import subprocess, sys

# 🧠 Safe dependency install with NumPy fix
subprocess.run(
    [sys.executable, "-m", "pip", "install", 
     "numpy<2", "moviepy==1.0.3", "imageio[ffmpeg]",
     "diffusers==0.30.0", "transformers", "accelerate",
     "torch==2.2.2", "gradio"], check=True
)

import gradio as gr
from diffusers import StableDiffusionPipeline, StableVideoDiffusionPipeline
import torch, moviepy.editor as mpy

device = "cpu"  # 🧩 Force CPU-only mode

# 🔹 Step 1: Lightweight Stable Diffusion v1.5
img_pipe = StableDiffusionPipeline.from_pretrained(
    "runwayml/stable-diffusion-v1-5",
    torch_dtype=torch.float32
).to(device)

# 🔹 Step 2: Image → Video
vid_pipe = StableVideoDiffusionPipeline.from_pretrained(
    "stabilityai/stable-video-diffusion-img2vid",
    torch_dtype=torch.float32
).to(device)

def generate_from_prompt(prompt, frames=12, motion_strength=0.6, fps=6):
    # Generate image from prompt
    image = img_pipe(prompt).images[0]

    # Animate it (limited for CPU)
    result = vid_pipe(
        image,
        num_frames=frames,
        motion_bucket_id=int(motion_strength * 127),
        noise_aug_strength=0.05
    )

    frames_list = result.frames[0]
    clip = mpy.ImageSequenceClip(frames_list, fps=fps)
    output_path = "/tmp/generated_video.mp4"
    clip.write_videofile(output_path, codec="libx264", audio=False, verbose=False, logger=None)
    return output_path

iface = gr.Interface(
    fn=generate_from_prompt,
    inputs=[
        gr.Textbox(label="🎨 Prompt (e.g. 'Indian influencer smiling in sunlight')"),
        gr.Slider(8, 20, value=12, step=1, label="Frames (lower = faster on CPU)"),
        gr.Slider(0.0, 1.0, value=0.6, step=0.05, label="Motion Strength"),
        gr.Slider(4, 10, value=6, step=1, label="FPS")
    ],
    outputs=gr.Video(label="🎬 Generated AI Video"),
    title="🪄 AI Prompt → Image → Video (CPU Mode)",
    description="Runs fully on CPU. Generates an image from text and animates it into a short AI video."
)

iface.launch()