Fix SSR mode error and improve token handling for HF Spaces deployment

app.py

@@ -2,7 +2,7 @@ import os
 from huggingface_hub import login
 
 # run once at startup
-if "HF_TOKEN" in os.environ:
+if "HF_TOKEN" in os.environ and os.environ["HF_TOKEN"]:
     login(token=os.environ["HF_TOKEN"])
 
 # app.py
@@ -10,9 +10,17 @@ import os; os.environ.setdefault('HF_HOME', '/data/hf-cache')
 os.environ.setdefault('HF_HUB_ENABLE_HF_TRANSFER', '1')
 
 from huggingface_hub import login
-login(os.getenv("HF_TOKEN", ""))
+hf_token = os.getenv("HF_TOKEN", "")
+if hf_token:
+    login(token=hf_token)
+
+try:
+    from spaces import GPU
+except ImportError:
+    # For local testing, create a no-op decorator
+    def GPU(f):
+        return f
 
-from spaces import GPU
 import torch
 from exceptiongroup import catch
 from transformers import AutoTokenizer, AutoModelForCausalLM
@@ -321,4 +329,4 @@ with gr.Blocks(theme="soft") as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(ssr_mode=False)

requirements.txt

@@ -2,4 +2,6 @@ torch
 transformers
 pandas
 tqdm
-scikit-learn
+scikit-learn
+gradio>=5.0.0
+huggingface_hub