Create app.py

app.py

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+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import os
+
+# Initialize Hugging Face model and tokenizer
+MODEL_NAME = "microsoft/codebert-base"
+
+# Load the pre-trained CodeBERT model for understanding code
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)
+
+# Helper function to analyze code
+def analyze_code(code):
+    # Split the code into manageable chunks
+    max_length = 512
+    lines = code.split("\n")
+    chunks = ["\n".join(lines[i:i+max_length]) for i in range(0, len(lines), max_length)]
+    
+    results = []
+    for chunk in chunks:
+        tokenized_code = tokenizer(chunk, return_tensors="pt", truncation=True, max_length=max_length)
+        outputs = model(**tokenized_code)
+        logits = outputs.logits
+        results.append(logits.argmax(dim=1).item())
+    
+    return results
+
+# Function to simulate quality and bug detection
+# Note: Replace with a real analysis pipeline.
+def check_code_quality_and_bugs(code):
+    suggestions = []
+
+    # Example: Check for readability (placeholder logic)
+    if len(code.split("\n")) < 5:
+        suggestions.append("Code seems too short, ensure functionality is implemented correctly.")
+
+    # Example: Check for comments (placeholder logic)
+    if "#" not in code:
+        suggestions.append("Consider adding comments to improve code clarity.")
+
+    # Example: Check for style guide adherence (placeholder logic)
+    if "import" in code and "os" not in code:
+        suggestions.append("Unused imports detected; consider removing them.")
+
+    # Example: Detect code smells (placeholder logic)
+    if "try" in code and "except" not in code:
+        suggestions.append("`try` block without `except` may lead to unhandled exceptions.")
+
+    return suggestions
+
+# Streamlit app UI
+st.title("Code Quality and Bug Detection Tool")
+st.markdown("Analyze your code for syntax issues, quality, and potential bugs.")
+
+# File uploader
+uploaded_file = st.file_uploader("Upload a Python code file", type=["py"])
+
+# Code snippet input
+code_snippet = st.text_area("Or paste your code snippet below:")
+
+if st.button("Analyze Code"):
+    if uploaded_file is not None:
+        code = uploaded_file.read().decode("utf-8")
+    elif code_snippet.strip():
+        code = code_snippet
+    else:
+        st.error("Please upload a file or paste code to analyze.")
+        st.stop()
+
+    # Perform code analysis
+    st.subheader("Analysis Results")
+    
+    st.write("**Code Quality and Bug Suggestions:**")
+    suggestions = check_code_quality_and_bugs(code)
+    if suggestions:
+        for i, suggestion in enumerate(suggestions, 1):
+            st.write(f"{i}. {suggestion}")
+    else:
+        st.write("No issues detected. Your code looks good!")
+
+    # Simulated CodeBERT analysis (placeholder)
+    st.write("**Model Analysis:**")
+    model_results = analyze_code(code)
+    for idx, result in enumerate(model_results, 1):
+        st.write(f"Chunk {idx} classification result: {result}")
+
+st.markdown("---")
+st.markdown("*Powered by Hugging Face and Streamlit*")