fix import error
This commit is contained in:
parent
6723dd79dc
commit
1670594908
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@ -1,10 +1,33 @@
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import numpy as np
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from llm_server import opts
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from llm_server.cluster.cluster_config import cluster_config
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from llm_server.cluster.redis_cycle import add_backend_cycler, redis_cycle
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from llm_server.cluster.cluster_config import cluster_config, get_a_cluster_backend
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from llm_server.cluster.stores import redis_running_models
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from llm_server.custom_redis import redis
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from llm_server.llm.generator import generator
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from llm_server.llm.info import get_info
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from llm_server.routes.helpers.model import estimate_model_size
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from llm_server.routes.queue import priority_queue
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from llm_server.routes.stats import get_active_gen_workers_model, calculate_wait_time
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def get_backends_from_model(model_name: str):
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return [x.decode('utf-8') for x in redis_running_models.smembers(model_name)]
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def get_running_models():
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return redis_running_models.keys()
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def purge_backend_from_running_models(backend_url: str):
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keys = redis_running_models.keys()
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pipeline = redis_running_models.pipeline()
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for model in keys:
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pipeline.srem(model, backend_url)
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pipeline.execute()
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def is_valid_model(model_name: str):
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return redis_running_models.exists(model_name)
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def test_backend(backend_url: str, test_prompt: bool = False):
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@ -28,81 +51,64 @@ def test_backend(backend_url: str, test_prompt: bool = False):
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return True, i
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def get_backends():
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backends = cluster_config.all()
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result = {}
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for k, v in backends.items():
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b = cluster_config.get_backend(k)
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status = b.get('online', False)
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priority = b['priority']
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result[k] = {'status': status, 'priority': priority}
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if not opts.prioritize_by_size:
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online_backends = sorted(
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((url, info) for url, info in backends.items() if info['online']),
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key=lambda kv: -kv[1]['priority'],
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reverse=True
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)
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else:
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online_backends = sorted(
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((url, info) for url, info in backends.items() if info['online']),
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key=lambda kv: estimate_model_size(kv[1]['model_config']),
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reverse=True
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)
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offline_backends = sorted(
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((url, info) for url, info in backends.items() if not info['online']),
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key=lambda kv: -kv[1]['priority'],
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reverse=True
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)
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return [url for url, info in online_backends], [url for url, info in offline_backends]
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def get_a_cluster_backend(model=None):
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"""
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Get a backend from Redis. If there are no online backends, return None.
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If `model` is not supplied, we will pick one ourself.
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"""
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if model:
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# First, determine if there are multiple backends hosting the same model.
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backends_hosting_model = [i.decode('utf-8') for i in redis_running_models.smembers(model)]
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def get_model_choices(regen: bool = False):
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if not regen:
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c = redis.getp('model_choices')
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if c:
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return c
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# If so, create an iterator for those backends
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if len(backends_hosting_model):
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add_backend_cycler(model, backends_hosting_model)
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cycled = redis_cycle(model)
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if len(cycled):
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return cycled[0]
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base_client_api = redis.get('base_client_api', dtype=str)
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running_models = get_running_models()
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model_choices = {}
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for model in running_models:
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b = get_backends_from_model(model)
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context_size = []
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avg_gen_per_worker = []
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concurrent_gens = 0
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for backend_url in b:
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backend_info = cluster_config.get_backend(backend_url)
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if backend_info.get('model_config'):
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context_size.append(backend_info['model_config']['max_position_embeddings'])
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if backend_info.get('average_generation_elapsed_sec'):
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avg_gen_per_worker.append(backend_info['average_generation_elapsed_sec'])
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concurrent_gens += backend_info['concurrent_gens']
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active_gen_workers = get_active_gen_workers_model(model)
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proompters_in_queue = priority_queue.len(model)
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if len(avg_gen_per_worker):
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average_generation_elapsed_sec = np.average(avg_gen_per_worker)
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else:
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# No backend hosting that model
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return None
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else:
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online, _ = get_backends()
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if len(online):
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return online[0]
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average_generation_elapsed_sec = 0
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estimated_wait_sec = calculate_wait_time(average_generation_elapsed_sec, proompters_in_queue, concurrent_gens, active_gen_workers)
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model_choices[model] = {
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'model': model,
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'client_api': f'https://{base_client_api}/{model}',
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'ws_client_api': f'wss://{base_client_api}/{model}/v1/stream' if opts.enable_streaming else None,
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'openai_client_api': f'https://{base_client_api}/openai/{model}' if opts.enable_openi_compatible_backend else 'disabled',
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'backend_count': len(b),
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'estimated_wait': estimated_wait_sec,
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'queued': proompters_in_queue,
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'processing': active_gen_workers,
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'avg_generation_time': average_generation_elapsed_sec,
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'concurrent_gens': concurrent_gens
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}
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def get_backends_from_model(model_name: str):
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return [x.decode('utf-8') for x in redis_running_models.smembers(model_name)]
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if len(context_size):
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model_choices[model]['context_size'] = min(context_size)
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# Python wants to sort lowercase vs. uppercase letters differently.
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model_choices = dict(sorted(model_choices.items(), key=lambda item: item[0].upper()))
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# def verify_context_size(model_name:str):
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# b = get_backends_from_model(model_name)
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# for backend_url in b:
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# backend_info = cluster_config.get_backend(backend_url)
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# backend_info.get()
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default_backend_url = get_a_cluster_backend()
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default_backend_info = cluster_config.get_backend(default_backend_url)
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if not default_backend_info.get('model'):
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return None, None
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default_model = default_backend_info['model']
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def get_running_models():
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return redis_running_models.keys()
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def purge_backend_from_running_models(backend_url: str):
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keys = redis_running_models.keys()
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pipeline = redis_running_models.pipeline()
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for model in keys:
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pipeline.srem(model, backend_url)
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pipeline.execute()
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def is_valid_model(model_name: str):
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return redis_running_models.exists(model_name)
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redis.setp('model_choices', (model_choices, default_model))
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return model_choices, default_model
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@ -1,3 +1,60 @@
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from llm_server import opts
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from llm_server.cluster.redis_config_cache import RedisClusterStore
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from llm_server.cluster.redis_cycle import add_backend_cycler, redis_cycle
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from llm_server.cluster.stores import redis_running_models
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from llm_server.routes.helpers.model import estimate_model_size
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cluster_config = RedisClusterStore('cluster_config')
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def get_backends():
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backends = cluster_config.all()
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result = {}
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for k, v in backends.items():
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b = cluster_config.get_backend(k)
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status = b.get('online', False)
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priority = b['priority']
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result[k] = {'status': status, 'priority': priority}
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if not opts.prioritize_by_size:
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online_backends = sorted(
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((url, info) for url, info in backends.items() if info['online']),
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key=lambda kv: -kv[1]['priority'],
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reverse=True
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)
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else:
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online_backends = sorted(
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((url, info) for url, info in backends.items() if info['online']),
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key=lambda kv: estimate_model_size(kv[1]['model_config']),
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reverse=True
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)
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offline_backends = sorted(
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((url, info) for url, info in backends.items() if not info['online']),
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key=lambda kv: -kv[1]['priority'],
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reverse=True
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)
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return [url for url, info in online_backends], [url for url, info in offline_backends]
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def get_a_cluster_backend(model=None):
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"""
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Get a backend from Redis. If there are no online backends, return None.
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If `model` is not supplied, we will pick one ourself.
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"""
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if model:
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# First, determine if there are multiple backends hosting the same model.
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backends_hosting_model = [i.decode('utf-8') for i in redis_running_models.smembers(model)]
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# If so, create an iterator for those backends
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if len(backends_hosting_model):
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add_backend_cycler(model, backends_hosting_model)
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cycled = redis_cycle(model)
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if len(cycled):
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return cycled[0]
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else:
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# No backend hosting that model
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return None
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else:
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online, _ = get_backends()
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if len(online):
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return online[0]
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@ -1,70 +1 @@
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import numpy as np
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from llm_server import opts
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from llm_server.cluster.backend import get_a_cluster_backend, get_backends_from_model, get_running_models
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from llm_server.cluster.cluster_config import cluster_config
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from llm_server.custom_redis import redis
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from llm_server.routes.queue import priority_queue
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from llm_server.routes.stats import calculate_wait_time, get_active_gen_workers_model
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# TODO: give this a better name!
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def get_model_choices(regen: bool = False):
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if not regen:
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c = redis.getp('model_choices')
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if c:
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return c
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base_client_api = redis.get('base_client_api', dtype=str)
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running_models = get_running_models()
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model_choices = {}
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for model in running_models:
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b = get_backends_from_model(model)
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context_size = []
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avg_gen_per_worker = []
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concurrent_gens = 0
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for backend_url in b:
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backend_info = cluster_config.get_backend(backend_url)
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if backend_info.get('model_config'):
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context_size.append(backend_info['model_config']['max_position_embeddings'])
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if backend_info.get('average_generation_elapsed_sec'):
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avg_gen_per_worker.append(backend_info['average_generation_elapsed_sec'])
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concurrent_gens += backend_info['concurrent_gens']
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active_gen_workers = get_active_gen_workers_model(model)
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proompters_in_queue = priority_queue.len(model)
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if len(avg_gen_per_worker):
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average_generation_elapsed_sec = np.average(avg_gen_per_worker)
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else:
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average_generation_elapsed_sec = 0
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estimated_wait_sec = calculate_wait_time(average_generation_elapsed_sec, proompters_in_queue, concurrent_gens, active_gen_workers)
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model_choices[model] = {
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'model': model,
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'client_api': f'https://{base_client_api}/{model}',
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'ws_client_api': f'wss://{base_client_api}/{model}/v1/stream' if opts.enable_streaming else None,
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'openai_client_api': f'https://{base_client_api}/openai/{model}' if opts.enable_openi_compatible_backend else 'disabled',
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'backend_count': len(b),
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'estimated_wait': estimated_wait_sec,
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'queued': proompters_in_queue,
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'processing': active_gen_workers,
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'avg_generation_time': average_generation_elapsed_sec,
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'concurrent_gens': concurrent_gens
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}
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if len(context_size):
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model_choices[model]['context_size'] = min(context_size)
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# Python wants to sort lowercase vs. uppercase letters differently.
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model_choices = dict(sorted(model_choices.items(), key=lambda item: item[0].upper()))
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default_backend_url = get_a_cluster_backend()
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default_backend_info = cluster_config.get_backend(default_backend_url)
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if not default_backend_info.get('model'):
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return None, None
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default_model = default_backend_info['model']
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redis.setp('model_choices', (model_choices, default_model))
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return model_choices, default_model
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@ -45,5 +45,16 @@ class RedisClusterStore:
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else:
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return {}
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# def get(self, name: str):
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# return self.all().get(name)
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def validate_backend(self, backend_url: str):
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"""
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Returns the backend URL that was given, or a new one if that was offline.
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:param backend_url:
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:return:
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"""
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backend_info = self.get_backend(backend_url)
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if not backend_info['online']:
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old = backend_url
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backend_url = get_a_cluster_backend()
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print(f'Backend {old} offline. Request was redirected to {backend_url}')
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return backend_url
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@ -1,8 +1,8 @@
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import time
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from threading import Thread
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from llm_server.cluster.backend import test_backend
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from llm_server.cluster.cluster_config import cluster_config
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from llm_server.cluster.backend import test_backend
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from llm_server.cluster.stores import redis_running_models
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@ -4,7 +4,6 @@ import requests
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import tiktoken
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from llm_server import opts
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from llm_server.cluster.backend import get_a_cluster_backend
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from llm_server.cluster.cluster_config import cluster_config
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@ -13,15 +12,9 @@ def tokenize(prompt: str, backend_url: str) -> int:
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assert isinstance(prompt, str)
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assert isinstance(backend_url, str)
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# TODO: put this in a shared function
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# The backend could have died between when the request was
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# submitted and now, so let's double check it's still online.
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backend_info = cluster_config.get_backend(backend_url)
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if not backend_info['online']:
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old = backend_url
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backend_url = get_a_cluster_backend()
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print(f'Backend {old} offline. Request was redirected to {backend_url}')
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del old # gc
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backend_url = cluster_config.validate_backend(backend_url)
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if not prompt:
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# The tokenizers have issues when the prompt is None.
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@ -7,8 +7,7 @@ from llm_server.custom_redis import ONE_MONTH_SECONDS, flask_cache, redis
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from . import openai_bp
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from ..stats import server_start_time
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from ... import opts
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from ...cluster.backend import get_a_cluster_backend
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from ...cluster.cluster_config import cluster_config
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from ...cluster.cluster_config import cluster_config, get_a_cluster_backend
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from ...helpers import jsonify_pretty
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from ...llm.openai.transform import generate_oai_string
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@ -9,7 +9,7 @@ import flask
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from flask import Response, jsonify, make_response
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from llm_server import opts
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from llm_server.cluster.model_choices import get_model_choices
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from llm_server.cluster.backend import get_model_choices
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from llm_server.custom_redis import redis
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from llm_server.database.database import is_api_key_moderated, log_prompt
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from llm_server.llm import get_token_count
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@ -5,8 +5,7 @@ import flask
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from flask import Response, request
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from llm_server import opts
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from llm_server.cluster.backend import get_a_cluster_backend
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from llm_server.cluster.cluster_config import cluster_config
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from llm_server.cluster.cluster_config import cluster_config, get_a_cluster_backend
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from llm_server.custom_redis import redis
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from llm_server.database.database import get_token_ratelimit, log_prompt
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from llm_server.helpers import auto_set_base_client_api
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@ -3,7 +3,7 @@ from datetime import datetime
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from llm_server import opts
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from llm_server.cluster.cluster_config import cluster_config
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from llm_server.cluster.model_choices import get_model_choices
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from llm_server.cluster.backend import get_model_choices
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from llm_server.custom_redis import redis
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from llm_server.database.database import get_distinct_ips_24h, sum_column
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from llm_server.helpers import deep_sort
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@ -5,8 +5,8 @@ from flask import jsonify, request
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from llm_server.custom_redis import flask_cache
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from . import bp
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from ... import opts
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from ...cluster.backend import get_a_cluster_backend, get_backends_from_model, is_valid_model
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from ...cluster.cluster_config import cluster_config
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from ...cluster.backend import get_backends_from_model, is_valid_model
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from ...cluster.cluster_config import cluster_config, get_a_cluster_backend
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@bp.route('/v1/model', methods=['GET'])
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@ -4,8 +4,7 @@ from llm_server.custom_redis import flask_cache
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from . import bp
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from .generate_stats import generate_stats
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from ..auth import requires_auth
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from ...cluster.backend import get_backends
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from ...cluster.cluster_config import cluster_config
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from ...cluster.cluster_config import cluster_config, get_backends
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from ...helpers import jsonify_pretty
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@ -1,8 +1,7 @@
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import threading
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import time
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from llm_server.cluster.backend import get_a_cluster_backend
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from llm_server.cluster.cluster_config import cluster_config
|
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from llm_server.cluster.cluster_config import cluster_config, get_a_cluster_backend
|
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from llm_server.custom_redis import redis
|
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from llm_server.llm.generator import generator
|
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from llm_server.routes.queue import DataEvent, decr_active_workers, decrement_ip_count, incr_active_workers, increment_ip_count, priority_queue
|
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|
|
|
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|
|
@ -3,8 +3,7 @@ import time
|
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import requests
|
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|
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from llm_server import opts
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from llm_server.cluster.backend import get_backends
|
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from llm_server.cluster.cluster_config import cluster_config
|
||||
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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|
|
|
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|
|
@ -13,7 +13,7 @@ import simplejson as json
|
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from flask import Flask, jsonify, render_template, request
|
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|
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from llm_server.cluster.cluster_config import cluster_config
|
||||
from llm_server.cluster.model_choices import get_model_choices
|
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from llm_server.cluster.backend import get_model_choices
|
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from llm_server.config.config import mode_ui_names
|
||||
from llm_server.config.load import load_config
|
||||
from llm_server.database.conn import database
|
||||
|
|
|
|||
Loading…
Reference in New Issue