53 lines
1.5 KiB
Python
53 lines
1.5 KiB
Python
import json
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import threading
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import traceback
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import redis as redis_redis
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from llm_server.llm.openai.moderation import check_moderation_endpoint
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redis_moderation = redis_redis.Redis()
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def start_moderation_workers(num_workers):
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i = 0
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for _ in range(num_workers):
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t = threading.Thread(target=moderation_worker)
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t.daemon = True
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t.start()
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i += 1
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print(f'Started {i} moderation workers.')
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def moderation_worker():
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while True:
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result = redis_moderation.blpop('queue:msgs_to_check')
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try:
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msg, tag = json.loads(result[1])
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print(tag)
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_, categories = check_moderation_endpoint(msg)
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redis_moderation.rpush('queue:flagged_categories', json.dumps((tag, categories)))
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except:
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print(result)
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traceback.print_exc()
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continue
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def add_moderation_task(msg, tag):
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redis_moderation.rpush('queue:msgs_to_check', json.dumps((msg, str(tag))))
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def get_results(tag, num_tasks):
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tag = str(tag) # Required for comparison with Redis results.
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flagged_categories = set()
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num_results = 0
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while num_results < num_tasks:
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result = redis_moderation.blpop('queue:flagged_categories')
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result_tag, categories = json.loads(result[1])
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if result_tag == tag:
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if categories:
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for item in categories:
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flagged_categories.add(item)
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num_results += 1
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return list(flagged_categories)
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