127 lines
3.9 KiB
Python
127 lines
3.9 KiB
Python
import json
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import pickle
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import threading
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import time
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from uuid import uuid4
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from redis import Redis
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from llm_server import opts
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from llm_server.llm.generator import generator
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from llm_server.routes.cache import redis
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from llm_server.routes.stats import generation_elapsed, generation_elapsed_lock
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redis.set_dict('processing_ips', {})
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def increment_ip_count(client_ip: int, redis_key):
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ip_count = redis.get_dict(redis_key)
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ip_count[client_ip] = ip_count.get(client_ip, 0) + 1
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redis.set_dict(redis_key, ip_count)
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return ip_count
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def decrement_ip_count(client_ip: int, redis_key):
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ip_count = redis.get_dict(redis_key)
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if client_ip in ip_count.keys():
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ip_count[client_ip] -= 1
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if ip_count[client_ip] == 0:
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del ip_count[client_ip] # Remove the IP from the dictionary if count is 0
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redis.set_dict(redis_key, ip_count)
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return ip_count
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class RedisPriorityQueue:
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def __init__(self):
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self._index = 0
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self._lock = threading.Lock()
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self.redis = Redis(host='localhost', port=6379, db=15)
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# Clear the DB
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for key in self.redis.scan_iter('*'):
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self.redis.delete(key)
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self.pubsub = self.redis.pubsub()
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self.pubsub.subscribe('events')
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def put(self, item, priority):
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event = DataEvent()
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# Check if the IP is already in the dictionary and if it has reached the limit
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ip_count = self.redis.hget('queued_ip_count', item[1])
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if ip_count and int(ip_count) >= opts.simultaneous_requests_per_ip and priority != 0:
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return None # reject the request
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self.redis.zadd('queue', {json.dumps((self._index, item, event.event_id)): -priority})
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self._index += 1
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# Increment the count for this IP
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with self._lock:
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self.increment_ip_count(item[1], 'queued_ip_count')
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return event
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def get(self):
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while True:
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data = self.redis.zpopmin('queue')
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if data:
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item = json.loads(data[0][0])
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client_ip = item[1][1]
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# Decrement the count for this IP
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with self._lock:
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self.decrement_ip_count(client_ip, 'queued_ip_count')
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return item
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time.sleep(1) # wait for an item to be added to the queue
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def increment_ip_count(self, ip, key):
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self.redis.hincrby(key, ip, 1)
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def decrement_ip_count(self, ip, key):
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self.redis.hincrby(key, ip, -1)
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def __len__(self):
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return self.redis.zcard('queue')
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class DataEvent:
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def __init__(self, event_id=None):
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self.event_id = event_id if event_id else str(uuid4())
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self.redis = Redis(host='localhost', port=6379, db=14)
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self.pubsub = self.redis.pubsub()
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self.pubsub.subscribe(self.event_id)
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def set(self, data):
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self.redis.publish(self.event_id, pickle.dumps(data))
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def wait(self):
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for item in self.pubsub.listen():
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if item['type'] == 'message':
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return pickle.loads(item['data'])
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priority_queue = RedisPriorityQueue()
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def worker():
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while True:
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index, (request_json_body, client_ip, token, parameters), event_id = priority_queue.get()
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increment_ip_count(client_ip, 'processing_ips')
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redis.incr('active_gen_workers')
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start_time = time.time()
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success, response, error_msg = generator(request_json_body)
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end_time = time.time()
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elapsed_time = end_time - start_time
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with generation_elapsed_lock:
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generation_elapsed.append((end_time, elapsed_time))
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event = DataEvent(event_id)
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event.set((success, response, error_msg))
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decrement_ip_count(client_ip, 'processing_ips')
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redis.decr('active_gen_workers')
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def start_workers(num_workers: int):
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for _ in range(num_workers):
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threading.Thread(target=worker).start()
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