Update app.py

app.py

@@ -5,21 +5,29 @@ import uvicorn
 
 app = FastAPI(title="AI Detector API")
 
-# Load model
+# Load the model once at startup
 MODEL_NAME = "roberta-base-openai-detector"
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
 model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)
 model.eval()
 
 def get_ai_probability(text: str) -> float:
+    """Return AI probability (0–100%) for the given text."""
     inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512)
     with torch.no_grad():
         logits = model(**inputs).logits
         probs = torch.softmax(logits, dim=1)
-    return round(probs[0][1].item() * 100, 2)
+    ai_score = probs[0][1].item() * 100
+    return round(ai_score, 2)
 
 @app.post("/analyze")
 async def analyze_text(request: Request):
+    """
+    Example body:
+    {
+      "text": "Your text here"
+    }
+    """
     data = await request.json()
     text = data.get("text", "").strip()
     if not text:
@@ -46,7 +54,7 @@ async def analyze_text(request: Request):
 
 @app.get("/")
 async def root():
-    return {"message": "AI Detector API running on port 8080"}
+    return {"message": "AI Detector API is running. Use POST /analyze"}
 
 if __name__ == "__main__":
-    uvicorn.run(app, host="0.0.0.0", port=8080)
+    uvicorn.run(app, host="0.0.0.0", port=7860)