Remove Hathora service integration
Hathora is shutting down on March 5, 2026. Remove the STT/TTS services, examples, and related references.
This commit is contained in:
Mark Backman
26
README.md
26
README.md
@@ -81,19 +81,19 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout
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## 🧩 Available services
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## 🧩 Available services
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| Category | Services |
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| Category | Services |
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| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| ------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [Hathora](https://docs.pipecat.ai/server/services/stt/hathora), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) |
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| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) |
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| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) |
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| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) |
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| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hathora](https://docs.pipecat.ai/server/services/tts/hathora), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [Resemble](https://docs.pipecat.ai/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
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| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [Resemble](https://docs.pipecat.ai/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
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| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), |
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| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), |
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| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local |
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| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local |
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| Serializers | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage) |
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| Serializers | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage) |
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| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [LemonSlice](https://docs.pipecat.ai/server/services/video/lemonslice), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) |
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| Video | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [LemonSlice](https://docs.pipecat.ai/server/services/video/lemonslice), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) |
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| Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) |
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| Memory | [mem0](https://docs.pipecat.ai/server/services/memory/mem0) |
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| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) |
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| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) |
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| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter) |
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| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter) |
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| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) |
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| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) |
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📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
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📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
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@@ -86,9 +86,6 @@ GROK_API_KEY=...
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# Groq
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# Groq
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GROQ_API_KEY=...
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GROQ_API_KEY=...
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# Hathora
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HATHORA_API_KEY=...
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# Heygen
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# Heygen
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HEYGEN_API_KEY=...
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HEYGEN_API_KEY=...
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HEYGEN_LIVE_AVATAR_API_KEY=...
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HEYGEN_LIVE_AVATAR_API_KEY=...
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@@ -1,123 +0,0 @@
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#
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# Copyright (c) 2024–2026, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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import os
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from dotenv import load_dotenv
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from loguru import logger
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from pipecat.audio.vad.silero import SileroVADAnalyzer
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from pipecat.frames.frames import LLMRunFrame
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from pipecat.pipeline.pipeline import Pipeline
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from pipecat.pipeline.runner import PipelineRunner
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from pipecat.pipeline.task import PipelineParams, PipelineTask
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from pipecat.processors.aggregators.llm_context import LLMContext
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from pipecat.processors.aggregators.llm_response_universal import (
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LLMContextAggregatorPair,
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LLMUserAggregatorParams,
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)
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from pipecat.runner.types import RunnerArguments
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from pipecat.runner.utils import create_transport
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from pipecat.services.hathora.stt import HathoraSTTService
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from pipecat.services.hathora.tts import HathoraTTSService
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from pipecat.services.openai.llm import OpenAILLMService
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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from pipecat.transports.daily.transport import DailyParams
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from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
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load_dotenv(override=True)
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# We use lambdas to defer transport parameter creation until the transport
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# type is selected at runtime.
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transport_params = {
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"daily": lambda: DailyParams(
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audio_in_enabled=True,
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audio_out_enabled=True,
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),
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"twilio": lambda: FastAPIWebsocketParams(
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audio_in_enabled=True,
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audio_out_enabled=True,
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),
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"webrtc": lambda: TransportParams(
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audio_in_enabled=True,
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audio_out_enabled=True,
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),
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}
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async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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logger.info(f"Starting bot")
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stt = HathoraSTTService(
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model="nvidia-parakeet-tdt-0.6b-v3",
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)
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tts = HathoraTTSService(
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model="hexgrad-kokoro-82m",
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)
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# See https://models.hathora.dev/model/qwen3-30b-a3b
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llm = OpenAILLMService(
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base_url="https://app-362f7ca1-6975-4e18-a605-ab202bf2c315.app.hathora.dev/v1",
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api_key=os.getenv("HATHORA_API_KEY"),
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model=None,
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system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.",
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)
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context = LLMContext()
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context_aggregator = LLMContextAggregatorPair(
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context,
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user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
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)
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pipeline = Pipeline(
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[
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transport.input(), # Transport user input
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stt,
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context_aggregator.user(), # User responses
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llm, # LLM
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tts, # TTS
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transport.output(), # Transport bot output
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context_aggregator.assistant(), # Assistant spoken responses
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]
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)
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task = PipelineTask(
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pipeline,
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params=PipelineParams(
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enable_metrics=True,
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enable_usage_metrics=True,
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),
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idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
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)
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@transport.event_handler("on_client_connected")
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async def on_client_connected(transport, client):
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logger.info(f"Client connected")
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# Kick off the conversation.
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context.add_message({"role": "system", "content": "Please introduce yourself to the user."})
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await task.queue_frames([LLMRunFrame()])
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@transport.event_handler("on_client_disconnected")
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async def on_client_disconnected(transport, client):
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logger.info(f"Client disconnected")
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await task.cancel()
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runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
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await runner.run(task)
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async def bot(runner_args: RunnerArguments):
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"""Main bot entry point compatible with Pipecat Cloud."""
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transport = await create_transport(runner_args, transport_params)
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await run_bot(transport, runner_args)
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if __name__ == "__main__":
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from pipecat.runner.run import main
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main()
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@@ -1,121 +0,0 @@
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#
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# Copyright (c) 2024-2026, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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import asyncio
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import os
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|
|
||||||
from dotenv import load_dotenv
|
|
||||||
from loguru import logger
|
|
||||||
|
|
||||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
|
||||||
from pipecat.frames.frames import LLMRunFrame, TTSUpdateSettingsFrame
|
|
||||||
from pipecat.pipeline.pipeline import Pipeline
|
|
||||||
from pipecat.pipeline.runner import PipelineRunner
|
|
||||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
|
||||||
from pipecat.processors.aggregators.llm_context import LLMContext
|
|
||||||
from pipecat.processors.aggregators.llm_response_universal import (
|
|
||||||
LLMContextAggregatorPair,
|
|
||||||
LLMUserAggregatorParams,
|
|
||||||
)
|
|
||||||
from pipecat.runner.types import RunnerArguments
|
|
||||||
from pipecat.runner.utils import create_transport
|
|
||||||
from pipecat.services.deepgram.stt import DeepgramSTTService
|
|
||||||
from pipecat.services.hathora.tts import HathoraTTSService, HathoraTTSSettings
|
|
||||||
from pipecat.services.openai.llm import OpenAILLMService
|
|
||||||
from pipecat.transports.base_transport import BaseTransport, TransportParams
|
|
||||||
from pipecat.transports.daily.transport import DailyParams
|
|
||||||
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
|
|
||||||
|
|
||||||
load_dotenv(override=True)
|
|
||||||
|
|
||||||
transport_params = {
|
|
||||||
"daily": lambda: DailyParams(
|
|
||||||
audio_in_enabled=True,
|
|
||||||
audio_out_enabled=True,
|
|
||||||
),
|
|
||||||
"twilio": lambda: FastAPIWebsocketParams(
|
|
||||||
audio_in_enabled=True,
|
|
||||||
audio_out_enabled=True,
|
|
||||||
),
|
|
||||||
"webrtc": lambda: TransportParams(
|
|
||||||
audio_in_enabled=True,
|
|
||||||
audio_out_enabled=True,
|
|
||||||
),
|
|
||||||
}
|
|
||||||
|
|
||||||
|
|
||||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
|
||||||
logger.info(f"Starting bot")
|
|
||||||
|
|
||||||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
|
||||||
|
|
||||||
tts = HathoraTTSService(
|
|
||||||
api_key=os.getenv("HATHORA_API_KEY"),
|
|
||||||
model="hexgrad-kokoro-82m",
|
|
||||||
)
|
|
||||||
|
|
||||||
llm = OpenAILLMService(
|
|
||||||
api_key=os.getenv("OPENAI_API_KEY"),
|
|
||||||
system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.",
|
|
||||||
)
|
|
||||||
|
|
||||||
context = LLMContext()
|
|
||||||
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
|
|
||||||
context,
|
|
||||||
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
|
|
||||||
)
|
|
||||||
|
|
||||||
pipeline = Pipeline(
|
|
||||||
[
|
|
||||||
transport.input(),
|
|
||||||
stt,
|
|
||||||
user_aggregator,
|
|
||||||
llm,
|
|
||||||
tts,
|
|
||||||
transport.output(),
|
|
||||||
assistant_aggregator,
|
|
||||||
]
|
|
||||||
)
|
|
||||||
|
|
||||||
task = PipelineTask(
|
|
||||||
pipeline,
|
|
||||||
params=PipelineParams(
|
|
||||||
enable_metrics=True,
|
|
||||||
enable_usage_metrics=True,
|
|
||||||
),
|
|
||||||
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
|
|
||||||
)
|
|
||||||
|
|
||||||
@transport.event_handler("on_client_connected")
|
|
||||||
async def on_client_connected(transport, client):
|
|
||||||
logger.info(f"Client connected")
|
|
||||||
context.add_message({"role": "system", "content": "Please introduce yourself to the user."})
|
|
||||||
await task.queue_frames([LLMRunFrame()])
|
|
||||||
|
|
||||||
await asyncio.sleep(10)
|
|
||||||
logger.info("Updating Hathora TTS settings: speed=1.5")
|
|
||||||
await task.queue_frame(TTSUpdateSettingsFrame(delta=HathoraTTSSettings(speed=1.5)))
|
|
||||||
|
|
||||||
@transport.event_handler("on_client_disconnected")
|
|
||||||
async def on_client_disconnected(transport, client):
|
|
||||||
logger.info(f"Client disconnected")
|
|
||||||
await task.cancel()
|
|
||||||
|
|
||||||
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
|
|
||||||
|
|
||||||
await runner.run(task)
|
|
||||||
|
|
||||||
|
|
||||||
async def bot(runner_args: RunnerArguments):
|
|
||||||
"""Main bot entry point compatible with Pipecat Cloud."""
|
|
||||||
transport = await create_transport(runner_args, transport_params)
|
|
||||||
await run_bot(transport, runner_args)
|
|
||||||
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
|
||||||
from pipecat.runner.run import main
|
|
||||||
|
|
||||||
main()
|
|
||||||
@@ -1,127 +0,0 @@
|
|||||||
#
|
|
||||||
# Copyright (c) 2024-2026, Daily
|
|
||||||
#
|
|
||||||
# SPDX-License-Identifier: BSD 2-Clause License
|
|
||||||
#
|
|
||||||
|
|
||||||
import asyncio
|
|
||||||
import os
|
|
||||||
|
|
||||||
from dotenv import load_dotenv
|
|
||||||
from loguru import logger
|
|
||||||
|
|
||||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
|
||||||
from pipecat.frames.frames import LLMRunFrame, STTUpdateSettingsFrame
|
|
||||||
from pipecat.pipeline.pipeline import Pipeline
|
|
||||||
from pipecat.pipeline.runner import PipelineRunner
|
|
||||||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
|
||||||
from pipecat.processors.aggregators.llm_context import LLMContext
|
|
||||||
from pipecat.processors.aggregators.llm_response_universal import (
|
|
||||||
LLMContextAggregatorPair,
|
|
||||||
LLMUserAggregatorParams,
|
|
||||||
)
|
|
||||||
from pipecat.runner.types import RunnerArguments
|
|
||||||
from pipecat.runner.utils import create_transport
|
|
||||||
from pipecat.services.cartesia.tts import CartesiaTTSService
|
|
||||||
from pipecat.services.hathora.stt import HathoraSTTService, HathoraSTTSettings
|
|
||||||
from pipecat.services.hathora.utils import ConfigOption
|
|
||||||
from pipecat.services.openai.llm import OpenAILLMService
|
|
||||||
from pipecat.transcriptions.language import Language
|
|
||||||
from pipecat.transports.base_transport import BaseTransport, TransportParams
|
|
||||||
from pipecat.transports.daily.transport import DailyParams
|
|
||||||
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
|
|
||||||
|
|
||||||
load_dotenv(override=True)
|
|
||||||
|
|
||||||
transport_params = {
|
|
||||||
"daily": lambda: DailyParams(
|
|
||||||
audio_in_enabled=True,
|
|
||||||
audio_out_enabled=True,
|
|
||||||
),
|
|
||||||
"twilio": lambda: FastAPIWebsocketParams(
|
|
||||||
audio_in_enabled=True,
|
|
||||||
audio_out_enabled=True,
|
|
||||||
),
|
|
||||||
"webrtc": lambda: TransportParams(
|
|
||||||
audio_in_enabled=True,
|
|
||||||
audio_out_enabled=True,
|
|
||||||
),
|
|
||||||
}
|
|
||||||
|
|
||||||
|
|
||||||
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
|
||||||
logger.info(f"Starting bot")
|
|
||||||
|
|
||||||
stt = HathoraSTTService(
|
|
||||||
api_key=os.getenv("HATHORA_API_KEY"), model="nvidia-parakeet-tdt-0.6b-v3"
|
|
||||||
)
|
|
||||||
|
|
||||||
tts = CartesiaTTSService(
|
|
||||||
api_key=os.getenv("CARTESIA_API_KEY"),
|
|
||||||
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
|
||||||
)
|
|
||||||
|
|
||||||
llm = OpenAILLMService(
|
|
||||||
api_key=os.getenv("OPENAI_API_KEY"),
|
|
||||||
system_instruction="You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way.",
|
|
||||||
)
|
|
||||||
|
|
||||||
context = LLMContext()
|
|
||||||
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
|
|
||||||
context,
|
|
||||||
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
|
|
||||||
)
|
|
||||||
|
|
||||||
pipeline = Pipeline(
|
|
||||||
[
|
|
||||||
transport.input(),
|
|
||||||
stt,
|
|
||||||
user_aggregator,
|
|
||||||
llm,
|
|
||||||
tts,
|
|
||||||
transport.output(),
|
|
||||||
assistant_aggregator,
|
|
||||||
]
|
|
||||||
)
|
|
||||||
|
|
||||||
task = PipelineTask(
|
|
||||||
pipeline,
|
|
||||||
params=PipelineParams(
|
|
||||||
enable_metrics=True,
|
|
||||||
enable_usage_metrics=True,
|
|
||||||
),
|
|
||||||
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
|
|
||||||
)
|
|
||||||
|
|
||||||
@transport.event_handler("on_client_connected")
|
|
||||||
async def on_client_connected(transport, client):
|
|
||||||
logger.info(f"Client connected")
|
|
||||||
context.add_message({"role": "system", "content": "Please introduce yourself to the user."})
|
|
||||||
await task.queue_frames([LLMRunFrame()])
|
|
||||||
|
|
||||||
await asyncio.sleep(10)
|
|
||||||
logger.info("Updating Hathora STT settings: language=es")
|
|
||||||
await task.queue_frame(
|
|
||||||
STTUpdateSettingsFrame(delta=HathoraSTTSettings(language=Language.ES))
|
|
||||||
)
|
|
||||||
|
|
||||||
@transport.event_handler("on_client_disconnected")
|
|
||||||
async def on_client_disconnected(transport, client):
|
|
||||||
logger.info(f"Client disconnected")
|
|
||||||
await task.cancel()
|
|
||||||
|
|
||||||
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
|
|
||||||
|
|
||||||
await runner.run(task)
|
|
||||||
|
|
||||||
|
|
||||||
async def bot(runner_args: RunnerArguments):
|
|
||||||
"""Main bot entry point compatible with Pipecat Cloud."""
|
|
||||||
transport = await create_transport(runner_args, transport_params)
|
|
||||||
await run_bot(transport, runner_args)
|
|
||||||
|
|
||||||
|
|
||||||
if __name__ == "__main__":
|
|
||||||
from pipecat.runner.run import main
|
|
||||||
|
|
||||||
main()
|
|
||||||
@@ -144,7 +144,6 @@ TESTS_07 = [
|
|||||||
("07ze-interruptible-hume.py", EVAL_SIMPLE_MATH),
|
("07ze-interruptible-hume.py", EVAL_SIMPLE_MATH),
|
||||||
("07zf-interruptible-gradium.py", EVAL_SIMPLE_MATH),
|
("07zf-interruptible-gradium.py", EVAL_SIMPLE_MATH),
|
||||||
("07zg-interruptible-camb.py", EVAL_SIMPLE_MATH),
|
("07zg-interruptible-camb.py", EVAL_SIMPLE_MATH),
|
||||||
("07zh-interruptible-hathora.py", EVAL_SIMPLE_MATH),
|
|
||||||
("07zi-interruptible-piper.py", EVAL_SIMPLE_MATH),
|
("07zi-interruptible-piper.py", EVAL_SIMPLE_MATH),
|
||||||
("07zj-interruptible-kokoro.py", EVAL_SIMPLE_MATH),
|
("07zj-interruptible-kokoro.py", EVAL_SIMPLE_MATH),
|
||||||
# Needs a local XTTS docker instance running.
|
# Needs a local XTTS docker instance running.
|
||||||
|
|||||||
@@ -1,176 +0,0 @@
|
|||||||
#
|
|
||||||
# Copyright (c) 2024–2025, Daily
|
|
||||||
#
|
|
||||||
# SPDX-License-Identifier: BSD 2-Clause License
|
|
||||||
#
|
|
||||||
|
|
||||||
"""[Hathora-hosted](https://models.hathora.dev) speech-to-text services."""
|
|
||||||
|
|
||||||
import base64
|
|
||||||
import os
|
|
||||||
from dataclasses import dataclass, field
|
|
||||||
from typing import AsyncGenerator, Optional
|
|
||||||
|
|
||||||
import aiohttp
|
|
||||||
from pydantic import BaseModel
|
|
||||||
|
|
||||||
from pipecat.frames.frames import (
|
|
||||||
ErrorFrame,
|
|
||||||
Frame,
|
|
||||||
TranscriptionFrame,
|
|
||||||
)
|
|
||||||
from pipecat.services.settings import NOT_GIVEN, STTSettings, _NotGiven
|
|
||||||
from pipecat.services.stt_latency import HATHORA_TTFS_P99
|
|
||||||
from pipecat.services.stt_service import SegmentedSTTService
|
|
||||||
from pipecat.transcriptions.language import Language
|
|
||||||
from pipecat.utils.time import time_now_iso8601
|
|
||||||
from pipecat.utils.tracing.service_decorators import traced_stt
|
|
||||||
|
|
||||||
from .utils import ConfigOption
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class HathoraSTTSettings(STTSettings):
|
|
||||||
"""Settings for the Hathora STT service.
|
|
||||||
|
|
||||||
Parameters:
|
|
||||||
config: Some models support additional config, refer to
|
|
||||||
`docs <https://models.hathora.dev>`_ for each model to see
|
|
||||||
what is supported.
|
|
||||||
"""
|
|
||||||
|
|
||||||
config: list[ConfigOption] | _NotGiven = field(default_factory=lambda: NOT_GIVEN)
|
|
||||||
|
|
||||||
|
|
||||||
class HathoraSTTService(SegmentedSTTService):
|
|
||||||
"""This service supports several different speech-to-text models hosted by Hathora.
|
|
||||||
|
|
||||||
[Documentation](https://models.hathora.dev)
|
|
||||||
"""
|
|
||||||
|
|
||||||
_settings: HathoraSTTSettings
|
|
||||||
|
|
||||||
class InputParams(BaseModel):
|
|
||||||
"""Optional input parameters for Hathora STT configuration.
|
|
||||||
|
|
||||||
Parameters:
|
|
||||||
language: Language code (if supported by model).
|
|
||||||
config: Some models support additional config, refer to
|
|
||||||
[docs](https://models.hathora.dev) for each model to see
|
|
||||||
what is supported.
|
|
||||||
"""
|
|
||||||
|
|
||||||
language: Optional[str] = None
|
|
||||||
config: Optional[list[ConfigOption]] = None
|
|
||||||
|
|
||||||
def __init__(
|
|
||||||
self,
|
|
||||||
*,
|
|
||||||
model: str,
|
|
||||||
sample_rate: Optional[int] = None,
|
|
||||||
api_key: Optional[str] = None,
|
|
||||||
base_url: str = "https://api.models.hathora.dev/inference/v1/stt",
|
|
||||||
params: Optional[InputParams] = None,
|
|
||||||
ttfs_p99_latency: Optional[float] = HATHORA_TTFS_P99,
|
|
||||||
**kwargs,
|
|
||||||
):
|
|
||||||
"""Initialize the Hathora STT service.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
model: Model to use; find available models
|
|
||||||
[here](https://models.hathora.dev).
|
|
||||||
sample_rate: The sample rate for audio input. If None, will be determined
|
|
||||||
from the start frame.
|
|
||||||
api_key: API key for authentication with the Hathora service;
|
|
||||||
provision one [here](https://models.hathora.dev/tokens).
|
|
||||||
base_url: Base API URL for the Hathora STT service.
|
|
||||||
params: Configuration parameters.
|
|
||||||
ttfs_p99_latency: P99 latency from speech end to final transcript in seconds.
|
|
||||||
Override for your deployment. See https://github.com/pipecat-ai/stt-benchmark
|
|
||||||
**kwargs: Additional arguments passed to the parent class.
|
|
||||||
"""
|
|
||||||
params = params or HathoraSTTService.InputParams()
|
|
||||||
|
|
||||||
super().__init__(
|
|
||||||
sample_rate=sample_rate,
|
|
||||||
ttfs_p99_latency=ttfs_p99_latency,
|
|
||||||
settings=HathoraSTTSettings(
|
|
||||||
model=model,
|
|
||||||
language=params.language,
|
|
||||||
config=params.config,
|
|
||||||
),
|
|
||||||
**kwargs,
|
|
||||||
)
|
|
||||||
self._api_key = api_key or os.getenv("HATHORA_API_KEY")
|
|
||||||
self._base_url = base_url
|
|
||||||
|
|
||||||
def can_generate_metrics(self) -> bool:
|
|
||||||
"""Check if this service can generate processing metrics.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
True
|
|
||||||
"""
|
|
||||||
return True
|
|
||||||
|
|
||||||
@traced_stt
|
|
||||||
async def _handle_transcription(
|
|
||||||
self, transcript: str, is_final: bool, language: Optional[Language] = None
|
|
||||||
):
|
|
||||||
"""Handle a transcription result with tracing."""
|
|
||||||
pass
|
|
||||||
|
|
||||||
async def run_stt(self, audio: bytes) -> AsyncGenerator[Frame, None]:
|
|
||||||
"""Run speech-to-text on the provided audio data.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
audio: Raw audio bytes to transcribe.
|
|
||||||
|
|
||||||
Yields:
|
|
||||||
Frame: Frames containing transcription results (typically TextFrame).
|
|
||||||
"""
|
|
||||||
try:
|
|
||||||
await self.start_processing_metrics()
|
|
||||||
|
|
||||||
url = f"{self._base_url}"
|
|
||||||
|
|
||||||
payload = {
|
|
||||||
"model": self._settings.model,
|
|
||||||
}
|
|
||||||
|
|
||||||
if self._settings.language is not None:
|
|
||||||
payload["language"] = self._settings.language
|
|
||||||
if self._settings.config is not None:
|
|
||||||
payload["model_config"] = [
|
|
||||||
{"name": option.name, "value": option.value} for option in self._settings.config
|
|
||||||
]
|
|
||||||
|
|
||||||
base64_audio = base64.b64encode(audio).decode("utf-8")
|
|
||||||
payload["audio"] = base64_audio
|
|
||||||
|
|
||||||
async with aiohttp.ClientSession() as session:
|
|
||||||
async with session.post(
|
|
||||||
url,
|
|
||||||
headers={"Authorization": f"Bearer {self._api_key}"},
|
|
||||||
json=payload,
|
|
||||||
) as resp:
|
|
||||||
response = await resp.json()
|
|
||||||
|
|
||||||
if response and "text" in response:
|
|
||||||
text = response["text"].strip()
|
|
||||||
if text: # Only yield non-empty text
|
|
||||||
# Hathora's API currently doesn't return language info
|
|
||||||
# so we default to the requested language or "en"
|
|
||||||
response_language = self._settings.language or "en"
|
|
||||||
await self._handle_transcription(text, True, response_language)
|
|
||||||
yield TranscriptionFrame(
|
|
||||||
text,
|
|
||||||
self._user_id,
|
|
||||||
time_now_iso8601(),
|
|
||||||
Language(response_language),
|
|
||||||
result=response,
|
|
||||||
)
|
|
||||||
|
|
||||||
await self.stop_processing_metrics()
|
|
||||||
|
|
||||||
except Exception as e:
|
|
||||||
yield ErrorFrame(error=f"Unknown error occurred: {e}")
|
|
||||||
@@ -1,191 +0,0 @@
|
|||||||
#
|
|
||||||
# Copyright (c) 2024–2025, Daily
|
|
||||||
#
|
|
||||||
# SPDX-License-Identifier: BSD 2-Clause License
|
|
||||||
#
|
|
||||||
|
|
||||||
"""[Hathora-hosted](https://models.hathora.dev) text-to-speech services."""
|
|
||||||
|
|
||||||
import io
|
|
||||||
import os
|
|
||||||
import wave
|
|
||||||
from dataclasses import dataclass, field
|
|
||||||
from typing import AsyncGenerator, Optional, Tuple
|
|
||||||
|
|
||||||
import aiohttp
|
|
||||||
from pydantic import BaseModel
|
|
||||||
|
|
||||||
from pipecat.frames.frames import (
|
|
||||||
ErrorFrame,
|
|
||||||
Frame,
|
|
||||||
TTSAudioRawFrame,
|
|
||||||
TTSStartedFrame,
|
|
||||||
TTSStoppedFrame,
|
|
||||||
)
|
|
||||||
from pipecat.services.settings import NOT_GIVEN, TTSSettings, _NotGiven
|
|
||||||
from pipecat.services.tts_service import TTSService
|
|
||||||
from pipecat.utils.tracing.service_decorators import traced_tts
|
|
||||||
|
|
||||||
from .utils import ConfigOption
|
|
||||||
|
|
||||||
|
|
||||||
def _decode_audio_payload(
|
|
||||||
audio_bytes: bytes,
|
|
||||||
*,
|
|
||||||
fallback_sample_rate: int = 24000,
|
|
||||||
fallback_channels: int = 1,
|
|
||||||
) -> Tuple[bytes, int, int]:
|
|
||||||
"""Convert a WAV/PCM payload into raw PCM samples for TTSAudioRawFrame."""
|
|
||||||
try:
|
|
||||||
with wave.open(io.BytesIO(audio_bytes), "rb") as wav_reader:
|
|
||||||
channels = wav_reader.getnchannels()
|
|
||||||
sample_rate = wav_reader.getframerate()
|
|
||||||
frames = wav_reader.readframes(wav_reader.getnframes())
|
|
||||||
return frames, sample_rate, channels
|
|
||||||
except (wave.Error, EOFError):
|
|
||||||
# If the payload is already raw PCM, just pass it through.
|
|
||||||
return audio_bytes, fallback_sample_rate, fallback_channels
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class HathoraTTSSettings(TTSSettings):
|
|
||||||
"""Settings for Hathora TTS service.
|
|
||||||
|
|
||||||
Parameters:
|
|
||||||
speed: Speech speed multiplier (if supported by model).
|
|
||||||
config: Some models support additional config, refer to
|
|
||||||
[docs](https://models.hathora.dev) for each model to see
|
|
||||||
what is supported.
|
|
||||||
"""
|
|
||||||
|
|
||||||
speed: float | _NotGiven = field(default_factory=lambda: NOT_GIVEN)
|
|
||||||
config: list[ConfigOption] | _NotGiven = field(default_factory=lambda: NOT_GIVEN)
|
|
||||||
|
|
||||||
|
|
||||||
class HathoraTTSService(TTSService):
|
|
||||||
"""This service supports several different text-to-speech models hosted by Hathora.
|
|
||||||
|
|
||||||
[Documentation](https://models.hathora.dev)
|
|
||||||
"""
|
|
||||||
|
|
||||||
_settings: HathoraTTSSettings
|
|
||||||
|
|
||||||
class InputParams(BaseModel):
|
|
||||||
"""Optional input parameters for Hathora TTS configuration.
|
|
||||||
|
|
||||||
Parameters:
|
|
||||||
speed: Speech speed multiplier (if supported by model).
|
|
||||||
config: Some models support additional config, refer to
|
|
||||||
[docs](https://models.hathora.dev) for each model to see
|
|
||||||
what is supported.
|
|
||||||
"""
|
|
||||||
|
|
||||||
speed: Optional[float] = None
|
|
||||||
config: Optional[list[ConfigOption]] = None
|
|
||||||
|
|
||||||
def __init__(
|
|
||||||
self,
|
|
||||||
*,
|
|
||||||
model: str,
|
|
||||||
voice_id: Optional[str] = None,
|
|
||||||
sample_rate: Optional[int] = None,
|
|
||||||
api_key: Optional[str] = None,
|
|
||||||
base_url: str = "https://api.models.hathora.dev/inference/v1/tts",
|
|
||||||
params: Optional[InputParams] = None,
|
|
||||||
**kwargs,
|
|
||||||
):
|
|
||||||
"""Initialize the Hathora TTS service.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
model: Model to use; find available models
|
|
||||||
[here](https://models.hathora.dev).
|
|
||||||
voice_id: Voice to use for synthesis (if supported by model).
|
|
||||||
sample_rate: Output sample rate for generated audio.
|
|
||||||
api_key: API key for authentication with the Hathora service;
|
|
||||||
provision one [here](https://models.hathora.dev/tokens).
|
|
||||||
base_url: Base API URL for the Hathora TTS service.
|
|
||||||
params: Configuration parameters.
|
|
||||||
**kwargs: Additional arguments passed to the parent class.
|
|
||||||
"""
|
|
||||||
params = params or HathoraTTSService.InputParams()
|
|
||||||
|
|
||||||
super().__init__(
|
|
||||||
sample_rate=sample_rate,
|
|
||||||
settings=HathoraTTSSettings(
|
|
||||||
model=model,
|
|
||||||
voice=voice_id,
|
|
||||||
language=None, # Not applicable here
|
|
||||||
speed=params.speed,
|
|
||||||
config=params.config,
|
|
||||||
),
|
|
||||||
**kwargs,
|
|
||||||
)
|
|
||||||
self._api_key = api_key or os.getenv("HATHORA_API_KEY")
|
|
||||||
self._base_url = base_url
|
|
||||||
|
|
||||||
def can_generate_metrics(self) -> bool:
|
|
||||||
"""Check if this service can generate processing metrics.
|
|
||||||
|
|
||||||
Returns:
|
|
||||||
True
|
|
||||||
"""
|
|
||||||
return True
|
|
||||||
|
|
||||||
@traced_tts
|
|
||||||
async def run_tts(self, text: str, context_id: str) -> AsyncGenerator[Frame, None]:
|
|
||||||
"""Run text-to-speech synthesis on the provided text.
|
|
||||||
|
|
||||||
Args:
|
|
||||||
text: The text to synthesize into speech.
|
|
||||||
context_id: The context ID for tracking audio frames.
|
|
||||||
|
|
||||||
Yields:
|
|
||||||
Frame: Audio frames containing the synthesized speech.
|
|
||||||
"""
|
|
||||||
try:
|
|
||||||
await self.start_processing_metrics()
|
|
||||||
await self.start_ttfb_metrics()
|
|
||||||
|
|
||||||
url = f"{self._base_url}"
|
|
||||||
|
|
||||||
payload = {"model": self._settings.model, "text": text}
|
|
||||||
|
|
||||||
if self._settings.voice is not None:
|
|
||||||
payload["voice"] = self._settings.voice
|
|
||||||
if self._settings.speed is not None:
|
|
||||||
payload["speed"] = self._settings.speed
|
|
||||||
if self._settings.config is not None:
|
|
||||||
payload["model_config"] = [
|
|
||||||
{"name": option.name, "value": option.value} for option in self._settings.config
|
|
||||||
]
|
|
||||||
|
|
||||||
yield TTSStartedFrame(context_id=context_id)
|
|
||||||
|
|
||||||
async with aiohttp.ClientSession() as session:
|
|
||||||
async with session.post(
|
|
||||||
url,
|
|
||||||
headers={"Authorization": f"Bearer {self._api_key}"},
|
|
||||||
json=payload,
|
|
||||||
) as resp:
|
|
||||||
audio_data = await resp.read()
|
|
||||||
|
|
||||||
pcm_audio, sample_rate, num_channels = _decode_audio_payload(
|
|
||||||
audio_data,
|
|
||||||
fallback_sample_rate=self.sample_rate,
|
|
||||||
)
|
|
||||||
|
|
||||||
frame = TTSAudioRawFrame(
|
|
||||||
audio=pcm_audio,
|
|
||||||
sample_rate=self.sample_rate,
|
|
||||||
num_channels=num_channels,
|
|
||||||
context_id=context_id,
|
|
||||||
)
|
|
||||||
|
|
||||||
yield frame
|
|
||||||
|
|
||||||
except Exception as e:
|
|
||||||
yield ErrorFrame(error=f"Unknown error occurred: {e}")
|
|
||||||
finally:
|
|
||||||
await self.stop_ttfb_metrics()
|
|
||||||
await self.stop_processing_metrics()
|
|
||||||
yield TTSStoppedFrame(context_id=context_id)
|
|
||||||
@@ -1,22 +0,0 @@
|
|||||||
#
|
|
||||||
# Copyright (c) 2024–2025, Daily
|
|
||||||
#
|
|
||||||
# SPDX-License-Identifier: BSD 2-Clause License
|
|
||||||
#
|
|
||||||
|
|
||||||
"""Utilities and types for [Hathora-hosted](https://models.hathora.dev) voice services."""
|
|
||||||
|
|
||||||
from dataclasses import dataclass
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class ConfigOption:
|
|
||||||
"""Extra configuration option passed into model_config for Hathora (if supported by model).
|
|
||||||
|
|
||||||
Args:
|
|
||||||
name: Name of the configuration option.
|
|
||||||
value: Value of the configuration option.
|
|
||||||
"""
|
|
||||||
|
|
||||||
name: str
|
|
||||||
value: str
|
|
||||||
@@ -40,7 +40,6 @@ GLADIA_TTFS_P99: float = 1.49
|
|||||||
GOOGLE_TTFS_P99: float = 1.57
|
GOOGLE_TTFS_P99: float = 1.57
|
||||||
GRADIUM_TTFS_P99: float = 1.61
|
GRADIUM_TTFS_P99: float = 1.61
|
||||||
GROQ_TTFS_P99: float = 1.54
|
GROQ_TTFS_P99: float = 1.54
|
||||||
HATHORA_TTFS_P99: float = 0.87
|
|
||||||
OPENAI_TTFS_P99: float = 2.01
|
OPENAI_TTFS_P99: float = 2.01
|
||||||
OPENAI_REALTIME_TTFS_P99: float = 1.66
|
OPENAI_REALTIME_TTFS_P99: float = 1.66
|
||||||
SAMBANOVA_TTFS_P99: float = 2.20
|
SAMBANOVA_TTFS_P99: float = 2.20
|
||||||
|
|||||||
Reference in New Issue
Block a user