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>
111 lines
4.6 KiB
Python
111 lines
4.6 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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from google.adk.agents import LlmAgent
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from google.adk.runners import Runner
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from typing import Optional
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from google.genai import types
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from google.adk.sessions import InMemorySessionService
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from google.adk.tools import FunctionTool
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from google.adk.tools.tool_context import ToolContext
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from google.adk.tools.base_tool import BaseTool
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from typing import Dict, Any
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from copy import deepcopy
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GEMINI_2_FLASH="gemini-2.0-flash"
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# --- Define a Simple Tool Function (Same as before) ---
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def get_capital_city(country: str) -> str:
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"""Retrieves the capital city of a given country."""
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print(f"--- Tool 'get_capital_city' executing with country: {country} ---")
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country_capitals = {
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"united states": "Washington, D.C.",
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"canada": "Ottawa",
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"france": "Paris",
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"germany": "Berlin",
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}
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return {"result": country_capitals.get(country.lower(), f"Capital not found for {country}")}
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# --- Wrap the function into a Tool ---
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capital_tool = FunctionTool(func=get_capital_city)
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# --- Define the Callback Function ---
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def simple_after_tool_modifier(
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tool: BaseTool, args: Dict[str, Any], tool_context: ToolContext, tool_response: Dict
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) -> Optional[Dict]:
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"""Inspects/modifies the tool result after execution."""
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agent_name = tool_context.agent_name
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tool_name = tool.name
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print(f"[Callback] After tool call for tool '{tool_name}' in agent '{agent_name}'")
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print(f"[Callback] Args used: {args}")
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print(f"[Callback] Original tool_response: {tool_response}")
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# Default structure for function tool results is {"result": <return_value>}
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original_result_value = tool_response.get("result", "")
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# original_result_value = tool_response
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# --- Modification Example ---
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# If the tool was 'get_capital_city' and result is 'Washington, D.C.'
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if tool_name == 'get_capital_city' and original_result_value == "Washington, D.C.":
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print("[Callback] Detected 'Washington, D.C.'. Modifying tool response.")
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# IMPORTANT: Create a new dictionary or modify a copy
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modified_response = deepcopy(tool_response)
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modified_response["result"] = f"{original_result_value} (Note: This is the capital of the USA)."
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modified_response["note_added_by_callback"] = True # Add extra info if needed
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print(f"[Callback] Modified tool_response: {modified_response}")
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return modified_response # Return the modified dictionary
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print("[Callback] Passing original tool response through.")
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# Return None to use the original tool_response
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return None
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# Create LlmAgent and Assign Callback
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my_llm_agent = LlmAgent(
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name="AfterToolCallbackAgent",
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model=GEMINI_2_FLASH,
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instruction="You are an agent that finds capital cities using the get_capital_city tool. Report the result clearly.",
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description="An LLM agent demonstrating after_tool_callback",
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tools=[capital_tool], # Add the tool
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after_tool_callback=simple_after_tool_modifier # Assign the callback
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)
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APP_NAME = "guardrail_app"
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USER_ID = "user_1"
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SESSION_ID = "session_001"
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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=my_llm_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("united states") |