58 lines
3.2 KiB
Python
58 lines
3.2 KiB
Python
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import time
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import requests
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from llm_server import opts
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from llm_server.cluster.cluster_config import cluster_config, get_backends
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from llm_server.custom_redis import redis
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from llm_server.database.database import weighted_average_column_for_model
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from llm_server.llm.info import get_info
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from llm_server.routes.queue import RedisPriorityQueue, priority_queue
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def main_background_thread():
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while True:
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online, offline = get_backends()
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for backend_url in online:
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backend_info = cluster_config.get_backend(backend_url)
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backend_mode = backend_info['mode']
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backend_info = get_info(backend_url, backend_mode)
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running_model = backend_info.get('model')
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if not running_model:
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continue
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average_generation_elapsed_sec, average_output_tokens, estimated_avg_tps = calc_stats_for_backend(backend_url, running_model, backend_mode)
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if average_generation_elapsed_sec: # returns None on exception
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cluster_config.set_backend_value(backend_url, 'average_generation_elapsed_sec', average_generation_elapsed_sec)
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if average_output_tokens:
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cluster_config.set_backend_value(backend_url, 'average_output_tokens', average_output_tokens)
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if average_generation_elapsed_sec and average_output_tokens:
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cluster_config.set_backend_value(backend_url, 'estimated_avg_tps', estimated_avg_tps)
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if opts.background_homepage_cacher:
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try:
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base_client_api = redis.get('base_client_api', dtype=str)
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r = requests.get('https://' + base_client_api, timeout=5)
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except Exception as e:
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print(f'Failed fetch the homepage - {e.__class__.__name__}: {e}')
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backends = priority_queue.get_backends()
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for backend_url in backends:
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queue = RedisPriorityQueue(backend_url)
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queue.cleanup()
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time.sleep(30)
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def calc_stats_for_backend(backend_url, running_model, backend_mode):
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# exclude_zeros=True filters out rows where an error message was returned. Previously, if there was an error, 0
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# was entered into the column. The new code enters null instead but we need to be backwards compatible for now.
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average_generation_elapsed_sec = weighted_average_column_for_model('prompts', 'generation_time',
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running_model, backend_mode, backend_url, exclude_zeros=True,
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include_system_tokens=opts.include_system_tokens_in_stats) or 0
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average_output_tokens = weighted_average_column_for_model('prompts', 'response_tokens',
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running_model, backend_mode, backend_url, exclude_zeros=True,
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include_system_tokens=opts.include_system_tokens_in_stats) or 0
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estimated_avg_tps = round(average_output_tokens / average_generation_elapsed_sec, 2) if average_generation_elapsed_sec > 0 else 0 # Avoid division by zero
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return average_generation_elapsed_sec, average_output_tokens, estimated_avg_tps
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