Files
Gururaj Deshpande ff454ac1c9 fix: change call_agent to call_agent_async (#450)
* 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

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Co-authored-by: Lavi Nigam <98014943+lavinigam-gcp@users.noreply.github.com>
Co-authored-by: Lavi Nigam <lavinigam@google.com>
2025-06-28 00:10:12 +05:30

111 lines
4.6 KiB
Python

# Copyright 2025 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from google.adk.agents import LlmAgent
from google.adk.runners import Runner
from typing import Optional
from google.genai import types
from google.adk.sessions import InMemorySessionService
from google.adk.tools import FunctionTool
from google.adk.tools.tool_context import ToolContext
from google.adk.tools.base_tool import BaseTool
from typing import Dict, Any
from copy import deepcopy
GEMINI_2_FLASH="gemini-2.0-flash"
# --- Define a Simple Tool Function (Same as before) ---
def get_capital_city(country: str) -> str:
"""Retrieves the capital city of a given country."""
print(f"--- Tool 'get_capital_city' executing with country: {country} ---")
country_capitals = {
"united states": "Washington, D.C.",
"canada": "Ottawa",
"france": "Paris",
"germany": "Berlin",
}
return {"result": country_capitals.get(country.lower(), f"Capital not found for {country}")}
# --- Wrap the function into a Tool ---
capital_tool = FunctionTool(func=get_capital_city)
# --- Define the Callback Function ---
def simple_after_tool_modifier(
tool: BaseTool, args: Dict[str, Any], tool_context: ToolContext, tool_response: Dict
) -> Optional[Dict]:
"""Inspects/modifies the tool result after execution."""
agent_name = tool_context.agent_name
tool_name = tool.name
print(f"[Callback] After tool call for tool '{tool_name}' in agent '{agent_name}'")
print(f"[Callback] Args used: {args}")
print(f"[Callback] Original tool_response: {tool_response}")
# Default structure for function tool results is {"result": <return_value>}
original_result_value = tool_response.get("result", "")
# original_result_value = tool_response
# --- Modification Example ---
# If the tool was 'get_capital_city' and result is 'Washington, D.C.'
if tool_name == 'get_capital_city' and original_result_value == "Washington, D.C.":
print("[Callback] Detected 'Washington, D.C.'. Modifying tool response.")
# IMPORTANT: Create a new dictionary or modify a copy
modified_response = deepcopy(tool_response)
modified_response["result"] = f"{original_result_value} (Note: This is the capital of the USA)."
modified_response["note_added_by_callback"] = True # Add extra info if needed
print(f"[Callback] Modified tool_response: {modified_response}")
return modified_response # Return the modified dictionary
print("[Callback] Passing original tool response through.")
# Return None to use the original tool_response
return None
# Create LlmAgent and Assign Callback
my_llm_agent = LlmAgent(
name="AfterToolCallbackAgent",
model=GEMINI_2_FLASH,
instruction="You are an agent that finds capital cities using the get_capital_city tool. Report the result clearly.",
description="An LLM agent demonstrating after_tool_callback",
tools=[capital_tool], # Add the tool
after_tool_callback=simple_after_tool_modifier # Assign the callback
)
APP_NAME = "guardrail_app"
USER_ID = "user_1"
SESSION_ID = "session_001"
# Session and Runner
async def setup_session_and_runner():
session_service = InMemorySessionService()
session = await session_service.create_session(app_name=APP_NAME, user_id=USER_ID, session_id=SESSION_ID)
runner = Runner(agent=my_llm_agent, app_name=APP_NAME, session_service=session_service)
return session, runner
# Agent Interaction
async def call_agent_async(query):
content = types.Content(role='user', parts=[types.Part(text=query)])
session, runner = await setup_session_and_runner()
events = runner.run_async(user_id=USER_ID, session_id=SESSION_ID, new_message=content)
async for event in events:
if event.is_final_response():
final_response = event.content.parts[0].text
print("Agent Response: ", final_response)
# Note: In Colab, you can directly use 'await' at the top level.
# If running this code as a standalone Python script, you'll need to use asyncio.run() or manage the event loop.
await call_agent_async("united states")