57 lines
2.7 KiB
Python
57 lines
2.7 KiB
Python
import time
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from threading import Thread
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from llm_server import opts
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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_running_model
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from llm_server.routes.cache import redis
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def main_background_thread():
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redis.set('average_generation_elapsed_sec', 0)
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redis.set('estimated_avg_tps', 0)
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redis.set('average_output_tokens', 0)
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redis.set('backend_online', 0)
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redis.set_dict('backend_info', {})
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while True:
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# TODO: unify this
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if opts.mode == 'oobabooga':
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running_model, err = get_running_model()
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if err:
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print(err)
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redis.set('backend_online', 0)
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else:
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redis.set('running_model', running_model)
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redis.set('backend_online', 1)
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elif opts.mode == 'vllm':
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running_model, err = get_running_model()
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if err:
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print(err)
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redis.set('backend_online', 0)
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else:
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redis.set('running_model', running_model)
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redis.set('backend_online', 1)
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else:
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raise Exception
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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', running_model, opts.mode, opts.backend_url, exclude_zeros=True, include_system_tokens=opts.include_system_tokens_in_stats) or 0
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if average_generation_elapsed_sec: # returns None on exception
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redis.set('average_generation_elapsed_sec', average_generation_elapsed_sec)
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# overall = average_column_for_model('prompts', 'generation_time', opts.running_model)
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# print(f'Weighted: {average_generation_elapsed_sec}, overall: {overall}')
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average_output_tokens = weighted_average_column_for_model('prompts', 'response_tokens', running_model, opts.mode, opts.backend_url, exclude_zeros=True, include_system_tokens=opts.include_system_tokens_in_stats) or 0
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if average_generation_elapsed_sec:
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redis.set('average_output_tokens', average_output_tokens)
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# overall = average_column_for_model('prompts', 'response_tokens', opts.running_model)
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# print(f'Weighted: {average_output_tokens}, overall: {overall}')
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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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redis.set('estimated_avg_tps', estimated_avg_tps)
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time.sleep(60)
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