import os
import warnings
from typing import *
from dotenv import load_dotenv
from transformers import logging

from langgraph.checkpoint.memory import MemorySaver
from langchain_openai import ChatOpenAI

from interface import create_demo
from medrax.agent import *
from medrax.tools import *
from medrax.utils import *

warnings.filterwarnings("ignore")
logging.set_verbosity_error()
_ = load_dotenv()  # Loads your .env file (OPENAI_API_KEY and OPENAI_BASE_URL)

def initialize_agent(
    prompt_file,
    tools_to_use=None,
    model_dir="./model-weights",
    temp_dir="temp",
    device="cuda",
    model="google/gemini-1.5-flash-latest",  # ✅ updated model name for OpenRouter
    temperature=0.7,
    top_p=0.95, 
    openai_kwargs=None
):
    prompts = load_prompts_from_file(prompt_file)
    prompt = prompts["MEDICAL_ASSISTANT"]

    all_tools = {
        "ChestXRayClassifierTool": lambda: ChestXRayClassifierTool(device=device),
        "ChestXRaySegmentationTool": lambda: ChestXRaySegmentationTool(device=device),
        "LlavaMedTool": lambda: LlavaMedTool(cache_dir=model_dir, device=device, load_in_8bit=True),
        "XRayVQATool": lambda: XRayVQATool(cache_dir=model_dir, device=device),
        "ChestXRayReportGeneratorTool": lambda: ChestXRayReportGeneratorTool(
            cache_dir=model_dir, device=device
        ),
        "XRayPhraseGroundingTool": lambda: XRayPhraseGroundingTool(
            cache_dir=model_dir, temp_dir=temp_dir, load_in_8bit=True, device=device
        ),
        "ChestXRayGeneratorTool": lambda: ChestXRayGeneratorTool(
            model_path=f"{model_dir}/roentgen", temp_dir=temp_dir, device=device
        ),
        "ImageVisualizerTool": lambda: ImageVisualizerTool(),
        "DicomProcessorTool": lambda: DicomProcessorTool(temp_dir=temp_dir),
    }

    tools_dict = {}
    tools_to_use = tools_to_use or all_tools.keys()
    for tool_name in tools_to_use:
        if tool_name in all_tools:
            tools_dict[tool_name] = all_tools[tool_name]()

    checkpointer = MemorySaver()

    model = ChatOpenAI(model=model, temperature=temperature, top_p=top_p, **openai_kwargs)
    agent = Agent(
        model,
        tools=list(tools_dict.values()),
        log_tools=True,
        log_dir="logs",
        system_prompt=prompt,
        checkpointer=checkpointer,
    )

    print("Agent initialized")
    return agent, tools_dict


if __name__ == "__main__":
    print("Starting server...")

    selected_tools = [
        "ImageVisualizerTool",
        "DicomProcessorTool",
        "ChestXRayClassifierTool",
        "ChestXRaySegmentationTool",
        "ChestXRayReportGeneratorTool",
        "XRayVQATool",
        # "LlavaMedTool",
        # "XRayPhraseGroundingTool",
        # "ChestXRayGeneratorTool",
    ]

    # ✅ Collect environment variables and pass to model
    openai_kwargs = {}
    if api_key := os.getenv("OPENAI_API_KEY"):
        openai_kwargs["openai_api_key"] = api_key
    if base_url := os.getenv("OPENAI_BASE_URL"):
        openai_kwargs["openai_api_base"] = base_url

    agent, tools_dict = initialize_agent(
        "medrax/docs/system_prompts.txt",
        tools_to_use=selected_tools,
        model_dir="./model-weights",
        temp_dir="temp",
        device="cuda",
        model="google/gemini-1.5-flash-latest",  # ✅ Updated OpenRouter model
        temperature=0.7,
        top_p=0.95,
        openai_kwargs=openai_kwargs
    )

    demo = create_demo(agent, tools_dict)
    demo.launch(server_name="0.0.0.0", server_port=8585, share=True)