local-llm-server/llm_server/workers/moderator.py

import json
import threading
import time
import traceback

import redis as redis_redis

from llm_server import opts
from llm_server.llm.openai.moderation import check_moderation_endpoint

redis_moderation = redis_redis.Redis()


def start_moderation_workers(num_workers):
    i = 0
    for _ in range(num_workers):
        t = threading.Thread(target=moderation_worker)
        t.daemon = True
        t.start()
        i += 1
    print(f'Started {i} moderation workers.')


# TODO: don't use UUID tags to identify items. Use native redis

def get_results(tag, num_tasks):
    tag = str(tag)  # Cast a UUID4 to a string.
    flagged_categories = set()
    num_results = 0
    start_time = time.time()
    while num_results < num_tasks:
        result = redis_moderation.blpop(['queue:flagged_categories'], timeout=opts.openai_moderation_timeout)
        if result is None:
            break  # Timeout occurred, break the loop.
        result_tag, categories = json.loads(result[1])
        if result_tag == tag:
            if categories:
                for item in categories:
                    flagged_categories.add(item)
            num_results += 1
        if time.time() - start_time > opts.openai_moderation_timeout:
            print('----> Timed out waiting for result from moderator.')
            break
    return list(flagged_categories)


def moderation_worker():
    while True:
        result = redis_moderation.blpop(['queue:msgs_to_check'])
        try:
            msg, tag = json.loads(result[1])
            _, categories = check_moderation_endpoint(msg)
            redis_moderation.rpush('queue:flagged_categories', json.dumps((tag, categories)))
        except:
            traceback.print_exc()
            continue


def add_moderation_task(msg, tag):
    redis_moderation.rpush('queue:msgs_to_check', json.dumps((msg, str(tag))))