Add flush_audio() to LMNTTTSService

Pipecat small fixes and refactored function calling examples

.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/

.pre-commit-config.yaml

@@ -1,7 +1,8 @@
 repos:
-  - repo: local
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.9.7
     hooks:
-      - id: ruff-format-hook
-        name: Check ruff formatting
-        entry: sh scripts/pre-commit.sh
-        language: system
+      - id: ruff
+        language_version: python3
+        args: [ --select,  I, ]
+      - id: ruff-format

CHANGELOG.md

@@ -5,6 +5,214 @@ 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 a `flush_audio()` method to `AzureTTSService`, `FishTTSService`,
+  `PlayHTTTSService`, and `LMNTTTSService`.
+
+- Added `set_language()` and `set_model()` to `AzureSTTService`,
+  `AssemblySTTService`, and `GladiaSTTService`.
+
+- Added `on_user_turn_audio_data` and `on_bot_turn_audio_data` to
+  `AudioBufferProcessor`. This gives the ability to grab the audio of only that
+  turn for both the user and the bot.
+
+- Added new base class `BaseObject` which is now the base class of
+  `FrameProcessor`, `PipelineRunner`, `PipelineTask` and `BaseTransport`. The
+  new `BaseObject` adds supports for event handlers.
+
+- Added support for a unified format for specifying function calling across all
+  LLM services.
+
+```python
+  weather_function = FunctionSchema(
+      name="get_current_weather",
+      description="Get the current weather",
+      properties={
+          "location": {
+              "type": "string",
+              "description": "The city and state, e.g. San Francisco, CA",
+          },
+          "format": {
+              "type": "string",
+              "enum": ["celsius", "fahrenheit"],
+              "description": "The temperature unit to use. Infer this from the user's location.",
+          },
+      },
+      required=["location"],
+  )
+  tools = ToolsSchema(standard_tools=[weather_function])
+```
+
+- Added `speech_threshold` parameter to `GladiaSTTService`.
+
+- Allow passing user (`user_kwargs`) and assistant (`assistant_kwargs`) context
+  aggregator parameters when using `create_context_aggregator()`. The values are
+  passed as a mapping that will then be converted to arguments.
+
+- Added `speed` as an `InputParam` for both `ElevenLabsTTSService` and
+  `ElevenLabsHttpTTSService`.
+
+- Added new `LLMFullResponseAggregator` to aggregate full LLM completions. At
+  every completion the `on_completion` event handler is triggered.
+
+- Added a new frame, `RTVIServerMessageFrame`, and RTVI message
+  `RTVIServerMessage` which provides a generic mechanism for sending custom
+  messages from server to client. The `RTVIServerMessageFrame` is processed by
+  the `RTVIObserver` and will be delivered to the client's `onServerMessage`
+  callback or `ServerMessage` event.
+
+- Added `GoogleLLMOpenAIBetaService` for Google LLM integration with an
+  OpenAI-compatible interface. Added foundational example
+  `14o-function-calling-gemini-openai-format.py`.
+
+- Added `AzureRealtimeBetaLLMService` to support Azure's OpeanAI Realtime API. Added
+  foundational example `19a-azure-realtime-beta.py`.
+
+### Changed
+
+- Moved `flush_audio()` from the `TTSService` base class to
+  `WebsocketTTSService`.
+
+### Fixed
+
+- Fixed an issue in `GoogleSTTService`, where it didn't have a `set_language`
+  function. This required a name change from `set_languages` to `set_language`.
+
+## [0.0.58] - 2025-02-26
+
+### Added
+
+- Added track-specific audio event `on_track_audio_data` to
+  `AudioBufferProcessor` for accessing separate input and output audio tracks.
+
+- Pipecat version will now be logged on every application startup. This will
+  help us identify what version we are running in case of any issues.
+
+- Added a new `StopFrame` which can be used to stop a pipeline task while
+  keeping the frame processors running. The frame processors could then be used
+  in a different pipeline. The difference between a `StopFrame` and a
+  `StopTaskFrame` is that, as with `EndFrame` and `EndTaskFrame`, the
+  `StopFrame` is pushed from the task and the `StopTaskFrame` is pushed upstream
+  inside the pipeline by any processor.
+
+- Added a new `PipelineTask` parameter `observers` that replaces the previous
+  `PipelineParams.observers`.
+
+- Added a new `PipelineTask` parameter `check_dangling_tasks` to enable or
+  disable checking for frame processors' dangling tasks when the Pipeline
+  finishes running.
+
+- Added new `on_completion_timeout` event for LLM services (all OpenAI-based
+  services, Anthropic and Google). Note that this event will only get triggered
+  if LLM timeouts are setup and if the timeout was reached. It can be useful to
+  retrigger another completion and see if the timeout was just a blip.
+
+- Added new log observers `LLMLogObserver` and `TranscriptionLogObserver` that
+  can be useful for debugging your pipelines.
+
+- Added `room_url` property to `DailyTransport`.
+
+- Added `addons` argument to `DeepgramSTTService`.
+
+- Added `exponential_backoff_time()` to `utils.network` module.
+
+### Changed
+
+- ⚠️ `PipelineTask` now requires keyword arguments (except for the first one for
+  the pipeline).
+
+- Updated `PlayHTHttpTTSService` to take a `voice_engine` and `protocol` input
+  in the constructor. The previous method of providing a `voice_engine` input
+  that contains the engine and protocol is deprecated by PlayHT.
+
+- The base `TTSService` class now strips leading newlines before sending text
+  to the TTS provider. This change is to solve issues where some TTS providers,
+  like Azure, would not output text due to newlines.
+
+- `GrokLLMSService` now uses `grok-2` as the default model.
+
+- `AnthropicLLMService` now uses `claude-3-7-sonnet-20250219` as the default
+  model.
+
+- `RimeHttpTTSService` needs an `aiohttp.ClientSession` to be passed to the
+  constructor as all the other HTTP-based services.
+
+- `RimeHttpTTSService` doesn't use a default voice anymore.
+
+- `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"))
+```
+
+### Deprecated
+
+- `PipelineParams.observers` is now deprecated, you the new `PipelineTask`
+  parameter `observers`.
+
+### Removed
+
+- Remove `TransportParams.audio_out_is_live` since it was not being used at all.
+
+### Fixed
+
+- Fixed a `GoogleLLMService` that was causing an exception when sending inline
+  audio in some cases.
+
+- Fixed an `AudioContextWordTTSService` issue that would cause an `EndFrame` to
+  disconnect from the TTS service before audio from all the contexts was
+  received. This affected services like Cartesia and Rime.
+
+- Fixed an issue that was not allowing to pass an `OpenAILLMContext` to create
+  `GoogleLLMService`'s context aggregators.
+
+- Fixed a `ElevenLabsTTSService`, `FishAudioTTSService`, `LMNTTTSService` and
+  `PlayHTTTSService` issue that was resulting in audio requested before an
+  interruption being played after an interruption.
+
+- Fixed `match_endofsentence` support for ellipses.
+
+- Fixed an issue that would cause undesired interruptions via
+  `EmulateUserStartedSpeakingFrame` when only interim transcriptions (i.e. no
+  final transcriptions) where received.
+
+- Fixed an issue where `EndTaskFrame` was not triggering
+  `on_client_disconnected` or closing the WebSocket in FastAPI.
+
+- Fixed an issue in `DeepgramSTTService` where the `sample_rate` passed to the
+  `LiveOptions` was not being used, causing the service to use the default
+  sample rate of pipeline.
+
+- Fixed a context aggregator issue that would not append the LLM text response
+  to the context if a function call happened in the same LLM turn.
+
+- Fixed an issue that was causing HTTP TTS services to push `TTSStoppedFrame`
+  more than once.
+
+- 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`.
+
+- Added foundational example `34-audio-recording.py` showing how to use the
+  AudioBufferProcessor callbacks to save merged and track recordings.
+
 ## [0.0.57] - 2025-02-14
 
 ### Added

dev-requirements.txt

@@ -3,10 +3,10 @@ coverage~=7.6.12
 grpcio-tools~=1.67.1
 pip-tools~=7.4.1
 pre-commit~=4.0.1
-pyright~=1.1.393
+pyright~=1.1.394
 pytest~=8.3.4
-pytest-asyncio~=0.25.2
-ruff~=0.9.5
+pytest-asyncio~=0.25.3
+ruff~=0.9.7
 setuptools~=70.0.0
 setuptools_scm~=8.1.0
 python-dotenv~=1.0.1

dot-env.template

@@ -18,6 +18,9 @@ AZURE_DALLE_API_KEY=...
 AZURE_DALLE_ENDPOINT=https://...
 AZURE_DALLE_MODEL=...
 
+# Cartesia
+CARTESIA_API_KEY=...
+
 # Daily
 DAILY_API_KEY=...
 DAILY_SAMPLE_ROOM_URL=https://...

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/bot-ready-signalling/server/signalling_bot.py

@@ -17,7 +17,7 @@ from runner import configure
 from pipecat.frames.frames import AudioRawFrame, EndFrame, OutputAudioRawFrame, TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.pipeline.task import PipelineTask
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 

examples/canonical-metrics/bot.py

@@ -113,13 +113,13 @@ async def main():
                 llm,
                 tts,
                 transport.output(),
-                audio_buffer_processor,  # captures audio into a buffer
                 canonical,  # uploads audio buffer to Canonical AI for metrics
+                audio_buffer_processor,  # captures audio into a buffer
                 context_aggregator.assistant(),
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):

examples/chatbot-audio-recording/bot.py

@@ -32,10 +32,16 @@ load_dotenv(override=True)
 logger.remove(0)
 logger.add(sys.stderr, level="DEBUG")
 
+# Create the recordings directory if it doesn't exist
+os.makedirs("recordings", exist_ok=True)
 
-async def save_audio(audio: bytes, sample_rate: int, num_channels: int):
+
+async def save_audio(audio: bytes, sample_rate: int, num_channels: int, name: str):
     if len(audio) > 0:
-        filename = f"conversation_recording{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.wav"
+        filename = os.path.join(
+            "recordings",
+            f"{name}_conversation_recording{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.wav",
+        )
         with io.BytesIO() as buffer:
             with wave.open(buffer, "wb") as wf:
                 wf.setsampwidth(2)
@@ -110,7 +116,7 @@ async def main():
 
         # NOTE: Watch out! This will save all the conversation in memory. You
         # can pass `buffer_size` to get periodic callbacks.
-        audiobuffer = AudioBufferProcessor()
+        audiobuffer = AudioBufferProcessor(enable_turn_audio=True)
 
         pipeline = Pipeline(
             [
@@ -124,11 +130,19 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
 
         @audiobuffer.event_handler("on_audio_data")
         async def on_audio_data(buffer, audio, sample_rate, num_channels):
-            await save_audio(audio, sample_rate, num_channels)
+            await save_audio(audio, sample_rate, num_channels, "full")
+
+        @audiobuffer.event_handler("on_user_turn_audio_data")
+        async def on_user_turn_audio_data(buffer, audio, sample_rate, num_channels):
+            await save_audio(audio, sample_rate, num_channels, "user")
+
+        @audiobuffer.event_handler("on_bot_turn_audio_data")
+        async def on_bot_turn_audio_data(buffer, audio, sample_rate, num_channels):
+            await save_audio(audio, sample_rate, num_channels, "bot")
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):

examples/deployment/flyio-example/bot.py

@@ -70,7 +70,7 @@ async def main(room_url: str, token: str):
         ]
     )
 
-    task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+    task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
 
     @transport.event_handler("on_first_participant_joined")
     async def on_first_participant_joined(transport, participant):

examples/deployment/modal-example/bot.py

@@ -62,7 +62,7 @@ async def main(room_url: str, token: str):
 
     task = PipelineTask(
         pipeline,
-        PipelineParams(
+        params=PipelineParams(
             allow_interruptions=True,
             enable_metrics=True,
             enable_usage_metrics=True,

examples/foundational/03a-local-still-frame.py

@@ -18,8 +18,7 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
 from pipecat.services.fal import FalImageGenService
-from pipecat.transports.base_transport import TransportParams
-from pipecat.transports.local.tk import TkLocalTransport
+from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams
 
 load_dotenv(override=True)
 
@@ -34,7 +33,9 @@ async def main():
 
         transport = TkLocalTransport(
             tk_root,
-            TransportParams(camera_out_enabled=True, camera_out_width=1024, camera_out_height=1024),
+            TkTransportParams(
+                camera_out_enabled=True, camera_out_width=1024, camera_out_height=1024
+            ),
         )
 
         imagegen = FalImageGenService(

examples/foundational/03b-still-frame-imagen.py

@@ -44,7 +44,8 @@ async def main():
         runner = PipelineRunner()
 
         task = PipelineTask(
-            Pipeline([imagegen, transport.output()]), PipelineParams(enable_metrics=True)
+            Pipeline([imagegen, transport.output()]),
+            params=PipelineParams(enable_metrics=True),
         )
 
         @transport.event_handler("on_first_participant_joined")

examples/foundational/05a-local-sync-speech-and-image.py

@@ -30,8 +30,7 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.services.cartesia import CartesiaHttpTTSService
 from pipecat.services.fal import FalImageGenService
 from pipecat.services.openai import OpenAILLMService
-from pipecat.transports.base_transport import TransportParams
-from pipecat.transports.local.tk import TkLocalTransport, TkOutputTransport
+from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams
 
 load_dotenv(override=True)
 
@@ -152,7 +151,7 @@ async def main():
 
         transport = TkLocalTransport(
             tk_root,
-            TransportParams(
+            TkTransportParams(
                 audio_out_enabled=True,
                 camera_out_enabled=True,
                 camera_out_width=1024,

examples/foundational/06-listen-and-respond.py

@@ -105,7 +105,10 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(enable_metrics=True, enable_usage_metrics=True),
+            params=PipelineParams(
+                enable_metrics=True,
+                enable_usage_metrics=True,
+            ),
         )
 
         @transport.event_handler("on_first_participant_joined")

examples/foundational/06a-image-sync.py

@@ -127,7 +127,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07-interruptible-vad.py

@@ -76,7 +76,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07-interruptible.py

@@ -74,7 +74,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07a-interruptible-anthropic.py

@@ -79,7 +79,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07b-interruptible-langchain.py

@@ -103,7 +103,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07c-interruptible-deepgram-vad.py

@@ -81,7 +81,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07c-interruptible-deepgram.py

@@ -9,7 +9,6 @@ import os
 import sys
 
 import aiohttp
-from deepgram import LiveOptions
 from dotenv import load_dotenv
 from loguru import logger
 from runner import configure
@@ -45,23 +44,7 @@ async def main():
             ),
         )
 
-        # stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
-        stt = DeepgramSTTService(
-            api_key=os.getenv("DEEPGRAM_API_KEY"),
-            # url=deepgram_url,
-            live_options=LiveOptions(
-                encoding="linear16",
-                language="en-US",
-                model="nova-3",
-                channels=1,
-                interim_results=True,
-                # smart_format=smart_format,
-                # endpointing=endpointing,
-                vad_events=True,
-                diarize=True,
-                filler_words=True,
-            ),
-        )
+        stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
 
         tts = DeepgramTTSService(api_key=os.getenv("DEEPGRAM_API_KEY"), voice="aura-helios-en")
 
@@ -91,7 +74,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07d-interruptible-elevenlabs-http.py

@@ -0,0 +1,103 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+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.services.elevenlabs import ElevenLabsHttpTTSService
+from pipecat.services.openai import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                transcription_enabled=True,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+        tts = ElevenLabsHttpTTSService(
+            api_key=os.getenv("ELEVENLABS_API_KEY", ""),
+            voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
+            aiohttp_session=session,
+        )
+
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
+
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                context_aggregator.user(),  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            params=PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_transcription(participant["id"])
+            # 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_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/foundational/07d-interruptible-elevenlabs.py

@@ -74,7 +74,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07e-interruptible-playht-http.py

@@ -75,7 +75,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07e-interruptible-playht.py

@@ -77,7 +77,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07f-interruptible-azure.py

@@ -83,7 +83,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07g-interruptible-openai.py

@@ -81,7 +81,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07h-interruptible-openpipe.py

@@ -81,7 +81,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07i-interruptible-xtts.py

@@ -75,7 +75,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07j-interruptible-gladia.py

@@ -21,6 +21,7 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.services.cartesia import CartesiaTTSService
 from pipecat.services.gladia import GladiaSTTService
 from pipecat.services.openai import OpenAILLMService
+from pipecat.transcriptions.language import Language
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
 load_dotenv(override=True)
@@ -80,7 +81,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07k-interruptible-lmnt.py

@@ -71,7 +71,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07l-interruptible-together.py

@@ -88,7 +88,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07m-interruptible-polly.py

@@ -81,7 +81,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07n-interruptible-google.py

@@ -79,7 +79,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07o-interruptible-assemblyai.py

@@ -80,7 +80,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07p-interruptible-krisp.py

@@ -76,7 +76,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07q-interruptible-rime-http.py

@@ -0,0 +1,103 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+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.services.openai import OpenAILLMService
+from pipecat.services.rime import RimeHttpTTSService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                transcription_enabled=True,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+        tts = RimeHttpTTSService(
+            api_key=os.getenv("RIME_API_KEY", ""),
+            voice_id="rex",
+            aiohttp_session=session,
+        )
+
+        llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
+
+        messages = [
+            {
+                "role": "system",
+                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+            },
+        ]
+
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                context_aggregator.user(),  # User responses
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            params=PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                report_only_initial_ttfb=True,
+            ),
+        )
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_transcription(participant["id"])
+            # 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_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.cancel()
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/foundational/07q-interruptible-rime.py

@@ -74,7 +74,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07r-interruptible-riva-nim.py

@@ -74,7 +74,7 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):

examples/foundational/07s-interruptible-google-audio-in.py

@@ -251,7 +251,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/07t-interruptible-fish.py

@@ -74,7 +74,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/09-mirror.py

@@ -78,7 +78,11 @@ async def main():
         runner = PipelineRunner()
 
         task = PipelineTask(
-            pipeline, PipelineParams(audio_in_sample_rate=24000, audio_out_sample_rate=24000)
+            pipeline,
+            params=PipelineParams(
+                audio_in_sample_rate=24000,
+                audio_out_sample_rate=24000,
+            ),
         )
 
         await runner.run(task)

examples/foundational/09a-local-mirror.py

@@ -24,8 +24,7 @@ from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
-from pipecat.transports.base_transport import TransportParams
-from pipecat.transports.local.tk import TkLocalTransport
+from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams
 from pipecat.transports.services.daily import DailyParams, DailyTransport
 
 load_dotenv(override=True)
@@ -67,7 +66,7 @@ async def main():
 
         tk_transport = TkLocalTransport(
             tk_root,
-            TransportParams(
+            TkTransportParams(
                 audio_out_enabled=True,
                 camera_out_enabled=True,
                 camera_out_is_live=True,
@@ -83,7 +82,11 @@ async def main():
         pipeline = Pipeline([daily_transport.input(), MirrorProcessor(), tk_transport.output()])
 
         task = PipelineTask(
-            pipeline, PipelineParams(audio_in_sample_rate=24000, audio_out_sample_rate=24000)
+            pipeline,
+            params=PipelineParams(
+                audio_in_sample_rate=24000,
+                audio_out_sample_rate=24000,
+            ),
         )
 
         async def run_tk():

examples/foundational/10-wake-phrase.py

@@ -76,7 +76,7 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):

examples/foundational/14-function-calling.py

@@ -11,9 +11,10 @@ import sys
 import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
-from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
@@ -65,30 +66,24 @@ async def main():
         # sent to the same callback with an additional function_name parameter.
         llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
 
-        tools = [
-            ChatCompletionToolParam(
-                type="function",
-                function={
-                    "name": "get_current_weather",
-                    "description": "Get the current weather",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "location": {
-                                "type": "string",
-                                "description": "The city and state, e.g. San Francisco, CA",
-                            },
-                            "format": {
-                                "type": "string",
-                                "enum": ["celsius", "fahrenheit"],
-                                "description": "The temperature unit to use. Infer this from the users location.",
-                            },
-                        },
-                        "required": ["location", "format"],
-                    },
+        weather_function = FunctionSchema(
+            name="get_current_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
                 },
-            )
-        ]
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
+                },
+            },
+            required=["location", "format"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function])
+
         messages = [
             {
                 "role": "system",
@@ -112,7 +107,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/14a-function-calling-anthropic.py

@@ -13,6 +13,8 @@ from dotenv import load_dotenv
 from loguru import logger
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
@@ -59,22 +61,18 @@ async def main():
         )
         llm.register_function("get_weather", get_weather)
 
-        tools = [
-            {
-                "name": "get_weather",
-                "description": "Get the current weather in a given location",
-                "input_schema": {
-                    "type": "object",
-                    "properties": {
-                        "location": {
-                            "type": "string",
-                            "description": "The city and state, e.g. San Francisco, CA",
-                        }
-                    },
-                    "required": ["location"],
+        weather_function = FunctionSchema(
+            name="get_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
                 },
-            }
-        ]
+            },
+            required=["location"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function])
 
         # todo: test with very short initial user message
 
@@ -99,7 +97,13 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
+        task = PipelineTask(
+            pipeline,
+            params=PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):

examples/foundational/14b-function-calling-anthropic-video.py

@@ -13,6 +13,8 @@ from dotenv import load_dotenv
 from loguru import logger
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
@@ -72,36 +74,29 @@ async def main():
         llm.register_function("get_weather", get_weather)
         llm.register_function("get_image", get_image)
 
-        tools = [
-            {
-                "name": "get_weather",
-                "description": "Get the current weather in a given location",
-                "input_schema": {
-                    "type": "object",
-                    "properties": {
-                        "location": {
-                            "type": "string",
-                            "description": "The city and state, e.g. San Francisco, CA",
-                        }
-                    },
-                    "required": ["location"],
+        weather_function = FunctionSchema(
+            name="get_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
                 },
             },
-            {
-                "name": "get_image",
-                "description": "Get an image from the video stream.",
-                "input_schema": {
-                    "type": "object",
-                    "properties": {
-                        "question": {
-                            "type": "string",
-                            "description": "The question that the user is asking about the image.",
-                        }
-                    },
-                    "required": ["question"],
-                },
+            required=["location"],
+        )
+        get_image_function = FunctionSchema(
+            name="get_image",
+            description="Get an image from the video stream.",
+            properties={
+                "question": {
+                    "type": "string",
+                    "description": "The question that the user is asking about the image.",
+                }
             },
-        ]
+            required=["question"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function, get_image_function])
 
         # todo: test with very short initial user message
 
@@ -153,7 +148,13 @@ If you need to use a tool, simply use the tool. Do not tell the user the tool yo
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
+        task = PipelineTask(
+            pipeline,
+            params=PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+            ),
+        )
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):

examples/foundational/14c-function-calling-together.py

@@ -11,9 +11,10 @@ import sys
 import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
-from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
@@ -69,30 +70,23 @@ async def main():
         # sent to the same callback with an additional function_name parameter.
         llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
 
-        tools = [
-            ChatCompletionToolParam(
-                type="function",
-                function={
-                    "name": "get_current_weather",
-                    "description": "Get the current weather",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "location": {
-                                "type": "string",
-                                "description": "The city and state, e.g. San Francisco, CA",
-                            },
-                            "format": {
-                                "type": "string",
-                                "enum": ["celsius", "fahrenheit"],
-                                "description": "The temperature unit to use. Infer this from the users location.",
-                            },
-                        },
-                        "required": ["location", "format"],
-                    },
+        weather_function = FunctionSchema(
+            name="get_current_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
                 },
-            )
-        ]
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
+                },
+            },
+            required=["location", "format"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function])
         messages = [
             {
                 "role": "system",

examples/foundational/14d-function-calling-video.py

@@ -11,9 +11,10 @@ import sys
 import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
-from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
@@ -66,47 +67,34 @@ async def main():
         llm.register_function("get_weather", get_weather)
         llm.register_function("get_image", get_image)
 
-        tools = [
-            ChatCompletionToolParam(
-                type="function",
-                function={
-                    "name": "get_weather",
-                    "description": "Get the current weather",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "location": {
-                                "type": "string",
-                                "description": "The city and state, e.g. San Francisco, CA",
-                            },
-                            "format": {
-                                "type": "string",
-                                "enum": ["celsius", "fahrenheit"],
-                                "description": "The temperature unit to use. Infer this from the users location.",
-                            },
-                        },
-                        "required": ["location", "format"],
-                    },
+        weather_function = FunctionSchema(
+            name="get_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
                 },
-            ),
-            ChatCompletionToolParam(
-                type="function",
-                function={
-                    "name": "get_image",
-                    "description": "Get an image from the video stream.",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "question": {
-                                "type": "string",
-                                "description": "The question to ask the AI to generate an image of",
-                            },
-                        },
-                        "required": ["question"],
-                    },
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
                 },
-            ),
-        ]
+            },
+            required=["location"],
+        )
+        get_image_function = FunctionSchema(
+            name="get_image",
+            description="Get an image from the video stream.",
+            properties={
+                "question": {
+                    "type": "string",
+                    "description": "The question that the user is asking about the image.",
+                }
+            },
+            required=["question"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function, get_image_function])
 
         system_prompt = """\
 You are a helpful assistant who converses with a user and answers questions. Respond concisely to general questions.

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

@@ -13,7 +13,10 @@ from dotenv import load_dotenv
 from loguru import logger
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 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 +33,12 @@ 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.")
@@ -63,48 +72,37 @@ 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 = [
-            {
-                "function_declarations": [
-                    {
-                        "name": "get_weather",
-                        "description": "Get the current weather",
-                        "parameters": {
-                            "type": "object",
-                            "properties": {
-                                "location": {
-                                    "type": "string",
-                                    "description": "The city and state, e.g. San Francisco, CA",
-                                },
-                                "format": {
-                                    "type": "string",
-                                    "enum": ["celsius", "fahrenheit"],
-                                    "description": "The temperature unit to use. Infer this from the users location.",
-                                },
-                            },
-                            "required": ["location", "format"],
-                        },
-                    },
-                    {
-                        "name": "get_image",
-                        "description": "Get and image from the camera or video stream.",
-                        "parameters": {
-                            "type": "object",
-                            "properties": {
-                                "question": {
-                                    "type": "string",
-                                    "description": "The question to to use when running inference on the acquired image.",
-                                },
-                            },
-                            "required": ["question"],
-                        },
-                    },
-                ]
-            }
-        ]
+        weather_function = FunctionSchema(
+            name="get_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
+                },
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
+                },
+            },
+            required=["location", "format"],
+        )
+        get_image_function = FunctionSchema(
+            name="get_image",
+            description="Get an image from the video stream.",
+            properties={
+                "question": {
+                    "type": "string",
+                    "description": "The question that the user is asking about the image.",
+                }
+            },
+            required=["question"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function, get_image_function])
 
         system_prompt = """\
 You are a helpful assistant who converses with a user and answers questions. Respond concisely to general questions.
@@ -145,7 +143,7 @@ indicate you should use the get_image tool are:
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/14f-function-calling-groq.py

@@ -11,9 +11,10 @@ import sys
 import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
-from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
@@ -68,30 +69,23 @@ async def main():
         # sent to the same callback with an additional function_name parameter.
         llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
 
-        tools = [
-            ChatCompletionToolParam(
-                type="function",
-                function={
-                    "name": "get_current_weather",
-                    "description": "Get the current weather",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "location": {
-                                "type": "string",
-                                "description": "The city and state, e.g. San Francisco, CA",
-                            },
-                            "unit": {
-                                "type": "string",
-                                "enum": ["celsius", "fahrenheit"],
-                                "description": "The temperature unit to use. Infer this from the users location.",
-                            },
-                        },
-                        "required": ["location"],
-                    },
+        weather_function = FunctionSchema(
+            name="get_current_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
                 },
-            )
-        ]
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
+                },
+            },
+            required=["location"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function])
         messages = [
             {
                 "role": "system",
@@ -116,7 +110,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/14g-function-calling-grok.py

@@ -11,9 +11,10 @@ import sys
 import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
-from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
@@ -66,30 +67,23 @@ async def main():
         # sent to the same callback with an additional function_name parameter.
         llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
 
-        tools = [
-            ChatCompletionToolParam(
-                type="function",
-                function={
-                    "name": "get_current_weather",
-                    "description": "Get the current weather",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "location": {
-                                "type": "string",
-                                "description": "The city and state, e.g. San Francisco, CA",
-                            },
-                            "format": {
-                                "type": "string",
-                                "enum": ["celsius", "fahrenheit"],
-                                "description": "The temperature unit to use. Infer this from the users location.",
-                            },
-                        },
-                        "required": ["location", "format"],
-                    },
+        weather_function = FunctionSchema(
+            name="get_current_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
                 },
-            )
-        ]
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
+                },
+            },
+            required=["location", "format"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function])
         messages = [
             {
                 "role": "system",
@@ -113,7 +107,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/14h-function-calling-azure.py

@@ -11,9 +11,10 @@ import sys
 import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
-from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
@@ -70,30 +71,23 @@ async def main():
         # sent to the same callback with an additional function_name parameter.
         llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
 
-        tools = [
-            ChatCompletionToolParam(
-                type="function",
-                function={
-                    "name": "get_current_weather",
-                    "description": "Get the current weather",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "location": {
-                                "type": "string",
-                                "description": "The city and state, e.g. San Francisco, CA",
-                            },
-                            "format": {
-                                "type": "string",
-                                "enum": ["celsius", "fahrenheit"],
-                                "description": "The temperature unit to use. Infer this from the users location.",
-                            },
-                        },
-                        "required": ["location", "format"],
-                    },
+        weather_function = FunctionSchema(
+            name="get_current_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
                 },
-            )
-        ]
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
+                },
+            },
+            required=["location", "format"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function])
         messages = [
             {
                 "role": "system",
@@ -117,7 +111,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/14i-function-calling-fireworks.py

@@ -11,9 +11,10 @@ import sys
 import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
-from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
@@ -69,30 +70,23 @@ async def main():
         # sent to the same callback with an additional function_name parameter.
         llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
 
-        tools = [
-            ChatCompletionToolParam(
-                type="function",
-                function={
-                    "name": "get_current_weather",
-                    "description": "Get the current weather",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "location": {
-                                "type": "string",
-                                "description": "The city and state, e.g. San Francisco, CA",
-                            },
-                            "format": {
-                                "type": "string",
-                                "enum": ["celsius", "fahrenheit"],
-                                "description": "The temperature unit to use. Infer this from the users location.",
-                            },
-                        },
-                        "required": ["location", "format"],
-                    },
+        weather_function = FunctionSchema(
+            name="get_current_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
                 },
-            )
-        ]
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
+                },
+            },
+            required=["location", "format"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function])
         messages = [
             {
                 "role": "system",
@@ -116,7 +110,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/14j-function-calling-nim.py

@@ -11,9 +11,10 @@ import sys
 import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
-from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
@@ -69,30 +70,23 @@ async def main():
         # sent to the same callback with an additional function_name parameter.
         llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
 
-        tools = [
-            ChatCompletionToolParam(
-                type="function",
-                function={
-                    "name": "get_current_weather",
-                    "description": "Returns the current weather at a location, if one is specified, and defaults to the user's location.",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "location": {
-                                "type": "string",
-                                "description": "The location to find the weather of, or if not provided, it's the default location.",
-                            },
-                            "format": {
-                                "type": "string",
-                                "enum": ["celsius", "fahrenheit"],
-                                "description": "Whether to use SI or USCS units (celsius or fahrenheit).",
-                            },
-                        },
-                        "required": ["location", "format"],
-                    },
+        weather_function = FunctionSchema(
+            name="get_current_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
                 },
-            )
-        ]
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
+                },
+            },
+            required=["location", "format"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function])
         messages = [
             {
                 "role": "system",
@@ -116,7 +110,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/14k-function-calling-cerebras.py

@@ -11,9 +11,10 @@ import sys
 import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
-from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
@@ -66,30 +67,23 @@ async def main():
         # sent to the same callback with an additional function_name parameter.
         llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
 
-        tools = [
-            ChatCompletionToolParam(
-                type="function",
-                function={
-                    "name": "get_current_weather",
-                    "description": "Get the current weather for a specific location. You MUST use this function whenever asked about weather.",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "location": {
-                                "type": "string",
-                                "description": "The city and state, e.g. San Francisco, CA",
-                            },
-                            "format": {
-                                "type": "string",
-                                "enum": ["celsius", "fahrenheit"],
-                                "description": "The temperature unit to use. Use fahrenheit for US locations, celsius for others.",
-                            },
-                        },
-                        "required": ["location", "format"],
-                    },
+        weather_function = FunctionSchema(
+            name="get_current_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
                 },
-            )
-        ]
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
+                },
+            },
+            required=["location", "format"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function])
         messages = [
             {
                 "role": "system",
@@ -123,7 +117,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/14l-function-calling-deepseek.py

@@ -11,9 +11,10 @@ import sys
 import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
-from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
@@ -66,30 +67,23 @@ async def main():
         # sent to the same callback with an additional function_name parameter.
         llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
 
-        tools = [
-            ChatCompletionToolParam(
-                type="function",
-                function={
-                    "name": "get_current_weather",
-                    "description": "Get the current weather for a specific location. You MUST use this function whenever asked about weather.",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "location": {
-                                "type": "string",
-                                "description": "The city and state, e.g. San Francisco, CA",
-                            },
-                            "format": {
-                                "type": "string",
-                                "enum": ["celsius", "fahrenheit"],
-                                "description": "The temperature unit to use. Use fahrenheit for US locations, celsius for others.",
-                            },
-                        },
-                        "required": ["location", "format"],
-                    },
+        weather_function = FunctionSchema(
+            name="get_current_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
                 },
-            )
-        ]
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
+                },
+            },
+            required=["location", "format"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function])
         messages = [
             {
                 "role": "system",
@@ -123,7 +117,7 @@ Start by asking me for my location. Then, use 'get_weather_current' to give me a
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/14m-function-calling-openrouter.py

@@ -11,9 +11,10 @@ import sys
 import aiohttp
 from dotenv import load_dotenv
 from loguru import logger
-from openai.types.chat import ChatCompletionToolParam
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.frames.frames import TTSSpeakFrame
 from pipecat.pipeline.pipeline import Pipeline
@@ -70,30 +71,23 @@ async def main():
         # sent to the same callback with an additional function_name parameter.
         llm.register_function(None, fetch_weather_from_api, start_callback=start_fetch_weather)
 
-        tools = [
-            ChatCompletionToolParam(
-                type="function",
-                function={
-                    "name": "get_current_weather",
-                    "description": "Get the current weather",
-                    "parameters": {
-                        "type": "object",
-                        "properties": {
-                            "location": {
-                                "type": "string",
-                                "description": "The city and state, e.g. San Francisco, CA",
-                            },
-                            "format": {
-                                "type": "string",
-                                "enum": ["celsius", "fahrenheit"],
-                                "description": "The temperature unit to use. Infer this from the users location.",
-                            },
-                        },
-                        "required": ["location", "format"],
-                    },
+        weather_function = FunctionSchema(
+            name="get_current_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
                 },
-            )
-        ]
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
+                },
+            },
+            required=["location", "format"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function])
         messages = [
             {
                 "role": "system",
@@ -117,7 +111,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/14n-function-calling-perplexity.py

@@ -83,7 +83,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/14o-function-calling-gemini-openai-format.py

@@ -0,0 +1,131 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import ToolsSchema
+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
+from pipecat.services.elevenlabs import ElevenLabsTTSService
+from pipecat.services.google import GoogleLLMOpenAIBetaService
+from pipecat.services.openai import OpenAILLMContext
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+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 fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    await result_callback({"conditions": "nice", "temperature": "75"})
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                transcription_enabled=True,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+        tts = ElevenLabsTTSService(
+            api_key=os.getenv("ELEVENLABS_API_KEY", ""),
+            voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
+        )
+
+        llm = GoogleLLMOpenAIBetaService(api_key=os.getenv("GEMINI_API_KEY"))
+        # Register a function_name of None to get all functions
+        # sent to the same callback with an additional function_name parameter.
+        llm.register_function(
+            "get_current_weather", fetch_weather_from_api, start_callback=start_fetch_weather
+        )
+
+        weather_function = FunctionSchema(
+            name="get_current_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
+                },
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
+                },
+            },
+            required=["location", "format"],
+        )
+        tools = ToolsSchema(standard_tools=[weather_function])
+        messages = [
+            {
+                "role": "user",
+                "content": "Start a conversation with 'Hey there' to get the current weather.",
+            },
+        ]
+
+        context = OpenAILLMContext(messages, tools)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                context_aggregator.user(),
+                llm,
+                tts,
+                transport.output(),
+                context_aggregator.assistant(),
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            params=PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+            ),
+        )
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_transcription(participant["id"])
+            # Kick off the conversation.
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/foundational/15-switch-voices.py

@@ -133,7 +133,7 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):

examples/foundational/15a-switch-languages.py

@@ -126,7 +126,7 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):

examples/foundational/16-gpu-container-local-bot.py

@@ -85,7 +85,13 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
+        task = PipelineTask(
+            pipeline,
+            params=PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+            ),
+        )
 
         # When a participant joins, start transcription for that participant so the
         # bot can "hear" and respond to them.

examples/foundational/17-detect-user-idle.py

@@ -108,7 +108,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 report_only_initial_ttfb=True,

examples/foundational/18-gstreamer-filesrc.py

@@ -38,7 +38,6 @@ async def main():
             "GStreamer",
             DailyParams(
                 audio_out_enabled=True,
-                audio_out_is_live=True,
                 camera_out_enabled=True,
                 camera_out_width=1280,
                 camera_out_height=720,

examples/foundational/19-openai-realtime-beta.py

@@ -154,7 +154,7 @@ Remember, your responses should be short. Just one or two sentences, usually."""
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/19a-azure-realtime-beta.py

@@ -0,0 +1,179 @@
+#
+# Copyright (c) 2024–2025, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+from datetime import datetime
+
+import aiohttp
+import websockets
+from dotenv import load_dotenv
+from loguru import logger
+from runner import configure
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.audio.vad.vad_analyzer import VADParams
+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.services.openai_realtime_beta import (
+    AzureRealtimeBetaLLMService,
+    InputAudioTranscription,
+    SessionProperties,
+    TurnDetection,
+)
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
+    temperature = 75 if args["format"] == "fahrenheit" else 24
+    await result_callback(
+        {
+            "conditions": "nice",
+            "temperature": temperature,
+            "format": args["format"],
+            "timestamp": datetime.now().strftime("%Y%m%d_%H%M%S"),
+        }
+    )
+
+
+tools = [
+    {
+        "type": "function",
+        "name": "get_current_weather",
+        "description": "Get the current weather",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
+                },
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the users location.",
+                },
+            },
+            "required": ["location", "format"],
+        },
+    }
+]
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_in_enabled=True,
+                audio_out_enabled=True,
+                transcription_enabled=False,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.8)),
+                vad_audio_passthrough=True,
+            ),
+        )
+
+        session_properties = SessionProperties(
+            input_audio_transcription=InputAudioTranscription(),
+            # Set openai TurnDetection parameters. Not setting this at all will turn it
+            # on by default
+            # turn_detection=TurnDetection(silence_duration_ms=1000),
+            # Or set to False to disable openai turn detection and use transport VAD
+            # turn_detection=False,
+            # tools=tools,
+            instructions="""Your knowledge cutoff is 2023-10. You are a helpful and friendly AI.
+
+Act like a human, but remember that you aren't a human and that you can't do human
+things in the real world. Your voice and personality should be warm and engaging, with a lively and
+playful tone.
+
+If interacting in a non-English language, start by using the standard accent or dialect familiar to
+the user. Talk quickly. You should always call a function if you can. Do not refer to these rules,
+even if you're asked about them.
+-
+You are participating in a voice conversation. Keep your responses concise, short, and to the point
+unless specifically asked to elaborate on a topic.
+
+Remember, your responses should be short. Just one or two sentences, usually.""",
+        )
+
+        llm = AzureRealtimeBetaLLMService(
+            api_key=os.getenv("AZURE_REALTIME_API_KEY"),
+            base_url=os.getenv("AZURE_REALTIME_BASE_URL"),
+            session_properties=session_properties,
+            start_audio_paused=False,
+        )
+
+        # you can either register a single function for all function calls, or specific functions
+        # llm.register_function(None, fetch_weather_from_api)
+        llm.register_function("get_current_weather", fetch_weather_from_api)
+
+        # Create a standard OpenAI LLM context object using the normal messages format. The
+        # OpenAIRealtimeBetaLLMService will convert this internally to messages that the
+        # openai WebSocket API can understand.
+        context = OpenAILLMContext(
+            [{"role": "user", "content": "Say hello!"}],
+            # [{"role": "user", "content": [{"type": "text", "text": "Say hello!"}]}],
+            #     [
+            #         {
+            #             "role": "user",
+            #             "content": [
+            #                 {"type": "text", "text": "Say"},
+            #                 {"type": "text", "text": "yo what's up!"},
+            #             ],
+            #         }
+            #     ],
+            tools,
+        )
+
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                context_aggregator.user(),
+                llm,  # LLM
+                context_aggregator.assistant(),
+                transport.output(),  # Transport bot output
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            params=PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+                # report_only_initial_ttfb=True,
+            ),
+        )
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_transcription(participant["id"])
+            # Kick off the conversation.
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/foundational/20a-persistent-context-openai.py

@@ -212,7 +212,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/20b-persistent-context-openai-realtime.py

@@ -237,7 +237,7 @@ Remember, your responses should be short. Just one or two sentences, usually."""
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/20c-persistent-context-anthropic.py

@@ -209,7 +209,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/20d-persistent-context-gemini.py

@@ -263,7 +263,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/21-tavus-layer.py

@@ -87,7 +87,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 # We just use 16000 because that's what Tavus is expecting and
                 # we avoid resampling.
                 audio_in_sample_rate=16000,

examples/foundational/22-natural-conversation.py

@@ -145,7 +145,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/22b-natural-conversation-proposal.py

@@ -138,6 +138,7 @@ class OutputGate(FrameProcessor):
         self._gate_open = start_open
         self._frames_buffer = []
         self._notifier = notifier
+        self._gate_task = None
 
     def close_gate(self):
         self._gate_open = False
@@ -178,10 +179,13 @@ class OutputGate(FrameProcessor):
 
     async def _start(self):
         self._frames_buffer = []
-        self._gate_task = self.create_task(self._gate_task_handler())
+        if not self._gate_task:
+            self._gate_task = self.create_task(self._gate_task_handler())
 
     async def _stop(self):
-        await self.cancel_task(self._gate_task)
+        if self._gate_task:
+            await self.cancel_task(self._gate_task)
+            self._gate_task = None
 
     async def _gate_task_handler(self):
         while True:
@@ -351,7 +355,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/22c-natural-conversation-mixed-llms.py

@@ -342,6 +342,7 @@ class OutputGate(FrameProcessor):
         self._gate_open = start_open
         self._frames_buffer = []
         self._notifier = notifier
+        self._gate_task = None
 
     def close_gate(self):
         self._gate_open = False
@@ -382,10 +383,13 @@ class OutputGate(FrameProcessor):
 
     async def _start(self):
         self._frames_buffer = []
-        self._gate_task = self.create_task(self._gate_task_handler())
+        if not self._gate_task:
+            self._gate_task = self.create_task(self._gate_task_handler())
 
     async def _stop(self):
-        await self.cancel_task(self._gate_task)
+        if self._gate_task:
+            await self.cancel_task(self._gate_task)
+            self._gate_task = None
 
     async def _gate_task_handler(self):
         while True:
@@ -560,7 +564,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/22d-natural-conversation-gemini-audio.py

@@ -23,12 +23,9 @@ from pipecat.frames.frames import (
     FunctionCallInProgressFrame,
     FunctionCallResultFrame,
     InputAudioRawFrame,
-    LLMFullResponseEndFrame,
     LLMFullResponseStartFrame,
-    LLMMessagesFrame,
     StartFrame,
     StartInterruptionFrame,
-    StopInterruptionFrame,
     SystemFrame,
     TextFrame,
     TranscriptionFrame,
@@ -39,7 +36,7 @@ from pipecat.pipeline.parallel_pipeline import ParallelPipeline
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.aggregators.llm_response import LLMResponseAggregator
+from pipecat.processors.aggregators.llm_response import LLMAssistantResponseAggregator
 from pipecat.processors.aggregators.openai_llm_context import (
     OpenAILLMContext,
     OpenAILLMContextFrame,
@@ -391,7 +388,7 @@ class AudioAccumulator(FrameProcessor):
             )
             self._user_speaking = False
             context = GoogleLLMContext()
-            context.add_audio_frames_message(text="Audio follows", audio_frames=self._audio_frames)
+            context.add_audio_frames_message(audio_frames=self._audio_frames)
             await self.push_frame(OpenAILLMContextFrame(context=context))
         elif isinstance(frame, InputAudioRawFrame):
             # Append the audio frame to our buffer. Treat the buffer as a ring buffer, dropping the oldest
@@ -434,7 +431,11 @@ class CompletenessCheck(FrameProcessor):
     async def process_frame(self, frame: Frame, direction: FrameDirection):
         await super().process_frame(frame, direction)
 
-        if isinstance(frame, UserStartedSpeakingFrame):
+        if isinstance(frame, (EndFrame, CancelFrame)):
+            if self._idle_task:
+                await self.cancel_task(self._idle_task)
+                self._idle_task = None
+        elif isinstance(frame, UserStartedSpeakingFrame):
             if self._idle_task:
                 await self.cancel_task(self._idle_task)
         elif isinstance(frame, TextFrame) and frame.text.startswith("YES"):
@@ -476,19 +477,11 @@ class CompletenessCheck(FrameProcessor):
             self._idle_task = None
 
 
-class UserAggregatorBuffer(LLMResponseAggregator):
+class LLMAggregatorBuffer(LLMAssistantResponseAggregator):
     """Buffers the output of the transcription LLM. Used by the bot output gate."""
 
     def __init__(self, **kwargs):
-        super().__init__(
-            messages=None,
-            role=None,
-            start_frame=LLMFullResponseStartFrame,
-            end_frame=LLMFullResponseEndFrame,
-            accumulator_frame=TextFrame,
-            handle_interruptions=True,
-            expect_stripped_words=False,
-        )
+        super().__init__(expect_stripped_words=False)
         self._transcription = ""
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):
@@ -546,7 +539,7 @@ class OutputGate(FrameProcessor):
         self,
         notifier: BaseNotifier,
         context: OpenAILLMContext,
-        user_transcription_buffer: "UserAggregatorBuffer",
+        llm_transcription_buffer: LLMAggregatorBuffer,
         **kwargs,
     ):
         super().__init__(**kwargs)
@@ -554,7 +547,8 @@ class OutputGate(FrameProcessor):
         self._frames_buffer = []
         self._notifier = notifier
         self._context = context
-        self._transcription_buffer = user_transcription_buffer
+        self._transcription_buffer = llm_transcription_buffer
+        self._gate_task = None
 
     def close_gate(self):
         self._gate_open = False
@@ -602,10 +596,13 @@ class OutputGate(FrameProcessor):
 
     async def _start(self):
         self._frames_buffer = []
-        self._gate_task = self.create_task(self._gate_task_handler())
+        if not self._gate_task:
+            self._gate_task = self.create_task(self._gate_task_handler())
 
     async def _stop(self):
-        await self.cancel_task(self._gate_task)
+        if self._gate_task:
+            await self.cancel_task(self._gate_task)
+            self._gate_task = None
 
     async def _gate_task_handler(self):
         while True:
@@ -697,10 +694,10 @@ async def main():
 
         conversation_audio_context_assembler = ConversationAudioContextAssembler(context=context)
 
-        user_aggregator_buffer = UserAggregatorBuffer()
+        llm_aggregator_buffer = LLMAggregatorBuffer()
 
         bot_output_gate = OutputGate(
-            notifier=notifier, context=context, user_transcription_buffer=user_aggregator_buffer
+            notifier=notifier, context=context, llm_transcription_buffer=llm_aggregator_buffer
         )
 
         pipeline = Pipeline(
@@ -721,7 +718,7 @@ async def main():
                             ],
                             [
                                 tx_llm,
-                                user_aggregator_buffer,
+                                llm_aggregator_buffer,
                             ],
                         )
                     ],
@@ -740,7 +737,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/23-bot-background-sound.py

@@ -87,7 +87,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/24-stt-mute-filter.py

@@ -122,7 +122,7 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):

examples/foundational/25-google-audio-in.py

@@ -354,7 +354,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/26-gemini-multimodal-live.py

@@ -63,7 +63,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/26a-gemini-multimodal-live-transcription.py

@@ -89,7 +89,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/26b-gemini-multimodal-live-function-calling.py

@@ -14,6 +14,8 @@ from dotenv import load_dotenv
 from loguru import logger
 from runner import configure
 
+from pipecat.adapters.schemas.function_schema import FunctionSchema
+from pipecat.adapters.schemas.tools_schema import AdapterType, ToolsSchema
 from pipecat.audio.vad.silero import SileroVADAnalyzer
 from pipecat.audio.vad.vad_analyzer import VADParams
 from pipecat.pipeline.pipeline import Pipeline
@@ -41,32 +43,6 @@ async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context
     )
 
 
-tools = [
-    {
-        "function_declarations": [
-            {
-                "name": "get_current_weather",
-                "description": "Get the current weather",
-                "parameters": {
-                    "type": "object",
-                    "properties": {
-                        "location": {
-                            "type": "string",
-                            "description": "The city and state, e.g. San Francisco, CA",
-                        },
-                        "format": {
-                            "type": "string",
-                            "enum": ["celsius", "fahrenheit"],
-                            "description": "The temperature unit to use. Infer this from the users location.",
-                        },
-                    },
-                    "required": ["location", "format"],
-                },
-            },
-        ]
-    }
-]
-
 system_instruction = """
 You are a helpful assistant who can answer questions and use tools.
 
@@ -95,6 +71,27 @@ async def main():
             ),
         )
 
+        weather_function = FunctionSchema(
+            name="get_current_weather",
+            description="Get the current weather",
+            properties={
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
+                },
+                "format": {
+                    "type": "string",
+                    "enum": ["celsius", "fahrenheit"],
+                    "description": "The temperature unit to use. Infer this from the user's location.",
+                },
+            },
+            required=["location", "format"],
+        )
+        search_tool = {"google_search": {}}
+        tools = ToolsSchema(
+            standard_tools=[weather_function], custom_tools={AdapterType.GEMINI: [search_tool]}
+        )
+
         llm = GeminiMultimodalLiveLLMService(
             api_key=os.getenv("GOOGLE_API_KEY"),
             system_instruction=system_instruction,
@@ -120,7 +117,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/26c-gemini-multimodal-live-video.py

@@ -79,7 +79,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/26d-gemini-multimodal-live-text.py

@@ -106,7 +106,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
                 enable_usage_metrics=True,

examples/foundational/26e-gemini-multimodal-google-search.py

@@ -1,5 +1,5 @@
 #
-# Copyright (c) 2024, Daily
+# Copyright (c) 2024-2025, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
@@ -34,7 +34,7 @@ search_tool = {"google_search": {}}
 tools = [search_tool]
 
 system_instruction = """
-You are an expert at providing the most recent news from any place. Your responses will be converted to audio, so avoid using special characters or overly complex formatting. 
+You are an expert at providing the most recent news from any place. Your responses will be converted to audio, so avoid using special characters or overly complex formatting.
 
 Always use the google search API to retrieve the latest news. You must also use it to check which day is today.
 
@@ -93,7 +93,7 @@ async def main():
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(pipeline, params=PipelineParams(allow_interruptions=True))
 
         @transport.event_handler("on_first_participant_joined")
         async def on_first_participant_joined(transport, participant):

examples/foundational/27-simli-layer.py

@@ -83,7 +83,7 @@ async def main():
 
         task = PipelineTask(
             pipeline,
-            PipelineParams(
+            params=PipelineParams(
                 allow_interruptions=True,
                 enable_metrics=True,
             ),