109 lines
4.2 KiB
Python
109 lines
4.2 KiB
Python
import os
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import logging
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import torch
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# 日志格式
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LOG_FORMAT = "%(levelname) -5s %(asctime)s" "-1d: %(message)s"
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logger = logging.getLogger()
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logger.setLevel(logging.INFO)
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logging.basicConfig(format=LOG_FORMAT)
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# 在以下字典中修改属性值，以指定本地embedding模型存储位置
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# 如将 "text2vec": "GanymedeNil/text2vec-large-chinese" 修改为 "text2vec": "User/Downloads/text2vec-large-chinese"
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# 此处请写绝对路径
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embedding_model_dict = {
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"ernie-tiny": "nghuyong/ernie-3.0-nano-zh",
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"ernie-base": "nghuyong/ernie-3.0-base-zh",
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"text2vec-base": "shibing624/text2vec-base-chinese",
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"text2vec": "GanymedeNil/text2vec-large-chinese",
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"text2vec-paraphrase": "shibing624/text2vec-base-chinese-paraphrase",
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"text2vec-sentence": "shibing624/text2vec-base-chinese-sentence",
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"text2vec-multilingual": "shibing624/text2vec-base-multilingual",
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"m3e-small": "moka-ai/m3e-small",
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"m3e-base": "/Users/liuqian/Downloads/ChatGLM-6B/m3e-base",
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"m3e-large": "moka-ai/m3e-large",
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}
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# 选用的 Embedding 名称
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EMBEDDING_MODEL = "m3e-base"
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# Embedding 模型运行设备
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EMBEDDING_DEVICE = "cuda" if torch.cuda.is_available() else "mps" if torch.backends.mps.is_available() else "cpu"
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llm_model_dict = {
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"chatglm-6b": {
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"local_model_path": "THUDM/chatglm-6b",
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"api_base_url": "http://localhost:8888/v1", # "name"修改为fastchat服务中的"api_base_url"
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"api_key": "EMPTY"
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},
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"chatglm-6b-int4": {
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"local_model_path": "THUDM/chatglm-6b-int4",
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"api_base_url": "http://localhost:8001/v1", # "name"修改为fastchat服务中的"api_base_url"
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"api_key": "EMPTY"
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},
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"chatglm2-6b": {
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"local_model_path": "/Users/liuqian/Downloads/ChatGLM-6B/chatglm2-6b", # "THUDM/chatglm2-6b",
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"api_base_url": "http://localhost:8888/v1", # "name"修改为fastchat服务中的"api_base_url"
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"api_key": "EMPTY"
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},
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"chatglm2-6b-32k": {
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"local_model_path": "THUDM/chatglm2-6b-32k", # "THUDM/chatglm2-6b-32k",
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"api_base_url": "http://localhost:8888/v1", # "name"修改为fastchat服务中的"api_base_url"
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"api_key": "EMPTY"
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},
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"vicuna-13b-hf": {
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"local_model_path": "",
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"api_base_url": "http://localhost:8000/v1", # "name"修改为fastchat服务中的"api_base_url"
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"api_key": "EMPTY"
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},
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# 调用chatgpt时如果报出： urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='api.openai.com', port=443):
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# Max retries exceeded with url: /v1/chat/completions
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# 则需要将urllib3版本修改为1.25.11
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# 如果依然报urllib3.exceptions.MaxRetryError: HTTPSConnectionPool，则将https改为http
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# 参考https://zhuanlan.zhihu.com/p/350015032
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# 如果报出：raise NewConnectionError(
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# urllib3.exceptions.NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x000001FE4BDB85E0>:
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# Failed to establish a new connection: [WinError 10060]
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# 则是因为内地和香港的IP都被OPENAI封了，需要切换为日本、新加坡等地
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"openai-chatgpt-3.5": {
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"local_model_path": "gpt-3.5-turbo",
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"api_base_url": "https://api.openapi.com/v1",
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"api_key": os.environ.get("OPENAI_API_KEY")
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},
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}
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# LLM 名称
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LLM_MODEL = "chatglm2-6b"
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# LLM 运行设备
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LLM_DEVICE = "cuda" if torch.cuda.is_available() else "mps" if torch.backends.mps.is_available() else "cpu"
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# 日志存储路径
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LOG_PATH = os.path.join(os.path.dirname(os.path.dirname(__file__)), "logs")
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if not os.path.exists(LOG_PATH):
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os.mkdir(LOG_PATH)
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# 知识库默认存储路径
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KB_ROOT_PATH = os.path.join(os.path.dirname(os.path.dirname(__file__)), "knowledge_base")
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# nltk 模型存储路径
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NLTK_DATA_PATH = os.path.join(os.path.dirname(os.path.dirname(__file__)), "nltk_data")
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# 基于本地知识问答的提示词模版
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PROMPT_TEMPLATE = """【指令】根据已知信息，简洁和专业的来回答问题。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”，不允许在答案中添加编造成分，答案请使用中文。
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【已知信息】{context}
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【问题】{question}"""
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# API 是否开启跨域，默认为False，如果需要开启，请设置为True
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# is open cross domain
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OPEN_CROSS_DOMAIN = False |