mirror of
https://github.com/google/adk-docs.git
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Gururaj Deshpande
ff454ac1c9
* fix: change call_agent to call_agent_async * added await in storyflow where missing * updated callbacks and storyflow with await and user comment * fixed more * added licencse header --------- Co-authored-by: Lavi Nigam <98014943+lavinigam-gcp@users.noreply.github.com> Co-authored-by: Lavi Nigam <lavinigam@google.com>
71 lines
2.6 KiB
Python
71 lines
2.6 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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import os
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from google.adk import Agent, Runner
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from google.adk.sessions import InMemorySessionService
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from google.adk.tools.langchain_tool import LangchainTool
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from google.genai import types
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from langchain_community.tools import TavilySearchResults
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# Ensure TAVILY_API_KEY is set in your environment
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if not os.getenv("TAVILY_API_KEY"):
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print("Warning: TAVILY_API_KEY environment variable not set.")
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APP_NAME = "news_app"
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USER_ID = "1234"
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SESSION_ID = "session1234"
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# Instantiate LangChain tool
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tavily_search = TavilySearchResults(
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max_results=5,
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search_depth="advanced",
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include_answer=True,
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include_raw_content=True,
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include_images=True,
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)
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# Wrap with LangchainTool
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adk_tavily_tool = LangchainTool(tool=tavily_search)
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# Define Agent with the wrapped tool
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my_agent = Agent(
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name="langchain_tool_agent",
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model="gemini-2.0-flash",
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description="Agent to answer questions using TavilySearch.",
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instruction="I can answer your questions by searching the internet. Just ask me anything!",
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tools=[adk_tavily_tool] # Add the wrapped tool here
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)
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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=my_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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# 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("stock price of GOOG")
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