Initial commit: Add AI tagging images project files

2026-02-04 11:12:34 +08:00
parent 1697372b46
commit a6f203a3e3
15 changed files with 1868 additions and 406 deletions
--- a/.gitignore
+++ b/.gitignore
@@ -3,21 +3,45 @@ __pycache__/
 *.py[cod]
 *$py.class
 *.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg

-# Virtual environment
+# Virtual Environment
 venv/
 env/
-.venv/
+ENV/

 # IDE
-.idea/
 .vscode/
+.idea/
 *.swp
 *.swo

-# Logs
-*.log
-
 # OS
 .DS_Store
 Thumbs.db
+
+# Logs
+*.log
+logs/
+
+# Data files
+*.json  # Except specific ones we want to track
+backup_data.json  # Track this specific json file
+
+# Local config
+config/local_settings.py
--- a/1.png
+++ b/1.png
--- a/ai_article.sql
+++ b/ai_article.sql
@@ -11,7 +11,7 @@
 Target Server Version : 90001 (9.0.1)
 File Encoding         : 65001

- Date: 28/01/2026 14:04:39
+ Date: 02/02/2026 16:34:15
 */

 SET NAMES utf8mb4;
@@ -41,7 +41,7 @@ CREATE TABLE `ai_article_images`  (
  INDEX `image_id`(`image_id` ASC) USING BTREE,
  INDEX `idx_tag_article_lookup`(`image_tag_id` ASC, `article_id` ASC) USING BTREE,
  INDEX `idx_article_images_article_tag`(`article_id` ASC, `image_tag_id` ASC) USING BTREE
-) ENGINE = InnoDB AUTO_INCREMENT = 699 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = DYNAMIC;
+) ENGINE = InnoDB AUTO_INCREMENT = 700 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = DYNAMIC;

 -- ----------------------------
 -- Table structure for ai_article_tags
@@ -111,7 +111,7 @@ CREATE TABLE `ai_articles`  (
  CONSTRAINT `ai_articles_ibfk_2` FOREIGN KEY (`created_user_id`) REFERENCES `ai_users` (`id`) ON DELETE RESTRICT ON UPDATE RESTRICT,
  CONSTRAINT `ai_articles_ibfk_3` FOREIGN KEY (`review_user_id`) REFERENCES `ai_users` (`id`) ON DELETE RESTRICT ON UPDATE RESTRICT,
  CONSTRAINT `ai_articles_ibfk_4` FOREIGN KEY (`publish_user_id`) REFERENCES `ai_users` (`id`) ON DELETE RESTRICT ON UPDATE RESTRICT
-) ENGINE = InnoDB AUTO_INCREMENT = 1180 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;
+) ENGINE = InnoDB AUTO_INCREMENT = 1350 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;

 -- ----------------------------
 -- Table structure for ai_authors
@@ -178,6 +178,25 @@ CREATE TABLE `ai_batch_uploads`  (
  CONSTRAINT `ai_batch_uploads_ibfk_1` FOREIGN KEY (`user_id`) REFERENCES `ai_users` (`id`) ON DELETE RESTRICT ON UPDATE RESTRICT
 ) ENGINE = InnoDB AUTO_INCREMENT = 101 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;

+-- ----------------------------
+-- Table structure for ai_department_config
+-- ----------------------------
+DROP TABLE IF EXISTS `ai_department_config`;
+CREATE TABLE `ai_department_config`  (
+  `id` int UNSIGNED NOT NULL AUTO_INCREMENT COMMENT '主键ID',
+  `department_name` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL COMMENT '科室名称',
+  `department_code` varchar(20) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL COMMENT '科室编码',
+  `keywords` text CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL COMMENT '关联关键词（JSON数组）',
+  `priority` int NOT NULL DEFAULT 0 COMMENT '优先级',
+  `status` tinyint NOT NULL DEFAULT 1 COMMENT '状态：0-禁用，1-启用',
+  `remark` varchar(500) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NULL DEFAULT NULL COMMENT '备注',
+  `create_time` datetime NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间',
+  `update_time` datetime NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '更新时间',
+  PRIMARY KEY (`id`) USING BTREE,
+  UNIQUE INDEX `uk_department_code`(`department_code` ASC) USING BTREE,
+  INDEX `idx_status`(`status` ASC) USING BTREE
+) ENGINE = InnoDB AUTO_INCREMENT = 3 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_unicode_ci COMMENT = '科室标签配置表' ROW_FORMAT = Dynamic;
+
 -- ----------------------------
 -- Table structure for ai_departments
 -- ----------------------------
@@ -218,8 +237,11 @@ CREATE TABLE `ai_image_tags`  (
  `created_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP,
  `updated_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
  `image_attached_article_count` int NOT NULL DEFAULT 0 COMMENT 'Number of articles the image is attached to',
-  `status` enum('draft','ready','doing','failed','finished','duplicates','calc_similarity','similarity','hit_yellow','automated_review','automated_review_failed','manual_review','manual_review_failed','published','published_failed') CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NOT NULL DEFAULT 'draft' COMMENT '图片完整扭转流程状态',
+  `status` enum('draft','ready','doing','failed','finished','duplicates','calc_similarity','similarity','tag_extension','hit_yellow','automated_review','automated_review_failed','manual_review','manual_review_failed','generate_review','generate','generate_failed','published','published_failed') CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NOT NULL DEFAULT 'draft' COMMENT '图片完整扭转流程状态',
  `blocking_reason` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NOT NULL DEFAULT '' COMMENT '审核不通过原因',
+  `similarity` enum('draft','yes','calc','recalc') CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NOT NULL DEFAULT 'draft' COMMENT 'yes=是相似|calc=已计算|recalc=需要重新计算',
+  `similarity_image_tags_id` int NOT NULL DEFAULT 0 COMMENT 'yes=是相似|把image_tags_id写入',
+  `similarity score` float NOT NULL DEFAULT 0 COMMENT '相似时候，计算相似度值',
  PRIMARY KEY (`id`) USING BTREE,
  UNIQUE INDEX `uk_image_tag`(`image_id` ASC, `tag_id` ASC) USING BTREE,
  INDEX `tag_id`(`tag_id` ASC) USING BTREE,
@@ -237,7 +259,7 @@ CREATE TABLE `ai_image_tags`  (
  INDEX `idx_tag_name_id`(`tag_name` ASC, `id` ASC) USING BTREE,
  INDEX `idx_tag_notnull_id`(`id` ASC, `tag_name` ASC, `image_id` ASC, `created_at` ASC) USING BTREE,
  CONSTRAINT `ai_image_tags_ibfk_2` FOREIGN KEY (`tag_id`) REFERENCES `ai_tags` (`id`) ON DELETE CASCADE ON UPDATE RESTRICT
-) ENGINE = InnoDB AUTO_INCREMENT = 929767 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;
+) ENGINE = InnoDB AUTO_INCREMENT = 929784 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;

 -- ----------------------------
 -- Table structure for ai_images
@@ -263,7 +285,7 @@ CREATE TABLE `ai_images`  (
  INDEX `upload_user_id`(`upload_user_id` ASC) USING BTREE,
  INDEX `idx_status_updated`(`status` ASC, `updated_at` ASC) USING BTREE,
  CONSTRAINT `ai_images_ibfk_1` FOREIGN KEY (`upload_user_id`) REFERENCES `ai_users` (`id`) ON DELETE RESTRICT ON UPDATE RESTRICT
-) ENGINE = InnoDB AUTO_INCREMENT = 26832 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;
+) ENGINE = InnoDB AUTO_INCREMENT = 26849 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;

 -- ----------------------------
 -- Table structure for ai_keywords
@@ -302,7 +324,7 @@ CREATE TABLE `ai_logs`  (
  INDEX `user_id`(`user_id` ASC) USING BTREE,
  INDEX `idx_created_at`(`created_at` DESC) USING BTREE,
  CONSTRAINT `ai_logs_ibfk_1` FOREIGN KEY (`user_id`) REFERENCES `ai_users` (`id`) ON DELETE RESTRICT ON UPDATE RESTRICT
-) ENGINE = InnoDB AUTO_INCREMENT = 116027 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;
+) ENGINE = InnoDB AUTO_INCREMENT = 116565 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;

 -- ----------------------------
 -- Table structure for ai_mip_click
@@ -412,7 +434,7 @@ CREATE TABLE `ai_mip_query_task`  (
  INDEX `idx_category`(`category` ASC) USING BTREE COMMENT '按分类查询',
  INDEX `idx_threshold`(`threshold_max` ASC, `current_count` ASC) USING BTREE COMMENT '阈值监控',
  INDEX `idx_closed`(`closed_at` ASC) USING BTREE COMMENT '关闭时间索引'
-) ENGINE = InnoDB AUTO_INCREMENT = 1 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci COMMENT = 'MIP查询任务表 - 用于存储查询词抓取网址任务' ROW_FORMAT = DYNAMIC;
+) ENGINE = InnoDB CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci COMMENT = 'MIP查询任务表 - 用于存储查询词抓取网址任务' ROW_FORMAT = DYNAMIC;

 -- ----------------------------
 -- Table structure for ai_mip_site
@@ -508,6 +530,61 @@ CREATE TABLE `ai_prompt_workflow`  (
  INDEX `idx_query_enable`(`query_enable` ASC) USING BTREE
 ) ENGINE = InnoDB AUTO_INCREMENT = 16 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;

+-- ----------------------------
+-- Table structure for ai_query_audit
+-- ----------------------------
+DROP TABLE IF EXISTS `ai_query_audit`;
+CREATE TABLE `ai_query_audit`  (
+  `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT COMMENT '主键ID',
+  `query_text` text CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL COMMENT 'Query原文',
+  `query_hash` varchar(64) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL COMMENT 'Query MD5哈希值，用于去重',
+  `query_status` tinyint NOT NULL DEFAULT 0 COMMENT 'Query状态：0-待审核，1-已过滤（黑名单），2-已通过，3-已拒绝，4-待人工审核',
+  `filter_reason` varchar(200) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NULL DEFAULT NULL COMMENT '过滤原因',
+  `matched_keywords` varchar(500) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NULL DEFAULT NULL COMMENT '命中的黑名单关键词（JSON数组）',
+  `department_tags` varchar(200) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NULL DEFAULT NULL COMMENT '科室标签（JSON数组）：影像科、CT等',
+  `batch_tag_result` text CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NULL COMMENT '批量打标签结果（JSON）',
+  `ai_score` decimal(5, 2) NULL DEFAULT NULL COMMENT 'AI评分',
+  `is_health_related` tinyint NULL DEFAULT NULL COMMENT '是否健康相关：0-否，1-是',
+  `is_complete_sentence` tinyint NULL DEFAULT NULL COMMENT '是否完整语句：0-否，1-是',
+  `has_person_name` tinyint NULL DEFAULT 0 COMMENT '是否包含人名：0-否，1-是',
+  `has_location` tinyint NULL DEFAULT 0 COMMENT '是否包含地名：0-否，1-是',
+  `has_hospital_name` tinyint NULL DEFAULT 0 COMMENT '是否包含医院名：0-否，1-是',
+  `source` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NULL DEFAULT NULL COMMENT '来源渠道',
+  `create_time` datetime NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间',
+  `update_time` datetime NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '更新时间',
+  PRIMARY KEY (`id`) USING BTREE,
+  UNIQUE INDEX `uk_query_hash`(`query_hash` ASC) USING BTREE,
+  INDEX `idx_query_status`(`query_status` ASC, `create_time` ASC) USING BTREE,
+  INDEX `idx_department_tags`(`department_tags`(100) ASC) USING BTREE,
+  INDEX `idx_create_time`(`create_time` ASC) USING BTREE
+) ENGINE = InnoDB CHARACTER SET = utf8mb4 COLLATE = utf8mb4_unicode_ci COMMENT = 'AI Query审核记录表' ROW_FORMAT = Dynamic;
+
+-- ----------------------------
+-- Table structure for ai_query_blacklist
+-- ----------------------------
+DROP TABLE IF EXISTS `ai_query_blacklist`;
+CREATE TABLE `ai_query_blacklist`  (
+  `id` bigint UNSIGNED NOT NULL AUTO_INCREMENT COMMENT '主键ID',
+  `keyword` varchar(100) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NOT NULL COMMENT '黑名单关键词',
+  `keyword_type` tinyint NOT NULL DEFAULT 1 COMMENT '关键词类型：1-通用词汇，2-人名，3-地名，4-医院名，5-其他',
+  `filter_rule` tinyint NOT NULL DEFAULT 1 COMMENT '过滤规则：1-包含即过滤，2-完全匹配，3-正则匹配',
+  `regex_pattern` varchar(200) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NULL DEFAULT NULL COMMENT '正则表达式（当filter_rule=3时使用）',
+  `category` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NULL DEFAULT NULL COMMENT '分类标签：药品、图片、费用等',
+  `priority` int NOT NULL DEFAULT 0 COMMENT '优先级，数值越大优先级越高',
+  `status` tinyint NOT NULL DEFAULT 1 COMMENT '状态：0-禁用，1-启用',
+  `remark` varchar(500) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NULL DEFAULT NULL COMMENT '备注说明',
+  `creator` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NULL DEFAULT NULL COMMENT '创建人',
+  `updater` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci NULL DEFAULT NULL COMMENT '更新人',
+  `create_time` datetime NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '创建时间',
+  `update_time` datetime NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '更新时间',
+  `is_deleted` tinyint NOT NULL DEFAULT 0 COMMENT '是否删除：0-未删除，1-已删除',
+  PRIMARY KEY (`id`) USING BTREE,
+  UNIQUE INDEX `uk_keyword`(`keyword` ASC, `is_deleted` ASC) USING BTREE,
+  INDEX `idx_keyword_type`(`keyword_type` ASC, `status` ASC) USING BTREE,
+  INDEX `idx_category`(`category` ASC, `status` ASC) USING BTREE,
+  INDEX `idx_create_time`(`create_time` ASC) USING BTREE
+) ENGINE = InnoDB AUTO_INCREMENT = 66 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_unicode_ci COMMENT = 'AI查询黑名单词表' ROW_FORMAT = Dynamic;
+
 -- ----------------------------
 -- Table structure for ai_query_category
 -- ----------------------------
@@ -700,7 +777,7 @@ CREATE TABLE `ai_tag_subsets`  (
  PRIMARY KEY (`id`) USING BTREE,
  INDEX `parent_tag_id`(`parent_tag_id` ASC) USING BTREE,
  CONSTRAINT `ai_tag_subsets_ibfk_1` FOREIGN KEY (`parent_tag_id`) REFERENCES `ai_tags` (`id`) ON DELETE CASCADE ON UPDATE RESTRICT
-) ENGINE = InnoDB AUTO_INCREMENT = 20478 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;
+) ENGINE = InnoDB AUTO_INCREMENT = 20495 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;

 -- ----------------------------
 -- Table structure for ai_tags
@@ -719,7 +796,7 @@ CREATE TABLE `ai_tags`  (
  PRIMARY KEY (`id`) USING BTREE,
  UNIQUE INDEX `uk_tag_name`(`tag_name` ASC) USING BTREE,
  INDEX `idx_status_updated`(`status` ASC, `updated_at` ASC) USING BTREE
-) ENGINE = InnoDB AUTO_INCREMENT = 13417 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;
+) ENGINE = InnoDB AUTO_INCREMENT = 13434 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_general_ci ROW_FORMAT = Dynamic;

 -- ----------------------------
 -- Table structure for ai_topic_type
@@ -810,7 +887,7 @@ CREATE TABLE `ai_users`  (
  `phone` varchar(20) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL,
  `xhs_cookie` text CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL COMMENT '小红书Cookie',
  `department` varchar(50) CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT NULL,
-  `role` enum('admin','editor','reviewer','publisher','each_title_reviewer','reviewer_query') CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NOT NULL DEFAULT 'editor' COMMENT '用户角色',
+  `role` enum('admin','editor','reviewer','publisher','each_title_reviewer','reviewer_query','reviewer_image') CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NOT NULL DEFAULT 'editor' COMMENT '用户角色',
  `status` enum('active','inactive','deleted') CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT 'active',
  `created_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP,
  `updated_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
@@ -848,7 +925,7 @@ CREATE TABLE `baidu_keyword`  (
  `blocking_reason` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NOT NULL DEFAULT '' COMMENT '审核不通过原因',
  `article_id` int NOT NULL DEFAULT 0 COMMENT '文章ID',
  `query_stage` enum('draft','created','summary','reviewed','generated','published') CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NOT NULL DEFAULT 'draft' COMMENT '分5个阶段，创建|总结|审核|生文|发布',
-  `query_status` enum('draft','ready','doing','failed','finished','duplicates','calc_similarity','similarity','hit_yellow','automated_review','automated_review_failed','manual_review','manual_review_failed','generate_review','generate','published','published_failed') CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT 'draft' COMMENT 'query完整扭转流程状态',
+  `query_status` enum('draft','ready','doing','failed','finished','duplicates','calc_similarity','similarity','hit_yellow','automated_review','automated_review_failed','manual_review','manual_review_failed','generate_review','generate','generate_failed','published','published_failed') CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT 'draft' COMMENT 'query完整扭转流程状态',
  `status` enum('draft','available','unavailable','successful','failed') CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NOT NULL DEFAULT 'draft' COMMENT '状态_分2个阶段|可用|不可用|发布成功|发布失败',
  `updated_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
  `review_user_id` int NOT NULL DEFAULT 0 COMMENT '审核用户ID',
@@ -857,6 +934,8 @@ CREATE TABLE `baidu_keyword`  (
  `similarity_query_keyword` varchar(255) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NOT NULL DEFAULT '' COMMENT 'yes=是相似|把query写入',
  `similarity score` float NOT NULL DEFAULT 0 COMMENT '相似时候，计算相似度值',
  `reviewed_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP COMMENT '审核日期',
+  `fast_track` tinyint(1) NOT NULL DEFAULT 0 COMMENT '加急|0=否|1=是',
+  `automated_review_failed_reason` varchar(64) CHARACTER SET utf8mb4 COLLATE utf8mb4_0900_ai_ci NOT NULL DEFAULT '' COMMENT '千问大模型审核query不符合原因',
  PRIMARY KEY (`id`) USING BTREE,
  UNIQUE INDEX `keyword`(`keyword` ASC) USING BTREE,
  INDEX `idx_crawled_seed`(`crawled` ASC, `seed_id` ASC) USING BTREE,
@@ -881,8 +960,9 @@ CREATE TABLE `baidu_keyword`  (
  INDEX `idx_query_status_cover`(`query_status` ASC) USING BTREE,
  INDEX `idx_query_status_id_asc`(`query_status` ASC, `id` ASC) USING BTREE,
  INDEX `idx_status_order_covering`(`query_status` ASC, `id` ASC, `keyword` ASC) USING BTREE,
+  INDEX `idx_status_fast_id_keyword`(`query_status` ASC, `fast_track` ASC, `id` ASC, `keyword` ASC) USING BTREE,
  FULLTEXT INDEX `idx_keyword_fulltext`(`keyword`)
-) ENGINE = InnoDB AUTO_INCREMENT = 901728 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci ROW_FORMAT = Dynamic;
+) ENGINE = InnoDB AUTO_INCREMENT = 901869 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci ROW_FORMAT = Dynamic;

 -- ----------------------------
 -- Table structure for baidu_query_task
@@ -922,9 +1002,14 @@ CREATE TABLE `baidu_seed_keywords`  (
  `status` enum('ready','doing','failed','finished') CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci NULL DEFAULT 'ready',
  `updated_at` timestamp NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
  `priority_weight` int NOT NULL DEFAULT 0 COMMENT '优先级和权重1~10000|更高的先处理',
+  `fast_track` tinyint(1) NOT NULL DEFAULT 0 COMMENT '加急|0=否|1=是',
  PRIMARY KEY (`id`) USING BTREE,
  UNIQUE INDEX `keyword`(`keyword` ASC) USING BTREE,
-  INDEX `idx_crawled_priority`(`crawled` ASC, `priority_weight` DESC) USING BTREE
-) ENGINE = InnoDB AUTO_INCREMENT = 48 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci ROW_FORMAT = DYNAMIC;
+  INDEX `idx_crawled_priority`(`crawled` ASC, `priority_weight` DESC) USING BTREE,
+  INDEX `idx_fast_track`(`fast_track` ASC) USING BTREE,
+  INDEX `idx_crawled_fast_weight`(`crawled` ASC, `fast_track` ASC, `priority_weight` DESC) USING BTREE,
+  INDEX `idx_crawled_fast_weight_covering`(`crawled` ASC, `fast_track` ASC, `priority_weight` DESC, `keyword` ASC, `id` ASC) USING BTREE,
+  INDEX `idx_crawled_fast_priority`(`crawled` ASC, `fast_track` ASC, `priority_weight` DESC, `id` ASC, `keyword` ASC) USING BTREE
+) ENGINE = InnoDB AUTO_INCREMENT = 100001 CHARACTER SET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci ROW_FORMAT = DYNAMIC;

 SET FOREIGN_KEY_CHECKS = 1;
--- a/ai_tags.txt
+++ b/ai_tags.txt
@@ -0,0 +1,9 @@
+12679
+#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#
+NULL
+妇科
+NULL
+0
+active
+2025-08-16 21:48:16
+2025-08-16 21:48:16
--- a/backup_data.json
+++ b/backup_data.json
@@ -0,0 +1,642 @@
+{
+  "ai_tags": [
+    {
+      "id": 12679,
+      "tag_name": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+      "tag_category": null,
+      "department": "妇科",
+      "description": null,
+      "usage_count": 0,
+      "status": "active",
+      "created_at": "2025-08-16T21:48:16",
+      "updated_at": "2025-08-16T21:48:16"
+    }
+  ],
+  "ai_image_tags": [
+    {
+      "id": 16495,
+      "image_id": 19346,
+      "image_name": "1755312359566253.png",
+      "image_url": "20250816/1755312359566253.png",
+      "image_thumb_url": "20250816/1755312359566253_thumb.png",
+      "tag_id": 12679,
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+      "image_source": 1,
+      "created_user_id": 0,
+      "created_at": "2025-08-16T21:48:16",
+      "updated_at": "2026-01-30T14:32:36",
+      "image_attached_article_count": 173,
+      "status": "draft",
+      "blocking_reason": "",
+      "similarity": "draft",
+      "similarity_image_tags_id": 0,
+      "similarity score": 0.0
+    },
+    {
+      "id": 16516,
+      "image_id": 19367,
+      "image_name": "1755312448884355.png",
+      "image_url": "20250816/1755312448884355.png",
+      "image_thumb_url": "20250816/1755312448884355_thumb.png",
+      "tag_id": 12679,
+      "tag_name": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+      "default_tag_id": 0,
+      "default_tag_name": "",
+      "keywords_id": 265,
+      "keywords_name": "废止",
+      "department_id": 11,
+      "department_name": "妇科",
+      "image_source": 1,
+      "created_user_id": 0,
+      "created_at": "2025-08-16T21:48:16",
+      "updated_at": "2026-01-30T14:33:14",
+      "image_attached_article_count": 111,
+      "status": "draft",
+      "blocking_reason": "",
+      "similarity": "draft",
+      "similarity_image_tags_id": 0,
+      "similarity score": 0.0
+    },
+    {
+      "id": 16517,
+      "image_id": 19368,
+      "image_name": "1755312451681906.png",
+      "image_url": "20250816/1755312451681906.png",
+      "image_thumb_url": "20250816/1755312451681906_thumb.png",
+      "tag_id": 12679,
+      "tag_name": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+      "default_tag_id": 0,
+      "default_tag_name": "",
+      "keywords_id": 265,
+      "keywords_name": "废止",
+      "department_id": 11,
+      "department_name": "妇科",
+      "image_source": 1,
+      "created_user_id": 0,
+      "created_at": "2025-08-16T21:48:16",
+      "updated_at": "2026-01-30T14:33:29",
+      "image_attached_article_count": 94,
+      "status": "draft",
+      "blocking_reason": "",
+      "similarity": "draft",
+      "similarity_image_tags_id": 0,
+      "similarity score": 0.0
+    },
+    {
+      "id": 16518,
+      "image_id": 19369,
+      "image_name": "1755312453351689.png",
+      "image_url": "20250816/1755312453351689.png",
+      "image_thumb_url": "20250816/1755312453351689_thumb.png",
+      "tag_id": 12679,
+      "tag_name": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+      "default_tag_id": 0,
+      "default_tag_name": "",
+      "keywords_id": 265,
+      "keywords_name": "废止",
+      "department_id": 11,
+      "department_name": "妇科",
+      "image_source": 1,
+      "created_user_id": 0,
+      "created_at": "2025-08-16T21:48:16",
+      "updated_at": "2026-01-30T14:33:24",
+      "image_attached_article_count": 100,
+      "status": "draft",
+      "blocking_reason": "",
+      "similarity": "draft",
+      "similarity_image_tags_id": 0,
+      "similarity score": 0.0
+    },
+    {
+      "id": 16519,
+      "image_id": 19370,
+      "image_name": "1755312456284588.png",
+      "image_url": "20250816/1755312456284588.png",
+      "image_thumb_url": "20250816/1755312456284588_thumb.png",
+      "tag_id": 12679,
+      "tag_name": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+      "default_tag_id": 0,
+      "default_tag_name": "",
+      "keywords_id": 265,
+      "keywords_name": "废止",
+      "department_id": 11,
+      "department_name": "妇科",
+      "image_source": 1,
+      "created_user_id": 0,
+      "created_at": "2025-08-16T21:48:16",
+      "updated_at": "2026-01-30T14:33:09",
+      "image_attached_article_count": 118,
+      "status": "draft",
+      "blocking_reason": "",
+      "similarity": "draft",
+      "similarity_image_tags_id": 0,
+      "similarity score": 0.0
+    }
+  ]
+}
--- a/config/settings.py
+++ b/config/settings.py
@@ -35,7 +35,8 @@ class QwenConfig:
@dataclass
 class TagDeriveConfig:
    """标签衍生配置"""
-    batch_size: int = 3                     # 每批处理图片数
+    batch_size: int = 50                    # 每批次从数据库读取的图片数量
+    concurrency: int = 10                   # 并发请求数（同时发出的API请求数）
    min_derived_tags: int = 5               # 最少衍生标签数
    max_derived_tags: int = 10              # 最多衍生标签数
    max_tag_length: int = 10                # 单个标签最大长度
@@ -86,6 +87,7 @@ class Settings:
        
        # 标签衍生配置
        settings.tag_derive.batch_size = int(os.getenv("BATCH_SIZE", settings.tag_derive.batch_size))
+        settings.tag_derive.concurrency = int(os.getenv("CONCURRENCY", settings.tag_derive.concurrency))
        settings.tag_derive.min_derived_tags = int(os.getenv("MIN_DERIVED_TAGS", settings.tag_derive.min_derived_tags))
        settings.tag_derive.max_derived_tags = int(os.getenv("MAX_DERIVED_TAGS", settings.tag_derive.max_derived_tags))
        settings.tag_derive.image_cdn_base = os.getenv("IMAGE_CDN_BASE", settings.tag_derive.image_cdn_base)
--- a/derive_results.json
+++ b/derive_results.json
@@ -1,4 +1,140 @@
 [
+  {
+    "success": true,
+    "image_id": 16495,
+    "original_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+    "derived_tags": [
+      "阴道炎",
+      "白带异常",
+      "妇科感染",
+      "盆腔炎",
+      "宫颈炎",
+      "分泌物增多",
+      "抗炎治疗",
+      "妇科检查"
+    ],
+    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##阴道炎##白带异常##妇科感染##盆腔炎#",
+    "new_tag_id": 13434
+  },
+  {
+    "success": true,
+    "image_id": 16508,
+    "original_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+    "derived_tags": [
+      "阴道炎",
+      "宫颈炎",
+      "盆腔炎",
+      "白带异常",
+      "外阴瘙痒",
+      "妇科检查",
+      "抗炎治疗",
+      "女性健康"
+    ],
+    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##阴道炎##宫颈炎##盆腔炎##白带异常#",
+    "new_tag_id": 13435
+  },
+  {
+    "success": true,
+    "image_id": 16506,
+    "original_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+    "derived_tags": [
+      "阴道炎",
+      "盆腔炎",
+      "白带异常",
+      "妇科检查",
+      "抗生素治疗",
+      "私处护理",
+      "月经不调",
+      "感染预防"
+    ],
+    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##阴道炎##盆腔炎##白带异常##妇科检查#",
+    "new_tag_id": 13436
+  },
+  {
+    "success": true,
+    "image_id": 16503,
+    "original_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+    "derived_tags": [
+      "阴道炎",
+      "宫颈炎",
+      "盆腔炎",
+      "白带异常",
+      "外阴瘙痒",
+      "妇科感染",
+      "炎症治疗",
+      "妇科疾病"
+    ],
+    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##阴道炎##宫颈炎##盆腔炎##白带异常#",
+    "new_tag_id": 13435
+  },
+  {
+    "success": true,
+    "image_id": 16515,
+    "original_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+    "derived_tags": [
+      "妇科疾病",
+      "阴道炎",
+      "盆腔炎",
+      "白带异常",
+      "月经不调",
+      "抗炎治疗",
+      "个人卫生",
+      "免疫力"
+    ],
+    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##妇科疾病##阴道炎##盆腔炎##白带异常#",
+    "new_tag_id": 13437
+  },
+  {
+    "success": true,
+    "image_id": 16512,
+    "original_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+    "derived_tags": [
+      "阴道炎",
+      "盆腔炎",
+      "白带异常",
+      "月经不调",
+      "抗生素治疗",
+      "妇科检查",
+      "免疫力下降",
+      "激素变化"
+    ],
+    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##阴道炎##盆腔炎##白带异常##月经不调#",
+    "new_tag_id": 13438
+  },
+  {
+    "success": true,
+    "image_id": 16514,
+    "original_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+    "derived_tags": [
+      "妇科疾病",
+      "阴道炎",
+      "盆腔炎",
+      "白带异常",
+      "抗生素治疗",
+      "个人卫生",
+      "免疫力下降",
+      "月经不调"
+    ],
+    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##妇科疾病##阴道炎##盆腔炎##白带异常#",
+    "new_tag_id": 13437
+  },
+  {
+    "success": true,
+    "image_id": 16513,
+    "original_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+    "derived_tags": [
+      "阴道炎",
+      "宫颈炎",
+      "盆腔炎",
+      "白带异常",
+      "瘙痒",
+      "抗生素治疗",
+      "个人卫生",
+      "妇科检查"
+    ],
+    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##阴道炎##宫颈炎##盆腔炎##白带异常#",
+    "new_tag_id": 13435
+  },
  {
    "success": true,
    "image_id": 16496,
@@ -7,47 +143,64 @@
      "阴道炎",
      "宫颈炎",
      "盆腔炎",
-      "感染因素",
-      "个人卫生",
+      "白带异常",
      "抗生素治疗",
-      "抗炎药物",
-      "预防措施"
+      "妇科检查",
+      "免疫力下降",
+      "性传播疾病"
    ],
-    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##阴道炎##宫颈炎##盆腔炎##感染因素#",
-    "new_tag_id": 12681
+    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##阴道炎##宫颈炎##盆腔炎##白带异常#",
+    "new_tag_id": 13435
  },
  {
    "success": true,
-    "image_id": 16497,
+    "image_id": 16500,
    "original_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
    "derived_tags": [
+      "妇科疾病",
      "阴道炎",
-      "宫颈炎",
      "盆腔炎",
-      "感染因素",
-      "个人卫生",
+      "白带异常",
+      "私处护理",
      "抗生素治疗",
-      "抗炎药物",
-      "预防措施"
+      "免疫力提升",
+      "月经不调"
    ],
-    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##阴道炎##宫颈炎##盆腔炎##感染因素#",
-    "new_tag_id": 12681
+    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##妇科疾病##阴道炎##盆腔炎##白带异常#",
+    "new_tag_id": 13437
  },
  {
    "success": true,
-    "image_id": 16498,
+    "image_id": 16516,
+    "original_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
+    "derived_tags": [
+      "更年期症状",
+      "激素变化",
+      "月经紊乱",
+      "潮热出汗",
+      "骨质疏松",
+      "情绪波动",
+      "妇科保健",
+      "内分泌失调"
+    ],
+    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##更年期症状##激素变化##月经紊乱##潮热出汗#",
+    "new_tag_id": 13439
+  },
+  {
+    "success": true,
+    "image_id": 16518,
    "original_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办#",
    "derived_tags": [
      "阴道炎",
-      "宫颈炎",
      "盆腔炎",
-      "感染因素",
-      "个人卫生",
+      "白带异常",
      "抗生素治疗",
-      "抗炎药物",
-      "预防措施"
+      "个人卫生",
+      "妇科检查",
+      "免疫力下降",
+      "性传播疾病"
    ],
-    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##阴道炎##宫颈炎##盆腔炎##感染因素#",
-    "new_tag_id": 12681
+    "merged_tag": "#妇科炎症##妇科炎症原因##妇科炎症治疗##妇科炎症怎么办##阴道炎##盆腔炎##白带异常##抗生素治疗#",
+    "new_tag_id": 13440
  }
 ]
--- a/image_tag_derive.py
+++ b/image_tag_derive.py
@@ -1,13 +1,14 @@
 # -*- coding: utf-8 -*-
 """
 千问大模型 - 图片标签衍生生成脚本
-流程：每次批量2-3张图片 -> 大模型返回各自衍生标签 -> 分别更新数据库
+流程：每批次N张图片并发请求 -> 大模型返回各自衍生标签 -> 分别更新数据库
 """

 import os
 import json
 from http import HTTPStatus
 from typing import List, Dict, Optional
+from concurrent.futures import ThreadPoolExecutor, as_completed

 from database_config import get_db
 from config.settings import settings
@@ -29,32 +30,25 @@ dashscope.api_key = settings.qwen.api_key


 # ============== Prompt模板 ==============
-BATCH_DERIVE_PROMPT = """你是一个专业的医疗健康内容标签分析专家。
+# 单张图片的Prompt
+SINGLE_DERIVE_PROMPT = """你是一个专业的医疗健康内容标签分析专家。

 ## 任务
-我提供了{image_count}张医疗健康相关图片，每张图片有一个原始标签。请分析每张图片，为每张图片生成衍生标签。
-
-## 图片及原始标签
-{image_tags_list}
+我提供了一张医疗健康相关图片，原始标签为「{original_tag}」。请分析图片内容，生成衍生标签。

 ## 要求
-1. 分析每张图片内容，结合其原始标签
-2. 为每张图片生成 5-8 个衍生标签
+1. 分析图片内容，结合原始标签
+2. 生成 5-8 个衍生标签
 3. 衍生标签包括：同义词、上位概念、下位概念、相关症状/治疗等
 4. 标签简洁，每个不超过10个字

 ## 输出格式
-请严格以JSON格式输出，按图片顺序返回：
+请严格以JSON格式输出：
 ```json
-{{
-    "results": [
-        {{"image_index": 1, "original_tag": "原始标签1", "derived_tags": ["衍生1", "衍生2", "衍生3"]}},
-        {{"image_index": 2, "original_tag": "原始标签2", "derived_tags": ["衍生1", "衍生2", "衍生3"]}}
-    ]
-}}
+{{"derived_tags": ["衍生1", "衍生2", "衍生3", "衍生4", "衍生5"]}}
 ```

-注意：只输出JSON，不要输出其他内容。results数组长度必须等于图片数量。
+注意：只输出JSON，不要输出其他内容。
 """


@@ -116,30 +110,20 @@ def merge_tags(original_tag: str, derived_tags: List[str], max_total_tags: int =


@retry(max_retries=settings.qwen.max_retries, delay=settings.qwen.retry_delay, backoff=2.0)
-def derive_tags_batch(items: List[Dict]) -> Dict:
+def derive_tags_single(item: Dict) -> Dict:
    """
-    批量调用千问大模型，每张图片独立返回衍生标签
-    items: [{"id": 1, "image_url": "...", "tag_name": "高血压"}, ...]
-    带重试机制
+    单张图片调用千问大模型获取衍生标签
+    item: {"id": 1, "image_url": "...", "tag_name": "高血压", ...}
+    返回: {"success": True/False, "item": item, "derived_tags": [...], "error": "..."}
    """
-    logger.info(f"[批量处理] {len(items)} 张图片")
+    logger.debug(f"  处理 ID:{item['id']} - {item['tag_name']}")
    
-    # 构建图片标签列表描述
-    image_tags_list = ""
-    for i, item in enumerate(items):
-        image_tags_list += f"- 图片{i+1}: 原始标签「{item['tag_name']}」\n"
-        logger.debug(f"  图片{i+1}: {item['tag_name']} - {item['image_url'][:50]}...")
+    prompt = SINGLE_DERIVE_PROMPT.format(original_tag=item['tag_name'])
    
-    prompt = BATCH_DERIVE_PROMPT.format(
-        image_count=len(items),
-        image_tags_list=image_tags_list.strip()
-    )
-    
-    # 构建多图消息
-    content = []
-    for item in items:
-        content.append({"image": item['image_url']})
-    content.append({"text": prompt})
+    content = [
+        {"image": item['image_url']},
+        {"text": prompt}
+    ]
    
    messages = [{"role": "user", "content": content}]
    
@@ -150,6 +134,7 @@ def derive_tags_batch(items: List[Dict]) -> Dict:
    
    if response.status_code == HTTPStatus.OK:
        result_text = response.output.choices[0].message.content[0]["text"]
+        logger.debug(f"  ID:{item['id']} 原始响应: {result_text[:200]}...")
        
        try:
            json_start = result_text.find('{')
@@ -157,50 +142,83 @@ def derive_tags_batch(items: List[Dict]) -> Dict:
            if json_start != -1 and json_end > json_start:
                json_str = result_text[json_start:json_end]
                result_json = json.loads(json_str)
-                results = result_json.get('results', [])
-                return {"success": True, "results": results}
+                derived_tags = result_json.get('derived_tags', [])
+                if not derived_tags:
+                    logger.warning(f"  ID:{item['id']} 返回JSON中无derived_tags字段: {json_str[:100]}")
+                return {"success": True, "item": item, "derived_tags": derived_tags}
+            else:
+                logger.warning(f"  ID:{item['id']} 未找到JSON内容: {result_text[:200]}")
+                return {"success": False, "item": item, "error": "未找到JSON内容"}
        except json.JSONDecodeError as e:
-            logger.error(f"  JSON解析失败: {e}")
+            logger.error(f"  ID:{item['id']} JSON解析失败: {e}, 内容: {result_text[:200]}")
        
-        return {"success": False, "error": "JSON解析失败"}
+        return {"success": False, "item": item, "error": "JSON解析失败"}
    else:
        error_msg = f"{response.code}-{response.message}"
-        logger.error(f"  API调用失败: {error_msg}")
+        logger.error(f"  ID:{item['id']} API调用失败: {error_msg}")
        raise Exception(error_msg)  # 抛出异常触发重试


-def process_batch(items: List[Dict], tags_dao: TagsDAO) -> List[Dict]:
+def process_batch(items: List[Dict], tags_dao: TagsDAO, concurrency: int = None) -> List[Dict]:
    """
-    处理一批图片
+    并发处理一批图片
+    
+    Args:
+        items: 要处理的图片列表
+        tags_dao: 标签 DAO
+        concurrency: 并发数（同时发出的请求数）
    """
-    # 1. 批量调用大模型
-    try:
-        result = derive_tags_batch(items)
-    except Exception as e:
-        logger.error(f"批量处理失败: {e}")
-        return [{"success": False, "image_id": item['id'], "error": str(e)} for item in items]
+    if concurrency is None:
+        concurrency = settings.tag_derive.concurrency
    
-    if not result.get('success'):
-        return [{"success": False, "image_id": item['id'], "error": result.get('error')} for item in items]
+    logger.info(f"[处理批次] {len(items)} 张图片，并发数: {concurrency}")
    
-    api_results = result.get('results', [])
    db = get_db()
    process_results = []
+    api_results = []
    
-    # 2. 逐个匹配并更新
-    for i, item in enumerate(items):
-        # 查找对应的衍生结果
-        derived_tags = []
-        for r in api_results:
-            if r.get('image_index') == i + 1 or r.get('original_tag') == item['tag_name']:
-                derived_tags = r.get('derived_tags', [])
-                break
+    # 1. 并发调用大模型（按并发数限制）
+    with ThreadPoolExecutor(max_workers=concurrency) as executor:
+        # 提交所有任务
+        future_to_item = {
+            executor.submit(derive_tags_single, item): item 
+            for item in items
+        }
        
-        if not derived_tags and i < len(api_results):
-            derived_tags = api_results[i].get('derived_tags', [])
+        # 收集结果
+        for future in as_completed(future_to_item):
+            item = future_to_item[future]
+            try:
+                result = future.result()
+                api_results.append(result)
+            except Exception as e:
+                logger.error(f"  ID:{item['id']} 处理异常: {e}")
+                api_results.append({
+                    "success": False, 
+                    "item": item, 
+                    "error": str(e)
+                })
+    
+    # 2. 逐个处理结果并更新数据库
+    for result in api_results:
+        item = result.get('item', {})
+        
+        if not result.get('success'):
+            process_results.append({
+                "success": False, 
+                "image_id": item.get('id'), 
+                "error": result.get('error', '未知错误')
+            })
+            continue
+        
+        derived_tags = result.get('derived_tags', [])
        
        if not derived_tags:
-            process_results.append({"success": False, "image_id": item['id'], "error": "未找到衍生标签"})
+            process_results.append({
+                "success": False, 
+                "image_id": item['id'], 
+                "error": "未获取到衍生标签"
+            })
            continue
        
        logger.info(f"  [{item['tag_name']}] 衍生: {derived_tags}")
@@ -211,14 +229,14 @@ def process_batch(items: List[Dict], tags_dao: TagsDAO) -> List[Dict]:
        
        # 插入ai_tags
        try:
-            new_tag_id = tags_dao.get_or_create(merged_tag_name, '衍生标签', item.get('department_name', ''))
+            new_tag_id = tags_dao.get_or_create(merged_tag_name, None, item.get('department_name', ''))
        except Exception as e:
            process_results.append({"success": False, "image_id": item['id'], "error": str(e)})
            continue
        
-        # 更新ai_image_tags
+        # 更新ai_image_tags（包括 tag_id, tag_name, status）
        try:
-            sql = "UPDATE ai_image_tags SET tag_id = %s, tag_name = %s WHERE id = %s"
+            sql = "UPDATE ai_image_tags SET tag_id = %s, tag_name = %s, status = 'manual_review' WHERE id = %s"
            db.execute_update(sql, (new_tag_id, merged_tag_name, item['id']))
            process_results.append({
                "success": True,
@@ -228,51 +246,52 @@ def process_batch(items: List[Dict], tags_dao: TagsDAO) -> List[Dict]:
                "merged_tag": merged_tag_name,
                "new_tag_id": new_tag_id
            })
-            logger.info(f"    ✓ ID:{item['id']} -> tag_id:{new_tag_id}")
+            logger.info(f"    ✓ ID:{item['id']} -> tag_id:{new_tag_id}, status -> manual_review")
        except Exception as e:
            process_results.append({"success": False, "image_id": item['id'], "error": str(e)})
    
    return process_results


-def batch_derive_tags(batch_size: int = None, start_id: int = None, end_id: int = None, ids: List[int] = None) -> List[Dict]:
+def batch_derive_tags(batch_size: int = None, concurrency: int = None, start_id: int = None, end_id: int = None, ids: List[int] = None) -> List[Dict]:
    """
-    分批处理，每批2-3张图片
+    分批处理图片标签衍生
    
    Args:
-        batch_size: 每批处理的图片数量
+        batch_size: 每批次从数据库读取的图片数量
+        concurrency: 并发请求数（同时发出的API请求数）
        start_id: 起始ID，从该ID开始处理（用于断点续传）
        end_id: 结束ID，处理到该ID为止
        ids: 指定ID列表，只处理这些ID
    """
    if batch_size is None:
        batch_size = settings.tag_derive.batch_size
+    if concurrency is None:
+        concurrency = settings.tag_derive.concurrency
    
    tags_dao = TagsDAO()
    db = get_db()
    
    # 查询需要处理的记录
    if ids:
-        # 按指定ID查询（同样检查是否已有衍生标签）
+        # 按指定ID查询（查询 status='tag_extension' 的记录）
        placeholders = ','.join(['%s'] * len(ids))
        sql = f"""
            SELECT it.id, it.image_thumb_url, it.tag_id, it.tag_name, it.department_name
            FROM ai_image_tags it
-            LEFT JOIN ai_tags t ON it.tag_id = t.id
            WHERE it.id IN ({placeholders})
              AND it.image_thumb_url != '' AND it.tag_name != ''
-              AND (t.tag_category IS NULL OR t.tag_category != '衍生标签')
+              AND it.status = 'tag_extension'
            ORDER BY it.id
        """
        items = db.execute_query(sql, ids)
    else:
-        # 按条件查询
+        # 按条件查询 status='tag_extension' 的记录
        sql = """
            SELECT it.id, it.image_thumb_url, it.tag_id, it.tag_name, it.department_name
            FROM ai_image_tags it
-            LEFT JOIN ai_tags t ON it.tag_id = t.id
            WHERE it.image_thumb_url != '' AND it.tag_name != ''
-              AND (t.tag_category IS NULL OR t.tag_category != '衍生标签')
+              AND it.status = 'tag_extension'
        """
        
        params = []
@@ -299,7 +318,7 @@ def batch_derive_tags(batch_size: int = None, start_id: int = None, end_id: int
            item['image_url'] = ''
    
    total = len(items)
-    logger.info(f"待处理: {total} 条，每批 {batch_size} 张")
+    logger.info(f"待处理: {total} 条，每批 {batch_size} 张，并发数: {concurrency}")
    
    all_results = []
    
@@ -310,7 +329,7 @@ def batch_derive_tags(batch_size: int = None, start_id: int = None, end_id: int
        logger.info(f"{'='*60}")
        logger.info(f"批次 {batch_num}/{(total + batch_size - 1) // batch_size}")
        
-        results = process_batch(batch, tags_dao)
+        results = process_batch(batch, tags_dao, concurrency)
        all_results.extend(results)
        
        success = sum(1 for r in results if r.get('success'))
@@ -345,13 +364,17 @@ def main():
    parser = argparse.ArgumentParser(description='千问视觉大模型 - 图片标签衍生生成器')
    parser.add_argument('--start-id', type=int, default=None, help='起始ID，从该ID开始处理（用于断点续传）')
    parser.add_argument('--end-id', type=int, default=None, help='结束ID，处理到该ID为止')
-    parser.add_argument('--batch-size', type=int, default=None, help='每批处理的图片数量')
+    parser.add_argument('--batch-size', type=int, default=None, help='每批次从数据库读取的图片数量')
+    parser.add_argument('--concurrency', type=int, default=None, help='并发请求数（同时发出的API请求数）')
    parser.add_argument('--id', type=int, nargs='+', default=None, help='指定ID，只处理这些ID（可指定多个）')
    args = parser.parse_args()
    
+    batch_size = args.batch_size or settings.tag_derive.batch_size
+    concurrency = args.concurrency or settings.tag_derive.concurrency
+    
    logger.info("=" * 60)
    logger.info("千问视觉大模型 - 图片标签衍生生成器")
-    logger.info(f"模式: 每批{args.batch_size or settings.tag_derive.batch_size}张图片，各自返回衍生标签")
+    logger.info(f"模式: 每批 {batch_size} 张，并发 {concurrency} 个请求")
    if args.id:
        logger.info(f"指定ID: {args.id}")
    elif args.start_id or args.end_id:
@@ -359,7 +382,13 @@ def main():
        logger.info(f"ID范围: {id_range}")
    logger.info("=" * 60)
    
-    results = batch_derive_tags(batch_size=args.batch_size, start_id=args.start_id, end_id=args.end_id, ids=args.id)
+    results = batch_derive_tags(
+        batch_size=args.batch_size, 
+        concurrency=args.concurrency,
+        start_id=args.start_id, 
+        end_id=args.end_id, 
+        ids=args.id
+    )
    
    if results:
        print_summary(results)
--- a/query_tags.py
+++ b/query_tags.py
@@ -1,34 +1,185 @@
 # -*- coding: utf-8 -*-
-"""查询所有带标签字段的数据"""
-
-from database_config import get_db
-
-db = get_db()
-
-# 查询所有带标签相关字段的数据
-sql = """
-SELECT id, image_id, image_name, 
-       tag_id, tag_name, 
-       default_tag_id, default_tag_name, 
-       keywords_id, keywords_name, 
-       department_id, department_name, 
-       status 
-FROM ai_image_tags 
-ORDER BY id
+"""
+标签数据查询脚本
+支持查询 ai_image_tags 和 ai_tags 表的相关数据
 """

-results = db.execute_query(sql)
+import argparse
+from database_config import get_db

-print(f"{'=' * 120}")
-print(f"ai_image_tags 表中共有 {len(results)} 条数据")
-print(f"{'=' * 120}")

-# 表头
-print(f"{'ID':<6} {'图片ID':<8} {'标签名':<15} {'初始标签名':<15} {'关键词':<12} {'科室':<10} {'状态':<10}")
-print(f"{'-' * 120}")
+def query_image_tags_by_status(status: str = None, limit: int = 20):
+    """按状态查询 ai_image_tags 表"""
+    db = get_db()
+    
+    if status:
+        sql = """
+            SELECT id, image_id, image_name, tag_id, tag_name, 
+                   default_tag_id, default_tag_name, 
+                   keywords_name, department_name, status, created_at
+            FROM ai_image_tags 
+            WHERE status = %s
+            ORDER BY id DESC
+            LIMIT %s
+        """
+        results = db.execute_query(sql, (status, limit))
+    else:
+        sql = """
+            SELECT id, image_id, image_name, tag_id, tag_name, 
+                   default_tag_id, default_tag_name, 
+                   keywords_name, department_name, status, created_at
+            FROM ai_image_tags 
+            ORDER BY id DESC
+            LIMIT %s
+        """
+        results = db.execute_query(sql, (limit,))
+    
+    print(f"\n{'=' * 130}")
+    print(f"ai_image_tags 查询结果 (status={status or '全部'}, limit={limit})")
+    print(f"{'=' * 130}")
+    print(f"{'ID':<8} {'tag_id':<8} {'tag_name':<25} {'default_tag':<20} {'department':<12} {'status':<20}")
+    print(f"{'-' * 130}")
+    
+    for r in results:
+        tag_name = (r['tag_name'] or '')[:24]
+        default_tag = (r['default_tag_name'] or '')[:19]
+        dept = (r['department_name'] or '')[:11]
+        print(f"{r['id']:<8} {r['tag_id']:<8} {tag_name:<25} {default_tag:<20} {dept:<12} {r['status']:<20}")
+    
+    print(f"{'=' * 130}")
+    print(f"显示 {len(results)} 条记录")

-for r in results:
-    print(f"{r['id']:<6} {r['image_id']:<8} {r['tag_name']:<15} {r['default_tag_name']:<15} {r['keywords_name']:<12} {r['department_name']:<10} {r['status']:<10}")

-print(f"{'=' * 120}")
-print(f"总计: {len(results)} 条记录")
+def query_status_stats():
+    """统计各状态的数量"""
+    db = get_db()
+    
+    sql = "SELECT status, COUNT(*) as cnt FROM ai_image_tags GROUP BY status ORDER BY cnt DESC"
+    results = db.execute_query(sql)
+    
+    print(f"\n{'=' * 50}")
+    print(f"ai_image_tags 状态统计")
+    print(f"{'=' * 50}")
+    print(f"{'状态':<25} {'数量':>10}")
+    print(f"{'-' * 50}")
+    
+    total = 0
+    for r in results:
+        print(f"{r['status']:<25} {r['cnt']:>10}")
+        total += r['cnt']
+    
+    print(f"{'-' * 50}")
+    print(f"{'总计':<25} {total:>10}")
+
+
+def query_tags_by_category(category: str = None, limit: int = 20):
+    """查询 ai_tags 表"""
+    db = get_db()
+    
+    if category:
+        sql = """
+            SELECT id, tag_name, tag_category, department, usage_count, status, created_at
+            FROM ai_tags 
+            WHERE tag_category = %s
+            ORDER BY id DESC
+            LIMIT %s
+        """
+        results = db.execute_query(sql, (category, limit))
+    else:
+        sql = """
+            SELECT id, tag_name, tag_category, department, usage_count, status, created_at
+            FROM ai_tags 
+            ORDER BY id DESC
+            LIMIT %s
+        """
+        results = db.execute_query(sql, (limit,))
+    
+    print(f"\n{'=' * 120}")
+    print(f"ai_tags 查询结果 (category={category or '全部'}, limit={limit})")
+    print(f"{'=' * 120}")
+    print(f"{'ID':<8} {'tag_name':<40} {'category':<15} {'department':<12} {'usage':<8}")
+    print(f"{'-' * 120}")
+    
+    for r in results:
+        tag_name = (r['tag_name'] or '')[:39]
+        category_val = (r['tag_category'] or '')[:14]
+        dept = (r['department'] or '')[:11]
+        print(f"{r['id']:<8} {tag_name:<40} {category_val:<15} {dept:<12} {r['usage_count']:<8}")
+    
+    print(f"{'=' * 120}")
+    print(f"显示 {len(results)} 条记录")
+
+
+def query_join_data(status: str = 'tag_extension', limit: int = 20):
+    """关联查询 ai_image_tags 和 ai_tags"""
+    db = get_db()
+    
+    sql = """
+        SELECT it.id, it.image_id, it.tag_id, it.tag_name as it_tag_name,
+               it.default_tag_name, it.department_name, it.status,
+               t.tag_name as t_tag_name, t.tag_category
+        FROM ai_image_tags it
+        LEFT JOIN ai_tags t ON it.tag_id = t.id
+        WHERE it.status = %s
+        ORDER BY it.id DESC
+        LIMIT %s
+    """
+    results = db.execute_query(sql, (status, limit))
+    
+    print(f"\n{'=' * 140}")
+    print(f"关联查询 (ai_image_tags.status={status})")
+    print(f"{'=' * 140}")
+    print(f"{'it.id':<8} {'tag_id':<8} {'it.tag_name':<30} {'t.tag_name':<30} {'t.category':<15} {'department':<12}")
+    print(f"{'-' * 140}")
+    
+    for r in results:
+        it_tag = (r['it_tag_name'] or '')[:29]
+        t_tag = (r['t_tag_name'] or '')[:29]
+        category = (r['tag_category'] or '')[:14]
+        dept = (r['department_name'] or '')[:11]
+        print(f"{r['id']:<8} {r['tag_id'] or 0:<8} {it_tag:<30} {t_tag:<30} {category:<15} {dept:<12}")
+    
+    print(f"{'=' * 140}")
+    print(f"显示 {len(results)} 条记录")
+
+
+def query_both_tables(status: str = None, category: str = None, limit: int = 20):
+    """同时查询 ai_image_tags 和 ai_tags 两个表"""
+    query_status_stats()
+    query_image_tags_by_status(status=status, limit=limit)
+    query_tags_by_category(category=category, limit=limit)
+
+
+def main():
+    parser = argparse.ArgumentParser(description='标签数据查询工具')
+    parser.add_argument('--status', '-s', type=str, default=None,
+                        help='按状态过滤 ai_image_tags (如: tag_extension, manual_review, draft)')
+    parser.add_argument('--category', '-c', type=str, default=None,
+                        help='按分类过滤 ai_tags (如: 衍生标签)')
+    parser.add_argument('--limit', '-l', type=int, default=20,
+                        help='返回记录数限制 (默认: 20)')
+    parser.add_argument('--stats', action='store_true',
+                        help='仅显示状态统计')
+    parser.add_argument('--join', '-j', action='store_true',
+                        help='关联查询 ai_image_tags 和 ai_tags')
+    parser.add_argument('--image-tags', '-i', action='store_true',
+                        help='仅查询 ai_image_tags 表')
+    parser.add_argument('--tags', '-t', action='store_true',
+                        help='仅查询 ai_tags 表')
+    args = parser.parse_args()
+    
+    if args.stats:
+        query_status_stats()
+    elif args.join:
+        query_join_data(status=args.status or 'tag_extension', limit=args.limit)
+    elif args.image_tags:
+        query_image_tags_by_status(status=args.status, limit=args.limit)
+    elif args.tags:
+        query_tags_by_category(category=args.category, limit=args.limit)
+    else:
+        # 默认同时查询两个表
+        query_both_tables(status=args.status, category=args.category, limit=args.limit)
+
+
+if __name__ == "__main__":
+    main()
--- a/rebuild_database.py
+++ b/rebuild_database.py
@@ -0,0 +1,310 @@
+# -*- coding: utf-8 -*-
+"""
+数据库重建脚本
+根据 ai_article.sql 重建数据库结构，从 ai_image_tags.txt 导入数据
+"""
+
+import mysql.connector
+import os
+
+
+# 数据库配置
+DB_CONFIG = {
+    "host": "localhost",
+    "port": 3306,
+    "user": "root",
+    "password": "liang20020523",
+    "charset": "utf8mb4"
+}
+
+DATABASE_NAME = "ai_article"
+SQL_FILE = "ai_article.sql"
+DATA_FILE = "ai_image_tags.txt"
+
+
+def get_connection(with_database=False):
+    """获取数据库连接"""
+    config = DB_CONFIG.copy()
+    if with_database:
+        config["database"] = DATABASE_NAME
+    return mysql.connector.connect(**config)
+
+
+def rebuild_database_structure():
+    """重建数据库结构"""
+    print("=" * 60)
+    print("步骤1: 重建数据库结构")
+    print("=" * 60)
+    
+    # 读取SQL文件
+    sql_path = os.path.join(os.path.dirname(__file__), SQL_FILE)
+    print(f"读取SQL文件: {sql_path}")
+    
+    with open(sql_path, "r", encoding="utf-8") as f:
+        sql_content = f.read()
+    
+    # 连接MySQL（不指定数据库）
+    conn = get_connection(with_database=False)
+    cursor = conn.cursor()
+    
+    try:
+        # 删除并重新创建数据库
+        print(f"\n删除数据库 {DATABASE_NAME}（如果存在）...")
+        cursor.execute(f"DROP DATABASE IF EXISTS `{DATABASE_NAME}`")
+        
+        print(f"创建数据库 {DATABASE_NAME}...")
+        cursor.execute(f"CREATE DATABASE `{DATABASE_NAME}` CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci")
+        
+        print(f"切换到数据库 {DATABASE_NAME}...")
+        cursor.execute(f"USE `{DATABASE_NAME}`")
+        
+        # 分割并执行SQL语句
+        print("\n执行SQL脚本...")
+        
+        # 移除注释并分割SQL语句
+        statements = []
+        current_statement = ""
+        in_comment = False
+        
+        for line in sql_content.split("\n"):
+            stripped = line.strip()
+            
+            # 跳过空行
+            if not stripped:
+                continue
+            
+            # 跳过单行注释
+            if stripped.startswith("--"):
+                continue
+            
+            # 处理多行注释开始
+            if stripped.startswith("/*"):
+                in_comment = True
+                continue
+            
+            # 处理多行注释结束
+            if "*/" in stripped:
+                in_comment = False
+                continue
+            
+            # 跳过注释中的内容
+            if in_comment:
+                continue
+            
+            current_statement += line + "\n"
+            
+            # 检查语句是否结束
+            if stripped.endswith(";"):
+                statements.append(current_statement.strip())
+                current_statement = ""
+        
+        # 执行每条SQL语句
+        success_count = 0
+        error_count = 0
+        
+        for i, stmt in enumerate(statements):
+            if not stmt or stmt.strip() == ";":
+                continue
+            try:
+                cursor.execute(stmt)
+                conn.commit()
+                success_count += 1
+                # 打印表创建信息
+                if "CREATE TABLE" in stmt.upper():
+                    table_name = stmt.split("`")[1] if "`" in stmt else "unknown"
+                    print(f"  ✓ 创建表: {table_name}")
+            except mysql.connector.Error as e:
+                error_count += 1
+                # 只打印关键错误
+                if "already exists" not in str(e).lower():
+                    print(f"  ✗ SQL执行错误: {str(e)[:100]}")
+        
+        print(f"\nSQL执行完成: 成功 {success_count} 条, 失败 {error_count} 条")
+        
+    finally:
+        cursor.close()
+        conn.close()
+
+
+def import_image_tags_data():
+    """从 ai_image_tags.txt 导入数据"""
+    print("\n" + "=" * 60)
+    print("步骤2: 导入 ai_image_tags 数据")
+    print("=" * 60)
+    
+    data_path = os.path.join(os.path.dirname(__file__), DATA_FILE)
+    print(f"读取数据文件: {data_path}")
+    
+    if not os.path.exists(data_path):
+        print(f"数据文件不存在: {data_path}")
+        return
+    
+    with open(data_path, "r", encoding="utf-8") as f:
+        lines = f.readlines()
+    
+    # 解析数据
+    # 文件格式：第9行是列头，从第10行开始是数据
+    data_rows = []
+    header_line = None
+    
+    for i, line in enumerate(lines):
+        stripped = line.strip()
+        if not stripped:
+            continue
+        
+        # 找到列头行（包含 id, image_id 等）
+        if stripped.startswith("id\t"):
+            header_line = stripped
+            print(f"找到列头（第{i+1}行）: {stripped[:80]}...")
+            continue
+        
+        # 跳过非数据行
+        if header_line is None:
+            continue
+        
+        # 解析数据行（以数字开头）
+        parts = stripped.split("\t")
+        if len(parts) >= 10 and parts[0].isdigit():
+            data_rows.append(parts)
+    
+    print(f"解析到 {len(data_rows)} 条数据")
+    
+    if not data_rows:
+        print("没有数据需要导入")
+        return
+    
+    # 连接数据库
+    conn = get_connection(with_database=True)
+    cursor = conn.cursor()
+    
+    try:
+        # 禁用外键检查
+        cursor.execute("SET FOREIGN_KEY_CHECKS = 0")
+        print("已禁用外键检查")
+        
+        # 插入数据
+        insert_sql = """
+            INSERT INTO ai_image_tags 
+            (id, image_id, image_name, image_url, image_thumb_url, tag_id, tag_name, 
+             default_tag_id, default_tag_name, keywords_id, keywords_name, 
+             department_id, department_name, image_source, created_user_id, 
+             created_at, updated_at, image_attached_article_count, status, blocking_reason)
+            VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
+        """
+        
+        success_count = 0
+        error_count = 0
+        
+        for row in data_rows:
+            try:
+                # 处理数据，确保长度匹配
+                while len(row) < 20:
+                    row.append("")
+                
+                # 转换数据类型
+                values = (
+                    int(row[0]),                    # id
+                    int(row[1]),                    # image_id
+                    row[2],                         # image_name
+                    row[3],                         # image_url
+                    row[4],                         # image_thumb_url
+                    int(row[5]),                    # tag_id
+                    row[6],                         # tag_name
+                    int(row[7]) if row[7] else 0,   # default_tag_id
+                    row[8],                         # default_tag_name
+                    int(row[9]),                    # keywords_id
+                    row[10],                        # keywords_name
+                    int(row[11]),                   # department_id
+                    row[12],                        # department_name
+                    int(row[13]) if row[13] else 1, # image_source
+                    int(row[14]) if row[14] else 0, # created_user_id
+                    row[15],                        # created_at
+                    row[16],                        # updated_at
+                    int(row[17]) if row[17] else 0, # image_attached_article_count
+                    row[18] if row[18] else "draft", # status
+                    row[19] if len(row) > 19 else "" # blocking_reason
+                )
+                
+                cursor.execute(insert_sql, values)
+                success_count += 1
+                
+            except Exception as e:
+                error_count += 1
+                if error_count <= 3:
+                    print(f"  插入错误 (id={row[0]}): {e}")
+        
+        conn.commit()
+        print(f"\n数据导入完成: 成功 {success_count} 条, 失败 {error_count} 条")
+        
+        # 恢复外键检查
+        cursor.execute("SET FOREIGN_KEY_CHECKS = 1")
+        print("已恢复外键检查")
+        
+    finally:
+        cursor.close()
+        conn.close()
+
+
+def verify_database():
+    """验证数据库"""
+    print("\n" + "=" * 60)
+    print("步骤3: 验证数据库")
+    print("=" * 60)
+    
+    conn = get_connection(with_database=True)
+    cursor = conn.cursor()
+    
+    try:
+        # 检查表数量
+        cursor.execute("SHOW TABLES")
+        tables = cursor.fetchall()
+        print(f"\n数据库中共有 {len(tables)} 张表:")
+        for t in tables[:10]:
+            print(f"  - {t[0]}")
+        if len(tables) > 10:
+            print(f"  ... 还有 {len(tables) - 10} 张表")
+        
+        # 检查 ai_image_tags 表数据
+        cursor.execute("SELECT COUNT(*) FROM ai_image_tags")
+        count = cursor.fetchone()[0]
+        print(f"\nai_image_tags 表共有 {count} 条记录")
+        
+        if count > 0:
+            cursor.execute("SELECT id, tag_name, department_name FROM ai_image_tags LIMIT 3")
+            rows = cursor.fetchall()
+            print("示例数据:")
+            for row in rows:
+                print(f"  ID: {row[0]}, 标签: {row[1][:30]}..., 科室: {row[2]}")
+        
+    finally:
+        cursor.close()
+        conn.close()
+
+
+def main():
+    print("\n" + "=" * 60)
+    print("           数据库重建脚本")
+    print("=" * 60)
+    print(f"数据库: {DATABASE_NAME}")
+    print(f"SQL文件: {SQL_FILE}")
+    print(f"数据文件: {DATA_FILE}")
+    print("=" * 60)
+    
+    # 确认操作
+    confirm = input("\n警告: 此操作将删除并重建数据库，所有数据将丢失！\n确认继续? (输入 'yes' 确认): ")
+    if confirm.lower() != "yes":
+        print("操作已取消")
+        return
+    
+    # 执行重建
+    rebuild_database_structure()
+    import_image_tags_data()
+    verify_database()
+    
+    print("\n" + "=" * 60)
+    print("数据库重建完成！")
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    main()
--- a/reset_image_tags_data.py
+++ b/reset_image_tags_data.py
@@ -1,162 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-重置 ai_image_tags 和 ai_tags 表数据
-从 ai_image_tags.txt (Tab分隔格式) 导入数据
-"""
-
-import os
-from database_config import get_db
-from logger import get_logger
-
-logger = get_logger("reset_data")
-
-
-def parse_tsv_file(file_path: str) -> list:
-    """
-    解析 Tab 分隔的 ai_image_tags.txt 文件
-    """
-    with open(file_path, 'r', encoding='utf-8') as f:
-        lines = f.readlines()
-    
-    records = []
-    header = None
-    
-    for line in lines:
-        line = line.strip()
-        if not line:
-            continue
-        
-        # 跳过头信息行
-        if line.startswith('8.149') or line.startswith('http://') or '正在显示' in line or line.startswith('SELECT'):
-            continue
-        
-        # 解析表头
-        if line.startswith('id\t'):
-            header = line.split('\t')
-            logger.info(f"解析到表头: {len(header)} 列")
-            continue
-        
-        # 解析数据行
-        if header and line[0].isdigit():
-            fields = line.split('\t')
-            if len(fields) >= 19:  # 至少要有19列
-                record = {
-                    'id': int(fields[0]) if fields[0] else 0,
-                    'image_id': int(fields[1]) if fields[1] else 0,
-                    'image_name': fields[2],
-                    'image_url': fields[3],
-                    'image_thumb_url': fields[4],
-                    'tag_id': int(fields[5]) if fields[5] else 0,
-                    'tag_name': fields[6],
-                    'default_tag_id': int(fields[7]) if fields[7] else 0,
-                    'default_tag_name': fields[8],
-                    'keywords_id': int(fields[9]) if fields[9] else 0,
-                    'keywords_name': fields[10],
-                    'department_id': int(fields[11]) if fields[11] else 0,
-                    'department_name': fields[12],
-                    'image_source': int(fields[13]) if fields[13] else 1,
-                    'created_user_id': int(fields[14]) if fields[14] else 0,
-                    'created_at': fields[15] if fields[15] else None,
-                    'updated_at': fields[16] if fields[16] else None,
-                    'image_attached_article_count': int(fields[17]) if fields[17] else 0,
-                    'status': fields[18] if fields[18] else 'draft',
-                    'blocking_reason': fields[19] if len(fields) > 19 else ''
-                }
-                records.append(record)
-    
-    return records
-
-
-def reset_tables_and_import(file_path: str):
-    """
-    清空表并导入数据
-    """
-    db = get_db()
-    
-    # 解析文件
-    logger.info(f"正在解析文件: {file_path}")
-    records = parse_tsv_file(file_path)
-    logger.info(f"共解析 {len(records)} 条记录")
-    
-    if not records:
-        logger.error("没有解析到有效数据，操作取消")
-        return
-    
-    # 收集所有 tag
-    tag_map = {}
-    for r in records:
-        if r['tag_id'] and r['tag_name']:
-            tag_map[r['tag_id']] = r['tag_name']
-    
-    # 确认操作
-    print(f"\n即将执行以下操作:")
-    print(f"1. 清空 ai_image_tags 表")
-    print(f"2. 清空 ai_tags 表")
-    print(f"3. 导入 {len(tag_map)} 条 ai_tags 记录")
-    print(f"4. 导入 {len(records)} 条 ai_image_tags 记录")
-    print(f"\n注意: 此操作不可逆!")
-    
-    confirm = input("\n确认执行? (输入 yes 继续): ")
-    if confirm.lower() != 'yes':
-        logger.info("操作已取消")
-        return
-    
-    try:
-        # 清空表（先删子表，再删父表）
-        logger.info("清空 ai_image_tags 表...")
-        db.execute_update("DELETE FROM ai_image_tags")
-        logger.info("清空 ai_tags 表...")
-        db.execute_update("DELETE FROM ai_tags")
-        
-        # 重置自增ID
-        db.execute_update("ALTER TABLE ai_image_tags AUTO_INCREMENT = 1")
-        db.execute_update("ALTER TABLE ai_tags AUTO_INCREMENT = 1")
-        
-        # 插入 ai_tags
-        logger.info(f"插入 ai_tags...")
-        for tag_id, tag_name in tag_map.items():
-            sql = "INSERT INTO ai_tags (id, tag_name, status) VALUES (%s, %s, 'active')"
-            try:
-                db.execute_insert(sql, (tag_id, tag_name))
-            except Exception as e:
-                logger.warning(f"插入 tag {tag_id} 失败: {e}")
-        
-        # 插入 ai_image_tags
-        logger.info(f"插入 ai_image_tags...")
-        success_count = 0
-        for r in records:
-            sql = """
-                INSERT INTO ai_image_tags 
-                (id, image_id, image_name, image_url, image_thumb_url, tag_id, tag_name, 
-                 default_tag_id, default_tag_name, keywords_id, keywords_name, 
-                 department_id, department_name, image_source, created_user_id, 
-                 created_at, updated_at, image_attached_article_count, status, blocking_reason)
-                VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
-            """
-            params = (
-                r['id'], r['image_id'], r['image_name'], r['image_url'], r['image_thumb_url'],
-                r['tag_id'], r['tag_name'], r['default_tag_id'], r['default_tag_name'],
-                r['keywords_id'], r['keywords_name'], r['department_id'], r['department_name'],
-                r['image_source'], r['created_user_id'], r['created_at'], r['updated_at'],
-                r['image_attached_article_count'], r['status'], r['blocking_reason']
-            )
-            try:
-                db.execute_insert(sql, params)
-                success_count += 1
-            except Exception as e:
-                logger.error(f"插入记录 {r['id']} 失败: {e}")
-        
-        # 恢复自增ID到最大值
-        db.execute_update("ALTER TABLE ai_image_tags AUTO_INCREMENT = 1")
-        db.execute_update("ALTER TABLE ai_tags AUTO_INCREMENT = 1")
-        
-        logger.info(f"导入完成: 成功 {success_count}/{len(records)} 条")
-        
-    except Exception as e:
-        logger.error(f"操作失败: {e}")
-        raise
-
-
-if __name__ == "__main__":
-    file_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "ai_image_tags.txt")
-    reset_tables_and_import(file_path)
--- a/reset_tags.py
+++ b/reset_tags.py
@@ -1,81 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-重置标签数据脚本
-1. 把 ai_image_tags 的 tag_id/tag_name 恢复为 default_tag_id/default_tag_name
-2. 删除 ai_tags 表中的衍生标签
-"""
-
-from database_config import get_db
-
-
-def reset_database():
-    db = get_db()
-    
-    # 1. 先查看当前状态
-    print("=" * 60)
-    print("当前数据状态")
-    print("=" * 60)
-    
-    # 查看衍生标签数量
-    derived_count = db.execute_one(
-        "SELECT COUNT(*) as cnt FROM ai_tags WHERE tag_category = '衍生标签'"
-    )
-    print(f"ai_tags 表中的衍生标签数量: {derived_count['cnt']}")
-    
-    # 查看需要恢复的图片数量
-    need_reset = db.execute_one("""
-        SELECT COUNT(*) as cnt FROM ai_image_tags 
-        WHERE default_tag_id > 0 
-          AND (tag_id != default_tag_id OR tag_name != default_tag_name)
-    """)
-    print(f"需要恢复到初始标签的图片数量: {need_reset['cnt']}")
-    
-    print("\n" + "=" * 60)
-    print("开始执行清理")
-    print("=" * 60)
-    
-    # 2. 把 ai_image_tags 的标签恢复为初始标签
-    print("\n[步骤1] 恢复 ai_image_tags 到初始标签...")
-    affected = db.execute_update("""
-        UPDATE ai_image_tags 
-        SET tag_id = default_tag_id, 
-            tag_name = default_tag_name 
-        WHERE default_tag_id > 0
-    """)
-    print(f"  已更新 {affected} 条记录")
-    
-    # 3. 删除衍生标签
-    print("\n[步骤2] 删除 ai_tags 表中的衍生标签...")
-    deleted = db.execute_update(
-        "DELETE FROM ai_tags WHERE tag_category = '衍生标签'"
-    )
-    print(f"  已删除 {deleted} 条衍生标签")
-    
-    # 4. 验证结果
-    print("\n" + "=" * 60)
-    print("清理完成，验证结果")
-    print("=" * 60)
-    
-    remaining_derived = db.execute_one(
-        "SELECT COUNT(*) as cnt FROM ai_tags WHERE tag_category = '衍生标签'"
-    )
-    print(f"剩余衍生标签数量: {remaining_derived['cnt']}")
-    
-    sample = db.execute_query("""
-        SELECT id, image_id, tag_name, default_tag_name 
-        FROM ai_image_tags 
-        WHERE default_tag_id > 0 
-        LIMIT 5
-    """)
-    print("\n前5条图片标签示例:")
-    for row in sample:
-        print(f"  ID:{row['id']} | tag_name: {row['tag_name']} | default_tag_name: {row['default_tag_name']}")
-
-
-if __name__ == "__main__":
-    confirm = input("确认执行数据库清理？这将:\n1. 把所有图片标签恢复为初始标签\n2. 删除所有衍生标签\n输入 'yes' 确认: ")
-    if confirm.lower() == 'yes':
-        reset_database()
-        print("\n✓ 数据库已重置到干净状态")
-    else:
-        print("已取消操作")
--- a/restore_database.py
+++ b/restore_database.py
@@ -0,0 +1,299 @@
+# -*- coding: utf-8 -*-
+"""
+数据库恢复脚本
+根据 ai_article.sql 重建数据库结构，从 backup_data.json 恢复数据
+"""
+
+import mysql.connector
+import json
+import os
+
+
+# 数据库配置
+DB_CONFIG = {
+    "host": "localhost",
+    "port": 3306,
+    "user": "root",
+    "password": "liang20020523",
+    "charset": "utf8mb4"
+}
+
+DATABASE_NAME = "ai_article"
+SQL_FILE = "ai_article.sql"
+BACKUP_FILE = "backup_data.json"
+
+
+def get_connection(with_database=False):
+    """获取数据库连接"""
+    config = DB_CONFIG.copy()
+    if with_database:
+        config["database"] = DATABASE_NAME
+    return mysql.connector.connect(**config)
+
+
+def rebuild_database_structure():
+    """重建数据库结构"""
+    print("=" * 60)
+    print("步骤1: 重建数据库结构")
+    print("=" * 60)
+    
+    sql_path = os.path.join(os.path.dirname(__file__), SQL_FILE)
+    print(f"读取SQL文件: {sql_path}")
+    
+    with open(sql_path, "r", encoding="utf-8") as f:
+        sql_content = f.read()
+    
+    conn = get_connection(with_database=False)
+    cursor = conn.cursor()
+    
+    try:
+        print(f"\n删除数据库 {DATABASE_NAME}（如果存在）...")
+        cursor.execute(f"DROP DATABASE IF EXISTS `{DATABASE_NAME}`")
+        
+        print(f"创建数据库 {DATABASE_NAME}...")
+        cursor.execute(f"CREATE DATABASE `{DATABASE_NAME}` CHARACTER SET utf8mb4 COLLATE utf8mb4_general_ci")
+        
+        print(f"切换到数据库 {DATABASE_NAME}...")
+        cursor.execute(f"USE `{DATABASE_NAME}`")
+        
+        print("\n执行SQL脚本...")
+        
+        statements = []
+        current_statement = ""
+        in_comment = False
+        
+        for line in sql_content.split("\n"):
+            stripped = line.strip()
+            if not stripped:
+                continue
+            if stripped.startswith("--"):
+                continue
+            if stripped.startswith("/*"):
+                in_comment = True
+                continue
+            if "*/" in stripped:
+                in_comment = False
+                continue
+            if in_comment:
+                continue
+            
+            current_statement += line + "\n"
+            
+            if stripped.endswith(";"):
+                statements.append(current_statement.strip())
+                current_statement = ""
+        
+        success_count = 0
+        table_count = 0
+        
+        for stmt in statements:
+            if not stmt or stmt.strip() == ";":
+                continue
+            try:
+                cursor.execute(stmt)
+                conn.commit()
+                success_count += 1
+                if "CREATE TABLE" in stmt.upper():
+                    table_name = stmt.split("`")[1] if "`" in stmt else "unknown"
+                    print(f"  ✓ 创建表: {table_name}")
+                    table_count += 1
+            except mysql.connector.Error as e:
+                if "already exists" not in str(e).lower():
+                    print(f"  ✗ SQL执行错误: {str(e)[:80]}")
+        
+        print(f"\n表结构创建完成: {table_count} 张表")
+        
+    finally:
+        cursor.close()
+        conn.close()
+
+
+def restore_data():
+    """从备份文件恢复数据"""
+    print("\n" + "=" * 60)
+    print("步骤2: 恢复表数据")
+    print("=" * 60)
+    
+    backup_path = os.path.join(os.path.dirname(__file__), BACKUP_FILE)
+    print(f"读取备份文件: {backup_path}")
+    
+    if not os.path.exists(backup_path):
+        print(f"备份文件不存在: {backup_path}")
+        return
+    
+    with open(backup_path, "r", encoding="utf-8") as f:
+        data = json.load(f)
+    
+    conn = get_connection(with_database=True)
+    cursor = conn.cursor()
+    
+    try:
+        # 禁用外键检查
+        cursor.execute("SET FOREIGN_KEY_CHECKS = 0")
+        print("已禁用外键检查\n")
+        
+        # 恢复 ai_tags
+        tags = data.get("ai_tags", [])
+        print(f"恢复 ai_tags 表 ({len(tags)} 条)...")
+        
+        if tags:
+            for tag in tags:
+                columns = ", ".join(f"`{k}`" for k in tag.keys())
+                placeholders = ", ".join(["%s"] * len(tag))
+                sql = f"INSERT INTO ai_tags ({columns}) VALUES ({placeholders})"
+                try:
+                    cursor.execute(sql, list(tag.values()))
+                except mysql.connector.Error as e:
+                    print(f"  插入错误: {e}")
+            conn.commit()
+            print(f"  ✓ ai_tags 恢复完成")
+        
+        # 恢复 ai_image_tags
+        image_tags = data.get("ai_image_tags", [])
+        print(f"恢复 ai_image_tags 表 ({len(image_tags)} 条)...")
+        
+        if image_tags:
+            success = 0
+            for item in image_tags:
+                columns = ", ".join(f"`{k}`" for k in item.keys())
+                placeholders = ", ".join(["%s"] * len(item))
+                sql = f"INSERT INTO ai_image_tags ({columns}) VALUES ({placeholders})"
+                try:
+                    cursor.execute(sql, list(item.values()))
+                    success += 1
+                except mysql.connector.Error as e:
+                    print(f"  插入错误 (id={item.get('id')}): {e}")
+            conn.commit()
+            print(f"  ✓ ai_image_tags 恢复完成 ({success} 条)")
+        
+        # 恢复外键检查
+        cursor.execute("SET FOREIGN_KEY_CHECKS = 1")
+        print("\n已恢复外键检查")
+        
+    finally:
+        cursor.close()
+        conn.close()
+
+
+def verify_database():
+    """验证数据库"""
+    print("\n" + "=" * 60)
+    print("步骤3: 验证数据库")
+    print("=" * 60)
+    
+    conn = get_connection(with_database=True)
+    cursor = conn.cursor()
+    
+    try:
+        cursor.execute("SHOW TABLES")
+        tables = cursor.fetchall()
+        print(f"\n数据库共有 {len(tables)} 张表")
+        
+        cursor.execute("SELECT COUNT(*) FROM ai_tags")
+        count = cursor.fetchone()[0]
+        print(f"ai_tags 表: {count} 条记录")
+        
+        cursor.execute("SELECT COUNT(*) FROM ai_image_tags")
+        count = cursor.fetchone()[0]
+        print(f"ai_image_tags 表: {count} 条记录")
+        
+        # 显示示例数据
+        cursor.execute("SELECT id, tag_name, department FROM ai_tags LIMIT 3")
+        rows = cursor.fetchall()
+        if rows:
+            print("\nai_tags 示例:")
+            for row in rows:
+                print(f"  ID: {row[0]}, 标签: {row[1][:40]}..., 科室: {row[2]}")
+        
+    finally:
+        cursor.close()
+        conn.close()
+
+
+def backup_current_data():
+    """备份当前数据到 backup_data.json"""
+    print("=" * 60)
+    print("备份当前数据")
+    print("=" * 60)
+    
+    conn = get_connection(with_database=True)
+    cursor = conn.cursor(dictionary=True)
+    
+    try:
+        # 导出 ai_tags
+        cursor.execute('SELECT * FROM ai_tags')
+        tags = cursor.fetchall()
+        print(f"ai_tags: {len(tags)} 条")
+        
+        # 导出 ai_image_tags
+        cursor.execute('SELECT * FROM ai_image_tags')
+        image_tags = cursor.fetchall()
+        print(f"ai_image_tags: {len(image_tags)} 条")
+        
+        # 转换datetime为字符串
+        def convert_datetime(obj):
+            for key, value in obj.items():
+                if hasattr(value, 'isoformat'):
+                    obj[key] = value.isoformat()
+            return obj
+        
+        tags = [convert_datetime(t) for t in tags]
+        image_tags = [convert_datetime(t) for t in image_tags]
+        
+        # 保存为JSON
+        backup_path = os.path.join(os.path.dirname(__file__), BACKUP_FILE)
+        data = {'ai_tags': tags, 'ai_image_tags': image_tags}
+        with open(backup_path, 'w', encoding='utf-8') as f:
+            json.dump(data, f, ensure_ascii=False, indent=2)
+        
+        print(f"\n数据已保存到 {backup_path}")
+        
+    finally:
+        cursor.close()
+        conn.close()
+
+
+def main():
+    print("\n" + "=" * 60)
+    print("           数据库恢复脚本")
+    print("=" * 60)
+    print(f"数据库: {DATABASE_NAME}")
+    print(f"SQL文件: {SQL_FILE}")
+    print(f"备份文件: {BACKUP_FILE}")
+    print("=" * 60)
+    
+    print("\n请选择操作:")
+    print("  1. 完整恢复 (重建结构 + 恢复数据)")
+    print("  2. 仅恢复数据 (保留现有结构)")
+    print("  3. 备份当前数据")
+    print("  0. 取消")
+    
+    choice = input("\n请输入选项 (0-3): ").strip()
+    
+    if choice == "1":
+        confirm = input("\n警告: 此操作将删除并重建数据库！确认? (输入 'yes'): ")
+        if confirm.lower() == "yes":
+            rebuild_database_structure()
+            restore_data()
+            verify_database()
+            print("\n" + "=" * 60)
+            print("数据库恢复完成！")
+            print("=" * 60)
+        else:
+            print("操作已取消")
+            
+    elif choice == "2":
+        restore_data()
+        verify_database()
+        print("\n数据恢复完成！")
+        
+    elif choice == "3":
+        backup_current_data()
+        print("\n备份完成！")
+        
+    else:
+        print("操作已取消")
+
+
+if __name__ == "__main__":
+    main()
--- a/tag_derive_api.py
+++ b/tag_derive_api.py
@@ -251,13 +251,12 @@ class TagDeriveService:
        return ''.join([f'#{t}#' for t in all_tags])
    
    def get_pending_images(self, limit: int = 100) -> List[Dict]:
-        """获取待处理的图片"""
+        """获取待处理的图片（status='tag_extension'）"""
        sql = """
            SELECT it.id, it.image_thumb_url, it.tag_id, it.tag_name, it.department_name
            FROM ai_image_tags it
-            LEFT JOIN ai_tags t ON it.tag_id = t.id
            WHERE it.image_thumb_url != '' AND it.tag_name != ''
-              AND (t.tag_category IS NULL OR t.tag_category != '衍生标签')
+              AND it.status = 'tag_extension'
            ORDER BY it.id
            LIMIT %s
        """
@@ -279,12 +278,15 @@ class TagDeriveService:
            "SELECT COUNT(*) as cnt FROM ai_image_tags WHERE image_thumb_url != ''"
        )['cnt']
        
-        # 已处理数
-        processed = self.db.execute_one("""
-            SELECT COUNT(*) as cnt FROM ai_image_tags it
-            JOIN ai_tags t ON it.tag_id = t.id
-            WHERE t.tag_category = '衍生标签'
-        """)['cnt']
+        # 待处理数（status='tag_extension'）
+        pending = self.db.execute_one(
+            "SELECT COUNT(*) as cnt FROM ai_image_tags WHERE status = 'tag_extension'"
+        )['cnt']
+        
+        # 已处理数（status='manual_review'）
+        processed = self.db.execute_one(
+            "SELECT COUNT(*) as cnt FROM ai_image_tags WHERE status = 'manual_review'"
+        )['cnt']
        
        # 衍生标签数
        derived_count = self.db.execute_one(
@@ -294,7 +296,7 @@ class TagDeriveService:
        return {
            "total_images": total,
            "processed_images": processed,
-            "pending_images": total - processed,
+            "pending_images": pending,
            "derived_tags_count": derived_count
        }

--- a/增加字段.txt
+++ b/增加字段.txt
@@ -1 +0,0 @@
-ALTER TABLE ai_article.ai_image_tags ADD COLUMN derived_tag VARCHAR(1000) NOT NULL DEFAULT '' COMMENT '衍生标签，格式:#标签1##标签2#';
				`@@ -1 +0,0 @@`
				`ALTER TABLE ai_article.ai_image_tags ADD COLUMN derived_tag VARCHAR(1000) NOT NULL DEFAULT '' COMMENT '衍生标签，格式:#标签1##标签2#';`