42 lines
1.6 KiB
Python
42 lines
1.6 KiB
Python
import torch.cuda
|
||
import torch.backends
|
||
import os
|
||
|
||
embedding_model_dict = {
|
||
"ernie-tiny": "nghuyong/ernie-3.0-nano-zh",
|
||
"ernie-base": "nghuyong/ernie-3.0-base-zh",
|
||
"text2vec-base": "shibing624/text2vec-base-chinese",
|
||
"text2vec": "GanymedeNil/text2vec-large-chinese",
|
||
}
|
||
|
||
# Embedding model name
|
||
EMBEDDING_MODEL = "text2vec"
|
||
|
||
# Embedding running device
|
||
EMBEDDING_DEVICE = "cuda" if torch.cuda.is_available() else "mps" if torch.backends.mps.is_available() else "cpu"
|
||
|
||
# supported LLM models
|
||
llm_model_dict = {
|
||
"chatyuan": "ClueAI/ChatYuan-large-v2",
|
||
"chatglm-6b-int4-qe": "THUDM/chatglm-6b-int4-qe",
|
||
"chatglm-6b-int4": "THUDM/chatglm-6b-int4",
|
||
"chatglm-6b-int8": "THUDM/chatglm-6b-int8",
|
||
"chatglm-6b": "THUDM/chatglm-6b",
|
||
}
|
||
|
||
# LLM model name
|
||
LLM_MODEL = "chatglm-6b"
|
||
|
||
# Use p-tuning-v2 PrefixEncoder
|
||
USE_PTUNING_V2 = False
|
||
|
||
# LLM running device
|
||
LLM_DEVICE = "cuda" if torch.cuda.is_available() else "mps" if torch.backends.mps.is_available() else "cpu"
|
||
|
||
VS_ROOT_PATH = os.path.join(os.path.dirname(os.path.dirname(__file__)), "vector_store", "")
|
||
|
||
UPLOAD_ROOT_PATH = os.path.join(os.path.dirname(os.path.dirname(__file__)), "content", "")
|
||
|
||
# 基于上下文的prompt模版，请务必保留"{question}"和"{context}"
|
||
PROMPT_TEMPLATE = """基于以下已知信息，简洁和专业的来回答用户的问题，问题是"{question}"。如果无法从中得到答案，请说 "根据已知信息无法回答该问题" 或 "没有提供足够的相关信息"，不允许在答案中添加编造成分，答案请使用中文。已知内容如下:
|
||
{context} """ |