Your Name
2 months ago
parent
4a9a0ba3ef
commit
54dfa692a8
@ -1,49 +0,0 @@
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import concurrent.futures
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from typing import List, Tuple, Any, Dict, Union, Callable
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def execute_concurrently(
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callable_functions: List[
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Tuple[Callable, Tuple[Any, ...], Dict[str, Any]]
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],
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max_workers: int = 5,
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) -> List[Union[Any, Exception]]:
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"""
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Executes callable functions concurrently using multithreading.
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Parameters:
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- callable_functions: A list of tuples, each containing the callable function and its arguments.
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For example: [(function1, (arg1, arg2), {'kwarg1': val1}), (function2, (), {})]
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- max_workers: The maximum number of threads to use.
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Returns:
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- results: A list of results returned by the callable functions. If an error occurs in any function,
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the exception object will be placed at the corresponding index in the list.
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"""
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results = [None] * len(callable_functions)
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def worker(
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fn: Callable,
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args: Tuple[Any, ...],
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kwargs: Dict[str, Any],
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index: int,
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) -> None:
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try:
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result = fn(*args, **kwargs)
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results[index] = result
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except Exception as e:
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results[index] = e
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with concurrent.futures.ThreadPoolExecutor(
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max_workers=max_workers
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) as executor:
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futures = []
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for i, (fn, args, kwargs) in enumerate(callable_functions):
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futures.append(
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executor.submit(worker, fn, args, kwargs, i)
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)
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# Wait for all threads to complete
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concurrent.futures.wait(futures)
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return results
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@ -1,80 +0,0 @@
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import functools
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import logging
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import threading
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import warnings
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def retry_decorator(max_retries: int = 5):
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"""
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Decorator that retries a function a specified number of times if an exception occurs.
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Args:
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max_retries (int): The maximum number of times to retry the function.
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Returns:
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function: The decorated function.
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"""
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def decorator(func):
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@functools.wraps(func)
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def wrapper(*args, **kwargs):
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for _ in range(max_retries):
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try:
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return func(*args, **kwargs)
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except Exception as error:
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logging.error(
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f" Error in {func.__name__}:"
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f" {str(error)} Retrying ...."
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)
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return func(*args, **kwargs)
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return wrapper
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return decorator
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def singleton_decorator(cls):
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instances = {}
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def wrapper(*args, **kwargs):
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if cls not in instances:
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instances[cls] = cls(*args, **kwargs)
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return instances[cls]
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return wrapper
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def synchronized_decorator(func):
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func.__lock__ = threading.Lock()
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def wrapper(*args, **kwargs):
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with func.__lock__:
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return func(*args, **kwargs)
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return wrapper
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def deprecated_decorator(func):
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@functools.wraps(func)
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def wrapper(*args, **kwargs):
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warnings.warn(
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f"{func.__name__} is deprecated",
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category=DeprecationWarning,
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)
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return func(*args, **kwargs)
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return wrapper
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def validate_inputs_decorator(validator):
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def decorator(func):
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@functools.wraps(func)
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def wrapper(*args, **kwargs):
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if not validator(*args, **kwargs):
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raise ValueError("Invalid Inputs")
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return func(*args, **kwargs)
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return wrapper
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return decorator
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@ -1,23 +1,33 @@
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import os
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import uuid
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from loguru import logger
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WORKSPACE_DIR = os.getenv("WORKSPACE_DIR")
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def initialize_logger(log_folder: str = "logs"):
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logger.add(
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os.path.join(WORKSPACE_DIR, "swarms.log"),
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level="INFO",
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colorize=True,
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backtrace=True,
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diagnose=True,
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)
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WORKSPACE_DIR = os.getenv("WORKSPACE_DIR")
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if not os.path.exists(WORKSPACE_DIR):
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os.makedirs(WORKSPACE_DIR)
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# Create a folder within the workspace_dir
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log_folder_path = os.path.join(WORKSPACE_DIR, log_folder)
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if not os.path.exists(log_folder_path):
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os.makedirs(log_folder_path)
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def loguru_logger(file_path: str = "swarms.log"):
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return logger.add(
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os.path.join(WORKSPACE_DIR, file_path),
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# Generate a unique identifier for the log file
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uuid_for_log = str(uuid.uuid4())
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log_file_path = os.path.join(
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log_folder_path, f"{log_folder}_{uuid_for_log}.log"
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)
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logger.add(
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log_file_path,
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level="INFO",
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colorize=True,
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backtrace=True,
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diagnose=True,
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enqueue=True,
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retention="10 days",
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compression="zip",
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)
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return logger
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@ -1,108 +0,0 @@
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import datetime
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import os
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import platform
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import traceback
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from loguru import logger
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# Remove default logger configuration
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logger.remove()
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# Define the path for the log folder
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log_folder = os.path.join(os.getcwd(), "errors")
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try:
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# Create the log folder if it doesn't exist
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os.makedirs(log_folder, exist_ok=True)
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except PermissionError:
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logger.error(f"Permission denied: '{log_folder}'")
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except Exception as e:
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logger.error(
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f"An error occurred while creating the log folder: {e}"
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)
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else:
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# If the folder was created successfully, add a new logger
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logger.add(
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os.path.join(log_folder, "error_{time}.log"),
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level="ERROR",
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format="<red>{time}</red> - <level>{level}</level> - <level>{message}</level>",
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)
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def report_error(error: Exception):
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"""
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Logs an error message and provides instructions for reporting the issue on Swarms GitHub
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or joining the community on Discord for real-time support.
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Args:
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error (Exception): The exception that occurred.
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Returns:
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None
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Raises:
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None
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"""
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# Gather extensive context information
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context_info = {
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"exception_type": type(error).__name__,
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"exception_message": str(error),
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"stack_trace": traceback.format_exc(),
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"timestamp": datetime.datetime.now().isoformat(),
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"python_version": platform.python_version(),
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"platform": platform.platform(),
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"machine": platform.machine(),
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"processor": platform.processor(),
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"user": os.getenv("USER") or os.getenv("USERNAME"),
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"current_working_directory": os.getcwd(),
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}
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error_message = (
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f"\n"
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f"------------------Error: {error}-----------------------\n"
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f"#########################################\n"
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f"# #\n"
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f"# ERROR DETECTED! #\n"
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f"# #\n"
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f"# #\n"
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f"# #\n"
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f"# #\n"
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f"#########################################\n"
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f"\n"
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f"Error Message: {context_info['exception_message']} ({context_info['exception_type']})\n"
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f"\n"
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f"Stack Trace:\n{context_info['stack_trace']}\n"
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f"\n"
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f"Context Information:\n"
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f"-----------------------------------------\n"
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f"Timestamp: {context_info['timestamp']}\n"
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f"Python Version: {context_info['python_version']}\n"
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f"Platform: {context_info['platform']}\n"
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f"Machine: {context_info['machine']}\n"
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f"Processor: {context_info['processor']}\n"
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f"User: {context_info['user']}\n"
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f"Current Working Directory: {context_info['current_working_directory']}\n"
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f"-----------------------------------------\n"
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f"\n"
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"Support"
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f"\n"
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f"\n"
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f"To report this issue, please visit the Swarms GitHub Issues page:\n"
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f"https://github.com/kyegomez/swarms/issues\n"
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f"\n"
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f"You can also join the Swarms community on Discord for real-time support:\n"
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f"https://discord.com/servers/agora-999382051935506503\n"
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f"\n"
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f"#########################################\n"
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f"-----------------------------------------\n"
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)
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return logger.error(error_message)
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# # Example usage:
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# try:
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# # Simulate an error
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# raise ValueError("An example error")
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# except Exception as e:
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# report_error(e)
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@ -1,34 +0,0 @@
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from typing import Union, Dict, List
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from swarms.artifacts.main_artifact import Artifact
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def handle_artifact_outputs(
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file_path: str,
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data: Union[str, Dict, List],
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output_type: str = "txt",
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folder_path: str = "./artifacts",
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) -> str:
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"""
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Handle different types of data and create files in various formats.
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Args:
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file_path: Path where the file should be saved
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data: Input data that can be string, dict or list
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output_type: Type of output file (txt, md, pdf, csv, json)
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folder_path: Folder to save artifacts
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Returns:
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str: Path to the created file
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"""
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# Create artifact with appropriate file type
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artifact = Artifact(
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folder_path=folder_path,
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file_path=file_path,
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file_type=output_type,
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contents=data,
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edit_count=0,
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)
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# Save the file
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# artifact.save()
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artifact.save_as(output_format=output_type)
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Loading…
Reference in new issue