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Mandy Chan
72 lines
3.4 KiB
Python
72 lines
3.4 KiB
Python
# Copyright 2025 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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from google.adk.agents import Agent
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from google.adk.runners import Runner
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from google.adk.sessions import InMemorySessionService
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from google.adk.tools.agent_tool import AgentTool
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from google.genai import types
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APP_NAME="summary_agent"
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USER_ID="user1234"
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SESSION_ID="1234"
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summary_agent = Agent(
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model="gemini-2.0-flash",
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name="summary_agent",
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instruction="""You are an expert summarizer. Please read the following text and provide a concise summary.""",
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description="Agent to summarize text",
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)
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root_agent = Agent(
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model='gemini-2.0-flash',
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name='root_agent',
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instruction="""You are a helpful assistant. When the user provides a text, use the 'summarize' tool to generate a summary. Always forward the user's message exactly as received to the 'summarize' tool, without modifying or summarizing it yourself. Present the response from the tool to the user.""",
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tools=[AgentTool(agent=summary_agent, skip_summarization=True)]
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)
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# Session and Runner
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async def setup_session_and_runner():
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session_service = InMemorySessionService()
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session = await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID)
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runner = Runner(agent=root_agent, app_name=APP_NAME, session_service=session_service)
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return session, runner
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# Agent Interaction
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async def call_agent_async(query):
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content = types.Content(role='user', parts=[types.Part(text=query)])
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session, runner = await setup_session_and_runner()
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events = runner.run_async(user_id=USER_ID, session_id=SESSION_ID, new_message=content)
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async for event in events:
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if event.is_final_response():
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final_response = event.content.parts[0].text
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print("Agent Response: ", final_response)
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long_text = """Quantum computing represents a fundamentally different approach to computation,
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leveraging the bizarre principles of quantum mechanics to process information. Unlike classical computers
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that rely on bits representing either 0 or 1, quantum computers use qubits which can exist in a state of superposition - effectively
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being 0, 1, or a combination of both simultaneously. Furthermore, qubits can become entangled,
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meaning their fates are intertwined regardless of distance, allowing for complex correlations. This parallelism and
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interconnectedness grant quantum computers the potential to solve specific types of incredibly complex problems - such
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as drug discovery, materials science, complex system optimization, and breaking certain types of cryptography - far
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faster than even the most powerful classical supercomputers could ever achieve, although the technology is still largely in its developmental stages."""
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# Note: In Colab, you can directly use 'await' at the top level.
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# If running this code as a standalone Python script, you'll need to use asyncio.run() or manage the event loop.
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await call_agent_async(long_text)
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