chore: import upstream snapshot with attribution
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This commit is contained in:
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# Copyright 2026 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import asyncio
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from typing import AsyncGenerator
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from google.adk.agents import LiveRequestQueue
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from google.adk.agents.llm_agent import Agent
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from google.adk.tools.function_tool import FunctionTool
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from google.genai import types as genai_types
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async def monitor_stock_price(stock_symbol: str) -> AsyncGenerator[str, None]:
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"""This function will monitor the price for the given stock_symbol in a continuous, streaming and asynchronously way."""
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print(f"Start monitor stock price for {stock_symbol}!")
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# Let's mock stock price change.
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await asyncio.sleep(4)
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price_alert1 = f"the price for {stock_symbol} is 300"
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yield price_alert1
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print(price_alert1)
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await asyncio.sleep(4)
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price_alert1 = f"the price for {stock_symbol} is 400"
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yield price_alert1
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print(price_alert1)
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await asyncio.sleep(20)
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price_alert1 = f"the price for {stock_symbol} is 900"
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yield price_alert1
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print(price_alert1)
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await asyncio.sleep(20)
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price_alert1 = f"the price for {stock_symbol} is 500"
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yield price_alert1
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print(price_alert1)
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# for video streaming, `input_stream: LiveRequestQueue` is required and reserved key parameter for ADK to pass the video streams in.
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async def monitor_video_stream(
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input_stream: LiveRequestQueue,
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) -> AsyncGenerator[str, None]:
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"""Monitor how many people are in the video streams."""
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from google.genai import Client
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print("start monitor_video_stream!")
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from google.genai import Client
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client = Client(enterprise=False)
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prompt_text = (
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"Count the number of people in this image. Just respond with a numeric"
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" number."
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)
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last_count = None
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while True:
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last_valid_req = None
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print("Start monitoring loop")
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# use this loop to pull the latest images and discard the old ones
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while input_stream._queue.qsize() != 0:
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live_req = await input_stream.get()
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if live_req.blob is not None and live_req.blob.mime_type == "image/jpeg":
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last_valid_req = live_req
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# If we found a valid image, process it
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if last_valid_req is not None:
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print("Processing the most recent frame from the queue")
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# Create an image part using the blob's data and mime type
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image_part = genai_types.Part.from_bytes(
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data=last_valid_req.blob.data, mime_type=last_valid_req.blob.mime_type
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)
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contents = genai_types.Content(
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role="user",
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parts=[image_part, genai_types.Part.from_text(text=prompt_text)],
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)
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# Call the model to generate content based on the provided image and prompt
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response = client.models.generate_content(
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contents=contents,
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config=genai_types.GenerateContentConfig(
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system_instruction=(
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"You are a helpful video analysis assistant. You can count"
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" the number of people in this image or video. Just respond"
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" with a numeric number."
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)
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),
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)
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if not last_count:
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last_count = response.candidates[0].content.parts[0].text
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elif last_count != response.candidates[0].content.parts[0].text:
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last_count = response.candidates[0].content.parts[0].text
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yield response
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print("response:", response)
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# Wait before checking for new images
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await asyncio.sleep(0.5)
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# Use this exact function to help ADK stop your streaming tools when requested.
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# for example, if we want to stop `monitor_stock_price`, then the agent will
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# invoke this function with stop_streaming(function_name=monitor_stock_price).
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def stop_streaming(function_name: str):
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"""Stop the streaming
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Args:
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function_name: The name of the streaming function to stop.
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"""
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pass
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root_agent = Agent(
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# Find supported models in Vertex here: https://docs.cloud.google.com/vertex-ai/generative-ai/docs/live-api
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model="gemini-live-2.5-flash-native-audio", # Vertex
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# Find supported models in Gemini API here: https://ai.google.dev/gemini-api/docs/models
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# model='gemini-2.5-flash-native-audio-preview-12-2025', # Gemini API
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name="video_streaming_agent",
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instruction="""
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You are a monitoring agent. You can do video monitoring and stock price monitoring
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using the provided tools/functions.
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When users want to monitor a video stream,
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You can use monitor_video_stream function to do that. When monitor_video_stream
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returns the alert, you should tell the users.
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When users want to monitor a stock price, you can use monitor_stock_price.
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Don't ask too many questions. Don't be too talkative.
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""",
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tools=[
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monitor_video_stream,
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monitor_stock_price,
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FunctionTool(stop_streaming),
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],
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)
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