Use Gradio 5.x (get_token/whoami); drop huggingface_hub pin and debug logs

README.md

@@ -1,7 +1,7 @@
 ---
 title: Cinematic Video Generation
 sdk: gradio
-sdk_version: "4.44.0"
+sdk_version: "5.41.0"
 app_file: app.py
 ---
 

app.py

@@ -2,26 +2,9 @@
 Cinematic video generation Space using CogVideoX-5B with optional ExVideo LoRA.
 Uses Hugging Face ZeroGPU: select ZeroGPU hardware in Space settings.
 """
-# #region agent log
-import json
-import time
-_logpath = "/Users/jordanlegg/Code/math/.cursor/debug-f92435.log"
-try:
-    with open(_logpath, "a") as _f:
-        _f.write(json.dumps({"sessionId": "f92435", "runId": "post-fix", "hypothesisId": "H4", "location": "app.py:start", "message": "pre_import", "data": {"huggingface_hub_version": getattr(__import__("huggingface_hub"), "__version__", "?"), "has_HfFolder": hasattr(__import__("huggingface_hub"), "HfFolder")}, "timestamp": int(time.time() * 1000)}) + "\n")
-except Exception:
-    pass
-# #endregion
 import tempfile
 import torch
 import gradio as gr
-# #region agent log
-try:
-    with open(_logpath, "a") as _f:
-        _f.write(json.dumps({"sessionId": "f92435", "runId": "post-fix", "hypothesisId": "H5", "location": "app.py:after_gr", "message": "gradio_imported", "data": {"gradio_version": getattr(gr, "__version__", "?")}, "timestamp": int(time.time() * 1000)}) + "\n")
-except Exception:
-    pass
-# #endregion
 
 # ZeroGPU: import and use @spaces.GPU so the function runs on dynamically allocated GPU
 try:

requirements.txt

@@ -1,7 +1,6 @@
-huggingface_hub==0.22.2
 torch>=2.1.0
 diffusers>=0.32.0
 transformers
 accelerate
 safetensors
-gradio>=4.0
+gradio>=5.0.0