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from ast import Dict |
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import logging |
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import logging.handlers |
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import os |
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import sys |
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import base64 |
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from PIL import Image |
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from io import BytesIO |
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import json |
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import requests |
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from constants import LOGDIR |
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import datetime |
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server_error_msg = ( |
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"**NETWORK ERROR DUE TO HIGH TRAFFIC. PLEASE REGENERATE OR REFRESH THIS PAGE.**" |
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) |
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moderation_msg = ( |
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"YOUR INPUT VIOLATES OUR CONTENT MODERATION GUIDELINES. PLEASE TRY AGAIN." |
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) |
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handler = None |
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def build_logger(logger_name, logger_filename): |
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global handler |
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formatter = logging.Formatter( |
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fmt="%(asctime)s | %(levelname)s | %(name)s | %(message)s", |
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datefmt="%Y-%m-%d %H:%M:%S", |
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) |
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if not logging.getLogger().handlers: |
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logging.basicConfig(level=logging.INFO) |
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logging.getLogger().handlers[0].setFormatter(formatter) |
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stdout_logger = logging.getLogger("stdout") |
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stdout_logger.setLevel(logging.INFO) |
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sl = StreamToLogger(stdout_logger, logging.INFO) |
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sys.stdout = sl |
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stderr_logger = logging.getLogger("stderr") |
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stderr_logger.setLevel(logging.ERROR) |
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sl = StreamToLogger(stderr_logger, logging.ERROR) |
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sys.stderr = sl |
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logger = logging.getLogger(logger_name) |
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logger.setLevel(logging.INFO) |
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if handler is None: |
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os.makedirs(LOGDIR, exist_ok=True) |
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filename = os.path.join(LOGDIR, logger_filename) |
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handler = logging.handlers.TimedRotatingFileHandler( |
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filename, when="D", utc=True |
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) |
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handler.setFormatter(formatter) |
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for name, item in logging.root.manager.loggerDict.items(): |
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if isinstance(item, logging.Logger): |
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item.addHandler(handler) |
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return logger |
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class StreamToLogger(object): |
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""" |
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Fake file-like stream object that redirects writes to a logger instance. |
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""" |
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def __init__(self, logger, log_level=logging.INFO): |
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self.terminal = sys.stdout |
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self.logger = logger |
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self.log_level = log_level |
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self.linebuf = "" |
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def __getattr__(self, attr): |
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return getattr(self.terminal, attr) |
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def write(self, buf): |
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temp_linebuf = self.linebuf + buf |
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self.linebuf = "" |
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for line in temp_linebuf.splitlines(True): |
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if line[-1] == "\n": |
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self.logger.log(self.log_level, line.rstrip()) |
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else: |
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self.linebuf += line |
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def flush(self): |
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if self.linebuf != "": |
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self.logger.log(self.log_level, self.linebuf.rstrip()) |
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self.linebuf = "" |
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def disable_torch_init(): |
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""" |
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Disable the redundant torch default initialization to accelerate model creation. |
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""" |
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import torch |
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setattr(torch.nn.Linear, "reset_parameters", lambda self: None) |
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setattr(torch.nn.LayerNorm, "reset_parameters", lambda self: None) |
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def violates_moderation(text): |
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""" |
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Check whether the text violates OpenAI moderation API. |
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""" |
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url = "https://api.openai.com/v1/moderations" |
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headers = { |
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"Content-Type": "application/json", |
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"Authorization": "Bearer " + os.environ["OPENAI_API_KEY"], |
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} |
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text = text.replace("\n", "") |
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data = "{" + '"input": ' + f'"{text}"' + "}" |
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data = data.encode("utf-8") |
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try: |
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ret = requests.post(url, headers=headers, data=data, timeout=5) |
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flagged = ret.json()["results"][0]["flagged"] |
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except requests.exceptions.RequestException as e: |
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flagged = False |
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except KeyError as e: |
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flagged = False |
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return flagged |
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def pretty_print_semaphore(semaphore): |
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if semaphore is None: |
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return "None" |
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return f"Semaphore(value={semaphore._value}, locked={semaphore.locked()})" |
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def load_image_from_base64(image): |
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return Image.open(BytesIO(base64.b64decode(image))) |
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def get_log_filename(): |
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t = datetime.datetime.now() |
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name = os.path.join(LOGDIR, f"{t.year}-{t.month:02d}-{t.day:02d}-conv.json") |
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return name |
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def data_wrapper(data): |
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if isinstance(data, bytes): |
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return data |
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elif isinstance(data, Image.Image): |
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buffered = BytesIO() |
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data.save(buffered, format="PNG") |
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return buffered.getvalue() |
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elif isinstance(data, str): |
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return data.encode() |
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elif isinstance(data, Dict): |
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return json.dumps(data).encode() |
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else: |
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raise ValueError(f"Unsupported data type: {type(data)}") |
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