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local-llm-server/llm_server/workers/mainer.py

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2023-09-29 00:09:44 -06:00
import time
from llm_server import opts
from llm_server.cluster.backend import get_a_cluster_backend, get_backends
from llm_server.cluster.cluster_config import cluster_config
from llm_server.custom_redis import redis
from llm_server.database.database import weighted_average_column_for_model
from llm_server.llm.info import get_running_model
def main_background_thread():
while True:
online, offline = get_backends()
for backend_url in online:
backend_info = cluster_config.get_backend(backend_url)
backend_mode = backend_info['mode']
running_model, err = get_running_model(backend_url, backend_mode)
if err:
continue
average_generation_elapsed_sec, average_output_tokens, estimated_avg_tps = calc_stats_for_backend(backend_url, running_model, backend_mode)
if average_generation_elapsed_sec: # returns None on exception
cluster_config.set_backend_value(backend_url, 'average_generation_elapsed_sec', average_generation_elapsed_sec)
if average_output_tokens:
cluster_config.set_backend_value(backend_url, 'average_output_tokens', average_output_tokens)
if average_generation_elapsed_sec and average_output_tokens:
cluster_config.set_backend_value(backend_url, 'estimated_avg_tps', estimated_avg_tps)
default_backend_url = get_a_cluster_backend()
default_backend_info = cluster_config.get_backend(default_backend_url)
default_backend_mode = default_backend_info['mode']
default_running_model, err = get_running_model(default_backend_url, default_backend_mode)
if err:
continue
default_average_generation_elapsed_sec, default_average_output_tokens, default_estimated_avg_tps = calc_stats_for_backend(default_running_model, default_running_model, default_backend_mode)
if default_average_generation_elapsed_sec:
redis.set('average_generation_elapsed_sec', default_average_generation_elapsed_sec)
if default_average_output_tokens:
redis.set('average_output_tokens', default_average_output_tokens)
if default_average_generation_elapsed_sec and default_average_output_tokens:
redis.set('estimated_avg_tps', default_estimated_avg_tps)
time.sleep(30)
def calc_stats_for_backend(backend_url, running_model, backend_mode):
# exclude_zeros=True filters out rows where an error message was returned. Previously, if there was an error, 0
# was entered into the column. The new code enters null instead but we need to be backwards compatible for now.
average_generation_elapsed_sec = weighted_average_column_for_model('prompts', 'generation_time',
running_model, backend_mode, backend_url, exclude_zeros=True,
include_system_tokens=opts.include_system_tokens_in_stats) or 0
average_output_tokens = weighted_average_column_for_model('prompts', 'response_tokens',
running_model, backend_mode, backend_url, exclude_zeros=True,
include_system_tokens=opts.include_system_tokens_in_stats) or 0
estimated_avg_tps = round(average_output_tokens / average_generation_elapsed_sec, 2) if average_generation_elapsed_sec > 0 else 0 # Avoid division by zero
return average_generation_elapsed_sec, average_output_tokens, estimated_avg_tps