Update release evals for OpenAI Realtime, Gemini Live Vertex; shorten 26 foundational names

examples/foundational/26d-gemini-live-text.py

@@ -0,0 +1,158 @@
+#
+# Copyright (c) 2024–2025, 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 LLMRunFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.runner.types import RunnerArguments
+from pipecat.runner.utils import create_transport
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.services.google.gemini_live.llm import (
+    GeminiLiveLLMService,
+    GeminiModalities,
+    InputParams,
+)
+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)
+
+
+SYSTEM_INSTRUCTION = f"""
+"You are Gemini Chatbot, a friendly, helpful robot.
+
+Your goal is to demonstrate your capabilities in a succinct way.
+
+Your output will be converted to audio so don't include special characters in your answers.
+
+Respond to what the user said in a creative and helpful way. Keep your responses brief. One or two sentences at most.
+"""
+
+
+# We store functions so objects (e.g. SileroVADAnalyzer) don't get
+# instantiated. The function will be called when the desired transport gets
+# selected.
+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. This doesn't really
+        # matter because we can only use the Multimodal Live API's phrase
+        # endpointing, for now.
+        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)),
+    ),
+    "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. This doesn't really
+        # matter because we can only use the Multimodal Live API's phrase
+        # endpointing, for now.
+        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)),
+    ),
+    "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. This doesn't really
+        # matter because we can only use the Multimodal Live API's phrase
+        # endpointing, for now.
+        vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)),
+    ),
+}
+
+
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
+    logger.info(f"Starting bot")
+
+    # KNOWN ISSUE: If using GeminiVertexLiveLLMService, it appears
+    # you cannot specify a modality other than AUDIO.
+    llm = GeminiLiveLLMService(
+        api_key=os.getenv("GOOGLE_API_KEY"),
+        system_instruction=SYSTEM_INSTRUCTION,
+        tools=[{"google_search": {}}, {"code_execution": {}}],
+        params=InputParams(modalities=GeminiModalities.TEXT),
+    )
+
+    # Optionally, you can set the response modalities via a function
+    # llm.set_model_modalities(
+    #     GeminiMultimodalModalities.TEXT
+    # )
+
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"), voice_id="71a7ad14-091c-4e8e-a314-022ece01c121"
+    )
+
+    messages = [
+        {
+            "role": "user",
+            "content": 'Start by saying "Hello, I\'m Gemini".',
+        },
+    ]
+
+    # Set up conversation context and management
+    # The context_aggregator will automatically collect conversation context
+    context = OpenAILLMContext(messages)
+    context_aggregator = llm.create_context_aggregator(context)
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            context_aggregator.user(),
+            llm,
+            tts,
+            transport.output(),
+            context_aggregator.assistant(),
+        ]
+    )
+
+    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")
+        # Kick off the conversation.
+        await task.queue_frames([LLMRunFrame()])
+
+    @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()