mirror of
https://github.com/google/adk-docs.git
synced 2026-09-14 16:16:59 +08:00
Adrian Altermatt
116 lines
5.0 KiB
Python
116 lines
5.0 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.agents.callback_context import CallbackContext
|
|
from google.adk.runners import Runner
|
|
from typing import Optional
|
|
from google.genai import types
|
|
from google.adk.sessions import InMemorySessionService
|
|
from google.adk.models import LlmResponse
|
|
from copy import deepcopy
|
|
|
|
GEMINI_2_FLASH="gemini-2.0-flash"
|
|
|
|
# --- Define the Callback Function ---
|
|
def simple_after_model_modifier(
|
|
callback_context: CallbackContext, llm_response: LlmResponse
|
|
) -> Optional[LlmResponse]:
|
|
"""Inspects/modifies the LLM response after it's received."""
|
|
agent_name = callback_context.agent_name
|
|
print(f"[Callback] After model call for agent: {agent_name}")
|
|
|
|
# --- Inspection ---
|
|
original_text = ""
|
|
if llm_response.content and llm_response.content.parts:
|
|
# Assuming simple text response for this example
|
|
if llm_response.content.parts[0].text:
|
|
original_text = llm_response.content.parts[0].text
|
|
print(f"[Callback] Inspected original response text: '{original_text[:100]}...'") # Log snippet
|
|
elif llm_response.content.parts[0].function_call:
|
|
print(f"[Callback] Inspected response: Contains function call '{llm_response.content.parts[0].function_call.name}'. No text modification.")
|
|
return None # Don't modify tool calls in this example
|
|
else:
|
|
print("[Callback] Inspected response: No text content found.")
|
|
return None
|
|
elif llm_response.error_message:
|
|
print(f"[Callback] Inspected response: Contains error '{llm_response.error_message}'. No modification.")
|
|
return None
|
|
else:
|
|
print("[Callback] Inspected response: Empty LlmResponse.")
|
|
return None # Nothing to modify
|
|
|
|
# --- Modification Example ---
|
|
# Replace "joke" with "funny story" (case-insensitive)
|
|
search_term = "joke"
|
|
replace_term = "funny story"
|
|
if search_term in original_text.lower():
|
|
print(f"[Callback] Found '{search_term}'. Modifying response.")
|
|
modified_text = original_text.replace(search_term, replace_term)
|
|
modified_text = modified_text.replace(search_term.capitalize(), replace_term.capitalize()) # Handle capitalization
|
|
|
|
# Create a NEW LlmResponse with the modified content
|
|
# Deep copy parts to avoid modifying original if other callbacks exist
|
|
modified_parts = [deepcopy(part) for part in llm_response.content.parts]
|
|
modified_parts[0].text = modified_text # Update the text in the copied part
|
|
|
|
new_response = LlmResponse(
|
|
content=types.Content(role="model", parts=modified_parts),
|
|
# Copy other relevant fields if necessary, e.g., grounding_metadata
|
|
grounding_metadata=llm_response.grounding_metadata
|
|
)
|
|
print(f"[Callback] Returning modified response.")
|
|
return new_response # Return the modified response
|
|
else:
|
|
print(f"[Callback] '{search_term}' not found. Passing original response through.")
|
|
# Return None to use the original llm_response
|
|
return None
|
|
|
|
|
|
# Create LlmAgent and Assign Callback
|
|
my_llm_agent = LlmAgent(
|
|
name="AfterModelCallbackAgent",
|
|
model=GEMINI_2_FLASH,
|
|
instruction="You are a helpful assistant.",
|
|
description="An LLM agent demonstrating after_model_callback",
|
|
after_model_callback=simple_after_model_modifier # Assign the function here
|
|
)
|
|
|
|
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):
|
|
session, runner = await setup_session_and_runner()
|
|
|
|
content = types.Content(role='user', parts=[types.Part(text=query)])
|
|
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("""write multiple time the word "joke" """)
|