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https://github.com/oobabooga/text-generation-webui.git
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78 lines
2.4 KiB
Python
78 lines
2.4 KiB
Python
from extensions.openai.embeddings import get_embeddings_model_name
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from extensions.openai.errors import *
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from modules import shared
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from modules.models import load_model, unload_model
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from modules.models_settings import get_model_metadata, update_model_parameters
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from modules.utils import get_available_models
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def get_current_model_list() -> list:
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return [shared.model_name] # The real chat/completions model, maybe "None"
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def get_pseudo_model_list() -> list:
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return [ # these are expected by so much, so include some here as a dummy
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'gpt-3.5-turbo',
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'text-embedding-ada-002',
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]
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def load_model(model_name: str) -> dict:
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resp = {
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"id": model_name,
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"object": "engine",
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"owner": "self",
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"ready": True,
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}
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if model_name not in get_pseudo_model_list() + [get_embeddings_model_name()] + get_current_model_list(): # Real model only
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# No args. Maybe it works anyways!
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# TODO: hack some heuristics into args for better results
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shared.model_name = model_name
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unload_model()
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model_settings = get_model_metadata(shared.model_name)
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shared.settings.update({k: v for k, v in model_settings.items() if k in shared.settings})
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update_model_parameters(model_settings, initial=True)
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if shared.settings['mode'] != 'instruct':
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shared.settings['instruction_template'] = None
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shared.model, shared.tokenizer = load_model(shared.model_name)
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if not shared.model: # load failed.
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shared.model_name = "None"
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raise OpenAIError(f"Model load failed for: {shared.model_name}")
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return resp
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def list_models(is_legacy: bool = False) -> dict:
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# TODO: Lora's?
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all_model_list = get_current_model_list() + [get_embeddings_model_name()] + get_pseudo_model_list() + get_available_models()
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models = {}
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if is_legacy:
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models = [{"id": id, "object": "engine", "owner": "user", "ready": True} for id in all_model_list]
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if not shared.model:
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models[0]['ready'] = False
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else:
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models = [{"id": id, "object": "model", "owned_by": "user", "permission": []} for id in all_model_list]
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resp = {
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"object": "list",
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"data": models,
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}
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return resp
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def model_info(model_name: str) -> dict:
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return {
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"id": model_name,
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"object": "model",
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"owned_by": "user",
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"permission": []
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}
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