fix: upgrade to Gradio 5.25.0 to resolve HfFolder import error with transformers 5.x

README.md

@@ -4,7 +4,7 @@ emoji: 🐱
 colorFrom: purple
 colorTo: pink
 sdk: gradio
-sdk_version: "4.44.0"
+sdk_version: "5.25.0"
 app_file: spaces_app.py
 pinned: false
 license: apache-2.0

requirements.txt

@@ -7,6 +7,6 @@ soundfile>=0.12.0
 numpy>=1.24.0
 einops>=0.8.0
 faster-whisper>=1.0.0
-gradio>=4.0.0
-huggingface-hub>=0.24.0,<0.25.0
+gradio>=5.0.0
+huggingface-hub>=1.3.0
 tqdm>=4.65.0

spaces_app.py

@@ -1,57 +1,56 @@
-"""
-HuggingFace Spaces entry point for LongCat-AudioDiT Enhanced.
-
-Handles:
-  - /tmp storage for outputs, models, voices (Spaces has no persistent /app writes)
-  - HF_HOME → /tmp so model cache lands in writable space
-  - GPU detection and graceful CPU fallback
-  - Gradio theme passed to launch() (Gradio 6 compat)
-"""
-
-import os
-import sys
-from pathlib import Path
-
-# ── Redirect HF cache + all writable dirs to /tmp ────────────────────────────
-os.environ["HF_HOME"]              = "/tmp/hf_home"
-os.environ["TRANSFORMERS_CACHE"]   = "/tmp/hf_home/transformers"
-os.environ["HF_DATASETS_CACHE"]    = "/tmp/hf_home/datasets"
-
-for d in ["/tmp/hf_home", "/tmp/audiodit_outputs", "/tmp/audiodit_voices"]:
-    Path(d).mkdir(parents=True, exist_ok=True)
-
-# ── Patch app constants before import ────────────────────────────────────────
-import app as _app
-import voice_library as _vl
-import whisper_helper as _wh
-
-_app.OUTPUT_DIR = Path("/tmp/audiodit_outputs")
-
-# Patch voice library to store in /tmp
-_vl.VOICES_DIR   = Path("/tmp/audiodit_voices")
-_vl.LIBRARY_FILE = Path("/tmp/audiodit_voices/library.json")
-_vl.VOICES_DIR.mkdir(parents=True, exist_ok=True)
-_vl._library = None  # reset singleton so it picks up patched paths
-
-# Patch Whisper download root
-_orig_wh_init = _wh.WhisperHelper.__init__
-def _patched_wh_init(self, model_size="turbo", device="auto", compute_type="auto", download_root=None):
-    _orig_wh_init(self, model_size=model_size, device=device, compute_type=compute_type,
-                  download_root=download_root or "/tmp/hf_home/whisper")
-_wh.WhisperHelper.__init__ = _patched_wh_init
-
-# ── Launch ───────────────────────────────────────────────────────────────────
-import torch
-import gradio as gr
-
-device = "cuda" if torch.cuda.is_available() else "cpu"
-print(f"[Spaces] device={device}  CUDA={torch.cuda.is_available()}")
-
-demo = _app.build_ui(default_device=device)
-demo.launch(
-    server_name="0.0.0.0",
-    server_port=int(os.environ.get("PORT", 7860)),
-    share=False,
-    show_error=True,
-    theme=gr.themes.Soft(),
-)
+"""
+HuggingFace Spaces entry point for LongCat-AudioDiT Enhanced.
+
+Handles:
+  - /tmp storage for outputs, models, voices (Spaces has no persistent /app writes)
+  - HF_HOME → /tmp so model cache lands in writable space
+  - GPU detection and graceful CPU fallback
+  - Gradio theme passed to launch() (Gradio 6 compat)
+"""
+
+import os
+import sys
+from pathlib import Path
+
+# ── Redirect HF cache + all writable dirs to /tmp ────────────────────────────
+os.environ["HF_HOME"]              = "/tmp/hf_home"
+os.environ["TRANSFORMERS_CACHE"]   = "/tmp/hf_home/transformers"
+os.environ["HF_DATASETS_CACHE"]    = "/tmp/hf_home/datasets"
+
+for d in ["/tmp/hf_home", "/tmp/audiodit_outputs", "/tmp/audiodit_voices"]:
+    Path(d).mkdir(parents=True, exist_ok=True)
+
+# ── Patch app constants before import ────────────────────────────────────────
+import app as _app
+import voice_library as _vl
+import whisper_helper as _wh
+
+_app.OUTPUT_DIR = Path("/tmp/audiodit_outputs")
+
+# Patch voice library to store in /tmp
+_vl.VOICES_DIR   = Path("/tmp/audiodit_voices")
+_vl.LIBRARY_FILE = Path("/tmp/audiodit_voices/library.json")
+_vl.VOICES_DIR.mkdir(parents=True, exist_ok=True)
+_vl._library = None  # reset singleton so it picks up patched paths
+
+# Patch Whisper download root
+_orig_wh_init = _wh.WhisperHelper.__init__
+def _patched_wh_init(self, model_size="turbo", device="auto", compute_type="auto", download_root=None):
+    _orig_wh_init(self, model_size=model_size, device=device, compute_type=compute_type,
+                  download_root=download_root or "/tmp/hf_home/whisper")
+_wh.WhisperHelper.__init__ = _patched_wh_init
+
+# ── Launch ───────────────────────────────────────────────────────────────────
+import torch
+import gradio as gr
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+print(f"[Spaces] device={device}  CUDA={torch.cuda.is_available()}")
+
+demo = _app.build_ui(default_device=device)
+demo.launch(
+    server_name="0.0.0.0",
+    server_port=int(os.environ.get("PORT", 7860)),
+    share=False,
+    show_error=True,
+)