Merge pull request #1177 from pipecat-ai/mb/perplexity
Add PerplexityLLMService
This commit is contained in:
Mark Backman
@@ -14,6 +14,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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base class `BaseWhisperSTTService` to handle common Whisper API
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base class `BaseWhisperSTTService` to handle common Whisper API
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functionality.
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functionality.
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- Added `PerplexityLLMService` for Perplexity NIM API integration, with an
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OpenAI-compatible interface. Also, added foundational example
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`14n-function-calling-perplexity.py`.
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### Changed
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### Changed
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- Updated foundation example `14f-function-calling-groq.py` to use
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- Updated foundation example `14f-function-calling-groq.py` to use
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22
README.md
22
README.md
@@ -55,17 +55,17 @@ pip install "pipecat-ai[option,...]"
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### Available services
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### Available services
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| Category | Services | Install Command Example |
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| Category | Services | Install Command Example |
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| ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
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| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------- |
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| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | `pip install "pipecat-ai[deepgram]"` |
|
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) | `pip install "pipecat-ai[deepgram]"` |
|
||||||
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [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), [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), [Together AI](https://docs.pipecat.ai/server/services/llm/together) | `pip install "pipecat-ai[openai]"` |
|
| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [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), [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), [Together AI](https://docs.pipecat.ai/server/services/llm/together) | `pip install "pipecat-ai[openai]"` |
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||||||
| Text-to-Speech | [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [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), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | `pip install "pipecat-ai[cartesia]"` |
|
| Text-to-Speech | [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [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), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) | `pip install "pipecat-ai[cartesia]"` |
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| Speech-to-Speech | [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) | `pip install "pipecat-ai[openai]"` |
|
| Speech-to-Speech | [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai) | `pip install "pipecat-ai[google]"` |
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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), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | `pip install "pipecat-ai[daily]"` |
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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), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local | `pip install "pipecat-ai[daily]"` |
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| Video | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | `pip install "pipecat-ai[tavus,simli]"` |
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| Video | [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli) | `pip install "pipecat-ai[tavus,simli]"` |
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| Vision & Image | [Moondream](https://docs.pipecat.ai/server/services/vision/moondream), [fal](https://docs.pipecat.ai/server/services/image-generation/fal) | `pip install "pipecat-ai[moondream]"` |
|
| Vision & Image | [Moondream](https://docs.pipecat.ai/server/services/vision/moondream), [fal](https://docs.pipecat.ai/server/services/image-generation/fal) | `pip install "pipecat-ai[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), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter) | `pip install "pipecat-ai[silero]"` |
|
| 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), [Noisereduce](https://docs.pipecat.ai/server/utilities/audio/noisereduce-filter) | `pip install "pipecat-ai[silero]"` |
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| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/server/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | `pip install "pipecat-ai[canonical]"` |
|
| Analytics & Metrics | [Canonical AI](https://docs.pipecat.ai/server/services/analytics/canonical), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) | `pip install "pipecat-ai[canonical]"` |
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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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106
examples/foundational/14n-function-calling-perplexity.py
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106
examples/foundational/14n-function-calling-perplexity.py
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@@ -0,0 +1,106 @@
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#
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# Copyright (c) 2024–2025, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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"""This example demonstrates using the Perplexity API as a drop-in replacement for OpenAI.
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Note that while this file is in the function-calling examples, Perplexity's API does not
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currently support function calling. The example shows basic chat completion functionality
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using Perplexity's API while maintaining compatibility with the OpenAI interface.
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"""
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import asyncio
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import os
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import sys
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import aiohttp
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from dotenv import load_dotenv
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from loguru import logger
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from openai.types.chat import ChatCompletionToolParam
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from runner import configure
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from pipecat.audio.vad.silero import SileroVADAnalyzer
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from pipecat.frames.frames import TTSSpeakFrame
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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.services.cartesia import CartesiaTTSService
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from pipecat.services.openai import OpenAILLMContext, OpenAILLMService
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from pipecat.services.perplexity import PerplexityLLMService
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from pipecat.transports.services.daily import DailyParams, DailyTransport
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load_dotenv(override=True)
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logger.remove(0)
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logger.add(sys.stderr, level="DEBUG")
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async def main():
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async with aiohttp.ClientSession() as session:
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(room_url, token) = await configure(session)
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transport = DailyTransport(
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room_url,
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token,
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"Respond bot",
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DailyParams(
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audio_out_enabled=True,
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transcription_enabled=True,
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vad_enabled=True,
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vad_analyzer=SileroVADAnalyzer(),
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),
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)
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tts = CartesiaTTSService(
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api_key=os.getenv("CARTESIA_API_KEY"),
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voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
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)
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llm = PerplexityLLMService(api_key=os.getenv("PERPLEXITY_API_KEY"), model="sonar")
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messages = [
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{
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"role": "user",
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"content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
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},
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]
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context = OpenAILLMContext(messages)
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context_aggregator = llm.create_context_aggregator(context)
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pipeline = Pipeline(
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[
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transport.input(),
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context_aggregator.user(),
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llm,
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tts,
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transport.output(),
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context_aggregator.assistant(),
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]
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)
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task = PipelineTask(
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pipeline,
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PipelineParams(
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allow_interruptions=True,
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enable_metrics=True,
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enable_usage_metrics=True,
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report_only_initial_ttfb=True,
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),
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)
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@transport.event_handler("on_first_participant_joined")
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async def on_first_participant_joined(transport, participant):
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await transport.capture_participant_transcription(participant["id"])
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# Kick off the conversation.
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await task.queue_frames([context_aggregator.user().get_context_frame()])
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runner = PipelineRunner()
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await runner.run(task)
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if __name__ == "__main__":
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asyncio.run(main())
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@@ -71,6 +71,7 @@ nim = [ "openai~=1.59.6" ]
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noisereduce = [ "noisereduce~=3.0.3" ]
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noisereduce = [ "noisereduce~=3.0.3" ]
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openai = [ "openai~=1.59.6", "websockets~=13.1", "python-deepcompare~=2.1.0" ]
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openai = [ "openai~=1.59.6", "websockets~=13.1", "python-deepcompare~=2.1.0" ]
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openpipe = [ "openpipe~=4.45.0" ]
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openpipe = [ "openpipe~=4.45.0" ]
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perplexity = [ "openai~=1.59.6" ]
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playht = [ "pyht~=0.1.6", "websockets~=13.1" ]
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playht = [ "pyht~=0.1.6", "websockets~=13.1" ]
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riva = [ "nvidia-riva-client~=2.18.0" ]
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riva = [ "nvidia-riva-client~=2.18.0" ]
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sentry = [ "sentry-sdk~=2.20.0" ]
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sentry = [ "sentry-sdk~=2.20.0" ]
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141
src/pipecat/services/perplexity.py
Normal file
141
src/pipecat/services/perplexity.py
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@@ -0,0 +1,141 @@
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#
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# Copyright (c) 2024–2025, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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from typing import List
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from loguru import logger
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from pipecat.metrics.metrics import LLMTokenUsage
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from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
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from pipecat.services.openai import OpenAILLMService
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try:
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from openai import (
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NOT_GIVEN,
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AsyncStream,
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)
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from openai.types.chat import ChatCompletionChunk, ChatCompletionMessageParam
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except ModuleNotFoundError as e:
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logger.error(f"Exception: {e}")
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logger.error(
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"In order to use Perplexity, you need to `pip install pipecat-ai[perplexity]`. Also, set `PERPLEXITY_API_KEY` environment variable."
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)
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raise Exception(f"Missing module: {e}")
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class PerplexityLLMService(OpenAILLMService):
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"""A service for interacting with Perplexity's API.
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This service extends OpenAILLMService to work with Perplexity's API while maintaining
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compatibility with the OpenAI-style interface. It specifically handles the difference
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in token usage reporting between Perplexity (incremental) and OpenAI (final summary).
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Args:
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api_key (str): The API key for accessing Perplexity's API
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base_url (str, optional): The base URL for Perplexity's API. Defaults to "https://api.perplexity.ai"
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model (str, optional): The model identifier to use. Defaults to "sonar"
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**kwargs: Additional keyword arguments passed to OpenAILLMService
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"""
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def __init__(
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self,
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*,
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api_key: str,
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base_url: str = "https://api.perplexity.ai",
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model: str = "sonar",
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**kwargs,
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):
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super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs)
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# Counters for accumulating token usage metrics
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self._prompt_tokens = 0
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self._completion_tokens = 0
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self._total_tokens = 0
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self._has_reported_prompt_tokens = False
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self._is_processing = False
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async def get_chat_completions(
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self, context: OpenAILLMContext, messages: List[ChatCompletionMessageParam]
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) -> AsyncStream[ChatCompletionChunk]:
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"""Get chat completions from Perplexity API using OpenAI-compatible parameters.
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Args:
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context: The context containing conversation history and settings
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messages: The messages to send to the API
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Returns:
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A stream of chat completion chunks
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"""
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params = {
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"model": self.model_name,
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"stream": True,
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"messages": messages,
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}
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# Add OpenAI-compatible parameters if they're set
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if self._settings["frequency_penalty"] is not NOT_GIVEN:
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params["frequency_penalty"] = self._settings["frequency_penalty"]
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if self._settings["presence_penalty"] is not NOT_GIVEN:
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params["presence_penalty"] = self._settings["presence_penalty"]
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if self._settings["temperature"] is not NOT_GIVEN:
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params["temperature"] = self._settings["temperature"]
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if self._settings["top_p"] is not NOT_GIVEN:
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params["top_p"] = self._settings["top_p"]
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if self._settings["max_tokens"] is not NOT_GIVEN:
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params["max_tokens"] = self._settings["max_tokens"]
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chunks = await self._client.chat.completions.create(**params)
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return chunks
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async def _process_context(self, context: OpenAILLMContext):
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||||||
|
"""Process a context through the LLM and accumulate token usage metrics.
|
||||||
|
|
||||||
|
This method overrides the parent class implementation to handle
|
||||||
|
Perplexity's incremental token reporting style, accumulating the counts
|
||||||
|
and reporting them once at the end of processing.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
context (OpenAILLMContext): The context to process, containing messages
|
||||||
|
and other information needed for the LLM interaction.
|
||||||
|
"""
|
||||||
|
# Reset all counters and flags at the start of processing
|
||||||
|
self._prompt_tokens = 0
|
||||||
|
self._completion_tokens = 0
|
||||||
|
self._total_tokens = 0
|
||||||
|
self._has_reported_prompt_tokens = False
|
||||||
|
self._is_processing = True
|
||||||
|
|
||||||
|
try:
|
||||||
|
await super()._process_context(context)
|
||||||
|
finally:
|
||||||
|
self._is_processing = False
|
||||||
|
# Report final accumulated token usage at the end of processing
|
||||||
|
if self._prompt_tokens > 0 or self._completion_tokens > 0:
|
||||||
|
self._total_tokens = self._prompt_tokens + self._completion_tokens
|
||||||
|
tokens = LLMTokenUsage(
|
||||||
|
prompt_tokens=self._prompt_tokens,
|
||||||
|
completion_tokens=self._completion_tokens,
|
||||||
|
total_tokens=self._total_tokens,
|
||||||
|
)
|
||||||
|
await super().start_llm_usage_metrics(tokens)
|
||||||
|
|
||||||
|
async def start_llm_usage_metrics(self, tokens: LLMTokenUsage):
|
||||||
|
"""Accumulate token usage metrics during processing.
|
||||||
|
|
||||||
|
Perplexity reports token usage incrementally during streaming,
|
||||||
|
unlike OpenAI which provides a final summary. We accumulate the
|
||||||
|
counts and report the total at the end of processing.
|
||||||
|
"""
|
||||||
|
if not self._is_processing:
|
||||||
|
return
|
||||||
|
|
||||||
|
# Record prompt tokens the first time we see them
|
||||||
|
if not self._has_reported_prompt_tokens and tokens.prompt_tokens > 0:
|
||||||
|
self._prompt_tokens = tokens.prompt_tokens
|
||||||
|
self._has_reported_prompt_tokens = True
|
||||||
|
|
||||||
|
# Update completion tokens count if it has increased
|
||||||
|
if tokens.completion_tokens > self._completion_tokens:
|
||||||
|
self._completion_tokens = tokens.completion_tokens
|
||||||
Reference in New Issue
Block a user