# 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")