Fix PYTHONPATH issue and add runtime deps

app.py

@@ -1,46 +1,61 @@
-import subprocess, uuid, os
+import subprocess
+import uuid
+import os
 from pathlib import Path
 import gradio as gr
 
-# --- CONFIG ---------------------------------------------------------------
-CKPT_PATH = "checkpoints/t2m_50step.pt"   # you already uploaded this
+# ---------------------------------------------------------------------
+# CONFIG
+# ---------------------------------------------------------------------
+CKPT_PATH = "checkpoints/t2m_50step.pt"   # make sure this file exists
 DEVICE    = "cpu"                         # free HF Spaces have no GPU
-# --------------------------------------------------------------------------
+# ---------------------------------------------------------------------
 
 
 def generate_motion(prompt: str) -> str:
     """
-    Calls the repo’s built-in inference script and returns the path to
-    the generated BVH file so Gradio can hand it to the user.
+    Runs the MDM sampling script in a subprocess and returns the BVH
+    file path so Gradio can hand it to the user.
     """
     out_file = Path("/tmp") / f"{uuid.uuid4().hex}.bvh"
 
     cmd = [
         "python",
         "-m",
-        "motion_diffusion_model.sample.generate",   # script in the repo
-        "--model_path", CKPT_PATH,
-        "--prompt", prompt,
-        "--output", str(out_file),
-        "--device", DEVICE,
-        "--num_steps", "50"                         # matches the checkpoint
+        "motion_diffusion_model.sample.generate",
+        "--model_path", str(CKPT_PATH),
+        "--prompt",     prompt,
+        "--output",     str(out_file),
+        "--device",     DEVICE,
+        "--num_steps",  "50",            # matches the checkpoint
     ]
 
-    # Run the subprocess and surface errors cleanly in the UI
-    completed = subprocess.run(cmd, capture_output=True, text=True)
+    # --- make sure the local repo root is on PYTHONPATH so
+    #     'utils.*' imports inside the script can be resolved
+    env = os.environ.copy()
+    root = Path(__file__).parent
+    env["PYTHONPATH"] = f"{env.get('PYTHONPATH', '')}:{root}"
+
+    completed = subprocess.run(cmd, env=env, capture_output=True, text=True)
     if completed.returncode != 0:
         raise RuntimeError(f"Inference failed:\n{completed.stderr}")
 
     return str(out_file)
 
 
-# ----------------- GRADIO UI ------------------------------------------------
+# -----------------------  Gradio UI  ----------------------------------
 iface = gr.Interface(
     fn=generate_motion,
-    inputs=gr.Textbox(lines=2, placeholder="e.g. a person walks and waves"),
+    inputs=gr.Textbox(
+        lines=2,
+        placeholder="e.g. a person walks forward and waves"
+    ),
     outputs=gr.File(label="Download BVH"),
-    title="Text-to-Motion (MDM – 50-step)",
-    description="Enter a natural-language description to generate a 3-D human-motion BVH file.",
+    title="Motion Diffusion Model – Text-to-Motion (50-step CPU demo)",
+    description=(
+        "Enter a natural-language prompt and receive a 3-D skeletal "
+        "animation in BVH format."
+    ),
 )
 
 if __name__ == "__main__":

requirements.txt

@@ -2,6 +2,6 @@ torch>=2.0
 gradio
 numpy
 tqdm
-transformers
 scipy
-git+https://github.com/openai/CLIP.git   # CLIP is needed for the text encoder
+transformers
+git+https://github.com/openai/CLIP.git