import os

MODEL_ROOT_PATH = ""
EMBEDDING_MODEL = "bge-large-zh-v1.5"  # bge-large-zh
EMBEDDING_DEVICE = "auto"
EMBEDDING_KEYWORD_FILE = "keywords.txt"
EMBEDDING_MODEL_OUTPUT_PATH = "output"

SUPPORT_AGENT_MODELS = [
    "chatglm3-6b",
    "openai-api",
    "Qwen-14B-Chat",
    "Qwen-7B-Chat",
]
LLM_MODEL_CONFIG = {
    "preprocess_model": {
        # "Mixtral-8x7B-v0.1": {
        #     "temperature": 0.01,
        #     "max_tokens": 5,
        #     "prompt_name": "default",
        #     "callbacks": False
        # },
        "chatglm3-6b": {
            "temperature": 0.05,
            "max_tokens": 4096,
            "prompt_name": "default",
            "callbacks": False
        },
    },
    "llm_model": {
        # "Mixtral-8x7B-v0.1": {
        #     "temperature": 0.9,
        #     "max_tokens": 4000,
        #     "history_len": 5,
        #     "prompt_name": "default",
        #     "callbacks": True
        # },
        "chatglm3-6b": {
            "temperature": 0.05,
            "max_tokens": 4096,
            "prompt_name": "default",
            "history_len": 10,
            "callbacks": True
        },
    },
    "action_model": {
        # "Qwen-14B-Chat": {
        #     "temperature": 0.05,
        #     "max_tokens": 4096,
        #     "prompt_name": "qwen",
        #     "callbacks": True
        # },
        "chatglm3-6b": {
            "temperature": 0.05,
            "max_tokens": 4096,
            "prompt_name": "ChatGLM3",
            "callbacks": True
        },
        # "zhipu-api": {
        #     "temperature": 0.01,
        #     "max_tokens": 4096,
        #     "prompt_name": "ChatGLM3",
        #     "callbacks": True
        # }

    },
    "postprocess_model": {
        "zhipu-api": {
            "temperature": 0.01,
            "max_tokens": 4096,
            "prompt_name": "default",
            "callbacks": True
        }
    },
}
 
 
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",
        "nlp_gte_sentence-embedding_chinese-large": "damo/nlp_gte_sentence-embedding_chinese-large",
        "text-embedding-ada-002": "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",
    }
}

NLTK_DATA_PATH = os.path.join(os.path.dirname(os.path.dirname(__file__)), "nltk_data")
 
LOOM_CONFIG = "./loom.yaml"
OPENAI_KEY = None
OPENAI_PROXY = None