""" 项目配置文件 从.env文件读取配置 """ import os from dotenv import load_dotenv from contextvars import ContextVar from typing import Optional, Dict, Any # 加载.env文件 load_dotenv() # ==================== 大模型配置 ==================== LLM_CONFIG = { # "model": "Qwen3.5-35B-A3B", "model": "46-qwen3.5-35B", # "model": "Qwen3-14B", "base_url": "http://192.168.0.46:59800/v1", "api_key": "gpustack_dee9ca823290886c_5edfc86aeeeceb1e9ee5162941cb2cb5", "temperature": float("0.1"), "max_tokens": int("8192"), "timeout": int("30") } # ==================== 嵌入模型配置 ==================== EMBEDDING_CONFIG = { "model": "bge-m3", "base_url": "http://192.168.0.46:59700/v1/embeddings", "api_key": "gpustack_dee9ca823290886c_5edfc86aeeeceb1e9ee5162941cb2cb5", "base_url_v2" : "http://192.168.0.46:59700/v1", } # ==================== 线程安全的请求上下文配置 ==================== # 使用 contextvars 存储每个请求的用户配置，确保多用户并发时不会相互干扰 _request_user_config: ContextVar[Optional[Dict[str, str]]] = ContextVar('request_user_config', default=None) # RAG配置的默认值 _RAG_CONFIG_DEFAULT = { "search_endpoint": "http://192.168.0.46:11000/api/v1/knowledge/search/", "x-user-id": "1", "x-user-name": "testuser", "x-role": "admin", "kb-id": None, "file-id": None } class DynamicRAGConfig(dict): """ 动态RAG配置类，支持线程安全的请求级配置 当访问用户相关配置时，自动从当前请求上下文读取 其他配置项直接返回默认值 兼容字典的所有操作方式（如 get(), [], in 等） """ def __getitem__(self, key: str): # 如果是用户相关配置或知识库参数，从当前请求上下文读取 if key in ["x-user-id", "x-user-name", "x-role", "kb-id", "file-id"]: request_config = _request_user_config.get() if request_config and key in request_config: return request_config[key] # 如果没有设置，返回默认值 return _RAG_CONFIG_DEFAULT[key] # 其他配置项直接返回默认值 return _RAG_CONFIG_DEFAULT.get(key) def get(self, key: str, default=None): """支持 get() 方法""" try: return self[key] except KeyError: return default def __contains__(self, key: str): """支持 in 操作符""" return key in _RAG_CONFIG_DEFAULT def keys(self): """返回所有键""" return _RAG_CONFIG_DEFAULT.keys() def values(self): """返回所有值（动态读取用户配置）""" return [self[key] for key in _RAG_CONFIG_DEFAULT.keys()] def items(self): """返回所有键值对（动态读取用户配置）""" return [(key, self[key]) for key in _RAG_CONFIG_DEFAULT.keys()] # ==================== RAG服务配置 ==================== # 使用动态配置类，支持多用户并发时自动读取各自的配置 RAG_CONFIG = DynamicRAGConfig() def set_request_user_config(x_user_id: Optional[str] = None, x_user_name: Optional[str] = None, x_role: Optional[str] = None, text_kb_id: Optional[str] = None, text_file_id: Optional[str] = None): """ 设置当前请求的用户配置和知识库参数（线程安全） Args: x_user_id: 用户ID x_user_name: 用户名称 x_role: 角色 text_kb_id: 文本检索知识库ID text_file_id: 文本检索文件ID """ config = {} if x_user_id is not None: config["x-user-id"] = x_user_id if x_user_name is not None: config["x-user-name"] = x_user_name if x_role is not None: config["x-role"] = x_role # 仅当非空字符串时才设置，空字符串时不传入 RAG 接口 if text_kb_id is not None and str(text_kb_id).strip(): config["kb-id"] = str(text_kb_id).strip() if text_file_id is not None and str(text_file_id).strip(): config["file-id"] = str(text_file_id).strip() _request_user_config.set(config if config else None) # ==================== 图谱检索服务配置 ==================== GRAPH_SEARCH_CONFIG = { "search_endpoint": "http://192.168.0.46:59085/search_graph", "graph_timeout": float("30.0"), "default_top_k": int("10"), "operation_search_endpoint": "http://192.168.0.46:59085/operation_graph_search" } # ==================== 设备到系统检索服务配置 ==================== DEVICE_SYSTEM_CONFIG = { "endpoint": "http://192.168.0.46:59085/device_to_system", "timeout": float("30.0"), "default_min_hops": int("2"), "default_max_hops": int("8"), "default_top_k": int("10") } # ==================== 图册检索服务配置 ==================== ATLAS_CONFIG = { "endpoint": "http://192.168.0.46:59085/atlas_retrieval", "timeout": float("30.0"), "default_top_k": int("10") } # ==================== 工作流配置 ==================== WORKFLOW_CONFIG = { "max_retry_count": int("2"), # 最大重试次数 "image_clarity_threshold": float("0.7"), # 图片清晰度阈值 "default_timeout": int("30") # 默认超时时间（秒） } # ==================== 服务器配置 ==================== SERVER_CONFIG = { "host": "192.168.0.46", "port": "59088", "base_url": "http://192.168.0.46:59088" } # ==================== ASR服务配置 ==================== ASR_CONFIG = { "api_base": "http://192.168.0.46:59900/v1", "model": "base", "language": "zh", "timeout": int("30") } # ==================== VLM服务配置 ==================== VLM_CONFIG = { "api_base" : "http://192.168.0.46:59801/v1", "model" : "Qwen3-VL-8B" } # ==================== Neo4J配置 ==================== NEO4J_CONFIG = { "uri": "neo4j://192.168.0.46:57687", "user": "neo4j", "password": "zdht123@" } # ==================== 知识库匹配配置 ==================== KB_TREE_CONFIG = { "url": "http://192.168.0.46:11000/api/v1/knowledge/knowledge_base/tree" } # ==================== 维修反馈统计配置 ==================== REPAIR_FEEDBACK_CONFIG = { "url": "http://192.168.0.46:22000", "email": "15088888888@163.com", "password": "11223344" } # ==================== 数据库配置 ==================== POSTGRES_CONNECTION_STRING = "postgresql://postgres:password@192.168.0.46:5432/an_webui" #POSTGRES_CONNECTION_STRING = "postgresql+psycopg://postgres:password@192.168.0.46:5432/an_webui" POSTGRES_SQLALCHEMY_URL = "postgresql+psycopg://postgres:password@192.168.0.46:5432/an_webui" # ==================== 索引配置 ==================== INDEX_CONFIG = { "NAME_PROPERTY" : "名称", "FULLTEXT_PROPERTY" :"fulltext", "EMBEDDING_PROPERTY" : "embedding", "SEARCH_LABEL" : "Searchable", "VECTOR_INDEX_NAME" : "global_searchable_embedding", "FULLTEXT_INDEX_NAME" : "global_searchable_content_search" } # ==================== sql表格字段与neo4j节点映射 ==================== MAP_INS={ "故障模式" : "fault", "系统" : "system_name", "设备" : "device_name", "舷号" : "ship_number", } # ==================== neo4j配置 ==================== NEO4J_CONFIG = { "uri": "neo4j://192.168.0.46:57687", "user": "neo4j", "password": "zdht123@" } API_URLS = [ "http://192.168.0.46:59988/analyze-pdf", # "http://192.168.0.111:9977/analyze-pdf", # "http://192.168.0.111:9978/analyze-pdf", #"http://192.168.0.111:9979/analyze-pdf", #"http://192.168.0.111:9980/analyze-pdf", # "http://192.168.0.111:9975/analyze-pdf", ]