Update app.py

app.py

@@ -1,10 +1,6 @@
-# app.py — EduPrompt API (per-task lazy load + cache-safe on Spaces)
+# app.py — EduPrompt API (per-task lazy load + cache-safe on Spaces, debug prints)
 
-from fastapi import FastAPI
-from pydantic import BaseModel
-from fastapi.middleware.cors import CORSMiddleware
-from transformers import pipeline
-import os, time
+import os
 
 # ---------- Force ALL caches to /tmp ----------
 BASE = "/tmp"
@@ -22,6 +18,12 @@ for d in [
 ]:
     os.makedirs(d, exist_ok=True)
 
+import time
+from fastapi import FastAPI
+from pydantic import BaseModel
+from fastapi.middleware.cors import CORSMiddleware
+from transformers import pipeline
+
 app = FastAPI(title="EduPrompt API")
 app.add_middleware(
     CORSMiddleware,
@@ -39,7 +41,12 @@ def health():
         writable = True
     except Exception:
         writable = False
-    return {"ok": True, "service": "eduprompt-api", "tmpWritable": writable}
+    return {
+        "ok": True,
+        "service": "eduprompt-api",
+        "tmpWritable": writable,
+        "TRANSFORMERS_CACHE": os.environ["TRANSFORMERS_CACHE"]
+    }
 
 # ---------- lazy singletons ----------
 _summarizer = None
@@ -51,6 +58,7 @@ def safe_pipeline(task: str, model_id: str):
     """Cache every model in its own /tmp subdir. CPU-only."""
     model_cache = os.path.join(os.environ["TRANSFORMERS_CACHE"], model_id.replace("/", "_"))
     os.makedirs(model_cache, exist_ok=True)
+    print(f"Loading model '{model_id}' for task '{task}' into cache dir: {model_cache}")
     return pipeline(task, model=model_id, cache_dir=model_cache, trust_remote_code=True, device=-1)
 
 def get_model(task: str):
@@ -93,6 +101,8 @@ async def run_task(data: InputData):
     try:
         model, model_used = get_model(task)
     except Exception as e:
+        import traceback
+        print(traceback.format_exc())
         return {"error": f"model_load_failed: {type(e).__name__}: {str(e)}"}
 
     try:
@@ -109,6 +119,8 @@ async def run_task(data: InputData):
             prompt = f"Explain what this code does in simple language:\n{text}"
             output = model(prompt, max_new_tokens=200, truncation=True)[0]["generated_text"]
     except Exception as e:
+        import traceback
+        print(traceback.format_exc())
         return {"error": f"inference_failed: {type(e).__name__}: {str(e)}"}
 
     return {