import gradio as gr
import torch
from diffusers import StableDiffusionPipeline
from PIL import Image
import time
import traceback
from typing import Optional

# ---- Configuration ----
model_id: str = "runwayml/stable-diffusion-v1-5"
device: str = "cpu"  # force CPU usage for compatibility

# ---- Load Model ----
image_generator_pipe: Optional[StableDiffusionPipeline] = None

try:
    print(f"Loading Stable Diffusion pipeline ({model_id}) on CPU...")
    pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
    image_generator_pipe = pipe.to(device)
    print("Stable Diffusion pipeline loaded successfully.")
except Exception as e:
    print(f"Failed to load Stable Diffusion model: {e}")
    traceback.print_exc()

# ---- Core Image Generation Function ----
def generate_image_sd(prompt: str, negative_prompt: str, guidance_scale: float, num_inference_steps: int) -> Image.Image:
    if not image_generator_pipe:
        raise gr.Error("Stable Diffusion pipeline failed to load. Image generation unavailable.")

    if not prompt.strip():
        raise gr.Error("Prompt cannot be empty.")

    print(f"Generating image with prompt: {prompt[:100]}...")
    print(f"Negative prompt: {negative_prompt}")
    print(f"Guidance scale: {guidance_scale}, Steps: {num_inference_steps}")

    start_time = time.time()

    try:
        with torch.no_grad():
            output = image_generator_pipe(
                prompt=prompt,
                negative_prompt=negative_prompt,
                guidance_scale=guidance_scale,
                num_inference_steps=num_inference_steps
            )
            image = output.images[0] if output.images else None

        if not image:
            raise RuntimeError("No image was returned from the generation pipeline.")

        end_time = time.time()
        print(f"Image generated in {end_time - start_time:.2f} seconds.")
        return image

    except Exception as e:
        print(f"Error generating image: {e}")
        traceback.print_exc()
        raise gr.Error(f"Image generation failed: {e}")

# ---- Gradio UI ----
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("# Stable Diffusion Image Generator (CPU Mode)")

    with gr.Row():
        with gr.Column(scale=1):
            prompt = gr.Textbox(label="Prompt", placeholder="A beautiful futuristic city skyline at night")
            neg_prompt = gr.Textbox(label="Negative Prompt", placeholder="blurry, distorted, watermark")
            guidance = gr.Slider(1.0, 15.0, value=7.5, step=0.5, label="Guidance Scale")
            steps = gr.Slider(10, 50, value=25, step=1, label="Inference Steps")
            generate_btn = gr.Button("Generate Image")

        with gr.Column(scale=1):
            output_image = gr.Image(label="Generated Image", type="pil")

    generate_btn.click(
        fn=generate_image_sd,
        inputs=[prompt, neg_prompt, guidance, steps],
        outputs=output_image
    )

# ---- Launch ----
if __name__ == "__main__":
    if not image_generator_pipe:
        print("WARNING: Image generator pipeline is not available. UI will launch, but generation will fail.")
    demo.launch(server_name="0.0.0.0", server_port=7860)