From b301244bd6e2f0775b434ef391a862612a28389e Mon Sep 17 00:00:00 2001 From: sunxiqing <2240398334@qq.com> Date: Thu, 18 Sep 2025 14:46:09 +0800 Subject: [PATCH] =?UTF-8?q?```=20refactor(config):=20=E6=9B=B4=E6=96=B0?= =?UTF-8?q?=E6=95=B0=E6=8D=AE=E5=BA=93=E8=BF=9E=E6=8E=A5=E5=92=8CAPI?= =?UTF-8?q?=E5=9C=B0=E5=9D=80=E9=85=8D=E7=BD=AE?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 将Druid连接池的最大连接数从20增加到50，并更新了主从数据库的URL、用户名和密码。同时，更新了多个后端服务的API地址，包括RAG服务、LLM训练和服务API、大模型管理API等，以指向新的服务器地址。``` --- .../src/main/resources/application-local.yaml | 85 ++++++++++--------- 1 file changed, 43 insertions(+), 42 deletions(-) diff --git a/yudao-server/src/main/resources/application-local.yaml b/yudao-server/src/main/resources/application-local.yaml index 7012b7f92..9c2810514 100644 --- a/yudao-server/src/main/resources/application-local.yaml +++ b/yudao-server/src/main/resources/application-local.yaml @@ -34,7 +34,7 @@ spring: druid: # Druid 【连接池】相关的全局配置 initial-size: 1 # 初始连接数 min-idle: 1 # 最小连接池数量 - max-active: 20 # 最大连接池数量 + max-active: 50 # 最大连接池数量 max-wait: 600000 # 配置获取连接等待超时的时间，单位：毫秒 time-between-eviction-runs-millis: 60000 # 配置间隔多久才进行一次检测，检测需要关闭的空闲连接，单位：毫秒 min-evictable-idle-time-millis: 300000 # 配置一个连接在池中最小生存的时间，单位：毫秒 @@ -46,14 +46,14 @@ spring: primary: master datasource: master: - url: jdbc:mysql://119.3.223.215:3306/xhllm?useSSL=false&serverTimezone=Asia/Shanghai&allowPublicKeyRetrieval=true&nullCatalogMeansCurrent=true&rewriteBatchedStatements=true # MySQL Connector/J 8.X 连接的示例 - username: xhllm_user - password: XNJZ-xhllm_user-!#%246 + url: jdbc:mysql://221.238.217.216:4156/ruoyi-vue-pro?useSSL=false&serverTimezone=Asia/Shanghai&allowPublicKeyRetrieval=true&nullCatalogMeansCurrent=true&rewriteBatchedStatements=true # MySQL Connector/J 8.X 连接的示例 + username: root + password: 123456 slave: # 模拟从库，可根据自己需要修改 lazy: true # 开启懒加载，保证启动速度 - url: jdbc:mysql://119.3.223.215:3306/xhllm?useSSL=false&serverTimezone=Asia/Shanghai&allowPublicKeyRetrieval=true&rewriteBatchedStatements=true&nullCatalogMeansCurrent=true - username: xhllm_user - password: XNJZ-xhllm_user-!#%246 + url: jdbc:mysql://221.238.217.216:4156/ruoyi-vue-pro?useSSL=false&serverTimezone=Asia/Shanghai&allowPublicKeyRetrieval=true&rewriteBatchedStatements=true&nullCatalogMeansCurrent=true + username: root + password: 123456 # Redis 配置。Redisson 默认的配置足够使用，一般不需要进行调优 redis: @@ -248,57 +248,58 @@ llm: backend: #################### 8123: RAG服务、训练集和标注相关API。 ################### ### RAG服务 + request_address: http://221.238.217.216:4143 #RAG健康检查 GET - rag_health: http://36.103.199.248:8123/health + rag_health: http://221.238.217.216:4142/health #上传并向量化 POST - rag_embed: http://36.103.199.248:8123/embed + rag_embed: http://221.238.217.216:4142/embed #获取所有向量id GET - rag_ids: http://36.103.199.248:8123/ids + rag_ids: http://221.238.217.216:4142/ids #根据id获取文档 GET - rag_documents: http://36.103.199.248:8123/documents + rag_documents: http://221.238.217.216:4142/documents #根据id删除文档 DEL - rag_documents_del: http://36.103.199.248:8123/documents + rag_documents_del: http://221.238.217.216:4142/documents #根据file_id检索向量 POST - rag_query: http://36.103.199.248:8123/query + rag_query: http://221.238.217.216:4142/query #支持多个文件id查询向量 GET - rag_query_multiple: http://36.103.199.248:8123/query_multiple + rag_query_multiple: http://221.238.217.216:4142/query_multiple # 知识库向量嵌入 - embed: http://36.103.199.248:8123/embed + embed: http://221.238.217.216:4142/embed # 知识库查询 - embed_query: http://36.103.199.248:8123/query + embed_query: http://221.238.217.216:4142/query #### LLM train and service api 训练集、标注相关API # 训练集列表 GET - dataset_list: http://localhost:8123/api/mgr/datasets/list + dataset_list: http://221.238.217.216:4142/api/mgr/datasets/list # 上传训练集 POST - dataset_create: http://localhost:8123/api/mgr/datasets/create + dataset_create: http://221.238.217.216:4142/api/mgr/datasets/create # 删除训练集 DELETE - dataset_delete: http://localhost:8123/api/mgr/datasets/ + dataset_delete: http://221.238.217.216:4142/api/mgr/datasets/ # 训练集标注 GET - annotation_task_list: http://localhost:8123/api/mgr/annotation/task/list + annotation_task_list: http://221.238.217.216:4142/api/mgr/annotation/task/list # 标注信息 GET - annotation_task: http://localhost:8123/api/mgr/annotation/task + annotation_task: http://221.238.217.216:4142/api/mgr/annotation/task # 保存标注 POST - annotation_task_save: http://localhost:8123/api/mgr/annotation/task/task-6025001b-692c-44a1-9bc7-2a34bd7c0efe/segment/das-2eedd7bf-3770-4816-a961-b30c446b7a4f/mark + annotation_task_save: http://221.238.217.216:4142/api/mgr/annotation/task/task-6025001b-692c-44a1-9bc7-2a34bd7c0efe/segment/das-2eedd7bf-3770-4816-a961-b30c446b7a4f/mark #################### 9000: 大模型管理、微调任务、文件上传和模型部署相关API。 ################### # 大模型列表 GET - models_list: http://36.103.199.248:9000/api/models + models_list: http://221.238.217.216:9000/api/models # 登录 POST - login: http://36.103.199.248:9000/api/auth/login - account: http://36.103.199.248:9000/api/auth/account + login: http://221.238.217.216:9000/api/auth/login + account: http://221.238.217.216:9000/api/auth/account login_username: admin login_password: admin # 微调任务详情 GET - finetuning_detail: http://36.103.199.248:9000/api/finetuning + finetuning_detail: http://221.238.217.216:9000/api/finetuning # 微调任务取消 - finetuning_cancel: http://36.103.199.248:9000/api/finetuning/%s/cancel + finetuning_cancel: http://221.238.217.216:9000/api/finetuning/%s/cancel # 微调文件列表 GET - finetuning_file_list: http://36.103.199.248:9000/api/files?purpose=fine-tune + finetuning_file_list: http://221.238.217.216:9000/api/files?purpose=fine-tune # 模型部署 - model_create: http://36.103.199.248:9000/api/models + model_create: http://221.238.217.216:9000/api/models # aigc模型推理 - aigc_model_completions: http://36.103.199.248:9000/api/channels/chat/completions + aigc_model_completions: http://221.238.217.216:9000/api/channels/chat/completions #################### 5123: 微调任务、模型部署、文件管理、提示词优化、自动评估、文生图等API。 ################### @@ -319,41 +320,41 @@ llm: # 模型文件下载 model_file_download: /models/download/?file_path= # 提示词优化 - optimize_prompt: http://36.103.199.248:5123/optimize-prompt + optimize_prompt: http://221.238.217.216:4143/optimize-prompt # 自动评估 auto_evaluation: /llm-eval # 文生图 - text_to_image: http://36.103.199.248:5123/generate-image + text_to_image: http://221.238.217.216:4143/generate-image # 检查点文件列表 check_file_list: /llm/finetuning/checkpoints?model_name= # 模型调优停止 POST stop_finetuning: /llm/finetuning/stop # 基座模型状态 POST - base_model_status: http://36.103.199.248:5123/llm/deploy/list + base_model_status: http://221.238.217.216:4143/llm/deploy/list # 模型部署 POST - deploy_model: http://36.103.199.248:5123/llm/deploy + deploy_model: http://221.238.217.216:4143/llm/deploy # 模型删除 - delete_model: http://36.103.199.248:5123/llm/deploy/stop + delete_model: http://221.238.217.216:4143/llm/deploy/stop # 模型列表 get - a_list_of_available_models: http://36.103.199.248:5123/llm/list + a_list_of_available_models: http://221.238.217.216:4143/llm/list #删除模型 delete_the_model: /delete_model - delete_the_model_full: http://36.103.199.248:5123/delete_model + delete_the_model_full: http://221.238.217.216:4143/delete_model # 知识库分块文件 - knowledgeBaseChunkedFiles : http:/36.103.199.248:8123/documents + knowledgeBaseChunkedFiles : http:/221.238.217.216:4142/documents #################### 30000: 大模型对话相关API。 ################### #### 大模型对话 # 模型列表 GET - base_model_list: http://36.103.199.248:30000/model/v1/models + base_model_list: http://221.238.217.216:30000/model/v1/models # 模型对话 POST - model_completions: http://36.103.199.248:30000/v1/chat/completions + model_completions: http://221.238.217.216:30000/v1/chat/completions #################### 48080: 应用和管理服务相关API。 ################### - application_api: http://localhost:48080/admin-api/llm/application/api/apiKey/chat + application_api: http://221.238.217.216:48080/admin-api/llm/application/api/apiKey/chat - model_service_api: http://localhost:48080/admin-api/llm/model-service/api/apiKey/chat + model_service_api: http://221.238.217.216:48080/admin-api/llm/model-service/api/apiKey/chat --- #################### iot相关配置 TODO 芋艿：再瞅瞅 ####################