import gradio as gr import subprocess import sys import os import threading import time import uuid import glob import shutil from pathlib import Path from huggingface_hub import HfApi from apscheduler.schedulers.background import BackgroundScheduler default_command = "bigcodebench.evaluate" is_running = False def generate_command( jsonl_file, split, subset, parallel, min_time_limit, max_as_limit, max_data_limit, max_stack_limit, check_gt_only, no_gt ): command = [default_command] if jsonl_file is not None: # Copy the uploaded file to the current directory local_filename = os.path.basename(jsonl_file.name) shutil.copy(jsonl_file.name, local_filename) command.extend(["--samples", local_filename]) command.extend(["--split", split, "--subset", subset]) if parallel is not None and parallel != 0: command.extend(["--parallel", str(int(parallel))]) command.extend([ "--min-time-limit", str(min_time_limit), "--max-as-limit", str(int(max_as_limit)), "--max-data-limit", str(int(max_data_limit)), "--max-stack-limit", str(int(max_stack_limit)) ]) if check_gt_only: command.append("--check-gt-only") if no_gt: command.append("--no-gt") return " ".join(command) def cleanup_previous_files(jsonl_file): if jsonl_file is not None: file_list = ['Dockerfile', 'app.py', 'README.md', os.path.basename(jsonl_file.name), "__pycache__"] else: file_list = ['Dockerfile', 'app.py', 'README.md', "__pycache__"] for file in glob.glob("*"): try: if file not in file_list: os.remove(file) except Exception as e: print(f"Error during cleanup of {file}: {e}") def find_result_file(): json_files = glob.glob("*.json") if json_files: return max(json_files, key=os.path.getmtime) return None def run_bigcodebench(command): global is_running if is_running: yield "A command is already running. Please wait for it to finish.\n" return is_running = True try: yield f"Executing command: {command}\n" process = subprocess.Popen(command.split(), stdout=subprocess.PIPE, stderr=subprocess.STDOUT, universal_newlines=True) def kill_process(): if process.poll() is None: # If the process is still running process.terminate() is_running = False yield "Process terminated after 12 minutes timeout.\n" # Start a timer to kill the process after 12 minutes timer = threading.Timer(720, kill_process) timer.start() for line in process.stdout: yield line # process.wait() timer.cancel() if process.returncode != 0: yield f"Error: Command exited with status {process.returncode}\n" yield "Evaluation completed.\n" result_file = find_result_file() if result_file: yield f"Result file found: {result_file}\n" else: yield "No result file found.\n" finally: is_running = False def stream_logs(command, jsonl_file=None): global is_running if is_running: yield "A command is already running. Please wait for it to finish.\n" return cleanup_previous_files(jsonl_file) yield "Cleaned up previous files.\n" log_content = [] for log_line in run_bigcodebench(command): log_content.append(log_line) yield "".join(log_content) with gr.Blocks() as demo: gr.Markdown("# BigCodeBench Evaluator") with gr.Row(): jsonl_file = gr.File(label="Upload JSONL file", file_types=[".jsonl"]) split = gr.Dropdown(choices=["complete", "instruct"], label="Split", value="complete") subset = gr.Dropdown(choices=["hard", "full"], label="Subset", value="hard") with gr.Row(): parallel = gr.Number(label="Parallel (optional)", precision=0) min_time_limit = gr.Number(label="Min Time Limit", value=1, precision=1) max_as_limit = gr.Number(label="Max AS Limit", value=25*1024, precision=0) with gr.Row(): max_data_limit = gr.Number(label="Max Data Limit", value=25*1024, precision=0) max_stack_limit = gr.Number(label="Max Stack Limit", value=10, precision=0) check_gt_only = gr.Checkbox(label="Check GT Only") no_gt = gr.Checkbox(label="No GT") command_output = gr.Textbox(label="Command", value=default_command, interactive=False) with gr.Row(): submit_btn = gr.Button("Run Evaluation") download_btn = gr.DownloadButton(label="Download Result") log_output = gr.Textbox(label="Execution Logs", lines=20) input_components = [ jsonl_file, split, subset, parallel, min_time_limit, max_as_limit, max_data_limit, max_stack_limit, check_gt_only, no_gt ] for component in input_components: component.change(generate_command, inputs=input_components, outputs=command_output) def start_evaluation(command, jsonl_file, subset, split): extra = subset + "_" if subset != "full" else "" if jsonl_file is not None: result_path = os.path.basename(jsonl_file.name).replace(".jsonl", f"_{extra}eval_results.json") else: result_path = None for log in stream_logs(command, jsonl_file): if jsonl_file is not None: yield log, gr.update(value=result_path, label=result_path), gr.update() else: yield log, gr.update(), gr.update() result_file = find_result_file() if result_file: return gr.update(label="Evaluation completed. Result file found."), gr.update(value=result_file) # gr.Button(visible=False)#, # gr.DownloadButton(label="Download Result", value=result_file, visible=True)) else: return gr.update(label="Evaluation completed. No result file found."), gr.update(value=result_path) # gr.Button("Run Evaluation", visible=True), # gr.DownloadButton(visible=False)) submit_btn.click(start_evaluation, inputs=[command_output, jsonl_file, subset, split], outputs=[log_output, download_btn]) REPO_ID = "bigcode/bigcodebench-evaluator" HF_TOKEN = os.environ.get("HF_TOKEN", None) API = HfApi(token=HF_TOKEN) def restart_space(): API.restart_space(repo_id=REPO_ID, token=HF_TOKEN) demo.queue(max_size=300).launch(share=True, server_name="0.0.0.0", server_port=7860) scheduler = BackgroundScheduler() scheduler.add_job(restart_space, "interval", hours=3) # restarted every 3h as backup in case automatic updates are not working scheduler.start()