diff --git a/.gitignore b/.gitignore index 50944a3a8..1a11c0f2a 100644 --- a/.gitignore +++ b/.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/ diff --git a/CHANGELOG.md b/CHANGELOG.md index 9f9cd7e0c..b816d4ecd 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -5,18 +5,67 @@ 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] +## Unreleased ### Added +- Added `room_url` property to `DailyTransport`. + +- Added `addons` argument to `DeepgramSTTService`. + +- Added `exponential_backoff_time()` to `utils.network` module. + +### Changed + +- `DeepgramSTTService` now uses the new `nova-3` model by default. If you want + to use the previous model you can pass `LiveOptions(model="nova-2-general")`. + (see https://deepgram.com/learn/introducing-nova-3-speech-to-text-api) + +```python +stt = DeepgramSTTService(..., live_options=LiveOptions(model="nova-2-general")) +``` + +### Fixed + +- Fixed a `FishAudioTTSService` issue where `TTSStoppedFrame` was not being + pushed. + +- Fixed an issue that `start_callback` was not invoked for some LLM services. + +- Fixed an issue that would cause `DeepgramSTTService` to stop working after an + error occurred (e.g. sudden network loss). If the network recovered we would + not reconnect. + +- Fixed a `STTMuteFilter` issue that would not mute user audio frames causing + transcriptions to be generated by the STT service. + +### Other + +- Added Gemini support to `examples/phone-chatbot`. + +## [0.0.57] - 2025-02-14 + +### Added + +- Added new `AudioContextWordTTSService`. This is a TTS base class for TTS + services that handling multiple separate audio requests. + +- Added new frames `EmulateUserStartedSpeakingFrame` and + `EmulateUserStoppedSpeakingFrame` which can be used to emulated VAD behavior + without VAD being present or not being triggered. + - Added a new `audio_in_stream_on_start` field to `TransportParams`. - -- Added a new method `start_audio_in_streaming` in the `BaseInputTransport`. - - This method should be used to start receiving the input audio in case the field `audio_in_stream_on_start` is set to `false`. -- Added support for the `RTVIProcessor` to handle buffered audio in `base64` format, converting it into InputAudioRawFrame for transport. +- Added a new method `start_audio_in_streaming` in the `BaseInputTransport`. -- Added support for the `RTVIProcessor` to trigger `start_audio_in_streaming` only after the `client-ready` message. + - This method should be used to start receiving the input audio in case the + field `audio_in_stream_on_start` is set to `false`. + +- Added support for the `RTVIProcessor` to handle buffered audio in `base64` + format, converting it into InputAudioRawFrame for transport. + +- Added support for the `RTVIProcessor` to trigger `start_audio_in_streaming` + only after the `client-ready` message. - Added new `MUTE_UNTIL_FIRST_BOT_COMPLETE` strategy to `STTMuteStrategy`. This strategy starts muted and remains muted until the first bot speech completes, @@ -38,18 +87,23 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 OpenAI-compatible interface. Also, added foundational example `14n-function-calling-perplexity.py`. -- Added `DailyTransport.update_remote_participants()`. This allows you to - update remote participant's settings, like their permissions or which of - their devices are enabled. Requires that the local participant have - participant admin permission. +- Added `DailyTransport.update_remote_participants()`. This allows you to update + remote participant's settings, like their permissions or which of their + devices are enabled. Requires that the local participant have participant + admin permission. ### Changed -- Updated `DailyTransport` to respect the `audio_in_stream_on_start` field, ensuring it only starts receiving the audio input if it is enabled. +- We don't consider a colon `:` and end of sentence any more. -- Updated `FastAPIWebsocketOutputTransport` to send `TransportMessageFrame` and `TransportMessageUrgentFrame` to the serializer. +- Updated `DailyTransport` to respect the `audio_in_stream_on_start` field, + ensuring it only starts receiving the audio input if it is enabled. -- Updated `WebsocketServerOutputTransport` to send `TransportMessageFrame` and `TransportMessageUrgentFrame` to the serializer. +- Updated `FastAPIWebsocketOutputTransport` to send `TransportMessageFrame` and + `TransportMessageUrgentFrame` to the serializer. + +- Updated `WebsocketServerOutputTransport` to send `TransportMessageFrame` and + `TransportMessageUrgentFrame` to the serializer. - Enhanced `STTMuteConfig` to validate strategy combinations, preventing `MUTE_UNTIL_FIRST_BOT_COMPLETE` and `FIRST_SPEECH` from being used together @@ -91,6 +145,25 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 ### Fixed +- Fixed a `FalImageGenService` issue that was causing the event loop to be + blocked while loading the downloadded image. + +- Fixed a `CartesiaTTSService` service issue that would cause audio overlapping + in some cases. + +- Fixed a websocket-based service issue (e.g. `CartesiaTTSService`) that was + preventing a reconnection after the server disconnected cleanly, which was + causing an inifite loop instead. + +- Fixed a `BaseOutputTransport` issue that was causing upstream frames to no be + pushed upstream. + +- Fixed multiple issue where user transcriptions where not being handled + properly. It was possible for short utterances to not trigger VAD which would + cause user transcriptions to be ignored. It was also possible for one or more + transcriptions to be generated after VAD in which case they would also be + ignored. + - Fixed an issue that was causing `BotStoppedSpeakingFrame` to be generated too late. This could then cause issues unblocking `STTMuteFilter` later than desired. @@ -104,6 +177,18 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 - Fixed an issue[#1192] in 11labs where we are trying to reconnect/disconnect the websocket connection even when the connection is already closed. +- Fixed an issue where `has_regular_messages` condition was always true in + `GoogleLLMContext` due to `Part` having `function_call` & `function_response` + with `None` values. + +### Other + +- Added new `instant-voice` example. This example showcases how to enable + instant voice communication as soon as a user connects. + +- Added new `local-input-select-stt` example. This examples allows you to play + with local audio inputs by slecting them through a nice text interface. + ## [0.0.56] - 2025-02-06 ### Changed @@ -283,7 +368,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 - Added `enable_recording` and `geo` parameters to `DailyRoomProperties`. -- Added `RecordingsBucketConfig` to `DailyRoomProperties` to upload recordings to a custom AWS bucket. +- Added `RecordingsBucketConfig` to `DailyRoomProperties` to upload recordings + to a custom AWS bucket. ### Changed diff --git a/examples/bot-ready-signalling/client/react-native/.nvmrc b/examples/bot-ready-signalling/client/react-native/.nvmrc new file mode 100644 index 000000000..744ca17ec --- /dev/null +++ b/examples/bot-ready-signalling/client/react-native/.nvmrc @@ -0,0 +1 @@ +22.14 diff --git a/examples/bot-ready-signalling/client/react-native/README.md b/examples/bot-ready-signalling/client/react-native/README.md new file mode 100644 index 000000000..5da0c67be --- /dev/null +++ b/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. diff --git a/examples/bot-ready-signalling/client/react-native/app.json b/examples/bot-ready-signalling/client/react-native/app.json new file mode 100644 index 000000000..fb9394e96 --- /dev/null +++ b/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" + } + } + ] + ] + } +} diff --git a/examples/bot-ready-signalling/client/react-native/assets/adaptive-icon.png b/examples/bot-ready-signalling/client/react-native/assets/adaptive-icon.png new file mode 100644 index 000000000..03d6f6b6c Binary files /dev/null and b/examples/bot-ready-signalling/client/react-native/assets/adaptive-icon.png differ diff --git a/examples/bot-ready-signalling/client/react-native/assets/favicon.png b/examples/bot-ready-signalling/client/react-native/assets/favicon.png new file mode 100644 index 000000000..e75f697b1 Binary files /dev/null and b/examples/bot-ready-signalling/client/react-native/assets/favicon.png differ diff --git a/examples/bot-ready-signalling/client/react-native/assets/icon.png b/examples/bot-ready-signalling/client/react-native/assets/icon.png new file mode 100644 index 000000000..a0b1526fc Binary files /dev/null and b/examples/bot-ready-signalling/client/react-native/assets/icon.png differ diff --git a/examples/bot-ready-signalling/client/react-native/assets/splash.png b/examples/bot-ready-signalling/client/react-native/assets/splash.png new file mode 100644 index 000000000..0e89705a9 Binary files /dev/null and b/examples/bot-ready-signalling/client/react-native/assets/splash.png differ diff --git a/examples/bot-ready-signalling/client/react-native/babel.config.js b/examples/bot-ready-signalling/client/react-native/babel.config.js new file mode 100644 index 000000000..81d4cb0da --- /dev/null +++ b/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"]], + }; +}; diff --git a/examples/bot-ready-signalling/client/react-native/env.example b/examples/bot-ready-signalling/client/react-native/env.example new file mode 100644 index 000000000..4c242c880 --- /dev/null +++ b/examples/bot-ready-signalling/client/react-native/env.example @@ -0,0 +1 @@ +API_BASE_URL=http://YOUR_LOCAL_IP:7860 diff --git a/examples/bot-ready-signalling/client/react-native/index.js b/examples/bot-ready-signalling/client/react-native/index.js new file mode 100644 index 000000000..9d93586db --- /dev/null +++ b/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); diff --git a/examples/bot-ready-signalling/client/react-native/metro.config.js b/examples/bot-ready-signalling/client/react-native/metro.config.js new file mode 100644 index 000000000..9430b0f9b --- /dev/null +++ b/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); diff --git a/examples/bot-ready-signalling/client/react-native/package-lock.json b/examples/bot-ready-signalling/client/react-native/package-lock.json new file mode 100644 index 000000000..c8cff3517 --- /dev/null +++ b/examples/bot-ready-signalling/client/react-native/package-lock.json @@ -0,0 +1,10983 @@ +{ + "name": "bot-ready-rn", + "version": "1.0.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "bot-ready-rn", + "version": "1.0.0", + "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", + 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"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 +} diff --git a/examples/bot-ready-signalling/client/react-native/src/App.js b/examples/bot-ready-signalling/client/react-native/src/App.js new file mode 100644 index 000000000..46b4c1e91 --- /dev/null +++ b/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 ( + + + + Status: {connectionStatus} + + + + + + + + +
+

Debug Info

+
+
+ + + + + + + diff --git a/examples/instant-voice/client/javascript/package-lock.json b/examples/instant-voice/client/javascript/package-lock.json new file mode 100644 index 000000000..54ed9131c --- /dev/null +++ b/examples/instant-voice/client/javascript/package-lock.json @@ -0,0 +1,1449 @@ +{ + "name": "client", + "version": "1.0.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "client", + "version": "1.0.0", + "license": "ISC", + "dependencies": { + "@pipecat-ai/client-js": "^0.3.2", + "@pipecat-ai/daily-transport": "^0.3.5" + }, + "devDependencies": { + "@types/node": "^22.13.1", + "@vitejs/plugin-react-swc": "^3.7.2", + "typescript": "^5.7.3", + "vite": "^6.0.2" + } + }, + "node_modules/@babel/runtime": { + "version": "7.26.0", + "resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.26.0.tgz", + "integrity": "sha512-FDSOghenHTiToteC/QRlv2q3DhPZ/oOXTBoirfWNx1Cx3TMVcGWQtMMmQcSvb/JjpNeGzx8Pq/b4fKEJuWm1sw==", + "license": "MIT", + 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new file mode 100644 index 000000000..9c3afb89a --- /dev/null +++ b/examples/instant-voice/client/javascript/package.json @@ -0,0 +1,24 @@ +{ + "name": "client", + "version": "1.0.0", + "main": "index.js", + "scripts": { + "dev": "vite", + "build": "tsc && vite build", + "preview": "vite preview" + }, + "keywords": [], + "author": "", + "license": "ISC", + "description": "", + "devDependencies": { + "@types/node": "^22.13.1", + "@vitejs/plugin-react-swc": "^3.7.2", + "typescript": "^5.7.3", + "vite": "^6.0.2" + }, + "dependencies": { + "@pipecat-ai/client-js": "^0.3.2", + "@pipecat-ai/daily-transport": "^0.3.5" + } +} diff --git a/examples/instant-voice/client/javascript/src/app.ts b/examples/instant-voice/client/javascript/src/app.ts new file mode 100644 index 000000000..bb587307c --- /dev/null +++ b/examples/instant-voice/client/javascript/src/app.ts @@ -0,0 +1,268 @@ +/** + * Copyright (c) 2024–2025, Daily + * + * SPDX-License-Identifier: BSD 2-Clause License + */ + +/** + * RTVI Client Implementation + * + * This client connects to an RTVI-compatible bot server using WebRTC (via Daily). + * It handles audio/video streaming and manages the connection lifecycle. + * + * Requirements: + * - A running RTVI bot server (defaults to http://localhost:7860) + * - The server must implement the /connect endpoint that returns Daily.co room credentials + * - Browser with WebRTC support + */ + +import { + Participant, + RTVIClient, + RTVIClientOptions, + RTVIEvent, +} from '@pipecat-ai/client-js'; +import { DailyTransport } from '@pipecat-ai/daily-transport'; +import SoundUtils from "./util/soundUtils"; +import { InstantVoiceHelper } from "./util/instantVoiceHelper"; + +/** + * InstantVoiceClient handles the connection and media management for a real-time + * voice and video interaction with an AI bot. + */ +class InstantVoiceClient { + + private declare rtviClient: RTVIClient; + private connectBtn: HTMLButtonElement | null = null; + private disconnectBtn: HTMLButtonElement | null = null; + private statusSpan: HTMLElement | null = null; + private bufferingAudioSpan: HTMLElement | null = null; + private debugLog: HTMLElement | null = null; + private botAudio: HTMLAudioElement; + private declare startTime: number; + + constructor() { + this.botAudio = document.createElement('audio'); + this.botAudio.autoplay = true; + document.body.appendChild(this.botAudio); + this.setupDOMElements(); + this.setupEventListeners(); + this.initializeRTVIClient(); + } + + /** + * Set up references to DOM elements and create necessary media elements + */ + private setupDOMElements(): void { + this.connectBtn = document.getElementById('connect-btn') as HTMLButtonElement; + this.disconnectBtn = document.getElementById('disconnect-btn') as HTMLButtonElement; + this.statusSpan = document.getElementById('connection-status'); + this.bufferingAudioSpan = document.getElementById('buffering-status'); + this.debugLog = document.getElementById('debug-log'); + } + + /** + * Set up event listeners for connect/disconnect buttons + */ + private setupEventListeners(): void { + this.connectBtn?.addEventListener('click', () => this.connect()); + this.disconnectBtn?.addEventListener('click', () => this.disconnect()); + } + + private initializeRTVIClient(): void { + const transport = new DailyTransport({ + bufferLocalAudioUntilBotReady: true + }); + const RTVIConfig: RTVIClientOptions = { + transport, + params: { + // The baseURL and endpoint of your bot server that the client will connect to + baseUrl: 'http://localhost:7860', + endpoints: { connect: '/connect' }, + }, + enableMic: true, + enableCam: false, + callbacks: { + onConnected: () => { + this.updateStatus('Connected'); + if (this.connectBtn) this.connectBtn.disabled = true; + if (this.disconnectBtn) this.disconnectBtn.disabled = false; + }, + onDisconnected: () => { + this.updateStatus('Disconnected'); + this.updateBufferingStatus('No'); + if (this.connectBtn) this.connectBtn.disabled = false; + if (this.disconnectBtn) this.disconnectBtn.disabled = true; + this.log('Client disconnected'); + }, + onBotConnected: (participant: Participant) => { + this.log(`onBotConnected, timeTaken: ${Date.now() - this.startTime}`); + }, + onBotReady: (data) => { + this.log(`onBotReady, timeTaken: ${Date.now() - this.startTime}`); + this.log(`Bot ready: ${JSON.stringify(data)}`); + this.setupMediaTracks(); + }, + onUserTranscript: (data) => { + if (data.final) { + this.log(`User: ${data.text}`); + } + }, + onBotTranscript: (data) => this.log(`Bot: ${data.text}`), + onMessageError: (error) => console.error('Message error:', error), + onError: (error) => console.error('Error:', error), + }, + } + + this.rtviClient = new RTVIClient(RTVIConfig); + this.rtviClient.registerHelper("transport", new InstantVoiceHelper({ + callbacks: { + onAudioBufferingStarted: () => { + SoundUtils.beep() + this.updateBufferingStatus('Yes'); + this.log(`onMicCaptureStarted, timeTaken: ${Date.now() - this.startTime}`); + }, + onAudioBufferingStopped: () => { + this.updateBufferingStatus('No'); + this.log(`onMicCaptureStopped, timeTaken: ${Date.now() - this.startTime}`); + } + } + } + )); + this.setupTrackListeners(); + } + + /** + * Add a timestamped message to the debug log + */ + private log(message: string): void { + if (!this.debugLog) return; + const entry = document.createElement('div'); + entry.textContent = `${new Date().toISOString()} - ${message}`; + if (message.startsWith('User: ')) { + entry.style.color = '#2196F3'; + } else if (message.startsWith('Bot: ')) { + entry.style.color = '#4CAF50'; + } + this.debugLog.appendChild(entry); + this.debugLog.scrollTop = this.debugLog.scrollHeight; + console.log(message); + } + + /** + * Update the connection status display + */ + private updateStatus(status: string): void { + if (this.statusSpan) { + this.statusSpan.textContent = status; + } + this.log(`Status: ${status}`); + } + + /** + * Update the connection status display + */ + private updateBufferingStatus(status: string): void { + if (this.bufferingAudioSpan) { + this.bufferingAudioSpan.textContent = status; + } + this.log(`BufferingStatus: ${status}`); + } + + /** + * Check for available media tracks and set them up if present + * This is called when the bot is ready or when the transport state changes to ready + */ + setupMediaTracks() { + if (!this.rtviClient) return; + const tracks = this.rtviClient.tracks(); + if (tracks.bot?.audio) { + this.setupAudioTrack(tracks.bot.audio); + } + } + + /** + * Set up listeners for track events (start/stop) + * This handles new tracks being added during the session + */ + setupTrackListeners() { + if (!this.rtviClient) return; + + // Listen for new tracks starting + this.rtviClient.on(RTVIEvent.TrackStarted, (track, participant) => { + // Only handle non-local (bot) tracks + if (!participant?.local && track.kind === 'audio') { + this.setupAudioTrack(track); + } + }); + + // Listen for tracks stopping + this.rtviClient.on(RTVIEvent.TrackStopped, (track, participant) => { + this.log(`Track stopped: ${track.kind} from ${participant?.name || 'unknown'}`); + }); + } + + /** + * Set up an audio track for playback + * Handles both initial setup and track updates + */ + private setupAudioTrack(track: MediaStreamTrack): void { + this.log('Setting up audio track'); + if (this.botAudio.srcObject && "getAudioTracks" in this.botAudio.srcObject) { + const oldTrack = this.botAudio.srcObject.getAudioTracks()[0]; + if (oldTrack?.id === track.id) return; + } + this.botAudio.srcObject = new MediaStream([track]); + } + + /** + * Initialize and connect to the bot + * This sets up the RTVI client, initializes devices, and establishes the connection + */ + public async connect(): Promise { + try { + this.startTime = Date.now(); + this.log('Connecting to bot...'); + await this.rtviClient.connect(); + } catch (error) { + this.log(`Error connecting: ${(error as Error).message}`); + this.updateStatus('Error'); + this.updateBufferingStatus('No'); + + // Clean up if there's an error + if (this.rtviClient) { + try { + await this.rtviClient.disconnect(); + } catch (disconnectError) { + this.log(`Error during disconnect: ${disconnectError}`); + } + } + } + } + + /** + * Disconnect from the bot and clean up media resources + */ + public async disconnect(): Promise { + try { + await this.rtviClient.disconnect(); + if (this.botAudio.srcObject && "getAudioTracks" in this.botAudio.srcObject) { + this.botAudio.srcObject.getAudioTracks().forEach((track) => track.stop()); + this.botAudio.srcObject = null; + } + } catch (error) { + this.log(`Error disconnecting: ${(error as Error).message}`); + } + } +} + +declare global { + interface Window { + InstantVoiceClient: typeof InstantVoiceClient; + } +} + +window.addEventListener('DOMContentLoaded', () => { + window.InstantVoiceClient = InstantVoiceClient; + new InstantVoiceClient(); +}); diff --git a/examples/instant-voice/client/javascript/src/style.css b/examples/instant-voice/client/javascript/src/style.css new file mode 100644 index 000000000..9c147266e --- /dev/null +++ b/examples/instant-voice/client/javascript/src/style.css @@ -0,0 +1,98 @@ +body { + margin: 0; + padding: 20px; + font-family: Arial, sans-serif; + background-color: #f0f0f0; +} + +.container { + max-width: 1200px; + margin: 0 auto; +} + +.status-bar { + display: flex; + justify-content: space-between; + align-items: center; + padding: 10px; + background-color: #fff; + border-radius: 8px; + margin-bottom: 20px; +} + +.controls button { + padding: 8px 16px; + margin-left: 10px; + border: none; + border-radius: 4px; + cursor: pointer; +} + +#connect-btn { + background-color: #4caf50; + color: white; +} + +#disconnect-btn { + background-color: #f44336; + color: white; +} + +button:disabled { + opacity: 0.5; + cursor: not-allowed; +} + +.main-content { + background-color: #fff; + border-radius: 8px; + padding: 20px; + margin-bottom: 20px; +} + +.bot-container { + display: flex; + flex-direction: column; + align-items: center; +} + +#bot-video-container { + width: 640px; + height: 360px; + background-color: #e0e0e0; + border-radius: 8px; + margin: 20px auto; + overflow: hidden; + display: flex; + align-items: center; + justify-content: center; +} + +#bot-video-container video { + width: 100%; + height: 100%; + object-fit: cover; +} + +.debug-panel { + background-color: #fff; + border-radius: 8px; + padding: 20px; +} + +.debug-panel h3 { + margin: 0 0 10px 0; + font-size: 16px; + font-weight: bold; +} + +#debug-log { + height: 500px; + overflow-y: auto; + background-color: #f8f8f8; + padding: 10px; + border-radius: 4px; + font-family: monospace; + font-size: 12px; + line-height: 1.4; +} diff --git a/examples/instant-voice/client/javascript/src/util/instantVoiceHelper.ts b/examples/instant-voice/client/javascript/src/util/instantVoiceHelper.ts new file mode 100644 index 000000000..2ce3a15ce --- /dev/null +++ b/examples/instant-voice/client/javascript/src/util/instantVoiceHelper.ts @@ -0,0 +1,39 @@ +import {RTVIClientHelper, RTVIClientHelperOptions, RTVIMessage} from "@pipecat-ai/client-js"; +import {DailyRTVIMessageType} from '@pipecat-ai/daily-transport'; + +export type InstantVoiceHelperCallbacks = Partial<{ + onAudioBufferingStarted: () => void; + onAudioBufferingStopped: () => void; +}>; + +// --- Interface and class +export interface InstantVoiceHelperOptions extends RTVIClientHelperOptions { + callbacks?: InstantVoiceHelperCallbacks; +} +export class InstantVoiceHelper extends RTVIClientHelper { + + protected declare _options: InstantVoiceHelperOptions; + + constructor(options: InstantVoiceHelperOptions) { + super(options); + } + + handleMessage(rtviMessage: RTVIMessage): void { + switch (rtviMessage.type) { + case DailyRTVIMessageType.AUDIO_BUFFERING_STARTED: + if (this._options.callbacks?.onAudioBufferingStarted) { + this._options.callbacks?.onAudioBufferingStarted() + } + break; + case DailyRTVIMessageType.AUDIO_BUFFERING_STOPPED: + if (this._options.callbacks?.onAudioBufferingStopped) { + this._options.callbacks?.onAudioBufferingStopped() + } + break; + } + } + + getMessageTypes(): string[] { + return [DailyRTVIMessageType.AUDIO_BUFFERING_STARTED, DailyRTVIMessageType.AUDIO_BUFFERING_STOPPED]; + } +} diff --git a/examples/instant-voice/client/javascript/src/util/soundUtils.ts b/examples/instant-voice/client/javascript/src/util/soundUtils.ts new file mode 100644 index 000000000..996185f40 --- /dev/null +++ b/examples/instant-voice/client/javascript/src/util/soundUtils.ts @@ -0,0 +1,8 @@ +class SoundUtils { + static beep() { + const snd = new Audio("data:audio/wav;base64,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"); + void snd.play(); + } +} + +export default SoundUtils; diff --git a/examples/instant-voice/client/javascript/tsconfig.json b/examples/instant-voice/client/javascript/tsconfig.json new file mode 100644 index 000000000..c9c555d96 --- /dev/null +++ b/examples/instant-voice/client/javascript/tsconfig.json @@ -0,0 +1,111 @@ +{ + "compilerOptions": { + /* Visit https://aka.ms/tsconfig to read more about this file */ + + /* Projects */ + // "incremental": true, /* Save .tsbuildinfo files to allow for incremental compilation of projects. */ + // "composite": true, /* Enable constraints that allow a TypeScript project to be used with project references. */ + // "tsBuildInfoFile": "./.tsbuildinfo", /* Specify the path to .tsbuildinfo incremental compilation file. */ + // "disableSourceOfProjectReferenceRedirect": true, /* Disable preferring source files instead of declaration files when referencing composite projects. */ + // "disableSolutionSearching": true, /* Opt a project out of multi-project reference checking when editing. */ + // "disableReferencedProjectLoad": true, /* Reduce the number of projects loaded automatically by TypeScript. */ + + /* Language and Environment */ + "target": "es2016", /* Set the JavaScript language version for emitted JavaScript and include compatible library declarations. */ + // "lib": [], /* Specify a set of bundled library declaration files that describe the target runtime environment. */ + // "jsx": "preserve", /* Specify what JSX code is generated. */ + // "experimentalDecorators": true, /* Enable experimental support for legacy experimental decorators. */ + // "emitDecoratorMetadata": true, /* Emit design-type metadata for decorated declarations in source files. */ + // "jsxFactory": "", /* Specify the JSX factory function used when targeting React JSX emit, e.g. 'React.createElement' or 'h'. */ + // "jsxFragmentFactory": "", /* Specify the JSX Fragment reference used for fragments when targeting React JSX emit e.g. 'React.Fragment' or 'Fragment'. */ + // "jsxImportSource": "", /* Specify module specifier used to import the JSX factory functions when using 'jsx: react-jsx*'. */ + // "reactNamespace": "", /* Specify the object invoked for 'createElement'. This only applies when targeting 'react' JSX emit. */ + // "noLib": true, /* Disable including any library files, including the default lib.d.ts. */ + // "useDefineForClassFields": true, /* Emit ECMAScript-standard-compliant class fields. */ + // "moduleDetection": "auto", /* Control what method is used to detect module-format JS files. */ + + /* Modules */ + "module": "commonjs", /* Specify what module code is generated. */ + // "rootDir": "./", /* Specify the root folder within your source files. */ + // "moduleResolution": "node10", /* Specify how TypeScript looks up a file from a given module specifier. */ + // "baseUrl": "./", /* Specify the base directory to resolve non-relative module names. */ + // "paths": {}, /* Specify a set of entries that re-map imports to additional lookup locations. */ + // "rootDirs": [], /* Allow multiple folders to be treated as one when resolving modules. */ + // "typeRoots": [], /* Specify multiple folders that act like './node_modules/@types'. */ + // "types": [], /* Specify type package names to be included without being referenced in a source file. */ + // "allowUmdGlobalAccess": true, /* Allow accessing UMD globals from modules. */ + // "moduleSuffixes": [], /* List of file name suffixes to search when resolving a module. */ + // "allowImportingTsExtensions": true, /* Allow imports to include TypeScript file extensions. Requires '--moduleResolution bundler' and either '--noEmit' or '--emitDeclarationOnly' to be set. */ + // "rewriteRelativeImportExtensions": true, /* Rewrite '.ts', '.tsx', '.mts', and '.cts' file extensions in relative import paths to their JavaScript equivalent in output files. */ + // "resolvePackageJsonExports": true, /* Use the package.json 'exports' field when resolving package imports. */ + // "resolvePackageJsonImports": true, /* Use the package.json 'imports' field when resolving imports. */ + // "customConditions": [], /* Conditions to set in addition to the resolver-specific defaults when resolving imports. */ + // "noUncheckedSideEffectImports": true, /* Check side effect imports. */ + // "resolveJsonModule": true, /* Enable importing .json files. */ + // "allowArbitraryExtensions": true, /* Enable importing files with any extension, provided a declaration file is present. */ + // "noResolve": true, /* Disallow 'import's, 'require's or ''s from expanding the number of files TypeScript should add to a project. */ + + /* JavaScript Support */ + // "allowJs": true, /* Allow JavaScript files to be a part of your program. Use the 'checkJS' option to get errors from these files. */ + // "checkJs": true, /* Enable error reporting in type-checked JavaScript files. */ + // "maxNodeModuleJsDepth": 1, /* Specify the maximum folder depth used for checking JavaScript files from 'node_modules'. Only applicable with 'allowJs'. */ + + /* Emit */ + // "declaration": true, /* Generate .d.ts files from TypeScript and JavaScript files in your project. */ + // "declarationMap": true, /* Create sourcemaps for d.ts files. */ + // "emitDeclarationOnly": true, /* Only output d.ts files and not JavaScript files. */ + // "sourceMap": true, /* Create source map files for emitted JavaScript files. */ + // "inlineSourceMap": true, /* Include sourcemap files inside the emitted JavaScript. */ + // "noEmit": true, /* Disable emitting files from a compilation. */ + // "outFile": "./", /* Specify a file that bundles all outputs into one JavaScript file. If 'declaration' is true, also designates a file that bundles all .d.ts output. */ + // "outDir": "./", /* Specify an output folder for all emitted files. */ + // "removeComments": true, /* Disable emitting comments. */ + // "importHelpers": true, /* Allow importing helper functions from tslib once per project, instead of including them per-file. */ + // "downlevelIteration": true, /* Emit more compliant, but verbose and less performant JavaScript for iteration. */ + // "sourceRoot": "", /* Specify the root path for debuggers to find the reference source code. */ + // "mapRoot": "", /* Specify the location where debugger should locate map files instead of generated locations. */ + // "inlineSources": true, /* Include source code in the sourcemaps inside the emitted JavaScript. */ + // "emitBOM": true, /* Emit a UTF-8 Byte Order Mark (BOM) in the beginning of output files. */ + // "newLine": "crlf", /* Set the newline character for emitting files. */ + // "stripInternal": true, /* Disable emitting declarations that have '@internal' in their JSDoc comments. */ + // "noEmitHelpers": true, /* Disable generating custom helper functions like '__extends' in compiled output. */ + // "noEmitOnError": true, /* Disable emitting files if any type checking errors are reported. */ + // "preserveConstEnums": true, /* Disable erasing 'const enum' declarations in generated code. */ + // "declarationDir": "./", /* Specify the output directory for generated declaration files. */ + + /* Interop Constraints */ + // "isolatedModules": true, /* Ensure that each file can be safely transpiled without relying on other imports. */ + // "verbatimModuleSyntax": true, /* Do not transform or elide any imports or exports not marked as type-only, ensuring they are written in the output file's format based on the 'module' setting. */ + // "isolatedDeclarations": true, /* Require sufficient annotation on exports so other tools can trivially generate declaration files. */ + // "allowSyntheticDefaultImports": true, /* Allow 'import x from y' when a module doesn't have a default export. */ + "esModuleInterop": true, /* Emit additional JavaScript to ease support for importing CommonJS modules. This enables 'allowSyntheticDefaultImports' for type compatibility. */ + // "preserveSymlinks": true, /* Disable resolving symlinks to their realpath. This correlates to the same flag in node. */ + "forceConsistentCasingInFileNames": true, /* Ensure that casing is correct in imports. */ + + /* Type Checking */ + "strict": true, /* Enable all strict type-checking options. */ + // "noImplicitAny": true, /* Enable error reporting for expressions and declarations with an implied 'any' type. */ + // "strictNullChecks": true, /* When type checking, take into account 'null' and 'undefined'. */ + // "strictFunctionTypes": true, /* When assigning functions, check to ensure parameters and the return values are subtype-compatible. */ + // "strictBindCallApply": true, /* Check that the arguments for 'bind', 'call', and 'apply' methods match the original function. */ + // "strictPropertyInitialization": true, /* Check for class properties that are declared but not set in the constructor. */ + // "strictBuiltinIteratorReturn": true, /* Built-in iterators are instantiated with a 'TReturn' type of 'undefined' instead of 'any'. */ + // "noImplicitThis": true, /* Enable error reporting when 'this' is given the type 'any'. */ + // "useUnknownInCatchVariables": true, /* Default catch clause variables as 'unknown' instead of 'any'. */ + // "alwaysStrict": true, /* Ensure 'use strict' is always emitted. */ + // "noUnusedLocals": true, /* Enable error reporting when local variables aren't read. */ + // "noUnusedParameters": true, /* Raise an error when a function parameter isn't read. */ + // "exactOptionalPropertyTypes": true, /* Interpret optional property types as written, rather than adding 'undefined'. */ + // "noImplicitReturns": true, /* Enable error reporting for codepaths that do not explicitly return in a function. */ + // "noFallthroughCasesInSwitch": true, /* Enable error reporting for fallthrough cases in switch statements. */ + // "noUncheckedIndexedAccess": true, /* Add 'undefined' to a type when accessed using an index. */ + // "noImplicitOverride": true, /* Ensure overriding members in derived classes are marked with an override modifier. */ + // "noPropertyAccessFromIndexSignature": true, /* Enforces using indexed accessors for keys declared using an indexed type. */ + // "allowUnusedLabels": true, /* Disable error reporting for unused labels. */ + // "allowUnreachableCode": true, /* Disable error reporting for unreachable code. */ + + /* Completeness */ + // "skipDefaultLibCheck": true, /* Skip type checking .d.ts files that are included with TypeScript. */ + "skipLibCheck": true /* Skip type checking all .d.ts files. */ + } +} diff --git a/examples/instant-voice/client/javascript/vite.config.js b/examples/instant-voice/client/javascript/vite.config.js new file mode 100644 index 000000000..daf85167d --- /dev/null +++ b/examples/instant-voice/client/javascript/vite.config.js @@ -0,0 +1,15 @@ +import { defineConfig } from 'vite'; +import react from '@vitejs/plugin-react-swc'; + +export default defineConfig({ + plugins: [react()], + server: { + proxy: { + // Proxy /api requests to the backend server + '/connect': { + target: 'http://0.0.0.0:7860', // Replace with your backend URL + changeOrigin: true, + }, + }, + }, +}); diff --git a/examples/instant-voice/client/javascript/yarn.lock b/examples/instant-voice/client/javascript/yarn.lock new file mode 100644 index 000000000..e74aef8b7 --- /dev/null +++ b/examples/instant-voice/client/javascript/yarn.lock @@ -0,0 +1,339 @@ +# THIS IS AN AUTOGENERATED FILE. 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index 000000000..7dd76e98c --- /dev/null +++ b/examples/instant-voice/server/env.example @@ -0,0 +1,3 @@ +DAILY_API_KEY= +GOOGLE_API_KEY= +DAILY_SAMPLE_ROOM_URL=https://yourdomain.daily.co/yourroom # (for joining the bot to the same room repeatedly for local dev) \ No newline at end of file diff --git a/examples/instant-voice/server/pyproject.toml b/examples/instant-voice/server/pyproject.toml new file mode 100644 index 000000000..2c2ce8e48 --- /dev/null +++ b/examples/instant-voice/server/pyproject.toml @@ -0,0 +1,11 @@ +[tool.ruff] +exclude = [".git", "*_pb2.py"] +line-length = 100 + +[tool.ruff.lint] +select = [ + "I", # Import rules +] + +[tool.ruff.lint.pydocstyle] +convention = "google" \ No newline at end of file diff --git a/examples/instant-voice/server/requirements.txt b/examples/instant-voice/server/requirements.txt new file mode 100644 index 000000000..292de88c2 --- /dev/null +++ b/examples/instant-voice/server/requirements.txt @@ -0,0 +1,4 @@ +python-dotenv +fastapi[all] +uvicorn +pipecat-ai[openai,silero,websocket,google,daily] diff --git a/examples/instant-voice/server/src/server.py b/examples/instant-voice/server/src/server.py new file mode 100644 index 000000000..0777a3730 --- /dev/null +++ b/examples/instant-voice/server/src/server.py @@ -0,0 +1,200 @@ +# +# Copyright (c) 2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# +import asyncio +import os +from contextlib import asynccontextmanager +from typing import Any, Dict, List + +import aiohttp +import uvicorn +from dotenv import load_dotenv +from fastapi import FastAPI, HTTPException, Request +from fastapi.middleware.cors import CORSMiddleware +from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper, DailyRoomParams + +# Load environment variables +load_dotenv(override=True) + +NUMBER_OF_ROOMS = 1 + + +class RoomPool: + """Manages a pool of pre-created rooms for quick allocation.""" + + def __init__(self, daily_rest_helper: DailyRESTHelper): + self.daily_rest_helper = daily_rest_helper + self.pool: List[Dict[str, str]] = [] + self.lock = asyncio.Lock() + + async def fill_pool(self, count: int): + """Fills the pool with `count` new rooms.""" + for _ in range(count): + await self.add_room() + + async def add_room(self): + """Creates a new room and adds it to the pool.""" + try: + room = await self.daily_rest_helper.create_room(DailyRoomParams()) + if not room.url: + raise HTTPException(status_code=500, detail="Failed to create room") + + user_token = await self.daily_rest_helper.get_token(room.url) + if not user_token: + raise HTTPException(status_code=500, detail="Failed to get user token") + + bot_token = await self.daily_rest_helper.get_token(room.url) + if not bot_token: + raise HTTPException(status_code=500, detail="Failed to get bot token") + + async with self.lock: + self.pool.append( + {"room_url": room.url, "user_token": user_token, "bot_token": bot_token} + ) + + except Exception as e: + print(f"Error adding room to pool: {e}") + + async def get_room(self) -> Dict[str, str]: + """Retrieves a room from the pool and requests a new one to maintain the size.""" + async with self.lock: + if not self.pool: + raise HTTPException(status_code=503, detail="No available rooms") + + room = self.pool.pop(0) # Get first available room + + # Start a background task to replenish the pool + asyncio.create_task(self.add_room()) + + return room + + async def delete_room(self, room_url: str): + """Deletes a room when it is not needed anymore""" + await self.daily_rest_helper.delete_room_by_url(room_url) + + async def cleanup(self): + for rooms in self.pool: + room_url = rooms["room_url"] + await self.delete_room(room_url) + + +class BotManager: + """Manages bot subprocesses asynchronously.""" + + def __init__(self): + self.bot_procs: Dict[int, asyncio.subprocess.Process] = {} + self.room_mappings: Dict[int, str] = {} # Maps process ID to room URL + + async def start_bot(self, room_url: str, token: str) -> int: + bot_file = "single_bot" + command = f"python3 -m {bot_file} -u {room_url} -t {token}" + + try: + proc = await asyncio.create_subprocess_shell( + command, + cwd=os.path.dirname(os.path.abspath(__file__)), + ) + if proc.pid is None: + raise HTTPException(status_code=500, detail="Failed to get subprocess PID") + + self.bot_procs[proc.pid] = proc + self.room_mappings[proc.pid] = room_url + # Monitor the process and delete the room when it exits + asyncio.create_task(self._monitor_process(proc.pid)) + + return proc.pid + except Exception as e: + raise HTTPException(status_code=500, detail=f"Failed to start subprocess: {e}") + + async def _monitor_process(self, pid: int): + """Monitors a bot process and deletes the associated room when it exits.""" + proc = self.bot_procs.get(pid) + if proc: + await proc.wait() # Wait for the process to exit + room_url = self.room_mappings.pop(pid, None) + + if room_url: + await room_pool.delete_room(room_url) + print(f"Deleted room: {room_url}") + + del self.bot_procs[pid] + + async def cleanup(self): + """Terminates all running bot processes and deletes associated rooms.""" + for pid, proc in list(self.bot_procs.items()): + try: + proc.terminate() + await asyncio.wait_for(proc.wait(), timeout=5) + + room_url = self.room_mappings.pop(pid, None) + if room_url: + await room_pool.delete_room(room_url) # Delete room when process terminates + print(f"Deleted room: {room_url}") + + except asyncio.TimeoutError: + print(f"Process {pid} did not terminate in time.") + except Exception as e: + print(f"Error terminating process {pid}: {e}") + + # Clear remaining mappings + self.bot_procs.clear() + self.room_mappings.clear() + + +# Global instances +bot_manager = BotManager() +room_pool: RoomPool # Will be initialized in lifespan + + +@asynccontextmanager +async def lifespan(app: FastAPI): + """Handles FastAPI startup and shutdown.""" + global room_pool + aiohttp_session = aiohttp.ClientSession() + daily_rest_helper = DailyRESTHelper( + daily_api_key=os.getenv("DAILY_API_KEY", ""), + daily_api_url=os.getenv("DAILY_API_URL", "https://api.daily.co/v1"), + aiohttp_session=aiohttp_session, + ) + + room_pool = RoomPool(daily_rest_helper) + await room_pool.fill_pool(NUMBER_OF_ROOMS) # Fill pool on startup + + yield # Run app + + await bot_manager.cleanup() + await room_pool.cleanup() + await aiohttp_session.close() + + +# Initialize FastAPI app with lifespan manager +app = FastAPI(lifespan=lifespan) + +# Configure CORS to allow requests from any origin +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + + +@app.post("/connect") +async def bot_connect(request: Request) -> Dict[Any, Any]: + try: + room = await room_pool.get_room() + await bot_manager.start_bot(room["room_url"], room["bot_token"]) + except HTTPException as e: + return {"error": str(e)} + + return { + "room_url": room["room_url"], + "token": room["user_token"], + } + + +if __name__ == "__main__": + uvicorn.run(app, host="0.0.0.0", port=7860) diff --git a/examples/instant-voice/server/src/single_bot.py b/examples/instant-voice/server/src/single_bot.py new file mode 100644 index 000000000..e1e9df68a --- /dev/null +++ b/examples/instant-voice/server/src/single_bot.py @@ -0,0 +1,120 @@ +# +# Copyright (c) 2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# +import argparse +import asyncio +import os +import sys + +from dotenv import load_dotenv +from loguru import logger +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.processors.frameworks.rtvi import RTVIConfig, RTVIProcessor +from pipecat.services.gemini_multimodal_live import GeminiMultimodalLiveLLMService +from pipecat.transports.services.daily import DailyParams, DailyTransport + +load_dotenv(override=True) + +logger.remove(0) +logger.add(sys.stderr, level="DEBUG") + +SYSTEM_INSTRUCTION = f""" +"You are Gemini Chatbot, a friendly, helpful robot. + +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. Keep your responses brief. One or two sentences at most. +""" + + +def extract_arguments(): + parser = argparse.ArgumentParser(description="Instant Voice Example") + parser.add_argument( + "-u", "--url", type=str, required=True, help="URL of the Daily room to join" + ) + parser.add_argument( + "-t", "--token", type=str, required=False, help="Token of the Daily room to join" + ) + args, unknown = parser.parse_known_args() + url = args.url or os.getenv("DAILY_SAMPLE_ROOM_URL") + token = args.token + return url, token + + +async def main(): + room_url, token = extract_arguments() + print(f"room_url: {room_url}") + + daily_transport = DailyTransport( + room_url, + token, + "Instant voice Chatbot", + DailyParams( + audio_out_enabled=True, + vad_enabled=True, + vad_analyzer=SileroVADAnalyzer(), + vad_audio_passthrough=True, + ), + ) + + llm = GeminiMultimodalLiveLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + voice_id="Puck", # Aoede, Charon, Fenrir, Kore, Puck + transcribe_user_audio=True, + transcribe_model_audio=True, + system_instruction=SYSTEM_INSTRUCTION, + ) + + context = OpenAILLMContext() + context_aggregator = llm.create_context_aggregator(context) + + # RTVI events for Pipecat client UI + rtvi = RTVIProcessor(config=RTVIConfig(config=[]), transport=daily_transport) + + pipeline = Pipeline( + [ + daily_transport.input(), + context_aggregator.user(), + rtvi, + llm, # LLM + daily_transport.output(), + context_aggregator.assistant(), + ] + ) + + task = PipelineTask( + pipeline, + params=PipelineParams( + allow_interruptions=True, + observers=[rtvi.observer()], + ), + ) + + @rtvi.event_handler("on_client_ready") + async def on_client_ready(rtvi): + await rtvi.set_bot_ready() + + @daily_transport.event_handler("on_first_participant_joined") + async def on_first_participant_joined(transport, participant): + await task.queue_frames([context_aggregator.user().get_context_frame()]) + + @daily_transport.event_handler("on_participant_left") + async def on_participant_left(transport, participant, reason): + print(f"Participant left: {participant}") + await task.cancel() + + runner = PipelineRunner(handle_sigint=False) + + await runner.run(task) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/examples/local-input-select-stt/bot.py b/examples/local-input-select-stt/bot.py index 1cedbf96c..f472152b9 100644 --- a/examples/local-input-select-stt/bot.py +++ b/examples/local-input-select-stt/bot.py @@ -18,7 +18,7 @@ from pipecat.pipeline.runner import PipelineRunner from pipecat.pipeline.task import PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor from pipecat.services.whisper import Model, WhisperSTTService -from pipecat.transports.local.audio import LocalAudioTransport, LocalTransportParams +from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams load_dotenv(override=True) @@ -36,7 +36,7 @@ class TranscriptionLogger(FrameProcessor): async def main(input_device: int, output_device: int): transport = LocalAudioTransport( - LocalTransportParams( + LocalAudioTransportParams( audio_in_enabled=True, audio_out_enabled=False, input_device_index=input_device, diff --git a/examples/phone-chatbot/README.md b/examples/phone-chatbot/README.md index 68bb64bf5..65562dbc4 100644 --- a/examples/phone-chatbot/README.md +++ b/examples/phone-chatbot/README.md @@ -113,6 +113,7 @@ We have introduced support for Google's Gemini 2.0 Flash Lite model in this exam **Quick Start** To use the Gemini-based bot instead of OpenAI: + ```shell curl -X POST "http://localhost:7860/daily_gemini_start_bot" \ py pipecat -H "Content-Type: application/json" \ diff --git a/examples/phone-chatbot/bot_daily_gemini.py b/examples/phone-chatbot/bot_daily_gemini.py index cb44117f1..48cdedb70 100644 --- a/examples/phone-chatbot/bot_daily_gemini.py +++ b/examples/phone-chatbot/bot_daily_gemini.py @@ -7,7 +7,7 @@ import argparse import asyncio import os import sys -from pprint import pprint + from typing import Optional from dotenv import load_dotenv @@ -102,6 +102,7 @@ async def terminate_call( function_name, tool_call_id, args, llm: LLMService, context, result_callback ): """Function the bot can call to terminate the call upon completion of the call.""" + await llm.queue_frame(EndTaskFrame(), FrameDirection.UPSTREAM) diff --git a/examples/translation-chatbot/bot.py b/examples/translation-chatbot/bot.py index d35cf7af2..8d4ee851e 100644 --- a/examples/translation-chatbot/bot.py +++ b/examples/translation-chatbot/bot.py @@ -24,17 +24,15 @@ from pipecat.frames.frames import ( ) from pipecat.pipeline.pipeline import Pipeline from pipecat.pipeline.runner import PipelineRunner -from pipecat.pipeline.task import PipelineTask +from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.processors.frameworks.rtvi import RTVIObserver, RTVIProcessor from pipecat.processors.transcript_processor import TranscriptProcessor from pipecat.services.cartesia import CartesiaTTSService from pipecat.services.deepgram import DeepgramSTTService from pipecat.services.openai import OpenAILLMService -from pipecat.transports.services.daily import ( - DailyParams, - DailyTransport, -) +from pipecat.transports.services.daily import DailyParams, DailyTransport load_dotenv(override=True) @@ -166,21 +164,32 @@ async def main(): async def on_transcript_update(processor, frame): await transcript_handler.on_transcript_update(processor, frame) + rtvi = RTVIProcessor() + pipeline = Pipeline( [ transport.input(), + rtvi, stt, transcript.user(), # User transcripts tp, llm, tts, transport.output(), + transcript.assistant(), context_aggregator.assistant(), - transcript.assistant(), # Assistant transcripts ] ) - task = PipelineTask(pipeline) + task = PipelineTask( + pipeline, + PipelineParams( + allow_interruptions=False, # We don't want to interrupt the translator bot + enable_metrics=True, + enable_usage_metrics=True, + observers=[RTVIObserver(rtvi)], + ), + ) @transport.event_handler("on_first_participant_joined") async def on_first_participant_joined(transport, participant): diff --git a/examples/translation-chatbot/requirements.txt b/examples/translation-chatbot/requirements.txt index 6f05d3425..da1cbf0af 100644 --- a/examples/translation-chatbot/requirements.txt +++ b/examples/translation-chatbot/requirements.txt @@ -1,4 +1,4 @@ python-dotenv fastapi[all] -pipecat-ai[daily,openai,azure] +pipecat-ai[cartesia,daily,deepgram,openai,silero] aiohttp diff --git a/pyproject.toml b/pyproject.toml index 0578c9622..3c5d6262b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -55,7 +55,7 @@ elevenlabs = [ "websockets~=13.1" ] fal = [ "fal-client~=0.5.6" ] fish = [ "ormsgpack~=1.7.0", "websockets~=13.1" ] gladia = [ "websockets~=13.1" ] -google = [ "google-generativeai~=0.8.3", "google-cloud-texttospeech~=2.24.0", "google-genai~=1.0.0", "google-cloud-speech~=2.30.0" ] +google = [ "google-cloud-speech~=2.31.0", "google-cloud-texttospeech~=2.25.0", "google-genai~=1.2.0", "google-generativeai~=0.8.4" ] grok = [ "openai~=1.59.6" ] groq = [ "openai~=1.59.6" ] gstreamer = [ "pygobject~=3.50.0" ] diff --git a/src/pipecat/frames/frames.py b/src/pipecat/frames/frames.py index 09d0a93b0..c9b812a1c 100644 --- a/src/pipecat/frames/frames.py +++ b/src/pipecat/frames/frames.py @@ -565,6 +565,22 @@ class UserStoppedSpeakingFrame(SystemFrame): pass +@dataclass +class EmulateUserStartedSpeakingFrame(SystemFrame): + """Emitted by internal processors upstream to emulate VAD behavior when a + user starts speaking.""" + + pass + + +@dataclass +class EmulateUserStoppedSpeakingFrame(SystemFrame): + """Emitted by internal processors upstream to emulate VAD behavior when a + user stops speaking.""" + + pass + + @dataclass class BotInterruptionFrame(SystemFrame): """Emitted by when the bot should be interrupted. This will mainly cause the diff --git a/src/pipecat/processors/aggregators/llm_response.py b/src/pipecat/processors/aggregators/llm_response.py index 78db72dfb..2de3ebae4 100644 --- a/src/pipecat/processors/aggregators/llm_response.py +++ b/src/pipecat/processors/aggregators/llm_response.py @@ -4,9 +4,16 @@ # SPDX-License-Identifier: BSD 2-Clause License # -from typing import List, Optional, Type +import asyncio +import time +from abc import abstractmethod +from typing import List from pipecat.frames.frames import ( + CancelFrame, + EmulateUserStartedSpeakingFrame, + EmulateUserStoppedSpeakingFrame, + EndFrame, Frame, InterimTranscriptionFrame, LLMFullResponseEndFrame, @@ -15,6 +22,7 @@ from pipecat.frames.frames import ( LLMMessagesFrame, LLMMessagesUpdateFrame, LLMSetToolsFrame, + StartFrame, StartInterruptionFrame, TextFrame, TranscriptionFrame, @@ -28,121 +36,105 @@ from pipecat.processors.aggregators.openai_llm_context import ( from pipecat.processors.frame_processor import FrameDirection, FrameProcessor -class LLMResponseAggregator(FrameProcessor): +class BaseLLMResponseAggregator(FrameProcessor): + """This is the base class for all LLM response aggregators. These + aggregators process incoming frames and aggregate content until they are + ready to push the aggregation. In the case of a user, an aggregation might + be a full transcription received from the STT service. + + The LLM response aggregators also keep a store (e.g. a message list or an + LLM context) of the current conversation, that is, it stores the messages + said by the user or by the bot. + + """ + + def __init__(self, **kwargs): + super().__init__(**kwargs) + + @property + @abstractmethod + def messages(self) -> List[dict]: + """Returns the messages from the current conversation.""" + pass + + @property + @abstractmethod + def role(self) -> str: + """Returns the role (e.g. user, assistant...) for this aggregator.""" + pass + + @abstractmethod + def add_messages(self, messages): + """Add the given messages to the conversation.""" + pass + + @abstractmethod + def set_messages(self, messages): + """Reset the conversation with the given messages.""" + pass + + @abstractmethod + def set_tools(self, tools): + """Set LLM tools to be used in the current conversation.""" + pass + + @abstractmethod + def reset(self): + """Reset the internals of this aggregator. This should not modify the + internal messages.""" + pass + + @abstractmethod + async def push_aggregation(self): + pass + + +class LLMResponseAggregator(BaseLLMResponseAggregator): + """This is a base LLM aggregator that uses a simple list of messages to + store the conversation. It pushes `LLMMessagesFrame` as an aggregation + frame. + + """ + def __init__( self, *, messages: List[dict], - role: str, - start_frame, - end_frame, - accumulator_frame: Type[TextFrame], - interim_accumulator_frame: Optional[Type[TextFrame]] = None, - handle_interruptions: bool = False, - expect_stripped_words: bool = True, # if True, need to add spaces between words + role: str = "user", + **kwargs, ): - super().__init__() + super().__init__(**kwargs) self._messages = messages self._role = role - self._start_frame = start_frame - self._end_frame = end_frame - self._accumulator_frame = accumulator_frame - self._interim_accumulator_frame = interim_accumulator_frame - self._handle_interruptions = handle_interruptions - self._expect_stripped_words = expect_stripped_words - # Reset our accumulator state. - self._reset() + self._aggregation = "" + + self.reset() @property - def messages(self): + def messages(self) -> List[dict]: return self._messages @property - def role(self): + def role(self) -> str: return self._role - # - # Frame processor - # + def add_messages(self, messages): + self._messages.extend(messages) - # Use cases implemented: - # - # S: Start, E: End, T: Transcription, I: Interim, X: Text - # - # S E -> None - # S T E -> X - # S I T E -> X - # S I E T -> X - # S I E I T -> X - # S E T -> X - # S E I T -> X - # - # The following case would not be supported: - # - # S I E T1 I T2 -> X - # - # and T2 would be dropped. + def set_messages(self, messages): + self.reset() + self._messages.clear() + self._messages.extend(messages) - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) + def set_tools(self, tools): + pass - send_aggregation = False + def reset(self): + self._aggregation = "" - if isinstance(frame, self._start_frame): - self._aggregation = "" - self._aggregating = True - self._seen_start_frame = True - self._seen_end_frame = False - self._seen_interim_results = False - await self.push_frame(frame, direction) - elif isinstance(frame, self._end_frame): - self._seen_end_frame = True - self._seen_start_frame = False - - # We might have received the end frame but we might still be - # aggregating (i.e. we have seen interim results but not the final - # text). - self._aggregating = self._seen_interim_results or len(self._aggregation) == 0 - - # Send the aggregation if we are not aggregating anymore (i.e. no - # more interim results received). - send_aggregation = not self._aggregating - await self.push_frame(frame, direction) - elif isinstance(frame, self._accumulator_frame): - if self._aggregating: - if self._expect_stripped_words: - self._aggregation += f" {frame.text}" if self._aggregation else frame.text - else: - self._aggregation += frame.text - # We have recevied a complete sentence, so if we have seen the - # end frame and we were still aggregating, it means we should - # send the aggregation. - send_aggregation = self._seen_end_frame - - # We just got our final result, so let's reset interim results. - self._seen_interim_results = False - elif self._interim_accumulator_frame and isinstance(frame, self._interim_accumulator_frame): - self._seen_interim_results = True - elif self._handle_interruptions and isinstance(frame, StartInterruptionFrame): - await self._push_aggregation() - # Reset anyways - self._reset() - await self.push_frame(frame, direction) - elif isinstance(frame, LLMMessagesAppendFrame): - self._add_messages(frame.messages) - elif isinstance(frame, LLMMessagesUpdateFrame): - self._set_messages(frame.messages) - elif isinstance(frame, LLMSetToolsFrame): - self._set_tools(frame.tools) - else: - await self.push_frame(frame, direction) - - if send_aggregation: - await self._push_aggregation() - - async def _push_aggregation(self): + async def push_aggregation(self): if len(self._aggregation) > 0: self._messages.append({"role": self._role, "content": self._aggregation}) @@ -153,109 +145,27 @@ class LLMResponseAggregator(FrameProcessor): frame = LLMMessagesFrame(self._messages) await self.push_frame(frame) - # TODO-CB: Types - def _add_messages(self, messages): - self._messages.extend(messages) - def _set_messages(self, messages): - self._reset() - self._messages.clear() - self._messages.extend(messages) +class LLMContextResponseAggregator(BaseLLMResponseAggregator): + """This is a base LLM aggregator that uses an LLM context to store the + conversation. It pushes `OpenAILLMContextFrame` as an aggregation frame. - def _set_tools(self, tools): - # noop in the base class - pass - - def _reset(self): - self._aggregation = "" - self._aggregating = False - self._seen_start_frame = False - self._seen_end_frame = False - self._seen_interim_results = False - - -class LLMAssistantResponseAggregator(LLMResponseAggregator): - def __init__(self, messages: List[dict] = []): - super().__init__( - messages=messages, - role="assistant", - start_frame=LLMFullResponseStartFrame, - end_frame=LLMFullResponseEndFrame, - accumulator_frame=TextFrame, - handle_interruptions=True, - ) - - -class LLMUserResponseAggregator(LLMResponseAggregator): - def __init__(self, messages: List[dict] = []): - super().__init__( - messages=messages, - role="user", - start_frame=UserStartedSpeakingFrame, - end_frame=UserStoppedSpeakingFrame, - accumulator_frame=TranscriptionFrame, - interim_accumulator_frame=InterimTranscriptionFrame, - ) - - -class LLMFullResponseAggregator(FrameProcessor): - """This class aggregates Text frames until it receives a - LLMFullResponseEndFrame, then emits the concatenated text as - a single text frame. - - given the following frames: - - TextFrame("Hello,") - TextFrame(" world.") - TextFrame(" I am") - TextFrame(" an LLM.") - LLMFullResponseEndFrame()] - - this processor will yield nothing for the first 4 frames, then - - TextFrame("Hello, world. I am an LLM.") - LLMFullResponseEndFrame() - - when passed the last frame. - - >>> async def print_frames(aggregator, frame): - ... async for frame in aggregator.process_frame(frame): - ... if isinstance(frame, TextFrame): - ... print(frame.text) - ... else: - ... print(frame.__class__.__name__) - - >>> aggregator = LLMFullResponseAggregator() - >>> asyncio.run(print_frames(aggregator, TextFrame("Hello,"))) - >>> asyncio.run(print_frames(aggregator, TextFrame(" world."))) - >>> asyncio.run(print_frames(aggregator, TextFrame(" I am"))) - >>> asyncio.run(print_frames(aggregator, TextFrame(" an LLM."))) - >>> asyncio.run(print_frames(aggregator, LLMFullResponseEndFrame())) - Hello, world. I am an LLM. - LLMFullResponseEndFrame """ - def __init__(self): - super().__init__() - self._aggregation = "" - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - if isinstance(frame, TextFrame): - self._aggregation += frame.text - elif isinstance(frame, LLMFullResponseEndFrame): - await self.push_frame(TextFrame(self._aggregation)) - await self.push_frame(frame) - self._aggregation = "" - else: - await self.push_frame(frame, direction) - - -class LLMContextAggregator(LLMResponseAggregator): - def __init__(self, *, context: OpenAILLMContext, **kwargs): + def __init__(self, *, context: OpenAILLMContext, role: str, **kwargs): super().__init__(**kwargs) self._context = context + self._role = role + + self._aggregation = "" + + @property + def messages(self) -> List[dict]: + return self._context.get_messages() + + @property + def role(self) -> str: + return self._role @property def context(self): @@ -264,23 +174,25 @@ class LLMContextAggregator(LLMResponseAggregator): def get_context_frame(self) -> OpenAILLMContextFrame: return OpenAILLMContextFrame(context=self._context) - async def push_context_frame(self): + async def push_context_frame(self, direction: FrameDirection = FrameDirection.DOWNSTREAM): frame = self.get_context_frame() - await self.push_frame(frame) + await self.push_frame(frame, direction) - # TODO-CB: Types - def _add_messages(self, messages): + def add_messages(self, messages): self._context.add_messages(messages) - def _set_messages(self, messages): + def set_messages(self, messages): self._context.set_messages(messages) - def _set_tools(self, tools: List): + def set_tools(self, tools: List): self._context.set_tools(tools) - async def _push_aggregation(self): + def reset(self): + self._aggregation = "" + + async def push_aggregation(self): if len(self._aggregation) > 0: - self._context.add_message({"role": self._role, "content": self._aggregation}) + self._context.add_message({"role": self.role, "content": self._aggregation}) # Reset the aggregation. Reset it before pushing it down, otherwise # if the tasks gets cancelled we won't be able to clear things up. @@ -290,31 +202,239 @@ class LLMContextAggregator(LLMResponseAggregator): await self.push_frame(frame) # Reset our accumulator state. - self._reset() + self.reset() -class LLMAssistantContextAggregator(LLMContextAggregator): - def __init__(self, context: OpenAILLMContext, *, expect_stripped_words: bool = True): - super().__init__( - messages=[], - context=context, - role="assistant", - start_frame=LLMFullResponseStartFrame, - end_frame=LLMFullResponseEndFrame, - accumulator_frame=TextFrame, - handle_interruptions=True, - expect_stripped_words=expect_stripped_words, - ) +class LLMUserContextAggregator(LLMContextResponseAggregator): + """This is a user LLM aggregator that uses an LLM context to store the + conversation. It aggregates transcriptions from the STT service and it has + logic to handle multiple scenarios where transcriptions are received between + VAD events (`UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame`) or + even outside or no VAD events at all. + + """ + + def __init__( + self, + context: OpenAILLMContext, + aggregation_timeout: float = 1.0, + bot_interruption_timeout: float = 2.0, + **kwargs, + ): + super().__init__(context=context, role="user", **kwargs) + self._aggregation_timeout = aggregation_timeout + self._bot_interruption_timeout = bot_interruption_timeout + + self._seen_interim_results = False + self._user_speaking = False + self._last_user_speaking_time = 0 + self._emulating_vad = False + + self._aggregation_event = asyncio.Event() + self._aggregation_task = None + + self.reset() + + def reset(self): + super().reset() + self._seen_interim_results = False + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + + if isinstance(frame, StartFrame): + await self._start(frame) + await self.push_frame(frame, direction) + elif isinstance(frame, EndFrame): + await self._stop(frame) + await self.push_frame(frame, direction) + elif isinstance(frame, CancelFrame): + await self._cancel(frame) + await self.push_frame(frame, direction) + elif isinstance(frame, UserStartedSpeakingFrame): + await self._handle_user_started_speaking(frame) + await self.push_frame(frame, direction) + elif isinstance(frame, UserStoppedSpeakingFrame): + await self._handle_user_stopped_speaking(frame) + await self.push_frame(frame, direction) + elif isinstance(frame, TranscriptionFrame): + await self._handle_transcription(frame) + elif isinstance(frame, InterimTranscriptionFrame): + await self._handle_interim_transcription(frame) + elif isinstance(frame, LLMMessagesAppendFrame): + self.add_messages(frame.messages) + elif isinstance(frame, LLMMessagesUpdateFrame): + self.set_messages(frame.messages) + elif isinstance(frame, LLMSetToolsFrame): + self.set_tools(frame.tools) + else: + await self.push_frame(frame, direction) + + async def _start(self, frame: StartFrame): + self._create_aggregation_task() + + async def _stop(self, frame: EndFrame): + await self._cancel_aggregation_task() + + async def _cancel(self, frame: CancelFrame): + await self._cancel_aggregation_task() + + async def _handle_user_started_speaking(self, _: UserStartedSpeakingFrame): + self._last_user_speaking_time = time.time() + self._user_speaking = True + + async def _handle_user_stopped_speaking(self, _: UserStoppedSpeakingFrame): + self._last_user_speaking_time = time.time() + self._user_speaking = False + if not self._seen_interim_results: + await self.push_aggregation() + + async def _handle_transcription(self, frame: TranscriptionFrame): + self._aggregation += f" {frame.text}" if self._aggregation else frame.text + # We just got a final result, so let's reset interim results. + self._seen_interim_results = False + # Reset aggregation timer. + self._aggregation_event.set() + + async def _handle_interim_transcription(self, _: InterimTranscriptionFrame): + self._seen_interim_results = True + # Reset aggregation timer. + self._aggregation_event.set() + + def _create_aggregation_task(self): + self._aggregation_task = self.create_task(self._aggregation_task_handler()) + + async def _cancel_aggregation_task(self): + if self._aggregation_task: + await self.cancel_task(self._aggregation_task) + self._aggregation_task = None + + async def _aggregation_task_handler(self): + while True: + try: + await asyncio.wait_for(self._aggregation_event.wait(), self._aggregation_timeout) + await self._maybe_push_bot_interruption() + except asyncio.TimeoutError: + if not self._user_speaking: + await self.push_aggregation() + + # If we are emulating VAD we still need to send the user stopped + # speaking frame. + if self._emulating_vad: + await self.push_frame( + EmulateUserStoppedSpeakingFrame(), FrameDirection.UPSTREAM + ) + self._emulating_vad = False + finally: + self._aggregation_event.clear() + + async def _maybe_push_bot_interruption(self): + """If the user stopped speaking a while back and we got a transcription + frame we might want to interrupt the bot. + + """ + if not self._user_speaking: + diff_time = time.time() - self._last_user_speaking_time + if diff_time > self._bot_interruption_timeout: + # If we reach this case we received a transcription but VAD was + # not able to detect voice (e.g. when you whisper a short + # utterance). So, we need to emulate VAD (i.e. user + # start/stopped speaking). + await self.push_frame(EmulateUserStartedSpeakingFrame(), FrameDirection.UPSTREAM) + self._emulating_vad = True + + # Reset time so we don't interrupt again right away. + self._last_user_speaking_time = time.time() -class LLMUserContextAggregator(LLMContextAggregator): - def __init__(self, context: OpenAILLMContext): - super().__init__( - messages=[], - context=context, - role="user", - start_frame=UserStartedSpeakingFrame, - end_frame=UserStoppedSpeakingFrame, - accumulator_frame=TranscriptionFrame, - interim_accumulator_frame=InterimTranscriptionFrame, - ) +class LLMAssistantContextAggregator(LLMContextResponseAggregator): + """This is an assistant LLM aggregator that uses an LLM context to store the + conversation. It aggregates text frames received between + `LLMFullResponseStartFrame` and `LLMFullResponseEndFrame`. + + """ + + def __init__(self, context: OpenAILLMContext, *, expect_stripped_words: bool = True, **kwargs): + super().__init__(context=context, role="assistant", **kwargs) + self._expect_stripped_words = expect_stripped_words + + self._started = False + + self.reset() + + async def process_frame(self, frame: Frame, direction: FrameDirection): + await super().process_frame(frame, direction) + + if isinstance(frame, StartInterruptionFrame): + await self.push_aggregation() + # Reset anyways + self.reset() + await self.push_frame(frame, direction) + elif isinstance(frame, LLMFullResponseStartFrame): + await self._handle_llm_start(frame) + elif isinstance(frame, LLMFullResponseEndFrame): + await self._handle_llm_end(frame) + elif isinstance(frame, TextFrame): + await self._handle_text(frame) + elif isinstance(frame, LLMMessagesAppendFrame): + self.add_messages(frame.messages) + elif isinstance(frame, LLMMessagesUpdateFrame): + self.set_messages(frame.messages) + elif isinstance(frame, LLMSetToolsFrame): + self.set_tools(frame.tools) + else: + await self.push_frame(frame, direction) + + async def _handle_llm_start(self, _: LLMFullResponseStartFrame): + self._started = True + + async def _handle_llm_end(self, _: LLMFullResponseEndFrame): + self._started = False + await self.push_aggregation() + + async def _handle_text(self, frame: TextFrame): + if not self._started: + return + + if self._expect_stripped_words: + self._aggregation += f" {frame.text}" if self._aggregation else frame.text + else: + self._aggregation += frame.text + + +class LLMUserResponseAggregator(LLMUserContextAggregator): + def __init__(self, messages: List[dict] = [], **kwargs): + super().__init__(context=OpenAILLMContext(messages), **kwargs) + + async def push_aggregation(self): + if len(self._aggregation) > 0: + self._context.add_message({"role": self.role, "content": self._aggregation}) + + # Reset the aggregation. Reset it before pushing it down, otherwise + # if the tasks gets cancelled we won't be able to clear things up. + self._aggregation = "" + + frame = LLMMessagesFrame(self._context.messages) + await self.push_frame(frame) + + # Reset our accumulator state. + self.reset() + + +class LLMAssistantResponseAggregator(LLMAssistantContextAggregator): + def __init__(self, messages: List[dict] = [], **kwargs): + super().__init__(context=OpenAILLMContext(messages), **kwargs) + + async def push_aggregation(self): + if len(self._aggregation) > 0: + self._context.add_message({"role": self.role, "content": self._aggregation}) + + # Reset the aggregation. Reset it before pushing it down, otherwise + # if the tasks gets cancelled we won't be able to clear things up. + self._aggregation = "" + + frame = LLMMessagesFrame(self._context.messages) + await self.push_frame(frame) + + # Reset our accumulator state. + self.reset() diff --git a/src/pipecat/processors/aggregators/user_response.py b/src/pipecat/processors/aggregators/user_response.py index 0e2c09ebc..6998fe200 100644 --- a/src/pipecat/processors/aggregators/user_response.py +++ b/src/pipecat/processors/aggregators/user_response.py @@ -4,131 +4,15 @@ # SPDX-License-Identifier: BSD 2-Clause License # -from typing import Optional - -from pipecat.frames.frames import ( - Frame, - InterimTranscriptionFrame, - StartInterruptionFrame, - TextFrame, - TranscriptionFrame, - UserStartedSpeakingFrame, - UserStoppedSpeakingFrame, -) -from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.frames.frames import TextFrame +from pipecat.processors.aggregators.llm_response import LLMUserResponseAggregator -class ResponseAggregator(FrameProcessor): - """This frame processor aggregates frames between a start and an end frame - into complete text frame sentences. +class UserResponseAggregator(LLMUserResponseAggregator): + def __init__(self, **kwargs): + super().__init__(**kwargs) - For example, frame input/output: - UserStartedSpeakingFrame() -> None - TranscriptionFrame("Hello,") -> None - TranscriptionFrame(" world.") -> None - UserStoppedSpeakingFrame() -> TextFrame("Hello world.") - - Doctest: FIXME to work with asyncio - >>> async def print_frames(aggregator, frame): - ... async for frame in aggregator.process_frame(frame): - ... if isinstance(frame, TextFrame): - ... print(frame.text) - - >>> aggregator = ResponseAggregator(start_frame = UserStartedSpeakingFrame, - ... end_frame=UserStoppedSpeakingFrame, - ... accumulator_frame=TranscriptionFrame, - ... pass_through=False) - >>> asyncio.run(print_frames(aggregator, UserStartedSpeakingFrame())) - >>> asyncio.run(print_frames(aggregator, TranscriptionFrame("Hello,", 1, 1))) - >>> asyncio.run(print_frames(aggregator, TranscriptionFrame("world.", 1, 2))) - >>> asyncio.run(print_frames(aggregator, UserStoppedSpeakingFrame())) - Hello, world. - - """ - - def __init__( - self, - *, - start_frame, - end_frame, - accumulator_frame: TextFrame, - interim_accumulator_frame: Optional[TextFrame] = None, - ): - super().__init__() - - self._start_frame = start_frame - self._end_frame = end_frame - self._accumulator_frame = accumulator_frame - self._interim_accumulator_frame = interim_accumulator_frame - - # Reset our accumulator state. - self._reset() - - # - # Frame processor - # - - # Use cases implemented: - # - # S: Start, E: End, T: Transcription, I: Interim, X: Text - # - # S E -> None - # S T E -> X - # S I T E -> X - # S I E T -> X - # S I E I T -> X - # S E T -> X - # S E I T -> X - # - # The following case would not be supported: - # - # S I E T1 I T2 -> X - # - # and T2 would be dropped. - - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - send_aggregation = False - - if isinstance(frame, self._start_frame): - self._aggregating = True - self._seen_start_frame = True - self._seen_end_frame = False - self._seen_interim_results = False - await self.push_frame(frame, direction) - elif isinstance(frame, self._end_frame): - self._seen_end_frame = True - self._seen_start_frame = False - - # We might have received the end frame but we might still be - # aggregating (i.e. we have seen interim results but not the final - # text). - self._aggregating = self._seen_interim_results or len(self._aggregation) == 0 - - # Send the aggregation if we are not aggregating anymore (i.e. no - # more interim results received). - send_aggregation = not self._aggregating - await self.push_frame(frame, direction) - elif isinstance(frame, self._accumulator_frame): - if self._aggregating: - self._aggregation += f" {frame.text}" - # We have recevied a complete sentence, so if we have seen the - # end frame and we were still aggregating, it means we should - # send the aggregation. - send_aggregation = self._seen_end_frame - - # We just got our final result, so let's reset interim results. - self._seen_interim_results = False - elif self._interim_accumulator_frame and isinstance(frame, self._interim_accumulator_frame): - self._seen_interim_results = True - else: - await self.push_frame(frame, direction) - - if send_aggregation: - await self._push_aggregation() - - async def _push_aggregation(self): + async def push_aggregation(self): if len(self._aggregation) > 0: frame = TextFrame(self._aggregation.strip()) @@ -139,21 +23,4 @@ class ResponseAggregator(FrameProcessor): await self.push_frame(frame) # Reset our accumulator state. - self._reset() - - def _reset(self): - self._aggregation = "" - self._aggregating = False - self._seen_start_frame = False - self._seen_end_frame = False - self._seen_interim_results = False - - -class UserResponseAggregator(ResponseAggregator): - def __init__(self): - super().__init__( - start_frame=UserStartedSpeakingFrame, - end_frame=UserStoppedSpeakingFrame, - accumulator_frame=TranscriptionFrame, - interim_accumulator_frame=InterimTranscriptionFrame, - ) + self.reset() diff --git a/src/pipecat/processors/filters/stt_mute_filter.py b/src/pipecat/processors/filters/stt_mute_filter.py index fb1753263..3c1ae53af 100644 --- a/src/pipecat/processors/filters/stt_mute_filter.py +++ b/src/pipecat/processors/filters/stt_mute_filter.py @@ -23,6 +23,7 @@ from pipecat.frames.frames import ( Frame, FunctionCallInProgressFrame, FunctionCallResultFrame, + InputAudioRawFrame, StartFrame, StartInterruptionFrame, StopInterruptionFrame, @@ -185,13 +186,14 @@ class STTMuteFilter(FrameProcessor): StopInterruptionFrame, UserStartedSpeakingFrame, UserStoppedSpeakingFrame, + InputAudioRawFrame, ), ): # Only pass VAD-related frames when not muted if not self.is_muted: await self.push_frame(frame, direction) else: - logger.debug(f"{frame.__class__.__name__} suppressed - STT currently muted") + logger.trace(f"{frame.__class__.__name__} suppressed - STT currently muted") else: # Pass all other frames through await self.push_frame(frame, direction) diff --git a/src/pipecat/processors/frame_processor.py b/src/pipecat/processors/frame_processor.py index 3fb515a87..f27c6d6c2 100644 --- a/src/pipecat/processors/frame_processor.py +++ b/src/pipecat/processors/frame_processor.py @@ -73,10 +73,11 @@ class FrameProcessor: self._metrics.set_processor_name(self.name) # Processors have an input queue. The input queue will be processed - # immediately (default) or it will block if `pause_processing_frames()` is - # called. To resume processing frames we need to call - # `resume_processing_frames()`. + # immediately (default) or it will block if `pause_processing_frames()` + # is called. To resume processing frames we need to call + # `resume_processing_frames()` which will wake up the event. self.__should_block_frames = False + self.__input_event = asyncio.Event() self.__input_frame_task: Optional[asyncio.Task] = None # Every processor in Pipecat should only output frames from a single @@ -335,8 +336,8 @@ class FrameProcessor: def __create_input_task(self): if not self.__input_frame_task: self.__should_block_frames = False + self.__input_event.clear() self.__input_queue = asyncio.Queue() - self.__input_event = asyncio.Event() self.__input_frame_task = self.create_task(self.__input_frame_task_handler()) async def __cancel_input_task(self): diff --git a/src/pipecat/services/ai_services.py b/src/pipecat/services/ai_services.py index b8d223176..05c637126 100644 --- a/src/pipecat/services/ai_services.py +++ b/src/pipecat/services/ai_services.py @@ -15,6 +15,7 @@ from loguru import logger from pipecat.audio.utils import calculate_audio_volume, exp_smoothing from pipecat.frames.frames import ( AudioRawFrame, + BotStoppedSpeakingFrame, CancelFrame, EndFrame, ErrorFrame, @@ -75,13 +76,13 @@ class AIService(FrameProcessor): ) for key, value in settings.items(): - print("Update request for:", key, value) + logger.debug("Update request for:", key, value) if key in self._settings: logger.info(f"Updating LLM setting {key} to: [{value}]") self._settings[key] = value elif key in SessionProperties.model_fields: - print("Attempting to update", key, value) + logger.debug("Attempting to update", key, value) try: from pipecat.services.openai_realtime_beta.events import ( @@ -174,6 +175,7 @@ class LLMService(AIService): f = self._callbacks[None] else: return None + await self.call_start_function(context, function_name) await context.call_function( f, function_name=function_name, @@ -207,11 +209,13 @@ class TTSService(AIService): # if True, TTSService will push TTSStoppedFrames, otherwise subclass must do it push_stop_frames: bool = False, # if push_stop_frames is True, wait for this idle period before pushing TTSStoppedFrame - stop_frame_timeout_s: float = 1.0, + stop_frame_timeout_s: float = 2.0, # if True, TTSService will push silence audio frames after TTSStoppedFrame push_silence_after_stop: bool = False, # if push_silence_after_stop is True, send this amount of audio silence silence_time_s: float = 2.0, + # if True, we will pause processing frames while we are receiving audio + pause_frame_processing: bool = False, # TTS output sample rate sample_rate: Optional[int] = None, text_filter: Optional[BaseTextFilter] = None, @@ -224,6 +228,7 @@ class TTSService(AIService): self._stop_frame_timeout_s: float = stop_frame_timeout_s self._push_silence_after_stop: bool = push_silence_after_stop self._silence_time_s: float = silence_time_s + self._pause_frame_processing: bool = pause_frame_processing self._init_sample_rate = sample_rate self._sample_rate = 0 self._voice_id: str = "" @@ -234,6 +239,7 @@ class TTSService(AIService): self._stop_frame_queue: asyncio.Queue = asyncio.Queue() self._current_sentence: str = "" + self._processing_text: bool = False @property def sample_rate(self) -> int: @@ -299,6 +305,7 @@ class TTSService(AIService): async def process_frame(self, frame: Frame, direction: FrameDirection): await super().process_frame(frame, direction) + if ( isinstance(frame, TextFrame) and not isinstance(frame, InterimTranscriptionFrame) @@ -307,9 +314,16 @@ class TTSService(AIService): await self._process_text_frame(frame) elif isinstance(frame, StartInterruptionFrame): await self._handle_interruption(frame, direction) + await self.push_frame(frame, direction) elif isinstance(frame, (LLMFullResponseEndFrame, EndFrame)): + # We pause processing incoming frames if the LLM response included + # text (it might be that it's only a function calling response). We + # pause to avoid audio overlapping. + await self._maybe_pause_frame_processing() + sentence = self._current_sentence self._current_sentence = "" + self._processing_text = False await self._push_tts_frames(sentence) if isinstance(frame, LLMFullResponseEndFrame): if self._push_text_frames: @@ -318,9 +332,16 @@ class TTSService(AIService): await self.push_frame(frame, direction) elif isinstance(frame, TTSSpeakFrame): await self._push_tts_frames(frame.text) + # We pause processing incoming frames because we are sending data to + # the TTS. We pause to avoid audio overlapping. + await self._maybe_pause_frame_processing() await self.flush_audio() + self._processing_text = False elif isinstance(frame, TTSUpdateSettingsFrame): await self._update_settings(frame.settings) + elif isinstance(frame, BotStoppedSpeakingFrame): + await self._maybe_resume_frame_processing() + await self.push_frame(frame, direction) else: await self.push_frame(frame, direction) @@ -347,9 +368,17 @@ class TTSService(AIService): async def _handle_interruption(self, frame: StartInterruptionFrame, direction: FrameDirection): self._current_sentence = "" + self._processing_text = False if self._text_filter: self._text_filter.handle_interruption() - await self.push_frame(frame, direction) + + async def _maybe_pause_frame_processing(self): + if self._processing_text and self._pause_frame_processing: + await self.pause_processing_frames() + + async def _maybe_resume_frame_processing(self): + if self._pause_frame_processing: + await self.resume_processing_frames() async def _process_text_frame(self, frame: TextFrame): text: Optional[str] = None @@ -371,6 +400,11 @@ class TTSService(AIService): if not text.strip(): return + # This is just a flag that indicates if we sent something to the TTS + # service. It will be cleared if we sent text because of a TTSSpeakFrame + # or when we received an LLMFullResponseEndFrame + self._processing_text = True + await self.start_processing_metrics() if self._text_filter: self._text_filter.reset_interruption() @@ -419,7 +453,7 @@ class WordTTSService(TTSService): async def start(self, frame: StartFrame): await super().start(frame) - await self._create_words_task() + self._create_words_task() async def stop(self, frame: EndFrame): await super().stop(frame) @@ -439,7 +473,7 @@ class WordTTSService(TTSService): await super()._handle_interruption(frame, direction) self.reset_word_timestamps() - async def _create_words_task(self): + def _create_words_task(self): self._words_task = self.create_task(self._words_task_handler()) async def _stop_words_task(self): @@ -469,6 +503,115 @@ class WordTTSService(TTSService): self._words_queue.task_done() +class AudioContextWordTTSService(WordTTSService): + """This services allow us to send multiple TTS request to the services. Each + request could be multiple sentences long which are grouped by context. For + this to work, the TTS service needs to support handling multiple requests at + once (i.e. multiple simultaneous contexts). + + The audio received from the TTS will be played in context order. That is, if + we requested audio for a context "A" and then audio for context "B", the + audio from context ID "A" will be played first. + + """ + + def __init__(self, **kwargs): + super().__init__(**kwargs) + self._contexts_queue = asyncio.Queue() + self._contexts: Dict[str, asyncio.Queue] = {} + self._audio_context_task = None + + async def create_audio_context(self, context_id: str): + """Create a new audio context.""" + await self._contexts_queue.put(context_id) + self._contexts[context_id] = asyncio.Queue() + logger.trace(f"{self} created audio context {context_id}") + + async def append_to_audio_context(self, context_id: str, frame: TTSAudioRawFrame): + """Append audio to an existing context.""" + if self.audio_context_available(context_id): + logger.trace(f"{self} appending audio {frame} to audio context {context_id}") + await self._contexts[context_id].put(frame) + else: + logger.warning(f"{self} unable to append audio to context {context_id}") + + async def remove_audio_context(self, context_id: str): + """Remove an existing audio context.""" + if self.audio_context_available(context_id): + # We just mark the audio context for deletion by appending + # None. Once we reach None while handling audio we know we can + # safely remove the context. + logger.trace(f"{self} marking audio context {context_id} for deletion") + await self._contexts[context_id].put(None) + else: + logger.warning(f"{self} unable to remove context {context_id}") + + def audio_context_available(self, context_id: str) -> bool: + """Checks whether the given audio context is registered.""" + return context_id in self._contexts + + async def start(self, frame: StartFrame): + await super().start(frame) + self._create_audio_context_task() + + async def stop(self, frame: EndFrame): + await super().stop(frame) + await self._stop_audio_context_task() + + async def cancel(self, frame: CancelFrame): + await super().cancel(frame) + await self._stop_audio_context_task() + + async def _handle_interruption(self, frame: StartInterruptionFrame, direction: FrameDirection): + await super()._handle_interruption(frame, direction) + await self._stop_audio_context_task() + self._create_audio_context_task() + + def _create_audio_context_task(self): + self._contexts_queue = asyncio.Queue() + self._contexts: Dict[str, asyncio.Queue] = {} + self._audio_context_task = self.create_task(self._audio_context_task_handler()) + + async def _stop_audio_context_task(self): + if self._audio_context_task: + await self.cancel_task(self._audio_context_task) + self._audio_context_task = None + + async def _audio_context_task_handler(self): + """In this task we process audio contexts in order.""" + while True: + context_id = await self._contexts_queue.get() + + # Process the audio context until the context doesn't have more + # audio available (i.e. we find None). + await self._handle_audio_context(context_id) + + # We just finished processing the context, so we can safely remove it. + del self._contexts[context_id] + self._contexts_queue.task_done() + + # Append some silence between sentences. + silence = b"\x00" * self.sample_rate + frame = TTSAudioRawFrame(audio=silence, sample_rate=self.sample_rate, num_channels=1) + await self.push_frame(frame) + + async def _handle_audio_context(self, context_id: str): + # If we don't receive any audio during this time, we consider the context finished. + AUDIO_CONTEXT_TIMEOUT = 3.0 + queue = self._contexts[context_id] + running = True + while running: + try: + frame = await asyncio.wait_for(queue.get(), timeout=AUDIO_CONTEXT_TIMEOUT) + if frame: + await self.push_frame(frame) + running = frame is not None + except asyncio.TimeoutError: + # We didn't get audio, so let's consider this context finished. + logger.trace(f"{self} time out on audio context {context_id}") + break + + class STTService(AIService): """STTService is a base class for speech-to-text services.""" @@ -577,7 +720,7 @@ class SegmentedSTTService(STTService): self._smoothing_factor = 0.2 self._prev_volume = 0 - async def process_audio_frame(self, frame: AudioRawFrame): + async def process_audio_frame(self, frame: AudioRawFrame, direction: FrameDirection): # Try to filter out empty background noise volume = self._get_smoothed_volume(frame) if volume >= self._min_volume: diff --git a/src/pipecat/services/anthropic.py b/src/pipecat/services/anthropic.py index a593ced89..80235199b 100644 --- a/src/pipecat/services/anthropic.py +++ b/src/pipecat/services/anthropic.py @@ -126,9 +126,11 @@ class AnthropicLLMService(LLMService): def create_context_aggregator( context: OpenAILLMContext, *, assistant_expect_stripped_words: bool = True ) -> AnthropicContextAggregatorPair: + if isinstance(context, OpenAILLMContext): + context = AnthropicLLMContext.from_openai_context(context) user = AnthropicUserContextAggregator(context) assistant = AnthropicAssistantContextAggregator( - user, expect_stripped_words=assistant_expect_stripped_words + context, expect_stripped_words=assistant_expect_stripped_words ) return AnthropicContextAggregatorPair(_user=user, _assistant=assistant) @@ -651,11 +653,8 @@ class AnthropicLLMContext(OpenAILLMContext): class AnthropicUserContextAggregator(LLMUserContextAggregator): - def __init__(self, context: OpenAILLMContext | AnthropicLLMContext): - super().__init__(context=context) - - if isinstance(context, OpenAILLMContext): - self._context = AnthropicLLMContext.from_openai_context(context) + def __init__(self, context: OpenAILLMContext | AnthropicLLMContext, **kwargs): + super().__init__(context=context, **kwargs) async def process_frame(self, frame, direction): await super().process_frame(frame, direction) @@ -703,9 +702,8 @@ class AnthropicUserContextAggregator(LLMUserContextAggregator): class AnthropicAssistantContextAggregator(LLMAssistantContextAggregator): - def __init__(self, user_context_aggregator: AnthropicUserContextAggregator, **kwargs): - super().__init__(context=user_context_aggregator._context, **kwargs) - self._user_context_aggregator = user_context_aggregator + def __init__(self, context: OpenAILLMContext | AnthropicLLMContext, **kwargs): + super().__init__(context=context, **kwargs) self._function_call_in_progress = None self._function_call_result = None self._pending_image_frame_message = None @@ -725,7 +723,7 @@ class AnthropicAssistantContextAggregator(LLMAssistantContextAggregator): ): self._function_call_in_progress = None self._function_call_result = frame - await self._push_aggregation() + await self.push_aggregation() else: logger.warning( "FunctionCallResultFrame tool_call_id != InProgressFrame tool_call_id" @@ -734,9 +732,9 @@ class AnthropicAssistantContextAggregator(LLMAssistantContextAggregator): self._function_call_result = None elif isinstance(frame, AnthropicImageMessageFrame): self._pending_image_frame_message = frame - await self._push_aggregation() + await self.push_aggregation() - async def _push_aggregation(self): + async def push_aggregation(self): if not ( self._aggregation or self._function_call_result or self._pending_image_frame_message ): @@ -746,7 +744,7 @@ class AnthropicAssistantContextAggregator(LLMAssistantContextAggregator): properties: Optional[FunctionCallResultProperties] = None aggregation = self._aggregation - self._reset() + self.reset() try: if self._function_call_result: @@ -799,15 +797,14 @@ class AnthropicAssistantContextAggregator(LLMAssistantContextAggregator): run_llm = True if run_llm: - await self._user_context_aggregator.push_context_frame() + await self.push_context_frame(FrameDirection.UPSTREAM) # Emit the on_context_updated callback once the function call result is added to the context if properties and properties.on_context_updated is not None: await properties.on_context_updated() # Push context frame - frame = OpenAILLMContextFrame(self._context) - await self.push_frame(frame) + await self.push_context_frame() # Push timestamp frame with current time timestamp_frame = OpenAILLMContextAssistantTimestampFrame(timestamp=time_now_iso8601()) diff --git a/src/pipecat/services/cartesia.py b/src/pipecat/services/cartesia.py index d5ea46a30..67fc67ebf 100644 --- a/src/pipecat/services/cartesia.py +++ b/src/pipecat/services/cartesia.py @@ -27,7 +27,7 @@ from pipecat.frames.frames import ( TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.ai_services import TTSService, WordTTSService +from pipecat.services.ai_services import AudioContextWordTTSService, TTSService from pipecat.services.websocket_service import WebsocketService from pipecat.transcriptions.language import Language @@ -75,7 +75,7 @@ def language_to_cartesia_language(language: Language) -> Optional[str]: return result -class CartesiaTTSService(WordTTSService, WebsocketService): +class CartesiaTTSService(AudioContextWordTTSService, WebsocketService): class InputParams(BaseModel): language: Optional[Language] = Language.EN speed: Optional[Union[str, float]] = "" @@ -105,10 +105,11 @@ class CartesiaTTSService(WordTTSService, WebsocketService): # if we're interrupted. Cartesia gives us word-by-word timestamps. We # can use those to generate text frames ourselves aligned with the # playout timing of the audio! - WordTTSService.__init__( + AudioContextWordTTSService.__init__( self, aggregate_sentences=True, push_text_frames=False, + pause_frame_processing=True, sample_rate=sample_rate, **kwargs, ) @@ -191,12 +192,12 @@ class CartesiaTTSService(WordTTSService, WebsocketService): self._receive_task = self.create_task(self._receive_task_handler(self.push_error)) async def _disconnect(self): - await self._disconnect_websocket() - if self._receive_task: await self.cancel_task(self._receive_task) self._receive_task = None + await self._disconnect_websocket() + async def _connect_websocket(self): try: logger.debug("Connecting to Cartesia") @@ -239,21 +240,19 @@ class CartesiaTTSService(WordTTSService, WebsocketService): logger.trace(f"{self}: flushing audio") msg = self._build_msg(text="", continue_transcript=False) await self._websocket.send(msg) + self._context_id = None async def _receive_messages(self): async for message in self._get_websocket(): msg = json.loads(message) - if not msg or msg["context_id"] != self._context_id: + if not msg or not self.audio_context_available(msg["context_id"]): continue if msg["type"] == "done": await self.stop_ttfb_metrics() - # Unset _context_id but not the _context_id_start_timestamp - # because we are likely still playing out audio and need the - # timestamp to set send context frames. - self._context_id = None await self.add_word_timestamps( [("TTSStoppedFrame", 0), ("LLMFullResponseEndFrame", 0), ("Reset", 0)] ) + await self.remove_audio_context(msg["context_id"]) elif msg["type"] == "timestamps": await self.add_word_timestamps( list(zip(msg["word_timestamps"]["words"], msg["word_timestamps"]["start"])) @@ -266,28 +265,16 @@ class CartesiaTTSService(WordTTSService, WebsocketService): sample_rate=self.sample_rate, num_channels=1, ) - await self.push_frame(frame) + await self.append_to_audio_context(msg["context_id"], frame) elif msg["type"] == "error": logger.error(f"{self} error: {msg}") await self.push_frame(TTSStoppedFrame()) await self.stop_all_metrics() await self.push_error(ErrorFrame(f"{self} error: {msg['error']}")) + self._context_id = None else: logger.error(f"{self} error, unknown message type: {msg}") - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - # If we received a TTSSpeakFrame and the LLM response included text (it - # might be that it's only a function calling response) we pause - # processing more frames until we receive a BotStoppedSpeakingFrame. - if isinstance(frame, TTSSpeakFrame): - await self.pause_processing_frames() - elif isinstance(frame, LLMFullResponseEndFrame) and self._context_id: - await self.pause_processing_frames() - elif isinstance(frame, BotStoppedSpeakingFrame): - await self.resume_processing_frames() - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: logger.debug(f"Generating TTS: [{text}]") @@ -299,6 +286,7 @@ class CartesiaTTSService(WordTTSService, WebsocketService): await self.start_ttfb_metrics() yield TTSStartedFrame() self._context_id = str(uuid.uuid4()) + await self.create_audio_context(self._context_id) msg = self._build_msg(text=text or " ") # Text must contain at least one character diff --git a/src/pipecat/services/deepgram.py b/src/pipecat/services/deepgram.py index b9d39fa63..010c2c626 100644 --- a/src/pipecat/services/deepgram.py +++ b/src/pipecat/services/deepgram.py @@ -5,7 +5,7 @@ # import asyncio -from typing import AsyncGenerator, Optional +from typing import AsyncGenerator, Dict, Optional from loguru import logger @@ -34,6 +34,7 @@ try: AsyncListenWebSocketClient, DeepgramClient, DeepgramClientOptions, + ErrorResponse, LiveOptions, LiveResultResponse, LiveTranscriptionEvents, @@ -120,6 +121,7 @@ class DeepgramSTTService(STTService): url: str = "", sample_rate: Optional[int] = None, live_options: Optional[LiveOptions] = None, + addons: Optional[Dict] = None, **kwargs, ): super().__init__(sample_rate=sample_rate, **kwargs) @@ -127,7 +129,7 @@ class DeepgramSTTService(STTService): default_options = LiveOptions( encoding="linear16", language=Language.EN, - model="nova-2-general", + model="nova-3-general", channels=1, interim_results=True, smart_format=True, @@ -147,6 +149,7 @@ class DeepgramSTTService(STTService): merged_options.language = merged_options.language.value self._settings = merged_options.to_dict() + self._addons = addons self._client = DeepgramClient( api_key, @@ -155,13 +158,10 @@ class DeepgramSTTService(STTService): options={"keepalive": "true"}, # verbose=logging.DEBUG ), ) - self._connection: AsyncListenWebSocketClient = self._client.listen.asyncwebsocket.v("1") - self._connection.on(LiveTranscriptionEvents.Transcript, self._on_message) + if self.vad_enabled: self._register_event_handler("on_speech_started") self._register_event_handler("on_utterance_end") - self._connection.on(LiveTranscriptionEvents.SpeechStarted, self._on_speech_started) - self._connection.on(LiveTranscriptionEvents.UtteranceEnd, self._on_utterance_end) @property def vad_enabled(self): @@ -202,7 +202,25 @@ class DeepgramSTTService(STTService): async def _connect(self): logger.debug("Connecting to Deepgram") - if not await self._connection.start(self._settings): + + self._connection: AsyncListenWebSocketClient = self._client.listen.asyncwebsocket.v("1") + + self._connection.on( + LiveTranscriptionEvents(LiveTranscriptionEvents.Transcript), self._on_message + ) + self._connection.on(LiveTranscriptionEvents(LiveTranscriptionEvents.Error), self._on_error) + + if self.vad_enabled: + self._connection.on( + LiveTranscriptionEvents(LiveTranscriptionEvents.SpeechStarted), + self._on_speech_started, + ) + self._connection.on( + LiveTranscriptionEvents(LiveTranscriptionEvents.UtteranceEnd), + self._on_utterance_end, + ) + + if not await self._connection.start(options=self._settings, addons=self._addons): logger.error(f"{self}: unable to connect to Deepgram") async def _disconnect(self): @@ -214,6 +232,15 @@ class DeepgramSTTService(STTService): await self.start_ttfb_metrics() await self.start_processing_metrics() + async def _on_error(self, *args, **kwargs): + error: ErrorResponse = kwargs["error"] + logger.warning(f"{self} connection error, will retry: {error}") + await self.stop_all_metrics() + # NOTE(aleix): we don't disconnect (i.e. call finish on the connection) + # because this triggers more errors internally in the Deepgram SDK. So, + # we just forget about the previous connection and create a new one. + await self._connect() + async def _on_speech_started(self, *args, **kwargs): await self.start_metrics() await self._call_event_handler("on_speech_started", *args, **kwargs) diff --git a/src/pipecat/services/elevenlabs.py b/src/pipecat/services/elevenlabs.py index e0b985411..5c312e7fe 100644 --- a/src/pipecat/services/elevenlabs.py +++ b/src/pipecat/services/elevenlabs.py @@ -191,7 +191,7 @@ class ElevenLabsTTSService(WordTTSService, WebsocketService): aggregate_sentences=True, push_text_frames=False, push_stop_frames=True, - stop_frame_timeout_s=2.0, + pause_frame_processing=True, sample_rate=sample_rate, **kwargs, ) @@ -289,19 +289,6 @@ class ElevenLabsTTSService(WordTTSService, WebsocketService): if isinstance(frame, TTSStoppedFrame): await self.add_word_timestamps([("LLMFullResponseEndFrame", 0), ("Reset", 0)]) - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - # If we received a TTSSpeakFrame and the LLM response included text (it - # might be that it's only a function calling response) we pause - # processing more frames until we receive a BotStoppedSpeakingFrame. - if isinstance(frame, TTSSpeakFrame): - await self.pause_processing_frames() - elif isinstance(frame, LLMFullResponseEndFrame) and self._started: - await self.pause_processing_frames() - elif isinstance(frame, BotStoppedSpeakingFrame): - await self.resume_processing_frames() - async def _connect(self): await self._connect_websocket() @@ -370,8 +357,13 @@ class ElevenLabsTTSService(WordTTSService, WebsocketService): except Exception as e: logger.error(f"{self} error closing websocket: {e}") + def _get_websocket(self): + if self._websocket: + return self._websocket + raise Exception("Websocket not connected") + async def _receive_messages(self): - async for message in self._websocket: + async for message in self._get_websocket(): msg = json.loads(message) if msg.get("audio"): await self.stop_ttfb_metrics() diff --git a/src/pipecat/services/fal.py b/src/pipecat/services/fal.py index d229861f1..7173861ab 100644 --- a/src/pipecat/services/fal.py +++ b/src/pipecat/services/fal.py @@ -4,6 +4,7 @@ # SPDX-License-Identifier: BSD 2-Clause License # +import asyncio import io import os from typing import AsyncGenerator, Dict, Optional, Union @@ -53,6 +54,11 @@ class FalImageGenService(ImageGenService): os.environ["FAL_KEY"] = key async def run_image_gen(self, prompt: str) -> AsyncGenerator[Frame, None]: + def load_image_bytes(encoded_image: bytes): + buffer = io.BytesIO(encoded_image) + image = Image.open(buffer) + return (image.tobytes(), image.size, image.format) + logger.debug(f"Generating image from prompt: {prompt}") response = await fal_client.run_async( @@ -73,10 +79,8 @@ class FalImageGenService(ImageGenService): logger.debug(f"Downloading image {image_url} ...") async with self._aiohttp_session.get(image_url) as response: logger.debug(f"Downloaded image {image_url}") - image_stream = io.BytesIO(await response.content.read()) - image = Image.open(image_stream) + encoded_image = await response.content.read() + (image_bytes, size, format) = await asyncio.to_thread(load_image_bytes, encoded_image) - frame = URLImageRawFrame( - url=image_url, image=image.tobytes(), size=image.size, format=image.format - ) + frame = URLImageRawFrame(url=image_url, image=image_bytes, size=size, format=format) yield frame diff --git a/src/pipecat/services/fish.py b/src/pipecat/services/fish.py index d61514eb2..e2a75bdb2 100644 --- a/src/pipecat/services/fish.py +++ b/src/pipecat/services/fish.py @@ -11,16 +11,13 @@ from loguru import logger from pydantic import BaseModel from pipecat.frames.frames import ( - BotStoppedSpeakingFrame, CancelFrame, EndFrame, ErrorFrame, Frame, - LLMFullResponseEndFrame, StartFrame, StartInterruptionFrame, TTSAudioRawFrame, - TTSSpeakFrame, TTSStartedFrame, TTSStoppedFrame, ) @@ -60,7 +57,12 @@ class FishAudioTTSService(TTSService, WebsocketService): params: InputParams = InputParams(), **kwargs, ): - super().__init__(sample_rate=sample_rate, **kwargs) + super().__init__( + push_stop_frames=True, + pause_frame_processing=True, + sample_rate=sample_rate, + **kwargs, + ) self._api_key = api_key self._base_url = "wss://api.fish.audio/v1/tts/live" @@ -166,16 +168,6 @@ class FishAudioTTSService(TTSService, WebsocketService): except Exception as e: logger.error(f"Error processing message: {e}") - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - if isinstance(frame, TTSSpeakFrame): - await self.pause_processing_frames() - elif isinstance(frame, LLMFullResponseEndFrame) and self._request_id: - await self.pause_processing_frames() - elif isinstance(frame, BotStoppedSpeakingFrame): - await self.resume_processing_frames() - async def _handle_interruption(self, frame: StartInterruptionFrame, direction: FrameDirection): await super()._handle_interruption(frame, direction) await self.stop_all_metrics() diff --git a/src/pipecat/services/gemini_multimodal_live/gemini.py b/src/pipecat/services/gemini_multimodal_live/gemini.py index 4f26b6e9f..6e7a1c0fa 100644 --- a/src/pipecat/services/gemini_multimodal_live/gemini.py +++ b/src/pipecat/services/gemini_multimodal_live/gemini.py @@ -115,10 +115,10 @@ class GeminiMultimodalLiveUserContextAggregator(OpenAIUserContextAggregator): class GeminiMultimodalLiveAssistantContextAggregator(OpenAIAssistantContextAggregator): - async def _push_aggregation(self): + async def push_aggregation(self): # We don't want to store any images in the context. Revisit this later when the API evolves. self._pending_image_frame_message = None - await super()._push_aggregation() + await super().push_aggregation() @dataclass @@ -706,6 +706,6 @@ class GeminiMultimodalLiveLLMService(LLMService): GeminiMultimodalLiveContext.upgrade(context) user = GeminiMultimodalLiveUserContextAggregator(context) assistant = GeminiMultimodalLiveAssistantContextAggregator( - user, expect_stripped_words=assistant_expect_stripped_words + context, expect_stripped_words=assistant_expect_stripped_words ) return GeminiMultimodalLiveContextAggregatorPair(_user=user, _assistant=assistant) diff --git a/src/pipecat/services/google/google.py b/src/pipecat/services/google/google.py index 28cd0d421..0a8a86580 100644 --- a/src/pipecat/services/google/google.py +++ b/src/pipecat/services/google/google.py @@ -537,7 +537,7 @@ def language_to_google_stt_language(language: Language) -> Optional[str]: class GoogleUserContextAggregator(OpenAIUserContextAggregator): - async def _push_aggregation(self): + async def push_aggregation(self): if len(self._aggregation) > 0: self._context.add_message( glm.Content(role="user", parts=[glm.Part(text=self._aggregation)]) @@ -552,11 +552,11 @@ class GoogleUserContextAggregator(OpenAIUserContextAggregator): await self.push_frame(frame) # Reset our accumulator state. - self._reset() + self.reset() class GoogleAssistantContextAggregator(OpenAIAssistantContextAggregator): - async def _push_aggregation(self): + async def push_aggregation(self): if not ( self._aggregation or self._function_call_result or self._pending_image_frame_message ): @@ -566,7 +566,7 @@ class GoogleAssistantContextAggregator(OpenAIAssistantContextAggregator): properties: Optional[FunctionCallResultProperties] = None aggregation = self._aggregation - self._reset() + self.reset() try: if self._function_call_result: @@ -626,15 +626,14 @@ class GoogleAssistantContextAggregator(OpenAIAssistantContextAggregator): run_llm = True if run_llm: - await self._user_context_aggregator.push_context_frame() + await self.push_context_frame(FrameDirection.UPSTREAM) # Emit the on_context_updated callback once the function call result is added to the context if properties and properties.on_context_updated is not None: await properties.on_context_updated() # Push context frame - frame = OpenAILLMContextFrame(self._context) - await self.push_frame(frame) + await self.push_context_frame() # Push timestamp frame with current time timestamp_frame = OpenAILLMContextAssistantTimestampFrame(timestamp=time_now_iso8601()) @@ -917,9 +916,9 @@ class GoogleLLMContext(OpenAILLMContext): # Check if we only have function-related messages (no regular text) has_regular_messages = any( len(msg.parts) == 1 - and hasattr(msg.parts[0], "text") - and not hasattr(msg.parts[0], "function_call") - and not hasattr(msg.parts[0], "function_response") + and not getattr(msg.parts[0], "text", None) + and getattr(msg.parts[0], "function_call", None) + and getattr(msg.parts[0], "function_response", None) for msg in self._messages ) @@ -1175,7 +1174,7 @@ class GoogleLLMService(LLMService): ) -> GoogleContextAggregatorPair: user = GoogleUserContextAggregator(context) assistant = GoogleAssistantContextAggregator( - user, expect_stripped_words=assistant_expect_stripped_words + context, expect_stripped_words=assistant_expect_stripped_words ) return GoogleContextAggregatorPair(_user=user, _assistant=assistant) diff --git a/src/pipecat/services/grok.py b/src/pipecat/services/grok.py index 7221cc09e..064dd8829 100644 --- a/src/pipecat/services/grok.py +++ b/src/pipecat/services/grok.py @@ -17,6 +17,7 @@ from pipecat.processors.aggregators.openai_llm_context import ( OpenAILLMContext, OpenAILLMContextFrame, ) +from pipecat.processors.frame_processor import FrameDirection from pipecat.services.openai import ( OpenAIAssistantContextAggregator, OpenAILLMService, @@ -27,7 +28,7 @@ from pipecat.services.openai import ( class GrokAssistantContextAggregator(OpenAIAssistantContextAggregator): """Custom assistant context aggregator for Grok that handles empty content requirement.""" - async def _push_aggregation(self): + async def push_aggregation(self): if not ( self._aggregation or self._function_call_result or self._pending_image_frame_message ): @@ -37,7 +38,7 @@ class GrokAssistantContextAggregator(OpenAIAssistantContextAggregator): properties: Optional[FunctionCallResultProperties] = None aggregation = self._aggregation - self._reset() + self.reset() try: if self._function_call_result: @@ -91,14 +92,13 @@ class GrokAssistantContextAggregator(OpenAIAssistantContextAggregator): run_llm = True if run_llm: - await self._user_context_aggregator.push_context_frame() + await self.push_context_frame(FrameDirection.UPSTREAM) # Emit the on_context_updated callback once the function call result is added to the context if properties and properties.on_context_updated is not None: await properties.on_context_updated() - frame = OpenAILLMContextFrame(self._context) - await self.push_frame(frame) + await self.push_context_frame() except Exception as e: logger.error(f"Error processing frame: {e}") @@ -212,6 +212,6 @@ class GrokLLMService(OpenAILLMService): ) -> GrokContextAggregatorPair: user = OpenAIUserContextAggregator(context) assistant = GrokAssistantContextAggregator( - user, expect_stripped_words=assistant_expect_stripped_words + context, expect_stripped_words=assistant_expect_stripped_words ) return GrokContextAggregatorPair(_user=user, _assistant=assistant) diff --git a/src/pipecat/services/lmnt.py b/src/pipecat/services/lmnt.py index 645494cc1..0272690e8 100644 --- a/src/pipecat/services/lmnt.py +++ b/src/pipecat/services/lmnt.py @@ -73,6 +73,7 @@ class LmntTTSService(TTSService, WebsocketService): TTSService.__init__( self, push_stop_frames=True, + pause_frame_processing=True, sample_rate=sample_rate, **kwargs, ) diff --git a/src/pipecat/services/openai.py b/src/pipecat/services/openai.py index bc251025e..15c1a197a 100644 --- a/src/pipecat/services/openai.py +++ b/src/pipecat/services/openai.py @@ -110,7 +110,7 @@ class BaseOpenAILLMService(LLMService): seed: Optional[int] = Field(default_factory=lambda: NOT_GIVEN, ge=0) temperature: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=2.0) # Note: top_k is currently not supported by the OpenAI client library, - # so top_k is ignore right now. + # so top_k is ignored right now. top_k: Optional[int] = Field(default=None, ge=0) top_p: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0) max_tokens: Optional[int] = Field(default_factory=lambda: NOT_GIVEN, ge=1) @@ -266,7 +266,6 @@ class BaseOpenAILLMService(LLMService): if tool_call.function and tool_call.function.name: function_name += tool_call.function.name tool_call_id = tool_call.id - await self.call_start_function(context, function_name) if tool_call.function and tool_call.function.arguments: # Keep iterating through the response to collect all the argument fragments arguments += tool_call.function.arguments @@ -355,7 +354,7 @@ class OpenAILLMService(BaseOpenAILLMService): ) -> OpenAIContextAggregatorPair: user = OpenAIUserContextAggregator(context) assistant = OpenAIAssistantContextAggregator( - user, expect_stripped_words=assistant_expect_stripped_words + context, expect_stripped_words=assistant_expect_stripped_words ) return OpenAIContextAggregatorPair(_user=user, _assistant=assistant) @@ -555,8 +554,8 @@ class OpenAIImageMessageFrame(Frame): class OpenAIUserContextAggregator(LLMUserContextAggregator): - def __init__(self, context: OpenAILLMContext): - super().__init__(context=context) + def __init__(self, context: OpenAILLMContext, **kwargs): + super().__init__(context=context, **kwargs) async def process_frame(self, frame, direction): await super().process_frame(frame, direction) @@ -592,9 +591,8 @@ class OpenAIUserContextAggregator(LLMUserContextAggregator): class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator): - def __init__(self, user_context_aggregator: OpenAIUserContextAggregator, **kwargs): - super().__init__(context=user_context_aggregator._context, **kwargs) - self._user_context_aggregator = user_context_aggregator + def __init__(self, context: OpenAILLMContext, **kwargs): + super().__init__(context=context, **kwargs) self._function_calls_in_progress = {} self._function_call_result = None self._pending_image_frame_message = None @@ -614,7 +612,7 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator): del self._function_calls_in_progress[frame.tool_call_id] self._function_call_result = frame # TODO-CB: Kwin wants us to refactor this out of here but I REFUSE - await self._push_aggregation() + await self.push_aggregation() else: logger.warning( "FunctionCallResultFrame tool_call_id does not match any function call in progress" @@ -622,9 +620,9 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator): self._function_call_result = None elif isinstance(frame, OpenAIImageMessageFrame): self._pending_image_frame_message = frame - await self._push_aggregation() + await self.push_aggregation() - async def _push_aggregation(self): + async def push_aggregation(self): if not ( self._aggregation or self._function_call_result or self._pending_image_frame_message ): @@ -634,7 +632,7 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator): properties: Optional[FunctionCallResultProperties] = None aggregation = self._aggregation - self._reset() + self.reset() try: if self._function_call_result: @@ -686,15 +684,14 @@ class OpenAIAssistantContextAggregator(LLMAssistantContextAggregator): run_llm = True if run_llm: - await self._user_context_aggregator.push_context_frame() + await self.push_context_frame(FrameDirection.UPSTREAM) # Emit the on_context_updated callback once the function call result is added to the context if properties and properties.on_context_updated is not None: await properties.on_context_updated() # Push context frame - frame = OpenAILLMContextFrame(self._context) - await self.push_frame(frame) + await self.push_context_frame() # Push timestamp frame with current time timestamp_frame = OpenAILLMContextAssistantTimestampFrame(timestamp=time_now_iso8601()) diff --git a/src/pipecat/services/openai_realtime_beta/context.py b/src/pipecat/services/openai_realtime_beta/context.py index da287194a..31639dc6b 100644 --- a/src/pipecat/services/openai_realtime_beta/context.py +++ b/src/pipecat/services/openai_realtime_beta/context.py @@ -166,7 +166,7 @@ class OpenAIRealtimeUserContextAggregator(OpenAIUserContextAggregator): if isinstance(frame, LLMSetToolsFrame): await self.push_frame(frame, direction) - async def _push_aggregation(self): + async def push_aggregation(self): # for the moment, ignore all user input coming into the pipeline. # todo: think about whether/how to fix this to allow for text input from # upstream (transport/transcription, or other sources) @@ -174,7 +174,7 @@ class OpenAIRealtimeUserContextAggregator(OpenAIUserContextAggregator): class OpenAIRealtimeAssistantContextAggregator(OpenAIAssistantContextAggregator): - async def _push_aggregation(self): + async def push_aggregation(self): # the only thing we implement here is function calling. in all other cases, messages # are added to the context when we receive openai realtime api events if not self._function_call_result: @@ -182,7 +182,7 @@ class OpenAIRealtimeAssistantContextAggregator(OpenAIAssistantContextAggregator) properties: Optional[FunctionCallResultProperties] = None - self._reset() + self.reset() try: run_llm = True frame = self._function_call_result @@ -217,8 +217,8 @@ class OpenAIRealtimeAssistantContextAggregator(OpenAIAssistantContextAggregator) # The standard function callback code path pushes the FunctionCallResultFrame from the llm itself, # so we didn't have a chance to add the result to the openai realtime api context. Let's push a # special frame to do that. - await self._user_context_aggregator.push_frame( - RealtimeFunctionCallResultFrame(result_frame=frame) + await self.push_frame( + RealtimeFunctionCallResultFrame(result_frame=frame), FrameDirection.UPSTREAM ) if properties and properties.run_llm is not None: # If the tool call result has a run_llm property, use it @@ -228,14 +228,13 @@ class OpenAIRealtimeAssistantContextAggregator(OpenAIAssistantContextAggregator) run_llm = not bool(self._function_calls_in_progress) if run_llm: - await self._user_context_aggregator.push_context_frame() + await self.push_context_frame(FrameDirection.UPSTREAM) # Emit the on_context_updated callback once the function call result is added to the context if properties and properties.on_context_updated is not None: await properties.on_context_updated() - frame = OpenAILLMContextFrame(self._context) - await self.push_frame(frame) + await self.push_context_frame() except Exception as e: logger.error(f"Error processing frame: {e}") diff --git a/src/pipecat/services/openai_realtime_beta/openai.py b/src/pipecat/services/openai_realtime_beta/openai.py index a42ed7b9a..bc173d765 100644 --- a/src/pipecat/services/openai_realtime_beta/openai.py +++ b/src/pipecat/services/openai_realtime_beta/openai.py @@ -568,6 +568,6 @@ class OpenAIRealtimeBetaLLMService(LLMService): OpenAIRealtimeLLMContext.upgrade_to_realtime(context) user = OpenAIRealtimeUserContextAggregator(context) assistant = OpenAIRealtimeAssistantContextAggregator( - user, expect_stripped_words=assistant_expect_stripped_words + context, expect_stripped_words=assistant_expect_stripped_words ) return OpenAIContextAggregatorPair(_user=user, _assistant=assistant) diff --git a/src/pipecat/services/playht.py b/src/pipecat/services/playht.py index bd9463f91..297e802d3 100644 --- a/src/pipecat/services/playht.py +++ b/src/pipecat/services/playht.py @@ -120,6 +120,7 @@ class PlayHTTTSService(TTSService, WebsocketService): ): TTSService.__init__( self, + pause_frame_processing=True, sample_rate=sample_rate, **kwargs, ) @@ -269,19 +270,6 @@ class PlayHTTTSService(TTSService, WebsocketService): except json.JSONDecodeError: logger.error(f"Invalid JSON message: {message}") - async def process_frame(self, frame: Frame, direction: FrameDirection): - await super().process_frame(frame, direction) - - # If we received a TTSSpeakFrame and the LLM response included text (it - # might be that it's only a function calling response) we pause - # processing more frames until we receive a BotStoppedSpeakingFrame. - if isinstance(frame, TTSSpeakFrame): - await self.pause_processing_frames() - elif isinstance(frame, LLMFullResponseEndFrame) and self._request_id: - await self.pause_processing_frames() - elif isinstance(frame, BotStoppedSpeakingFrame): - await self.resume_processing_frames() - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: logger.debug(f"Generating TTS: [{text}]") diff --git a/src/pipecat/services/rime.py b/src/pipecat/services/rime.py index 0210f8de6..e12844a96 100644 --- a/src/pipecat/services/rime.py +++ b/src/pipecat/services/rime.py @@ -7,28 +7,25 @@ import base64 import json import uuid -from typing import AsyncGenerator, Optional, Union +from typing import AsyncGenerator, Optional import aiohttp from loguru import logger from pydantic import BaseModel from pipecat.frames.frames import ( - BotStoppedSpeakingFrame, CancelFrame, EndFrame, ErrorFrame, Frame, - LLMFullResponseEndFrame, StartFrame, StartInterruptionFrame, TTSAudioRawFrame, - TTSSpeakFrame, TTSStartedFrame, TTSStoppedFrame, ) from pipecat.processors.frame_processor import FrameDirection -from pipecat.services.ai_services import TTSService, WordTTSService +from pipecat.services.ai_services import AudioContextWordTTSService, TTSService from pipecat.services.websocket_service import WebsocketService from pipecat.transcriptions.language import Language @@ -58,7 +55,7 @@ def language_to_rime_language(language: Language) -> str: return LANGUAGE_MAP.get(language, "eng") -class RimeTTSService(WordTTSService, WebsocketService): +class RimeTTSService(AudioContextWordTTSService, WebsocketService): """Text-to-Speech service using Rime's websocket API. Uses Rime's websocket JSON API to convert text to speech with word-level timing @@ -95,12 +92,12 @@ class RimeTTSService(WordTTSService, WebsocketService): params: Additional configuration parameters. """ # Initialize with parent class settings for proper frame handling - WordTTSService.__init__( + AudioContextWordTTSService.__init__( self, aggregate_sentences=True, push_text_frames=False, push_stop_frames=True, - stop_frame_timeout_s=2.0, + pause_frame_processing=True, sample_rate=sample_rate, **kwargs, ) @@ -126,7 +123,6 @@ class RimeTTSService(WordTTSService, WebsocketService): # State tracking self._context_id = None # Tracks current turn self._receive_task = None - self._started = False self._cumulative_time = 0 # Accumulates time across messages def can_generate_metrics(self) -> bool: @@ -200,7 +196,6 @@ class RimeTTSService(WordTTSService, WebsocketService): await self._websocket.send(json.dumps(self._build_eos_msg())) await self._websocket.close() self._websocket = None - self._started = False self._context_id = None except Exception as e: logger.error(f"{self} error closing websocket: {e}") @@ -217,7 +212,6 @@ class RimeTTSService(WordTTSService, WebsocketService): await self.stop_all_metrics() if self._context_id: await self._get_websocket().send(json.dumps(self._build_clear_msg())) - self._started = False self._context_id = None def _calculate_word_times(self, words: list, starts: list, ends: list) -> list: @@ -249,12 +243,18 @@ class RimeTTSService(WordTTSService, WebsocketService): return word_pairs + async def flush_audio(self): + if not self._context_id or not self._websocket: + return + logger.trace(f"{self}: flushing audio") + self._context_id = None + async def _receive_messages(self): """Process incoming websocket messages.""" async for message in self._get_websocket(): msg = json.loads(message) - if not msg or msg["contextId"] != self._context_id: + if not msg or not self.audio_context_available(msg["contextId"]): continue if msg["type"] == "chunk": @@ -266,7 +266,7 @@ class RimeTTSService(WordTTSService, WebsocketService): sample_rate=self.sample_rate, num_channels=1, ) - await self.push_frame(frame) + await self.append_to_audio_context(msg["contextId"], frame) elif msg["type"] == "timestamps": # Process word timing information @@ -288,26 +288,15 @@ class RimeTTSService(WordTTSService, WebsocketService): await self.push_frame(TTSStoppedFrame()) await self.stop_all_metrics() await self.push_error(ErrorFrame(f"{self} error: {msg['message']}")) + self._context_id = None async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM): """Push frame and handle end-of-turn conditions.""" await super().push_frame(frame, direction) if isinstance(frame, (TTSStoppedFrame, StartInterruptionFrame)): - self._started = False if isinstance(frame, TTSStoppedFrame): await self.add_word_timestamps([("LLMFullResponseEndFrame", 0), ("Reset", 0)]) - async def process_frame(self, frame: Frame, direction: FrameDirection): - """Process frames and manage turn state.""" - await super().process_frame(frame, direction) - - if isinstance(frame, TTSSpeakFrame): - await self.pause_processing_frames() - elif isinstance(frame, LLMFullResponseEndFrame) and self._started: - await self.pause_processing_frames() - elif isinstance(frame, BotStoppedSpeakingFrame): - await self.resume_processing_frames() - async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]: """Generate speech from text. @@ -323,12 +312,12 @@ class RimeTTSService(WordTTSService, WebsocketService): await self._connect() try: - if not self._started: + if not self._context_id: await self.start_ttfb_metrics() yield TTSStartedFrame() - self._started = True self._cumulative_time = 0 self._context_id = str(uuid.uuid4()) + await self.create_audio_context(self._context_id) msg = self._build_msg(text=text) await self._get_websocket().send(json.dumps(msg)) diff --git a/src/pipecat/services/websocket_service.py b/src/pipecat/services/websocket_service.py index 9c942b019..a8dc97414 100644 --- a/src/pipecat/services/websocket_service.py +++ b/src/pipecat/services/websocket_service.py @@ -10,8 +10,10 @@ from typing import Awaitable, Callable, Optional import websockets from loguru import logger +from websockets.protocol import State from pipecat.frames.frames import ErrorFrame +from pipecat.utils.network import exponential_backoff_time class WebsocketService(ABC): @@ -50,27 +52,6 @@ class WebsocketService(ABC): await self._connect_websocket() return await self._verify_connection() - def _calculate_wait_time( - self, attempt: int, min_wait: float = 4, max_wait: float = 10, multiplier: float = 1 - ) -> float: - """Calculate exponential backoff wait time. - - Args: - attempt: Current attempt number (1-based) - min_wait: Minimum wait time in seconds - max_wait: Maximum wait time in seconds - multiplier: Base multiplier for exponential calculation - - Returns: - Wait time in seconds - """ - try: - exp = 2 ** (attempt - 1) * multiplier - result = max(0, min(exp, max_wait)) - return max(min_wait, result) - except (ValueError, ArithmeticError): - return max_wait - async def _receive_task_handler(self, report_error: Callable[[ErrorFrame], Awaitable[None]]): """Handles WebSocket message receiving with automatic retry logic. @@ -83,11 +64,13 @@ class WebsocketService(ABC): while True: try: await self._receive_messages() - logger.debug(f"{self} connection established successfully") retry_count = 0 # Reset counter on successful message receive - except websockets.ConnectionClosed as e: - logger.warning(f"{self} connection closed: {e}") - break + if self._websocket and self._websocket.state == State.CLOSED: + raise websockets.ConnectionClosedOK( + self._websocket.close_rcvd, + self._websocket.close_sent, + self._websocket.close_rcvd_then_sent, + ) except Exception as e: retry_count += 1 if retry_count >= MAX_RETRIES: @@ -101,7 +84,7 @@ class WebsocketService(ABC): try: if await self._reconnect_websocket(retry_count): retry_count = 0 # Reset counter on successful reconnection - wait_time = self._calculate_wait_time(retry_count) + wait_time = exponential_backoff_time(retry_count) await asyncio.sleep(wait_time) except Exception as reconnect_error: logger.error(f"{self} reconnection failed: {reconnect_error}") diff --git a/src/pipecat/tests/utils.py b/src/pipecat/tests/utils.py index ff92164a4..7fcecc3ff 100644 --- a/src/pipecat/tests/utils.py +++ b/src/pipecat/tests/utils.py @@ -5,6 +5,7 @@ # import asyncio +from dataclasses import dataclass from typing import Any, Awaitable, Callable, Dict, Sequence, Tuple from pipecat.frames.frames import ( @@ -12,6 +13,7 @@ from pipecat.frames.frames import ( Frame, HeartbeatFrame, StartFrame, + SystemFrame, ) from pipecat.observers.base_observer import BaseObserver from pipecat.pipeline.pipeline import Pipeline @@ -20,6 +22,16 @@ from pipecat.pipeline.task import PipelineParams, PipelineTask from pipecat.processors.frame_processor import FrameDirection, FrameProcessor +@dataclass +class SleepFrame(SystemFrame): + """This frame is used by test framework to introduce some sleep time before + the next frame is pushed. This is useful to control system frames vs data or + control frames. + """ + + sleep: float = 0.1 + + class HeartbeatsObserver(BaseObserver): def __init__( self, @@ -44,7 +56,11 @@ class HeartbeatsObserver(BaseObserver): class QueuedFrameProcessor(FrameProcessor): def __init__( - self, queue: asyncio.Queue, queue_direction: FrameDirection, ignore_start: bool = True + self, + *, + queue: asyncio.Queue, + queue_direction: FrameDirection, + ignore_start: bool = True, ): super().__init__() self._queue = queue @@ -72,21 +88,35 @@ async def run_test( ) -> Tuple[Sequence[Frame], Sequence[Frame]]: received_up = asyncio.Queue() received_down = asyncio.Queue() - source = QueuedFrameProcessor(received_up, FrameDirection.UPSTREAM, ignore_start) - sink = QueuedFrameProcessor(received_down, FrameDirection.DOWNSTREAM, ignore_start) + source = QueuedFrameProcessor( + queue=received_up, + queue_direction=FrameDirection.UPSTREAM, + ignore_start=ignore_start, + ) + sink = QueuedFrameProcessor( + queue=received_down, + queue_direction=FrameDirection.DOWNSTREAM, + ignore_start=ignore_start, + ) pipeline = Pipeline([source, processor, sink]) task = PipelineTask(pipeline, params=PipelineParams(start_metadata=start_metadata)) - for frame in frames_to_send: - await task.queue_frame(frame) + async def push_frames(): + # Just give a little head start to the runner. + await asyncio.sleep(0.01) + for frame in frames_to_send: + if isinstance(frame, SleepFrame): + await asyncio.sleep(frame.sleep) + else: + await task.queue_frame(frame) - if send_end_frame: - await task.queue_frame(EndFrame()) + if send_end_frame: + await task.queue_frame(EndFrame()) runner = PipelineRunner() - await runner.run(task) + await asyncio.gather(runner.run(task), push_frames()) # # Down frames @@ -98,6 +128,7 @@ async def run_test( received_down_frames.append(frame) print("received DOWN frames =", received_down_frames) + print("expected DOWN frames =", expected_down_frames) assert len(received_down_frames) == len(expected_down_frames) @@ -113,6 +144,7 @@ async def run_test( received_up_frames.append(frame) print("received UP frames =", received_up_frames) + print("expected UP frames =", expected_up_frames) assert len(received_up_frames) == len(expected_up_frames) diff --git a/src/pipecat/transports/base_input.py b/src/pipecat/transports/base_input.py index 6bfe86001..ee7ae7f7c 100644 --- a/src/pipecat/transports/base_input.py +++ b/src/pipecat/transports/base_input.py @@ -14,6 +14,8 @@ from pipecat.audio.vad.vad_analyzer import VADAnalyzer, VADState from pipecat.frames.frames import ( BotInterruptionFrame, CancelFrame, + EmulateUserStartedSpeakingFrame, + EmulateUserStoppedSpeakingFrame, EndFrame, FilterUpdateSettingsFrame, Frame, @@ -112,9 +114,13 @@ class BaseInputTransport(FrameProcessor): await self.cancel(frame) await self.push_frame(frame, direction) elif isinstance(frame, BotInterruptionFrame): - logger.debug("Bot interruption") - await self._start_interruption() - await self.push_frame(StartInterruptionFrame()) + await self._handle_bot_interruption(frame) + elif isinstance(frame, EmulateUserStartedSpeakingFrame): + logger.debug("Emulating user started speaking") + await self._handle_user_interruption(UserStartedSpeakingFrame()) + elif isinstance(frame, EmulateUserStoppedSpeakingFrame): + logger.debug("Emulating user stopped speaking") + await self._handle_user_interruption(UserStoppedSpeakingFrame()) # All other system frames elif isinstance(frame, SystemFrame): await self.push_frame(frame, direction) @@ -137,7 +143,13 @@ class BaseInputTransport(FrameProcessor): # Handle interruptions # - async def _handle_interruptions(self, frame: Frame): + async def _handle_bot_interruption(self, frame: BotInterruptionFrame): + logger.debug("Bot interruption") + if self.interruptions_allowed: + await self._start_interruption() + await self.push_frame(StartInterruptionFrame()) + + async def _handle_user_interruption(self, frame: Frame): if isinstance(frame, UserStartedSpeakingFrame): logger.debug("User started speaking") # Make sure we notify about interruptions quickly out-of-band. @@ -162,11 +174,9 @@ class BaseInputTransport(FrameProcessor): async def _vad_analyze(self, audio_frame: InputAudioRawFrame) -> VADState: state = VADState.QUIET if self.vad_analyzer: - logger.trace(f"{self}: analyzing VAD on {audio_frame}") state = await self.get_event_loop().run_in_executor( self._executor, self.vad_analyzer.analyze_audio, audio_frame.audio ) - logger.trace(f"{self}: done analyzing VAD on {audio_frame}") return state async def _handle_vad(self, audio_frame: InputAudioRawFrame, vad_state: VADState): @@ -183,7 +193,7 @@ class BaseInputTransport(FrameProcessor): frame = UserStoppedSpeakingFrame() if frame: - await self._handle_interruptions(frame) + await self._handle_user_interruption(frame) vad_state = new_vad_state return vad_state diff --git a/src/pipecat/transports/base_output.py b/src/pipecat/transports/base_output.py index 6bf4a9ff3..1b6d1e833 100644 --- a/src/pipecat/transports/base_output.py +++ b/src/pipecat/transports/base_output.py @@ -170,6 +170,8 @@ class BaseOutputTransport(FrameProcessor): # TODO(aleix): Images and audio should support presentation timestamps. elif frame.pts: await self._sink_clock_queue.put((frame.pts, frame.id, frame)) + elif direction == FrameDirection.UPSTREAM: + await self.push_frame(frame, direction) else: await self._sink_queue.put(frame) diff --git a/src/pipecat/transports/local/audio.py b/src/pipecat/transports/local/audio.py index 30bdaaf79..e7b803f2b 100644 --- a/src/pipecat/transports/local/audio.py +++ b/src/pipecat/transports/local/audio.py @@ -26,17 +26,18 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") -class LocalTransportParams(TransportParams): - input_device_index: int = 0 - output_device_index: int = 0 +class LocalAudioTransportParams(TransportParams): + input_device_index: Optional[int] = None + output_device_index: Optional[int] = None class LocalAudioInputTransport(BaseInputTransport): - _params: LocalTransportParams + _params: LocalAudioTransportParams - def __init__(self, py_audio: pyaudio.PyAudio, params: LocalTransportParams): + def __init__(self, py_audio: pyaudio.PyAudio, params: LocalAudioTransportParams): super().__init__(params) self._py_audio = py_audio + self._in_stream = None self._sample_rate = 0 @@ -77,11 +78,12 @@ class LocalAudioInputTransport(BaseInputTransport): class LocalAudioOutputTransport(BaseOutputTransport): - _params: LocalTransportParams + _params: LocalAudioTransportParams - def __init__(self, py_audio: pyaudio.PyAudio, params: TransportParams): + def __init__(self, py_audio: pyaudio.PyAudio, params: LocalAudioTransportParams): super().__init__(params) self._py_audio = py_audio + self._out_stream = None self._sample_rate = 0 @@ -117,7 +119,7 @@ class LocalAudioOutputTransport(BaseOutputTransport): class LocalAudioTransport(BaseTransport): - def __init__(self, params: LocalTransportParams): + def __init__(self, params: LocalAudioTransportParams): super().__init__() self._params = params self._pyaudio = pyaudio.PyAudio() diff --git a/src/pipecat/transports/local/tk.py b/src/pipecat/transports/local/tk.py index 40147d39f..73777c573 100644 --- a/src/pipecat/transports/local/tk.py +++ b/src/pipecat/transports/local/tk.py @@ -34,8 +34,15 @@ except ModuleNotFoundError as e: raise Exception(f"Missing module: {e}") +class TkTransportParams(TransportParams): + audio_input_device_index: Optional[int] = None + audio_output_device_index: Optional[int] = None + + class TkInputTransport(BaseInputTransport): - def __init__(self, py_audio: pyaudio.PyAudio, params: TransportParams): + _params: TkTransportParams + + def __init__(self, py_audio: pyaudio.PyAudio, params: TkTransportParams): super().__init__(params) self._py_audio = py_audio self._in_stream = None @@ -54,6 +61,7 @@ class TkInputTransport(BaseInputTransport): frames_per_buffer=num_frames, stream_callback=self._audio_in_callback, input=True, + input_device_index=self._params.audio_input_device_index, ) self._in_stream.start_stream() @@ -76,6 +84,8 @@ class TkInputTransport(BaseInputTransport): class TkOutputTransport(BaseOutputTransport): + _params: TkTransportParams + def __init__(self, tk_root: tk.Tk, py_audio: pyaudio.PyAudio, params: TransportParams): super().__init__(params) self._py_audio = py_audio @@ -103,6 +113,7 @@ class TkOutputTransport(BaseOutputTransport): channels=self._params.audio_out_channels, rate=self._sample_rate, output=True, + output_device_index=self._params.audio_output_device_index, ) self._out_stream.start_stream() diff --git a/src/pipecat/transports/services/daily.py b/src/pipecat/transports/services/daily.py index 2274b3e8f..7ce329659 100644 --- a/src/pipecat/transports/services/daily.py +++ b/src/pipecat/transports/services/daily.py @@ -329,6 +329,10 @@ class DailyTransportClient(EventHandler): def _speaker_name(self): return f"speaker-{self}" + @property + def room_url(self) -> str: + return self._room_url + @property def participant_id(self) -> str: return self._participant_id @@ -1112,6 +1116,10 @@ class DailyTransport(BaseTransport): # DailyTransport # + @property + def room_url(self) -> str: + return self._client.room_url + @property def participant_id(self) -> str: return self._client.participant_id diff --git a/src/pipecat/utils/network.py b/src/pipecat/utils/network.py new file mode 100644 index 000000000..27bec990c --- /dev/null +++ b/src/pipecat/utils/network.py @@ -0,0 +1,27 @@ +# +# Copyright (c) 2024–2025, Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +def exponential_backoff_time( + attempt: int, min_wait: float = 4, max_wait: float = 10, multiplier: float = 1 +) -> float: + """Calculate exponential backoff wait time. + + Args: + attempt: Current attempt number (1-based) + min_wait: Minimum wait time in seconds + max_wait: Maximum wait time in seconds + multiplier: Base multiplier for exponential calculation + + Returns: + Wait time in seconds + """ + try: + exp = 2 ** (attempt - 1) * multiplier + result = max(0, min(exp, max_wait)) + return max(min_wait, result) + except (ValueError, ArithmeticError): + return max_wait diff --git a/src/pipecat/utils/string.py b/src/pipecat/utils/string.py index c269c5e57..916dfad41 100644 --- a/src/pipecat/utils/string.py +++ b/src/pipecat/utils/string.py @@ -13,8 +13,8 @@ ENDOFSENTENCE_PATTERN_STR = r""" (? 1", + "Line break": "Line break", + "Mixed & <entities>": "Mixed & ", + } + + for input_text, expected in test_cases.items(): + result = self.filter.filter(input_text) + self.assertEqual(result, expected, f"HTML entity conversion failed for: '{input_text}'") + + async def test_asterisk_removal(self): + """Test removal of Markdown asterisk formatting.""" + test_cases = { + "**bold text**": "bold text", # Double asterisks + "*italic text*": "italic text", # Single asterisks + "**bold** and *italic*": "bold and italic", # Mixed + "multiple**bold**words": "multipleboldwords", # No spaces + "edge**cases***here*": "edgecaseshere", # Adjacent asterisks + } + + for input_text, expected in test_cases.items(): + result = self.filter.filter(input_text) + self.assertEqual(result, expected, f"Asterisk removal failed for: '{input_text}'") + + async def test_newline_handling(self): + """Test handling of empty and whitespace-only lines.""" + test_cases = { + "Line 1\n\nLine 2": "Line 1\n Line 2", # Empty line becomes space + "Line 1\n \nLine 2": "Line 1\n Line 2", # Whitespace line becomes single space + "Text\n\n\nMore": "Text\n More", # Multiple empty lines become spaces + } + + for input_text, expected in test_cases.items(): + result = self.filter.filter(input_text) + self.assertEqual( + result, expected, f"Newline handling failed for:\n{input_text}\nGot:\n{result}" + ) + + async def test_numbered_list_marker_handling(self): + """Test handling of numbered lists with the special §NUM§ marker.""" + test_cases = { + "1. First\n2. Second": "1. First\n2. Second", # Basic numbered list + " 1. Indented": " 1. Indented", # Indented numbered list + "1. Item\nText\n2. Item": "1. Item\nText\n2. Item", # Text between items + "1.No space": "1.No space", # Not a list item (no space) + "12. Large number": "12. Large number", # Multi-digit numbers + } + + for input_text, expected in test_cases.items(): + result = self.filter.filter(input_text) + self.assertEqual( + result, + expected, + f"Numbered list handling failed for:\n{input_text}\nGot:\n{result}", + ) + + async def test_inline_code_handling(self): + """Test handling of inline code with backticks.""" + test_cases = { + "`code`": "code", # Basic inline code + "Text `code` more": "Text code more", # Inline code within text + "``nested`code``": "nested`code", # Nested backticks + "`code1` and `code2`": "code1 and code2", # Multiple inline codes + "No``space``between": "Nospacebetween", # No spaces around backticks + } + + for input_text, expected in test_cases.items(): + result = self.filter.filter(input_text) + self.assertEqual(result, expected, f"Inline code handling failed for: '{input_text}'") + + async def test_simple_table_removal(self): + """Test removal of a simple markdown table.""" + filter = MarkdownTextFilter(params=MarkdownTextFilter.InputParams(filter_tables=True)) + + input_text = "| Column 1 | Column 2 |\n|----------|----------|\n| Cell 1 | Cell 2 |" + + expected = "" + + result = filter.filter(input_text) + self.assertEqual( + result.strip(), + expected.strip(), + f"Simple table removal failed.\nExpected:\n{expected}\nGot:\n{result}", + ) + + async def test_feature_toggles(self): + """Test enabling/disabling specific filter features.""" + # Create a filter with all features disabled + filter = MarkdownTextFilter( + params=MarkdownTextFilter.InputParams( + enable_text_filter=False, + filter_code=False, + filter_tables=False, + ) + ) + + # Test with text filtering disabled + text_with_markdown = "**bold** and *italic* with `code`" + self.assertEqual( + filter.filter(text_with_markdown), + text_with_markdown, + "Disabled filter should not modify text", + ) + + # Enable just text filtering + filter.update_settings({"enable_text_filter": True}) + self.assertEqual( + filter.filter(text_with_markdown), + "bold and italic with code", + "Enabled filter should remove markdown", + ) + + async def test_settings_update(self): + """Test that filter settings can be updated at runtime.""" + filter = MarkdownTextFilter() + + # Initial state - formatting should be removed + input_text = "**bold** and *italic*" + self.assertEqual(filter.filter(input_text), "bold and italic") + + # Disable text filtering + filter.update_settings({"enable_text_filter": False}) + self.assertEqual(filter.filter(input_text), input_text, "Text filtering should be disabled") + + # Re-enable text filtering + filter.update_settings({"enable_text_filter": True}) + self.assertEqual( + filter.filter(input_text), "bold and italic", "Text filtering should be re-enabled" + ) diff --git a/tests/test_pipeline.py b/tests/test_pipeline.py index caac89c11..0aff922b2 100644 --- a/tests/test_pipeline.py +++ b/tests/test_pipeline.py @@ -21,11 +21,11 @@ class TestPipeline(unittest.IsolatedAsyncioTestCase): pipeline = Pipeline([IdentityFilter()]) frames_to_send = [TextFrame(text="Hello from Pipecat!")] - expected_returned_frames = [TextFrame] + expected_down_frames = [TextFrame] await run_test( pipeline, frames_to_send=frames_to_send, - expected_down_frames=expected_returned_frames, + expected_down_frames=expected_down_frames, ) async def test_pipeline_multiple(self): @@ -36,22 +36,22 @@ class TestPipeline(unittest.IsolatedAsyncioTestCase): pipeline = Pipeline([identity1, identity2, identity3]) frames_to_send = [TextFrame(text="Hello from Pipecat!")] - expected_returned_frames = [TextFrame] + expected_down_frames = [TextFrame] await run_test( pipeline, frames_to_send=frames_to_send, - expected_down_frames=expected_returned_frames, + expected_down_frames=expected_down_frames, ) async def test_pipeline_start_metadata(self): pipeline = Pipeline([IdentityFilter()]) frames_to_send = [] - expected_returned_frames = [StartFrame] + expected_down_frames = [StartFrame] (received_down, _) = await run_test( pipeline, frames_to_send=frames_to_send, - expected_down_frames=expected_returned_frames, + expected_down_frames=expected_down_frames, ignore_start=False, start_metadata={"foo": "bar"}, ) @@ -63,11 +63,11 @@ class TestParallelPipeline(unittest.IsolatedAsyncioTestCase): pipeline = ParallelPipeline([IdentityFilter()]) frames_to_send = [TextFrame(text="Hello from Pipecat!")] - expected_returned_frames = [TextFrame] + expected_down_frames = [TextFrame] await run_test( pipeline, frames_to_send=frames_to_send, - expected_down_frames=expected_returned_frames, + expected_down_frames=expected_down_frames, ) async def test_parallel_multiple(self): @@ -75,11 +75,11 @@ class TestParallelPipeline(unittest.IsolatedAsyncioTestCase): pipeline = ParallelPipeline([IdentityFilter()], [IdentityFilter()]) frames_to_send = [TextFrame(text="Hello from Pipecat!")] - expected_returned_frames = [TextFrame] + expected_down_frames = [TextFrame] await run_test( pipeline, frames_to_send=frames_to_send, - expected_down_frames=expected_returned_frames, + expected_down_frames=expected_down_frames, ) diff --git a/tests/test_stt_mute_filter.py b/tests/test_stt_mute_filter.py index 62bdd03c9..a55c4609e 100644 --- a/tests/test_stt_mute_filter.py +++ b/tests/test_stt_mute_filter.py @@ -11,12 +11,13 @@ from pipecat.frames.frames import ( BotStoppedSpeakingFrame, FunctionCallInProgressFrame, FunctionCallResultFrame, + InputAudioRawFrame, STTMuteFrame, UserStartedSpeakingFrame, UserStoppedSpeakingFrame, ) from pipecat.processors.filters.stt_mute_filter import STTMuteConfig, STTMuteFilter, STTMuteStrategy -from pipecat.tests.utils import run_test +from pipecat.tests.utils import SleepFrame, run_test class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase): @@ -26,10 +27,14 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase): frames_to_send = [ BotStartedSpeakingFrame(), # First bot speech starts UserStartedSpeakingFrame(), # Should be suppressed + InputAudioRawFrame( + audio=b"", sample_rate=16000, num_channels=1 + ), # Should be suppressed UserStoppedSpeakingFrame(), # Should be suppressed BotStoppedSpeakingFrame(), # First bot speech ends BotStartedSpeakingFrame(), # Second bot speech UserStartedSpeakingFrame(), # Should pass through + InputAudioRawFrame(audio=b"", sample_rate=16000, num_channels=1), # Should pass through UserStoppedSpeakingFrame(), # Should pass through BotStoppedSpeakingFrame(), ] @@ -41,6 +46,7 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase): STTMuteFrame, # mute=False BotStartedSpeakingFrame, UserStartedSpeakingFrame, # Now passes through + InputAudioRawFrame, # Now passes through UserStoppedSpeakingFrame, # Now passes through BotStoppedSpeakingFrame, ] @@ -57,12 +63,19 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase): frames_to_send = [ BotStartedSpeakingFrame(), # First speech starts UserStartedSpeakingFrame(), # Should be suppressed + InputAudioRawFrame( + audio=b"", sample_rate=16000, num_channels=1 + ), # Should be suppressed UserStoppedSpeakingFrame(), # Should be suppressed BotStoppedSpeakingFrame(), # First speech ends UserStartedSpeakingFrame(), # Should pass through + InputAudioRawFrame(audio=b"", sample_rate=16000, num_channels=1), # Should pass through UserStoppedSpeakingFrame(), # Should pass through BotStartedSpeakingFrame(), # Second speech starts UserStartedSpeakingFrame(), # Should be suppressed again + InputAudioRawFrame( + audio=b"", sample_rate=16000, num_channels=1 + ), # Should be suppressed again UserStoppedSpeakingFrame(), # Should be suppressed again BotStoppedSpeakingFrame(), # Second speech ends ] @@ -73,6 +86,7 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase): BotStoppedSpeakingFrame, STTMuteFrame, # mute=False UserStartedSpeakingFrame, + InputAudioRawFrame, UserStoppedSpeakingFrame, BotStartedSpeakingFrame, STTMuteFrame, # mute=True @@ -134,15 +148,23 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase): frames_to_send = [ UserStartedSpeakingFrame(), # Should be suppressed (starts muted) + InputAudioRawFrame( + audio=b"", sample_rate=16000, num_channels=1 + ), # Should be suppressed UserStoppedSpeakingFrame(), # Should be suppressed BotStartedSpeakingFrame(), # First bot speech UserStartedSpeakingFrame(), # Should be suppressed + InputAudioRawFrame( + audio=b"", sample_rate=16000, num_channels=1 + ), # Should be suppressed UserStoppedSpeakingFrame(), # Should be suppressed BotStoppedSpeakingFrame(), # First speech ends, unmutes UserStartedSpeakingFrame(), # Should pass through + InputAudioRawFrame(audio=b"", sample_rate=16000, num_channels=1), # Should pass through UserStoppedSpeakingFrame(), # Should pass through BotStartedSpeakingFrame(), # Second speech UserStartedSpeakingFrame(), # Should pass through + InputAudioRawFrame(audio=b"", sample_rate=16000, num_channels=1), # Should pass through UserStoppedSpeakingFrame(), # Should pass through BotStoppedSpeakingFrame(), ] @@ -153,9 +175,11 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase): BotStoppedSpeakingFrame, STTMuteFrame, # mute=False after first speech UserStartedSpeakingFrame, + InputAudioRawFrame, UserStoppedSpeakingFrame, BotStartedSpeakingFrame, UserStartedSpeakingFrame, + InputAudioRawFrame, UserStoppedSpeakingFrame, BotStoppedSpeakingFrame, ] @@ -190,23 +214,30 @@ class TestSTTMuteFilter(unittest.IsolatedAsyncioTestCase): frames_to_send = [ UserStartedSpeakingFrame(), # Should pass through + InputAudioRawFrame(audio=b"", sample_rate=16000, num_channels=1), # Should pass through UserStoppedSpeakingFrame(), # Should pass through BotStartedSpeakingFrame(), # Bot starts speaking UserStartedSpeakingFrame(), # Should be suppressed + InputAudioRawFrame( + audio=b"", sample_rate=16000, num_channels=1 + ), # Should be suppressed UserStoppedSpeakingFrame(), # Should be suppressed BotStoppedSpeakingFrame(), # Bot stops speaking UserStartedSpeakingFrame(), # Should pass through + InputAudioRawFrame(audio=b"", sample_rate=16000, num_channels=1), # Should pass through UserStoppedSpeakingFrame(), # Should pass through ] expected_returned_frames = [ UserStartedSpeakingFrame, + InputAudioRawFrame, UserStoppedSpeakingFrame, BotStartedSpeakingFrame, STTMuteFrame, # mute=True BotStoppedSpeakingFrame, STTMuteFrame, # mute=False UserStartedSpeakingFrame, + InputAudioRawFrame, UserStoppedSpeakingFrame, ] diff --git a/tests/test_transcript_processor.py b/tests/test_transcript_processor.py new file mode 100644 index 000000000..1c6db277f --- /dev/null +++ b/tests/test_transcript_processor.py @@ -0,0 +1,428 @@ +# +# Copyright (c) 2024-2025 Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + + +import asyncio +import unittest +from datetime import datetime, timezone +from typing import List, Tuple, cast + +from pipecat.frames.frames import ( + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + CancelFrame, + StartInterruptionFrame, + TranscriptionFrame, + TranscriptionMessage, + TranscriptionUpdateFrame, + TTSTextFrame, +) +from pipecat.processors.transcript_processor import ( + AssistantTranscriptProcessor, + UserTranscriptProcessor, +) +from pipecat.tests.utils import SleepFrame, run_test + + +class TestUserTranscriptProcessor(unittest.IsolatedAsyncioTestCase): + """Tests for UserTranscriptProcessor""" + + async def test_basic_transcription(self): + """Test basic transcription frame processing""" + # Create processor + processor = UserTranscriptProcessor() + + # Create test timestamp + timestamp = datetime.now(timezone.utc).isoformat() + + # Create frames to send + frames_to_send = [ + TranscriptionFrame(text="Hello, world!", user_id="test_user", timestamp=timestamp) + ] + + # Expected frames downstream - note the order: + # 1. TranscriptionUpdateFrame (processor emits the update first) + # 2. TranscriptionFrame (original frame is passed through) + expected_down_frames = [TranscriptionUpdateFrame, TranscriptionFrame] + + # Run test + received_frames, _ = await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + # Verify the content of the TranscriptionUpdateFrame + update_frame = cast( + TranscriptionUpdateFrame, received_frames[0] + ) # Note: now checking first frame + self.assertIsInstance(update_frame, TranscriptionUpdateFrame) + self.assertEqual(len(update_frame.messages), 1) + message = update_frame.messages[0] + self.assertEqual(message.role, "user") + self.assertEqual(message.content, "Hello, world!") + self.assertEqual(message.timestamp, timestamp) + + async def test_event_handler(self): + """Test that event handlers are called with transcript updates""" + # Create processor + processor = UserTranscriptProcessor() + + # Track received updates + received_updates: List[TranscriptionMessage] = [] + + # Register event handler + @processor.event_handler("on_transcript_update") + async def handle_update(proc, frame: TranscriptionUpdateFrame): + received_updates.extend(frame.messages) + + # Create test data + timestamp = datetime.now(timezone.utc).isoformat() + frames_to_send = [ + TranscriptionFrame(text="First message", user_id="test_user", timestamp=timestamp), + TranscriptionFrame(text="Second message", user_id="test_user", timestamp=timestamp), + ] + + expected_down_frames = [ + TranscriptionUpdateFrame, + TranscriptionFrame, # First message + TranscriptionUpdateFrame, + TranscriptionFrame, # Second message + ] + + # Run test + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + # Verify event handler received updates + self.assertEqual(len(received_updates), 2) + + # Check first message + self.assertEqual(received_updates[0].role, "user") + self.assertEqual(received_updates[0].content, "First message") + self.assertEqual(received_updates[0].timestamp, timestamp) + + # Check second message + self.assertEqual(received_updates[1].role, "user") + self.assertEqual(received_updates[1].content, "Second message") + self.assertEqual(received_updates[1].timestamp, timestamp) + + async def test_text_aggregation(self): + """Test that TTSTextFrames are properly aggregated into a single message""" + # Create processor + processor = AssistantTranscriptProcessor() + + # Track received updates + received_updates: List[TranscriptionUpdateFrame] = [] + + @processor.event_handler("on_transcript_update") + async def handle_update(proc, frame: TranscriptionUpdateFrame): + received_updates.append(frame) + + # Create test frames simulating bot speaking multiple text chunks + frames_to_send = [ + BotStartedSpeakingFrame(), + SleepFrame(sleep=0.1), # Wait for StartedSpeaking to process + TTSTextFrame(text="Hello"), + TTSTextFrame(text="world!"), + TTSTextFrame(text="How"), + TTSTextFrame(text="are"), + TTSTextFrame(text="you?"), + SleepFrame(sleep=0.1), # Wait for text frames to queue + BotStoppedSpeakingFrame(), + ] + + # Expected order: + # 1. BotStartedSpeakingFrame (system frame, immediate) + # 2. All queued TTSTextFrames + # 3. BotStoppedSpeakingFrame (system frame, immediate) + # 4. TranscriptionUpdateFrame (after aggregation) + expected_down_frames = [ + BotStartedSpeakingFrame, + TTSTextFrame, + TTSTextFrame, + TTSTextFrame, + TTSTextFrame, + TTSTextFrame, + BotStoppedSpeakingFrame, + TranscriptionUpdateFrame, + ] + + # Run test + received_frames, _ = await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + # Verify update was received + self.assertEqual(len(received_updates), 1) + + # Get the update frame + update_frame = received_updates[0] + + # Should have one aggregated message + self.assertEqual(len(update_frame.messages), 1) + + message = update_frame.messages[0] + self.assertEqual(message.role, "assistant") + self.assertEqual(message.content, "Hello world! How are you?") + + # Verify timestamp exists + self.assertIsNotNone(message.timestamp) + + # All frames should be passed through in order, with update at end + downstream_update = cast(TranscriptionUpdateFrame, received_frames[-1]) + self.assertEqual(downstream_update.messages[0].content, "Hello world! How are you?") + + async def test_empty_text_handling(self): + """Test that empty messages are not emitted""" + processor = AssistantTranscriptProcessor() + + received_updates: List[TranscriptionUpdateFrame] = [] + + @processor.event_handler("on_transcript_update") + async def handle_update(proc, frame: TranscriptionUpdateFrame): + received_updates.append(frame) + + frames_to_send = [ + BotStartedSpeakingFrame(), + SleepFrame(sleep=0.1), + TTSTextFrame(text=""), # Empty text + TTSTextFrame(text=" "), # Just whitespace + TTSTextFrame(text="\n"), # Just newline + BotStoppedSpeakingFrame(), + # Pipeline ends here; run_test will automatically send EndFrame + ] + + # From our earlier tests, we know BotStoppedSpeakingFrame comes before TTSTextFrames + expected_down_frames = [ + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + TTSTextFrame, # empty + TTSTextFrame, # whitespace + TTSTextFrame, # newline + # No TranscriptionUpdateFrame since content is empty after stripping + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + self.assertEqual(len(received_updates), 0, "No updates should be emitted for empty content") + + async def test_interruption_handling(self): + """Test that messages are properly captured when bot is interrupted""" + processor = AssistantTranscriptProcessor() + + # Track received updates + received_updates: List[TranscriptionUpdateFrame] = [] + + @processor.event_handler("on_transcript_update") + async def handle_update(proc, frame: TranscriptionUpdateFrame): + received_updates.append(frame) + + # Simulate bot being interrupted mid-sentence + frames_to_send = [ + BotStartedSpeakingFrame(), + SleepFrame(sleep=0.1), + TTSTextFrame(text="Hello"), + TTSTextFrame(text="world"), + TTSTextFrame(text="!"), + SleepFrame(sleep=0.1), + StartInterruptionFrame(), # User interrupts here + BotStartedSpeakingFrame(), + SleepFrame(sleep=0.1), + TTSTextFrame(text="New"), + TTSTextFrame(text="response"), + SleepFrame(sleep=0.1), + BotStoppedSpeakingFrame(), + ] + + # Actual order of frames: + expected_down_frames = [ + BotStartedSpeakingFrame, + TTSTextFrame, # "Hello" + TTSTextFrame, # "world" + TTSTextFrame, # "!" + TranscriptionUpdateFrame, # First message (emitted due to interruption) + StartInterruptionFrame, # Interruption frame comes after the update + BotStartedSpeakingFrame, + TTSTextFrame, # "New" + TTSTextFrame, # "response" + BotStoppedSpeakingFrame, + TranscriptionUpdateFrame, # Second message + ] + + # Run test + received_frames, _ = await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + # Should have received two updates + self.assertEqual(len(received_updates), 2) + + # First update should be interrupted message + first_message = received_updates[0].messages[0] + self.assertEqual(first_message.role, "assistant") + self.assertEqual(first_message.content, "Hello world !") + self.assertIsNotNone(first_message.timestamp) + + # Second update should be new response + second_message = received_updates[1].messages[0] + self.assertEqual(second_message.role, "assistant") + self.assertEqual(second_message.content, "New response") + self.assertIsNotNone(second_message.timestamp) + + # Verify timestamps are different + self.assertNotEqual(first_message.timestamp, second_message.timestamp) + + async def test_end_frame_handling(self): + """Test that final messages are captured when pipeline ends normally""" + processor = AssistantTranscriptProcessor() + + received_updates: List[TranscriptionUpdateFrame] = [] + + @processor.event_handler("on_transcript_update") + async def handle_update(proc, frame: TranscriptionUpdateFrame): + received_updates.append(frame) + + frames_to_send = [ + BotStartedSpeakingFrame(), + SleepFrame(sleep=0.1), + TTSTextFrame(text="Hello"), + TTSTextFrame(text="world"), + # Pipeline ends here; run_test will automatically send EndFrame + ] + + expected_down_frames = [ + BotStartedSpeakingFrame, + TTSTextFrame, + TTSTextFrame, + TranscriptionUpdateFrame, # Final message emitted due to EndFrame + ] + + # Run test - EndFrame will be sent automatically + received_frames, _ = await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + self.assertEqual(len(received_updates), 1) + message = received_updates[0].messages[0] + self.assertEqual(message.role, "assistant") + self.assertEqual(message.content, "Hello world") + + async def test_cancel_frame_handling(self): + """Test that messages are properly captured when pipeline is cancelled""" + processor = AssistantTranscriptProcessor() + + # Track updates with timestamps to verify order + received_updates: List[Tuple[str, float]] = [] + + @processor.event_handler("on_transcript_update") + async def handle_update(proc, frame: TranscriptionUpdateFrame): + # Record message content and time received + received_updates.append((frame.messages[0].content, asyncio.get_event_loop().time())) + + frames_to_send = [ + BotStartedSpeakingFrame(), + SleepFrame(sleep=0.1), + TTSTextFrame(text="Hello"), + TTSTextFrame(text="world"), + SleepFrame(sleep=0.1), # Ensure messages are processed + CancelFrame(), + ] + + # We don't need to verify frame order, just that CancelFrame triggers message emission + expected_down_frames = [ + BotStartedSpeakingFrame, + TTSTextFrame, + TTSTextFrame, + CancelFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + send_end_frame=False, + ) + + # Verify that we received an update + self.assertEqual(len(received_updates), 1, "Should receive one update before cancellation") + content, _ = received_updates[0] + self.assertEqual(content, "Hello world") + + async def test_transcript_processor_factory(self): + """Test that factory properly manages processors and event handlers""" + from pipecat.processors.transcript_processor import TranscriptProcessor + + factory = TranscriptProcessor() + received_updates: List[TranscriptionMessage] = [] + + # Register handler with factory + @factory.event_handler("on_transcript_update") + async def handle_update(proc, frame: TranscriptionUpdateFrame): + received_updates.extend(frame.messages) + + # Get processors and verify they're reused + user_proc1 = factory.user() + user_proc2 = factory.user() + self.assertIs(user_proc1, user_proc2, "User processor should be reused") + + asst_proc1 = factory.assistant() + asst_proc2 = factory.assistant() + self.assertIs(asst_proc1, asst_proc2, "Assistant processor should be reused") + + # Test user processor + timestamp = datetime.now(timezone.utc).isoformat() + frames_to_send = [ + TranscriptionFrame(text="User message", user_id="user1", timestamp=timestamp) + ] + + await run_test( + user_proc1, + frames_to_send=frames_to_send, + expected_down_frames=[TranscriptionUpdateFrame, TranscriptionFrame], + ) + + # Test assistant processor + frames_to_send = [ + BotStartedSpeakingFrame(), + SleepFrame(sleep=0.1), + TTSTextFrame(text="Assistant"), + TTSTextFrame(text="message"), + BotStoppedSpeakingFrame(), + ] + + # The actual order we see in the output: + await run_test( + asst_proc1, + frames_to_send=frames_to_send, + expected_down_frames=[ + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + TTSTextFrame, + TTSTextFrame, + TranscriptionUpdateFrame, + ], + ) + + # Verify both processors triggered the same handler + self.assertEqual(len(received_updates), 2) + self.assertEqual(received_updates[0].role, "user") + self.assertEqual(received_updates[0].content, "User message") + self.assertEqual(received_updates[1].role, "assistant") + self.assertEqual(received_updates[1].content, "Assistant message") diff --git a/tests/test_user_idle_processor.py b/tests/test_user_idle_processor.py new file mode 100644 index 000000000..a2f2fd386 --- /dev/null +++ b/tests/test_user_idle_processor.py @@ -0,0 +1,216 @@ +# +# Copyright (c) 2024-2025 Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import asyncio +import unittest + +from pipecat.frames.frames import ( + BotSpeakingFrame, + BotStartedSpeakingFrame, + BotStoppedSpeakingFrame, + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, +) +from pipecat.processors.user_idle_processor import UserIdleProcessor +from pipecat.tests.utils import SleepFrame, run_test + + +class TestUserIdleProcessor(unittest.IsolatedAsyncioTestCase): + async def test_basic_idle_detection(self): + """Test that idle callback is triggered after timeout when user stops speaking.""" + callback_called = asyncio.Event() + + async def idle_callback(processor: UserIdleProcessor) -> None: + callback_called.set() + + # Create processor with a short timeout for testing + processor = UserIdleProcessor(callback=idle_callback, timeout=0.1) # 100ms timeout + + frames_to_send = [ + # Start conversation + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + # Wait 200ms - double the idle timeout to ensure it triggers + SleepFrame(sleep=0.2), + ] + + expected_down_frames = [ + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + assert callback_called.is_set(), "Idle callback was not called" + + async def test_active_listening_resets_idle(self): + """Test that bot speaking frames reset the idle timer because user is actively listening.""" + callback_called = asyncio.Event() + + async def idle_callback(processor: UserIdleProcessor) -> None: + callback_called.set() + + processor = UserIdleProcessor(callback=idle_callback, timeout=0.2) + + frames_to_send = [ + # Start conversation + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + # Wait almost long enough for idle timeout + SleepFrame(sleep=0.1), + # Bot speaking frame should reset idle timer + BotSpeakingFrame(), + # Wait almost long enough for idle timeout again + SleepFrame(sleep=0.1), + # Another bot speaking frame resets timer again + BotSpeakingFrame(), + ] + + expected_down_frames = [ + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + BotSpeakingFrame, + BotSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + assert not callback_called.is_set(), ( + "Idle callback was called even though bot speaking frames reset the timer" + ) + + async def test_idle_retry_callback(self): + """Test that retry count increases until user activity resets it.""" + retry_counts = [] + + async def retry_callback(processor: UserIdleProcessor, retry_count: int) -> bool: + retry_counts.append(retry_count) + return True # Keep monitoring for idle events + + processor = UserIdleProcessor(callback=retry_callback, timeout=0.4) + + frames_to_send = [ + # Start conversation + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + # Wait for first idle timeout (count=1) + SleepFrame(sleep=0.5), + # Wait for second idle timeout (count=2) + SleepFrame(sleep=0.5), + # User activity resets the count + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + # Wait for new idle timeout (count should be 1 again) + SleepFrame(sleep=0.5), + ] + + expected_down_frames = [ + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + assert retry_counts == [1, 2, 1], f"Expected retry counts [1, 2, 1], got {retry_counts}" + + async def test_idle_monitoring_stops_on_false_return(self): + """Test that idle monitoring stops when callback returns False.""" + retry_counts = [] + + async def retry_callback(processor: UserIdleProcessor, retry_count: int) -> bool: + retry_counts.append(retry_count) + return retry_count < 2 # Stop after second retry + + processor = UserIdleProcessor(callback=retry_callback, timeout=0.4) + + frames_to_send = [ + UserStartedSpeakingFrame(), + UserStoppedSpeakingFrame(), + SleepFrame(sleep=0.5), # First retry (count=1, returns True) + SleepFrame(sleep=0.5), # Second retry (count=2, returns False) + SleepFrame(sleep=0.5), # Should not trigger callback + ] + + expected_down_frames = [ + UserStartedSpeakingFrame, + UserStoppedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + assert retry_counts == [1, 2], f"Expected retry counts [1, 2], got {retry_counts}" + + async def test_no_idle_before_conversation(self): + """Test that idle monitoring doesn't start before first conversation activity.""" + callback_called = asyncio.Event() + + async def idle_callback(processor: UserIdleProcessor) -> None: + callback_called.set() + + processor = UserIdleProcessor(callback=idle_callback, timeout=0.1) + + frames_to_send = [ + SleepFrame(sleep=0.2), # Should not trigger callback + # No conversation activity yet + ] + + expected_down_frames = [] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + assert not callback_called.is_set(), "Idle callback was called before conversation started" + + async def test_idle_starts_with_bot_speech(self): + """Test that monitoring starts with bot speaking frames, not just user speech.""" + callback_called = asyncio.Event() + + async def idle_callback(processor: UserIdleProcessor) -> None: + callback_called.set() + + processor = UserIdleProcessor(callback=idle_callback, timeout=0.1) + + frames_to_send = [ + BotStartedSpeakingFrame(), + BotSpeakingFrame(), + BotStoppedSpeakingFrame(), + SleepFrame(sleep=0.2), + ] + + expected_down_frames = [ + BotStartedSpeakingFrame, + BotSpeakingFrame, + BotStoppedSpeakingFrame, + ] + + await run_test( + processor, + frames_to_send=frames_to_send, + expected_down_frames=expected_down_frames, + ) + + assert callback_called.is_set(), "Idle callback not called after bot speech" diff --git a/tests/test_utils_network.py b/tests/test_utils_network.py new file mode 100644 index 000000000..5b8d96939 --- /dev/null +++ b/tests/test_utils_network.py @@ -0,0 +1,34 @@ +# +# Copyright (c) 2024-2025 Daily +# +# SPDX-License-Identifier: BSD 2-Clause License +# + +import unittest + +from pipecat.utils.network import exponential_backoff_time + + +class TestUtilsNetwork(unittest.IsolatedAsyncioTestCase): + async def test_exponential_backoff_time(self): + # min_wait=4, max_wait=10, multiplier=1 + assert exponential_backoff_time(attempt=1, min_wait=4, max_wait=10, multiplier=1) == 4 + assert exponential_backoff_time(attempt=2, min_wait=4, max_wait=10, multiplier=1) == 4 + assert exponential_backoff_time(attempt=3, min_wait=4, max_wait=10, multiplier=1) == 4 + assert exponential_backoff_time(attempt=4, min_wait=4, max_wait=10, multiplier=1) == 8 + assert exponential_backoff_time(attempt=5, min_wait=4, max_wait=10, multiplier=1) == 10 + assert exponential_backoff_time(attempt=6, min_wait=4, max_wait=10, multiplier=1) == 10 + # min_wait=1, max_wait=10, multiplier=1 + assert exponential_backoff_time(attempt=1, min_wait=1, max_wait=10, multiplier=1) == 1 + assert exponential_backoff_time(attempt=2, min_wait=1, max_wait=10, multiplier=1) == 2 + assert exponential_backoff_time(attempt=3, min_wait=1, max_wait=10, multiplier=1) == 4 + assert exponential_backoff_time(attempt=4, min_wait=1, max_wait=10, multiplier=1) == 8 + assert exponential_backoff_time(attempt=5, min_wait=1, max_wait=10, multiplier=1) == 10 + assert exponential_backoff_time(attempt=6, min_wait=1, max_wait=10, multiplier=1) == 10 + # min_wait=1, max_wait=20, multiplier=2 + assert exponential_backoff_time(attempt=1, min_wait=1, max_wait=20, multiplier=2) == 2 + assert exponential_backoff_time(attempt=2, min_wait=1, max_wait=20, multiplier=2) == 4 + assert exponential_backoff_time(attempt=3, min_wait=1, max_wait=20, multiplier=2) == 8 + assert exponential_backoff_time(attempt=4, min_wait=1, max_wait=20, multiplier=2) == 16 + assert exponential_backoff_time(attempt=5, min_wait=1, max_wait=20, multiplier=2) == 20 + assert exponential_backoff_time(attempt=6, min_wait=1, max_wait=20, multiplier=2) == 20 diff --git a/tests/test_utils_string.py b/tests/test_utils_string.py index aa135a639..660397f3c 100644 --- a/tests/test_utils_string.py +++ b/tests/test_utils_string.py @@ -14,7 +14,6 @@ class TestUtilsString(unittest.IsolatedAsyncioTestCase): assert match_endofsentence("This is a sentence.") assert match_endofsentence("This is a sentence! ") assert match_endofsentence("This is a sentence?") - assert match_endofsentence("This is a sentence:") assert match_endofsentence("This is a sentence;") assert not match_endofsentence("This is not a sentence") assert not match_endofsentence("This is not a sentence,") @@ -33,7 +32,6 @@ class TestUtilsString(unittest.IsolatedAsyncioTestCase): "你好！", "吃了吗？", "安全第一；", - "他说：", ] for i in chinese_sentences: assert match_endofsentence(i)