removed old Gemini Live example

examples/foundational/26-gemini-live.py

@@ -1,133 +0,0 @@
-#
-# Copyright (c) 2024-2026, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import os
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.audio.vad.silero import SileroVADAnalyzer
-from pipecat.audio.vad.vad_analyzer import VADParams
-from pipecat.frames.frames import LLMMessagesAppendFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineParams, PipelineTask
-from pipecat.processors.audio.vad_processor import VADProcessor
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.google.gemini_live.llm import GeminiLiveLLMService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-# Load environment variables
-load_dotenv(override=True)
-
-
-# We use lambdas to defer transport parameter creation until the transport
-# type is selected at runtime.
-transport_params = {
-    "daily": lambda: DailyParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-        # set stop_secs to something roughly similar to the internal setting
-        # of the Multimodal Live api, just to align events.
-    ),
-    "twilio": lambda: FastAPIWebsocketParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-        # set stop_secs to something roughly similar to the internal setting
-        # of the Multimodal Live api, just to align events.
-    ),
-    "webrtc": lambda: TransportParams(
-        audio_in_enabled=True,
-        audio_out_enabled=True,
-        # set stop_secs to something roughly similar to the internal setting
-        # of the Multimodal Live api, just to align events.
-    ),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    # Create the Gemini Multimodal Live LLM service
-    system_instruction = f"""
-    You are a helpful AI assistant.
-    Your goal is to demonstrate your capabilities in a helpful and engaging 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.
-    """
-
-    llm = GeminiLiveLLMService(
-        api_key=os.getenv("GOOGLE_API_KEY"),
-        settings=GeminiLiveLLMService.Settings(
-            system_instruction=system_instruction,
-            voice="Puck",  # Aoede, Charon, Fenrir, Kore, Puck
-        ),
-    )
-
-    vad_processor = VADProcessor(vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)))
-
-    # Build the pipeline
-    pipeline = Pipeline(
-        [
-            transport.input(),
-            vad_processor,
-            llm,
-            transport.output(),
-        ]
-    )
-
-    # Configure the pipeline task
-    task = PipelineTask(
-        pipeline,
-        params=PipelineParams(
-            enable_metrics=True,
-            enable_usage_metrics=True,
-        ),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
-
-    # Handle client connection event
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        logger.info(f"Client connected")
-        # Kick off the conversation.
-        await task.queue_frames(
-            [
-                LLMMessagesAppendFrame(
-                    messages=[
-                        {
-                            "role": "user",
-                            "content": f"Greet the user and introduce yourself.",
-                        }
-                    ]
-                )
-            ]
-        )
-
-    # Handle client disconnection events
-    @transport.event_handler("on_client_disconnected")
-    async def on_client_disconnected(transport, client):
-        logger.info(f"Client disconnected")
-        await task.cancel()
-
-    # Run the pipeline
-    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()