Spaces:
Running
Running
File size: 2,505 Bytes
71e47a3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 |
from extensions.openai.embeddings import get_embeddings_model_name
from extensions.openai.errors import OpenAIError
from modules import shared
from modules.models import load_model as _load_model
from modules.models import unload_model
from modules.models_settings import get_model_metadata, update_model_parameters
from modules.utils import get_available_models
def get_current_model_list() -> list:
return [shared.model_name] # The real chat/completions model, maybe "None"
def get_pseudo_model_list() -> list:
return [ # these are expected by so much, so include some here as a dummy
'gpt-3.5-turbo',
'text-embedding-ada-002',
]
def load_model(model_name: str) -> dict:
resp = {
"id": model_name,
"object": "engine",
"owner": "self",
"ready": True,
}
if model_name not in get_pseudo_model_list() + [get_embeddings_model_name()] + get_current_model_list(): # Real model only
# No args. Maybe it works anyways!
# TODO: hack some heuristics into args for better results
shared.model_name = model_name
unload_model()
model_settings = get_model_metadata(shared.model_name)
shared.settings.update({k: v for k, v in model_settings.items() if k in shared.settings})
update_model_parameters(model_settings, initial=True)
if shared.settings['mode'] != 'instruct':
shared.settings['instruction_template'] = None
shared.model, shared.tokenizer = _load_model(shared.model_name)
if not shared.model: # load failed.
shared.model_name = "None"
raise OpenAIError(f"Model load failed for: {shared.model_name}")
return resp
def list_models(is_legacy: bool = False) -> dict:
# TODO: Lora's?
all_model_list = get_current_model_list() + [get_embeddings_model_name()] + get_pseudo_model_list() + get_available_models()
models = {}
if is_legacy:
models = [{"id": id, "object": "engine", "owner": "user", "ready": True} for id in all_model_list]
if not shared.model:
models[0]['ready'] = False
else:
models = [{"id": id, "object": "model", "owned_by": "user", "permission": []} for id in all_model_list]
resp = {
"object": "list",
"data": models,
}
return resp
def model_info(model_name: str) -> dict:
return {
"id": model_name,
"object": "model",
"owned_by": "user",
"permission": []
}
|