Add training pipeline

app.py

@@ -4,6 +4,46 @@ Runs train_and_upgrade.py in the background, streams logs live,
 and exports the upgraded model to morpheuslord/rewrite on completion.
 """
 
+# ── Compatibility patch ───────────────────────────────────────────────────────
+# HF Spaces forces gradio 4.44.0 which imports HfFolder from huggingface_hub.
+# huggingface_hub >= 0.30 removed HfFolder. Patch it back before gradio loads.
+try:
+    from huggingface_hub import HfFolder  # noqa: F401 -- check if it exists
+except ImportError:
+    import os as _os
+    import huggingface_hub as _hfhub
+    from huggingface_hub import constants as _hfconst
+
+    class HfFolder:
+        path_token = _hfconst.HF_TOKEN_PATH
+
+        @classmethod
+        def get_token(cls):
+            env = _os.environ.get("HF_TOKEN") or _os.environ.get("HUGGING_FACE_HUB_TOKEN")
+            if env:
+                return env
+            try:
+                with open(cls.path_token) as f:
+                    return f.read().strip() or None
+            except Exception:
+                return None
+
+        @classmethod
+        def save_token(cls, token):
+            _os.makedirs(_os.path.dirname(cls.path_token), exist_ok=True)
+            with open(cls.path_token, "w") as f:
+                f.write(token)
+
+        @classmethod
+        def delete_token(cls):
+            try:
+                _os.remove(cls.path_token)
+            except FileNotFoundError:
+                pass
+
+    _hfhub.HfFolder = HfFolder
+# ─────────────────────────────────────────────────────────────────────────────
+
 import gradio as gr
 import subprocess
 import threading

requirements.txt

@@ -10,4 +10,3 @@ sentencepiece>=0.1.99
 huggingface_hub>=0.30.0
 nltk>=3.8.0
 numpy>=1.26.0
-gradio==5.29.0