Update app.py

app.py

@@ -1,14 +1,16 @@
-from fastapi import FastAPI, Request
+import os
+from fastapi import FastAPI
 from pydantic import BaseModel
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
-import os
 
-# Fix Hugging Face cache permission issue
+# ✅ Fix cache permission errors on Hugging Face Spaces
 os.environ["TRANSFORMERS_CACHE"] = "/tmp"
+os.environ["HF_HOME"] = "/tmp"
 
 MODEL_NAME = "roberta-base-openai-detector"
 
+# Load model safely inside /tmp
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
 model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)
 
@@ -18,15 +20,15 @@ class InputText(BaseModel):
     text: str
 
 @app.get("/")
-def read_root():
-    return {"status": "ok", "message": "AI Text Detector is running."}
+def root():
+    return {"message": "AI Text Detector is running", "usage": "POST /analyze with {'text': 'your text'}"}
 
 @app.post("/analyze")
-async def analyze_text(data: InputText):
+async def analyze(data: InputText):
     inputs = tokenizer(data.text, return_tensors="pt", truncation=True, padding=True)
     with torch.no_grad():
         logits = model(**inputs).logits
-        probs = torch.softmax(logits, dim=1).tolist()[0]
+        probs = torch.softmax(logits, dim=1)[0].tolist()
     
     results = [
         {"label": model.config.id2label[i], "score": round(probs[i], 4)}