Create app.py

app.py

@@ -0,0 +1,48 @@
+import streamlit as st
+import torch
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+
+
+# Load the fine-tuned model and tokenizer
+model_repo_path = 'sabssag/Latex_to_Python_CodeT5-base'
+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_from_latex(latex_expression, max_length=256):
+    inputs = tokenizer(f"Latex Expression: {latex_expression} Solution:", return_tensors="pt").to(model.device)
+    
+    # Generate the output
+    outputs = model.generate(**inputs, max_length=max_length)
+    
+    # Decode the output into Python code
+    generated_code = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    
+    return generated_code
+
+# Streamlit app layout
+st.title("LaTeX to Python Code Generator")
+
+# Define session state keys
+if 'latex_expr' not in st.session_state:
+    st.session_state.latex_expr = ""
+
+# User input for LaTeX expression
+latex_input = st.text_area("Enter the LaTeX Expression", value=st.session_state.latex_expr, height=150)
+
+# Update session state with the new LaTeX expression
+if st.button("Generate Code"):
+    if latex_input:
+        st.session_state.latex_expr = latex_input
+        with st.spinner("Generating Python Code..."):
+            try:
+                # 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.")