import gradio as gr
from transformers import pipeline
import torch

# Maximize CPU usage
torch.set_num_threads(torch.get_num_threads() * 2)

model1 = gr.load("models/Jonny001/NSFW_master")
model2 = gr.load("models/Jonny001/Alita-v1")
model3 = gr.load("models/lexa862/NSFWmodel")
model4 = gr.load("models/Keltezaa/flux_pussy_NSFW")
model5 = gr.load("models/prashanth970/flux-lora-uncensored")

def generate_images(text, selected_model):
    if selected_model == "Model 1 (NSFW Master)":
        model = model1
    elif selected_model == "Model 2 (Alita)":
        model = model2
    elif selected_model == "Model 3 (Lexa NSFW)":
        model = model3
    elif selected_model == "Model 4 (Flux NSFW)":
        model = model4
    elif selected_model == "Model 5 (Lora Uncensored)":
        model = model5
    else:
        return "Invalid model selection."
    
    results = []
    for i in range(3):
        modified_text = f"{text} variation {i+1}"
        result = model(modified_text)
        results.append(result)
    
    return results

interface = gr.Interface(
    fn=generate_images,
    inputs=[
        gr.Textbox(label="Type here your imagination:", placeholder="Type your prompt..."),
        gr.Radio(
            ["Model 1 (NSFW Master)", "Model 2 (Alita)", "Model 3 (Lexa NSFW)", "Model 4 (Flux NSFW)", "Model 5 (Lora Uncensored)"],
            label="Select Model (Try All Models & Get Different Results)",
            value="Model 1 (NSFW Master)",
        ),
    ],
    outputs=[
        gr.Image(label="Generated Image 1"),
        gr.Image(label="Generated Image 2"),
        gr.Image(label="Generated Image 3"),
    ],
    theme="Yntec/HaleyCH_Theme_Orange",
    description="⚠ Sorry for the inconvenience. The models are currently running on the CPU, which might affect performance. We appreciate your understanding.",
    cache_examples=False,
)

interface.launch()

# import gradio as gr
# from transformers import pipeline
# import torch

# # Maximize CPU usage
# torch.set_num_threads(torch.get_num_threads() * 2)

# # Load models using Hugging Face pipelines
# model1 = pipeline("text-to-image", model="Jonny001/NSFW_master", device_map="auto")
# model2 = pipeline("text-to-image", model="Jonny001/Alita-v1", device_map="auto")
# model3 = pipeline("text-to-image", model="lexa862/NSFWmodel", device_map="auto")
# model4 = pipeline("text-to-image", model="Keltezaa/flux_pussy_NSFW", device_map="auto")
# model5 = pipeline("text-to-image", model="prashanth970/flux-lora-uncensored", device_map="auto")

# # Function to generate images
# def generate_images(text, selected_model):
#     models = {
#         "Model 1 (NSFW Master)": model1,
#         "Model 2 (Alita)": model2,
#         "Model 3 (Lexa NSFW)": model3,
#         "Model 4 (Flux NSFW)": model4,
#         "Model 5 (Lora Uncensored)": model5,
#     }
    
#     model = models.get(selected_model, model1)
#     results = []
    
#     for i in range(3):
#         modified_text = f"{text} variation {i+1}"
#         result = model(modified_text)
#         results.append(result)

#     return results

# # Gradio interface
# interface = gr.Interface(
#     fn=generate_images,
#     inputs=[
#         gr.Textbox(label="Type here your imagination:", placeholder="Type your prompt..."),
#         gr.Radio(
#             ["Model 1 (NSFW Master)", "Model 2 (Alita)", "Model 3 (Lexa NSFW)", "Model 4 (Flux NSFW)", "Model 5 (Lora Uncensored)"],
#             label="Select Model (Try All Models & Get Different Results)",
#             value="Model 1 (NSFW Master)",
#         ),
#     ],
#     outputs=[
#         gr.Image(label="Generated Image 1"),
#         gr.Image(label="Generated Image 2"),
#         gr.Image(label="Generated Image 3"),
#     ],
#     theme="Yntec/HaleyCH_Theme_Orange",
#     description="⚠ Models are running on CPU for optimized performance. Your patience is appreciated!",
#     cache_examples=False,
# )

# # Launch the interface
# interface.launch()