移除未使用的导入和配置加载逻辑，简化lpmmconfig.py文件

src/chat/knowledge/lpmmconfig.py

@@ -1,10 +1,3 @@
-import os
-import toml
-import sys
-
-# import argparse
-from .global_logger import logger
-
 PG_NAMESPACE = "paragraph"
 ENT_NAMESPACE = "entity"
 REL_NAMESPACE = "relation"
@@ -26,112 +19,3 @@ INVALID_ENTITY = [
     "她们",
     "它们",
 ]
-
-
-def _load_config(config, config_file_path):
-    """读取TOML格式的配置文件"""
-    if not os.path.exists(config_file_path):
-        return
-    with open(config_file_path, "r", encoding="utf-8") as f:
-        file_config = toml.load(f)
-
-    # Check if all top-level keys from default config exist in the file config
-    for key in config.keys():
-        if key not in file_config:
-            logger.critical(f"警告: 配置文件 '{config_file_path}' 缺少必需的顶级键: '{key}'。请检查配置文件。")
-            logger.critical("请通过template/lpmm_config_template.toml文件进行更新")
-            sys.exit(1)
-
-    if "llm_providers" in file_config:
-        for provider in file_config["llm_providers"]:
-            if provider["name"] not in config["llm_providers"]:
-                config["llm_providers"][provider["name"]] = {}
-            config["llm_providers"][provider["name"]]["base_url"] = provider["base_url"]
-            config["llm_providers"][provider["name"]]["api_key"] = provider["api_key"]
-
-    if "entity_extract" in file_config:
-        config["entity_extract"] = file_config["entity_extract"]
-
-    if "rdf_build" in file_config:
-        config["rdf_build"] = file_config["rdf_build"]
-
-    if "embedding" in file_config:
-        config["embedding"] = file_config["embedding"]
-
-    if "rag" in file_config:
-        config["rag"] = file_config["rag"]
-
-    if "qa" in file_config:
-        config["qa"] = file_config["qa"]
-
-    if "persistence" in file_config:
-        config["persistence"] = file_config["persistence"]
-    # print(config)
-    logger.info(f"从文件中读取配置: {config_file_path}")
-
-
-global_config = dict(
-    {
-        "lpmm": {
-            "version": "0.1.0",
-        },
-        "llm_providers": {
-            "localhost": {
-                "base_url": "https://api.siliconflow.cn/v1",
-                "api_key": "sk-ospynxadyorf",
-            }
-        },
-        "entity_extract": {
-            "llm": {
-                "provider": "localhost",
-                "model": "Pro/deepseek-ai/DeepSeek-V3",
-            }
-        },
-        "rdf_build": {
-            "llm": {
-                "provider": "localhost",
-                "model": "Pro/deepseek-ai/DeepSeek-V3",
-            }
-        },
-        "embedding": {
-            "provider": "localhost",
-            "model": "Pro/BAAI/bge-m3",
-            "dimension": 1024,
-        },
-        "rag": {
-            "params": {
-                "synonym_search_top_k": 10,
-                "synonym_threshold": 0.75,
-            }
-        },
-        "qa": {
-            "params": {
-                "relation_search_top_k": 10,
-                "relation_threshold": 0.75,
-                "paragraph_search_top_k": 10,
-                "paragraph_node_weight": 0.05,
-                "ent_filter_top_k": 10,
-                "ppr_damping": 0.8,
-                "res_top_k": 10,
-            },
-            "llm": {
-                "provider": "localhost",
-                "model": "qa",
-            },
-        },
-        "persistence": {
-            "data_root_path": "data",
-            "raw_data_path": "data/raw.json",
-            "openie_data_path": "data/openie.json",
-            "embedding_data_dir": "data/embedding",
-            "rag_data_dir": "data/rag",
-        },
-        "info_extraction": {
-            "workers": 10,
-        },
-    }
-)
-
-ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
-config_path = os.path.join(ROOT_PATH, "config", "lpmm_config.toml")
-_load_config(global_config, config_path)