MLDeveloper/code_compiler
0
1import streamlit as st2import streamlit as st3import sys4import io5 6def execute_code(code, user_input=""):7 """Execute the given code with simulated input and return the output."""8 old_stdout = sys.stdout # Backup original stdout9 redirected_output = io.StringIO() # Create a new string buffer10 sys.stdout = redirected_output # Redirect stdout to buffer11 12 input_values = user_input.strip().split("\n") # Split user inputs by line13 input_counter = 0 14 15 def mock_input(prompt=""):16 nonlocal input_counter17 if input_counter < len(input_values):18 value = input_values[input_counter]19 input_counter += 120 return value21 else:22 raise ValueError("Not enough inputs provided.")23 24 try:25 exec(code, {"input": mock_input}) # Execute the user's code with mock input26 output = redirected_output.getvalue() # Get the output from buffer27 except Exception as e:28 output = f"Error: {str(e)}" # Capture and display any errors29 finally:30 sys.stdout = old_stdout # Restore original stdout31 32 return output.strip() # Return cleaned output33 34# Streamlit UI35st.title("๐ป Python Compiler ๐")36st.write("Write your Python code and get the correct output!")37 38code_input = st.text_area("Enter your Python code:", height=200)39user_input = st.text_area("Enter input values (one per line):", height=100) # Added input field40 41if st.button("Run Code"):42 if code_input.strip():43 with st.spinner("Executing..."):44 output = execute_code(code_input, user_input) # Execute user code with mock input45 st.subheader("Output:")46 st.code(output, language="plaintext")47 else:48 st.warning("โ ๏ธ Please enter some Python code before running.")49 50 51 52# V1 without gemini api53 54# import streamlit as st55# import requests56# import os # Import os to access environment variables57 58# # Get API token from environment variable59# API_TOKEN = os.getenv("HF_API_TOKEN")60 61 62# # Change MODEL_ID to a better model63# MODEL_ID = "Salesforce/codet5p-770m" # CodeT5+ (Recommended)64# # MODEL_ID = "bigcode/starcoder2-15b" # StarCoder265# # MODEL_ID = "bigcode/starcoder"66# API_URL = f"https://api-inference.huggingface.co/models/{MODEL_ID}"67# HEADERS = {"Authorization": f"Bearer {API_TOKEN}"}68 69# def translate_code(code_snippet, source_lang, target_lang):70# """Translate code using Hugging Face API securely."""71# prompt = f"Translate the following {source_lang} code to {target_lang}:\n\n{code_snippet}\n\nTranslated {target_lang} Code:\n"72 73# response = requests.post(API_URL, headers=HEADERS, json={74# "inputs": prompt,75# "parameters": {76# "max_new_tokens": 150,77# "temperature": 0.2,78# "top_k": 5079# # "stop": ["\n\n", "#", "//", "'''"]80# }81# })82 83# if response.status_code == 200:84# generated_text = response.json()[0]["generated_text"]85# translated_code = generated_text.split(f"Translated {target_lang} Code:\n")[-1].strip()86# return translated_code87# else:88# return f"Error: {response.status_code}, {response.text}"89 90# # Streamlit UI91# st.title("๐ Code Translator using StarCoder")92# st.write("Translate code between different programming languages using AI.")93 94# languages = ["Python", "Java", "C++", "C"]95 96# source_lang = st.selectbox("Select source language", languages)97# target_lang = st.selectbox("Select target language", languages)98# code_input = st.text_area("Enter your code here:", height=200)99 100# if st.button("Translate"):101# if code_input.strip():102# with st.spinner("Translating..."):103# translated_code = translate_code(code_input, source_lang, target_lang)104# st.subheader("Translated Code:")105# st.code(translated_code, language=target_lang.lower())106# else:107# st.warning(" โ ๏ธ Please enter some code before translating. ")