from google.adk.agents import LlmAgent
from google.adk.sessions import InMemorySessionService
from google.adk.runners import Runner
from google.genai.types import Content, Part
from google.adk.models.lite_llm import LiteLlm
from google.adk.models import LlmRequest
from google.genai import types
from pydantic import Field


import litellm
litellm._turn_on_debug()

import warnings
warnings.filterwarnings("ignore", category=UserWarning, message=".*InMemoryCredentialService.*")

import os
from dotenv import load_dotenv

# Load environment variables from the agent directory's .env file
load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")

# Define agent with output_key
root_agent = LlmAgent(
    name="name_of_agent",
    model=LiteLlm(model="azure/gpt-4o-mini"), 
    instruction="You are a customer agent to help the users with their concerns."
)


# --- Setup Runner and Session ---
app_name, user_id, session_id = "state_app", "user1", "session1"

session_service = InMemorySessionService()

runner = Runner(
    agent=root_agent,
    app_name=app_name,
    session_service=session_service
)

print(f"Runner created for agent '{runner.agent.name}'.")


session = await session_service.create_session(
    app_name=app_name,
    user_id=user_id,
    session_id=session_id
)

# --- Run the Agent ---

async def call_agent_async(query: str, runner, user_id, session_id):

    user_message = Content(parts=[Part(text=query)])

    async for event in runner.run_async(
        user_id=user_id,
        session_id=session_id,
        new_message=user_message
    ):
        print("event")
        print(f"  [Event]\n  Author: {event.author}\n  Type: {type(event).__name__}",
        f"\n  Final: {event.is_final_response()}\n  Content: {event.content}")

    return event

event = await call_agent_async("What is the capital of India.",runner=runner,user_id=user_id,session_id=session_id)

00:29:24 - LiteLLM:DEBUG: utils.py:348 - 

00:29:24 - LiteLLM:DEBUG: utils.py:348 - Request to litellm:
00:29:24 - LiteLLM:DEBUG: utils.py:348 - litellm.acompletion(model='azure/gpt-4o-mini', messages=[{'role': 'developer', 'content': 'You are a customer agent to help the users with their concerns.\n\nYou are an agent. Your internal name is "name_of_agent".'}, {'role': 'user', 'content': 'Handle the requests as specified in the System Instruction.'}], tools=None, response_format=None)

00:28:46 - LiteLLM:DEBUG: utils.py:349 - 

00:28:46 - LiteLLM:DEBUG: utils.py:349 - Request to litellm:
00:28:46 - LiteLLM:DEBUG: utils.py:349 - litellm.acompletion(model='azure/gpt-4o-mini', messages=[{'role': 'developer', 'content': 'You are a customer agent to help the users with their concerns.\n\nYou are an agent. Your internal name is "name_of_agent".'}, {'role': 'user', 'content': 'What is the capital of India.'}], tools=None, response_format=None)

import pytest
from google.genai import types
from google.adk.models.llm_request import LlmRequest
from google.adk.models.lite_llm import _get_completion_inputs


@pytest.mark.parametrize("content_kwargs", [
    # Case 1: Explicit role provided
    {"role": "user", "parts": [types.Part(text="This is an input text from user.")]},
    # Case 2: Role omitted, should still be treated as 'user'
    {"parts": [types.Part(text="This is an input text from user.")]}
])
def test_user_content_role_defaults_to_user(content_kwargs):
    """
    Verifies that user-provided messages are always passed to the LLM as 'user' role,
    regardless of whether the role is explicitly set in types.Content.
    
    The helper `_get_completion_inputs` should give normalize messages so that
    explicit 'user' and implicit (missing role) are equivalent.
    """
    llm_request = LlmRequest(
        contents=[types.Content(**content_kwargs)],
        config=types.GenerateContentConfig()
    )

    messages, _, _, _ = _get_completion_inputs(llm_request)

    assert all(
        msg.get("role") == "user" for msg in messages
    ), f"Expected role 'user' but got {messages}"
    assert any(
        "This is an input text from user." == (msg.get("content") or "") 
        for msg in messages
    ), f"Expected the user text to be preserved, but got {messages}"