import os # 可以指定一个绝对路径，统一存放所有的Embedding和LLM模型。 # 每个模型可以是一个单独的目录，也可以是某个目录下的二级子目录 MODEL_ROOT_PATH = "" # 在以下字典中修改属性值，以指定本地embedding模型存储位置。支持3种设置方法： # 1、将对应的值修改为模型绝对路径 # 2、不修改此处的值（以 text2vec 为例）： # 2.1 如果{MODEL_ROOT_PATH}下存在如下任一子目录： # - text2vec # - GanymedeNil/text2vec-large-chinese # - text2vec-large-chinese # 2.2 如果以上本地路径不存在，则使用huggingface模型 MODEL_PATH = { "embed_model": { "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", "text2vec-paraphrase": "shibing624/text2vec-base-chinese-paraphrase", "text2vec-sentence": "shibing624/text2vec-base-chinese-sentence", "text2vec-multilingual": "shibing624/text2vec-base-multilingual", "text2vec-bge-large-chinese": "shibing624/text2vec-bge-large-chinese", "m3e-small": "moka-ai/m3e-small", "m3e-base": "moka-ai/m3e-base", "m3e-large": "moka-ai/m3e-large", "bge-small-zh": "BAAI/bge-small-zh", "bge-base-zh": "BAAI/bge-base-zh", "bge-large-zh": "BAAI/bge-large-zh", "bge-large-zh-noinstruct": "BAAI/bge-large-zh-noinstruct", "bge-base-zh-v1.5": "BAAI/bge-base-zh-v1.5", "bge-large-zh-v1.5": "BAAI/bge-large-zh-v1.5", "piccolo-base-zh": "sensenova/piccolo-base-zh", "piccolo-large-zh": "sensenova/piccolo-large-zh", "text-embedding-ada-002": "your OPENAI_API_KEY", }, # TODO: add all supported llm models "llm_model": { # 以下部分模型并未完全测试，仅根据fastchat和vllm模型的模型列表推定支持 "chatglm-6b": "THUDM/chatglm-6b", "chatglm2-6b": "THUDM/chatglm2-6b", "chatglm2-6b-int4": "THUDM/chatglm2-6b-int4", "chatglm2-6b-32k": "THUDM/chatglm2-6b-32k", "baichuan2-13b": "baichuan-inc/Baichuan2-13B-Chat", "baichuan2-7b":"baichuan-inc/Baichuan2-7B-Chat", "baichuan-7b": "baichuan-inc/Baichuan-7B", "baichuan-13b": "baichuan-inc/Baichuan-13B", 'baichuan-13b-chat':'baichuan-inc/Baichuan-13B-Chat', "aquila-7b":"BAAI/Aquila-7B", "aquilachat-7b":"BAAI/AquilaChat-7B", "internlm-7b":"internlm/internlm-7b", "internlm-chat-7b":"internlm/internlm-chat-7b", "falcon-7b":"tiiuae/falcon-7b", "falcon-40b":"tiiuae/falcon-40b", "falcon-rw-7b":"tiiuae/falcon-rw-7b", "gpt2":"gpt2", "gpt2-xl":"gpt2-xl", "gpt-j-6b":"EleutherAI/gpt-j-6b", "gpt4all-j":"nomic-ai/gpt4all-j", "gpt-neox-20b":"EleutherAI/gpt-neox-20b", "pythia-12b":"EleutherAI/pythia-12b", "oasst-sft-4-pythia-12b-epoch-3.5":"OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5", "dolly-v2-12b":"databricks/dolly-v2-12b", "stablelm-tuned-alpha-7b":"stabilityai/stablelm-tuned-alpha-7b", "Llama-2-13b-hf":"meta-llama/Llama-2-13b-hf", "Llama-2-70b-hf":"meta-llama/Llama-2-70b-hf", "open_llama_13b":"openlm-research/open_llama_13b", "vicuna-13b-v1.3":"lmsys/vicuna-13b-v1.3", "koala":"young-geng/koala", "mpt-7b":"mosaicml/mpt-7b", "mpt-7b-storywriter":"mosaicml/mpt-7b-storywriter", "mpt-30b":"mosaicml/mpt-30b", "opt-66b":"facebook/opt-66b", "opt-iml-max-30b":"facebook/opt-iml-max-30b", "Qwen-7B":"Qwen/Qwen-7B", "Qwen-14B":"Qwen/Qwen-14B", "Qwen-7B-Chat":"Qwen/Qwen-7B-Chat", "Qwen-14B-Chat":"Qwen/Qwen-14B-Chat", }, } # 选用的 Embedding 名称 EMBEDDING_MODEL = "m3e-base" # 可以尝试最新的嵌入式sota模型：bge-large-zh-v1.5 # Embedding 模型运行设备。设为"auto"会自动检测，也可手动设定为"cuda","mps","cpu"其中之一。 EMBEDDING_DEVICE = "auto" # LLM 名称 LLM_MODEL = "chatglm2-6b" # LLM 运行设备。设为"auto"会自动检测，也可手动设定为"cuda","mps","cpu"其中之一。 LLM_DEVICE = "auto" # 历史对话轮数 HISTORY_LEN = 3 # LLM通用对话参数 TEMPERATURE = 0.7 # TOP_P = 0.95 # ChatOpenAI暂不支持该参数 LANGCHAIN_LLM_MODEL = { # 不需要走Fschat封装的，Langchain直接支持的模型。 # 调用chatgpt时如果报出： urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='api.openai.com', port=443): # Max retries exceeded with url: /v1/chat/completions # 则需要将urllib3版本修改为1.25.11 # 如果依然报urllib3.exceptions.MaxRetryError: HTTPSConnectionPool，则将https改为http # 参考https://zhuanlan.zhihu.com/p/350015032 # 如果报出：raise NewConnectionError( # urllib3.exceptions.NewConnectionError: : # Failed to establish a new connection: [WinError 10060] # 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 # 如果出现WARNING: Retrying langchain.chat_models.openai.acompletion_with_retry.._completion_with_retry in # 4.0 seconds as it raised APIConnectionError: Error communicating with OpenAI. # 需要添加代理访问(正常开的代理软件可能会拦截不上)需要设置配置openai_proxy 或者 使用环境遍历OPENAI_PROXY 进行设置 # 比如: "openai_proxy": 'http://127.0.0.1:4780' # 这些配置文件的名字不能改动 "Azure-OpenAI": { "deployment_name": "your Azure deployment name", "model_version": "0701", "openai_api_type": "azure", "api_base_url": "https://your Azure point.azure.com", "api_version": "2023-07-01-preview", "api_key": "your Azure api key", "openai_proxy": "", }, "OpenAI": { "model_name": "your openai model name(such as gpt-4)", "api_base_url": "https://api.openai.com/v1", "api_key": "your OPENAI_API_KEY", "openai_proxy": "", }, "Anthropic": { "model_name": "your claude model name(such as claude2-100k)", "api_key":"your ANTHROPIC_API_KEY", } } ONLINE_LLM_MODEL = { # 线上模型。请在server_config中为每个在线API设置不同的端口 # 具体注册及api key获取请前往 http://open.bigmodel.cn "zhipu-api": { "api_key": "", "version": "chatglm_pro", # 可选包括 "chatglm_lite", "chatglm_std", "chatglm_pro" "provider": "ChatGLMWorker", }, # 具体注册及api key获取请前往 https://api.minimax.chat/ "minimax-api": { "group_id": "", "api_key": "", "is_pro": False, "provider": "MiniMaxWorker", }, # 具体注册及api key获取请前往 https://xinghuo.xfyun.cn/ "xinghuo-api": { "APPID": "", "APISecret": "", "api_key": "", "is_v2": False, "provider": "XingHuoWorker", }, # 百度千帆 API，申请方式请参考 https://cloud.baidu.com/doc/WENXINWORKSHOP/s/4lilb2lpf "qianfan-api": { "version": "ernie-bot-turbo", # 当前支持 "ernie-bot" 或 "ernie-bot-turbo"， 更多的见官方文档。 "version_url": "", # 也可以不填写version，直接填写在千帆申请模型发布的API地址 "api_key": "", "secret_key": "", "provider": "QianFanWorker", }, # 火山方舟 API，文档参考 https://www.volcengine.com/docs/82379 "fangzhou-api": { "version": "chatglm-6b-model", # 当前支持 "chatglm-6b-model"， 更多的见文档模型支持列表中方舟部分。 "version_url": "", # 可以不填写version，直接填写在方舟申请模型发布的API地址 "api_key": "", "secret_key": "", "provider": "FangZhouWorker", }, # 阿里云通义千问 API，文档参考 https://help.aliyun.com/zh/dashscope/developer-reference/api-details "qwen-api": { "version": "qwen-turbo", # 可选包括 "qwen-turbo", "qwen-plus" "api_key": "", # 请在阿里云控制台模型服务灵积API-KEY管理页面创建 "provider": "QwenWorker", }, # 百川 API，申请方式请参考 https://www.baichuan-ai.com/home#api-enter "baichuan-api": { "version": "Baichuan2-53B", # 当前支持 "Baichuan2-53B"， 见官方文档。 "api_key": "", "secret_key": "", "provider": "BaiChuanWorker", }, } # 通常情况下不需要更改以下内容 # nltk 模型存储路径 NLTK_DATA_PATH = os.path.join(os.path.dirname(os.path.dirname(__file__)), "nltk_data") VLLM_MODEL_DICT = { "aquila-7b":"BAAI/Aquila-7B", "aquilachat-7b":"BAAI/AquilaChat-7B", "baichuan-7b": "baichuan-inc/Baichuan-7B", "baichuan-13b": "baichuan-inc/Baichuan-13B", 'baichuan-13b-chat':'baichuan-inc/Baichuan-13B-Chat', # 注意：bloom系列的tokenizer与model是分离的，因此虽然vllm支持，但与fschat框架不兼容 # "bloom":"bigscience/bloom", # "bloomz":"bigscience/bloomz", # "bloomz-560m":"bigscience/bloomz-560m", # "bloomz-7b1":"bigscience/bloomz-7b1", # "bloomz-1b7":"bigscience/bloomz-1b7", "internlm-7b":"internlm/internlm-7b", "internlm-chat-7b":"internlm/internlm-chat-7b", "falcon-7b":"tiiuae/falcon-7b", "falcon-40b":"tiiuae/falcon-40b", "falcon-rw-7b":"tiiuae/falcon-rw-7b", "gpt2":"gpt2", "gpt2-xl":"gpt2-xl", "gpt-j-6b":"EleutherAI/gpt-j-6b", "gpt4all-j":"nomic-ai/gpt4all-j", "gpt-neox-20b":"EleutherAI/gpt-neox-20b", "pythia-12b":"EleutherAI/pythia-12b", "oasst-sft-4-pythia-12b-epoch-3.5":"OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5", "dolly-v2-12b":"databricks/dolly-v2-12b", "stablelm-tuned-alpha-7b":"stabilityai/stablelm-tuned-alpha-7b", "Llama-2-13b-hf":"meta-llama/Llama-2-13b-hf", "Llama-2-70b-hf":"meta-llama/Llama-2-70b-hf", "open_llama_13b":"openlm-research/open_llama_13b", "vicuna-13b-v1.3":"lmsys/vicuna-13b-v1.3", "koala":"young-geng/koala", "mpt-7b":"mosaicml/mpt-7b", "mpt-7b-storywriter":"mosaicml/mpt-7b-storywriter", "mpt-30b":"mosaicml/mpt-30b", "opt-66b":"facebook/opt-66b", "opt-iml-max-30b":"facebook/opt-iml-max-30b", "Qwen-7B":"Qwen/Qwen-7B", "Qwen-14B":"Qwen/Qwen-14B", "Qwen-7B-Chat":"Qwen/Qwen-7B-Chat", "Qwen-14B-Chat":"Qwen/Qwen-14B-Chat", }