Create app.py

app.py

@@ -0,0 +1,31 @@
+import streamlit as st
+from transformers import pipeline
+
+# Set up the Streamlit app layout and title
+st.title("CodeWise - AI-based Code Commenting Tool")
+st.subheader("Paste your code below, and the AI will generate comments explaining it!")
+
+# Create an input text area where users can paste their code
+code_input = st.text_area("Paste your code here:", height=300)
+
+# Slider to select the length of comments
+comment_length = st.slider("Select the comment length", min_value=50, max_value=300, value=150, step=10)
+
+# Create a button to generate the comments
+if st.button("Generate Comments"):
+    if code_input.strip() == "":
+        st.warning("Please paste some code before generating comments.")
+    else:
+        # Load a pre-trained model from Hugging Face for code summarization
+        generator = pipeline("text2text-generation", model="Salesforce/codet5-base-multi-sum")
+
+        # Generate comments using the model
+        prompt = f"Comment this code:\n\n{code_input}"
+        result = generator(prompt, max_length=comment_length, num_return_sequences=1)
+
+        # Display the generated comments in the app
+        st.subheader("Generated Comments:")
+        st.code(result[0]['generated_text'], language='python')
+
+# Display a footer message
+st.write("Powered by [Hugging Face Transformers](https://huggingface.co/) and Streamlit.")