Update app.py

app.py

@@ -8,6 +8,15 @@ MODEL = "roberta-base-openai-detector"
 tokenizer = AutoTokenizer.from_pretrained(MODEL)
 model = AutoModelForSequenceClassification.from_pretrained(MODEL)
 
+def get_color(ai_score):
+    """
+    Convert AI score (0-1) into a smooth green-yellow-red gradient.
+    """
+    red = int(ai_score * 255)
+    green = int((1 - ai_score) * 255)
+    return f"rgb({red},{green},0)"
+
+
 def detect_ai(text):
     sentences = re.split(r'(?<=[.!?]) +', text)
     results = []
@@ -25,7 +34,8 @@ def detect_ai(text):
     # Build highlighted HTML
     highlighted = ""
     for r in results:
-        color = f"rgba(255,0,0,{r['ai_score']})"
+        color = get_color(r['ai_score'])
+        # Always mark as AI (show color regardless of how small)
         highlighted += f"<span style='background-color:{color}; padding:2px'>{r['sentence']} </span>"
 
     # Compute total AI percentage
@@ -39,10 +49,9 @@ def detect_ai(text):
     return highlighted, {"sentences": results, "total_ai_percent": total_percent}
 
 
-
 with gr.Blocks() as demo:
     gr.Markdown("## 🤖 AI Detector (like ZeroGPT)")
-    gr.Markdown("Paste your text below. Redder highlights = more AI-like.")
+    gr.Markdown("Paste your text below. Green = human-like, Yellow = mixed, Red = AI-like.")
     input_text = gr.Textbox(lines=8, placeholder="Enter text here...")
     output_html = gr.HTML()
     output_json = gr.JSON()