# 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" """)