92 lines
3.4 KiB
Python
92 lines
3.4 KiB
Python
import os
|
||
import platform
|
||
|
||
system_name = platform.system()
|
||
executable_path = os.getcwd()
|
||
|
||
# 日志存储路径
|
||
LOG_PATH = os.environ.get("LOG_PATH", None) or os.path.join(executable_path, "logs")
|
||
|
||
# 知识库默认存储路径
|
||
SOURCE_PATH = os.environ.get("SOURCE_PATH", None) or os.path.join(executable_path, "sources")
|
||
|
||
# 知识库默认存储路径
|
||
KB_ROOT_PATH = os.environ.get("KB_ROOT_PATH", None) or os.path.join(executable_path, "knowledge_base")
|
||
|
||
# 代码库默认存储路径
|
||
CB_ROOT_PATH = os.environ.get("CB_ROOT_PATH", None) or os.path.join(executable_path, "code_base")
|
||
|
||
# nltk 模型存储路径
|
||
NLTK_DATA_PATH = os.environ.get("NLTK_DATA_PATH", None) or os.path.join(executable_path, "nltk_data")
|
||
|
||
# 代码存储路径
|
||
JUPYTER_WORK_PATH = os.environ.get("JUPYTER_WORK_PATH", None) or os.path.join(executable_path, "jupyter_work")
|
||
|
||
# WEB_CRAWL存储路径
|
||
WEB_CRAWL_PATH = os.environ.get("WEB_CRAWL_PATH", None) or os.path.join(executable_path, "knowledge_base")
|
||
|
||
# NEBULA_DATA存储路径
|
||
NEBULA_PATH = os.environ.get("NEBULA_PATH", None) or os.path.join(executable_path, "data/nebula_data")
|
||
|
||
# CHROMA 存储路径
|
||
CHROMA_PERSISTENT_PATH = os.environ.get("CHROMA_PERSISTENT_PATH", None) or os.path.join(executable_path, "data/chroma_data")
|
||
|
||
for _path in [LOG_PATH, SOURCE_PATH, KB_ROOT_PATH, CB_ROOT_PATH, NLTK_DATA_PATH, JUPYTER_WORK_PATH, WEB_CRAWL_PATH, NEBULA_PATH, CHROMA_PERSISTENT_PATH]:
|
||
if not os.path.exists(_path):
|
||
os.makedirs(_path, exist_ok=True)
|
||
|
||
# 数据库默认存储路径。
|
||
# 如果使用sqlite，可以直接修改DB_ROOT_PATH；如果使用其它数据库，请直接修改SQLALCHEMY_DATABASE_URI。
|
||
DB_ROOT_PATH = os.path.join(KB_ROOT_PATH, "info.db")
|
||
SQLALCHEMY_DATABASE_URI = f"sqlite:///{DB_ROOT_PATH}"
|
||
|
||
kbs_config = {
|
||
"faiss": {
|
||
},}
|
||
|
||
|
||
# GENERAL SERVER CONFIG
|
||
DEFAULT_BIND_HOST = os.environ.get("DEFAULT_BIND_HOST", None) or "127.0.0.1"
|
||
|
||
# NEBULA SERVER CONFIG
|
||
NEBULA_HOST = DEFAULT_BIND_HOST
|
||
NEBULA_PORT = 9669
|
||
NEBULA_STORAGED_PORT = 9779
|
||
NEBULA_USER = 'root'
|
||
NEBULA_PASSWORD = ''
|
||
NEBULA_GRAPH_SERVER = {
|
||
"host": DEFAULT_BIND_HOST,
|
||
"port": NEBULA_PORT,
|
||
"docker_port": NEBULA_PORT
|
||
}
|
||
|
||
# CHROMA CONFIG
|
||
# CHROMA_PERSISTENT_PATH = '/home/user/chatbot/data/chroma_data'
|
||
# CHROMA_PERSISTENT_PATH = '/Users/bingxu/Desktop/工作/大模型/chatbot/codefuse-chatbot-antcode/data/chroma_data'
|
||
|
||
|
||
# 默认向量库类型。可选：faiss, milvus, pg.
|
||
DEFAULT_VS_TYPE = os.environ.get("DEFAULT_VS_TYPE") or "faiss"
|
||
|
||
# 缓存向量库数量
|
||
CACHED_VS_NUM = os.environ.get("CACHED_VS_NUM") or 1
|
||
|
||
# 知识库中单段文本长度
|
||
CHUNK_SIZE = os.environ.get("CHUNK_SIZE") or 500
|
||
|
||
# 知识库中相邻文本重合长度
|
||
OVERLAP_SIZE = os.environ.get("OVERLAP_SIZE") or 50
|
||
|
||
# 知识库匹配向量数量
|
||
VECTOR_SEARCH_TOP_K = os.environ.get("VECTOR_SEARCH_TOP_K") or 5
|
||
|
||
# 知识库匹配相关度阈值，取值范围在0-1之间，SCORE越小，相关度越高，取到1相当于不筛选，建议设置在0.5左右
|
||
# Mac 可能存在无法使用normalized_L2的问题，因此调整SCORE_THRESHOLD至 0~1100
|
||
FAISS_NORMALIZE_L2 = True if system_name in ["Linux", "Windows"] else False
|
||
SCORE_THRESHOLD = 1 if system_name in ["Linux", "Windows"] else 1100
|
||
|
||
# 搜索引擎匹配结题数量
|
||
SEARCH_ENGINE_TOP_K = os.environ.get("SEARCH_ENGINE_TOP_K") or 5
|
||
|
||
# 代码引擎匹配结题数量
|
||
CODE_SEARCH_TOP_K = os.environ.get("CODE_SEARCH_TOP_K") or 1 |