85 lines
3.7 KiB
Python
85 lines
3.7 KiB
Python
import time
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from threading import Thread
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import requests
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from llm_server import opts
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from llm_server.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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class MainBackgroundThread(Thread):
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backend_online = False
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# TODO: do I really need to put everything in Redis?
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# TODO: call generate_stats() every minute, cache the results, put results in a DB table, then have other parts of code call this cache
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def __init__(self):
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Thread.__init__(self)
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self.daemon = True
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redis.set('average_generation_elapsed_sec', 0)
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redis.set('average_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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def run(self):
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while True:
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if opts.mode == 'oobabooga':
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# try:
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# r = requests.get(f'{opts.backend_url}/api/v1/model', timeout=3, verify=opts.verify_ssl)
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# opts.running_model = r.json()['result']
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# redis.set('backend_online', 1)
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# except Exception as e:
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# redis.set('backend_online', 0)
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# # TODO: handle error
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# print(e)
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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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opts.running_model = model
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redis.set('backend_online', 1)
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elif opts.mode == 'hf-textgen':
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try:
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r = requests.get(f'{opts.backend_url}/info', timeout=3, verify=opts.verify_ssl)
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j = r.json()
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opts.running_model = j['model_id'].replace('/', '_')
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redis.set('backend_online', 1)
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redis.set_dict('backend_info', j)
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except Exception as e:
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redis.set('backend_online', 0)
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# TODO: handle error
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print(e)
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elif opts.mode == 'vllm':
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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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opts.running_model = 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', opts.running_model, opts.mode, exclude_zeros=True) or 0
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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', opts.running_model, opts.mode, exclude_zeros=True) or 0
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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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# Avoid division by zero
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average_tps = round(average_output_tokens / average_generation_elapsed_sec, 2) if average_generation_elapsed_sec > 0 else 0
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redis.set('average_tps', average_tps)
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time.sleep(60)
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