Initial AI detector app

app.py

@@ -0,0 +1,42 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+# Load model and tokenizer
+model_name = "Hello-SimpleAI/chatgpt-detector-roberta"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+def detect_ai_text(text):
+    if not text or len(text.strip()) == 0:
+        return {"error": "Please provide text to analyze"}
+    
+    # Tokenize
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=512, padding=True)
+    
+    # Get prediction
+    with torch.no_grad():
+        outputs = model(**inputs)
+        logits = outputs.logits
+        probs = torch.softmax(logits, dim=-1)
+    
+    # Get probabilities
+    human_prob = probs[0][0].item()
+    ai_prob = probs[0][1].item()
+    
+    return {
+        "Human": f"{human_prob * 100:.2f}%",
+        "AI Generated": f"{ai_prob * 100:.2f}%"
+    }
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=detect_ai_text,
+    inputs=gr.Textbox(lines=10, placeholder="Enter text to analyze..."),
+    outputs=gr.JSON(label="Detection Results"),
+    title="AI Text Detector",
+    description="Detects whether text was written by a human or generated by AI"
+)
+
+if __name__ == "__main__":
+    iface.launch()

requirements.txt

@@ -0,0 +1,5 @@
+gradio==4.44.0
+transformers==4.36.0
+torch==2.1.0
+sentencepiece==0.1.99
+protobuf==3.20.3