64 lines
2.6 KiB
Python
64 lines
2.6 KiB
Python
import time
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from datetime import datetime
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from llm_server import opts
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from llm_server.llm.info import get_running_model
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from llm_server.routes.cache import redis
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from llm_server.routes.queue import priority_queue
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from llm_server.routes.stats import SemaphoreCheckerThread, calculate_avg_gen_time, get_active_gen_workers, get_total_proompts, server_start_time
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def generate_stats():
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model_list, error = get_running_model() # will return False when the fetch fails
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if isinstance(model_list, bool):
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online = False
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else:
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online = True
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# t = elapsed_times.copy() # copy since we do multiple operations and don't want it to change
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# if len(t) == 0:
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# estimated_wait = 0
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# else:
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# waits = [elapsed for end, elapsed in t]
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# estimated_wait = int(sum(waits) / len(waits))
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proompters_in_queue = len(priority_queue) + get_active_gen_workers()
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average_tps = float(redis.get('average_tps'))
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if opts.average_generation_time_mode == 'database':
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average_generation_time = int(float(redis.get('average_generation_elapsed_sec')))
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average_output_tokens = int(float(redis.get('average_output_tokens')))
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estimated_wait_sec = int(((average_output_tokens / average_tps) * proompters_in_queue) / opts.concurrent_gens)
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elif opts.average_generation_time_mode == 'minute':
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average_generation_time = int(calculate_avg_gen_time())
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estimated_wait_sec = int((average_generation_time * proompters_in_queue) / opts.concurrent_gens)
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else:
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raise Exception
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# TODO: https://stackoverflow.com/questions/22721579/sorting-a-nested-ordereddict-by-key-recursively
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return {
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'stats': {
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'proompts_in_queue': proompters_in_queue,
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'proompters_1_min': SemaphoreCheckerThread.proompters_1_min,
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'total_proompts': get_total_proompts() if opts.show_num_prompts else None,
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'uptime': int((datetime.now() - server_start_time).total_seconds()) if opts.show_uptime else None,
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'average_generation_elapsed_sec': average_generation_time,
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'average_tps': average_tps,
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},
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'online': online,
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'mode': opts.mode,
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'model': model_list,
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'endpoints': {
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'blocking': opts.full_client_api,
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},
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'estimated_wait_sec': estimated_wait_sec,
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'timestamp': int(time.time()),
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'openaiKeys': '∞',
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'anthropicKeys': '∞',
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'config': {
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'gatekeeper': 'none' if opts.auth_required is False else 'token',
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'context_size': opts.context_size,
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'queue_size': opts.concurrent_gens,
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}
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}
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