Create app.py

app.py

@@ -0,0 +1,136 @@
+import subprocess
+import re
+import pandas as pd
+import plotly.express as px
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from prettytable import PrettyTable
+import streamlit as st
+
+st.title('Code Generation on the CoNaLa Dataset')
+
+class CodeGenerator:
+    def __init__(self):
+        self.tokenizer = AutoTokenizer.from_pretrained("AhmedSSoliman/MarianCG-CoNaLa-Large")
+        self.model = AutoModelForSeq2SeqLM.from_pretrained("AhmedSSoliman/MarianCG-CoNaLa-Large")
+        
+    def generate_code(self, nl_input):
+        input_ids = self.tokenizer.encode(nl_input, return_tensors="pt")
+        output_ids = self.model.generate(input_ids)
+        output_code = self.tokenizer.decode(output_ids[0], skip_special_tokens=True)
+        return output_code
+
+   
+
+  
+  
+    def check_code(self, code):
+        with open("temp.py", "w") as f:
+            f.write(code)
+        result = subprocess.run(["flake8", "temp.py"], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+        output = result.stdout.decode()
+        error = result.stderr.decode()
+
+        return self._process_output(output, error)
+
+    def check_code_list(self, code_list):
+        output = ""
+        error = ""
+        for code in code_list:
+            with open("temp.py", "w") as f:
+                f.write(code)
+            result = subprocess.run(["flake8", "--count", "temp.py"], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+            output += result.stdout.decode()
+            error += result.stderr.decode()
+
+        return self._process_output(output, error)
+
+    def _process_output(self, output, error):
+        if output:
+            output_counts = self._get_error_counts(output)
+            self.show_variables_in_table(output_counts, output)
+            self.visualize_all_errors(output_counts)
+            self.visualize_error_types(output_counts)
+            
+            return self._format_error_counts(output_counts)
+        else:
+            error_counts = self._get_error_counts(error)
+            self.show_variables_in_table(output_counts, output)
+            self.visualize_all_errors(error_counts)
+            self.visualize_error_types(error_counts)
+
+            return self._format_error_counts(error_counts)
+
+    def _get_error_counts(self, output):
+        error_counts = {}
+        error_messages = re.findall(r"temp.py:(\d+):\d+: (\w\d+)", output)
+        for message in error_messages:
+            error_type = message[1]
+            if error_type in error_counts:
+                error_counts[error_type] += 1
+            else:
+                error_counts[error_type] = 1
+        return error_counts
+
+    def _format_error_counts(self, error_counts):
+        error_message = "\n".join([f"{error_type}: {count}" for error_type, count in error_counts.items()])
+        return error_message
+
+    def visualize_all_errors(self, error_counts):
+        for error_type, count in error_counts.items():
+            print(f"{error_type}: {count}\n")
+
+
+    def visualize_error_types(self, error_counts):
+        df = pd.DataFrame({'Error Type': list(error_counts.keys()), 'Count': list(error_counts.values())})
+        fig = px.bar(df, x='Count', y='Error Type', title='Error Occurrences in The Generated Code')
+        fig.update_layout(
+            title={
+                'text': "Error Occurrences in The Generated Code",
+                'x': 0.5,
+                'y': 0.96,
+                'xanchor': 'center',
+                'yanchor': 'top'
+            },
+            xaxis_title="Error Counts",
+            yaxis_title="Error Codes"
+        )
+        fig.show()
+
+    def show_variables_in_table(self, output_counts, output):
+        table = PrettyTable()
+        table.field_names = ["Error Code", "Message"]
+        table.add_row([output_counts, output])
+        #table.add_row(["Error", error])
+        print(table)
+
+    def display_variables(self, output, error):
+        output_df = pd.DataFrame({"Output": [output]})
+        error_df = pd.DataFrame({"Error": [error]})
+        display(pd.concat([output_df, error_df], axis=1))
+
+
+
+code_generator = CodeGenerator()
+
+
+# Streamlit app
+def main():
+    st.title('Code Generator and Error Checker')
+    nl_input = st.text_area('Enter natural language input for code generation')
+    if st.button('Generate Code'):
+        # Generate code
+        output_code = code_generator.generate_code(nl_input)
+        st.subheader('Generated Code')
+        st.code(output_code, language='python')
+
+        # Check code for errors
+        st.subheader('Error Check')
+        error_message = code_generator.check_code(output_code)
+        st.write('Error Counts:')
+        st.write(error_message)
+
+
+if __name__ == '__main__':
+    
+    main()
+