app.py

import subprocess, uuid, os
from pathlib import Path
import gradio as gr

# ── paths ─────────────────────────────────────────────────────
CKPT   = "checkpoints/mld_humanml.pt"       # your 90 MB weight
DEVICE = "cpu"                              # free HF Spaces
STEPS  = "50"                               # diffusion steps
CFG    = "configs/config_mld_humanml3d.yaml"  # default config file
# ──────────────────────────────────────────────────────────────

def generate_motion(prompt: str) -> str:
    out_bvh = Path("/tmp") / f"{uuid.uuid4().hex}.bvh"

    cmd = [
        "python",
        "-m", "motion_latent_diffusion/demo.py",   # ← new: run demo.py
        "--cfg",        CFG,
        "--checkpoint", CKPT,
        "--prompt",     prompt,
        "--device",     DEVICE,
        "--steps",      STEPS,
        "--output",     str(out_bvh)
    ]

    # make repo importable
    env = os.environ.copy()
    root = Path(__file__).parent
    env["PYTHONPATH"] = f"{env.get('PYTHONPATH','')}:{root}"

    subprocess.run(cmd, env=env, check=True)
    return str(out_bvh)

# ── Gradio UI ─────────────────────────────────────────────────
iface = gr.Interface(
    fn=generate_motion,
    inputs=gr.Textbox(lines=2, placeholder="e.g. a person walks and waves"),
    outputs=gr.File(label="Download BVH"),
    title="Motion-Latent-Diffusion – Text → BVH (CPU demo)",
    description="Enter a prompt to generate a 3-second motion clip."
)

if __name__ == "__main__":
    iface.launch()