Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+# Load Pre-trained Model (Replace with your fine-tuned model)
+@st.cache_resource
+def load_model():
+    model_name = "microsoft/codebert-base"  # Replace with a fine-tuned model for vulnerability detection
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForSequenceClassification.from_pretrained(model_name)
+    return tokenizer, model
+
+tokenizer, model = load_model()
+
+# Vulnerability Explanation Function
+def analyze_code(code_snippet):
+    # Tokenize Input
+    inputs = tokenizer(code_snippet, return_tensors="pt", truncation=True, max_length=512)
+    outputs = model(**inputs)
+    predictions = torch.softmax(outputs.logits, dim=1)
+    vulnerability_score = predictions[0][1].item()  # Assuming index 1 corresponds to "vulnerable"
+    
+    # Generate Explanation
+    if vulnerability_score > 0.6:
+        explanation = (
+            f"The code has a high likelihood of being vulnerable. The model detected patterns "
+            f"indicative of potential security issues."
+        )
+    elif vulnerability_score > 0.3:
+        explanation = (
+            f"The code has some potential vulnerabilities. Review the logic carefully, especially in "
+            f"sensitive operations like input validation or file handling."
+        )
+    else:
+        explanation = (
+            f"The code appears to be safe based on the analysis. However, manual review is always recommended."
+        )
+    return vulnerability_score, explanation
+
+# Streamlit UI
+st.title("AI-Enhanced Code Vulnerability Scanner")
+st.markdown("""
+This tool uses AI to detect vulnerabilities in Python code and provides explanations for potential issues.
+""")
+
+# Input Section
+code_snippet = st.text_area("Paste your Python code here:", height=200)
+analyze_button = st.button("Analyze Code")
+
+if analyze_button and code_snippet.strip():
+    with st.spinner("Analyzing your code..."):
+        score, explanation = analyze_code(code_snippet)
+    
+    # Display Results
+    st.subheader("Analysis Results")
+    st.write(f"**Vulnerability Score:** {score:.2f}")
+    st.write(f"**Explanation:** {explanation}")
+else:
+    st.info("Please paste Python code and click 'Analyze Code'.")