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import gradio as gr
import io
import sys
import logging
import multiprocessing
import os
import pickle
import threading
import time
from collections import Counter, defaultdict
from concurrent.futures import ProcessPoolExecutor, as_completed, wait, FIRST_COMPLETED
from datetime import datetime
from typing import Any, Dict, List, Tuple
from warnings import warn
from contextlib import redirect_stdout, redirect_stderr
import numpy as np
from huggingface_hub import HfApi
from bigcodebench.data.utils import CACHE_DIR
from bigcodebench.eval import PASS, compatible_eval_result, estimate_pass_at_k, untrusted_check
from bigcodebench.gen.util import trusted_check
from apscheduler.schedulers.background import BackgroundScheduler
REPO_ID = "bigcode/bigcodebench-interaction"
HF_TOKEN = os.environ.get("HF_TOKEN", None)
API = HfApi(token=HF_TOKEN)
Result = Tuple[str, List[bool]]
def run_code(code: str) -> str:
# Create string buffers to capture output
stdout_buffer = io.StringIO()
stderr_buffer = io.StringIO()
# Create a dictionary for local variables
local_dict = {}
# Capture both stdout and stderr
with redirect_stdout(stdout_buffer), redirect_stderr(stderr_buffer):
try:
# Execute the code
exec(code, globals(), local_dict)
# Get the output
output = stdout_buffer.getvalue()
errors = stderr_buffer.getvalue()
# If there's a return value in the last expression, capture it
last_line = code.strip().split('\n')[-1]
if not (last_line.startswith('print') or last_line.strip() == ''):
try:
result = eval(last_line, globals(), local_dict)
if result is not None:
output += f"\n>>> {result}"
except:
pass
# Combine stdout and stderr
result = output
if errors:
result += "\n--- Errors ---\n" + errors
except Exception as e:
# Capture any execution errors
result = f"Error: {str(e)}"
return result if result.strip() else "Code executed successfully (no output)"
# Create the Gradio interface with better styling
interface = gr.Interface(
fn=run_code,
inputs=[
gr.Code(label="Python Code", language="python"),
],
outputs=[
gr.Textbox(label="Output")
],
)
interface.queue(default_concurrency_limit=None)
def restart_space():
logging.info(f"Restarting space with repo ID: {REPO_ID}")
try:
# Now restart the space
API.restart_space(repo_id=REPO_ID, token=HF_TOKEN)
logging.info("Space restarted successfully.")
except Exception as e:
logging.error(f"Failed to restart space: {e}")
scheduler = BackgroundScheduler()
scheduler.add_job(restart_space, "interval", hours=5) # Restart every 5hs
scheduler.start()
interface.launch(show_error=True)
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