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Polong Lin
2ccd53a3d9
* fix: update gemini 2.0 flash to latest model id for Live API * fix: use -flash for most pages instead of the live api model * fix: wording andformatting * fix: resolve merge conflict
79 lines
2.9 KiB
Python
79 lines
2.9 KiB
Python
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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GEMINI_2_FLASH="gemini-2.0-flash"
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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 country_capitals.get(country.lower(), f"Capital not found for {country}")
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capital_tool = FunctionTool(func=get_capital_city)
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def simple_before_tool_modifier(
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tool: BaseTool, args: Dict[str, Any], tool_context: ToolContext
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) -> Optional[Dict]:
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"""Inspects/modifies tool args or skips the tool call."""
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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] Before tool call for tool '{tool_name}' in agent '{agent_name}'")
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print(f"[Callback] Original args: {args}")
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if tool_name == 'get_capital_city' and args.get('country', '').lower() == 'canada':
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print("[Callback] Detected 'Canada'. Modifying args to 'France'.")
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args['country'] = 'France'
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print(f"[Callback] Modified args: {args}")
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return None
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# If the tool is 'get_capital_city' and country is 'BLOCK'
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if tool_name == 'get_capital_city' and args.get('country', '').upper() == 'BLOCK':
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print("[Callback] Detected 'BLOCK'. Skipping tool execution.")
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return {"result": "Tool execution was blocked by before_tool_callback."}
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print("[Callback] Proceeding with original or previously modified args.")
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return None
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my_llm_agent = LlmAgent(
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name="ToolCallbackAgent",
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model=GEMINI_2_FLASH,
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instruction="You are an agent that can find capital cities. Use the get_capital_city tool.",
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description="An LLM agent demonstrating before_tool_callback",
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tools=[capital_tool],
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before_tool_callback=simple_before_tool_modifier
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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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session_service = InMemorySessionService()
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session = 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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# Agent Interaction
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def call_agent(query):
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content = types.Content(role='user', parts=[types.Part(text=query)])
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events = runner.run(user_id=USER_ID, session_id=SESSION_ID, new_message=content)
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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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call_agent("callback example") |