app.py

import os
import streamlit as st
import tensorflow as tf
import tensorflow_hub as hub
from transformers import pipeline

os.system("pip freeze > requirements.txt")
os.system("pip install -r requirements.txt")

# Function to reverse engineer code
def reverse_prompt_engineer(input_code):
    # Analyze the input code using langchain
    analyzed_code = input_code
    
    # Load the tokenizer and model
    tokenizer = pipeline("text-generation", model="EleutherAI/gpt-neo-1.3B")
    model = tokenizer.model
    
    # Generate a prompt using the analyzed code
    prompt = "Reverse engineer the following code:\n\n" + analyzed_code
    
    # Generate similar code using the ChatGPT agent's generate_code method
    generated_code = tokenizer(prompt, max_length=100, do_sample=True)
    
    return generated_code[0]['generated_text']

# Set Streamlit page configuration
st.set_page_config(
    page_title="Code Generator",
    layout="wide",
    initial_sidebar_state="expanded"
)

# Code Generation Page
st.title("Code Generator")

# User input code area
user_input = st.text_area("Input Code")

# Generate Code button
if st.button("Generate Code"):
    if not user_input:
        st.error("Input field is empty!")
    else:
        try:
            generated_code = reverse_prompt_engineer(user_input)
            st.code(generated_code)
        except Exception as e:
            st.error(f"An error occurred: {str(e)}")