From 6e6e932370eb74f36a30ddfaeb35e57900a118a8 Mon Sep 17 00:00:00 2001 From: getchannel <78183014+getchannel@users.noreply.github.com> Date: Fri, 30 May 2025 17:36:36 -0400 Subject: [PATCH] Create 26g-gemini-multimodal-live-groundingMetadata.py --- ...emini-multimodal-live-groundingMetadata.py | 164 ++++++++++++++++++ 1 file changed, 164 insertions(+) create mode 100644 examples/foundational/26g-gemini-multimodal-live-groundingMetadata.py diff --git a/examples/foundational/26g-gemini-multimodal-live-groundingMetadata.py b/examples/foundational/26g-gemini-multimodal-live-groundingMetadata.py new file mode 100644 index 000000000..0c6d35ff0 --- /dev/null +++ b/examples/foundational/26g-gemini-multimodal-live-groundingMetadata.py @@ -0,0 +1,164 @@ + +import argparse +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.adapters.schemas.tools_schema import AdapterType, ToolsSchema +from pipecat.frames.frames import Frame +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.processors.frame_processor import FrameDirection, FrameProcessor +from pipecat.services.gemini_multimodal_live.gemini import GeminiMultimodalLiveLLMService +from pipecat.services.google.frames import LLMSearchResponseFrame +from pipecat.transports.base_transport import TransportParams +from pipecat.transports.network.small_webrtc import SmallWebRTCTransport +from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection + +load_dotenv(override=True) + +SYSTEM_INSTRUCTION = """ +You are a helpful AI assistant that actively uses Google Search to provide up-to-date, accurate information. + +IMPORTANT: For ANY question about current events, news, recent developments, real-time information, or anything that might have changed recently, you MUST use the google_search tool to get the latest information. + +You should use Google Search for: +- Current news and events +- Recent developments in any field +- Today's weather, stock prices, or other real-time data +- Any question that starts with "what's happening", "latest", "recent", "current", "today", etc. +- When you're not certain about recent information + +Always be proactive about using search when the user asks about anything that could benefit from real-time information. + +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, always using search for current information. +""" + + +class GroundingMetadataProcessor(FrameProcessor): + """Processor to capture and display grounding metadata from Gemini Live API.""" + + def __init__(self): + super().__init__() + self._grounding_count = 0 + + async def process_frame(self, frame: Frame, direction: FrameDirection): + # Always call super().process_frame first + await super().process_frame(frame, direction) + + # Only log important frame types, not every audio frame + if hasattr(frame, '__class__'): + frame_type = frame.__class__.__name__ + if frame_type in ['LLMTextFrame', 'TTSTextFrame', 'LLMFullResponseStartFrame', 'LLMFullResponseEndFrame']: + logger.debug(f"GroundingProcessor received: {frame_type}") + + if isinstance(frame, LLMSearchResponseFrame): + self._grounding_count += 1 + logger.info(f"\nšŸ” GROUNDING METADATA RECEIVED #{self._grounding_count}") + logger.info(f"šŸ“ Search Result Text: {frame.search_result[:200]}...") + + if frame.rendered_content: + logger.info(f"šŸ”— Rendered Content: {frame.rendered_content}") + + if frame.origins: + logger.info(f"šŸ“ Number of Origins: {len(frame.origins)}") + for i, origin in enumerate(frame.origins): + logger.info(f" Origin {i+1}: {origin.site_title} - {origin.site_uri}") + if origin.results: + logger.info(f" Results: {len(origin.results)} items") + + # Always push the frame downstream + await self.push_frame(frame, direction) + + +async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace): + logger.info(f"Starting Gemini Live Grounding Test Bot") + + # Initialize the SmallWebRTCTransport with the connection + transport = SmallWebRTCTransport( + webrtc_connection=webrtc_connection, + params=TransportParams( + audio_in_enabled=True, + audio_out_enabled=True, + video_in_enabled=False, + vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)), + ), + ) + + # Create tools using ToolsSchema with custom tools for Gemini + tools = ToolsSchema( + standard_tools=[], # No standard function declarations needed + custom_tools={ + AdapterType.GEMINI: [ + {"google_search": {}}, + {"code_execution": {}} + ] + } + ) + + llm = GeminiMultimodalLiveLLMService( + api_key=os.getenv("GOOGLE_API_KEY"), + system_instruction=SYSTEM_INSTRUCTION, + voice_id="Charon", # Aoede, Charon, Fenrir, Kore, Puck + transcribe_user_audio=True, + tools=tools, + ) + + # Create a processor to capture grounding metadata + grounding_processor = GroundingMetadataProcessor() + + messages = [ + { + "role": "user", + "content": 'Please introduce yourself and let me know that you can help with current information by searching the web. Ask me what current information I\'d like to know about.', + }, + ] + + # Set up conversation context and management + context = OpenAILLMContext(messages) + context_aggregator = llm.create_context_aggregator(context) + + pipeline = Pipeline( + [ + transport.input(), + context_aggregator.user(), + llm, + grounding_processor, # Add our grounding processor here + transport.output(), + context_aggregator.assistant(), + ] + ) + + task = PipelineTask(pipeline) + + @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([context_aggregator.user().get_context_frame()]) + + @transport.event_handler("on_client_disconnected") + async def on_client_disconnected(transport, client): + logger.info(f"Client disconnected") + + @transport.event_handler("on_client_closed") + async def on_client_closed(transport, client): + logger.info(f"Client closed connection") + await task.cancel() + + runner = PipelineRunner(handle_sigint=False) + + await runner.run(task) + + +if __name__ == "__main__": + from run import main + + main()