Update app.py

app.py

@@ -2,13 +2,15 @@ import streamlit as st
 import torch
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
+
+
 # Load the fine-tuned model and tokenizer
 model_repo_path = 'sabssag/Code-T5'
 model = AutoModelForSeq2SeqLM.from_pretrained(model_repo_path)
 tokenizer = AutoTokenizer.from_pretrained(model_repo_path)
 
 # Function to generate Python code from LaTeX expression
-def generate_code(latex_expression, max_length=256):
+def generate_code_from_latex(latex_expression, max_length=256):
     inputs = tokenizer(f"Latex Expression: {latex_expression} Solution:", return_tensors="pt").to(model.device)
     
     # Generate the output
@@ -35,11 +37,12 @@ if st.button("Generate Code"):
         st.session_state.latex_expr = latex_input
         with st.spinner("Generating Python Code..."):
             try:
-                generated_code = generate_code(latex_expr=st.session_state.latex_expr)
+                # Correct function name here
+                generated_code = generate_code_from_latex(latex_expression=st.session_state.latex_expr)
                 # Display the generated code
                 st.subheader("Generated Python Code")
                 st.code(generated_code, language='python')
             except Exception as e:
                 st.error(f"Error during code generation: {e}")
     else:
-        st.warning("Please enter a LaTeX expression to generate Python code.")
+        st.warning("Please enter a LaTeX expression to generate Python code.")