Update app.py

app.py

@@ -3,9 +3,56 @@ import torch
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
 import re
 
-# ... (आपका मौजूदा डिटेक्शन कोड यहाँ रहेगा) ...
+# Load AI detection model
+MODEL_NAME = "roberta-base-openai-detector"
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)
 
-# ग्रेडियो इंटरफेस को एकीकृत करें
+# AI content detection function
+def detect_ai_content(text):
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+    with torch.no_grad():
+        outputs = model(**inputs)
+    scores = torch.nn.functional.softmax(outputs.logits, dim=1)
+    return scores[0][1].item()  # AI probability
+
+# Writing style analysis
+def stylometry_analysis(text):
+    words = text.split()
+    avg_word_length = sum(len(word) for word in words) / len(words) if words else 0
+    complex_words_ratio = len([word for word in words if len(word) > 6]) / len(words) if words else 0
+    passive_voice_count = len(re.findall(r'\b(is|was|were|has been|have been|had been)\b \w+ed', text))
+    return avg_word_length, complex_words_ratio, passive_voice_count
+
+# Semantic similarity analysis
+def semantic_analysis(text):
+    keywords = ["AI", "generated", "neural network", "LLM", "GPT", "transformer"]
+    ai_patterns = sum([text.lower().count(keyword) for keyword in keywords])
+    return ai_patterns / len(text.split()) if text.split() else 0
+
+# Final AI Detection Logic
+def analyze_text(text):
+    ai_probability = detect_ai_content(text)
+    avg_word_length, complex_words_ratio, passive_voice_count = stylometry_analysis(text)
+    semantic_score = semantic_analysis(text)
+
+    is_ai_generated = (
+        ai_probability > 0.5 or 
+        complex_words_ratio > 0.4 or 
+        semantic_score > 0.2
+    )
+
+    result = "🟢 Human-Written" if not is_ai_generated else "🔴 AI-Generated"
+
+    return {
+        "Final Verdict": result,
+        "AI Probability": round(ai_probability, 2),
+        "Complex Words Ratio": round(complex_words_ratio, 2),
+        "Passive Voice Count": passive_voice_count,
+        "Semantic Score": round(semantic_score, 2)
+    }
+
+# Gradio UI
 def create_interface():
     with gr.Blocks(title="AI Content Detector") as demo:
         # UI भाग