added debugging print statements

app.py

@@ -20,9 +20,14 @@ local_cache = snapshot_download(
         f"{SUBFOLDER}/*.safetensors",
     ],
 )
+print("[DEBUG] snapshot_download → local_cache:", local_cache)
+import pathlib
+print("[DEBUG] MODEL root contents:", list(pathlib.Path(local_cache).glob(f"{SUBFOLDER}/*")))
 
 # ——— 2) Point MODEL_DIR at that subfolder ———
 MODEL_DIR = os.path.join(local_cache, SUBFOLDER)
+print("[DEBUG] MODEL_DIR:", MODEL_DIR)
+print("[DEBUG] MODEL_DIR files:", os.listdir(MODEL_DIR))
 
 # ——— 3) Load tokenizer & model from disk ———
 tokenizer = AutoTokenizer.from_pretrained(
@@ -30,6 +35,7 @@ tokenizer = AutoTokenizer.from_pretrained(
     use_fast=False,
     trust_remote_code=True,
 )
+print("[DEBUG] Loaded tokenizer object:", tokenizer, "type:", type(tokenizer))
 
 model = AutoModelForCausalLM.from_pretrained(
     MODEL_DIR,
@@ -38,6 +44,7 @@ model = AutoModelForCausalLM.from_pretrained(
     trust_remote_code=True,
 )
 model.eval()
+print("[DEBUG] Loaded model object:", model.__class__.__name__, "device:", next(model.parameters()).device)
 
 
 # === Role Agent with instruction/input/output format ===
@@ -54,7 +61,9 @@ class RoleAgent:
             f"Output:"
         )
         print("__file__ is:", __file__)
+        print("At import, tokenizer is:", tokenizer, type(tokenizer))
         print("tokenizer is:", self.tokenizer, "— type:", type(self.tokenizer))
+        print("[DEBUG] prompt:", prompt)
         encoding = self.tokenizer(prompt, return_tensors="pt")
         inputs = {k: v.to(self.model.device) for k, v in encoding.items()}