import json
import threading
import traceback

import redis as redis_redis

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.')


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:
            print(result)
            traceback.print_exc()
            continue


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


def get_results(tag, num_tasks):
    tag = str(tag)  # Required for comparison with Redis results.
    flagged_categories = set()
    num_results = 0
    while num_results < num_tasks:
        result = redis_moderation.blpop('queue:flagged_categories')
        result_tag, categories = json.loads(result[1])
        if result_tag == tag:
            if categories:
                for item in categories:
                    flagged_categories.add(item)
            num_results += 1
    return list(flagged_categories)