'commit'

dsRag/Config/Config.py

@@ -1,20 +1,3 @@
-# Elasticsearch配置
-ES_CONFIG = {
-    "hosts": "https://10.10.14.206:9200",
-    "basic_auth": ("elastic", "jv9h8uwRrRxmDi1dq6u8"),
-    "verify_certs": False,
-    "ssl_show_warn": False,
-    "default_index": "knowledge_base"
-}
-
-# 词向量模型路径
-WORD2VEC_MODEL_PATH = r"D:\Tencent_AILab_ChineseEmbedding\Tencent_AILab_ChineseEmbedding.txt"
-
-# DeepSeek
-DEEPSEEK_API_KEY = 'sk-44ae895eeb614aa1a9c6460579e322f1'
-DEEPSEEK_URL = 'https://api.deepseek.com'
-
-
 # MYSQL配置信息
 MYSQL_HOST = "10.10.14.210"
 MYSQL_PORT = 22066
@@ -26,4 +9,21 @@ MYSQL_DB_NAME = "base_db"
 # https://bailian.console.aliyun.com/?spm=a2c4g.11186623.0.0.77b17980FcMVYv&apiKey=1#/api-key
 MODEL_API_KEY = "sk-01d13a39e09844038322108ecdbd1bbc"
 MODEL_NAME = "qwen-plus"
-#MODEL_NAME = "deepseek-v3"
+#MODEL_NAME = "deepseek-v3"
+
+# Milvus 服务器的主机地址
+MS_HOST = "10.10.14.207"
+# Milvus 服务器的端口号
+MS_PORT = "19530"
+# Milvus 集合的名称
+MS_COLLECTION_NAME = "ds_collection"
+# Milvus 连接池的最大连接数
+MS_MAX_CONNECTIONS = 50
+# 腾讯 AI Lab 中文词向量模型的路径
+MS_MODEL_PATH = "D:/Tencent_AILab_ChineseEmbedding/Tencent_AILab_ChineseEmbedding.txt"
+# 加载词向量模型时限制的词汇数量
+MS_MODEL_LIMIT = 10000
+# 词向量的维度（腾讯 AI Lab 中文词向量模型的维度为 200）
+MS_DIMENSION = 200
+# Milvus 搜索时的 nprobe 参数，用于控制搜索的精度和性能
+MS_NPROBE = 100

dsRag/Milvus/Config/MulvusConfig.py

@@ -1,84 +0,0 @@
-# Milvus 服务器的主机地址
-#MS_HOST = "10.10.14.205"
-MS_HOST = "10.10.14.207"
-# Milvus 服务器的端口号
-MS_PORT = "19530"
-
-# Milvus 集合的名称
-MS_COLLECTION_NAME = "ds_collection"
-
-# Milvus 连接池的最大连接数
-MS_MAX_CONNECTIONS = 50
-
-# 腾讯 AI Lab 中文词向量模型的路径
-MS_MODEL_PATH = "D:/Tencent_AILab_ChineseEmbedding/Tencent_AILab_ChineseEmbedding.txt"
-
-# 加载词向量模型时限制的词汇数量
-MS_MODEL_LIMIT = 10000
-
-# 词向量的维度（腾讯 AI Lab 中文词向量模型的维度为 200）
-MS_DIMENSION = 200
-
-# Milvus 搜索时的 nprobe 参数，用于控制搜索的精度和性能
-MS_NPROBE = 100
-
-# Redis 配置
-REDIS_HOST = '10.10.14.14'  # Redis 服务器地址
-REDIS_PORT = 18890  # Redis 端口
-REDIS_DB = 0  # Redis 数据库编号
-REDIS_PASSWORD = None  # Redis 密码（如果没有密码，设置为 None）
-
-# MYSQL配置信息
-MYSQL_HOST = "10.10.14.210"
-MYSQL_PORT = 22066
-MYSQL_USER = "root"
-MYSQL_PASSWORD = "DsideaL147258369"
-MYSQL_DB_NAME = "ai_db"
-
-# JWT密匙
-JWT_SECRET_KEY = "DsideaL4r5t6y7u"
-# 配置 JWT
-ALGORITHM = "HS256"
-ACCESS_TOKEN_EXPIRE_MINUTES = 24 * 60 * 30 # 一个月有效期
-#  ----------------下面的配置需要根据情况进行修改-------------------------
-
-'''
-######################### 驿来特 #########################
-ACCESS_KEY_ID = 'LTAI5t5jxkgJtRK8wew8fnbq'
-ACCESS_KEY_SECRET = 'b8HXNGz7IkI3Dhv7BZx9BNBEZy1uku'
-BUCKET_NAME = 'ylt'
-ENDPOINT = 'https://oss-cn-hangzhou.aliyuncs.com'
-OSS_PREFIX = "https://ylt.oss-cn-hangzhou.aliyuncs.com/"
-
-# 阿里云中用来调用 deepseek v3 的密钥
-MODEL_API_KEY = "sk-f6da0c787eff4b0389e4ad03a35a911f"
-#MODEL_NAME = "qwen-plus"
-MODEL_NAME = "deepseek-v3"
-
-# TTS的APPKEY
-APPKEY = "90RJcqjlN4ZqymGd"  # 获取Appkey请前往控制台：https://nls-portal.console.aliyun.com/applist
-'''
-
-######################### 绘智 #########################
-ACCESS_KEY_ID = 'LTAI5tE4tgpGcKWhbZg6C4bh'
-ACCESS_KEY_SECRET = 'oizcTOZ8izbGUouboC00RcmGE8vBQ1'
-BUCKET_NAME = 'hzkc'
-ENDPOINT = 'https://oss-cn-beijing.aliyuncs.com'
-OSS_PREFIX = "https://hzkc.oss-cn-beijing.aliyuncs.com/"
-REGION_ID = 'cn-beijing'
-
-# 阿里云中用来调用 deepseek v3 的密钥
-# https://bailian.console.aliyun.com/?spm=a2c4g.11186623.0.0.77b17980FcMVYv&apiKey=1#/api-key
-MODEL_API_KEY = "sk-01d13a39e09844038322108ecdbd1bbc"
-##MODEL_NAME = "qwen-plus"
-MODEL_NAME = "deepseek-v3"
-
-# TTS的APPKEY
-# 获取Appkey请前往控制台：https://nls-portal.console.aliyun.com/applist
-APPKEY = "CBeQJK7KbjpQXrFZ"
-# ----------------------------------------------------------------------
-
-# 魔搭社区黄海的令牌
-# https://modelscope.cn/my/myaccesstoken
-# 18686619970
-MODELSCOPE_ACCESS_TOKEN = '9b486dc5-28a3-4793-bb2c-0123c72a214f'

dsRag/Milvus/X1_create_collection.py

@@ -4,7 +4,7 @@ pip install pymilvus gensim
 
 from pymilvus import FieldSchema, DataType, utility
 
-from Milvus.Config.MulvusConfig import MS_HOST, MS_PORT, MS_MAX_CONNECTIONS, MS_COLLECTION_NAME, MS_DIMENSION
+from Config.Config import MS_HOST, MS_PORT, MS_MAX_CONNECTIONS, MS_COLLECTION_NAME, MS_DIMENSION
 from Milvus.Utils.MilvusCollectionManager import MilvusCollectionManager
 from Milvus.Utils.MilvusConnectionPool import *
 

dsRag/Milvus/X2_create_index.py

@@ -1,6 +1,6 @@
 from Milvus.Utils.MilvusCollectionManager import MilvusCollectionManager
 from Milvus.Utils.MilvusConnectionPool import *
-from Milvus.Config.MulvusConfig import *
+from Config.Config import *
 
 # 1. 使用连接池管理 Milvus 连接
 milvus_pool = MilvusConnectionPool(host=MS_HOST, port=MS_PORT, max_connections=MS_MAX_CONNECTIONS)

dsRag/Milvus/X4_InsertMathData.py

@@ -1,4 +1,4 @@
-from Milvus.Config.MulvusConfig import *
+from Config.Config import *
 from Milvus.Utils.MilvusCollectionManager import MilvusCollectionManager
 from Milvus.Utils.MilvusConnectionPool import *
 from gensim.models import KeyedVectors

dsRag/Milvus/X5_select_all_data.py

@@ -1,6 +1,6 @@
 from Milvus.Utils.MilvusCollectionManager import MilvusCollectionManager
 from Milvus.Utils.MilvusConnectionPool import *
-from Milvus.Config.MulvusConfig import *
+from Config.Config import *
 
 # 1. 使用连接池管理 Milvus 连接
 milvus_pool = MilvusConnectionPool(host=MS_HOST, port=MS_PORT, max_connections=MS_MAX_CONNECTIONS)

dsRag/Milvus/X6_search_near_data.py

@@ -2,7 +2,7 @@ import time
 import jieba  # 导入 jieba 分词库
 from Milvus.Utils.MilvusCollectionManager import MilvusCollectionManager
 from Milvus.Utils.MilvusConnectionPool import *
-from Milvus.Config.MulvusConfig import *
+from Config.Config import *
 from gensim.models import KeyedVectors
 
 # 1. 加载预训练的 Word2Vec 模型