Added 07n-interruptible-gemini
This commit is contained in:
Mark Backman
@@ -9,6 +9,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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### Added
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- Added `GeminiTTSService` which uses Google Gemini to generate TTS output. The
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Gemini model can be prompted to insert styled speech to control the TTS
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output.
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- Added Exotel support to Pipecat's development runner. You can now connect
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using the runner with `uv run bot.py -t exotel` and an ngrok connection to
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HTTP port 7860.
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@@ -76,6 +80,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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(e.g. `ParallelPipeline`) into a single processor so the main pipeline becomes
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simpler.
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- Added `07n-interruptible-gemini.py`, demonstrating how to use
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`GeminiTTSService`.
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## [0.0.79] - 2025-08-07
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### Changed
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163
examples/foundational/07n-interruptible-gemini.py
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163
examples/foundational/07n-interruptible-gemini.py
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@@ -0,0 +1,163 @@
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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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"""
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A conversational AI bot using Gemini for both LLM and TTS.
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This example demonstrates how to use Gemini's TTS capabilities with the new
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GeminiTTSService, which uses Gemini's TTS-specific models instead of Google Cloud TTS.
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Features showcased:
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- Gemini LLM for conversation
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- Gemini TTS with natural voice control
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- Support for different voice personalities
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- Style and tone control through natural language prompts
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Run with:
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python examples/foundational/gemini-tts.py
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Make sure to set your environment variables:
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export GOOGLE_API_KEY=your_api_key_here
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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.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.openai_llm_context import OpenAILLMContext
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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.google.llm import GoogleLLMService
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from pipecat.services.google.stt import GoogleSTTService
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from pipecat.services.google.tts import GeminiTTSService
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from pipecat.transcriptions.language import Language
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
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from pipecat.transports.services.daily import DailyParams
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load_dotenv(override=True)
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# We store functions so objects (e.g. SileroVADAnalyzer) don't get
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# instantiated. The function will be called when the desired transport gets
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# selected.
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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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vad_analyzer=SileroVADAnalyzer(),
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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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vad_analyzer=SileroVADAnalyzer(),
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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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vad_analyzer=SileroVADAnalyzer(),
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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 with Gemini TTS")
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stt = GoogleSTTService(
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params=GoogleSTTService.InputParams(languages=Language.EN_US),
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credentials=os.getenv("GOOGLE_TEST_CREDENTIALS"),
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)
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tts = GeminiTTSService(
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api_key=os.getenv("GOOGLE_API_KEY"),
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model="gemini-2.5-flash-preview-tts", # TTS-specific model
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voice_id="Charon",
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params=GeminiTTSService.InputParams(language=Language.EN_US),
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)
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llm = GoogleLLMService(
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api_key=os.getenv("GOOGLE_API_KEY"),
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model="gemini-2.5-flash",
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)
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# System message that instructs the AI on how to speak
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messages = [
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{
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"role": "system",
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"content": """You are a helpful AI assistant in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way.
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IMPORTANT: Since you're using Gemini TTS which supports natural voice control, you can include speaking instructions in your responses. For example:
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- "Say cheerfully: Welcome to our conversation!"
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- "Read this in a calm, professional tone: Here are the details you requested."
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- "Speak in an excited whisper: I have some great news to share!"
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- "Say slowly and clearly: Let me explain this step by step."
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Feel free to use natural language instructions to control your voice style, tone, pace, and emotion. The TTS system will interpret these instructions and adjust the speech accordingly.
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Your output will be converted to audio, so avoid 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(), # Transport user input
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stt, # STT
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context_aggregator.user(), # User responses
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llm, # LLM
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tts, # Gemini 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 with a styled introduction
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messages.append(
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{
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"role": "system",
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"content": "Say cheerfully and warmly: Hello! I'm your AI assistant powered by Gemini's new TTS technology. I can speak with different voices, tones, and styles. How can I help you today?",
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}
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)
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await task.queue_frames([context_aggregator.user().get_context_frame()])
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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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@@ -68,6 +68,7 @@ TESTS_07 = [
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("07k-interruptible-lmnt.py", PROMPT_SIMPLE_MATH, None),
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("07l-interruptible-groq.py", PROMPT_SIMPLE_MATH, None),
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("07m-interruptible-aws.py", PROMPT_SIMPLE_MATH, None),
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("07n-interruptible-gemini.py", PROMPT_SIMPLE_MATH, None),
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("07n-interruptible-google.py", PROMPT_SIMPLE_MATH, None),
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("07o-interruptible-assemblyai.py", PROMPT_SIMPLE_MATH, None),
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("07q-interruptible-rime.py", PROMPT_SIMPLE_MATH, None),
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