/xcode/) to build for iOS;
+- [Android Studio](https://developer.android.com/studio) to build for Android;
+
+#### Install the demo dependencies
+
+```bash
+# Use the version of node specified in .nvmrc
+nvm i
+
+# Install dependencies
+npm i
+
+# Before a native app can be compiled, the native source code must be generated.
+npx expo prebuild
+
+# Configure the environment variable to connect to the local server
+cp env.example .env
+# edit .env and add your local ip address, for example: http://192.168.1.16:7860
+```
+
+#### Running on Android
+
+After plugging in an Android device [configured for debugging](https://developer.android.com/studio/debug/dev-options), run the following command:
+
+```
+npm run android
+```
+
+#### Running on iOS
+
+Run the following command:
+
+```
+npm run ios
+```
+
+#### Connect to the server
+Use the http://localhost:5173 in your app.

examples/bot-ready-signalling/client/react-native/app.json

@@ -0,0 +1,75 @@
+{
+  "expo": {
+    "name": "bot-ready-rn",
+    "slug": "bot-ready-rn",
+    "version": "1.0.0",
+    "orientation": "portrait",
+    "icon": "./assets/icon.png",
+    "userInterfaceStyle": "light",
+    "splash": {
+      "image": "./assets/splash.png",
+      "resizeMode": "contain",
+      "backgroundColor": "#ffffff"
+    },
+    "updates": {
+      "fallbackToCacheTimeout": 0
+    },
+    "assetBundlePatterns": [
+      "**/*"
+    ],
+    "ios": {
+      "supportsTablet": true,
+      "bitcode": false,
+      "bundleIdentifier": "co.daily.expo.BotReady",
+      "infoPlist": {
+        "UIBackgroundModes": [
+          "voip"
+        ]
+      },
+      "appleTeamId": "EEBGKV9N3N"
+    },
+    "android": {
+      "adaptiveIcon": {
+        "foregroundImage": "./assets/adaptive-icon.png",
+        "backgroundColor": "#FFFFFF"
+      },
+      "package": "co.daily.expo.BotReady",
+      "permissions": [
+        "android.permission.ACCESS_NETWORK_STATE",
+        "android.permission.BLUETOOTH",
+        "android.permission.CAMERA",
+        "android.permission.INTERNET",
+        "android.permission.MODIFY_AUDIO_SETTINGS",
+        "android.permission.RECORD_AUDIO",
+        "android.permission.SYSTEM_ALERT_WINDOW",
+        "android.permission.WAKE_LOCK",
+        "android.permission.FOREGROUND_SERVICE",
+        "android.permission.FOREGROUND_SERVICE_CAMERA",
+        "android.permission.FOREGROUND_SERVICE_MICROPHONE",
+        "android.permission.FOREGROUND_SERVICE_MEDIA_PROJECTION",
+        "android.permission.POST_NOTIFICATIONS"
+      ]
+    },
+    "web": {
+      "favicon": "./assets/favicon.png"
+    },
+    "plugins": [
+      "@config-plugins/react-native-webrtc",
+      "@daily-co/config-plugin-rn-daily-js",
+      [
+        "expo-build-properties",
+        {
+          "android": {
+            "minSdkVersion": 24,
+            "compileSdkVersion": 35,
+            "targetSdkVersion": 34,
+            "buildToolsVersion": "35.0.0"
+          },
+          "ios": {
+            "deploymentTarget": "15.1"
+          }
+        }
+      ]
+    ]
+  }
+}

examples/bot-ready-signalling/client/react-native/babel.config.js

@@ -0,0 +1,7 @@
+module.exports = function(api) {
+  api.cache(true);
+  return {
+    presets: ['babel-preset-expo'],
+    plugins: [["module:react-native-dotenv"]],
+  };
+};

examples/bot-ready-signalling/client/react-native/env.example

@@ -0,0 +1 @@
+API_BASE_URL=http://YOUR_LOCAL_IP:7860

examples/bot-ready-signalling/client/react-native/index.js

@@ -0,0 +1,7 @@
+import { registerRootComponent } from "expo";
+
+import App from "./src/App";
+
+// registerRootComponent calls AppRegistry.registerComponent('main', () => App);
+// It also ensures that the environment is set up appropriately
+registerRootComponent(App);

examples/bot-ready-signalling/client/react-native/metro.config.js

@@ -0,0 +1,4 @@
+// Learn more https://docs.expo.io/guides/customizing-metro
+const { getDefaultConfig } = require('expo/metro-config');
+
+module.exports = getDefaultConfig(__dirname);

examples/bot-ready-signalling/client/react-native/package.json

@@ -0,0 +1,31 @@
+{
+  "name": "bot-ready-rn",
+  "version": "1.0.0",
+  "scripts": {
+    "start": "expo start --dev-client",
+    "android": "expo run:android --device",
+    "ios": "expo run:ios --device",
+    "web": "expo start --web"
+  },
+  "dependencies": {
+    "@config-plugins/react-native-webrtc": "^10.0.0",
+    "@daily-co/config-plugin-rn-daily-js": "0.0.7",
+    "@daily-co/react-native-daily-js": "^0.70.0",
+    "@daily-co/react-native-webrtc": "^118.0.3-daily.2",
+    "@react-native-async-storage/async-storage": "1.23.1",
+    "expo": "^52.0.0",
+    "expo-build-properties": "~0.13.1",
+    "expo-dev-client": "~5.0.5",
+    "expo-splash-screen": "~0.29.16",
+    "expo-status-bar": "~2.0.0",
+    "react": "18.3.1",
+    "react-native": "0.76.3",
+    "react-native-background-timer": "^2.4.1",
+    "react-native-dotenv": "^3.4.11",
+    "react-native-get-random-values": "^1.11.0"
+  },
+  "devDependencies": {
+    "@babel/core": "^7.12.9"
+  },
+  "private": true
+}

examples/bot-ready-signalling/client/react-native/src/App.js

@@ -0,0 +1,121 @@
+import React, { useState, useEffect } from 'react';
+import {SafeAreaView, View, Text, Button, StyleSheet, ScrollView} from 'react-native';
+import Daily from "@daily-co/react-native-daily-js";
+import { API_BASE_URL } from "@env";
+
+const CallScreen = () => {
+  const [connectionStatus, setConnectionStatus] = useState('Disconnected');
+  const [isConnected, setIsConnected] = useState(false);
+  const [callObject, setCallObject] = useState(null);
+  const [logs, setLogs] = useState([]);
+
+  useEffect(() => {
+    if (callObject) {
+      setupTrackListeners(callObject);
+    }
+  }, [callObject]);
+
+  const log = (message) => {
+    setLogs((prevLogs) => [...prevLogs, `${new Date().toISOString()} - ${message}`]);
+    console.log(message);
+  };
+
+  const setupTrackListeners = (callObject) => {
+    callObject.on("joined-meeting", () => {
+      setConnectionStatus('Connected');
+      setIsConnected(true);
+      log('Client connected');
+    });
+    callObject.on("left-meeting", () => {
+      setConnectionStatus('Disconnected');
+      setIsConnected(false);
+      log('Client disconnected');
+    });
+    callObject.on("participant-left", () => {
+      // When the bot leaves, we are also disconnecting from the call
+      disconnect().catch((err) => {
+        log(`Failed to disconnect ${err}`);
+      })
+    });
+    // Trigger so the bot can start sending audio
+    callObject.on("track-started", (evt) => {
+      if (evt.track.kind === "audio" && evt.participant.local === false) {
+        handleEventToConsole(evt)
+        log("Sending the message that will trigger the bot to play the audio.")
+        callObject.sendAppMessage("playable")
+      }
+    });
+    callObject.on("error", (evt) => log(`Error: ${evt.error}`));
+    // Other events just for awareness
+    callObject.on("track-stopped", handleEventToConsole);
+    callObject.on("participant-joined", handleEventToConsole);
+    callObject.on("participant-updated", handleEventToConsole);
+  };
+
+  const handleEventToConsole = (evt) => {
+    log(`Received event: ${evt.action}`);
+  };
+
+  const connect = async () => {
+    try {
+      const callObject = Daily.createCallObject({ subscribeToTracksAutomatically: true });
+      setCallObject(callObject);
+      const connectionUrl = `${API_BASE_URL}/connect`
+      const res = await fetch(connectionUrl, { method: "POST", headers: { "Content-Type": "application/json" } });
+      const roomInfo = await res.json();
+      await callObject.join({ url: roomInfo.room_url });
+    } catch (error) {
+      log(`Error connecting: ${error.message}`);
+    }
+  };
+
+  const disconnect = async () => {
+    if (callObject) {
+      try {
+        await callObject.leave();
+        await callObject.destroy();
+        setCallObject(null);
+      } catch (error) {
+        log(`Error disconnecting: ${error.message}`);
+      }
+    }
+  };
+
+  return (
+      <SafeAreaView style={styles.safeArea}>
+        <View style={styles.container}>
+          <View style={styles.statusBar}>
+            <Text>Status: <Text style={styles.status}>{connectionStatus}</Text></Text>
+            <View style={styles.controls}>
+              <Button
+                title={isConnected ? "Disconnect" : "Connect"}
+                onPress={isConnected ? disconnect : connect}
+              />
+            </View>
+          </View>
+
+          <View style={styles.debugPanel}>
+            <Text style={styles.debugTitle}>Debug Info</Text>
+            <ScrollView style={styles.debugLog}>
+              {logs.map((logEntry, index) => (
+                  <Text key={index} style={styles.logText}>{logEntry}</Text>
+              ))}
+            </ScrollView>
+          </View>
+        </View>
+      </SafeAreaView>
+  );
+};
+
+const styles = StyleSheet.create({
+  safeArea: { flex: 1, backgroundColor: '#f0f0f0', padding: 20 },
+  container: { flex: 1, margin: 20 },
+  statusBar: { flexDirection: 'row', justifyContent: 'space-between', alignItems: 'center', padding: 10, backgroundColor: '#fff', borderRadius: 8, marginBottom: 20 },
+  status: { fontWeight: 'bold' },
+  controls: { flexDirection: 'row', gap: 10 },
+  debugPanel: { height: '80%', backgroundColor: '#fff', borderRadius: 8, padding: 20},
+  debugTitle: { fontSize: 16, fontWeight: 'bold' },
+  debugLog: { height: '100%', overflow: 'scroll', backgroundColor: '#f8f8f8', padding: 10, borderRadius: 4, fontFamily: 'monospace', fontSize: 12, lineHeight: 1.4 },
+});
+
+export default CallScreen;

examples/foundational/14e-function-calling-gemini.py

@@ -14,6 +14,7 @@ from loguru import logger
 from runner import configure
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -30,6 +31,12 @@ logger.add(sys.stderr, level="DEBUG")
 video_participant_id = None
 
 
+async def start_fetch_weather(function_name, llm, context):
+    """Push a frame to the LLM; this is handy when the LLM response might take a while."""
+    await llm.push_frame(TTSSpeakFrame("Let me check on that."))
+    logger.debug(f"Starting fetch_weather_from_api with function_name: {function_name}")
+
+
 async def get_weather(function_name, tool_call_id, arguments, llm, context, result_callback):
     location = arguments["location"]
     await result_callback(f"The weather in {location} is currently 72 degrees and sunny.")
@@ -63,7 +70,7 @@ async def main():
         )
 
         llm = GoogleLLMService(api_key=os.getenv("GOOGLE_API_KEY"), model="gemini-2.0-flash-001")
-        llm.register_function("get_weather", get_weather)
+        llm.register_function("get_weather", get_weather, start_fetch_weather)
         llm.register_function("get_image", get_image)
 
         tools = [

examples/phone-chatbot/README.md

@@ -1,3 +1,5 @@
+<!-- @format -->
+
 <div align="center">
  <img alt="pipecat" width="300px" height="auto" src="image.png">
 </div>
@@ -104,6 +106,41 @@ curl -X POST "http://localhost:7860/daily_start_bot" \
      -d '{"dialoutNumber": "+18057145330", "detectVoicemail": true}'
 ```
 
+### New! Using Gemini 2.0 Flash Lite with Daily
+
+We have introduced support for Google's Gemini 2.0 Flash Lite model in this example. This lightweight model offers faster response times and reduced costs while maintaining good conversational capabilities.
+
+**Quick Start**
+To use the Gemini-based bot instead of OpenAI:
+
+
+```shell
+curl -X POST "http://localhost:7860/daily_gemini_start_bot" \                                                                                                        py pipecat
+     -H "Content-Type: application/json" \
+     -d '{"detectVoicemail": true}'
+```
+
+All request body parameters supported by /daily_start_bot (such as detectVoicemail, dialoutNumber, etc.) are also compatible with /daily_gemini_start_bot.
+
+This example uses context switching to help steer the bot in the right direction. As Flash Lite is a smaller model, getting it to consistently call functions was difficult for these longer prompts. Breaking the prompt
+down into smaller pieces helped improve the accuracy of the bot.
+
+**Implementation Details**
+The implementation is available in bot_daily_gemini.py and features:
+
+Staged prompting approach: Breaking down complex tasks into smaller, more focused prompts to improve the lightweight model's performance
+Dynamic context switching: The bot can change its behavior in real-time based on what it detects (voicemail vs. human caller)
+Function-based architecture: Uses function calling to trigger context switches and call termination
+
+**Optimizations for Lightweight Models**
+Working with Gemini 2.0 Flash Lite required some specific optimizations:
+
+Simplified prompts: Each prompt focuses on a single task with clear instructions
+Function-driven state changes: The model calls specific functions to switch between different conversation modes
+Reduced context requirements: Each stage maintains only the context needed for its specific purpose
+
+This approach significantly improves the consistency of function calling in this lightweight model, which was challenging with longer, more complex prompts.
+
 ### More information
 
 For more configuration options, please consult [Daily's API documentation](https://docs.daily.co).

examples/phone-chatbot/bot_daily.py

@@ -49,7 +49,11 @@ async def main(
     # If you are handling this via Twilio, Telnyx, set this to None
     # and handle call-forwarding when on_dialin_ready fires.
 
-    dialin_settings = DailyDialinSettings(call_id=callId, call_domain=callDomain)
+    # We don't want to specify dialin settings if we're not dialing in
+    dialin_settings = None
+    if callId and callDomain:
+        dialin_settings = DailyDialinSettings(call_id=callId, call_domain=callDomain)
+
     transport = DailyTransport(
         room_url,
         token,
@@ -96,8 +100,16 @@ async def main(
             - **"Please leave a message after the beep."**
             - **"No one is available to take your call."**
             - **"Record your message after the tone."**
+            - **"Please leave a message after the beep"**
+            - **"You have reached voicemail for..."**
+            - **"You have reached [phone number]"**
+            - **"[phone number] is unavailable"**
+            - **"The person you are trying to reach..."**
+            - **"The number you have dialed..."**
+            - **"Your call has been forwarded to an automated voice messaging system"**
             - **Any phrase that suggests an answering machine or voicemail.**
             - **ASSUME IT IS A VOICEMAIL. DO NOT WAIT FOR MORE CONFIRMATION.**
+            - **IF THE CALL SAYS "PLEASE LEAVE A MESSAGE AFTER THE BEEP", WAIT FOR THE BEEP BEFORE LEAVING A MESSAGE.**
 
             #### **Step 2: Leave a Voicemail Message**
             - Immediately say:
@@ -110,7 +122,9 @@ async def main(
             - If the call is answered by a human, say:
             *"Oh, hello! I'm a friendly chatbot. Is there anything I can help you with?"*
             - Keep responses **brief and helpful**.
-            - If the user no longer needs assistance, **call `terminate_call` immediately.**
+            - If the user no longer needs assistance, say:
+            *"Okay, thank you! Have a great day!"*
+            -**Then call `terminate_call` immediately.**
 
             ---
 

examples/phone-chatbot/bot_daily_gemini.py

@@ -0,0 +1,393 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+import argparse
+import asyncio
+import os
+import sys
+from dataclasses import dataclass
+from typing import Optional
+
+import google.ai.generativelanguage as glm
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import (
+    BotStoppedSpeakingFrame,
+    EndTaskFrame,
+    Frame,
+    InputAudioRawFrame,
+    StopTaskFrame,
+    SystemFrame,
+    TranscriptionFrame,
+    UserStartedSpeakingFrame,
+    UserStoppedSpeakingFrame,
+)
+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 OpenAILLMContextFrame
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.services.ai_services import LLMService
+from pipecat.services.elevenlabs import ElevenLabsTTSService
+from pipecat.services.google import GoogleLLMContext, GoogleLLMService
+from pipecat.transports.services.daily import DailyDialinSettings, DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+daily_api_key = os.getenv("DAILY_API_KEY", "")
+daily_api_url = os.getenv("DAILY_API_URL", "https://api.daily.co/v1")
+
+system_message = None
+
+
+class UserAudioCollector(FrameProcessor):
+    """This FrameProcessor collects audio frames in a buffer, then adds them to the
+    LLM context when the user stops speaking.
+    """
+
+    def __init__(self, context, user_context_aggregator):
+        super().__init__()
+        self._context = context
+        self._user_context_aggregator = user_context_aggregator
+        self._audio_frames = []
+        self._start_secs = 0.2  # this should match VAD start_secs (hardcoding for now)
+        self._user_speaking = False
+
+    async def process_frame(self, frame, direction):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, TranscriptionFrame):
+            # We could gracefully handle both audio input and text/transcription input ...
+            # but let's leave that as an exercise to the reader. :-)
+            return
+        if isinstance(frame, UserStartedSpeakingFrame):
+            self._user_speaking = True
+        elif isinstance(frame, UserStoppedSpeakingFrame):
+            self._user_speaking = False
+            self._context.add_audio_frames_message(audio_frames=self._audio_frames)
+            await self._user_context_aggregator.push_frame(
+                self._user_context_aggregator.get_context_frame()
+            )
+        elif isinstance(frame, InputAudioRawFrame):
+            if self._user_speaking:
+                self._audio_frames.append(frame)
+            else:
+                # Append the audio frame to our buffer. Treat the buffer as a ring buffer, dropping the oldest
+                # frames as necessary. Assume all audio frames have the same duration.
+                self._audio_frames.append(frame)
+                frame_duration = len(frame.audio) / 16 * frame.num_channels / frame.sample_rate
+                buffer_duration = frame_duration * len(self._audio_frames)
+                while buffer_duration > self._start_secs:
+                    self._audio_frames.pop(0)
+                    buffer_duration -= frame_duration
+
+        await self.push_frame(frame, direction)
+
+
+class ContextSwitcher:
+    def __init__(self, llm, context_aggregator):
+        self._llm = llm
+        self._context_aggregator = context_aggregator
+
+    async def switch_context(self, system_instruction):
+        """Switch the context to a new system instruction based on what the bot hears."""
+        # Create messages with updated system instruction
+        messages = [
+            {
+                "role": "system",
+                "content": system_instruction,
+            }
+        ]
+
+        # Update context with new messages
+        self._context_aggregator.set_messages(messages)
+        # Get the context frame with the updated messages
+        context_frame = self._context_aggregator.get_context_frame()
+        # Trigger LLM response by pushing a context frame
+        await self._llm.push_frame(context_frame)
+
+
+class FunctionHandlers:
+    def __init__(self, context_switcher):
+        self.context_switcher = context_switcher
+
+    async def voicemail_response(
+        self, function_name, tool_call_id, args, llm, context, result_callback
+    ):
+        """Function the bot can call to leave a voicemail message."""
+        print(f"!!! Got a voicemail response, llm is: {llm}")
+        system_message = """You are Chatbot leaving a voicemail message. Say EXACTLY this message and nothing else:
+
+                    "Hello, this is a message for Pipecat example user. This is Chatbot. Please call back on 123-456-7891. Thank you."
+
+                    After saying this message, call the terminate_call function."""
+        print("!!! about to push stop task frame from voicemail")
+        await llm.queue_frame(StopTaskFrame(), FrameDirection.UPSTREAM)
+        print("!!! pushed stop task frame from voicemail")
+        await result_callback("Goodbye")
+
+    async def human_conversation(
+        self, function_name, tool_call_id, args, llm, context, result_callback
+    ):
+        """Function the bot can when it detects it's talking to a human."""
+        print(f"!!! Got a human response, llm is: {llm}")
+
+        system_message = """You are Chatbot talking to a human. Be friendly and helpful.
+
+                    Start with: "Hello! I'm a friendly chatbot. How can I help you today?"
+
+                    Keep your responses brief and to the point. Listen to what the person says.
+
+                    When the person indicates they're done with the conversation by saying something like:
+                    - "Goodbye"
+                    - "That's all"
+                    - "I'm done"
+                    - "Thank you, that's all I needed"
+
+                    THEN say: "Thank you for chatting. Goodbye!" and call the terminate_call function."""
+        print("!!! about to push stop task frame from human")
+        await llm.queue_frame(StopTaskFrame(), FrameDirection.UPSTREAM)
+        print("!!! pushed stop task frame from human")
+        await result_callback("Goodbye")
+
+
+async def terminate_call(
+    function_name, tool_call_id, args, llm: LLMService, context, result_callback
+):
+    """Function the bot can call to terminate the call upon completion of the call."""
+    await llm.queue_frame(EndTaskFrame(), FrameDirection.UPSTREAM)
+
+
+async def main(
+    room_url: str,
+    token: str,
+    callId: str,
+    callDomain: str,
+    detect_voicemail: bool,
+    dialout_number: Optional[str],
+):
+    # dialin_settings are only needed if Daily's SIP URI is used
+    # If you are handling this via Twilio, Telnyx, set this to None
+    # and handle call-forwarding when on_dialin_ready fires.
+
+    # We don't want to specify dialin settings if we're not dialing in
+    dialin_settings = None
+    if callId and callDomain:
+        dialin_settings = DailyDialinSettings(call_id=callId, call_domain=callDomain)
+
+    transport = DailyTransport(
+        room_url,
+        token,
+        "Chatbot",
+        DailyParams(
+            api_url=daily_api_url,
+            api_key=daily_api_key,
+            dialin_settings=dialin_settings,
+            audio_in_enabled=True,
+            audio_out_enabled=True,
+            camera_out_enabled=False,
+            vad_enabled=True,
+            vad_analyzer=SileroVADAnalyzer(),
+            vad_audio_passthrough=True,
+            # transcription_enabled=True,
+        ),
+    )
+
+    tts = ElevenLabsTTSService(
+        api_key=os.getenv("ELEVENLABS_API_KEY", ""),
+        voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
+    )
+
+    tools = [
+        {
+            "function_declarations": [
+                {
+                    "name": "switch_to_voicemail_response",
+                    "description": "Call this function when you detect this is a voicemail system.",
+                },
+                {
+                    "name": "switch_to_human_conversation",
+                    "description": "Call this function when you detect this is a human.",
+                },
+                {
+                    "name": "terminate_call",
+                    "description": "Call this function to terminate the call.",
+                },
+            ]
+        }
+    ]
+
+    system_instruction = """You are Chatbot trying to determine if this is a voicemail system or a human.
+
+If you hear any of these phrases (or very similar ones):
+- "Please leave a message after the beep"
+- "No one is available to take your call"
+- "Record your message after the tone"
+- "You have reached voicemail for..."
+- "You have reached [phone number]"
+- "[phone number] is unavailable"
+- "The person you are trying to reach..."
+- "The number you have dialed..."
+- "Your call has been forwarded to an automated voice messaging system"
+
+Then call the function switch_to_voicemail_response.
+
+If it sounds like a human (saying hello, asking questions, etc.), call the function switch_to_human_conversation.
+
+DO NOT say anything until you've determined if this is a voicemail or human."""
+
+    greeting_llm = GoogleLLMService(
+        model="models/gemini-2.0-flash-lite-preview-02-05",
+        api_key=os.getenv("GOOGLE_API_KEY"),
+        system_instruction=system_instruction,
+        tools=tools,
+    )
+
+    greeting_context = GoogleLLMContext()
+    greeting_context_aggregator = greeting_llm.create_context_aggregator(greeting_context)
+    greeting_audio_collector = UserAudioCollector(
+        greeting_context, greeting_context_aggregator.user()
+    )
+
+    context_switcher = ContextSwitcher(greeting_llm, greeting_context_aggregator.user())
+    handlers = FunctionHandlers(context_switcher)
+
+    greeting_llm.register_function("switch_to_voicemail_response", handlers.voicemail_response)
+    greeting_llm.register_function("switch_to_human_conversation", handlers.human_conversation)
+    greeting_llm.register_function("terminate_call", terminate_call)
+
+    greeting_pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            greeting_audio_collector,  # Collect audio frames
+            greeting_context_aggregator.user(),  # User responses
+            greeting_llm,  # LLM
+            tts,  # TTS
+            transport.output(),  # Transport bot output
+            greeting_context_aggregator.assistant(),  # Assistant spoken responses
+        ]
+    )
+    greeting_pipeline_task = PipelineTask(
+        greeting_pipeline,
+        PipelineParams(allow_interruptions=True),
+    )
+    runner = PipelineRunner()
+
+    print("!!! starting greeting")
+    await runner.run(greeting_pipeline_task)
+    print("!!! Done with greeting")
+
+    # Create conversation pipeline with new system message
+    conversation_llm = GoogleLLMService(
+        model="models/gemini-2.0-flash-lite-preview-02-05",
+        api_key=os.getenv("GOOGLE_API_KEY"),
+        system_instruction=system_message if system_message else "You are a helpful chatbot.",
+        tools=[
+            {
+                "function_declarations": [
+                    {
+                        "name": "terminate_call",
+                        "description": "Call this function to terminate the call.",
+                    }
+                ]
+            }
+        ],
+    )
+    conversation_llm.register_function("terminate_call", terminate_call)
+
+    conversation_context = GoogleLLMContext()
+    conversation_context_aggregator = conversation_llm.create_context_aggregator(
+        conversation_context
+    )
+    conversation_audio_collector = UserAudioCollector(
+        conversation_context, conversation_context_aggregator.user()
+    )
+
+    conversation_pipeline = Pipeline(
+        [
+            transport.input(),  # Transport user input
+            conversation_audio_collector,  # Collect audio frames
+            conversation_context_aggregator.user(),  # User responses
+            conversation_llm,  # LLM
+            tts,  # TTS
+            transport.output(),  # Transport bot output
+            conversation_context_aggregator.assistant(),  # Assistant spoken responses
+        ]
+    )
+
+    conversation_task = PipelineTask(
+        conversation_pipeline,
+        PipelineParams(allow_interruptions=True),
+    )
+
+    if dialout_number:
+        logger.debug("dialout number detected; doing dialout")
+
+        # Configure some handlers for dialing out
+        @transport.event_handler("on_joined")
+        async def on_joined(transport, data):
+            logger.debug(f"Joined; starting dialout to: {dialout_number}")
+            await transport.start_dialout({"phoneNumber": dialout_number})
+
+        @transport.event_handler("on_dialout_connected")
+        async def on_dialout_connected(transport, data):
+            logger.debug(f"Dial-out connected: {data}")
+
+        @transport.event_handler("on_dialout_answered")
+        async def on_dialout_answered(transport, data):
+            logger.debug(f"Dial-out answered: {data}")
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_transcription(participant["id"])
+            # unlike the dialin case, for the dialout case, the caller will speak first. Presumably
+            # they will answer the phone and say "Hello?" Since we've captured their transcript,
+            # That will put a frame into the pipeline and prompt an LLM completion, which is how the
+            # bot will then greet the user.
+    elif detect_voicemail:
+        logger.debug("Detect voicemail example. You can test this in example in Daily Prebuilt")
+
+        # For the voicemail detection case, we do not want the bot to answer the phone. We want it to wait for the voicemail
+        # machine to say something like 'Leave a message after the beep', or for the user to say 'Hello?'.
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_transcription(participant["id"])
+    else:
+        logger.debug("no dialout number; assuming dialin")
+
+        # Different handlers for dialin
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_transcription(participant["id"])
+            # For the dialin case, we want the bot to answer the phone and greet the user. We
+            # can prompt the bot to speak by putting the context into the pipeline.
+            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 conversation_task.cancel()
+
+    print("!!! Starting conversation")
+    await runner.run(conversation_task)
+    print("!!! Done with conversation")
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Pipecat Simple ChatBot")
+    parser.add_argument("-u", type=str, help="Room URL")
+    parser.add_argument("-t", type=str, help="Token")
+    parser.add_argument("-i", type=str, help="Call ID")
+    parser.add_argument("-d", type=str, help="Call Domain")
+    parser.add_argument("-v", action="store_true", help="Detect voicemail")
+    parser.add_argument("-o", type=str, help="Dialout number", default=None)
+    config = parser.parse_args()
+
+    asyncio.run(main(config.u, config.t, config.i, config.d, config.v, config.o))

examples/phone-chatbot/bot_runner.py

@@ -110,10 +110,15 @@ async def _create_daily_room(
 
     # Spawn a new agent, and join the user session
     # Note: this is mostly for demonstration purposes (refer to 'deployment' in docs)
+    print(f"Vendor: {vendor}")
     if vendor == "daily":
         bot_proc = f"python3 -m bot_daily -u {room.url} -t {token} -i {callId} -d {callDomain}{' -v' if detect_voicemail else ''}"
         if dialoutNumber:
             bot_proc += f" -o {dialoutNumber}"
+    elif vendor == "daily-gemini":
+        bot_proc = f"python3 -m bot_daily_gemini -u {room.url} -t {token} -i {callId} -d {callDomain}{' -v' if detect_voicemail else ''}"
+        if dialoutNumber:
+            bot_proc += f" -o {dialoutNumber}"
     else:
         bot_proc = f"python3 -m bot_twilio -u {room.url} -t {token} -i {callId} -s {room.config.sip_endpoint}"
 
@@ -201,6 +206,38 @@ async def daily_start_bot(request: Request) -> JSONResponse:
     return JSONResponse({"room_url": room.url, "sipUri": room.config.sip_endpoint})
 
 
+@app.post("/daily_gemini_start_bot")
+async def daily_gemini_start_bot(request: Request) -> JSONResponse:
+    # The /daily_start_bot is invoked when a call is received on Daily's SIP URI
+    # daily_start_bot will create the room, put the call on hold until
+    # the bot and sip worker are ready. Daily will automatically
+    # forward the call to the SIP URi when dialin_ready fires.
+
+    # Use specified room URL, or create a new one if not specified
+    room_url = os.getenv("DAILY_SAMPLE_ROOM_URL", None)
+    # Get the dial-in properties from the request
+    try:
+        data = await request.json()
+        if "test" in data:
+            # Pass through any webhook checks
+            return JSONResponse({"test": True})
+        detect_voicemail = data.get("detectVoicemail", False)
+        callId = data.get("callId", None)
+        callDomain = data.get("callDomain", None)
+        dialoutNumber = data.get("dialoutNumber", None)
+    except Exception:
+        raise HTTPException(
+            status_code=500, detail="Missing properties 'callId', 'callDomain', or 'dialoutNumber'"
+        )
+
+    room: DailyRoomObject = await _create_daily_room(
+        room_url, callId, callDomain, dialoutNumber, "daily-gemini", detect_voicemail
+    )
+
+    # Grab a token for the user to join with
+    return JSONResponse({"room_url": room.url, "sipUri": room.config.sip_endpoint})
+
+
 # ----------------- Main ----------------- #
 
 

examples/translation-chatbot/bot.py

@@ -24,17 +24,15 @@ from pipecat.frames.frames import (
 )
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineTask
+from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.processors.frameworks.rtvi import RTVIObserver, RTVIProcessor
 from pipecat.processors.transcript_processor import TranscriptProcessor
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.deepgram import DeepgramSTTService
 from pipecat.services.openai import OpenAILLMService
-from pipecat.transports.services.daily import (
-    DailyParams,
-    DailyTransport,
-)
+from pipecat.transports.services.daily import DailyParams, DailyTransport
 
 load_dotenv(override=True)
 
@@ -166,21 +164,32 @@ async def main():
         async def on_transcript_update(processor, frame):
             await transcript_handler.on_transcript_update(processor, frame)
 
+        rtvi = RTVIProcessor()
+
         pipeline = Pipeline(
             [
                 transport.input(),
+                rtvi,
                 stt,
                 transcript.user(),  # User transcripts
                 tp,
                 llm,
                 tts,
                 transport.output(),
+                transcript.assistant(),
                 context_aggregator.assistant(),
-                transcript.assistant(),  # Assistant transcripts
             ]
         )
 
-        task = PipelineTask(pipeline)
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=False,  # We don't want to interrupt the translator bot
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                observers=[RTVIObserver(rtvi)],
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):

examples/translation-chatbot/requirements.txt

@@ -1,4 +1,4 @@
 python-dotenv
 fastapi[all]
-pipecat-ai[daily,openai,azure]
+pipecat-ai[cartesia,daily,deepgram,openai,silero]
 aiohttp

src/pipecat/processors/filters/stt_mute_filter.py

@@ -23,6 +23,7 @@ from pipecat.frames.frames import (
     Frame,
     FunctionCallInProgressFrame,
     FunctionCallResultFrame,
+    InputAudioRawFrame,
     StartFrame,
     StartInterruptionFrame,
     StopInterruptionFrame,
@@ -185,13 +186,14 @@ class STTMuteFilter(FrameProcessor):
                 StopInterruptionFrame,
                 UserStartedSpeakingFrame,
                 UserStoppedSpeakingFrame,
+                InputAudioRawFrame,
             ),
         ):
             # Only pass VAD-related frames when not muted
             if not self.is_muted:
                 await self.push_frame(frame, direction)
             else:
-                logger.debug(f"{frame.__class__.__name__} suppressed - STT currently muted")
+                logger.trace(f"{frame.__class__.__name__} suppressed - STT currently muted")
         else:
             # Pass all other frames through
             await self.push_frame(frame, direction)

src/pipecat/services/ai_services.py

@@ -175,6 +175,7 @@ class LLMService(AIService):
             f = self._callbacks[None]
         else:
             return None
+        await self.call_start_function(context, function_name)
         await context.call_function(
             f,
             function_name=function_name,
@@ -208,7 +209,7 @@ class TTSService(AIService):
         # if True, TTSService will push TTSStoppedFrames, otherwise subclass must do it
         push_stop_frames: bool = False,
         # if push_stop_frames is True, wait for this idle period before pushing TTSStoppedFrame
-        stop_frame_timeout_s: float = 1.0,
+        stop_frame_timeout_s: float = 2.0,
         # if True, TTSService will push silence audio frames after TTSStoppedFrame
         push_silence_after_stop: bool = False,
         # if push_silence_after_stop is True, send this amount of audio silence

src/pipecat/services/deepgram.py

@@ -5,7 +5,7 @@
 #
 
 import asyncio
-from typing import AsyncGenerator, Optional
+from typing import AsyncGenerator, Dict, Optional
 
 from loguru import logger
 
@@ -34,6 +34,7 @@ try:
         AsyncListenWebSocketClient,
         DeepgramClient,
         DeepgramClientOptions,
+        ErrorResponse,
         LiveOptions,
         LiveResultResponse,
         LiveTranscriptionEvents,
@@ -120,6 +121,7 @@ class DeepgramSTTService(STTService):
         url: str = "",
         sample_rate: Optional[int] = None,
         live_options: Optional[LiveOptions] = None,
+        addons: Optional[Dict] = None,
         **kwargs,
     ):
         super().__init__(sample_rate=sample_rate, **kwargs)
@@ -127,7 +129,7 @@ class DeepgramSTTService(STTService):
         default_options = LiveOptions(
             encoding="linear16",
             language=Language.EN,
-            model="nova-2-general",
+            model="nova-3-general",
             channels=1,
             interim_results=True,
             smart_format=True,
@@ -147,6 +149,7 @@ class DeepgramSTTService(STTService):
             merged_options.language = merged_options.language.value
 
         self._settings = merged_options.to_dict()
+        self._addons = addons
 
         self._client = DeepgramClient(
             api_key,
@@ -155,13 +158,10 @@ class DeepgramSTTService(STTService):
                 options={"keepalive": "true"},  # verbose=logging.DEBUG
             ),
         )
-        self._connection: AsyncListenWebSocketClient = self._client.listen.asyncwebsocket.v("1")
-        self._connection.on(LiveTranscriptionEvents.Transcript, self._on_message)
+
         if self.vad_enabled:
             self._register_event_handler("on_speech_started")
             self._register_event_handler("on_utterance_end")
-            self._connection.on(LiveTranscriptionEvents.SpeechStarted, self._on_speech_started)
-            self._connection.on(LiveTranscriptionEvents.UtteranceEnd, self._on_utterance_end)
 
     @property
     def vad_enabled(self):
@@ -202,7 +202,25 @@ class DeepgramSTTService(STTService):
 
     async def _connect(self):
         logger.debug("Connecting to Deepgram")
-        if not await self._connection.start(self._settings):
+
+        self._connection: AsyncListenWebSocketClient = self._client.listen.asyncwebsocket.v("1")
+
+        self._connection.on(
+            LiveTranscriptionEvents(LiveTranscriptionEvents.Transcript), self._on_message
+        )
+        self._connection.on(LiveTranscriptionEvents(LiveTranscriptionEvents.Error), self._on_error)
+
+        if self.vad_enabled:
+            self._connection.on(
+                LiveTranscriptionEvents(LiveTranscriptionEvents.SpeechStarted),
+                self._on_speech_started,
+            )
+            self._connection.on(
+                LiveTranscriptionEvents(LiveTranscriptionEvents.UtteranceEnd),
+                self._on_utterance_end,
+            )
+
+        if not await self._connection.start(options=self._settings, addons=self._addons):
             logger.error(f"{self}: unable to connect to Deepgram")
 
     async def _disconnect(self):
@@ -214,6 +232,15 @@ class DeepgramSTTService(STTService):
         await self.start_ttfb_metrics()
         await self.start_processing_metrics()
 
+    async def _on_error(self, *args, **kwargs):
+        error: ErrorResponse = kwargs["error"]
+        logger.warning(f"{self} connection error, will retry: {error}")
+        await self.stop_all_metrics()
+        # NOTE(aleix): we don't disconnect (i.e. call finish on the connection)
+        # because this triggers more errors internally in the Deepgram SDK. So,
+        # we just forget about the previous connection and create a new one.
+        await self._connect()
+
     async def _on_speech_started(self, *args, **kwargs):
         await self.start_metrics()
         await self._call_event_handler("on_speech_started", *args, **kwargs)

src/pipecat/services/elevenlabs.py

@@ -191,7 +191,6 @@ class ElevenLabsTTSService(WordTTSService, WebsocketService):
             aggregate_sentences=True,
             push_text_frames=False,
             push_stop_frames=True,
-            stop_frame_timeout_s=2.0,
             pause_frame_processing=True,
             sample_rate=sample_rate,
             **kwargs,

src/pipecat/services/fish.py

@@ -11,16 +11,13 @@ from loguru import logger
 from pydantic import BaseModel
 
 from pipecat.frames.frames import (
-    BotStoppedSpeakingFrame,
     CancelFrame,
     EndFrame,
     ErrorFrame,
     Frame,
-    LLMFullResponseEndFrame,
     StartFrame,
     StartInterruptionFrame,
     TTSAudioRawFrame,
-    TTSSpeakFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
 )
@@ -60,7 +57,12 @@ class FishAudioTTSService(TTSService, WebsocketService):
         params: InputParams = InputParams(),
         **kwargs,
     ):
-        super().__init__(pause_frame_processing=True, sample_rate=sample_rate, **kwargs)
+        super().__init__(
+            push_stop_frames=True,
+            pause_frame_processing=True,
+            sample_rate=sample_rate,
+            **kwargs,
+        )
 
         self._api_key = api_key
         self._base_url = "wss://api.fish.audio/v1/tts/live"

src/pipecat/services/openai.py

@@ -266,7 +266,6 @@ class BaseOpenAILLMService(LLMService):
                 if tool_call.function and tool_call.function.name:
                     function_name += tool_call.function.name
                     tool_call_id = tool_call.id
-                    await self.call_start_function(context, function_name)
                 if tool_call.function and tool_call.function.arguments:
                     # Keep iterating through the response to collect all the argument fragments
                     arguments += tool_call.function.arguments

src/pipecat/services/rime.py

@@ -14,16 +14,13 @@ from loguru import logger
 from pydantic import BaseModel
 
 from pipecat.frames.frames import (
-    BotStoppedSpeakingFrame,
     CancelFrame,
     EndFrame,
     ErrorFrame,
     Frame,
-    LLMFullResponseEndFrame,
     StartFrame,
     StartInterruptionFrame,
     TTSAudioRawFrame,
-    TTSSpeakFrame,
     TTSStartedFrame,
     TTSStoppedFrame,
 )
@@ -100,7 +97,6 @@ class RimeTTSService(AudioContextWordTTSService, WebsocketService):
             aggregate_sentences=True,
             push_text_frames=False,
             push_stop_frames=True,
-            stop_frame_timeout_s=2.0,
             pause_frame_processing=True,
             sample_rate=sample_rate,
             **kwargs,

src/pipecat/services/websocket_service.py

@@ -13,6 +13,7 @@ from loguru import logger
 from websockets.protocol import State
 
 from pipecat.frames.frames import ErrorFrame
+from pipecat.utils.network import exponential_backoff_time
 
 
 class WebsocketService(ABC):
@@ -51,27 +52,6 @@ class WebsocketService(ABC):
         await self._connect_websocket()
         return await self._verify_connection()
 
-    def _calculate_wait_time(
-        self, attempt: int, min_wait: float = 4, max_wait: float = 10, multiplier: float = 1
-    ) -> float:
-        """Calculate exponential backoff wait time.
-
-        Args:
-            attempt: Current attempt number (1-based)
-            min_wait: Minimum wait time in seconds
-            max_wait: Maximum wait time in seconds
-            multiplier: Base multiplier for exponential calculation
-
-        Returns:
-            Wait time in seconds
-        """
-        try:
-            exp = 2 ** (attempt - 1) * multiplier
-            result = max(0, min(exp, max_wait))
-            return max(min_wait, result)
-        except (ValueError, ArithmeticError):
-            return max_wait
-
     async def _receive_task_handler(self, report_error: Callable[[ErrorFrame], Awaitable[None]]):
         """Handles WebSocket message receiving with automatic retry logic.
 
@@ -104,7 +84,7 @@ class WebsocketService(ABC):
                 try:
                     if await self._reconnect_websocket(retry_count):
                         retry_count = 0  # Reset counter on successful reconnection
-                    wait_time = self._calculate_wait_time(retry_count)
+                    wait_time = exponential_backoff_time(retry_count)
                     await asyncio.sleep(wait_time)
                 except Exception as reconnect_error:
                     logger.error(f"{self} reconnection failed: {reconnect_error}")

src/pipecat/transports/base_input.py

@@ -174,11 +174,9 @@ class BaseInputTransport(FrameProcessor):
     async def _vad_analyze(self, audio_frame: InputAudioRawFrame) -> VADState:
         state = VADState.QUIET
         if self.vad_analyzer:
-            logger.trace(f"{self}: analyzing VAD on {audio_frame}")
             state = await self.get_event_loop().run_in_executor(
                 self._executor, self.vad_analyzer.analyze_audio, audio_frame.audio
             )
-            logger.trace(f"{self}: done analyzing VAD on {audio_frame}")
         return state
 
     async def _handle_vad(self, audio_frame: InputAudioRawFrame, vad_state: VADState):

src/pipecat/transports/services/daily.py

@@ -329,6 +329,10 @@ class DailyTransportClient(EventHandler):
     def _speaker_name(self):
         return f"speaker-{self}"
 
+    @property
+    def room_url(self) -> str:
+        return self._room_url
+
     @property
     def participant_id(self) -> str:
         return self._participant_id
@@ -1112,6 +1116,10 @@ class DailyTransport(BaseTransport):
     # DailyTransport
     #
 
+    @property
+    def room_url(self) -> str:
+        return self._client.room_url
+
     @property
     def participant_id(self) -> str:
         return self._client.participant_id

src/pipecat/utils/network.py

@@ -0,0 +1,27 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+
+def exponential_backoff_time(
+    attempt: int, min_wait: float = 4, max_wait: float = 10, multiplier: float = 1
+) -> float:
+    """Calculate exponential backoff wait time.
+
+    Args:
+        attempt: Current attempt number (1-based)
+        min_wait: Minimum wait time in seconds
+        max_wait: Maximum wait time in seconds
+        multiplier: Base multiplier for exponential calculation
+
+    Returns:
+        Wait time in seconds
+    """
+    try:
+        exp = 2 ** (attempt - 1) * multiplier
+        result = max(0, min(exp, max_wait))
+        return max(min_wait, result)
+    except (ValueError, ArithmeticError):
+        return max_wait

tests/test_stt_mute_filter.py

@@ -11,12 +11,13 @@ from pipecat.frames.frames import (
     BotStoppedSpeakingFrame,
     FunctionCallInProgressFrame,
     FunctionCallResultFrame,
+    InputAudioRawFrame,
     STTMuteFrame,
     UserStartedSpeakingFrame,
     UserStoppedSpeakingFrame,
 )
 from pipecat.processors.filters.stt_mute_filter import STTMuteConfig, STTMuteFilter, STTMuteStrategy
-from pipecat.tests.utils import run_test
+from pipecat.tests.utils import SleepFrame, run_test
 
 
 class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase):
@@ -26,10 +27,14 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase):
         frames_to_send = [
             BotStartedSpeakingFrame(),  # First bot speech starts
             UserStartedSpeakingFrame(),  # Should be suppressed
+            InputAudioRawFrame(
+                audio=b"", sample_rate=16000, num_channels=1
+            ),  # Should be suppressed
             UserStoppedSpeakingFrame(),  # Should be suppressed
             BotStoppedSpeakingFrame(),  # First bot speech ends
             BotStartedSpeakingFrame(),  # Second bot speech
             UserStartedSpeakingFrame(),  # Should pass through
+            InputAudioRawFrame(audio=b"", sample_rate=16000, num_channels=1),  # Should pass through
             UserStoppedSpeakingFrame(),  # Should pass through
             BotStoppedSpeakingFrame(),
         ]
@@ -41,6 +46,7 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase):
             STTMuteFrame,  # mute=False
             BotStartedSpeakingFrame,
             UserStartedSpeakingFrame,  # Now passes through
+            InputAudioRawFrame,  # Now passes through
             UserStoppedSpeakingFrame,  # Now passes through
             BotStoppedSpeakingFrame,
         ]
@@ -57,12 +63,19 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase):
         frames_to_send = [
             BotStartedSpeakingFrame(),  # First speech starts
             UserStartedSpeakingFrame(),  # Should be suppressed
+            InputAudioRawFrame(
+                audio=b"", sample_rate=16000, num_channels=1
+            ),  # Should be suppressed
             UserStoppedSpeakingFrame(),  # Should be suppressed
             BotStoppedSpeakingFrame(),  # First speech ends
             UserStartedSpeakingFrame(),  # Should pass through
+            InputAudioRawFrame(audio=b"", sample_rate=16000, num_channels=1),  # Should pass through
             UserStoppedSpeakingFrame(),  # Should pass through
             BotStartedSpeakingFrame(),  # Second speech starts
             UserStartedSpeakingFrame(),  # Should be suppressed again
+            InputAudioRawFrame(
+                audio=b"", sample_rate=16000, num_channels=1
+            ),  # Should be suppressed again
             UserStoppedSpeakingFrame(),  # Should be suppressed again
             BotStoppedSpeakingFrame(),  # Second speech ends
         ]
@@ -73,6 +86,7 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase):
             BotStoppedSpeakingFrame,
             STTMuteFrame,  # mute=False
             UserStartedSpeakingFrame,
+            InputAudioRawFrame,
             UserStoppedSpeakingFrame,
             BotStartedSpeakingFrame,
             STTMuteFrame,  # mute=True
@@ -134,15 +148,23 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase):
 
         frames_to_send = [
             UserStartedSpeakingFrame(),  # Should be suppressed (starts muted)
+            InputAudioRawFrame(
+                audio=b"", sample_rate=16000, num_channels=1
+            ),  # Should be suppressed
             UserStoppedSpeakingFrame(),  # Should be suppressed
             BotStartedSpeakingFrame(),  # First bot speech
             UserStartedSpeakingFrame(),  # Should be suppressed
+            InputAudioRawFrame(
+                audio=b"", sample_rate=16000, num_channels=1
+            ),  # Should be suppressed
             UserStoppedSpeakingFrame(),  # Should be suppressed
             BotStoppedSpeakingFrame(),  # First speech ends, unmutes
             UserStartedSpeakingFrame(),  # Should pass through
+            InputAudioRawFrame(audio=b"", sample_rate=16000, num_channels=1),  # Should pass through
             UserStoppedSpeakingFrame(),  # Should pass through
             BotStartedSpeakingFrame(),  # Second speech
             UserStartedSpeakingFrame(),  # Should pass through
+            InputAudioRawFrame(audio=b"", sample_rate=16000, num_channels=1),  # Should pass through
             UserStoppedSpeakingFrame(),  # Should pass through
             BotStoppedSpeakingFrame(),
         ]
@@ -153,9 +175,11 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase):
             BotStoppedSpeakingFrame,
             STTMuteFrame,  # mute=False after first speech
             UserStartedSpeakingFrame,
+            InputAudioRawFrame,
             UserStoppedSpeakingFrame,
             BotStartedSpeakingFrame,
             UserStartedSpeakingFrame,
+            InputAudioRawFrame,
             UserStoppedSpeakingFrame,
             BotStoppedSpeakingFrame,
         ]
@@ -190,23 +214,30 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase):
 
         frames_to_send = [
             UserStartedSpeakingFrame(),  # Should pass through
+            InputAudioRawFrame(audio=b"", sample_rate=16000, num_channels=1),  # Should pass through
             UserStoppedSpeakingFrame(),  # Should pass through
             BotStartedSpeakingFrame(),  # Bot starts speaking
             UserStartedSpeakingFrame(),  # Should be suppressed
+            InputAudioRawFrame(
+                audio=b"", sample_rate=16000, num_channels=1
+            ),  # Should be suppressed
             UserStoppedSpeakingFrame(),  # Should be suppressed
             BotStoppedSpeakingFrame(),  # Bot stops speaking
             UserStartedSpeakingFrame(),  # Should pass through
+            InputAudioRawFrame(audio=b"", sample_rate=16000, num_channels=1),  # Should pass through
             UserStoppedSpeakingFrame(),  # Should pass through
         ]
 
         expected_returned_frames = [
             UserStartedSpeakingFrame,
+            InputAudioRawFrame,
             UserStoppedSpeakingFrame,
             BotStartedSpeakingFrame,
             STTMuteFrame,  # mute=True
             BotStoppedSpeakingFrame,
             STTMuteFrame,  # mute=False
             UserStartedSpeakingFrame,
+            InputAudioRawFrame,
             UserStoppedSpeakingFrame,
         ]
 

tests/test_utils_network.py

@@ -0,0 +1,34 @@
+#
+# Copyright (c) 2024-2025 Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import unittest
+
+from pipecat.utils.network import exponential_backoff_time
+
+
+class TestUtilsNetwork(unittest.IsolatedAsyncioTestCase):
+    async def test_exponential_backoff_time(self):
+        # min_wait=4, max_wait=10, multiplier=1
+        assert exponential_backoff_time(attempt=1, min_wait=4, max_wait=10, multiplier=1) == 4
+        assert exponential_backoff_time(attempt=2, min_wait=4, max_wait=10, multiplier=1) == 4
+        assert exponential_backoff_time(attempt=3, min_wait=4, max_wait=10, multiplier=1) == 4
+        assert exponential_backoff_time(attempt=4, min_wait=4, max_wait=10, multiplier=1) == 8
+        assert exponential_backoff_time(attempt=5, min_wait=4, max_wait=10, multiplier=1) == 10
+        assert exponential_backoff_time(attempt=6, min_wait=4, max_wait=10, multiplier=1) == 10
+        # min_wait=1, max_wait=10, multiplier=1
+        assert exponential_backoff_time(attempt=1, min_wait=1, max_wait=10, multiplier=1) == 1
+        assert exponential_backoff_time(attempt=2, min_wait=1, max_wait=10, multiplier=1) == 2
+        assert exponential_backoff_time(attempt=3, min_wait=1, max_wait=10, multiplier=1) == 4
+        assert exponential_backoff_time(attempt=4, min_wait=1, max_wait=10, multiplier=1) == 8
+        assert exponential_backoff_time(attempt=5, min_wait=1, max_wait=10, multiplier=1) == 10
+        assert exponential_backoff_time(attempt=6, min_wait=1, max_wait=10, multiplier=1) == 10
+        # min_wait=1, max_wait=20, multiplier=2
+        assert exponential_backoff_time(attempt=1, min_wait=1, max_wait=20, multiplier=2) == 2
+        assert exponential_backoff_time(attempt=2, min_wait=1, max_wait=20, multiplier=2) == 4
+        assert exponential_backoff_time(attempt=3, min_wait=1, max_wait=20, multiplier=2) == 8
+        assert exponential_backoff_time(attempt=4, min_wait=1, max_wait=20, multiplier=2) == 16
+        assert exponential_backoff_time(attempt=5, min_wait=1, max_wait=20, multiplier=2) == 20
+        assert exponential_backoff_time(attempt=6, min_wait=1, max_wait=20, multiplier=2) == 20