Upload app.py with huggingface_hub

app.py

@@ -45,19 +45,24 @@ with open(formatter_path, "w") as f:
 
 print("✅ result_formatter.py fixed")
 
-# ── STEP 3: Load model at startup ────────────────────────────
-from transformers import AutoProcessor, GlmOcrForConditionalGeneration
-
-print("Loading model at startup...")
-processor = AutoProcessor.from_pretrained("zai-org/GLM-OCR")
-model = GlmOcrForConditionalGeneration.from_pretrained(
-    "zai-org/GLM-OCR",
-    torch_dtype=torch.bfloat16,
-    device_map="auto",
-)
-print(f"✅ Model ready on {next(model.parameters()).device}")
-
-ABANDON = set(config["pipeline"]["result_formatter"]["abandon"])
+# ── STEP 3: Lazy model load ───────────────────────────────────
+processor = None
+model     = None
+ABANDON   = set(config["pipeline"]["result_formatter"]["abandon"])
+
+def load_model():
+    global processor, model
+    if model is not None:
+        return
+    from transformers import AutoProcessor, GlmOcrForConditionalGeneration
+    print("Loading model...")
+    processor = AutoProcessor.from_pretrained("zai-org/GLM-OCR")
+    model = GlmOcrForConditionalGeneration.from_pretrained(
+        "zai-org/GLM-OCR",
+        torch_dtype=torch.bfloat16,
+        device_map="auto",
+    )
+    print(f"✅ Model ready on {next(model.parameters()).device}")
 
 # ── STEP 4: OCR one image ─────────────────────────────────────
 def ocr_image(img_path):
@@ -102,6 +107,8 @@ def run_ocr(uploaded_file):
         return "Please upload a file.", "No regions detected."
 
     try:
+        load_model()
+
         path = uploaded_file.name if hasattr(uploaded_file, "name") else str(uploaded_file)
 
         if path.lower().endswith(".pdf"):