src/streamlit_app.py

src/streamlit_app.py

@@ -1,9 +1,19 @@
-# app_paint_by_example.py
+# streamlit_app.py
+import os
 import streamlit as st
 from PIL import Image
 import torch
 from diffusers import PaintByExamplePipeline
 
+# 👉 Forcer les dossiers de cache dans /app/.cache (où tu as les droits)
+os.environ["HF_HOME"] = "/app/.cache/huggingface"
+os.environ["TRANSFORMERS_CACHE"] = "/app/.cache/transformers"
+os.environ["DIFFUSERS_CACHE"] = "/app/.cache/diffusers"
+
+os.makedirs("/app/.cache/huggingface", exist_ok=True)
+os.makedirs("/app/.cache/transformers", exist_ok=True)
+os.makedirs("/app/.cache/diffusers", exist_ok=True)
+
 st.set_page_config(page_title="Paint-By-Example", layout="centered")
 
 @st.cache_resource(show_spinner=False)
@@ -11,7 +21,8 @@ def load_pipe():
     dtype = torch.float16 if torch.cuda.is_available() else torch.float32
     pipe = PaintByExamplePipeline.from_pretrained(
         "Fantasy-Studio/Paint-by-Example",
-        torch_dtype=dtype
+        torch_dtype=dtype,
+        cache_dir=os.environ["DIFFUSERS_CACHE"]  # 👉 important : on précise le cache
     )
     pipe = pipe.to("cuda" if torch.cuda.is_available() else "cpu")
     return pipe
@@ -33,5 +44,10 @@ if st.button("Appliquer"):
         ref = Image.open(ref_file).convert("RGB")
 
         with st.spinner("Génération…"):
-            out = pipe(image=image, mask_image=mask, example_image=ref, num_inference_steps=steps).images[0]
+            out = pipe(
+                image=image,
+                mask_image=mask,
+                example_image=ref,
+                num_inference_steps=steps
+            ).images[0]
         st.image(out, caption="Résultat", use_column_width=True)