import gradio as gr
from config import howManyModelsToUse,num_models,max_images,inference_timeout,MAX_SEED,thePrompt,preSetPrompt,negPreSetPrompt
from all_models import models
import asyncio
from externalmod import gr_Interface_load, save_image, randomize_seed
import os
from threading import RLock
lock = RLock()
HF_TOKEN = os.getenv("ohgoddamn")
default_models = models[:num_models]
def get_current_time():
    from datetime import datetime
    now = datetime.now()
    current_time = now.strftime("%y-%m-%d %H:%M:%S")
    return current_time








def load_fn(models, HF_TOKEN):
    global models_load
    models_load = {}
    for model in models:
        if model not in models_load:
            try:
                m = gr_Interface_load(f'models/{model}', hf_token=HF_TOKEN)
                models_load[model] = m.fn  # Store the callable
            except Exception as error:
                print(error)
                models_load[model] = lambda **kwargs: None

async def infer(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1, timeout=120, hf_token=None):
    print(f"{prompt}\n{model_str}\n{timeout}\n")
    kwargs = {}
    if height > 0: kwargs["height"] = height
    if width > 0: kwargs["width"] = width
    if steps > 0: kwargs["num_inference_steps"] = steps
    if cfg > 0: kwargs["guidance_scale"] = cfg
    kwargs["negative_prompt"] = nprompt

    theSeed = randomize_seed() if seed == -1 else seed
    kwargs["seed"] = theSeed
    if hf_token:
        kwargs["token"] = hf_token

    try:
        task = asyncio.create_task(asyncio.to_thread(models_load[model_str], prompt=prompt, **kwargs))
        result = await asyncio.wait_for(task, timeout=timeout)
    except asyncio.TimeoutError as e:
        print(f"Timeout: {model_str}")
        if not task.done(): task.cancel()
        raise Exception(f"Timeout: {model_str}") from e
    except Exception as e:
        print(f"Exception: {model_str} -> {e}")
        if not task.done(): task.cancel()
        raise Exception(f"Inference failed: {model_str}") from e

    if result is not None and not isinstance(result, tuple):
        with lock:
            png_path =  model_str.replace("/", "_") + " - " + get_current_time() + "_" + str(theSeed) + ".png"
            image = save_image(result, png_path, model_str, prompt, nprompt, height, width, steps, cfg, theSeed)
        return image
    return None

def gen_fn(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1, inference_timeout2=120):
    try:
        loop = asyncio.new_event_loop()
        result = loop.run_until_complete(infer(model_str, prompt, nprompt,
                                               height, width, steps, cfg, seed, inference_timeout2, HF_TOKEN))
    except Exception as e:
        print(f"gen_fn: Task aborted: {model_str} -> {e}")
        raise gr.Error(f"Task aborted: {model_str}, Error: {e}")
    finally:
        loop.close()
    return result





    
'''
def load_fn(models,HF_TOKEN):
    global models_load
    models_load = {}
    for model in models:
        if model not in models_load.keys():
            try:
                m = gr_Interface_load(f'models/{model}', hf_token=HF_TOKEN)
            except Exception as error:
                print(error)
                m = gr.Interface(lambda: None, ['text'], ['image'])
            models_load.update({model: m})

async def infer(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1, timeout=inference_timeout):
    print(f"{prompt}\n")
    print(f"{model_str}\n")
    print(f"{timeout}\n")
    kwargs = {}
    if height > 0: kwargs["height"] = height
    if width > 0: kwargs["width"] = width
    if steps > 0: kwargs["num_inference_steps"] = steps
    if cfg > 0: cfg = kwargs["guidance_scale"] = cfg
    if seed == -1:
        theSeed = randomize_seed()
    else: 
        theSeed = seed
    kwargs["seed"] = theSeed
    task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn, prompt=prompt, negative_prompt=nprompt, **kwargs, token=HF_TOKEN))
    print(f"await")
    await asyncio.sleep(20)
    try:
        result = await asyncio.wait_for(task, timeout=timeout)
    except asyncio.TimeoutError as e:
        print(e)
        print(f"infer: Task timed out: {model_str}")
        if not task.done(): task.cancel()
        result = None
        raise Exception(f"Task timed out: {model_str}") from e
    except Exception as e:
        print(e)
        print(f"infer: exception: {model_str}")
        if not task.done(): task.cancel()
        result = None
        raise Exception() from e
    if task.done() and result is not None and not isinstance(result, tuple):
        print(f"{result}")
        with lock:
            png_path =  model_str.replace("/", "_") + " - " + get_current_time() + "_" + str(theSeed) + ".png"
            image = save_image(result, png_path, model_str, prompt, nprompt, height, width, steps, cfg, theSeed)
        return image
    return None

def gen_fn(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1, inference_timeout2=120):
    try:
        loop = asyncio.new_event_loop()
        result = loop.run_until_complete(infer(model_str, prompt, nprompt,
                                         height, width, steps, cfg, seed, inference_timeout2))
    except (Exception, asyncio.CancelledError) as e:
        print(e)
        print(f"gen_fn: Task aborted: {model_str}")
        result = None
        raise gr.Error(f"Task aborted: {model_str}, Error: {e}")
    finally:
        loop.close()
    return result
'''