Update app.py

app.py

@@ -1,12 +1,12 @@
 import os
-import gradio as gr
+import streamlit as st
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 import torch
 import subprocess
 
 # Force CPU usage & prevent model download issues
 os.environ["HF_HOME"] = "./cache"  # Store model locally
-MODEL_NAME = "bigcode/t5-small"  # Updated model
+MODEL_NAME = "Salesforce/codegen-350M-mono"  # Updated model
 
 tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
 model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)
@@ -27,29 +27,20 @@ def execute_code(code, language):
             return str(e)
     return "Code execution only supported for Python."
 
-def generate_and_execute(description, language):
-    code = generate_code(description, language)
-    output = execute_code(code, language) if language == "Python" else "Execution not supported for this language."
-    return code, output
+# Streamlit UI
+st.title("Multi-Language Text-to-Code AI")
+st.write("Convert natural language descriptions into code in different programming languages! Run Python code directly in the app.")
 
-# Fix Gradio interface loading issue
-iface = gr.Interface(
-    fn=generate_and_execute,
-    inputs=[
-        gr.Textbox(lines=5, placeholder="Describe your coding task..."),
-        gr.Dropdown(choices=["Python", "JavaScript", "Java"], label="Programming Language")
-    ],
-    outputs=[
-        gr.Code(label="Generated Code"),
-        gr.Textbox(label="Execution Output")
-    ],
-    title="Multi-Language Text-to-Code AI",
-    description="Convert natural language descriptions into code in different programming languages! Run Python code directly in the app.",
-    theme="default",
-    allow_flagging="never",
-    live=True
-)
+description = st.text_area("Describe your coding task...")
+language = st.selectbox("Select Programming Language", ["Python", "JavaScript", "Java"])
 
-# Launch the app
-if __name__ == "__main__":
-    iface.launch(share=True)  # Simplified launch method
+if st.button("Generate Code"):
+    if description:
+        code = generate_code(description, language)
+        st.code(code, language=language.lower())
+        
+        if language == "Python":
+            output = execute_code(code, language)
+            st.text_area("Execution Output", output, height=150)
+    else:
+        st.warning("Please enter a description to generate code.")