98 lines
468 KiB
Plaintext
98 lines
468 KiB
Plaintext
{"type":"session","version":3,"id":"06a40d07-2755-4693-b2a1-41a4fb8d1231","timestamp":"2026-05-29T01:23:53.644Z","cwd":"/home/yangxuan/.openclaw/workspace/java"}
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{"type":"model_change","id":"8aa4b1c7","parentId":null,"timestamp":"2026-05-29T01:23:53.708Z","provider":"new-api","modelId":"deepseek-v4-flash"}
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{"type":"thinking_level_change","id":"ef39974c","parentId":"8aa4b1c7","timestamp":"2026-05-29T01:23:53.708Z","thinkingLevel":"off"}
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{"type":"custom","customType":"model-snapshot","data":{"timestamp":1780017833727,"provider":"new-api","modelApi":"openai-completions","modelId":"deepseek-v4-flash"},"id":"f5418b43","parentId":"ef39974c","timestamp":"2026-05-29T01:23:53.727Z"}
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{"type":"message","id":"856db5de","parentId":"f5418b43","timestamp":"2026-05-29T01:23:53.949Z","message":{"role":"user","content":[{"type":"text","text":"[Fri 2026-05-29 09:23 GMT+8] ## 查询近似规则\n\n- 应该要求ai返回名称和规格\n - 根据名称精确查询\n - 根据名称模糊查询\n - 根据规格模糊查询\n - 查询出多条 分析优先级\n帮我分析查询近似的方案"}],"timestamp":1780017833741}}
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{"type":"message","id":"61095d1d","parentId":"856db5de","timestamp":"2026-05-29T01:24:02.312Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user is asking about \"查询近似\" (approximate/typo-tolerant search) solutions. This seems to be about building a search feature that can handle typos or approximate matching for material/product names and specifications. Let me first look at the project structure to understand what they're working on, then analyze and propose a solution.\n\nLet me check the project structure first - they mentioned \"ruoyi-vue-pro\" as a project alias.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_7d268c52f08c4f5cace5863a","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro -type f -name \"*.java\" | xargs grep -l \"近似\\|近似\\|模糊\\|fuzzy\\|approx\\|similar\" 2>/dev/null | head -20","workdir":"/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro -type f -name \\\"*.java\\\" | xargs grep -l \\\"近似\\\\|近似\\\\|模糊\\\\|fuzzy\\\\|approx\\\\|similar\\\" 2>/dev/null | head -20\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro\"}"},{"type":"toolCall","id":"call_ec8e8ff437a74d9392516365","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro -type f -name \"*Material*\" -o -name \"*Product*\" | head -30","workdir":"/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro -type f -name \\\"*Material*\\\" -o -name \\\"*Product*\\\" | head -30\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":14852,"output":326,"cacheRead":0,"cacheWrite":0,"reasoningTokens":90,"totalTokens":15178,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780017834055,"responseId":"chatcmpl-8d20202f-80db-407e-8f1c-fbdce3c62981"}}
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{"type":"message","id":"70bd0656","parentId":"36342331","timestamp":"2026-05-29T01:24:03.651Z","message":{"role":"toolResult","toolCallId":"call_ec8e8ff437a74d9392516365","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/enums/product/IotProductDeviceTypeEnum.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/enums/product/IotProductStatusEnum.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/service/product/IotProductCategoryService.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/service/product/IotProductCategoryServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/service/product/IotProductService.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/service/product/IotProductServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/vo/product/IotProductRespVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/vo/product/IotProductSaveReqVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/vo/product/IotProductPageReqVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/vo/category/IotProductCategoryPageReqVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/vo/category/IotProductCategorySaveReqVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/vo/category/IotProductCategoryRespVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/IotProductController.http\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/IotProductCategoryController.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/IotProductController.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/device/vo/device/IotDeviceByProductKeyAndNamesReqVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/dal/dataobject/product/IotProductDO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/dal/dataobject/product/IotProductCategoryDO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/dal/mysql/product/IotProductMapper.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/dal/mysql/product/IotProductCategoryMapper.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-core/src/main/java/cn/iocoder/yudao/module/iot/core/util/IotProductAuthUtils.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-erp/src/main/java/cn/iocoder/yudao/module/erp/service/product/ErpProductCategoryServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-erp/src/main/java/cn/iocoder/yudao/module/erp/service/product/ErpProductCategoryService.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-erp/src/main/java/cn/iocoder/yudao/module/erp/service/product/ErpProductService.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-erp/src/main/java/cn/iocoder/yudao/module/erp/service/product/ErpProductUnitService.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-erp/src/main/java/cn/iocoder/yudao/module/erp/service/product/ErpProductUnitServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-erp/src/main/java/cn/iocoder/yudao/module/erp/service/product/ErpProductServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-erp/src/main/java/cn/iocoder/yudao/module/erp/controller/admin/product/vo/unit/ErpProductUnitRespVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-erp/src/main/java/cn/iocoder/yudao/module/erp/controller/admin/product/vo/unit/ErpProductUnitSaveReqVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-erp/src/main/java/cn/iocoder/yudao/module/erp/controller/admin/product/vo/unit/ErpProductUnitPageReqVO.java"}],"details":{"status":"completed","exitCode":0,"durationMs":417,"aggregated":"/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/enums/product/IotProductDeviceTypeEnum.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/enums/product/IotProductStatusEnum.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/service/product/IotProductCategoryService.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/service/product/IotProductCategoryServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/service/product/IotProductService.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/service/product/IotProductServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/vo/product/IotProductRespVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/vo/product/IotProductSaveReqVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/vo/product/IotProductPageReqVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/vo/category/IotProductCategoryPageReqVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/vo/category/IotProductCategorySaveReqVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/vo/category/IotProductCategoryRespVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/IotProductController.http\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/IotProductCategoryController.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/product/IotProductController.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/controller/admin/device/vo/device/IotDeviceByProductKeyAndNamesReqVO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/dal/dataobject/product/IotProductDO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/dal/dataobject/product/IotProductCategoryDO.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/dal/mysql/product/IotProductMapper.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-biz/src/main/java/cn/iocoder/yudao/module/iot/dal/mysql/product/IotProductCategoryMapper.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-iot/yudao-module-iot-core/src/main/java/cn/iocoder/yudao/module/iot/core/util/IotProductAuthUtils.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-erp/src/main/java/cn/iocoder/yudao/module/erp/service/product/ErpProductCategoryServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-erp/src/main/java/cn/iocoder/yudao/module/erp/service/product/ErpProductCategoryService.java\n/home/yangxuan/Projects/IdeaProjects/ruoyi-vue-pro/yudao-module-erp/src/main/java/cn/iocoder/yudao/module/erp/service/product/ErpProductService.java\n/home/yangxuan/Projects/IdeaProje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{"type":"message","id":"95e79db7","parentId":"70bd0656","timestamp":"2026-05-29T01:24:06.875Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user is asking about \"近似查询\" (approximate/fuzzy query) for materials, which seems to be related to the tiny-erp project. Let me check the tiny-erp project structure since \"tiny\" is aliased in TOOLS.md. The user seems to be referring to a business requirement - they want an AI to return material name and specification, and query based on exact name match, fuzzy name match, and fuzzy specification match, with priority analysis.\n\nLet me look at the tiny-erp project to understand the material structure.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_4a3fb7998ccb42729969afee","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/tiny-erp -type f \\( -name \"*.java\" -o -name \"*.vue\" -o -name \"*.sql\" -o -name \"*.xml\" \\) | xargs grep -l \"material\\|Material\\|物料\" 2>/dev/null | head -30","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/tiny-erp -type f \\\\( -name \\\"*.java\\\" -o -name \\\"*.vue\\\" -o -name \\\"*.sql\\\" -o -name \\\"*.xml\\\" \\\\) | xargs grep -l \\\"material\\\\|Material\\\\|物料\\\" 2>/dev/null | head -30\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":3042,"output":257,"cacheRead":14848,"cacheWrite":0,"reasoningTokens":110,"totalTokens":18147,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780017843653,"responseId":"chatcmpl-666c57c3-6584-4547-8e11-a28d6c400403"}}
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{"type":"message","id":"6d61b64a","parentId":"95e79db7","timestamp":"2026-05-29T01:24:07.637Z","message":{"role":"toolResult","toolCallId":"call_4a3fb7998ccb42729969afee","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/target/classes/mapper/fin/FundsMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/target/classes/mapper/im/OutboundItemMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/target/classes/mapper/im/StockMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/target/classes/mapper/im/InboundItemMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/target/classes/mapper/md/material/MaterialMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/.idea/workspace.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/.idea/sqldialects.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/.idea/data_source_mapping.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/.idea/dataSources/1c304160-ffc9-498c-98a2-4d88178008e4.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-slow-moving-data.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/22-material-type-dict.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/26-material-last-price.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/21-master-data-init.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/50-inventory.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/30-sales.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/03-fin.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/40-purchase.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/resources/mapper/fin/FundsMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/resources/mapper/im/OutboundItemMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/resources/mapper/im/StockMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/resources/mapper/im/InboundItemMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/resources/mapper/md/material/MaterialMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/mc/order/dto/PurchaseOrderItemSaveReqDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/mc/order/entity/PurchaseOrderItem.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/mc/order/service/impl/PurchaseOrderServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/home/dto/HomeNewsItemDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/home/service/impl/HomeServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/accounts/dto/ArPageRespDTO.java"}],"details":{"status":"completed","exitCode":0,"durationMs":245,"aggregated":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/target/classes/mapper/fin/FundsMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/target/classes/mapper/im/OutboundItemMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/target/classes/mapper/im/StockMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/target/classes/mapper/im/InboundItemMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/target/classes/mapper/md/material/MaterialMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/.idea/workspace.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/.idea/sqldialects.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/.idea/data_source_mapping.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/.idea/dataSources/1c304160-ffc9-498c-98a2-4d88178008e4.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-slow-moving-data.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/22-material-type-dict.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/26-material-last-price.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/21-master-data-init.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/50-inventory.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/30-sales.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/03-fin.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/40-purchase.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/resources/mapper/fin/FundsMapper.xml\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/resources/mapper/im/OutboundIte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{"type":"message","id":"eff3b166","parentId":"6d61b64a","timestamp":"2026-05-29T01:24:15.673Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user wants to discuss \"查询近似规则\" — query similarity rules for material lookup. This is about designing a query approach where:\n1. AI should return name and spec (规格)\n2. Exact match by name\n3. Fuzzy match by name\n4. Fuzzy match by spec\n5. When multiple results are found, analyze priority\n\nLet me look at the material-related code to understand the existing structure.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_6ebd4730cdf74e79a0e1c6fc","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \"*.java\" | xargs grep -l \"Material\" 2>/dev/null | grep -v target | head -20","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \\\"*.java\\\" | xargs grep -l \\\"Material\\\" 2>/dev/null | grep -v target | head -20\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"},{"type":"toolCall","id":"call_2df78806bc9b45d1ac6aa3b2","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \"MaterialMapper*.xml\" | head -5","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \\\"MaterialMapper*.xml\\\" | head -5\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":1248,"output":298,"cacheRead":17664,"cacheWrite":0,"reasoningTokens":84,"totalTokens":19210,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780017847639,"responseId":"chatcmpl-262beced-5dfb-4c7a-91f8-652debcbc368"}}
|
||
{"type":"message","id":"a23a1c3e","parentId":"eff3b166","timestamp":"2026-05-29T01:24:17.048Z","message":{"role":"toolResult","toolCallId":"call_6ebd4730cdf74e79a0e1c6fc","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/mc/order/service/impl/PurchaseOrderServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/home/service/impl/HomeServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/accounts/service/impl/FinAccountsAutoServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/accounts/service/impl/ArServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/accounts/service/impl/ApServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/funds/dto/RawMaterialSlowDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/funds/dto/RawMaterialSlowSummaryDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/funds/dto/SlowMovingInventoryDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/funds/service/impl/FundsServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/funds/controller/FundsController.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/dto/AiRecognitionResultDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/dto/MaterialOutboundSaveReqDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/dto/MaterialOutboundItemReqDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/service/impl/OutboundServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/service/OutboundService.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/controller/OutboundController.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/mapper/OutboundItemMapper.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/inbound/service/impl/InboundServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/inbound/controller/InboundController.java"}],"details":{"status":"completed","exitCode":0,"durationMs":425,"aggregated":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/mc/order/service/impl/PurchaseOrderServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/home/service/impl/HomeServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/accounts/service/impl/FinAccountsAutoServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/accounts/service/impl/ArServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/accounts/service/impl/ApServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/funds/dto/RawMaterialSlowDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/funds/dto/RawMaterialSlowSummaryDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/funds/dto/SlowMovingInventoryDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/funds/service/impl/FundsServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/funds/controller/FundsController.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/dto/AiRecognitionResultDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/dto/MaterialOutboundSaveReqDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/dto/MaterialOutboundItemReqDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/service/impl/OutboundServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/service/OutboundService.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/controller/OutboundController.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/mapper/OutboundItemMapper.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/inbound/service/impl/InboundServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/inbound/controller/InboundController.java","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780017857047}}
|
||
{"type":"message","id":"a86eedda","parentId":"a23a1c3e","timestamp":"2026-05-29T01:24:17.048Z","message":{"role":"toolResult","toolCallId":"call_2df78806bc9b45d1ac6aa3b2","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/resources/mapper/md/material/MaterialMapper.xml"}],"details":{"status":"completed","exitCode":0,"durationMs":426,"aggregated":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/resources/mapper/md/material/MaterialMapper.xml","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780017857048}}
|
||
{"type":"message","id":"d51fca2b","parentId":"a86eedda","timestamp":"2026-05-29T01:24:31.465Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Let me look at the existing MaterialMapper and the material-related DTOs and service code to understand the current data model before proposing the \"查询近似\" (query similar/approximate) solution.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_4098995ada9249c180b40fbb","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/resources/mapper/md/material/MaterialMapper.xml"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/resources/mapper/md/material/MaterialMapper.xml\"}"},{"type":"toolCall","id":"call_8915d4ffbe7942918c794c5e","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \"*.java\" | xargs grep -l \"MaterialDO\\|MaterialEntity\\|MaterialVO\\|materialMapper\\|MaterialService\" 2>/dev/null | grep -v target | sort -u","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \\\"*.java\\\" | xargs grep -l \\\"MaterialDO\\\\|MaterialEntity\\\\|MaterialVO\\\\|materialMapper\\\\|MaterialService\\\" 2>/dev/null | grep -v target | sort -u\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":1251,"output":231,"cacheRead":18688,"cacheWrite":0,"reasoningTokens":40,"totalTokens":20170,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780017857049,"responseId":"chatcmpl-399ebe10-19ee-4890-a83b-45826d2b8b4a"}}
|
||
{"type":"message","id":"b611f52e","parentId":"d51fca2b","timestamp":"2026-05-29T01:24:32.798Z","message":{"role":"toolResult","toolCallId":"call_4098995ada9249c180b40fbb","toolName":"read","content":[{"type":"text","text":"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<!DOCTYPE mapper PUBLIC \"-//mybatis.org//DTD Mapper 3.0//EN\" \"http://mybatis.org/dtd/mybatis-3-mapper.dtd\">\n<mapper namespace=\"com.witsoft.erp.module.md.material.mapper.MaterialMapper\">\n\n</mapper>"}],"isError":false,"timestamp":1780017872798}}
|
||
{"type":"message","id":"0752cae8","parentId":"b611f52e","timestamp":"2026-05-29T01:24:32.799Z","message":{"role":"toolResult","toolCallId":"call_8915d4ffbe7942918c794c5e","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/accounts/service/impl/FinAccountsAutoServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/inbound/service/impl/InboundServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/service/impl/OutboundServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/stock/service/impl/StockServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/stock/service/impl/StockTransactionServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/stocktake/service/impl/StocktakeServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/controller/MaterialController.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/MaterialService.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialFillServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialSelectorServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialServiceImpl.java"}],"details":{"status":"completed","exitCode":0,"durationMs":436,"aggregated":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/fin/accounts/service/impl/FinAccountsAutoServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/inbound/service/impl/InboundServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/outbound/service/impl/OutboundServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/stock/service/impl/StockServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/stock/service/impl/StockTransactionServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/stocktake/service/impl/StocktakeServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/controller/MaterialController.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/MaterialService.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialFillServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialSelectorServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialServiceImpl.java","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780017872798}}
|
||
{"type":"message","id":"bcdd921b","parentId":"0752cae8","timestamp":"2026-05-29T01:24:36.474Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Let me look at the Material-related service files, especially the AI recognition service, MaterialSelectorService, and Material service to understand the current query patterns.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_af1e35c7f6164298936b0e01","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialSelectorServiceImpl.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialSelectorServiceImpl.java\"}"},{"type":"toolCall","id":"call_d45ad4c7299e427da601a3c4","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java\"}"},{"type":"toolCall","id":"call_839245f782314f138c33f6ca","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/dto/AiRecognitionResultDTO.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/dto/AiRecognitionResultDTO.java\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":964,"output":243,"cacheRead":19712,"cacheWrite":0,"reasoningTokens":30,"totalTokens":20919,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780017872956,"responseId":"chatcmpl-aaf764de-2611-459d-922c-f798b2f85f63"}}
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{"type":"message","id":"81b18261","parentId":"bcdd921b","timestamp":"2026-05-29T01:24:37.988Z","message":{"role":"toolResult","toolCallId":"call_af1e35c7f6164298936b0e01","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.md.material.service.impl;\n\nimport com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;\nimport com.baomidou.mybatisplus.extension.plugins.pagination.Page;\nimport com.witsoft.erp.module.im.inbound.mapper.InboundItemMapper;\nimport com.witsoft.erp.module.im.outbound.mapper.OutboundItemMapper;\nimport com.witsoft.erp.module.im.stock.dto.StockPageDTO;\nimport com.witsoft.erp.module.im.stock.entity.Stock;\nimport com.witsoft.erp.module.im.stock.mapper.StockMapper;\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\nimport com.witsoft.erp.module.md.material.dto.MaterialSelectorReqDTO;\nimport com.witsoft.erp.module.md.material.entity.Material;\nimport com.witsoft.erp.module.md.material.mapper.MaterialMapper;\nimport com.witsoft.erp.module.md.material.service.MaterialFillService;\nimport com.witsoft.erp.module.md.material.service.MaterialSelectorService;\nimport lombok.RequiredArgsConstructor;\nimport org.springframework.stereotype.Service;\nimport org.springframework.util.StringUtils;\n\nimport java.math.BigDecimal;\nimport java.util.*;\nimport java.util.stream.Collectors;\n\n/**\n * 物料选择器 Service 实现\n */\n@Service\n@RequiredArgsConstructor\npublic class MaterialSelectorServiceImpl implements MaterialSelectorService {\n\n private final MaterialMapper materialMapper;\n private final MaterialFillService materialFillService;\n private final InboundItemMapper inboundItemMapper;\n private final OutboundItemMapper outboundItemMapper;\n private final StockMapper stockMapper;\n\n @Override\n public Page<StockPageDTO> pageInboundMaterial(MaterialSelectorReqDTO reqDTO) {\n Long categoryId = reqDTO.getCategoryId();\n String keyword = reqDTO.getKeyword();\n int pageNum = reqDTO.getPageNum() != null ? reqDTO.getPageNum() : 1;\n int pageSize = reqDTO.getPageSize() != null ? reqDTO.getPageSize() : 10;\n\n // 常用物料：近 30 天入库条目最多的 10 个物料\n if (categoryId != null && categoryId == 0L) {\n List<Long> recentIds = inboundItemMapper.selectRecentMaterialIds();\n if (recentIds.isEmpty()) {\n return new Page<>(pageNum, pageSize, 0);\n }\n return queryInboundMaterialByIds(recentIds, keyword);\n }\n\n // 按分类筛选 + 关键字：直接查 md_material（不受库存数量限制）\n // 入库场景需要展示所有可用物料，包括从未入库的新物料\n Long count = stockMapper.countInboundMaterialPage(categoryId, keyword);\n if (count == null || count == 0) {\n return new Page<>(pageNum, pageSize, 0);\n }\n\n int offset = (pageNum - 1) * pageSize;\n List<StockPageDTO> records = stockMapper.selectInboundMaterialPage(categoryId, keyword, offset, pageSize);\n\n // 补充物料显示信息（materialInfoMap 中有物料类型名称、安全库存等额外字段）\n List<Long> materialIds = records.stream()\n .map(StockPageDTO::getMaterialId)\n .collect(Collectors.toList());\n Map<Long, MaterialInfoDTO> infoMap = materialFillService.getMaterialInfoMap(materialIds);\n \n // 批量查询上次单价\n Map<Long, BigDecimal> inboundPriceMap = queryLastInboundPrices(materialIds);\n Map<Long, BigDecimal> outboundPriceMap = queryLastOutboundPrices(materialIds);\n \n for (StockPageDTO dto : records) {\n MaterialInfoDTO info = infoMap.get(dto.getMaterialId());\n if (info != null) {\n dto.setMaterialTypeName(info.getMaterialTypeName());\n dto.setMinSafeQty(info.getMinSafeQty());\n dto.setCategoryName(info.getCategoryName());\n }\n // 填充上次单价\n dto.setLastInboundPrice(inboundPriceMap.get(dto.getMaterialId()));\n dto.setLastOutboundPrice(outboundPriceMap.get(dto.getMaterialId()));\n }\n\n Page<StockPageDTO> resultPage = new Page<>(pageNum, pageSize, count);\n resultPage.setRecords(records);\n return resultPage;\n }\n\n @Override\n public Page<StockPageDTO> pageOutboundMaterial(MaterialSelectorReqDTO reqDTO) {\n Long categoryId = reqDTO.getCategoryId();\n String keyword = reqDTO.getKeyword();\n Long warehouseId = reqDTO.getWarehouseId();\n int pageNum = reqDTO.getPageNum() != null ? reqDTO.getPageNum() : 1;\n int pageSize = reqDTO.getPageSize() != null ? reqDTO.getPageSize() : 10;\n\n // 常用物料：近 30 天出库条目最多的 10 个物料\n if (categoryId != null && categoryId == 0L) {\n List<Long> recentIds = outboundItemMapper.selectRecentMaterialIds();\n if (recentIds.isEmpty()) {\n return new Page<>(pageNum, pageSize, 0);\n }\n return queryOutboundMaterialByIds(recentIds, keyword, warehouseId);\n }\n\n // 按分类筛选 + 关键字：XML 联表分页查询\n Long count = stockMapper.countStockPage(categoryId, keyword, warehouseId);\n if (count == null || count == 0) {\n return new Page<>(pageNum, pageSize, 0);\n }\n\n int offset = (pageNum - 1) * pageSize;\n List<StockPageDTO> records = stockMapper.selectStockPage(categoryId, keyword, warehouseId, offset, pageSize);\n\n // 补充物料显示信息（materialInfoMap 中有物料类型名称、安全库存等额外字段）\n List<Long> materialIds = records.stream()\n .map(StockPageDTO::getMaterialId)\n .collect(Collectors.toList());\n Map<Long, MaterialInfoDTO> infoMap = materialFillService.getMaterialInfoMap(materialIds);\n \n // 批量查询上次单价\n Map<Long, BigDecimal> inboundPriceMap = queryLastInboundPrices(materialIds);\n Map<Long, BigDecimal> outboundPriceMap = queryLastOutboundPrices(materialIds);\n \n for (StockPageDTO dto : records) {\n MaterialInfoDTO info = infoMap.get(dto.getMaterialId());\n if (info != null) {\n dto.setMaterialTypeName(info.getMaterialTypeName());\n dto.setMinSafeQty(info.getMinSafeQty());\n dto.setCategoryName(info.getCategoryName());\n }\n // 填充上次单价\n dto.setLastInboundPrice(inboundPriceMap.get(dto.getMaterialId()));\n dto.setLastOutboundPrice(outboundPriceMap.get(dto.getMaterialId()));\n }\n\n Page<StockPageDTO> resultPage = new Page<>(pageNum, pageSize, count);\n resultPage.setRecords(records);\n return resultPage;\n }\n\n /**\n * 根据物料 ID 列表查询入库物料（im_stock JOIN md_material），支持关键字过滤\n * 入库场景不限制仓库，查询所有仓库的库存\n */\n private Page<StockPageDTO> queryInboundMaterialByIds(List<Long> materialIds, String keyword) {\n // 从 im_stock 查询这些物料的库存记录（所有仓库，不限制库存数量）\n // 入库场景不禁用 quantity > 0，新入库或库存已清零的物料也需要展示\n LambdaQueryWrapper<Stock> wrapper = new LambdaQueryWrapper<>();\n wrapper.in(Stock::getMaterialId, materialIds);\n wrapper.eq(Stock::getDeleted, 0);\n\n List<Stock> stocks = stockMapper.selectList(wrapper);\n if (stocks.isEmpty()) {\n // 如果库存表中没有记录，将物料作为新物料返回（库存为 0）\n return buildEmptyStockPage(materialIds, keyword);\n }\n\n // 获取物料信息\n List<Long> ids = stocks.stream()\n .map(Stock::getMaterialId)\n .collect(Collectors.toList());\n Map<Long, MaterialInfoDTO> infoMap = materialFillService.getMaterialInfoMap(ids);\n \n // 批量查询上次单价\n Map<Long, BigDecimal> inboundPriceMap = queryLastInboundPrices(ids);\n Map<Long, BigDecimal> outboundPriceMap = queryLastOutboundPrices(ids);\n\n // 按传入 ID 顺序排序（与最近使用频次一致）\n Map<Long, Integer> orderMap = new HashMap<>();\n for (int i = 0; i < materialIds.size(); i++) {\n orderMap.put(materialIds.get(i), i);\n }\n stocks.sort(Comparator.comparingInt(s -> orderMap.getOrDefault(s.getMaterialId(), Integer.MAX_VALUE)));\n\n // 关键字过滤（内存中过滤）\n List<StockPageDTO> dtoList = stocks.stream()\n .map(s -> {\n StockPageDTO dto = buildStockPageDTOFromStock(s, infoMap.get(s.getMaterialId()));\n // 填充上次单价\n dto.setLastInboundPrice(inboundPriceMap.get(s.getMaterialId()));\n dto.setLastOutboundPrice(outboundPriceMap.get(s.getMaterialId()));\n return dto;\n })\n .filter(dto -> !StringUtils.hasText(keyword) || matchesKeyword(dto, keyword))\n .collect(Collectors.toList());\n\n Page<StockPageDTO> resultPage = new Page<>(1, dtoList.isEmpty() ? 10 : dtoList.size(), dtoList.size());\n resultPage.setRecords(dtoList);\n return resultPage;\n }\n\n /**\n * 根据物料 ID 列表查询出库物料（im_stock），支持关键字和仓库过滤\n */\n private Page<StockPageDTO> queryOutboundMaterialByIds(List<Long> materialIds, String keyword, Long warehouseId) {\n LambdaQueryWrapper<Stock> wrapper = new LambdaQueryWrapper<>();\n wrapper.in(Stock::getMaterialId, materialIds);\n wrapper.gt(Stock::getQuantity, BigDecimal.ZERO);\n wrapper.eq(Stock::getDeleted, 0);\n if (warehouseId != null) {\n wrapper.eq(Stock::getWarehouseId, warehouseId);\n }\n\n List<Stock> stocks = stockMapper.selectList(wrapper);\n if (stocks.isEmpty()) {\n return new Page<>(1, 10, 0);\n }\n\n // 获取物料信息\n List<Long> ids = stocks.stream()\n .map(Stock::getMaterialId)\n .collect(Collectors.toList());\n Map<Long, MaterialInfoDTO> infoMap = materialFillService.getMaterialInfoMap(ids);\n \n // 批量查询上次单价\n Map<Long, BigDecimal> inboundPriceMap = queryLastInboundPrices(ids);\n Map<Long, BigDecimal> outboundPriceMap = queryLastOutboundPrices(ids);\n\n // 按传入 ID 顺序排序\n Map<Long, Integer> orderMap = new HashMap<>();\n for (int i = 0; i < materialIds.size(); i++) {\n orderMap.put(materialIds.get(i), i);\n }\n stocks.sort(Comparator.comparingInt(s -> orderMap.getOrDefault(s.getMaterialId(), Integer.MAX_VALUE)));\n\n // 关键字过滤（内存中过滤）\n List<StockPageDTO> dtoList = stocks.stream()\n .map(s -> {\n StockPageDTO dto = buildStockPageDTOFromStock(s, infoMap.get(s.getMaterialId()));\n // 填充上次单价\n dto.setLastInboundPrice(inboundPriceMap.get(s.getMaterialId()));\n dto.setLastOutboundPrice(outboundPriceMap.get(s.getMaterialId()));\n return dto;\n })\n .filter(dto -> !StringUtils.hasText(keyword) || matchesKeyword(dto, keyword))\n .collect(Collectors.toList());\n\n Page<StockPageDTO> resultPage = new Page<>(1, dtoList.isEmpty() ? 10 : dtoList.size(), dtoList.size());\n resultPage.setRecords(dtoList);\n return resultPage;\n }\n\n /**\n * 当库存表中没有记录时，从物料表直接查询返回（库存为 0）\n * 用于入库场景展示从未入库过的新物料\n */\n private Page<StockPageDTO> buildEmptyStockPage(List<Long> materialIds, String keyword) {\n // 从 md_material 查询物料信息\n List<Material> materials = materialMapper.selectBatchIds(materialIds);\n if (materials.isEmpty()) {\n return new Page<>(1, 10, 0);\n }\n\n // 获取额外信息\n List<Long> ids = materials.stream()\n .map(Material::getId)\n .collect(Collectors.toList());\n Map<Long, MaterialInfoDTO> infoMap = materialFillService.getMaterialInfoMap(ids);\n\n // 按传入 ID 顺序排序\n Map<Long, Integer> orderMap = new HashMap<>();\n for (int i = 0; i < materialIds.size(); i++) {\n orderMap.put(materialIds.get(i), i);\n }\n materials.sort(Comparator.comparingInt(m -> orderMap.getOrDefault(m.getId(), Integer.MAX_VALUE)));\n\n // 关键字过滤（内存中过滤）\n List<StockPageDTO> dtoList = materials.stream()\n .map(m -> buildStockPageDTOFromMaterial(m, infoMap.get(m.getId())))\n .filter(dto -> !StringUtils.hasText(keyword) || matchesKeyword(dto, keyword))\n .collect(Collectors.toList());\n\n Page<StockPageDTO> resultPage = new Page<>(1, dtoList.isEmpty() ? 10 : dtoList.size(), dtoList.size());\n resultPage.setRecords(dtoList);\n return resultPage;\n }\n\n /**\n * 从 Material 和 MaterialInfoDTO 构建 StockPageDTO\n */\n private StockPageDTO buildStockPageDTOFromMaterial(Material material, MaterialInfoDTO info) {\n StockPageDTO dto = new StockPageDTO();\n dto.setId(material.getId()); // 使用物料 ID 作为唯一 ID，前端用作 key\n dto.setMaterialId(material.getId());\n dto.setMaterialCode(material.getMaterialCode());\n dto.setMaterialName(material.getMaterialName());\n dto.setSpec(material.getSpec());\n dto.setUnit(material.getUnit());\n dto.setMaterialType(material.getMaterialType());\n dto.setCategoryId(material.getCategoryId());\n if (info != null) {\n dto.setMaterialTypeName(info.getMaterialTypeName());\n dto.setCategoryName(info.getCategoryName());\n dto.setMinSafeQty(info.getMinSafeQty());\n }\n return dto;\n }\n\n /**\n * 从 Stock 和 MaterialInfoDTO 构建 StockPageDTO\n */\n private StockPageDTO buildStockPageDTOFromStock(Stock stock, MaterialInfoDTO info) {\n StockPageDTO dto = new StockPageDTO();\n dto.setId(stock.getId());\n dto.setWarehouseId(stock.getWarehouseId());\n dto.setMaterialId(stock.getMaterialId());\n dto.setQuantity(stock.getQuantity());\n if (info != null) {\n dto.setMaterialCode(info.getMaterialCode());\n dto.setMaterialName(info.getMaterialName());\n dto.setSpec(info.getSpec());\n dto.setUnit(info.getUnit());\n dto.setMaterialType(info.getMaterialType());\n dto.setMaterialTypeName(info.getMaterialTypeName());\n dto.setCategoryId(info.getCategoryId());\n dto.setCategoryName(info.getCategoryName());\n dto.setMinSafeQty(info.getMinSafeQty());\n }\n return dto;\n }\n\n /**\n * 关键字匹配（物料编码/名称/规格）\n */\n private boolean matchesKeyword(StockPageDTO dto, String keyword) {\n if (!StringUtils.hasText(keyword)) {\n return true;\n }\n String kw = keyword.toLowerCase();\n return (dto.getMaterialCode() != null && dto.getMaterialCode().toLowerCase().contains(kw))\n || (dto.getMaterialName() != null && dto.getMaterialName().toLowerCase().contains(kw))\n || (dto.getSpec() != null && dto.getSpec().toLowerCase().contains(kw));\n }\n\n /**\n * 批量查询物料的上次采购入库单价\n * @param materialIds 物料 ID 列表\n * @return Map<物料 ID, 上次入库单价>\n */\n private Map<Long, BigDecimal> queryLastInboundPrices(List<Long> materialIds) {\n if (materialIds == null || materialIds.isEmpty()) {\n return Collections.emptyMap();\n }\n // 从 md_material 表查询 last_inbound_price\n List<Material> materials = materialMapper.selectBatchIds(materialIds);\n return materials.stream()\n .filter(m -> m.getLastInboundPrice() != null)\n .collect(Collectors.toMap(Material::getId, Material::getLastInboundPrice));\n }\n\n /**\n * 批量查询物料的上次销售出库单价\n * @param materialIds 物料 ID 列表\n * @return Map<物料 ID, 上次出库单价>\n */\n private Map<Long, BigDecimal> queryLastOutboundPrices(List<Long> materialIds) {\n if (materialIds == null || materialIds.isEmpty()) {\n return Collections.emptyMap();\n }\n // 从 md_material 表查询 last_outbound_price\n List<Material> materials = materialMapper.selectBatchIds(materialIds);\n return materials.stream()\n .filter(m -> m.getLastOutboundPrice() != null)\n .collect(Collectors.toMap(Material::getId, Material::getLastOutboundPrice));\n }\n}\n"}],"isError":false,"timestamp":1780017877988}}
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{"type":"message","id":"65803083","parentId":"81b18261","timestamp":"2026-05-29T01:24:37.989Z","message":{"role":"toolResult","toolCallId":"call_d45ad4c7299e427da601a3c4","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.ai.service.impl;\n\nimport com.witsoft.erp.common.core.BusinessException;\nimport com.witsoft.erp.module.ai.dto.*;\nimport com.witsoft.erp.module.ai.service.AiRecognitionService;\nimport com.witsoft.erp.module.ai.service.AiService;\nimport com.witsoft.erp.module.md.customer.entity.Customer;\nimport com.witsoft.erp.module.md.customer.service.CustomerService;\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\nimport com.witsoft.erp.module.md.material.entity.Material;\nimport com.witsoft.erp.module.md.material.service.MaterialFillService;\nimport com.witsoft.erp.module.md.material.service.MaterialService;\nimport com.witsoft.erp.module.md.supplier.entity.Supplier;\nimport com.witsoft.erp.module.md.supplier.service.SupplierService;\nimport lombok.RequiredArgsConstructor;\nimport lombok.extern.slf4j.Slf4j;\nimport org.springframework.stereotype.Service;\nimport org.springframework.web.multipart.MultipartFile;\n\nimport java.math.BigDecimal;\nimport java.util.*;\nimport java.util.stream.Collectors;\n\n/**\n * AI 单据识别服务实现\n *\n * 流程：\n * 1. 调用 AI 识别单据图片\n * 2. 解析 AI 返回的 JSON\n * 3. 单据类型：purchase_inbound → typeValue=10, typeName=采购入库\n * 4. 模糊匹配供应商/客户（去空格 + 分词片段 + 降级匹配）\n * 5. 模糊匹配物料（去空格 + 分词 + MaterialFillService 填充）\n * 6. 返回前端可用的 id + name\n */\n@Slf4j\n@Service\n@RequiredArgsConstructor\npublic class AiRecognitionServiceImpl implements AiRecognitionService {\n\n private final AiService aiService;\n private final SupplierService supplierService;\n private final CustomerService customerService;\n private final MaterialService materialService;\n private final MaterialFillService materialFillService;\n\n private static final String RECOGNITION_PROMPT =\n \"请识别图片中的单据内容，严格按照 JSON 格式返回，不要包含 Markdown 代码块标记，不要有其他文字。\\n\" +\n \"\\n\" +\n \"如果是采购入库单/到货单，格式如下：\\n\" +\n \"{\\n\" +\n \" \\\"type\\\": \\\"purchase_inbound\\\",\\n\" +\n \" \\\"supplier_name\\\": \\\"供应商名称\\\",\\n\" +\n \" \\\"warehouse_name\\\": \\\"仓库名称（可选）\\\",\\n\" +\n \" \\\"date\\\": \\\"日期\\\",\\n\" +\n \" \\\"total_amount\\\": 总金额,\\n\" +\n \" \\\"remark\\\": \\\"备注\\\",\\n\" +\n \" \\\"items\\\": [\\n\" +\n \" {\\n\" +\n \" \\\"material_name\\\": \\\"物料名称\\\",\\n\" +\n \" \\\"spec\\\": \\\"规格（可选）\\\",\\n\" +\n \" \\\"quantity\\\": 数量,\\n\" +\n \" \\\"unit\\\": \\\"单位（可选）\\\",\\n\" +\n \" \\\"price\\\": 单价\\n\" +\n \" }\\n\" +\n \" ]\\n\" +\n \"}\\n\" +\n \"\\n\" +\n \"如果是销售出库单，格式如下：\\n\" +\n \"{\\n\" +\n \" \\\"type\\\": \\\"sales_outbound\\\",\\n\" +\n \" \\\"customer_name\\\": \\\"客户名称\\\",\\n\" +\n \" \\\"warehouse_name\\\": \\\"仓库名称（可选）\\\",\\n\" +\n \" \\\"date\\\": \\\"日期\\\",\\n\" +\n \" \\\"total_amount\\\": 总金额,\\n\" +\n \" \\\"remark\\\": \\\"备注\\\",\\n\" +\n \" \\\"items\\\": [\\n\" +\n \" {\\n\" +\n \" \\\"material_name\\\": \\\"物料名称\\\",\\n\" +\n \" \\\"spec\\\": \\\"规格（可选）\\\",\\n\" +\n \" \\\"quantity\\\": 数量,\\n\" +\n \" \\\"unit\\\": \\\"单位（可选）\\\",\\n\" +\n \" \\\"price\\\": 单价\\n\" +\n \" }\\n\" +\n \" ]\\n\" +\n \"}\";\n\n @Override\n public AiRecognitionResultDTO recognize(MultipartFile file) {\n // 1. 调用 AI 识别图片\n AiChatResponseDTO aiResponse = aiService.chatWithImages(RECOGNITION_PROMPT, Collections.singletonList(file));\n String rawReply = aiResponse.getReply();\n log.info(\"AI 识别原始回复：{}\", rawReply);\n\n // 2. 提取 JSON\n String json = extractJson(rawReply);\n if (json == null) {\n throw new BusinessException(500, \"AI 回复格式异常，无法解析为 JSON\");\n }\n\n // 3. 解析 JSON\n Map<String, Object> parsed = parseSimpleJson(json);\n String type = (String) parsed.get(\"type\");\n if (type == null) {\n throw new BusinessException(400, \"AI 未能识别单据类型\");\n }\n\n // 4. 转换单据类型 → 字典值\n Integer typeValue = toTypeValue(type);\n String typeName = toTypeName(typeValue);\n\n // 5. 构建返回结果\n AiRecognitionResultDTO.AiRecognitionResultDTOBuilder builder = AiRecognitionResultDTO.builder()\n .typeValue(typeValue)\n .typeName(typeName)\n .warehouseName((String) parsed.get(\"warehouse_name\"))\n .remark((String) parsed.get(\"remark\"));\n\n // 6. 模糊匹配供应商或客户（去空格 + 分词片段匹配）\n if (\"purchase_inbound\".equals(type)) {\n String supplierName = (String) parsed.get(\"supplier_name\");\n if (supplierName != null) {\n builder.counterparty(matchSupplier(supplierName));\n }\n } else if (\"sales_outbound\".equals(type)) {\n String customerName = (String) parsed.get(\"customer_name\");\n if (customerName != null) {\n builder.counterparty(matchCustomer(customerName));\n }\n }\n\n // 7. 模糊匹配物料明细（去空格 + 分词 + MaterialFillService 填充）\n @SuppressWarnings(\"unchecked\")\n List<Map<String, Object>> rawItems = (List<Map<String, Object>>) parsed.get(\"items\");\n if (rawItems != null && !rawItems.isEmpty()) {\n List<AiRecognitionResultDTO.RecognitionItem> items = rawItems.stream()\n .map(this::matchMaterialItem)\n .filter(Objects::nonNull)\n .collect(Collectors.toList());\n builder.items(items);\n }\n\n return builder.build();\n }\n\n // ========== 单据类型转换 ==========\n\n private static final Map<String, Integer> TYPE_MAPPING = Map.of(\n \"purchase_inbound\", 10,\n \"sales_outbound\", 10\n );\n\n private static final Map<Integer, String> TYPE_NAME_MAPPING = Map.of(\n 10, \"采购入库\",\n 20, \"退货入库\",\n 30, \"其他入库\"\n );\n\n private Integer toTypeValue(String type) {\n return TYPE_MAPPING.getOrDefault(type, 10);\n }\n\n private String toTypeName(Integer typeValue) {\n if (typeValue == null) return null;\n // 入库类型\n if (typeValue == 10) return \"采购入库\";\n if (typeValue == 20) return \"退货入库\";\n if (typeValue == 30) return \"其他入库\";\n return null;\n }\n\n // ========== 模糊匹配供应商/客户（去空格 + 分词） ==========\n\n private AiRecognitionResultDTO.Counterparty matchSupplier(String recognizedName) {\n return matchCounterparty(recognizedName,\n keyword -> supplierService.searchByNameLike(keyword),\n s -> AiRecognitionResultDTO.Counterparty.builder()\n .id(s.getId()).name(s.getName()));\n }\n\n private AiRecognitionResultDTO.Counterparty matchCustomer(String recognizedName) {\n return matchCounterparty(recognizedName,\n keyword -> customerService.searchByNameLike(keyword),\n c -> AiRecognitionResultDTO.Counterparty.builder()\n .id(c.getId()).name(c.getName()));\n }\n\n /**\n * 通用模糊匹配：\n * 1. 直接 LIKE 搜索（AI 识别的名称与原版去空格后 LIKE）\n * 2. 如果无结果，分词后每个片段单独 LIKE\n * 3. 如果仍无结果，返回原始名称（exactMatch=false）\n */\n private <T> AiRecognitionResultDTO.Counterparty matchCounterparty(\n String recognizedName,\n FuzzySearch<T> searcher,\n java.util.function.Function<T, AiRecognitionResultDTO.Counterparty.CounterpartyBuilder> mapper) {\n\n // 归一化：去空格\n String normalized = normalizeName(recognizedName);\n log.debug(\"供应商/客户模糊匹配：原始='{}', 归一='{}'\", recognizedName, normalized);\n\n // 1. 直接 LIKE 搜索（使用归一化后的名称）\n List<T> candidates = searcher.search(normalized);\n if (!candidates.isEmpty()) {\n T best = candidates.get(0);\n return mapper.apply(best)\n .recognizedName(recognizedName)\n .exactMatch(true)\n .build();\n }\n\n // 2. 分词后每个片段单独搜索\n List<String> tokens = tokenize(normalized);\n if (tokens.size() >= 2) {\n // 用最长分段词搜索\n String longestToken = tokens.stream()\n .max(Comparator.comparingInt(String::length))\n .orElse(\"\");\n if (longestToken.length() >= 2) {\n candidates = searcher.search(longestToken);\n if (!candidates.isEmpty()) {\n T best = candidates.get(0);\n return mapper.apply(best)\n .recognizedName(recognizedName)\n .exactMatch(false)\n .build();\n }\n }\n\n // 两个词组合搜索\n for (int i = 0; i < tokens.size() && candidates.isEmpty(); i++) {\n for (int j = i + 1; j < tokens.size(); j++) {\n String combined = tokens.get(i) + tokens.get(j).replace(tokens.get(i), \"\");\n if (combined.length() >= 2) {\n candidates = searcher.search(combined);\n if (!candidates.isEmpty()) break;\n }\n }\n }\n if (!candidates.isEmpty()) {\n T best = candidates.get(0);\n return mapper.apply(best)\n .recognizedName(recognizedName)\n .exactMatch(false)\n .build();\n }\n }\n\n // 3. 完全无法匹配，返回识别到的原始名称\n return AiRecognitionResultDTO.Counterparty.builder()\n .name(recognizedName)\n .recognizedName(recognizedName)\n .exactMatch(false)\n .build();\n }\n\n @FunctionalInterface\n private interface FuzzySearch<T> {\n List<T> search(String keyword);\n }\n\n // ========== 模糊匹配物料（去空格 + 分词 + MaterialFillService 填充） ==========\n\n private AiRecognitionResultDTO.RecognitionItem matchMaterialItem(Map<String, Object> raw) {\n String materialName = (String) raw.get(\"material_name\");\n String spec = (String) raw.get(\"spec\");\n Object qtyObj = raw.get(\"quantity\");\n Object priceObj = raw.get(\"price\");\n String unit = (String) raw.get(\"unit\");\n\n if (materialName == null || materialName.trim().isEmpty()) {\n return null;\n }\n\n BigDecimal quantity = toBigDecimal(qtyObj);\n BigDecimal price = toBigDecimal(priceObj);\n\n // 模糊匹配物料（多重降级）\n String normalized = normalizeName(materialName);\n\n List<Material> candidates = materialService.searchByNameLike(normalized);\n\n // 如果 combined 无结果，尝试只搜物料名称（去空格后）\n if (candidates.isEmpty() && spec != null) {\n candidates = materialService.searchByNameLike(normalized + \" \" + spec.replaceAll(\"\\\\s+\", \"\"));\n }\n\n // 如果仍无结果，分词匹配（按非字母数字分割）\n if (candidates.isEmpty()) {\n List<String> tokens = tokenize(normalized);\n // 依次用最长片段搜索\n tokens.sort((a, b) -> Integer.compare(b.length(), a.length()));\n for (String token : tokens) {\n if (token.length() >= 2) {\n candidates = materialService.searchByNameLike(token);\n if (!candidates.isEmpty()) break;\n }\n }\n }\n\n // 如果仍无结果，尝试数字+汉字分离匹配（如\"8.5玻璃棒\"→搜\"玻璃棒\"）\n if (candidates.isEmpty()) {\n String[] parts = normalized.split(\"(?<=\\\\d)(?=\\\\D)|(?<=\\\\D)(?=\\\\d)\");\n // 用最长的汉字片段搜索\n List<String> chineseParts = new ArrayList<>();\n for (String part : parts) {\n if (part.codePoints().anyMatch(cp -> Character.isIdeographic(cp))) {\n chineseParts.add(part);\n }\n }\n chineseParts.sort((a, b) -> Integer.compare(b.length(), a.length()));\n for (String cp : chineseParts) {\n if (cp.length() >= 2) {\n candidates = materialService.searchByNameLike(cp);\n if (!candidates.isEmpty()) break;\n }\n }\n }\n\n if (candidates.isEmpty()) {\n // 完全无法匹配：返回 AI 识别的原始信息\n return AiRecognitionResultDTO.RecognitionItem.builder()\n .materialName(materialName)\n .spec(spec)\n .recognizedName(materialName)\n .quantity(quantity)\n\n⚠️ [... middle content omitted — showing head and tail ...]\n\n }\n return null;\n }\n\n @SuppressWarnings(\"unchecked\")\n private Map<String, Object> parseSimpleJson(String json) {\n Map<String, Object> result = new LinkedHashMap<>();\n json = json.trim();\n if (json.startsWith(\"{\") && json.endsWith(\"}\")) {\n json = json.substring(1, json.length() - 1).trim();\n }\n List<String> segments = splitTopLevel(json);\n for (String seg : segments) {\n int colonIdx = seg.indexOf(':');\n if (colonIdx < 0) continue;\n String key = seg.substring(0, colonIdx).trim();\n String value = seg.substring(colonIdx + 1).trim();\n key = unquote(key);\n if (value.startsWith(\"\\\"\")) {\n result.put(key, unquote(value));\n } else if (value.startsWith(\"[\")) {\n result.put(key, parseArray(value));\n } else if (value.startsWith(\"{\")) {\n result.put(key, parseSimpleJson(value));\n } else if (value.equals(\"null\")) {\n result.put(key, null);\n } else {\n try {\n if (value.contains(\".\")) {\n result.put(key, new BigDecimal(value));\n } else {\n result.put(key, Long.parseLong(value));\n }\n } catch (NumberFormatException e) {\n result.put(key, value);\n }\n }\n }\n return result;\n }\n\n private List<Map<String, Object>> parseArray(String arrayStr) {\n List<Map<String, Object>> list = new ArrayList<>();\n arrayStr = arrayStr.trim();\n if (arrayStr.startsWith(\"[\") && arrayStr.endsWith(\"]\")) {\n arrayStr = arrayStr.substring(1, arrayStr.length() - 1).trim();\n }\n int braceDepth = 0;\n int start = 0;\n for (int i = 0; i < arrayStr.length(); i++) {\n char c = arrayStr.charAt(i);\n if (c == '{') braceDepth++;\n else if (c == '}') braceDepth--;\n else if (c == ',' && braceDepth == 0) {\n String item = arrayStr.substring(start, i).trim();\n if (!item.isEmpty()) list.add(parseSimpleJson(item));\n start = i + 1;\n }\n }\n String last = arrayStr.substring(start).trim();\n if (!last.isEmpty()) list.add(parseSimpleJson(last));\n return list;\n }\n\n private List<String> splitTopLevel(String s) {\n List<String> parts = new ArrayList<>();\n int depth = 0, bracketDepth = 0;\n boolean inString = false;\n int start = 0;\n for (int i = 0; i < s.length(); i++) {\n char c = s.charAt(i);\n if (c == '\"' && (i == 0 || s.charAt(i - 1) != '\\\\')) inString = !inString;\n else if (!inString) {\n if (c == '{') depth++;\n else if (c == '}') depth--;\n else if (c == '[') bracketDepth++;\n else if (c == ']') bracketDepth--;\n else if (c == ',' && depth == 0 && bracketDepth == 0) {\n parts.add(s.substring(start, i));\n start = i + 1;\n }\n }\n }\n String last = s.substring(start).trim();\n if (!last.isEmpty()) parts.add(last);\n return parts;\n }\n\n private String unquote(String s) {\n s = s.trim();\n if (s.startsWith(\"\\\"\") && s.endsWith(\"\\\"\")) {\n return s.substring(1, s.length() - 1);\n }\n return s;\n }\n\n private BigDecimal toBigDecimal(Object obj) {\n if (obj == null) return null;\n if (obj instanceof BigDecimal) return (BigDecimal) obj;\n if (obj instanceof Number) return BigDecimal.valueOf(((Number) obj).doubleValue());\n if (obj instanceof String) {\n try { return new BigDecimal((String) obj); }\n catch (NumberFormatException e) { return null; }\n }\n return null;\n }\n}[... 2662 more characters truncated]"}],"isError":false,"timestamp":1780017877988}}
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{"type":"message","id":"d8c74839","parentId":"65803083","timestamp":"2026-05-29T01:24:37.989Z","message":{"role":"toolResult","toolCallId":"call_839245f782314f138c33f6ca","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.ai.dto;\n\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\nimport lombok.AllArgsConstructor;\nimport lombok.Builder;\nimport lombok.Data;\nimport lombok.NoArgsConstructor;\n\nimport java.math.BigDecimal;\nimport java.util.List;\n\n/**\n * AI 识别单据返回 DTO\n * 供前端自动填充表单\n *\n * typeValue/typeName 使用数据字典格式（10-采购入库 / 10-销售出库）\n * counterparty 返回 name（供前端填充输入框）\n * items 使用 MaterialInfoDTO 风格字段（materialCode/spec/unit）\n */\n@Data\n@Builder\n@NoArgsConstructor\n@AllArgsConstructor\npublic class AiRecognitionResultDTO {\n\n /** 单据类型字典值（10-采购入库，20-退货入库 / 10-销售出库，20-领料出库） */\n private Integer typeValue;\n\n /** 单据类型名称（采购入库 / 销售出库） */\n private String typeName;\n\n /** 供应商/客户（含 id + name） */\n private Counterparty counterparty;\n\n /** 仓库名称（可选） */\n private String warehouseName;\n\n /** 备注 */\n private String remark;\n\n /** 物料明细 */\n private List<RecognitionItem> items;\n\n @Data\n @Builder\n @NoArgsConstructor\n @AllArgsConstructor\n public static class Counterparty {\n /** 匹配到的 ID */\n private Long id;\n /** 匹配到的名称（数据库中名称，前端直接填充） */\n private String name;\n /** AI 识别的原始名称 */\n private String recognizedName;\n /** 是否精确匹配 */\n private boolean exactMatch;\n }\n\n @Data\n @Builder\n @NoArgsConstructor\n @AllArgsConstructor\n public static class RecognitionItem {\n /** 匹配到的物料 ID */\n private Long materialId;\n /** 物料名称 */\n private String materialName;\n /** 物料编码（来自 MaterialInfoDTO） */\n private String materialCode;\n /** 规格 */\n private String spec;\n /** 单位（来自 MaterialInfoDTO） */\n private String unit;\n /** AI 识别的原始名称 */\n private String recognizedName;\n /** 数量 */\n private BigDecimal quantity;\n /** 单价 */\n private BigDecimal price;\n /** 是否精确匹配 */\n private boolean exactMatch;\n }\n}"}],"isError":false,"timestamp":1780017877989}}
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{"type":"message","id":"0d349d2b","parentId":"d8c74839","timestamp":"2026-05-29T01:24:41.677Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now let me look at the MaterialService to see what search methods are available, and also the Material entity to understand the data structure.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_5b1e143a7e1c4a7fbbae3bd8","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/MaterialService.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/MaterialService.java\"}"},{"type":"toolCall","id":"call_d5b8e58ea1af4dd1bebfaf56","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialServiceImpl.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialServiceImpl.java\"}"},{"type":"toolCall","id":"call_9ab786cf893541c884d74468","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \"Material.java\" | head -5","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \\\"Material.java\\\" | head -5\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":9553,"output":259,"cacheRead":20480,"cacheWrite":0,"reasoningTokens":27,"totalTokens":30292,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780017878144,"responseId":"chatcmpl-198206b0-70d4-42d8-a358-3163207f3e86"}}
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{"type":"message","id":"6a7624fd","parentId":"0d349d2b","timestamp":"2026-05-29T01:24:43.553Z","message":{"role":"toolResult","toolCallId":"call_5b1e143a7e1c4a7fbbae3bd8","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.md.material.service;\r\n\r\nimport com.baomidou.mybatisplus.extension.plugins.pagination.Page;\r\nimport com.baomidou.mybatisplus.extension.service.IService;\r\nimport com.witsoft.erp.module.md.material.dto.MaterialPageDTO;\r\nimport com.witsoft.erp.module.md.material.dto.MaterialPageQueryReqDTO;\r\nimport com.witsoft.erp.module.md.material.entity.Material;\r\n\r\nimport java.math.BigDecimal;\r\nimport java.util.List;\r\n\r\n/**\r\n * 物料服务接口\r\n */\r\npublic interface MaterialService extends IService<Material> {\r\n\r\n /**\r\n * 分页查询物料（带库存数量、分类名称）\r\n *\r\n * @param reqDTO 查询参数\r\n * @return 分页结果\r\n */\r\n Page<MaterialPageDTO> pageWithStock(MaterialPageQueryReqDTO reqDTO);\r\n\r\n /**\r\n * 根据关键字搜索物料 ID 列表（匹配编码、名称、规格）\r\n *\r\n * @param keyword 关键字\r\n * @return 匹配的物料 ID 列表\r\n */\r\n List<Long> searchMaterialIdsByKeyword(String keyword);\r\n\r\n /**\r\n * 根据关键字模糊搜索物料（返回完整实体）\r\n *\r\n * @param keyword 关键字\r\n * @return 匹配的物料列表\r\n */\r\n List<Material> searchByNameLike(String keyword);\r\n\r\n}\r\n"}],"isError":false,"timestamp":1780017883553}}
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{"type":"message","id":"a73e0772","parentId":"6a7624fd","timestamp":"2026-05-29T01:24:43.554Z","message":{"role":"toolResult","toolCallId":"call_d5b8e58ea1af4dd1bebfaf56","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.md.material.service.impl;\r\n\r\nimport com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;\r\nimport com.baomidou.mybatisplus.extension.plugins.pagination.Page;\r\nimport com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;\r\nimport com.witsoft.erp.module.md.material.dto.MaterialPageDTO;\r\nimport com.witsoft.erp.module.md.material.dto.MaterialPageQueryReqDTO;\r\nimport com.witsoft.erp.module.md.material.entity.Material;\r\nimport com.witsoft.erp.module.md.material.mapper.MaterialMapper;\r\nimport com.witsoft.erp.module.md.material.service.MaterialService;\r\nimport com.witsoft.erp.module.md.material.service.MaterialFillService;\r\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\r\nimport com.witsoft.erp.module.im.stock.entity.Stock;\r\nimport com.witsoft.erp.module.im.stock.service.StockService;\r\nimport lombok.RequiredArgsConstructor;\r\nimport lombok.extern.slf4j.Slf4j;\r\nimport org.springframework.stereotype.Service;\r\nimport org.springframework.util.StringUtils;\r\n\r\nimport java.math.BigDecimal;\r\nimport java.util.Collections;\r\nimport java.util.HashMap;\r\nimport java.util.List;\r\nimport java.util.Map;\r\nimport java.util.stream.Collectors;\r\n\r\nimport static com.witsoft.erp.common.util.LikeEscapeUtil.escapeLike;\r\n\r\n/**\r\n * 物料服务实现类\r\n */\r\n@Slf4j\r\n@Service\r\n@RequiredArgsConstructor\r\npublic class MaterialServiceImpl extends ServiceImpl<MaterialMapper, Material> implements MaterialService {\r\n\r\n private final MaterialMapper materialMapper;\r\n private final StockService stockService;\r\n private final MaterialFillService materialFillService;\r\n\r\n @Override\r\n public Page<MaterialPageDTO> pageWithStock(MaterialPageQueryReqDTO reqDTO) {\r\n int pageNum = reqDTO.getPageNum() != null ? reqDTO.getPageNum() : 1;\r\n int pageSize = reqDTO.getPageSize() != null ? reqDTO.getPageSize() : 10;\r\n \r\n // 1. 构建查询条件\r\n LambdaQueryWrapper<Material> queryWrapper = new LambdaQueryWrapper<>();\r\n \r\n // 分类筛选\r\n if (reqDTO.getCategoryId() != null) {\r\n queryWrapper.eq(Material::getCategoryId, reqDTO.getCategoryId());\r\n }\r\n \r\n // 状态筛选（默认查询有效物料）\r\n // status filter (this version)\r\n \r\n // 关键字模糊查询（支持特殊字符 % _ - 转义）\r\n String keyword = reqDTO.getKeyword();\r\n if (StringUtils.hasText(keyword)) {\r\n String escaped = escapeLike(keyword);\r\n queryWrapper.and(wrapper -> wrapper\r\n .apply(\"material_code LIKE {0}\", \"%\" + escaped + \"%\")\r\n .or()\r\n .apply(\"material_name LIKE {0}\", \"%\" + escaped + \"%\")\r\n .or()\r\n .apply(\"spec LIKE {0}\", \"%\" + escaped + \"%\")\r\n );\r\n }\r\n \r\n // 按创建时间降序\r\n queryWrapper.orderByDesc(Material::getCreateTime);\r\n \r\n // 2. 分页查询物料\r\n Page<Material> page = this.page(new Page<>(pageNum, pageSize), queryWrapper);\r\n \r\n // 3. 批量查询库存（按物料 ID）- 可选\r\n final Map<Long, BigDecimal> stockMap;\r\n Boolean withStock = reqDTO.getWithStock() != null ? reqDTO.getWithStock() : true;\r\n if (withStock) {\r\n final List<Long> materialIds = page.getRecords().stream()\r\n .map(Material::getId)\r\n .collect(Collectors.toList());\r\n \r\n if (!materialIds.isEmpty()) {\r\n List<Stock> stocks = stockService.list(new LambdaQueryWrapper<Stock>()\r\n .in(Stock::getMaterialId, materialIds));\r\n stockMap = stocks.stream()\r\n .collect(Collectors.toMap(Stock::getMaterialId, Stock::getQuantity, (v1, v2) -> v1));\r\n } else {\r\n stockMap = new HashMap<>();\r\n }\r\n } else {\r\n stockMap = new HashMap<>();\r\n }\r\n \r\n // 4. 使用公共填充服务获取物料信息\r\n List<Long> materialIds = page.getRecords().stream()\r\n .map(Material::getId)\r\n .collect(Collectors.toList());\r\n Map<Long, MaterialInfoDTO> materialInfoMap = materialFillService.getMaterialInfoMap(materialIds);\r\n \r\n // 5. 填充 DTO\r\n List<MaterialPageDTO> dtoList = page.getRecords().stream().map(material -> {\r\n MaterialPageDTO dto = new MaterialPageDTO();\r\n dto.setId(material.getId());\r\n dto.setMaterialCode(material.getMaterialCode());\r\n dto.setMaterialName(material.getMaterialName());\r\n dto.setSpec(material.getSpec());\r\n dto.setUnit(material.getUnit());\r\n dto.setCategoryId(material.getCategoryId());\r\n \r\n // 使用公共填充的物料信息\r\n MaterialInfoDTO info = materialInfoMap.get(material.getId());\r\n if (info != null) {\r\n dto.setCategoryName(info.getCategoryName());\r\n dto.setMaterialType(material.getMaterialType());\r\n dto.setMaterialTypeName(info.getMaterialTypeName());\r\n }\r\n \r\n dto.setStockQty(stockMap.getOrDefault(material.getId(), BigDecimal.ZERO));\r\n dto.setPrice(material.getPrice());\r\n dto.setStatus(material.getStatus());\r\n dto.setRemark(material.getRemark());\r\n return dto;\r\n }).collect(Collectors.toList());\r\n \r\n // 6. 构建分页结果\r\n Page<MaterialPageDTO> resultPage = new Page<>(pageNum, pageSize, page.getTotal());\r\n resultPage.setRecords(dtoList);\r\n \r\n return resultPage;\r\n }\r\n\r\n @Override\r\n public List<Long> searchMaterialIdsByKeyword(String keyword) {\r\n if (!StringUtils.hasText(keyword)) {\r\n return Collections.emptyList();\r\n }\r\n String escaped = escapeLike(keyword);\r\n LambdaQueryWrapper<Material> wrapper = new LambdaQueryWrapper<>();\r\n wrapper.and(w -> w\r\n .apply(\"material_code LIKE {0}\", \"%\" + escaped + \"%\")\r\n .or()\r\n .apply(\"material_name LIKE {0}\", \"%\" + escaped + \"%\")\r\n .or()\r\n .apply(\"spec LIKE {0}\", \"%\" + escaped + \"%\")\r\n );\r\n wrapper.select(Material::getId);\r\n return list(wrapper).stream()\r\n .map(Material::getId)\r\n .collect(Collectors.toList());\r\n }\r\n\r\n @Override\r\n public List<Material> searchByNameLike(String keyword) {\r\n if (!StringUtils.hasText(keyword)) {\r\n return Collections.emptyList();\r\n }\r\n String escaped = escapeLike(keyword);\r\n LambdaQueryWrapper<Material> wrapper = new LambdaQueryWrapper<>();\r\n wrapper.and(w -> w\r\n .apply(\"material_code LIKE {0}\", \"%\" + escaped + \"%\")\r\n .or()\r\n .apply(\"material_name LIKE {0}\", \"%\" + escaped + \"%\")\r\n .or()\r\n .apply(\"spec LIKE {0}\", \"%\" + escaped + \"%\")\r\n );\r\n wrapper.last(\"LIMIT 20\");\r\n return list(wrapper);\r\n }\r\n\r\n}\r\n"}],"isError":false,"timestamp":1780017883553}}
|
||
{"type":"message","id":"4aa06963","parentId":"a73e0772","timestamp":"2026-05-29T01:24:43.555Z","message":{"role":"toolResult","toolCallId":"call_9ab786cf893541c884d74468","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/entity/Material.java"}],"details":{"status":"completed","exitCode":0,"durationMs":214,"aggregated":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/entity/Material.java","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780017883554}}
|
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{"type":"message","id":"e45a7a3a","parentId":"4aa06963","timestamp":"2026-05-29T01:25:02.016Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Let me understand what the user is asking about. They want to implement a \"查询近似\" (find similar/approximate materials) feature. The requirements are:\n\n1. AI should return name and spec\n2. Exact match by name\n3. Fuzzy match by name\n4. Fuzzy match by spec\n5. When multiple results found, analyze priority\n\nLet me look at the Material entity to understand the fields we're working with.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_98ab0871ed06496491bf9e4f","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/entity/Material.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/entity/Material.java\"}"},{"type":"toolCall","id":"call_e72284ef44414b2d934f6623","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/dto/MaterialInfoDTO.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/dto/MaterialInfoDTO.java\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":2652,"output":232,"cacheRead":29952,"cacheWrite":0,"reasoningTokens":89,"totalTokens":32836,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780017883718,"responseId":"chatcmpl-bfeb5569-2b40-46d5-adb8-d40b6eb098c0"}}
|
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{"type":"message","id":"777b5840","parentId":"e45a7a3a","timestamp":"2026-05-29T01:25:02.941Z","message":{"role":"toolResult","toolCallId":"call_98ab0871ed06496491bf9e4f","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.md.material.entity;\r\n\r\nimport com.baomidou.mybatisplus.annotation.TableField;\r\nimport com.witsoft.erp.common.entity.BaseEntity;\r\nimport com.baomidou.mybatisplus.annotation.TableName;\r\nimport lombok.Data;\r\nimport lombok.EqualsAndHashCode;\r\n\r\nimport java.math.BigDecimal;\r\n\r\n/**\r\n * 物料实体\r\n */\r\n@Data\r\n@EqualsAndHashCode(callSuper = true)\r\n@TableName(\"md_material\")\r\npublic class Material extends BaseEntity {\r\n\r\n private static final long serialVersionUID = 1L;\r\n\r\n /**\r\n * 物料编码\r\n */\r\n private String materialCode;\r\n\r\n /**\r\n * 物料名称\r\n */\r\n private String materialName;\r\n\r\n /**\r\n * 规格型号\r\n */\r\n private String spec;\r\n\r\n /**\r\n * 物料分类 ID\r\n */\r\n private Long categoryId;\r\n\r\n /**\r\n * 物料类型（P-原材料，SA-半成品，FG-成品）\r\n */\r\n private String materialType;\r\n\r\n /**\r\n * 单位\r\n */\r\n private String unit;\r\n\r\n /**\r\n * 参考单价\r\n */\r\n private BigDecimal price;\r\n\r\n /**\r\n * 最小安全库存（0-未设置）\r\n */\r\n private BigDecimal minSafeQty;\r\n\r\n /**\r\n * 物料状态（0-有效，1-无效）\r\n */\r\n private Integer status;\r\n\r\n /**\r\n * 备注\r\n */\r\n private String remark;\r\n\r\n /**\r\n * 上次销售出库单价（用于销售出库自动带价）\r\n */\r\n private BigDecimal lastOutboundPrice;\r\n\r\n /**\r\n * 上次采购入库单价（用于采购入库自动带价）\r\n */\r\n private BigDecimal lastInboundPrice;\r\n\r\n}\r\n"}],"isError":false,"timestamp":1780017902941}}
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{"type":"message","id":"b90eba71","parentId":"777b5840","timestamp":"2026-05-29T01:25:02.941Z","message":{"role":"toolResult","toolCallId":"call_e72284ef44414b2d934f6623","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.md.material.dto;\n\nimport lombok.Data;\n\nimport java.io.Serializable;\nimport java.math.BigDecimal;\n\n/**\n * 物料信息 DTO（用于列表填充）\n */\n@Data\npublic class MaterialInfoDTO implements Serializable {\n\n private static final long serialVersionUID = 1L;\n\n /**\n * 物料 ID\n */\n private Long id;\n\n /**\n * 物料编码\n */\n private String materialCode;\n\n /**\n * 物料名称\n */\n private String materialName;\n\n /**\n * 规格型号\n */\n private String spec;\n\n /**\n * 单位\n */\n private String unit;\n\n /**\n * 物料类型（P-原材料，SA-半成品，FG-成品）\n */\n private String materialType;\n\n /**\n * 物料类型名称\n */\n private String materialTypeName;\n\n /**\n * 分类 ID\n */\n private Long categoryId;\n\n /**\n * 分类名称\n */\n private String categoryName;\n\n /**\n * 最小安全库存\n */\n private BigDecimal minSafeQty;\n}\n"}],"isError":false,"timestamp":1780017902941}}
|
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{"type":"message","id":"1da0c85a","parentId":"b90eba71","timestamp":"2026-05-29T01:25:07.417Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now I have a good understanding of the existing codebase. Let me also look at the DB schema to understand the material table structure better, and see how the existing LIKE search is implemented.\n\nLet me look at the current `searchByNameLike` method more closely and understand what the user is asking for. They want:\n\n1. AI should return name and spec (识别时)\n2. Exact name match\n3. Fuzzy name match (LIKE)\n4. Fuzzy spec match (LIKE)\n5. If multiple results found, analyze priority\n\nLet me read the relevant table schema to understand the data.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_61abefce586844c7a615b71e","name":"exec","arguments":{"command":"grep -A 30 \"md_material\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/00-init.sql 2>/dev/null || grep -A 30 \"md_material\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/02-tables.sql 2>/dev/null","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"grep -A 30 \\\"md_material\\\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/00-init.sql 2>/dev/null || grep -A 30 \\\"md_material\\\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/02-tables.sql 2>/dev/null\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"},{"type":"toolCall","id":"call_f06968d1b9dd48c7bd7dc084","name":"exec","arguments":{"command":"grep -l \"md_material\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/*.sql 2>/dev/null | head -5","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"grep -l \\\"md_material\\\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/*.sql 2>/dev/null | head -5\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":1005,"output":377,"cacheRead":32512,"cacheWrite":0,"reasoningTokens":122,"totalTokens":33894,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780017902944,"responseId":"chatcmpl-27a769d6-ba61-4549-836d-934239c16c7f"}}
|
||
{"type":"message","id":"63c1aab8","parentId":"1da0c85a","timestamp":"2026-05-29T01:25:08.579Z","message":{"role":"toolResult","toolCallId":"call_61abefce586844c7a615b71e","toolName":"exec","content":[{"type":"text","text":"\n\n(Command exited with code 2)"}],"details":{"status":"completed","exitCode":2,"durationMs":4,"aggregated":"\n\n(Command exited with code 2)","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780017908578}}
|
||
{"type":"message","id":"72e4d427","parentId":"63c1aab8","timestamp":"2026-05-29T01:25:08.580Z","message":{"role":"toolResult","toolCallId":"call_f06968d1b9dd48c7bd7dc084","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/21-master-data-init.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/26-material-last-price.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-slow-moving-data.sql"}],"details":{"status":"completed","exitCode":0,"durationMs":419,"aggregated":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/21-master-data-init.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/26-material-last-price.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-slow-moving-data.sql","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780017908579}}
|
||
{"type":"message","id":"921d5ac4","parentId":"72e4d427","timestamp":"2026-05-29T01:25:12.961Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now I have a good understanding of the project. Let me look at the MaterialSelectorReqDTO to understand the keyword search feature as well.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_4e27d877c92c40b2bf0de2df","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \"MaterialSelectorReqDTO.java\" | head -5","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \\\"MaterialSelectorReqDTO.java\\\" | head -5\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"},{"type":"toolCall","id":"call_14ab9aa261224b4188ce7a00","name":"exec","arguments":{"command":"grep -n \"CREATE TABLE\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/00-init.sql 2>/dev/null || grep -rn \"md_material\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/ --include=\"*.sql\" | grep -i \"create\\|table\" | head -5","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"grep -n \\\"CREATE TABLE\\\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/00-init.sql 2>/dev/null || grep -rn \\\"md_material\\\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/ --include=\\\"*.sql\\\" | grep -i \\\"create\\\\|table\\\" | head -5\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":650,"output":280,"cacheRead":33280,"cacheWrite":0,"reasoningTokens":28,"totalTokens":34210,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780017908861,"responseId":"chatcmpl-f8c01ea5-8bbe-485f-9b23-aa96dfe8ab10"}}
|
||
{"type":"message","id":"162880e6","parentId":"921d5ac4","timestamp":"2026-05-29T01:25:14.338Z","message":{"role":"toolResult","toolCallId":"call_4e27d877c92c40b2bf0de2df","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/dto/MaterialSelectorReqDTO.java"}],"details":{"status":"completed","exitCode":0,"durationMs":422,"aggregated":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/dto/MaterialSelectorReqDTO.java","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780017914337}}
|
||
{"type":"message","id":"7b3cc08b","parentId":"162880e6","timestamp":"2026-05-29T01:25:14.338Z","message":{"role":"toolResult","toolCallId":"call_14ab9aa261224b4188ce7a00","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql:11:DROP TABLE IF EXISTS md_material_category;\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql:12:CREATE TABLE md_material_category (\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql:28:COMMENT ON TABLE md_material_category IS '物料分类表';\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql:37:COMMENT ON COLUMN md_material_category.create_time IS '创建时间';\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql:43:CREATE INDEX idx_md_material_category_parent_ecid ON md_material_category(parent_id, ecid);"}],"details":{"status":"completed","exitCode":0,"durationMs":422,"aggregated":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql:11:DROP TABLE IF EXISTS md_material_category;\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql:12:CREATE TABLE md_material_category (\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql:28:COMMENT ON TABLE md_material_category IS '物料分类表';\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql:37:COMMENT ON COLUMN md_material_category.create_time IS '创建时间';\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/20-master-data.sql:43:CREATE INDEX idx_md_material_category_parent_ecid ON md_material_category(parent_id, ecid);","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780017914338}}
|
||
{"type":"message","id":"9c5b3045","parentId":"7b3cc08b","timestamp":"2026-05-29T01:25:28.235Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Let me understand the user's request. They're looking at the \"查询近似\" (query similar/similarity search) problem from the AI recognition flow. They want the AI to return name and spec, then match against materials using:\n1. Exact match on name\n2. Fuzzy match on name\n3. Fuzzy match on spec\n4. When multiple results are found, analyze priority\n\nLet me first understand the current state of the code and then analyze the existing query logic to provide a comprehensive analysis.\n\nLooking at the existing code:\n\n1. **MaterialServiceImpl.searchByNameLike()** - current approach:\n - Single SQL query with `material_code LIKE %keyword%` OR `material_name LIKE %keyword%` OR `spec LIKE %keyword%`\n - Uses `escapeLike()` to escape SQL special characters\n - Returns up to 20 results\n - **No prioritization** - all matched via OR, no ranking\n\n2. **MaterialSelectorServiceImpl.matchesKeyword()** - keyword filter:\n - Also matches across code, name, spec fields\n - Just contains() check after lowercase conversion\n - No scoring/prioritization\n\n3. **AiRecognitionServiceImpl.matchMaterialItem()** - AI recognition matching:\n - Multiple fallback strategies: full name → name+spec → token match → number-Han split\n - But the underlying `searchByNameLike()` still does the same flat LIKE across all three fields\n - No scoring\n\nThe problem: When multiple results match, there's no prioritization. For example, searching \"玻璃棒 8.5\" might return:\n- \"玻璃棒\" with spec \"8.5*100mm\" (best match)\n- \"玻璃棒\" with spec \"10*150mm\" (worse)\n- \"玻璃烧杯 8.5\" (worse)\n\nCurrent code doesn't rank by relevance - it's just \"whoever comes back from the DB first\" (which is unpredictable with OR conditions).\n\nLet me think about the best approach for this:\n\n**Problem Analysis:**\n- The current `searchByNameLike` does a flat LIKE on code/name/spec with `OR` — no priority scoring\n- When multiple results come back, there's no way to tell which one is the best match\n- For AI recognition, this means the first result is taken blindly\n\n**Solution Options:**\n\n### Option 1: Multi-phase query with priority scoring\n1. First try exact name match (highest priority)\n2. Then try name-like match (medium)\n3. Then try spec-match (lower)\n4. Deduplicate and rank\n\n### Option 2: Single query with ORDER BY CASE scoring\n```sql\nSELECT *\nFROM md_material\nWHERE name LIKE %kw% OR spec LIKE %kw%\nORDER BY \n CASE \n WHEN name = 'keyword' THEN 0 -- exact name match\n WHEN name LIKE 'keyword%' THEN 1 -- name prefix\n WHEN name LIKE '%keyword%' THEN 2 -- name contains\n WHEN spec LIKE '%keyword%' THEN 3 -- spec contains\n ELSE 4\n END\nLIMIT 20\n```\n\n### Option 3: Application-layer scoring\nReturn all candidates, then in Java rank them by:\n- Exact name match > name contains > spec contains\n- Prefer where name matches more tokens\n- Prefer where spec matches\n\nLet me now look at what the user actually wants to understand better. The request says:\n- \"应该要求ai返回名称和规格\" - AI should return name AND spec\n- \"根据名称精确查询\" - Exact match on name\n- \"根据名称模糊查询\" - Fuzzy match on name \n- \"根据规格模糊查询\" - Fuzzy match on spec\n- \"查询出多条 分析优先级\" - Multiple results, analyze priority\n\nSo they want a multi-strategy approach where we:\n1. Force the AI to return both name and spec\n2. Try multiple query strategies with priority\n3. Return scored/ranked results\n\nLet me look at what the current code does more closely, then provide the analysis and suggestion.\n\nLet me look at a few more files to understand the full picture.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_c523ea24ea484140924a1f95","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/dto/MaterialSelectorReqDTO.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/dto/MaterialSelectorReqDTO.java\"}"},{"type":"toolCall","id":"call_0ccd5a29925f445a86cae1e8","name":"exec","arguments":{"command":"grep -rn \"searchByNameLike\\|searchMaterialIdsByKeyword\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/src --include=\"*.java\" | grep -v target","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"grep -rn \\\"searchByNameLike\\\\|searchMaterialIdsByKeyword\\\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/src --include=\\\"*.java\\\" | grep -v target\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":663,"output":1055,"cacheRead":33792,"cacheWrite":0,"reasoningTokens":873,"totalTokens":35510,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780017914340,"responseId":"chatcmpl-a84fec30-a470-41e7-bf2d-e562409a37a5"}}
|
||
{"type":"message","id":"a024e81f","parentId":"9c5b3045","timestamp":"2026-05-29T01:25:29.418Z","message":{"role":"toolResult","toolCallId":"call_c523ea24ea484140924a1f95","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.md.material.dto;\n\nimport com.witsoft.erp.common.core.PageQuery;\nimport lombok.Data;\nimport lombok.EqualsAndHashCode;\n\n/**\n * 物料选择器请求 DTO\n */\n@Data\n@EqualsAndHashCode(callSuper = true)\npublic class MaterialSelectorReqDTO extends PageQuery {\n\n /**\n * 物料分类 ID（0=常用物料，>0=按分类筛选）\n */\n private Long categoryId;\n\n /**\n * 关键字（物料编码/名称/规格）\n */\n private String keyword;\n\n /**\n * 仓库 ID（出库场景必填）\n */\n private Long warehouseId;\n\n}"}],"isError":false,"timestamp":1780017929417}}
|
||
{"type":"message","id":"e8e2600e","parentId":"a024e81f","timestamp":"2026-05-29T01:25:29.418Z","message":{"role":"toolResult","toolCallId":"call_0ccd5a29925f445a86cae1e8","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java:175: keyword -> supplierService.searchByNameLike(keyword),\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java:182: keyword -> customerService.searchByNameLike(keyword),\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java:281: List<Material> candidates = materialService.searchByNameLike(normalized);\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java:285: candidates = materialService.searchByNameLike(normalized + \" \" + spec.replaceAll(\"\\\\s+\", \"\"));\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java:295: candidates = materialService.searchByNameLike(token);\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java:314: candidates = materialService.searchByNameLike(cp);\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/stock/service/impl/StockServiceImpl.java:112: List<Long> matchedMaterialIds = materialMapper.searchMaterialIdsByKeyword(dto.getKeyword());\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/stock/service/impl/StockServiceImpl.java:225: List<Long> ids = materialMapper.searchMaterialIdsByKeyword(dto.getKeyword());\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/customer/service/impl/CustomerServiceImpl.java:73: public List<Customer> searchByNameLike(String keyword) {\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/customer/service/CustomerService.java:46: List<Customer> searchByNameLike(String keyword);\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/supplier/service/SupplierService.java:45: List<Supplier> searchByNameLike(String keyword);\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/supplier/service/impl/SupplierServiceImpl.java:103: public List<Supplier> searchByNameLike(String keyword) {\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialServiceImpl.java:135: public List<Long> searchMaterialIdsByKeyword(String keyword) {\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialServiceImpl.java:155: public List<Material> searchByNameLike(String keyword) {\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/MaterialService.java:31: List<Long> searchMaterialIdsByKeyword(String keyword);\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/MaterialService.java:39: List<Material> searchByNameLike(String keyword);\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/mapper/MaterialMapper.java:26: default List<Long> searchMaterialIdsByKeyword(String keyword) {"}],"details":{"status":"completed","exitCode":0,"durationMs":429,"aggregated":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java:175: keyword -> supplierService.searchByNameLike(keyword),\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java:182: keyword -> customerService.searchByNameLike(keyword),\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java:281: List<Material> candidates = materialService.searchByNameLike(normalized);\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java:285: candidates = materialService.searchByNameLike(normalized + \" \" + spec.replaceAll(\"\\\\s+\", \"\"));\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java:295: candidates = materialService.searchByNameLike(token);\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java:314: candidates = materialService.searchByNameLike(cp);\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/stock/service/impl/StockServiceImpl.java:112: List<Long> matchedMaterialIds = materialMapper.searchMaterialIdsByKeyword(dto.getKeyword());\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/im/stock/service/impl/StockServiceImpl.java:225: List<Long> ids = materialMapper.searchMaterialIdsByKeyword(dto.getKeyword());\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/customer/service/impl/CustomerServiceImpl.java:73: public List<Customer> searchByNameLike(String keyword) {\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/customer/service/CustomerService.java:46: List<Customer> searchByNameLike(String keyword);\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/supplier/service/SupplierService.java:45: List<Supplier> searchByNameLike(String keyword);\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/supplier/service/impl/SupplierServiceImpl.java:103: public List<Supplier> searchByNameLike(String keyword) {\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialServiceImpl.java:135: public List<Long> searchMaterialIdsByKeyword(String keyword) {\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialServiceImpl.java:155: public List<Material> searchByNameLike(String keyword) {\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/MaterialService.java:31: List<Long> searchMaterialIdsByKeyword(String keyword);\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/MaterialService.java:39: List<Material> searchByNameLike(String keyword);\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/mapper/MaterialMapper.java:26: default List<Long> searchMaterialIdsByKeyword(String keyword) {","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780017929418}}
|
||
{"type":"message","id":"6adcc7b5","parentId":"e8e2600e","timestamp":"2026-05-29T01:25:32.576Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now I have a good understanding of the existing codebase. Let me also check the MaterialMapper and LikeEscapeUtil, then look at the customer and supplier implementations for comparison.\n\nLet me read the MaterialMapper to see the `searchMaterialIdsByKeyword` default method.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_50be0a1038084b649c3a759f","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/mapper/MaterialMapper.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/mapper/MaterialMapper.java\"}"},{"type":"toolCall","id":"call_4d47ea19647d4e97ac05b221","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/common/util/LikeEscapeUtil.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/common/util/LikeEscapeUtil.java\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":1415,"output":195,"cacheRead":34304,"cacheWrite":0,"reasoningTokens":55,"totalTokens":35914,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780017929422,"responseId":"chatcmpl-70db8991-9776-47d5-b4ee-7f4eff1abbb9"}}
|
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{"type":"message","id":"376e2bbd","parentId":"6adcc7b5","timestamp":"2026-05-29T01:25:33.583Z","message":{"role":"toolResult","toolCallId":"call_50be0a1038084b649c3a759f","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.md.material.mapper;\r\n\r\nimport com.baomidou.mybatisplus.core.mapper.BaseMapper;\r\nimport com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;\r\nimport com.witsoft.erp.module.md.material.entity.Material;\r\nimport org.apache.ibatis.annotations.Mapper;\r\nimport org.apache.ibatis.annotations.Param;\r\n\r\nimport java.math.BigDecimal;\r\nimport java.util.Collections;\r\nimport java.util.List;\r\nimport java.util.stream.Collectors;\r\n\r\n/**\r\n * 物料 Mapper 接口\r\n */\r\n@Mapper\r\npublic interface MaterialMapper extends BaseMapper<Material> {\r\n\r\n /**\r\n * 根据关键字搜索物料 ID 列表\r\n *\r\n * @param keyword 关键字（编码/名称/规格）\r\n * @return 物料 ID 列表\r\n */\r\n default List<Long> searchMaterialIdsByKeyword(String keyword) {\r\n if (keyword == null || keyword.trim().isEmpty()) {\r\n return Collections.emptyList();\r\n }\r\n String escaped = keyword.replace(\"%\", \"\\\\%\").replace(\"_\", \"\\\\_\");\r\n LambdaQueryWrapper<Material> wrapper = new LambdaQueryWrapper<>();\r\n wrapper.and(w -> w\r\n .apply(\"material_code LIKE {0}\", \"%\" + escaped + \"%\")\r\n .or()\r\n .apply(\"material_name LIKE {0}\", \"%\" + escaped + \"%\")\r\n .or()\r\n .apply(\"spec LIKE {0}\", \"%\" + escaped + \"%\")\r\n );\r\n wrapper.select(Material::getId);\r\n return selectList(wrapper).stream()\r\n .map(Material::getId)\r\n .collect(Collectors.toList());\r\n }\r\n\r\n}\r\n"}],"isError":false,"timestamp":1780017933583}}
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{"type":"message","id":"62f396c9","parentId":"376e2bbd","timestamp":"2026-05-29T01:25:33.583Z","message":{"role":"toolResult","toolCallId":"call_4d47ea19647d4e97ac05b221","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.common.util;\n\n/**\n * LIKE 查询特殊字符转义工具类\n * <p>\n * SQL LIKE 查询中，% 和 _ 是通配符，需要转义。\n * 本工具转义 \\ % _ 三个字符，配合 ESCAPE '\\' 使用。\n */\npublic class LikeEscapeUtil {\n\n /**\n * 转义 LIKE 查询中的特殊字符\n * <p>\n * SQL LIKE 通配符：% _ 需要转义\n * 数据中出现的特殊字符：空格、%、x、_、-、/、\\ 均不影响 LIKE 查询（% 和 _ 已被转义）\n * \n * @param keyword 原始关键字\n * @return 转义后的关键字\n */\n public static String escapeLike(String keyword) {\n if (keyword == null) {\n return null;\n }\n return keyword\n .replace(\"\\\\\", \"\\\\\\\\\")\n .replace(\"%\", \"\\\\%\")\n .replace(\"_\", \"\\\\_\");\n }\n}"}],"isError":false,"timestamp":1780017933583}}
|
||
{"type":"message","id":"7f6a9bf1","parentId":"62f396c9","timestamp":"2026-05-29T01:25:53.287Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now I have a full picture of the existing codebase. Let me analyze the situation and provide a comprehensive answer about the \"近似查询\" (approximate/fuzzy query) approach.\n\nThe user is asking about a query approximation strategy for materials, with these requirements:\n1. AI should return name and spec\n2. Exact match by name\n3. Fuzzy match by name\n4. Fuzzy match by spec\n5. When multiple results are returned, analyze priority\n\nLet me now look at what the current code already does and propose a comprehensive solution.\n\nCurrent state:\n- `MaterialServiceImpl.searchByNameLike(String keyword)` - does a combined LIKE on material_code, material_name, spec with `OR` - so all three fields are searched with the same keyword\n- `MaterialMapper.searchMaterialIdsByKeyword` - same combined LIKE\n- `MaterialSelectorServiceImpl` - keyword matching in `matchesKeyword()` method\n- `AiRecognitionServiceImpl.matchMaterialItem()` - complex multi-level fuzzy matching strategy\n\nThe user wants a more structured approach. Let me think about what would be a good design.\n\nThe key architectural question is: when the user/ai provides a query string that might match multiple materials by different criteria (exact name match, fuzzy name match, fuzzy spec match), how should we prioritize results?\n\nA good approach would be something like:\n\n1. **Separate the matching strategies** - don't use a single OR LIKE\n2. **Define priority tiers**:\n - Tier 1: Exact name match\n - Tier 2: Name starts with / prefix match\n - Tier 3: Name contains keyword (fuzzy)\n - Tier 4: Spec contains keyword\n - Tier 5: Code contains keyword\n3. **Return with priority label** so the caller knows which tier matched\n\nLet me propose a clean solution.","thinkingSignature":"reasoning_content"},{"type":"text","text":"现在我对整个查询链路有完整了解了。给你一个综合分析。\n\n---\n\n## 现有查询链路分析\n\n目前项目中有**三处**物料近似查询逻辑，分散在不同地方：\n\n| 位置 | 方式 | 问题 |\n|---|---|---|\n| `MaterialService.searchByNameLike()` | 一个 `keyword` 同时 LIKE 编码/名称/规格（OR） | 三条路混在一起，不知道哪个优先级 |\n| `MaterialSelectorServiceImpl.matchesKeyword()` | 内存中 `contains` 匹配代码/名称/规格 | 无优先级，纯集合过滤 |\n| `AiRecognitionServiceImpl.matchMaterialItem()` | 多层降级搜索（名称→名称+规格→分词→汉字片段） | 每次只取第一个，放弃多候选 |\n\n核心痛点：**没有按匹配类型分优先级排序，多条结果混在一起无法区分。**\n\n---\n\n## 推荐方案：结构化近似查询\n\n核心思路：**一个查询不只返回「有没有匹配到」，还要返回「匹配的场次（match_type）」。**\n\n### 1. 定义匹配优先级枚举\n\n```java\npublic enum MatchPriority {\n EXACT_NAME(1, \"名称精确匹配\"), // material_name = keyword\n PREFIX_NAME(2, \"名称前缀匹配\"), // material_name LIKE 'keyword%'\n FUZZY_NAME(3, \"名称模糊匹配\"), // material_name LIKE '%keyword%'\n FUZZY_SPEC(4, \"规格模糊匹配\"), // spec LIKE '%keyword%'\n FUZZY_CODE(5, \"编码模糊匹配\"); // material_code LIKE '%keyword%'\n\n public final int rank;\n public final String desc;\n\n MatchPriority(int rank, String desc) {\n this.rank = rank;\n this.desc = desc;\n }\n}\n```\n\n### 2. SQL 分步查询（按优先级降级）\n\n```sql\n-- Step 1: 精确匹配名称\nSELECT id, material_code, material_name, spec, unit, 'EXACT_NAME' AS match_type\n FROM md_material\n WHERE material_name = :keyword\n AND status = 0\n\n-- Step 2: 名称前缀匹配（如果有增删查改场景）\nSELECT id, ..., 'PREFIX_NAME' AS match_type\n FROM md_material\n WHERE material_name LIKE :keyword || '%'\n AND status = 0\n\n-- Step 3: 名称模糊匹配\nSELECT id, ..., 'FUZZY_NAME' AS match_type\n FROM md_material\n WHERE material_name LIKE '%' || :keyword || '%'\n AND status = 0\n\n-- Step 4: 规格模糊匹配\nSELECT id, ..., 'FUZZY_SPEC' AS match_type\n FROM md_material\n WHERE spec LIKE '%' || :keyword || '%'\n AND status = 0\n\n-- Step 5: 编码模糊匹配（兜底）\nSELECT id, ..., 'FUZZY_CODE' AS match_type\n FROM md_material\n WHERE material_code LIKE '%' || :keyword || '%'\n AND status = 0\n```\n\n> **为什么不全放一个 OR？** 因为 OR 出来的结果你无法知道是哪条条件命中的，排序时无法区分精确匹配和模糊匹配。\n\n### 3. 返回 DTO\n\n```java\n@Data\npublic class MaterialMatchResult {\n private Long id;\n private String materialCode;\n private String materialName;\n private String spec;\n private String unit;\n \n /** 命中类型（EXACT_NAME / FUZZY_SPEC 等） */\n private MatchPriority matchType;\n \n /** 排序权重（越小越优先，展示时按此排序） */\n private Integer matchRank;\n \n /** 总结果数（方便前端决策是否展示\"搜索到 N 条\"） */\n private Integer totalMatches;\n}\n```\n\n### 4. Service 实现架构\n\n```java\n@Override\npublic List<MaterialMatchResult> searchSimilar(String keyword) {\n String escaped = escapeLike(keyword);\n List<MaterialMatchResult> results = new ArrayList<>();\n Set<Long> addedIds = new HashSet<>(); // 防重复\n\n // 按优先级依次查询，已匹配的 ID 不再出现在更低优先级中\n // 1. 名称精确匹配\n searchAndAdd(results, addedIds, \n wrapper -> wrapper.eq(Material::getMaterialName, keyword),\n MatchPriority.EXACT_NAME);\n\n // 2. 名称前缀匹配\n searchAndAdd(results, addedIds,\n wrapper -> wrapper.apply(\"material_name LIKE {0}\", escaped + \"%\"),\n MatchPriority.PREFIX_NAME);\n\n // 3. 名称模糊匹配\n searchAndAdd(results, addedIds,\n wrapper -> wrapper.apply(\"material_name LIKE {0}\", \"%\" + escaped + \"%\"),\n MatchPriority.FUZZY_NAME);\n\n // 4. 规格模糊匹配\n searchAndAdd(results, addedIds,\n wrapper -> wrapper.apply(\"spec LIKE {0}\", \"%\" + escaped + \"%\"),\n MatchPriority.FUZZY_SPEC);\n\n // 5. 编码模糊匹配（兜底）\n searchAndAdd(results, addedIds,\n wrapper -> wrapper.apply(\"material_code LIKE {0}\", \"%\" + escaped + \"%\"),\n MatchPriority.FUZZY_CODE);\n\n return results;\n}\n\nprivate void searchAndAdd(List<MaterialMatchResult> results, Set<Long> addedIds,\n Consumer<LambdaQueryWrapper<Material>> condition, MatchPriority priority) {\n LambdaQueryWrapper<Material> wrapper = new LambdaQueryWrapper<>();\n condition.accept(wrapper);\n wrapper.eq(Material::getStatus, 0);\n wrapper.orderByDesc(Material::getCreateTime);\n wrapper.last(\"LIMIT 20\");\n\n List<Material> list = baseMapper.selectList(wrapper);\n for (Material m : list) {\n if (addedIds.add(m.getId())) {\n MaterialMatchResult r = new MaterialMatchResult();\n // 填充字段\n r.setMatchType(priority);\n r.setMatchRank(priority.rank);\n results.add(r);\n }\n }\n}\n```\n\n### 5. AI 场景的适配（`AiRecognitionServiceImpl`）\n\n现有逻辑每次只取 `candidates.get(0)`，改为：\n\n```java\n// 不再只取第一个，改用结构化搜索\nList<MaterialMatchResult> candidates = materialService.searchSimilar(normalized);\n\nif (candidates.isEmpty()) {\n // 降级：分词搜索（和现有逻辑一致）\n ...\n}\n\n// 取优先级最高的候选\nMaterialMatchResult best = candidates.get(0);\n```\n\n并且 `RecognitionItem` 中可以新增一个 `matchType` 字段，前端可以看到匹配质量（精确/模糊）。\n\n---\n\n## 优先级总览\n\n| 优先级 | 匹配方式 | SQL 条件 | 场景示例（输入\"8.5mm玻璃棒\"） |\n|---|---|---|---|\n| 🥇 1 | 名称精确匹配 | `name = keyword` | 数据库刚好有物料叫\"8.5mm玻璃棒\" |\n| 🥇 2 | 名称前缀匹配 | `name LIKE 'keyword%'` | 前缀匹配（较少用，视业务需求可跳过） |\n| 🥇 3 | 名称模糊匹配 | `name LIKE '%keyword%'` | 名称中包含\"8.5mm玻璃棒\" |\n| 🥇 4 | 规格模糊匹配 | `spec LIKE '%keyword%'` | 规格字段中有\"8.5mm\"或\"玻璃棒\" |\n| 🥇 5 | 编码模糊匹配 | `code LIKE '%keyword%'` | 编码中包含该关键字（兜底） |\n\n**输出自然形成排序：** 精确匹配排最前，越模糊越靠后。\n\n---\n\n## 与现有代码的兼容\n\n- `searchByNameLike()` 保留不动（现有调用者需要原始 OR 行为），新增 `searchSimilar()`\n- `MaterialSelectorServiceImpl.matchesKeyword()` 同理保留，不改\n- 只改 `AiRecognitionServiceImpl` 和物料搜索前端用的地方\n\n---\n\n要我把这个方案落地成代码？还是你先看方案，有地方需要调整再聊？"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":958,"output":2124,"cacheRead":35584,"cacheWrite":0,"reasoningTokens":377,"totalTokens":38666,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1780017933600,"responseId":"chatcmpl-aa6864f7-43cc-4f36-b462-ae56b7f496cd"}}
|
||
{"type":"message","id":"6f53d1c0","parentId":"7f6a9bf1","timestamp":"2026-05-29T01:30:33.710Z","message":{"role":"user","content":[{"type":"text","text":"[Fri 2026-05-29 09:30 GMT+8] 保存方案文档到 tiny yangxuan/设计"}],"timestamp":1780018233603}}
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{"type":"message","id":"6fef19eb","parentId":"6f53d1c0","timestamp":"2026-05-29T01:30:43.129Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user wants me to save the analysis/design document to a specific path. Let me interpret \"tiny yangxuan/设计\" - this likely means the tiny-erp project's design docs, and \"yangxuan/设计\" suggests a path structure. Let me think about where to put this.\n\nLooking at the context, the workspace is `/home/yangxuan/.openclaw/workspace/java`. The user said \"tiny yangxuan/设计\" - I think \"tiny\" refers to the tiny-erp project. Given the path convention, I'll save it under the workspace or a reasonable location. But actually, re-reading: \"保存方案文档到 tiny yangxuan/设计\" - this could mean:\n1. Save to the tiny-erp project's design folder with \"yangxuan/设计\" subpath\n2. Or save relative to workspace\n\nGiven the workspace is for \"java\" and the tiny-erp project is at `/home/yangxuan/Projects/IdeaProjects/tiny-erp`, I think the user wants me to save it to the tiny-erp project. But \"yangxuan/设计\" - maybe a design docs folder?\n\nLet me check if there's a design/docs folder in the tiny-erp project, or I'll create one.\n\nActually, re-reading more carefully: \"保存方案文档到 tiny yangxuan/设计\" - \"tiny\" is the project alias (from TOOLS.md: `tiny` / `tiny-erp` → `/home/yangxuan/Projects/IdeaProjects/tiny-erp`), so \"tiny yangxuan/设计\" means save to the tiny-erp project at path `yangxuan/设计/`. This is likely relative to the tiny-erp project root.\n\nLet me check if that path exists.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_6e2d01514735431a8a8f8d8d","name":"exec","arguments":{"command":"ls -la /home/yangxuan/Projects/IdeaProjects/tiny-erp/yangxuan/ 2>/dev/null || echo \"NOT_EXISTS\"","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"ls -la /home/yangxuan/Projects/IdeaProjects/tiny-erp/yangxuan/ 2>/dev/null || echo \\\"NOT_EXISTS\\\"\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":37647,"output":483,"cacheRead":0,"cacheWrite":0,"reasoningTokens":374,"totalTokens":38130,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018233910,"responseId":"chatcmpl-0462ac89-d4ec-4ac0-a7de-f21284e1addd"}}
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{"type":"message","id":"dfd63bad","parentId":"6fef19eb","timestamp":"2026-05-29T01:30:43.846Z","message":{"role":"toolResult","toolCallId":"call_6e2d01514735431a8a8f8d8d","toolName":"exec","content":[{"type":"text","text":"total 48\ndrwxrwxr-x 8 yangxuan yangxuan 4096 May 26 14:50 .\ndrwxrwxr-x 10 yangxuan yangxuan 4096 May 28 20:53 ..\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 26 10:42 API\n-rw-rw-r-- 1 yangxuan yangxuan 2763 May 25 18:56 README.md\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 29 09:23 其他\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 25 19:01 数据库\ndrwxr-xr-x 2 yangxuan yangxuan 4096 May 26 19:42 测试\n-rw-rw-r-- 1 yangxuan yangxuan 2771 May 26 14:56 物料信息填充公共服务总结.md\ndrwxrwxr-x 8 yangxuan yangxuan 4096 May 26 10:32 设计\ndrwxr-xr-x 8 yangxuan yangxuan 4096 May 25 18:58 需求\n-rw-rw-r-- 1 yangxuan yangxuan 5162 May 25 18:49 项目规范.md"}],"details":{"status":"completed","exitCode":0,"durationMs":207,"aggregated":"total 48\ndrwxrwxr-x 8 yangxuan yangxuan 4096 May 26 14:50 .\ndrwxrwxr-x 10 yangxuan yangxuan 4096 May 28 20:53 ..\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 26 10:42 API\n-rw-rw-r-- 1 yangxuan yangxuan 2763 May 25 18:56 README.md\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 29 09:23 其他\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 25 19:01 数据库\ndrwxr-xr-x 2 yangxuan yangxuan 4096 May 26 19:42 测试\n-rw-rw-r-- 1 yangxuan yangxuan 2771 May 26 14:56 物料信息填充公共服务总结.md\ndrwxrwxr-x 8 yangxuan yangxuan 4096 May 26 10:32 设计\ndrwxr-xr-x 8 yangxuan yangxuan 4096 May 25 18:58 需求\n-rw-rw-r-- 1 yangxuan yangxuan 5162 May 25 18:49 项目规范.md","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780018243846}}
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{"type":"message","id":"0fcae377","parentId":"dfd63bad","timestamp":"2026-05-29T01:30:46.377Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Good, the directory `设计` already exists under `yangxuan/`. Let me check what's already in it.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_6b68771c08894e71b545affa","name":"exec","arguments":{"command":"ls -la /home/yangxuan/Projects/IdeaProjects/tiny-erp/yangxuan/设计/","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"ls -la /home/yangxuan/Projects/IdeaProjects/tiny-erp/yangxuan/设计/\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":438,"output":124,"cacheRead":37632,"cacheWrite":0,"reasoningTokens":25,"totalTokens":38194,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018243848,"responseId":"chatcmpl-75593c6d-7d5f-49d2-bb91-5fdb5dccd207"}}
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{"type":"message","id":"6626aabc","parentId":"0fcae377","timestamp":"2026-05-29T01:30:47.122Z","message":{"role":"toolResult","toolCallId":"call_6b68771c08894e71b545affa","toolName":"exec","content":[{"type":"text","text":"total 56\ndrwxrwxr-x 8 yangxuan yangxuan 4096 May 26 10:32 .\ndrwxrwxr-x 8 yangxuan yangxuan 4096 May 26 14:50 ..\n-rw-r--r-- 1 yangxuan yangxuan 21349 May 23 17:17 01-开发方案.md\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 25 18:57 主数据模块\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 26 11:25 库存模块\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 25 18:57 系统模块\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 28 10:40 财务模块\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 25 18:57 采购模块\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 25 18:57 销售模块"}],"details":{"status":"completed","exitCode":0,"durationMs":211,"aggregated":"total 56\ndrwxrwxr-x 8 yangxuan yangxuan 4096 May 26 10:32 .\ndrwxrwxr-x 8 yangxuan yangxuan 4096 May 26 14:50 ..\n-rw-r--r-- 1 yangxuan yangxuan 21349 May 23 17:17 01-开发方案.md\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 25 18:57 主数据模块\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 26 11:25 库存模块\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 25 18:57 系统模块\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 28 10:40 财务模块\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 25 18:57 采购模块\ndrwxrwxr-x 2 yangxuan yangxuan 4096 May 25 18:57 销售模块","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780018247121}}
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{"type":"message","id":"995ed6a7","parentId":"6626aabc","timestamp":"2026-05-29T01:31:05.083Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user wants me to save the analysis document about the \"查询近似规则\" (fuzzy/approximate search) to the `tiny-erp/yangxuan/设计/` directory. I'll write a comprehensive design document there.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_49b53b043c024d128d4ec852","name":"write","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/yangxuan/设计/02-物料近似查询方案.md","content":"# 物料近似查询方案\n\n> 2026-05-29 更新\n\n## 一、背景\n\n现有物料查询存在多个入口，但缺乏统一的近似匹配策略：\n\n| 位置 | 方式 | 问题 |\n|------|------|------|\n| `MaterialService.searchByNameLike()` | 一个 `keyword` 同时 LIKE 编码/名称/规格（OR） | 三条路混在一起，无法区分命中类型，排序无优先级 |\n| `MaterialSelectorServiceImpl.matchesKeyword()` | 内存中 `contains` 匹配代码/名称/规格 | 无优先级，纯集合过滤 |\n| `AiRecognitionServiceImpl.matchMaterialItem()` | 多层降级搜索 | 每次只取第一个匹配，放弃多候选分析 |\n\n核心痛点：**无法知道命中哪个字段，无法按匹配质量排序，多条结果混在一起。**\n\n## 二、匹配优先级定义\n\n按精确度从高到低，定义 5 级匹配优先级：\n\n| 优先级 | 匹配方式 | SQL 条件 | 示意场景 |\n|--------|----------|----------|----------|\n| 🥇 1 | 名称精确匹配 | `material_name = keyword` | 输入\"8.5mm玻璃棒\" → 数据库刚好有这个名称 |\n| 🥇 2 | 名称前缀匹配 | `material_name LIKE 'keyword%'` | \"玻璃棒\" → \"玻璃棒 8.5mm\" |\n| 🥇 3 | 名称模糊匹配 | `material_name LIKE '%keyword%'` | \"玻璃棒\" → \"高硼硅玻璃棒\" |\n| 🥇 4 | 规格模糊匹配 | `spec LIKE '%keyword%'` | \"玻璃棒\" → 物料名称为\"石英管\"但规格字段含\"玻璃棒\" |\n| 🥇 5 | 编码模糊匹配 | `material_code LIKE '%keyword%'` | 兜底，编码中包含该关键字 |\n\n名称精确匹配最高，编码模糊匹配最低。\n\n## 三、数据结构\n\n### 3.1 匹配优先级枚举\n\n```java\npublic enum MatchPriority {\n EXACT_NAME(1, \"名称精确匹配\"),\n PREFIX_NAME(2, \"名称前缀匹配\"),\n FUZZY_NAME(3, \"名称模糊匹配\"),\n FUZZY_SPEC(4, \"规格模糊匹配\"),\n FUZZY_CODE(5, \"编码模糊匹配\");\n\n public final int rank; // 排序权重，越小越优先\n public final String desc;\n\n MatchPriority(int rank, String desc) {\n this.rank = rank;\n this.desc = desc;\n }\n}\n```\n\n### 3.2 统一返回 DTO\n\n```java\n@Data\npublic class MaterialMatchResult {\n private Long id;\n private String materialCode;\n private String materialName;\n private String spec;\n private String unit;\n\n /** 命中类型（EXACT_NAME / FUZZY_SPEC 等） */\n private MatchPriority matchType;\n\n /** 排序权重（rank 值，越小越优先） */\n private Integer matchRank;\n\n /** 关联数据（物料类型名称、分类名称等，后续由 MaterialFillService 填充） */\n private MaterialInfoDTO materialInfo;\n}\n```\n\n## 四、核心查询流程\n\n### 4.1 分步查询 + 去重\n\n核心思路：按优先级从高到低依次查询，**每个更低优先级只搜索未被命中过的物料 ID**，最终结果自然按优先级排序。\n\n```\n输入 keyword\n\nStep 1: SELECT ... WHERE material_name = :keyword\n → 加入结果集，记录：匹配类型 = EXACT_NAME\n → 记录已命中的 ID 集合\n\nStep 2: SELECT ... WHERE material_name LIKE :keyword || '%'\n → 过滤掉已命中的 ID，剩余加入结果集\n → 匹配类型 = PREFIX_NAME\n\nStep 3: SELECT ... WHERE material_name LIKE '%' || :keyword || '%'\n → 过滤已命中 ID\n → 匹配类型 = FUZZY_NAME\n\nStep 4: SELECT ... WHERE spec LIKE '%' || :keyword || '%'\n → 过滤已命中 ID\n → 匹配类型 = FUZZY_SPEC\n\nStep 5: SELECT ... WHERE material_code LIKE '%' || :keyword || '%'\n → 过滤已命中 ID\n → 匹配类型 = FUZZY_CODE\n\n返回 List<MaterialMatchResult>（有序，按 matchRank 升序）\n```\n\n### 4.2 为什么不用单个 OR？\n\n单个 OR 查询无法区分每条结果是命中 name 还是 spec 还是 code，排序时无法给精确匹配更高权重。分步查询天然得到优先级排序的结果。\n\n## 五、接口定义\n\n### 5.1 Service 层新增\n\n```java\npublic interface MaterialService extends IService<Material> {\n\n // 保留现有方法（不破坏调用者）\n Page<MaterialPageDTO> pageWithStock(MaterialPageQueryReqDTO reqDTO);\n List<Long> searchMaterialIdsByKeyword(String keyword);\n List<Material> searchByNameLike(String keyword);\n\n // 新增：结构化近似查询，结果按匹配优先级排序\n List<MaterialMatchResult> searchSimilar(String keyword);\n}\n```\n\n### 5.2 限流保护\n\n- 每个步骤 LIMIT 20\n- 最终结果上限：建议 30-50 条\n- 关键字空或过短（< 2 字符）时返回空\n\n## 六、现有调用处的迁移方案\n\n### 6.1 AI 识别场景（`AiRecognitionServiceImpl`）\n\n现有逻辑每次只取 `candidates.get(0)`，改为走结构化搜索：\n\n```java\n// 改前\nList<Material> candidates = materialService.searchByNameLike(normalized);\n// ... multi-level fallback ...\nif (!candidates.isEmpty()) {\n Material best = candidates.get(0);\n // ...\n}\n\n// 改后\nList<MaterialMatchResult> candidates = materialService.searchSimilar(normalized);\nif (candidates.isEmpty()) {\n // 降级：分词搜索（保留现有降级逻辑）\n}\nMaterialMatchResult best = candidates.get(0);\n// 同时可将 matchType 带回前端\n```\n\n在 `RecognitionItem` 中增加 `matchType` 字段，前端可视化展示匹配质量。\n\n### 6.2 物料选择器（`MaterialSelectorServiceImpl`）\n\n入库/出库选择器的 `matchesKeyword()` 内存过滤改为按优先级匹配：\n\n```java\n// 改前：内存中 contains 匹配\n.filter(dto -> matchesKeyword(dto, keyword))\n\n// 改后：按优先级搜索并排序（或者在 SQL 层就按优先级查）\n```\n\n### 6.3 库存查询场景（`StockServiceImpl`）\n\n当前库存分页查询中通过 `searchMaterialIdsByKeyword` 获取物料 ID 再 JOIN 库存表：\n\n```java\n// 改前\nList<Long> matchedMaterialIds = materialMapper.searchMaterialIdsByKeyword(dto.getKeyword());\n\n// 改后：加入排序，保持匹配优先级排序\nList<MaterialMatchResult> matched = materialService.searchSimilar(dto.getKeyword());\nList<Long> matchedMaterialIds = matched.stream().map(MaterialMatchResult::getId).toList();\n```\n\n## 七、特殊字符处理\n\n统一使用 `LikeEscapeUtil` 转义 `\\` `%` `_` 三个字符后拼接 `%` 通配符。\n\n```sql\n-- 示例：keyword = \"8.5%玻璃_棒\"\n-- 转义后：material_name LIKE '%8.5\\%玻璃\\_棒%' ESCAPE '\\'\n```\n\n## 八、与现有代码的兼容性\n\n- **`searchByNameLike()` 保留不动** — 现有调用方不需要改\n- **`searchMaterialIdsByKeyword()` 保留不动** — 兼容旧查询路径\n- **`matchesKeyword()` 保留不动** — 选择器内存过滤仍可用\n- 新增 `searchSimilar()` 方法，调用方按需迁移\n\n## 九、PostgreSQL 性能考虑\n\n- 物料表 `md_material` 预计规模不超过 10 万条\n- `material_name`、`spec`、`material_code` 建议建索引（**已建则忽略**）\n- 分步查询每次命中特定索引，不会出现全表扫描\n\n```sql\n-- 建议索引\nCREATE INDEX idx_md_material_name ON md_material(material_name);\nCREATE INDEX idx_md_material_spec ON md_material(spec);\nCREATE INDEX idx_md_material_code ON md_material(material_code);\n```\n\n## 十、前端展示建议\n\n返回结果携带 `matchType`，前端根据匹配类型给出视觉提示：\n\n| 匹配类型 | 展示样式 |\n|----------|----------|\n| EXACT_NAME | 正常高亮（绿底/粗体） |\n| PREFIX_NAME / FUZZY_NAME | 仅高亮匹配部分 |\n| FUZZY_SPEC | 灰色标注\"规格匹配\" |\n| FUZZY_CODE | 灰色标注\"编码匹配\" |\n\n同时展示每条结果的 `score/matchType`，帮助用户判断匹配质量。"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/yangxuan/设计/02-物料近似查询方案.md\", \"content\": \"# 物料近似查询方案\\n\\n> 2026-05-29 更新\\n\\n## 一、背景\\n\\n现有物料查询存在多个入口，但缺乏统一的近似匹配策略：\\n\\n| 位置 | 方式 | 问题 |\\n|------|------|------|\\n| `MaterialService.searchByNameLike()` | 一个 `keyword` 同时 LIKE 编码/名称/规格（OR） | 三条路混在一起，无法区分命中类型，排序无优先级 |\\n| `MaterialSelectorServiceImpl.matchesKeyword()` | 内存中 `contains` 匹配代码/名称/规格 | 无优先级，纯集合过滤 |\\n| `AiRecognitionServiceImpl.matchMaterialItem()` | 多层降级搜索 | 每次只取第一个匹配，放弃多候选分析 |\\n\\n核心痛点：**无法知道命中哪个字段，无法按匹配质量排序，多条结果混在一起。**\\n\\n## 二、匹配优先级定义\\n\\n按精确度从高到低，定义 5 级匹配优先级：\\n\\n| 优先级 | 匹配方式 | SQL 条件 | 示意场景 |\\n|--------|----------|----------|----------|\\n| 🥇 1 | 名称精确匹配 | `material_name = keyword` | 输入\\\"8.5mm玻璃棒\\\" → 数据库刚好有这个名称 |\\n| 🥇 2 | 名称前缀匹配 | `material_name LIKE 'keyword%'` | \\\"玻璃棒\\\" → \\\"玻璃棒 8.5mm\\\" |\\n| 🥇 3 | 名称模糊匹配 | `material_name LIKE '%keyword%'` | \\\"玻璃棒\\\" → \\\"高硼硅玻璃棒\\\" |\\n| 🥇 4 | 规格模糊匹配 | `spec LIKE '%keyword%'` | \\\"玻璃棒\\\" → 物料名称为\\\"石英管\\\"但规格字段含\\\"玻璃棒\\\" |\\n| 🥇 5 | 编码模糊匹配 | `material_code LIKE '%keyword%'` | 兜底，编码中包含该关键字 |\\n\\n名称精确匹配最高，编码模糊匹配最低。\\n\\n## 三、数据结构\\n\\n### 3.1 匹配优先级枚举\\n\\n```java\\npublic enum MatchPriority {\\n EXACT_NAME(1, \\\"名称精确匹配\\\"),\\n PREFIX_NAME(2, \\\"名称前缀匹配\\\"),\\n FUZZY_NAME(3, \\\"名称模糊匹配\\\"),\\n FUZZY_SPEC(4, \\\"规格模糊匹配\\\"),\\n FUZZY_CODE(5, \\\"编码模糊匹配\\\");\\n\\n public final int rank; // 排序权重，越小越优先\\n public final String desc;\\n\\n MatchPriority(int rank, String desc) {\\n this.rank = rank;\\n this.desc = desc;\\n }\\n}\\n```\\n\\n### 3.2 统一返回 DTO\\n\\n```java\\n@Data\\npublic class MaterialMatchResult {\\n private Long id;\\n private String materialCode;\\n private String materialName;\\n private String spec;\\n private String unit;\\n\\n /** 命中类型（EXACT_NAME / FUZZY_SPEC 等） */\\n private MatchPriority matchType;\\n\\n /** 排序权重（rank 值，越小越优先） */\\n private Integer matchRank;\\n\\n /** 关联数据（物料类型名称、分类名称等，后续由 MaterialFillService 填充） */\\n private MaterialInfoDTO materialInfo;\\n}\\n```\\n\\n## 四、核心查询流程\\n\\n### 4.1 分步查询 + 去重\\n\\n核心思路：按优先级从高到低依次查询，**每个更低优先级只搜索未被命中过的物料 ID**，最终结果自然按优先级排序。\\n\\n```\\n输入 keyword\\n\\nStep 1: SELECT ... WHERE material_name = :keyword\\n → 加入结果集，记录：匹配类型 = EXACT_NAME\\n → 记录已命中的 ID 集合\\n\\nStep 2: SELECT ... WHERE material_name LIKE :keyword || '%'\\n → 过滤掉已命中的 ID，剩余加入结果集\\n → 匹配类型 = PREFIX_NAME\\n\\nStep 3: SELECT ... WHERE material_name LIKE '%' || :keyword || '%'\\n → 过滤已命中 ID\\n → 匹配类型 = FUZZY_NAME\\n\\nStep 4: SELECT ... WHERE spec LIKE '%' || :keyword || '%'\\n → 过滤已命中 ID\\n → 匹配类型 = FUZZY_SPEC\\n\\nStep 5: SELECT ... WHERE material_code LIKE '%' || :keyword || '%'\\n → 过滤已命中 ID\\n → 匹配类型 = FUZZY_CODE\\n\\n返回 List<MaterialMatchResult>（有序，按 matchRank 升序）\\n```\\n\\n### 4.2 为什么不用单个 OR？\\n\\n单个 OR 查询无法区分每条结果是命中 name 还是 spec 还是 code，排序时无法给精确匹配更高权重。分步查询天然得到优先级排序的结果。\\n\\n## 五、接口定义\\n\\n### 5.1 Service 层新增\\n\\n```java\\npublic interface MaterialService extends IService<Material> {\\n\\n // 保留现有方法（不破坏调用者）\\n Page<MaterialPageDTO> pageWithStock(MaterialPageQueryReqDTO reqDTO);\\n List<Long> searchMaterialIdsByKeyword(String keyword);\\n List<Material> searchByNameLike(String keyword);\\n\\n // 新增：结构化近似查询，结果按匹配优先级排序\\n List<MaterialMatchResult> searchSimilar(String keyword);\\n}\\n```\\n\\n### 5.2 限流保护\\n\\n- 每个步骤 LIMIT 20\\n- 最终结果上限：建议 30-50 条\\n- 关键字空或过短（< 2 字符）时返回空\\n\\n## 六、现有调用处的迁移方案\\n\\n### 6.1 AI 识别场景（`AiRecognitionServiceImpl`）\\n\\n现有逻辑每次只取 `candidates.get(0)`，改为走结构化搜索：\\n\\n```java\\n// 改前\\nList<Material> candidates = materialService.searchByNameLike(normalized);\\n// ... multi-level fallback ...\\nif (!candidates.isEmpty()) {\\n Material best = candidates.get(0);\\n // ...\\n}\\n\\n// 改后\\nList<MaterialMatchResult> candidates = materialService.searchSimilar(normalized);\\nif (candidates.isEmpty()) {\\n // 降级：分词搜索（保留现有降级逻辑）\\n}\\nMaterialMatchResult best = candidates.get(0);\\n// 同时可将 matchType 带回前端\\n```\\n\\n在 `RecognitionItem` 中增加 `matchType` 字段，前端可视化展示匹配质量。\\n\\n### 6.2 物料选择器（`MaterialSelectorServiceImpl`）\\n\\n入库/出库选择器的 `matchesKeyword()` 内存过滤改为按优先级匹配：\\n\\n```java\\n// 改前：内存中 contains 匹配\\n.filter(dto -> matchesKeyword(dto, keyword))\\n\\n// 改后：按优先级搜索并排序（或者在 SQL 层就按优先级查）\\n```\\n\\n### 6.3 库存查询场景（`StockServiceImpl`）\\n\\n当前库存分页查询中通过 `searchMaterialIdsByKeyword` 获取物料 ID 再 JOIN 库存表：\\n\\n```java\\n// 改前\\nList<Long> matchedMaterialIds = materialMapper.searchMaterialIdsByKeyword(dto.getKeyword());\\n\\n// 改后：加入排序，保持匹配优先级排序\\nList<MaterialMatchResult> matched = materialService.searchSimilar(dto.getKeyword());\\nList<Long> matchedMaterialIds = matched.stream().map(MaterialMatchResult::getId).toList();\\n```\\n\\n## 七、特殊字符处理\\n\\n统一使用 `LikeEscapeUtil` 转义 `\\\\` `%` `_` 三个字符后拼接 `%` 通配符。\\n\\n```sql\\n-- 示例：keyword = \\\"8.5%玻璃_棒\\\"\\n-- 转义后：material_name LIKE '%8.5\\\\%玻璃\\\\_棒%' ESCAPE '\\\\'\\n```\\n\\n## 八、与现有代码的兼容性\\n\\n- **`searchByNameLike()` 保留不动** — 现有调用方不需要改\\n- **`searchMaterialIdsByKeyword()` 保留不动** — 兼容旧查询路径\\n- **`matchesKeyword()` 保留不动** — 选择器内存过滤仍可用\\n- 新增 `searchSimilar()` 方法，调用方按需迁移\\n\\n## 九、PostgreSQL 性能考虑\\n\\n- 物料表 `md_material` 预计规模不超过 10 万条\\n- `material_name`、`spec`、`material_code` 建议建索引（**已建则忽略**）\\n- 分步查询每次命中特定索引，不会出现全表扫描\\n\\n```sql\\n-- 建议索引\\nCREATE INDEX idx_md_material_name ON md_material(material_name);\\nCREATE INDEX idx_md_material_spec ON md_material(spec);\\nCREATE INDEX idx_md_material_code ON md_material(material_code);\\n```\\n\\n## 十、前端展示建议\\n\\n返回结果携带 `matchType`，前端根据匹配类型给出视觉提示：\\n\\n| 匹配类型 | 展示样式 |\\n|----------|----------|\\n| EXACT_NAME | 正常高亮（绿底/粗体） |\\n| PREFIX_NAME / FUZZY_NAME | 仅高亮匹配部分 |\\n| FUZZY_SPEC | 灰色标注\\\"规格匹配\\\" |\\n| FUZZY_CODE | 灰色标注\\\"编码匹配\\\" |\\n\\n同时展示每条结果的 `score/matchType`，帮助用户判断匹配质量。\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":545,"output":2098,"cacheRead":37888,"cacheWrite":0,"reasoningTokens":49,"totalTokens":40531,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018247125,"responseId":"chatcmpl-736acbf4-8027-41c9-80de-08cf329f8ce3"}}
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{"type":"message","id":"6f846074","parentId":"995ed6a7","timestamp":"2026-05-29T01:31:05.568Z","message":{"role":"toolResult","toolCallId":"call_49b53b043c024d128d4ec852","toolName":"write","content":[{"type":"text","text":"Successfully wrote 5213 bytes to /home/yangxuan/Projects/IdeaProjects/tiny-erp/yangxuan/设计/02-物料近似查询方案.md"}],"isError":false,"timestamp":1780018265567}}
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{"type":"message","id":"904c85b3","parentId":"6f846074","timestamp":"2026-05-29T01:31:09.534Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Document saved successfully. Let me confirm the path and summarize.","thinkingSignature":"reasoning_content"},{"type":"text","text":"已保存到 `tiny-erp/yangxuan/设计/02-物料近似查询方案.md` ✅\n\n文档覆盖了：\n1. **现有代码痛点分析** — 三个入口各有各的问题\n2. **5 级匹配优先级定义** — 精确名称 > 前缀 > 模糊名称 > 规格 > 编码\n3. **分步查询 + 去重实现方案** — 避免 OR 混在一起无法排序\n4. **枚举 + DTO 结构**\n5. **三处现有调用点的迁移路径** — AI 识别、物料选择器、库存查询\n6. **兼容性说明** — 旧方法保留不动，新增 `searchSimilar()`\n7. **索引建议** 和 **前端展示建议**"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":2129,"output":175,"cacheRead":38400,"cacheWrite":0,"reasoningTokens":12,"totalTokens":40704,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1780018265570,"responseId":"chatcmpl-b43acb25-e3af-43eb-98df-fb031cc294f6"}}
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{"type":"message","id":"1f4c53ef","parentId":"904c85b3","timestamp":"2026-05-29T01:36:39.085Z","message":{"role":"user","content":[{"type":"text","text":"[Fri 2026-05-29 09:36 GMT+8] ## 交互优化\n- 返回前端id 无法填充页面\n - 客户供应商需要查询名称\n - 物料使用com.witsoft.erp.module.md.material.service.MaterialFillService.getMaterialInfoMap填充\n - 单据类型使用 数据字典中类型\n - 使用local 库测试\n - [02-物料近似查询方案.md](yangxuan/设计/02-物料近似查询方案.md)"}],"timestamp":1780018598971}}
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{"type":"message","id":"0769cc9f","parentId":"1f4c53ef","timestamp":"2026-05-29T01:36:49.750Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user is asking me to read the current document and then discuss/handle an interaction optimization. Let me first read the document they referenced, and also understand what they're talking about.\n\nLet me re-read the conversation. The user said:\n\n- Return frontend id can't fill page\n- Customer/supplier need to query name\n- Material uses `MaterialFillService.getMaterialInfoMap` to fill\n- Document type uses data dictionary type\n- Test on local database\n\nSo it seems like they're talking about the AI recognition feature, where the current implementation returns IDs but the frontend can't directly use those IDs to fill in names on the page. They want:\n\n1. For counterparties (customer/supplier): instead of just returning ID, also query and return the name\n2. For materials: use the existing `MaterialFillService.getMaterialInfoMap` to fill in material info\n3. For document type: use data dictionary values\n4. Test on the local database\n\nWait, let me re-read the AiRecognitionServiceImpl.java - it already does some of this. Let me look more carefully at what might be missing.\n\nActually, looking again at the code I already read:\n\nThe `AiRecognitionResultDTO` already has:\n- `Counterparty` with `id`, `name`, `recognizedName`, `exactMatch`\n- `RecognitionItem` with `materialId`, `materialName`, `materialCode`, `spec`, `unit`\n- `typeValue`, `typeName`\n\nSo it seems like they already return names. But maybe the issue is that:\n\n1. For counterparty matching - if it's not exact match, it returns the recognized name without an ID, and the frontend can't map it\n2. For material matching - it returns materialId but the frontend can't display materialCode/spec/unit properly\n3. document type needs to be from data dictionary properly\n\nLet me look at the existing code more carefully to understand the actual problem. The user says \"返回前端id 无法填充页面\" - the frontend can't fill the page with just IDs.\n\nLet me re-examine the AiRecognitionServiceImpl code more carefully, especially the material matching part.\n\nFrom what I saw earlier, the `matchMaterialItem` method in `AiRecognitionServiceImpl`:\n1. Searches materials by name\n2. If found, builds a `RecognitionItem` with materialId, materialName etc.\n3. But it uses `MaterialFillService.getMaterialInfoMap` to fill in the material info\n\nWait, I didn't see the full method because it was truncated. Let me read the full file.\n\nActually, let me look at this more carefully. The user is talking about an interaction optimization. Let me re-read:\n\n1. \"返回前端id 无法填充页面\" - Returning just IDs to frontend can't fill the page\n2. \"客户供应商需要查询名称\" - Customer/supplier need to query names\n3. \"物料使用MaterialFillService.getMaterialInfoMap填充\" - Materials use MaterialFillService.getMaterialInfoMap to fill\n4. \"单据类型使用数据字典中类型\" - Document type should use data dictionary types\n5. \"使用local库测试\" - Test on local database\n\nSo the user wants me to analyze the AiRecognitionResultDTO and the flow to see what's wrong, and then optimize it.\n\nLet me read the full matchMaterialItem method to understand the current implementation better.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_2d536132adca4def9e1ebb45","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java","offset":310},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java\", \"offset\": 310}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":40786,"output":815,"cacheRead":0,"cacheWrite":0,"reasoningTokens":718,"totalTokens":41601,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018599297,"responseId":"chatcmpl-03d5605e-4f3a-4c58-a5d4-395fe80ad1de"}}
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{"type":"message","id":"1cc62cc2","parentId":"0769cc9f","timestamp":"2026-05-29T01:36:50.301Z","message":{"role":"toolResult","toolCallId":"call_2d536132adca4def9e1ebb45","toolName":"read","content":[{"type":"text","text":" }\n chineseParts.sort((a, b) -> Integer.compare(b.length(), a.length()));\n for (String cp : chineseParts) {\n if (cp.length() >= 2) {\n candidates = materialService.searchByNameLike(cp);\n if (!candidates.isEmpty()) break;\n }\n }\n }\n\n if (candidates.isEmpty()) {\n // 完全无法匹配：返回 AI 识别的原始信息\n return AiRecognitionResultDTO.RecognitionItem.builder()\n .materialName(materialName)\n .spec(spec)\n .recognizedName(materialName)\n .quantity(quantity)\n .price(price)\n .unit(unit)\n .exactMatch(false)\n .build();\n }\n\n // 取最佳匹配，并用 MaterialFillService 补充信息\n Material best = candidates.get(0);\n MaterialInfoDTO info = materialFillService.getMaterialInfo(best.getId());\n\n AiRecognitionResultDTO.RecognitionItem.RecognitionItemBuilder builder = AiRecognitionResultDTO.RecognitionItem.builder()\n .materialId(best.getId())\n .materialName(info != null ? info.getMaterialName() : best.getMaterialName())\n .materialCode(info != null ? info.getMaterialCode() : null)\n .spec(info != null ? info.getSpec() : best.getSpec())\n .unit(info != null ? info.getUnit() : best.getUnit())\n .recognizedName(materialName)\n .quantity(quantity)\n .price(price)\n .exactMatch(best.getMaterialName().replaceAll(\"\\\\s+\", \"\").equals(normalized));\n\n return builder.build();\n }\n\n // ========== 名称处理工具 ==========\n\n /** 归一化名称：去空格、全角转半角 */\n private String normalizeName(String name) {\n if (name == null) return \"\";\n // 去掉所有空白字符\n String result = name.replaceAll(\"\\\\s+\", \"\");\n // 全角转半角\n StringBuilder sb = new StringBuilder();\n for (char c : result.toCharArray()) {\n if (c >= 'Ａ' && c <= 'Ｚ') sb.append((char) (c - 'Ａ' + 'A'));\n else if (c >= 'ａ' && c <= 'ｚ') sb.append((char) (c - 'ａ' + 'a'));\n else if (c >= '０' && c <= '９') sb.append((char) (c - '０' + '0'));\n else sb.append(c);\n }\n return sb.toString();\n }\n\n /** 分词：按非中文/非数字/非字母字符分割 */\n private List<String> tokenize(String s) {\n List<String> tokens = new ArrayList<>();\n StringBuilder cur = new StringBuilder();\n for (char c : s.toCharArray()) {\n if (Character.isLetterOrDigit(c)) {\n cur.append(c);\n } else {\n if (cur.length() > 0) {\n tokens.add(cur.toString());\n cur.setLength(0);\n }\n }\n }\n if (cur.length() > 0) {\n tokens.add(cur.toString());\n }\n return tokens;\n }\n\n // ========== JSON 工具方法 ==========\n\n private String extractJson(String text) {\n if (text == null) return null;\n text = text.replaceAll(\"```json\\\\s*\", \"\").replaceAll(\"```\\\\s*\", \"\");\n text = text.trim();\n if (text.startsWith(\"{\") && text.endsWith(\"}\")) {\n return text;\n }\n int start = text.indexOf('{');\n int end = text.lastIndexOf('}');\n if (start >= 0 && end > start) {\n return text.substring(start, end + 1);\n }\n return null;\n }\n\n @SuppressWarnings(\"unchecked\")\n private Map<String, Object> parseSimpleJson(String json) {\n Map<String, Object> result = new LinkedHashMap<>();\n json = json.trim();\n if (json.startsWith(\"{\") && json.endsWith(\"}\")) {\n json = json.substring(1, json.length() - 1).trim();\n }\n List<String> segments = splitTopLevel(json);\n for (String seg : segments) {\n int colonIdx = seg.indexOf(':');\n if (colonIdx < 0) continue;\n String key = seg.substring(0, colonIdx).trim();\n String value = seg.substring(colonIdx + 1).trim();\n key = unquote(key);\n if (value.startsWith(\"\\\"\")) {\n result.put(key, unquote(value));\n } else if (value.startsWith(\"[\")) {\n result.put(key, parseArray(value));\n } else if (value.startsWith(\"{\")) {\n result.put(key, parseSimpleJson(value));\n } else if (value.equals(\"null\")) {\n result.put(key, null);\n } else {\n try {\n if (value.contains(\".\")) {\n result.put(key, new BigDecimal(value));\n } else {\n result.put(key, Long.parseLong(value));\n }\n } catch (NumberFormatException e) {\n result.put(key, value);\n }\n }\n }\n return result;\n }\n\n private List<Map<String, Object>> parseArray(String arrayStr) {\n List<Map<String, Object>> list = new ArrayList<>();\n arrayStr = arrayStr.trim();\n if (arrayStr.startsWith(\"[\") && arrayStr.endsWith(\"]\")) {\n arrayStr = arrayStr.substring(1, arrayStr.length() - 1).trim();\n }\n int braceDepth = 0;\n int start = 0;\n for (int i = 0; i < arrayStr.length(); i++) {\n char c = arrayStr.charAt(i);\n if (c == '{') braceDepth++;\n else if (c == '}') braceDepth--;\n else if (c == ',' && braceDepth == 0) {\n String item = arrayStr.substring(start, i).trim();\n if (!item.isEmpty()) list.add(parseSimpleJson(item));\n start = i + 1;\n }\n }\n String last = arrayStr.substring(start).trim();\n if (!last.isEmpty()) list.add(parseSimpleJson(last));\n return list;\n }\n\n private List<String> splitTopLevel(String s) {\n List<String> parts = new ArrayList<>();\n int depth = 0, bracketDepth = 0;\n boolean inString = false;\n int start = 0;\n for (int i = 0; i < s.length(); i++) {\n char c = s.charAt(i);\n if (c == '\"' && (i == 0 || s.charAt(i - 1) != '\\\\')) inString = !inString;\n else if (!inString) {\n if (c == '{') depth++;\n else if (c == '}') depth--;\n else if (c == '[') bracketDepth++;\n else if (c == ']') bracketDepth--;\n else if (c == ',' && depth == 0 && bracketDepth == 0) {\n parts.add(s.substring(start, i));\n start = i + 1;\n }\n }\n }\n String last = s.substring(start).trim();\n if (!last.isEmpty()) parts.add(last);\n return parts;\n }\n\n private String unquote(String s) {\n s = s.trim();\n if (s.startsWith(\"\\\"\") && s.endsWith(\"\\\"\")) {\n return s.substring(1, s.length() - 1);\n }\n return s;\n }\n\n private BigDecimal toBigDecimal(Object obj) {\n if (obj == null) return null;\n if (obj instanceof BigDecimal) return (BigDecimal) obj;\n if (obj instanceof Number) return BigDecimal.valueOf(((Number) obj).doubleValue());\n if (obj instanceof String) {\n try { return new BigDecimal((String) obj); }\n catch (NumberFormatException e) { return null; }\n }\n return null;\n }\n}"}],"isError":false,"timestamp":1780018610301}}
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{"type":"message","id":"d00fbfa0","parentId":"1cc62cc2","timestamp":"2026-05-29T01:37:01.900Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user wants me to understand the full AiRecognitionServiceImpl code. Let me also look at the Controller and other related files to understand how the recognition result flows to the frontend.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_1dd3f9c4cc7a483795b877f4","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \"AiRecognition*\" | grep -v target","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \\\"AiRecognition*\\\" | grep -v target\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":1915,"output":144,"cacheRead":40704,"cacheWrite":0,"reasoningTokens":37,"totalTokens":42763,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018616555,"responseId":"chatcmpl-11ee4d2d-2c5d-4690-85f6-655c332a2fba"}}
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{"type":"message","id":"936b187f","parentId":"d00fbfa0","timestamp":"2026-05-29T01:37:02.633Z","message":{"role":"toolResult","toolCallId":"call_1dd3f9c4cc7a483795b877f4","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/dto/AiRecognitionResultDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/AiRecognitionService.java"}],"details":{"status":"completed","exitCode":0,"durationMs":215,"aggregated":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/dto/AiRecognitionResultDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/AiRecognitionService.java","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780018622633}}
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{"type":"message","id":"36fa566e","parentId":"936b187f","timestamp":"2026-05-29T01:37:15.074Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user wants me to:\n\n1. Fix the issue where returning IDs to the frontend doesn't populate the page - need to return names\n2. Customer/supplier - need to query their names\n3. Materials - use `MaterialFillService.getMaterialInfoMap()` for filling\n4. Document type - use data dictionary type\n5. Test with local DB\n6. Reference the [02-物料近似查询方案.md](yangxuan/设计/02-物料近似查询方案.md) design doc\n\nLet me understand the full picture. The user is saying the current `AiRecognitionServiceImpl` returns IDs but the frontend can't populate the page because it only has IDs, not the names.\n\nLet me check the `AiRecognitionResultDTO` more carefully and understand what's being returned.\n\nLooking at the code:\n- `Counterparty` has `id` and `name` - seems okay\n- `RecognitionItem` has `materialId`, `materialName`, `materialCode`, `spec`, `unit` - seems okay\n- But `typeValue`/`typeName` - typeValue is a dict value, but is there a proper dict type mapping?\n\nLet me look at:\n1. The current AiRecognitionController to see what's returned\n2. The MaterialFillService to understand how it works\n3. The dict service\n4. The frontend code to understand what it needs\n\nActually, wait - re-reading the user's message more carefully:\n\n> - 返回前端id 无法填充页面 - 客户供应商需要查询名称\n\nThis means: the frontend gets back IDs but can't populate the page. The customer/supplier names need to be queried.\n\nLet me look at the current flow:\n\n1. `AiRecognitionServiceImpl.recognize()` returns `AiRecognitionResultDTO`\n2. This is returned to frontend\n3. Frontend tries to auto-fill a form\n\nThe issue is: the frontend needs the **names** of customers/suppliers to fill the form, not just IDs. Let me check what `Counterparty` looks like.\n\nLooking at `AiRecognitionResultDTO.Counterparty`:\n```java\npublic static class Counterparty {\n private Long id;\n private String name;\n private String recognizedName;\n private boolean exactMatch;\n}\n```\n\nIt already has `name`. Hmm, so what's the issue?\n\nLet me re-read: \"返回前端id 无法填充页面 - 客户供应商需要查询名称\"\n\nMaybe the issue is that the frontend fields expect names, but the backend is just returning IDs? Or maybe the `getMaterialInfo` call in the current code isn't properly populating everything?\n\nLet me look at the `MaterialFillService.getMaterialInfo` vs `getMaterialInfoMap`.\n\nActually, looking more carefully at the AI recognition code:\n```java\nMaterialInfoDTO info = materialFillService.getMaterialInfo(best.getId());\n```\n\nIt uses `getMaterialInfo` (single) rather than `getMaterialInfoMap` (batch). The user says to use `getMaterialInfoMap`. Let me check MaterialFillService.\n\nAlso, let me check what data dictionary usage exists for the document type.\n\nLet me also check the frontend code.\n\nLet me look at things more carefully. I think there are several things to improve:\n\n1. **MaterialFillService**: Change from `getMaterialInfo` to `getMaterialInfoMap` for batch loading\n2. **Document type**: Use data dictionary properly (currently hardcoded)\n3. **Counterparty matching**: Ensure names are properly returned\n4. **Test with local DB**\n\nLet me check what exists and then make the changes.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_413cd3f86d63498c909941c6","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/MaterialFillService.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/MaterialFillService.java\"}"},{"type":"toolCall","id":"call_1c74f442ceca4fdc94cb7bc3","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/AiRecognitionService.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/AiRecognitionService.java\"}"},{"type":"toolCall","id":"call_94b05d5bb62547758eec6bf8","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \"AiRecognitionController.java\" -o -name \"AiRecognition*Controller*\" | grep -v target","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \\\"AiRecognitionController.java\\\" -o -name \\\"AiRecognition*Controller*\\\" | grep -v target\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":352,"output":1011,"cacheRead":42496,"cacheWrite":0,"reasoningTokens":763,"totalTokens":43859,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018622635,"responseId":"chatcmpl-322b884f-d2aa-4025-9e66-7c0b927e02df"}}
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{"type":"message","id":"b5bbc117","parentId":"36fa566e","timestamp":"2026-05-29T01:37:16.407Z","message":{"role":"toolResult","toolCallId":"call_413cd3f86d63498c909941c6","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.md.material.service;\n\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\n\nimport java.util.List;\nimport java.util.Map;\n\n/**\n * 物料信息填充服务\n * 用于在列表接口中批量填充物料相关信息\n */\npublic interface MaterialFillService {\n\n /**\n * 根据物料 ID 列表批量查询物料信息\n *\n * @param materialIds 物料 ID 列表\n * @return Map<物料 ID, 物料信息>\n */\n Map<Long, MaterialInfoDTO> getMaterialInfoMap(List<Long> materialIds);\n\n /**\n * 根据物料 ID 获取物料信息\n *\n * @param materialId 物料 ID\n * @return 物料信息，不存在返回 null\n */\n MaterialInfoDTO getMaterialInfo(Long materialId);\n\n /**\n * 获取物料类型字典映射\n *\n * @return Map<字典值，字典标签>\n */\n Map<String, String> getMaterialTypeDictMap();\n}\n"}],"isError":false,"timestamp":1780018636407}}
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{"type":"message","id":"a33af350","parentId":"b5bbc117","timestamp":"2026-05-29T01:37:16.408Z","message":{"role":"toolResult","toolCallId":"call_1c74f442ceca4fdc94cb7bc3","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.ai.service;\n\nimport com.witsoft.erp.module.ai.dto.AiRecognitionResultDTO;\nimport org.springframework.web.multipart.MultipartFile;\n\n/**\n * AI 单据识别服务接口\n */\npublic interface AiRecognitionService {\n\n /**\n * 识别单据图片，返回结构化的识别结果（供应商/客户/物料已模糊匹配 ID）\n */\n AiRecognitionResultDTO recognize(MultipartFile file);\n}"}],"isError":false,"timestamp":1780018636408}}
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{"type":"message","id":"faadc6aa","parentId":"a33af350","timestamp":"2026-05-29T01:37:16.408Z","message":{"role":"toolResult","toolCallId":"call_94b05d5bb62547758eec6bf8","toolName":"exec","content":[{"type":"text","text":"\n\n(Command exited with code 1)"}],"details":{"status":"completed","exitCode":1,"durationMs":412,"aggregated":"\n\n(Command exited with code 1)","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780018636408}}
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{"type":"message","id":"d47ccae9","parentId":"faadc6aa","timestamp":"2026-05-29T01:37:24.723Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Let me understand the task. The user wants me to:\n\n1. Read the design document `02-物料近似查询方案.md`\n2. Fix the AI recognition result so that:\n - Client/Supplier: returns name (not just ID)\n - Material: uses `MaterialFillService.getMaterialInfoMap()` to fill name, code, spec, unit\n - Document type (单据类型) should use data dictionary values\n - Test with local database\n\nThe issue is that when the front end receives the result, it can't populate the form because:\n1. Customer/supplier info only returns `id` without `name`\n2. Material info only returns `materialId` without filling in `materialName`, `materialCode`, `spec`, `unit`\n3. Document type needs to use data dictionary\n\nLet me look at the AI recognition result DTO more carefully, and the controller to understand the full flow.\n\nActually, wait - looking at the `AiRecognitionResultDTO`, it already has:\n- `Counterparty` with `id`, `name`, `recognizedName`, `exactMatch`\n- `RecognitionItem` with `materialId`, `materialName`, `materialCode`, `spec`, `unit`\n\nAnd in the implementation `matchMaterialItem()`, it's already using `materialFillService.getMaterialInfo(best.getId())` to fill material info.\n\nAnd `matchSupplier()` / `matchCustomer()` already return `Counterparty` with `name` from the database.\n\nSo what's the actual issue? Let me look at the AiRecognitionController to see what happens after recognition.\n\nLet me also check what's happening in the frontend to understand the \"cannot fill page\" issue.\n\nActually, re-reading the user's message more carefully:\n\n- \"返回前端id 无法填充页面\" - returning only ID can't fill the form\n- \"客户供应商需要查询名称\" - customer/supplier needs to query name (maybe the returned name isn't being used?)\n- \"物料使用MaterialFillService填充\" - material needs to use MaterialFillService\n- \"单据类型使用数据字典中类型\" - document type should use data dictionary values\n- \"使用local 库测试\" - test with local database\n\nLet me look at the current code more carefully. The `matchMaterialItem` does use `materialFillService.getMaterialInfo(best.getId())` for single item. But I see it's using `getMaterialInfo` singleton, not `getMaterialInfoMap` batch.\n\nAlso, I should check if the material fill is using the dict service for material type.\n\nLet me look at the `materialFillService.getMaterialInfoMap` and the `MaterialFillServiceImpl` to understand the filling.\n\nActually let me re-read the AiRecognitionServiceImpl more carefully. The issue might be:\n\n1. When multiple items are returned from AI, the matching is done one by one with individual `searchByNameLike()` + `getMaterialInfo()` - not using batch filling\n2. The counterparty returns just id without filling in the full name from database (or maybe the name is wrong)\n3. The typeValue/typeName might not be using proper data dict values\n\nLet me look at the controller first.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_9c8f0fcf6e404a44a2f4241e","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \"*AiRecognition*\" -o -name \"*AiController*\" -o -name \"*ai*Controller*\" | grep -v target","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \\\"*AiRecognition*\\\" -o -name \\\"*AiController*\\\" -o -name \\\"*ai*Controller*\\\" | grep -v target\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"},{"type":"toolCall","id":"call_6518ff9758b94858956647ff","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialFillServiceImpl.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialFillServiceImpl.java\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":699,"output":857,"cacheRead":42752,"cacheWrite":0,"reasoningTokens":665,"totalTokens":44308,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018636410,"responseId":"chatcmpl-c7f6656f-c687-4c02-978c-ef90bf936d20"}}
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{"type":"message","id":"0879d556","parentId":"d47ccae9","timestamp":"2026-05-29T01:37:25.871Z","message":{"role":"toolResult","toolCallId":"call_9c8f0fcf6e404a44a2f4241e","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/dto/AiRecognitionResultDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/AiRecognitionService.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/controller/AiController.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/test/java/com/witsoft/erp/module/ai/AiControllerTest.java"}],"details":{"status":"completed","exitCode":0,"durationMs":419,"aggregated":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/dto/AiRecognitionResultDTO.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/AiRecognitionService.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/controller/AiController.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/test/java/com/witsoft/erp/module/ai/AiControllerTest.java","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780018645870}}
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{"type":"message","id":"3572eed3","parentId":"0879d556","timestamp":"2026-05-29T01:37:25.871Z","message":{"role":"toolResult","toolCallId":"call_6518ff9758b94858956647ff","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.md.material.service.impl;\n\nimport com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;\nimport com.witsoft.erp.module.md.category.entity.MaterialCategory;\nimport com.witsoft.erp.module.md.category.mapper.MaterialCategoryMapper;\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\nimport com.witsoft.erp.module.md.material.entity.Material;\nimport com.witsoft.erp.module.md.material.mapper.MaterialMapper;\nimport com.witsoft.erp.module.md.material.service.MaterialFillService;\nimport com.witsoft.erp.module.system.dict.entity.DictData;\nimport com.witsoft.erp.module.system.dict.mapper.DictDataMapper;\nimport lombok.RequiredArgsConstructor;\nimport org.springframework.stereotype.Service;\n\nimport java.util.Collections;\nimport java.util.List;\nimport java.util.Map;\nimport java.util.stream.Collectors;\n\n/**\n * 物料信息填充服务实现类\n */\n@Service\n@RequiredArgsConstructor\npublic class MaterialFillServiceImpl implements MaterialFillService {\n\n private final MaterialMapper materialMapper;\n private final MaterialCategoryMapper categoryMapper;\n private final DictDataMapper dictDataMapper;\n\n @Override\n public Map<Long, MaterialInfoDTO> getMaterialInfoMap(List<Long> materialIds) {\n if (materialIds == null || materialIds.isEmpty()) {\n return Collections.emptyMap();\n }\n\n // 批量查询物料\n List<Material> materials = materialMapper.selectBatchIds(materialIds);\n if (materials.isEmpty()) {\n return Collections.emptyMap();\n }\n\n // 提取分类 ID 列表\n List<Long> categoryIds = materials.stream()\n .map(Material::getCategoryId)\n .filter(id -> id != null)\n .distinct()\n .collect(Collectors.toList());\n\n // 批量查询分类\n final Map<Long, String> categoryMap;\n if (!categoryIds.isEmpty()) {\n List<MaterialCategory> categories = categoryMapper.selectBatchIds(categoryIds);\n categoryMap = categories.stream()\n .collect(Collectors.toMap(MaterialCategory::getId, MaterialCategory::getCategoryName, (v1, v2) -> v1));\n } else {\n categoryMap = Collections.emptyMap();\n }\n\n // 查询物料类型字典\n final Map<String, String> materialTypeDictMap = getMaterialTypeDictMap();\n\n // 构建物料信息 Map\n return materials.stream()\n .map(material -> {\n MaterialInfoDTO dto = new MaterialInfoDTO();\n dto.setId(material.getId());\n dto.setMaterialCode(material.getMaterialCode());\n dto.setMaterialName(material.getMaterialName());\n dto.setSpec(material.getSpec());\n dto.setUnit(material.getUnit());\n dto.setMaterialType(material.getMaterialType());\n dto.setMaterialTypeName(materialTypeDictMap.get(material.getMaterialType()));\n dto.setCategoryId(material.getCategoryId());\n dto.setCategoryName(categoryMap.get(material.getCategoryId()));\n dto.setMinSafeQty(material.getMinSafeQty());\n return dto;\n })\n .collect(Collectors.toMap(MaterialInfoDTO::getId, m -> m));\n }\n\n @Override\n public MaterialInfoDTO getMaterialInfo(Long materialId) {\n if (materialId == null) {\n return null;\n }\n Material material = materialMapper.selectById(materialId);\n if (material == null) {\n return null;\n }\n\n MaterialInfoDTO dto = new MaterialInfoDTO();\n dto.setId(material.getId());\n dto.setMaterialCode(material.getMaterialCode());\n dto.setMaterialName(material.getMaterialName());\n dto.setSpec(material.getSpec());\n dto.setUnit(material.getUnit());\n dto.setMaterialType(material.getMaterialType());\n\n // 查询分类名称\n if (material.getCategoryId() != null) {\n MaterialCategory category = categoryMapper.selectById(material.getCategoryId());\n if (category != null) {\n dto.setCategoryId(category.getId());\n dto.setCategoryName(category.getCategoryName());\n }\n }\n\n // 查询物料类型名称\n Map<String, String> materialTypeDictMap = getMaterialTypeDictMap();\n dto.setMaterialTypeName(materialTypeDictMap.get(material.getMaterialType()));\n dto.setMinSafeQty(material.getMinSafeQty());\n\n return dto;\n }\n\n @Override\n public Map<String, String> getMaterialTypeDictMap() {\n List<DictData> typeDictList = dictDataMapper.selectList(\n new LambdaQueryWrapper<DictData>()\n .eq(DictData::getDictType, \"material_type\")\n .eq(DictData::getStatus, 0)\n .orderByAsc(DictData::getSort)\n );\n return typeDictList.stream()\n .collect(Collectors.toMap(DictData::getDictValue, DictData::getDictLabel, (v1, v2) -> v1));\n }\n}\n"}],"isError":false,"timestamp":1780018645871}}
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{"type":"message","id":"dee62cd0","parentId":"3572eed3","timestamp":"2026-05-29T01:37:33.472Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now let me understand the current state better. The user wants:\n\n1. **Return 名称 and 规格 from AI recognition** - the current code already does this for materials via MaterialFillService. But for the DTO level (AiRecognitionResultDTO), the fields are already there.\n\n2. **Customer/Supplier need to query name** - currently `matchCounterparty` returns `Counterparty` with id + name, but the comment says \"返回id但前端无法填充页面\". The issue is likely that the frontend expects 名称 but only gets id. Let me look at the actual issue more carefully.\n\n3. **Material uses MaterialFillService.getMaterialInfoMap to fill** - The current code already uses `materialFillService.getMaterialInfo()` for single material. The DTO has materialCode, materialName, spec, unit, etc. So this seems OK.\n\n4. **单据类型使用数据字典** - Currently `AiRecognitionServiceImpl` hardcodes type name: `\"采购入库\"` etc. This should use dictionary service.\n\n5. **Use local DB for testing** - need to check current datasource config.\n\nLet me look at the frontend to understand what's expected.","thinkingSignature":"reasoning_content"},{"type":"text","text":"让我先看看前端期望的返回结构，以及 Controller/测试文件"},{"type":"toolCall","id":"call_d335dd39c3444b8bab10a702","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/controller/AiController.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/controller/AiController.java\"}"},{"type":"toolCall","id":"call_46addebd33f246528f1da701","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/test/java/com/witsoft/erp/module/ai/AiControllerTest.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/test/java/com/witsoft/erp/module/ai/AiControllerTest.java\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":1687,"output":401,"cacheRead":43264,"cacheWrite":0,"reasoningTokens":247,"totalTokens":45352,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018645873,"responseId":"chatcmpl-687afcda-64ae-4f38-86d2-8af5699e8aa7"}}
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{"type":"message","id":"1613d2cd","parentId":"dee62cd0","timestamp":"2026-05-29T01:37:34.405Z","message":{"role":"toolResult","toolCallId":"call_d335dd39c3444b8bab10a702","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.ai.controller;\n\nimport com.witsoft.erp.common.core.Result;\nimport com.witsoft.erp.module.ai.dto.AiChatResponseDTO;\nimport com.witsoft.erp.module.ai.dto.AiRecognitionResultDTO;\nimport com.witsoft.erp.module.ai.dto.ImageUploadResponseDTO;\nimport com.witsoft.erp.module.ai.service.AiRecognitionService;\nimport com.witsoft.erp.module.ai.service.AiService;\nimport lombok.RequiredArgsConstructor;\nimport lombok.extern.slf4j.Slf4j;\nimport org.springframework.http.MediaType;\nimport org.springframework.web.bind.annotation.*;\nimport org.springframework.web.multipart.MultipartFile;\n\nimport java.util.List;\n\n/**\n * AI 对话控制器\n */\n@Slf4j\n@RestController\n@RequestMapping(\"/ai\")\n@RequiredArgsConstructor\npublic class AiController {\n\n private final AiService aiService;\n private final AiRecognitionService aiRecognitionService;\n\n /**\n * 图片上传 → 转 base64 返回\n */\n @PostMapping(\"/upload\")\n public Result<ImageUploadResponseDTO> uploadImage(@RequestParam(\"file\") MultipartFile file) {\n String originalName = file.getOriginalFilename();\n String mimeType = file.getContentType() != null ? file.getContentType() : \"image/png\";\n String base64 = aiService.imageToBase64(file);\n String dataUrl = \"data:\" + mimeType + \";base64,\" + base64;\n\n ImageUploadResponseDTO resp = ImageUploadResponseDTO.builder()\n .base64(base64)\n .dataUrl(dataUrl)\n .originalName(originalName)\n .size(file.getSize())\n .build();\n\n log.info(\"图片上传成功：name={}, size={}, dataUrlLen={}\", originalName, file.getSize(), dataUrl.length());\n return Result.ok(resp);\n }\n\n /**\n * 纯文本对话\n */\n @PostMapping(\"/chat\")\n public Result<AiChatResponseDTO> chat(@RequestParam(\"text\") String text) {\n AiChatResponseDTO resp = aiService.chatText(text);\n log.info(\"AI text 对话：promptTokens={}, completionTokens={}\",\n resp.getPromptTokens(), resp.getCompletionTokens());\n return Result.ok(resp);\n }\n\n /**\n * 多模态对话（文本 + 图片）\n * 使用 multipart/form-data，text 和 images 分开传\n */\n @PostMapping(value = \"/chat-multi\", consumes = MediaType.MULTIPART_FORM_DATA_VALUE)\n public Result<AiChatResponseDTO> chatMulti(\n @RequestParam(value = \"text\", required = false) String text,\n @RequestParam(value = \"images\", required = false) List<MultipartFile> images) {\n\n AiChatResponseDTO resp = aiService.chatWithImages(text, images);\n log.info(\"AI multi 对话：promptTokens={}, completionTokens={}\",\n resp.getPromptTokens(), resp.getCompletionTokens());\n return Result.ok(resp);\n }\n\n /**\n * 单据识别：上传单据照片 → 返回结构化识别结果（含模糊匹配的 ID）\n */\n @PostMapping(value = \"/recognize\", consumes = MediaType.MULTIPART_FORM_DATA_VALUE)\n public Result<AiRecognitionResultDTO> recognize(@RequestParam(\"file\") MultipartFile file) {\n AiRecognitionResultDTO resp = aiRecognitionService.recognize(file);\n log.info(\"AI 单据识别完成：type={}({}), counterparty={}\",\n resp.getTypeName(), resp.getTypeValue(), resp.getCounterparty() != null ? resp.getCounterparty().getName() : \"null\");\n return Result.ok(resp);\n }\n}"}],"isError":false,"timestamp":1780018654405}}
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{"type":"message","id":"a774ec3b","parentId":"1613d2cd","timestamp":"2026-05-29T01:37:34.406Z","message":{"role":"toolResult","toolCallId":"call_46addebd33f246528f1da701","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.ai;\n\nimport com.witsoft.erp.ErpApplication;\nimport com.witsoft.erp.common.core.Result;\nimport com.witsoft.erp.module.ai.dto.AiChatResponseDTO;\nimport com.witsoft.erp.module.ai.dto.AiRecognitionResultDTO;\nimport com.witsoft.erp.module.ai.dto.ImageUploadResponseDTO;\nimport com.witsoft.erp.test.base.BaseControllerTest;\nimport lombok.extern.slf4j.Slf4j;\nimport org.junit.jupiter.api.*;\nimport org.springframework.boot.test.context.SpringBootTest;\nimport org.springframework.core.ParameterizedTypeReference;\nimport org.springframework.core.io.ByteArrayResource;\nimport org.springframework.core.io.ClassPathResource;\nimport org.springframework.http.*;\nimport org.springframework.util.LinkedMultiValueMap;\nimport org.springframework.util.MultiValueMap;\n\nimport javax.imageio.ImageIO;\nimport java.awt.*;\nimport java.awt.image.BufferedImage;\nimport java.io.ByteArrayOutputStream;\nimport java.io.InputStream;\nimport java.util.List;\n\nimport static org.junit.jupiter.api.Assertions.*;\n\n/**\n * {@link com.witsoft.erp.module.ai.controller.AiController} 集成测试\n */\n@Slf4j\n@SpringBootTest(classes = ErpApplication.class, webEnvironment = SpringBootTest.WebEnvironment.RANDOM_PORT)\n@TestMethodOrder(MethodOrderer.OrderAnnotation.class)\nclass AiControllerTest extends BaseControllerTest {\n\n /** 生成 32x32 红色测试 PNG */\n private static byte[] createTestPng() {\n try {\n BufferedImage img = new BufferedImage(32, 32, BufferedImage.TYPE_INT_RGB);\n Graphics2D g = img.createGraphics();\n g.setColor(Color.RED);\n g.fillRect(0, 0, 32, 32);\n g.dispose();\n ByteArrayOutputStream baos = new ByteArrayOutputStream();\n ImageIO.write(img, \"png\", baos);\n return baos.toByteArray();\n } catch (Exception e) {\n throw new RuntimeException(e);\n }\n }\n\n private static final byte[] TEST_PNG_BYTES = createTestPng();\n\n @Test\n @Order(1)\n @DisplayName(\"1. 用户登录\")\n void testLogin() {\n login();\n }\n\n @Test\n @Order(2)\n @DisplayName(\"2. 图片上传 → base64\")\n void testUploadImage() {\n assumeToken();\n\n HttpHeaders headers = new HttpHeaders();\n headers.setContentType(MediaType.MULTIPART_FORM_DATA);\n if (authToken != null) {\n headers.setBearerAuth(authToken);\n }\n\n MultiValueMap<String, Object> body = new LinkedMultiValueMap<>();\n body.add(\"file\", new ByteArrayResource(TEST_PNG_BYTES) {\n @Override\n public String getFilename() {\n return \"test-red.png\";\n }\n });\n\n HttpEntity<MultiValueMap<String, Object>> entity = new HttpEntity<>(body, headers);\n\n ResponseEntity<Result<ImageUploadResponseDTO>> resp = restTemplate.exchange(\n url(\"/ai/upload\"), HttpMethod.POST, entity,\n new ParameterizedTypeReference<Result<ImageUploadResponseDTO>>() {});\n\n assertOk(resp);\n ImageUploadResponseDTO data = resp.getBody().getData();\n assertNotNull(data);\n assertNotNull(data.getBase64(), \"base64 不应为空\");\n assertNotNull(data.getDataUrl(), \"dataUrl 不应为空\");\n assertTrue(data.getDataUrl().startsWith(\"data:image/png;base64,\"), \"dataUrl 应 png 格式\");\n assertEquals(\"test-red.png\", data.getOriginalName());\n assertTrue(data.getSize() > 0);\n log.info(\"图片上传成功：base64Len={}, size={}\", data.getBase64().length(), data.getSize());\n }\n\n @Test\n @Order(3)\n @DisplayName(\"3. AI 纯文本对话\")\n void testChatText() {\n assumeToken();\n\n ResponseEntity<Result<AiChatResponseDTO>> resp = restTemplate.exchange(\n url(\"/ai/chat?text=你好，请用一句话介绍你自己\"), HttpMethod.POST,\n new HttpEntity<>(authHeaders()),\n new ParameterizedTypeReference<Result<AiChatResponseDTO>>() {});\n\n assertOk(resp);\n AiChatResponseDTO data = resp.getBody().getData();\n assertNotNull(data);\n assertNotNull(data.getReply(), \"AI 回复不应为空\");\n assertTrue(data.getReply().length() > 0, \"AI 回复应有内容\");\n log.info(\"AI 文本对话回复：{}\", data.getReply().substring(0, Math.min(100, data.getReply().length())));\n log.info(\"token 消耗：prompt={}, completion={}, total={}\",\n data.getPromptTokens(), data.getCompletionTokens(), data.getTotalTokens());\n }\n\n @Test\n @Order(5)\n @DisplayName(\"5. AI 单据识别 - 到货单图片 → 匹配供应商 + 物料\")\n void testRecognize() {\n assumeToken();\n\n // 从 classpath 读取测试图片\n byte[] imageBytes;\n try (InputStream is = new ClassPathResource(\"test_png.png\").getInputStream()) {\n imageBytes = is.readAllBytes();\n } catch (Exception e) {\n throw new RuntimeException(\"无法读取 test_png.png\", e);\n }\n assertTrue(imageBytes.length > 0);\n\n HttpHeaders headers = new HttpHeaders();\n headers.setContentType(MediaType.MULTIPART_FORM_DATA);\n if (authToken != null) {\n headers.setBearerAuth(authToken);\n }\n\n MultiValueMap<String, Object> body = new LinkedMultiValueMap<>();\n body.add(\"file\", new ByteArrayResource(imageBytes) {\n @Override\n public String getFilename() {\n return \"test_png.png\";\n }\n });\n\n HttpEntity<MultiValueMap<String, Object>> entity = new HttpEntity<>(body, headers);\n\n ResponseEntity<Result<AiRecognitionResultDTO>> resp = restTemplate.exchange(\n url(\"/ai/recognize\"), HttpMethod.POST, entity,\n new ParameterizedTypeReference<Result<AiRecognitionResultDTO>>() {});\n\n assertOk(resp);\n AiRecognitionResultDTO data = resp.getBody().getData();\n assertNotNull(data, \"识别结果不应为空\");\n assertNotNull(data.getTypeValue(), \"应识别单据类型\");\n\n log.info(\"AI 单据识别结果：\");\n log.info(\" 类型：{} (value={})\", data.getTypeName(), data.getTypeValue());\n\n // 验证供应商匹配\n AiRecognitionResultDTO.Counterparty cp = data.getCounterparty();\n if (cp != null) {\n log.info(\" 供应商/客户：id={}, name={}, 原始={}, 精确匹配={}\",\n cp.getId(), cp.getName(), cp.getRecognizedName(), cp.isExactMatch());\n assertNotNull(cp.getId(), \"应匹配到供应商 ID\");\n assertEquals(\"老兵水晶店\", cp.getName(), \"供应商名称应一致\");\n }\n\n // 验证物料匹配\n List<AiRecognitionResultDTO.RecognitionItem> items = data.getItems();\n assertNotNull(items, \"物料明细不应为空\");\n assertFalse(items.isEmpty(), \"应识别出物料明细\");\n log.info(\" 物料明细（{} 条）：\", items.size());\n for (AiRecognitionResultDTO.RecognitionItem item : items) {\n log.info(\" - materialId={}, name={}, code={}, spec={}, unit={}, quantity={}, price={}, 原始={}, 精确={}\",\n item.getMaterialId(), item.getMaterialName(), item.getMaterialCode(),\n item.getSpec(), item.getUnit(),\n item.getQuantity(), item.getPrice(), item.getRecognizedName(), item.isExactMatch());\n }\n\n // 本地库有数据，验证物料应匹配成功\n long matchedCount = items.stream().filter(i -> i.getMaterialId() != null).count();\n long unmatchedCount = items.stream().filter(i -> i.getMaterialId() == null).count();\n log.info(\" 匹配结果：{} 条已匹配, {} 条未匹配\", matchedCount, unmatchedCount);\n\n log.info(\"✓ 单据识别验证通过\");\n }\n}"}],"isError":false,"timestamp":1780018654405}}
|
||
{"type":"message","id":"6e6b5dea","parentId":"a774ec3b","timestamp":"2026-05-29T01:37:58.959Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Let me understand what the user wants:\n\n1. **返回前端 id 无法填充页面** - The current DTO returns IDs for counterparty (supplier/customer) and materials, but the frontend can't fill the form with just IDs. It needs the names too.\n\n2. **客户供应商需要查询名称** - For customers and suppliers, the DTO needs to return the actual name (not just ID), so the frontend can display it.\n\n3. **物料使用 MaterialFillService.getMaterialInfoMap 填充** - For materials, use `MaterialFillService.getMaterialInfoMap()` to fill in material information.\n\n4. **单据类型使用数据字典中类型** - The document type should use values from the data dictionary.\n\n5. **使用 local 库测试** - Test using the local database.\n\nLet me look at the current `AiRecognitionResultDTO` to understand what it returns and what needs to change:\n\nLooking at the current code:\n- `Counterparty` already has `id`, `name`, `recognizedName`, `exactMatch` - seems like it already returns names\n- `RecognitionItem` already has `materialId`, `materialName`, `materialCode`, `spec`, `unit` - also seems fine\n\nWait, let me re-read the user's request more carefully:\n\n1. \"返回前端id无法填充页面\" - maybe the issue is that the Counterparty only returns an ID without name when match fails? Let me check.\n\nLooking at `AiRecognitionResultDTO.Counterparty`:\n```java\npublic static class Counterparty {\n private Long id;\n private String name; // 匹配到的名称\n private String recognizedName;\n private boolean exactMatch;\n}\n```\n\nAnd in `AiRecognitionResultDTO.RecognitionItem`:\n```java\npublic static class RecognitionItem {\n private Long materialId;\n private String materialName;\n private String materialCode;\n private String spec;\n private String unit;\n private String recognizedName;\n private BigDecimal quantity;\n private BigDecimal price;\n private boolean exactMatch;\n}\n```\n\nLooking at `matchCounterparty` in the impl, when it fails:\n```java\nreturn AiRecognitionResultDTO.Counterparty.builder()\n .name(recognizedName)\n .recognizedName(recognizedName)\n .exactMatch(false)\n .build();\n```\nThis returns name but no ID. That's probably OK.\n\nFor materials, when it fails:\n```java\nreturn AiRecognitionResultDTO.RecognitionItem.builder()\n .materialName(materialName)\n .spec(spec)\n .recognizedName(materialName)\n .quantity(quantity)\n .price(price)\n .unit(unit)\n .exactMatch(false)\n .build();\n```\nAlso returns name but no ID.\n\nHmm, but the user says \"返回前端id无法填充页面\" - maybe the issue is about a different part of the system? Let me think about this differently.\n\nThe user mentions these specific points:\n1. IDs alone can't fill the page → need name + code + spec etc.\n2. Customer/supplier need name query → use service to look up the actual name\n3. Materials use `MaterialFillService.getMaterialInfoMap` to fill info\n4. Document type uses data dictionary\n5. Use local database for testing\n\nLooking at the current code, it already does some of this. But let me look at the full context again. The user is asking me to implement changes that address these interaction/UX issues.\n\nLet me check: when the AI matches a counterparty, the current code returns `Counterparty` with id + name. Is the issue that the frontend can't use just an ID and needs the full name? That seems to already be there...\n\nWait, I think the user might be talking about a NEW feature or interaction point - not just the AI recognition. They might be talking about a general \"approximate query\" interaction where:\n\n1. User types something\n2. System does approximate match\n3. Returns structured results with display info (name, spec, code, unit, etc.) so the frontend can properly display and fill forms\n\nLet me re-read: \"返回前端id无法填充页面\" - this means \"returning an ID to the frontend can't fill the page\" - so the current behavior of returning IDs is insufficient. The frontend needs display names/descriptions.\n\nAnd \"客户供应商需要查询名称\" - for customer/supplier, we need to query and return the name.\n\n\"物料使用com.witsoft.erp.module.md.material.service.MaterialFillService.getMaterialInfoMap填充\" - for materials, use MaterialFillService to fill the info.\n\nI think the user wants me to improve the `AiRecognitionResultDTO` and its usage so that:\n1. Counterparty returns both id + name (already done)\n2. Materials use MaterialFillService to fill material info (already done)\n3. Document type uses dict values (need to check this)\n\nLet me check the `typeValue` handling. In `AiRecognitionServiceImpl`:\n```java\nprivate static final Map<String, Integer> TYPE_MAPPING = Map.of(\n \"purchase_inbound\", 10,\n \"sales_outbound\", 10\n);\n\nprivate Integer toTypeValue(String type) {\n return TYPE_MAPPING.getOrDefault(type, 10);\n}\n```\nThis hardcodes the mapping. The user wants to use the data dictionary instead of hardcoded values.\n\nActually wait, looking at the `toTypeName` method, it also has hardcoded values:\n```java\nprivate String toTypeName(Integer typeValue) {\n if (typeValue == null) return null;\n if (typeValue == 10) return \"采购入库\";\n if (typeValue == 20) return \"退货入库\";\n if (typeValue == 30) return \"其他入库\";\n return null;\n}\n```\n\nAnd `sales_outbound` maps to `10` too which is same as `purchase_inbound`, which seems wrong.\n\nThe user wants to:\n1. Query customer/supplier names properly → already done with `matchSupplier`/`matchCustomer`\n2. Use `MaterialFillService` for material info → already done with `materialFillService.getMaterialInfo(best.getId())`\n3. Use data dictionary for document types → need to replace hardcoded type mapping\n4. Ensure the frontend gets enough display info → need to ensure DTO has name, code, spec, unit etc.\n\nActually, let me reconsider. Maybe the user wants me to:\n1. Look at what the frontend expects\n2. Fix the current code to provide better structured data\n3. Write/update tests to verify with local DB\n\nLet me look at the test to understand the expected flow better.\n\nThe test (`AiControllerTest.testRecognize`) expects:\n- Counterparty id not null, name = \"老兵水晶店\"\n- Material items have materialId, materialName, materialCode, spec, unit, quantity, price\n\nSo the DTO already seems to provide name, code, spec, unit, etc.\n\nBut wait - the user says the issues are:\n1. IDs alone can't fill forms → need names\n2. Customer/supplier need name queries\n3. Material uses MaterialFillService\n4. Document type uses dict\n\nLooking more carefully at the existing code, I think the problem might be in how the AI recognition works end-to-end. Let me look at what the frontend might expect:\n\nFor a \"new inbound order\" or \"new outbound order\" page, the frontend probably:\n1. User uploads a receipt image\n2. AI recognizes it and returns structured data\n3. Frontend auto-fills the form with the recognized data\n4. The form needs: supplier name (or ID for autocomplete), warehouse, items with material name/code/spec/unit, quantities, prices, etc.\n\nIf the AI returns just IDs, the frontend can't render them without additional API calls. But our code already returns both id and name.\n\nLet me focus on what I think the user actually wants fixed:\n\n1. **单据类型使用数据字典** → Instead of hardcoded type mapping, use the `DictService` or `DictDataMapper` to look up document type from the data dictionary\n2. **Ensure the DTO properly returns display info** → Double-check all returned fields\n3. **Use MaterialFillService properly** → Already done, but let me verify it's comprehensive\n4. **Test with local DB** → The test uses `BaseControllerTest` which should use local DB\n\nActually, let me just start implementing. The user seems to want me to improve the code based on these points, and test it.\n\nKey changes needed:\n1. **Document type from dict**: Replace hardcoded `TYPE_MAPPING` and `toTypeName` with dict service lookup\n2. **Ensure counterparty returns name** for supplier/customer - already mostly there\n3. **Ensure material info is filled** via MaterialFillService - already there\n4. **Write/update tests** for local DB testing\n\nLet me also look at what document types are available in the dict system:\n\nLet me look at the dict_data table for document types.\n\nAlso, I need to understand what \"单据类型\" means in this context. The current code has `typeValue=10` for both `purchase_inbound` and `sales_outbound`, which maps to \"采购入库\" - this is clearly wrong for sales.\n\nLooking more carefully at the code, `TYPE_MAPPING` has:\n- `purchase_inbound` → 10 \n- `sales_outbound` → 10 (same as purchase_inbound, seems wrong)\n\nAnd `toTypeName`:\n- 10 → \"采购入库\"\n- 20 → \"退货入库\" \n- 30 → \"其他入库\"\n\nThis doesn't even account for sales outbound types. The user wants this to use data dictionary values instead.\n\nLet me look at what dict types exist in the system for inbound/outbound types:\n\nLet me check the SQL for inbound type dict and outbound type dict data.\n\nOK, I think I need to understand the dict structure first. Let me check the existing dict data in the system.\n\nActually, let me just check the SQL data to understand the dict structure for document types.\n\nLet me also look at the `DictService` to understand how to use it.\n\nLet me look at the system's DictService.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_64fedfdbe667489f8660afe2","name":"exec","arguments":{"command":"grep -rn \"inbound_type\\|outbound_type\\|business_type\\|bill_type\\|单据类型\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/ --include=\"*.sql\" | head -20","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"grep -rn \\\"inbound_type\\\\|outbound_type\\\\|business_type\\\\|bill_type\\\\|单据类型\\\" /home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/ --include=\\\"*.sql\\\" | head -20\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"},{"type":"toolCall","id":"call_0aaf98c75b714616859ea79f","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \"DictService.java\" -o -name \"DictDataMapper.java\" | grep -v target","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \\\"DictService.java\\\" -o -name \\\"DictDataMapper.java\\\" | grep -v target\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":2936,"output":2423,"cacheRead":44800,"cacheWrite":0,"reasoningTokens":2195,"totalTokens":50159,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018654408,"responseId":"chatcmpl-abc89529-1259-4279-9fd8-965ec05fdf26"}}
|
||
{"type":"message","id":"cefb912f","parentId":"6e6b5dea","timestamp":"2026-05-29T01:38:00.304Z","message":{"role":"toolResult","toolCallId":"call_64fedfdbe667489f8660afe2","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:7:-- inbound_type: 10-采购入库，20-退货入库，30-其他入库\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:8:-- outbound_type: 10-销售出库，20-领料出库，30-其他出库\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:62: INSERT INTO im_inbound (id,inbound_no,inbound_type,inbound_date,supplier_id,supplier_name,warehouse_id,warehouse_name,status,total_amount,remark,creator,create_time,updater,update_time,deleted,ecid) VALUES (inbound_id, inbound_no, 10, inbound_date, sup_id, '江苏料新', wh_id, '原料仓', 2, qty*price, '模拟入库', 'admin', now(), 'admin', now(), 0, 'default');\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:83: INSERT INTO im_inbound (id,inbound_no,inbound_type,inbound_date,supplier_id,supplier_name,warehouse_id,warehouse_name,status,total_amount,remark,creator,create_time,updater,update_time,deleted,ecid) VALUES (inbound_id, inbound_no, 10, inbound_date, sup_id, '梓伊水晶', wh_id, '原料仓', 2, qty*price, '模拟入库', 'admin', now(), 'admin', now(), 0, 'default');\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:104: INSERT INTO im_inbound (id,inbound_no,inbound_type,inbound_date,supplier_id,supplier_name,warehouse_id,warehouse_name,status,total_amount,remark,creator,create_time,updater,update_time,deleted,ecid) VALUES (inbound_id, inbound_no, 10, inbound_date, sup_id, '老兵水晶店', wh_id, '原料仓', 2, qty*price, '模拟入库', 'admin', now(), 'admin', now(), 0, 'default');\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:125: INSERT INTO im_outbound (id,outbound_no,outbound_type,outbound_date,customer_id,customer_name,warehouse_id,warehouse_name,status,total_amount,remark,creator,create_time,updater,update_time,deleted,ecid) VALUES (outbound_id, outbound_no, 10, outbound_date, cus_id, '老朱 001', wh_id, '成品仓', 2, qty*price, '模拟出库', 'admin', now(), 'admin', now(), 0, 'default');\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:146: INSERT INTO im_outbound (id,outbound_no,outbound_type,outbound_date,customer_id,customer_name,warehouse_id,warehouse_name,status,total_amount,remark,creator,create_time,updater,update_time,deleted,ecid) VALUES (outbound_id, outbound_no, 10, outbound_date, cus_id, '布莱恩宋锡元', wh_id, '成品仓', 2, qty*price, '模拟出库', 'admin', now(), 'admin', now(), 0, 'default');\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:167: INSERT INTO im_outbound (id,outbound_no,outbound_type,outbound_date,customer_id,customer_name,warehouse_id,warehouse_name,status,total_amount,remark,creator,create_time,updater,update_time,deleted,ecid) VALUES (outbound_id, outbound_no, 10, outbound_date, cus_id, 'LYMSAC2023', wh_id, '成品仓', 2, qty*price, '模拟出库', 'admin', now(), 'admin', now(), 0, 'default');\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-slow-moving-data.sql:149: INSERT INTO im_inbound (id, inbound_no, inbound_type, inbound_date, supplier_id, warehouse_id, total_amount, remark, creator, create_time, updater, update_time, deleted, ecid)\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-slow-moving-data.sql:192: INSERT INTO im_outbound (id, outbound_no, outbound_type, outbound_date, customer_id, warehouse_id, total_amount, remark, creator, create_time, updater, update_time, deleted, ecid)\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/10-system.sql:184: business_type SMALLINT,\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/10-system.sql:210:COMMENT ON COLUMN sys_oper_log.business_type IS '业务类型（0-其它，1-新增，2-修改，3-删除，4-导出，5-导入，6-审核）';\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:64:SELECT nextval('sys_dict_type_seq'), '入库类型', 'inbound_type', 10, 0, 'default', 'system', CURRENT_TIMESTAMP\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:65:WHERE NOT EXISTS (SELECT 1 FROM sys_dict_type WHERE dict_type = 'inbound_type' AND ecid = 'default');\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:69:SELECT nextval('sys_dict_type_seq'), '出库类型', 'outbound_type', 11, 0, 'default', 'system', CURRENT_TIMESTAMP\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:70:WHERE NOT EXISTS (SELECT 1 FROM sys_dict_type WHERE dict_type = 'outbound_type' AND ecid = 'default');\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:88:SELECT nextval('sys_dict_data_seq'), 'inbound_type', '采购入库', '10', 1, 0, 'default', 'system', CURRENT_TIMESTAMP\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:89:WHERE NOT EXISTS (SELECT 1 FROM sys_dict_data WHERE dict_type = 'inbound_type' AND dict_value = '10' AND ecid = 'default');\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:92:SELECT nextval('sys_dict_data_seq'), 'inbound_type', '退货入库', '20', 2, 0, 'default', 'system', CURRENT_TIMESTAMP\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:93:WHERE NOT EXISTS (SELECT 1 FROM sys_dict_data WHERE dict_type = 'inbound_type' AND dict_value = '20' AND ecid = 'default');"}],"details":{"status":"completed","exitCode":0,"durationMs":408,"aggregated":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:7:-- inbound_type: 10-采购入库，20-退货入库，30-其他入库\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:8:-- outbound_type: 10-销售出库，20-领料出库，30-其他出库\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:62: INSERT INTO im_inbound (id,inbound_no,inbound_type,inbound_date,supplier_id,supplier_name,warehouse_id,warehouse_name,status,total_amount,remark,creator,create_time,updater,update_time,deleted,ecid) VALUES (inbound_id, inbound_no, 10, inbound_date, sup_id, '江苏料新', wh_id, '原料仓', 2, qty*price, '模拟入库', 'admin', now(), 'admin', now(), 0, 'default');\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:83: INSERT INTO im_inbound (id,inbound_no,inbound_type,inbound_date,supplier_id,supplier_name,warehouse_id,warehouse_name,status,total_amount,remark,creator,create_time,updater,update_time,deleted,ecid) VALUES (inbound_id, inbound_no, 10, inbound_date, sup_id, '梓伊水晶', wh_id, '原料仓', 2, qty*price, '模拟入库', 'admin', now(), 'admin', now(), 0, 'default');\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:104: INSERT INTO im_inbound (id,inbound_no,inbound_type,inbound_date,supplier_id,supplier_name,warehouse_id,warehouse_name,status,total_amount,remark,creator,create_time,updater,update_time,deleted,ecid) VALUES (inbound_id, inbound_no, 10, inbound_date, sup_id, '老兵水晶店', wh_id, '原料仓', 2, qty*price, '模拟入库', 'admin', now(), 'admin', now(), 0, 'default');\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:125: INSERT INTO im_outbound (id,outbound_no,outbound_type,outbound_date,customer_id,customer_name,warehouse_id,warehouse_name,status,total_amount,remark,creator,create_time,updater,update_time,deleted,ecid) VALUES (outbound_id, outbound_no, 10, outbound_date, cus_id, '老朱 001', wh_id, '成品仓', 2, qty*price, '模拟出库', 'admin', now(), 'admin', now(), 0, 'default');\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:146: INSERT INTO im_outbound (id,outbound_no,outbound_type,outbound_date,customer_id,customer_name,warehouse_id,warehouse_name,status,total_amount,remark,creator,create_time,updater,update_time,deleted,ecid) VALUES (outbound_id, outbound_no, 10, outbound_date, cus_id, '布莱恩宋锡元', wh_id, '成品仓', 2, qty*price, '模拟出库', 'admin', now(), 'admin', now(), 0, 'default');\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-inout-data.sql:167: INSERT INTO im_outbound (id,outbound_no,outbound_type,outbound_date,customer_id,customer_name,warehouse_id,warehouse_name,status,total_amount,remark,creator,create_time,updater,update_time,deleted,ecid) VALUES (outbound_id, outbound_no, 10, outbound_date, cus_id, 'LYMSAC2023', wh_id, '成品仓', 2, qty*price, '模拟出库', 'admin', now(), 'admin', now(), 0, 'default');\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-slow-moving-data.sql:149: INSERT INTO im_inbound (id, inbound_no, inbound_type, inbound_date, supplier_id, warehouse_id, total_amount, remark, creator, create_time, updater, update_time, deleted, ecid)\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/mock-slow-moving-data.sql:192: INSERT INTO im_outbound (id, outbound_no, outbound_type, outbound_date, customer_id, warehouse_id, total_amount, remark, creator, create_time, updater, update_time, deleted, ecid)\r\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/10-system.sql:184: business_type SMALLINT,\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/10-system.sql:210:COMMENT ON COLUMN sys_oper_log.business_type IS '业务类型（0-其它，1-新增，2-修改，3-删除，4-导出，5-导入，6-审核）';\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:64:SELECT nextval('sys_dict_type_seq'), '入库类型', 'inbound_type', 10, 0, 'default', 'system', CURRENT_TIMESTAMP\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:65:WHERE NOT EXISTS (SELECT 1 FROM sys_dict_type WHERE dict_type = 'inbound_type' AND ecid = 'default');\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:69:SELECT nextval('sys_dict_type_seq'), '出库类型', 'outbound_type', 11, 0, 'default', 'system', CURRENT_TIMESTAMP\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:70:WHERE NOT EXISTS (SELECT 1 FROM sys_dict_type WHERE dict_type = 'outbound_type' AND ecid = 'default');\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:88:SELECT nextval('sys_dict_data_seq'), 'inbound_type', '采购入库', '10', 1, 0, 'default', 'system', CURRENT_TIMESTAMP\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:89:WHERE NOT EXISTS (SELECT 1 FROM sys_dict_data WHERE dict_type = 'inbound_type' AND dict_value = '10' AND ecid = 'default');\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:92:SELECT nextval('sys_dict_data_seq'), 'inbound_type', '退货入库', '20', 2, 0, 'default', 'system', CURRENT_TIMESTAMP\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/scripts/postgresql/99-data.sql:93:WHERE NOT EXISTS (SELECT 1 FROM sys_dict_data WHERE dict_type = 'inbound_type' AND dict_value = '20' AND ecid = 'default');","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780018680303}}
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||
{"type":"message","id":"d4af6a8d","parentId":"cefb912f","timestamp":"2026-05-29T01:38:00.305Z","message":{"role":"toolResult","toolCallId":"call_0aaf98c75b714616859ea79f","toolName":"exec","content":[{"type":"text","text":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/system/dict/service/DictService.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/system/dict/mapper/DictDataMapper.java"}],"details":{"status":"completed","exitCode":0,"durationMs":407,"aggregated":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/system/dict/service/DictService.java\n/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/system/dict/mapper/DictDataMapper.java","cwd":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"isError":false,"timestamp":1780018680304}}
|
||
{"type":"message","id":"f696779c","parentId":"d4af6a8d","timestamp":"2026-05-29T01:38:07.242Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Let me understand the full picture. The user wants to fix the AI recognition service so that:\n\n1. **客户/供应商** — currently returns `id` but the frontend needs the name too for filling. The `Counterparty` already has `name`, so need to check if it's filling properly from database.\n\n2. **物料** — should use `MaterialFillService.getMaterialInfoMap()` to enrich material info. Looking at current code, it already uses `materialFillService.getMaterialInfo(best.getId())` for each item individually. But the user wants batch query via `getMaterialInfoMap()`.\n\n3. **单据类型** — should use data dictionary values (`inbound_type` / `outbound_type`). Currently hardcoded mapping `toTypeValue`/`toTypeName` which is wrong - AI returns \"purchase_inbound\"/\"sales_outbound\" and maps to hardcoded values.\n\n4. **测试** — use local database.\n\nLet me re-read the requirements more carefully:\n\n> - 返回前端id 无法填充页面\n> - 客户供应商需要查询名称\n> - 物料使用MaterialFillService.getMaterialInfoMap填充\n> - 单据类型使用 数据字典中类型\n> - 使用local 库测试\n\nSo the issues are:\n1. Counterparty: currently uses `Counterparty` with `id` + `name`, but need to verify the name is actually being returned correctly. Let me check the `searchByNameLike` implementations for customer and supplier.\n\n2. Material: already uses `getMaterialInfo(best.getId())` per-item but not `getMaterialInfoMap()` batch. Should batch all matched material IDs.\n\n3. Document type: currently hardcoded, should use `inbound_type`/`outbound_type` dictionary from DB.\n\nLet me check the existing supplier/customer `searchByNameLike`:","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_3dac51f6a4d3497daad0f736","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/supplier/service/impl/SupplierServiceImpl.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/supplier/service/impl/SupplierServiceImpl.java\"}"},{"type":"toolCall","id":"call_3fcd46f4543f4da8b7f2d651","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/customer/service/impl/CustomerServiceImpl.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/customer/service/impl/CustomerServiceImpl.java\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":2173,"output":542,"cacheRead":47616,"cacheWrite":0,"reasoningTokens":394,"totalTokens":50331,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018680310,"responseId":"chatcmpl-367d85e7-81f8-4580-a775-5136d323c333"}}
|
||
{"type":"message","id":"64cf063f","parentId":"f696779c","timestamp":"2026-05-29T01:38:08.178Z","message":{"role":"toolResult","toolCallId":"call_3dac51f6a4d3497daad0f736","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.md.supplier.service.impl;\n\nimport com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;\nimport com.baomidou.mybatisplus.extension.plugins.pagination.Page;\nimport com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;\nimport com.witsoft.erp.common.util.CodeGeneratorUtil;\nimport com.witsoft.erp.module.md.supplier.dto.SupplierSaveReqDTO;\nimport com.witsoft.erp.module.md.supplier.entity.Supplier;\nimport com.witsoft.erp.module.md.supplier.mapper.SupplierMapper;\nimport com.witsoft.erp.module.md.supplier.service.SupplierService;\nimport lombok.RequiredArgsConstructor;\nimport org.springframework.jdbc.core.JdbcTemplate;\nimport org.springframework.stereotype.Service;\nimport org.springframework.transaction.annotation.Transactional;\n\nimport java.util.List;\n\n/**\n * 供应商 Service 实现类\n */\n@Service\n@RequiredArgsConstructor\npublic class SupplierServiceImpl extends ServiceImpl<SupplierMapper, Supplier> implements SupplierService {\n\n private final JdbcTemplate jdbcTemplate;\n\n @Override\n public Page<Supplier> pageList(Supplier supplier, int pageNum, int pageSize) {\n LambdaQueryWrapper<Supplier> wrapper = new LambdaQueryWrapper<Supplier>();\n\n if (supplier.getName() != null) {\n wrapper.like(Supplier::getName, supplier.getName());\n }\n if (supplier.getSupplierCode() != null) {\n wrapper.like(Supplier::getSupplierCode, supplier.getSupplierCode());\n }\n\n wrapper.orderByDesc(Supplier::getCreateTime);\n\n return this.page(new Page<>(pageNum, pageSize), wrapper);\n }\n\n @Override\n @Transactional(rollbackFor = Exception.class)\n public Long saveSupplier(SupplierSaveReqDTO dto) {\n Supplier supplier = new Supplier();\n\n // 如果编码为空，自动生成\n if (dto.getSupplierCode() == null || dto.getSupplierCode().trim().isEmpty()) {\n // 从序列获取下一个值\n Long sequenceValue = jdbcTemplate.queryForObject(\"SELECT nextval('seq_md_supplier_code')\", Long.class);\n supplier.setSupplierCode(CodeGeneratorUtil.generateSupplierCode(sequenceValue));\n } else {\n supplier.setSupplierCode(dto.getSupplierCode());\n }\n\n supplier.setName(dto.getName());\n supplier.setContact(dto.getContact());\n supplier.setMobile(dto.getMobile());\n supplier.setTelephone(dto.getTelephone());\n supplier.setPhone(dto.getPhone());\n supplier.setEmail(dto.getEmail());\n supplier.setFax(dto.getFax());\n supplier.setAddress(dto.getAddress());\n supplier.setTaxNumber(dto.getTaxNumber());\n supplier.setTaxPercent(dto.getTaxPercent());\n supplier.setBankName(dto.getBankName());\n supplier.setBankAccount(dto.getBankAccount());\n supplier.setBankAddress(dto.getBankAddress());\n supplier.setSort(dto.getSort());\n supplier.setStatus(dto.getStatus() != null ? dto.getStatus() : 0);\n supplier.setRemark(dto.getRemark());\n this.save(supplier);\n return supplier.getId();\n }\n\n @Override\n @Transactional(rollbackFor = Exception.class)\n public void updateSupplier(SupplierSaveReqDTO dto) {\n Supplier supplier = new Supplier();\n supplier.setId(dto.getId());\n supplier.setSupplierCode(dto.getSupplierCode());\n supplier.setName(dto.getName());\n supplier.setContact(dto.getContact());\n supplier.setMobile(dto.getMobile());\n supplier.setTelephone(dto.getTelephone());\n supplier.setPhone(dto.getPhone());\n supplier.setEmail(dto.getEmail());\n supplier.setFax(dto.getFax());\n supplier.setAddress(dto.getAddress());\n supplier.setTaxNumber(dto.getTaxNumber());\n supplier.setTaxPercent(dto.getTaxPercent());\n supplier.setBankName(dto.getBankName());\n supplier.setBankAccount(dto.getBankAccount());\n supplier.setBankAddress(dto.getBankAddress());\n supplier.setSort(dto.getSort());\n supplier.setStatus(dto.getStatus());\n supplier.setRemark(dto.getRemark());\n this.updateById(supplier);\n }\n\n @Override\n public List<Supplier> searchByNameLike(String keyword) {\n if (keyword == null || keyword.trim().isEmpty()) {\n return List.of();\n }\n LambdaQueryWrapper<Supplier> wrapper = new LambdaQueryWrapper<>();\n wrapper.like(Supplier::getName, keyword.trim());\n wrapper.last(\"LIMIT 10\");\n return list(wrapper);\n }\n\n}"}],"isError":false,"timestamp":1780018688178}}
|
||
{"type":"message","id":"db85b959","parentId":"64cf063f","timestamp":"2026-05-29T01:38:08.179Z","message":{"role":"toolResult","toolCallId":"call_3fcd46f4543f4da8b7f2d651","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.md.customer.service.impl;\r\n\r\nimport com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;\r\nimport com.baomidou.mybatisplus.extension.plugins.pagination.Page;\r\nimport com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;\r\nimport com.witsoft.erp.common.util.CodeGeneratorUtil;\r\nimport com.witsoft.erp.module.md.customer.dto.CustomerSaveReqDTO;\r\nimport com.witsoft.erp.module.md.customer.entity.Customer;\r\nimport com.witsoft.erp.module.md.customer.mapper.CustomerMapper;\r\nimport com.witsoft.erp.module.md.customer.service.CustomerService;\r\nimport lombok.RequiredArgsConstructor;\r\nimport org.springframework.jdbc.core.JdbcTemplate;\r\nimport org.springframework.stereotype.Service;\r\nimport org.springframework.transaction.annotation.Transactional;\r\n\r\nimport java.util.List;\r\n\r\n/**\r\n * 客户 Service 实现类\r\n */\r\n@Service\r\n@RequiredArgsConstructor\r\npublic class CustomerServiceImpl extends ServiceImpl<CustomerMapper, Customer> implements CustomerService {\r\n\r\n private final JdbcTemplate jdbcTemplate;\r\n\r\n @Override\r\n public Page<Customer> pageList(Customer customer, int pageNum, int pageSize) {\r\n LambdaQueryWrapper<Customer> wrapper = new LambdaQueryWrapper<Customer>();\r\n \r\n if (customer.getName() != null) {\r\n wrapper.like(Customer::getName, customer.getName());\r\n }\r\n if (customer.getCustomerCode() != null) {\r\n wrapper.like(Customer::getCustomerCode, customer.getCustomerCode());\r\n }\r\n \r\n wrapper.orderByDesc(Customer::getCreateTime);\r\n \r\n return this.page(new Page<>(pageNum, pageSize), wrapper);\r\n }\r\n\r\n @Override\r\n @Transactional(rollbackFor = Exception.class)\r\n public Long saveCustomer(CustomerSaveReqDTO dto) {\r\n Customer customer = new Customer();\r\n \r\n // 如果编码为空，自动生成\r\n if (dto.getCustomerCode() == null || dto.getCustomerCode().trim().isEmpty()) {\r\n // 从序列获取下一个值\r\n Long sequenceValue = jdbcTemplate.queryForObject(\"SELECT nextval('seq_md_customer_code')\", Long.class);\r\n customer.setCustomerCode(CodeGeneratorUtil.generateCustomerCode(sequenceValue));\r\n } else {\r\n customer.setCustomerCode(dto.getCustomerCode());\r\n }\r\n \r\n customer.setName(dto.getName());\r\n this.save(customer);\r\n return customer.getId();\r\n }\r\n\r\n @Override\r\n @Transactional(rollbackFor = Exception.class)\r\n public void updateCustomer(CustomerSaveReqDTO dto) {\r\n Customer customer = new Customer();\r\n customer.setId(dto.getId());\r\n customer.setCustomerCode(dto.getCustomerCode());\r\n customer.setName(dto.getName());\r\n this.updateById(customer);\r\n }\r\n\r\n @Override\r\n public List<Customer> searchByNameLike(String keyword) {\r\n if (keyword == null || keyword.trim().isEmpty()) {\r\n return List.of();\r\n }\r\n LambdaQueryWrapper<Customer> wrapper = new LambdaQueryWrapper<>();\r\n wrapper.like(Customer::getName, keyword.trim());\r\n wrapper.last(\"LIMIT 10\");\r\n return list(wrapper);\r\n }\r\n\r\n}\r\n"}],"isError":false,"timestamp":1780018688178}}
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{"type":"message","id":"adab0f98","parentId":"db85b959","timestamp":"2026-05-29T01:38:42.576Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Let me analyze the current problem and the requested changes:\n\n1. **返回前端id 无法填充页面** — 前端收到的是 `materialId` 等 ID 字段，但需要名称、规格等显示字段来填充页面表单\n2. **客户供应商需要查询名称** — 当前 `Counterparty` 只返回了 `id` + `name`，但 `name` 是数据库中存储的，前端可能需要显示 AI 识别名 vs 实际匹配名。不过从前端角度看，已有 `name`（数据库中的名称）和 `recognizedName`（AI 识别名称），看起来够用？问题是前端要填充客户/供应商 **名称** 到输入框，而不是 ID。看当前 DTO 结构，`Counterparty` 有 `name` 字段（匹配到的数据库名称），前端用这个应该能填充。但需要确认是否真的把 `name` 返回了。\n\n3. **物料使用 MaterialFillService.getMaterialInfoMap 填充** — 已有 `materialInfo` 字段在 `RecognitionItem` 中有 `materialName/materialCode/spec/unit`，但现在这些字段是 inline 的而不是通过 `MaterialInfoDTO`。改动的方向是统一用 `MaterialInfoDTO` 来填充物料信息。\n\n4. **单据类型使用数据字典中类型** — 当前 `toTypeName()` 是硬编码的 map，应该从数据字典（`inbound_type` / `outbound_type`）中查询。\n\n5. **使用 local 库测试** — 配置 local 数据库连接进行测试。\n\n让我看看现有代码的更完整结构，然后做修改。\n\n让我看看整个 `AiRecognitionServiceImpl` 的完整内容：\n\n我看过了。当前流程：\n1. AI 返回 JSON，解析出 `supplier_name` 或 `customer_name` + `items`（含有 `material_name`, `spec`, `quantity`, `price`）\n2. `matchSupplier`/`matchCustomer` 用模糊匹配查到供应商/客户的 ID 和 name\n3. `matchMaterialItem` 用模糊匹配查到物料的 ID，然后用 `materialFillService.getMaterialInfo(best.getId())` 填充\n\n问题分析：\n\n**1. 物料填充现有问题：**\n当前 `RecognitionItem` 字段：`materialId, materialName, materialCode, spec, unit, recognizedName, quantity, price, exactMatch`\n这些都填了。看起来没什么问题？\n\n但是用户说 \"返回前端id无法填充页面\"，可能意味着前端需要的是*完整的物料信息*（含编码、名称、规格、单位），而且这些信息通过 `MaterialInfoDTO` 统一获取比较可靠。当前代码确实用了 `MaterialInfoDTO info = materialFillService.getMaterialInfo(best.getId())` 来填充，应该已经包含了所有需要的信息。\n\n**2. 客户/供应商：**\n当前 `Counterparty` 有 `id`, `name`, `recognizedName`, `exactMatch`。前端需要名称来填充。看起来也是有的。\n\n等等，让我重新看下代码...\n\n`Counterparty`:\n```java\npublic static class Counterparty {\n private Long id;\n private String name; // 数据库中名称\n private String recognizedName; // AI 识别名称\n private boolean exactMatch;\n}\n```\n\n这个结构应该够了。前端用 `name` 填充输入框。\n\n**3. 单据类型使用数据字典：**\n\n当前代码：\n```java\nprivate static final Map<String, Integer> TYPE_MAPPING = Map.of(\n \"purchase_inbound\", 10,\n \"sales_outbound\", 10 // BUG！销售出库应该是不同类型\n);\n\nprivate static final Map<Integer, String> TYPE_NAME_MAPPING = Map.of(\n 10, \"采购入库\",\n 20, \"退货入库\",\n 30, \"其他入库\"\n);\n```\n\n这有两个问题：\n- `sales_outbound` 映射到 10，但它的类型名称硬编码返回 \"采购入库\"？不，`toTypeName(10)` 返回 \"采购入库\"。这显然不对，销售出库应该从 `outbound_type` 字典取值\n- 类型名称应该从数据字典查询，而不是硬编码\n\n数据字典中定义了：\n- `inbound_type`: 10-采购入库, 20-退货入库, 30-其他入库\n- `outbound_type`: 10-销售出库, 20-领料出库, 30-其他出库\n\n所以应该使用 `DictService` 来查询字典标签。\n\n**4. 使用 local 库测试：**\n需要在 `application-local.yml` 或者测试配置中指向本地数据库。\n\n让我看看 `DictService` 的结构：\n\n我记得 MEMORY.md 提到：\n```\n字典优先用 DictService：字典取值优先使用 DictService 公共方法，不手写字典查询逻辑\n```\n\n所以应该注入 `DictService` 而不是在 `AiRecognitionServiceImpl` 里手写字典映射。\n\n让我看看 DictService 接口：\n\n已经看到 `MaterialFillServiceImpl` 直接使用 `DictDataMapper` 来查询 material_type 字典。但用户要求的是用 `DictService`。\n\n让我确认 DictService 有什么方法：","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_e09bfefdaad0450590dd4e5c","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/system/dict/service/DictService.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/system/dict/service/DictService.java\"}"},{"type":"toolCall","id":"call_b03590fa911d4f91bbb74051","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \"DictServiceImpl.java\" | grep -v target","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -type f -name \\\"DictServiceImpl.java\\\" | grep -v target\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":2097,"output":1263,"cacheRead":49664,"cacheWrite":0,"reasoningTokens":1094,"totalTokens":53024,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018688495,"responseId":"chatcmpl-7bd31bb6-1963-4998-b3a9-e356e5d3ce00"}}
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{"type":"message","id":"968216e1","parentId":"adab0f98","timestamp":"2026-05-29T01:38:43.891Z","message":{"role":"toolResult","toolCallId":"call_e09bfefdaad0450590dd4e5c","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.system.dict.service;\n\nimport com.baomidou.mybatisplus.extension.service.IService;\nimport com.witsoft.erp.module.system.dict.entity.DictData;\nimport com.witsoft.erp.module.system.dict.entity.DictType;\n\nimport java.util.List;\nimport java.util.Map;\n\n/**\n * 字典服务接口\n */\npublic interface DictService extends IService<DictType> {\n\n /**\n * 获取字典类型列表\n */\n List<DictType> listTypes(DictType dictType);\n\n /**\n * 获取字典数据列表\n */\n List<DictData> listData(String dictType);\n\n /**\n * 获取多个字典类型的数据（用于前端下拉框批量填充）\n * 例：传入 [\"inbound_type\", \"outbound_type\"] 返回对应的字典数据 Map\n *\n * @param dictTypes 字典类型标识列表\n * @return Map<字典类型，字典数据列表>\n */\n Map<String, List<DictData>> listDataBatch(List<String> dictTypes);\n\n /**\n * 获取字典数据的 label-value 列表（前端下拉框格式）\n *\n * @param dictType 字典类型标识\n * @return List<Map<\"label\", \"value\">>\n */\n List<Map<String, Object>> listOptions(String dictType);\n\n /**\n * 批量获取多个字典类型的 options（前端下拉框格式）\n *\n * @param dictTypes 字典类型标识列表\n * @return Map<字典类型，List<Map<\"label\", \"value\">>>\n */\n Map<String, List<Map<String, Object>>> listOptionsBatch(List<String> dictTypes);\n\n}\n"}],"isError":false,"timestamp":1780018723891}}
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{"type":"message","id":"24dab807","parentId":"3e535f8d","timestamp":"2026-05-29T01:39:47.590Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Let me understand the full picture now. The user wants to improve the AI recognition result DTO so that the frontend can actually use it to populate forms. The key issues are:\n\n1. **返回前端id但无法填充** - The `RecognitionItem` has `materialId` but the frontend needs the full material info populated. The user wants us to use `MaterialFillService.getMaterialInfoMap()` for the material items, and query names for customers/suppliers.\n\n2. **客户供应商需要查询名称** - For the counterparty, we already return `name` from the database when there's a match. Need to ensure we're returning full name info.\n\n3. **物料使用 MaterialFillService.getMaterialInfoMap() 填充** - Already partially done (currently calls `getMaterialInfo()` for single item), but should be batch filled for efficiency.\n\n4. **单据类型使用数据字典中类型** - Currently the code has hardcoded `TYPE_MAPPING` and `TYPE_NAME_MAPPING`. Should use the DictService to look up from the database.\n\n5. **使用local库测试** - Run tests against local database.\n\nLet me re-read the current AiRecognitionResultDTO to see what's missing for frontend fill.\n\nLooking at the current `RecognitionItem`:\n```java\npublic static class RecognitionItem {\n private Long materialId;\n private String materialName;\n private String materialCode;\n private String spec;\n private String unit;\n private String recognizedName;\n private BigDecimal quantity;\n private BigDecimal price;\n private boolean exactMatch;\n}\n```\n\nIt already has materialCode, materialName, spec, unit. The issue might be that the frontend expects these fields in a specific way. Actually, looking at the issue description more carefully:\n\n\"返回前端id但无法填充页面\" - The front end receives IDs but can't fill the form fields. This means the front end expects to receive the full data (name, code, spec, unit) back, not just IDs.\n\nLooking at the code, it already does fill using `MaterialFillService`. So the question is - is there actually a missing piece?\n\nWait, let me re-read. The user says the frontend returns IDs but can't fill the form. So the DTO is already being populated with IDs. But the frontend expects the full data. Let me check if there's an issue with how the data is populated.\n\nActually, looking again at the current code flow:\n1. For materials - it calls `materialFillService.getMaterialInfo(best.getId())` for each item, but this is inefficient since it's one-by-one. It should batch.\n2. The `Counterparty` DTO has `name` field that should be the DB name. It already returns it.\n3. The `typeName` is hardcoded instead of using DictService.\n\nLet me also check if the issue is more about the frontend expecting certain structures. Let me look at the test to understand expected behavior...\n\nThe test expects:\n- `cp.getName()` equals \"老兵水晶店\"\n- Items have materialId, materialName, materialCode, spec, unit, quantity, price\n\nSo the DTO seems to already have the right fields. But the user is saying the frontend can't fill the page with just IDs.\n\nOK, I think the key improvements needed are:\n1. **Batch fill materials** - Currently uses `getMaterialInfo()` one-by-one in the item loop, should batch all items at once\n2. **Use DictService for type name** - Replace hardcoded TYPE_NAME_MAPPING with DictService lookup\n3. **Ensure counterparty returns full name info** - Already does this, but ensure it's consistent\n\nActually wait, I need to re-examine. The user said:\n- \"返回前端id但无法填充页面\" - maybe the current code doesn't return material_name at all when there's no match? No, it does return it.\n- \"客户供应商需要查询名称\" - maybe the counterparty is only returning ID but not the full name?\n\nLet me re-read the Counterparty:\n```java\n@Builder\nprivate Long id;\nprivate String name; // 数据库中名称\nprivate String recognizedName;\nprivate boolean exactMatch;\n```\n\nHmm, the builder pattern here is `CounterpartyBuilder`. When we do `mapper.apply(best).recognizedName().exactMatch().build()`, it should set id and name.\n\nLooking at `matchCounterparty`:\n```java\nreturn mapper.apply(best)\n .recognizedName(recognizedName)\n .exactMatch(true)\n .build();\n```\n\nAnd `matchSupplier`:\n```java\ns -> AiRecognitionResultDTO.Counterparty.builder()\n .id(s.getId()).name(s.getName())\n```\n\nSo it does return the DB name. The issue might be something else.\n\nLet me re-read the actual problem statement again: \"返回前端id但无法填充页面\" - \"returning front-end id but can't fill the page\"\n\nI think this means currently the code returns the ID from recognition, but the frontend needs additional data to populate the form (material name, code, spec, unit for each item). Looking at the current code, it does return those fields...\n\nWait, I need to look more carefully. The `AiRecognitionResultDTO` is returned as the response. Let me think about what the frontend expects:\n\nFor material items, the frontend probably has an autocomplete/selector component that needs:\n- materialId (to identify)\n- materialName (to display)\n- materialCode (for reference)\n- spec (for specification)\n- unit (for unit)\n\nThese already exist in `RecognitionItem`. So what's missing?\n\nActually, I think the user might be talking about a different scenario. Perhaps the previous version of this code (before my analysis) wasn't populating the material info properly, and the user wants me to ensure the improvements are made. Let me re-read the user's message:\n\n\"## 交互优化\n- 返回前端id但无法填充页面\n- 客户供应商需要查询名称\n- 物料使用com.witsoft.erp.module.md.material.service.MaterialFillService.getMaterialInfoMap填充\n- 单据类型使用 数据字典中类型\n- 使用local 库测试\n- [02-物料近似查询方案.md](yangxuan/设计/02-物料近似查询方案.md)\"\n\nOK so the user wants me to actually implement these improvements:\n\n1. Currently, the frontend receives IDs but can't fill forms because they lack the display data. Need to ensure full material/customer/supplier info is returned.\n2. Customer/Supplier should return the name from database when matched.\n3. Use `MaterialFillService.getMaterialInfoMap()` for batch filling of material info.\n4. Use DictService for the bill type (not hardcoded).\n5. Test with local database.\n\nLet me plan the implementation:\n\n### Changes needed:\n\n#### 1. `AiRecognitionResultDTO.java`\n- No structural changes needed, it already has the right fields.\n\n#### 2. `AiRecognitionServiceImpl.java` - Major refactoring:\n\na) **Batch material fill**: Instead of calling `materialFillService.getMaterialInfo()` per item, collect all matched IDs and batch fill.\n\nb) **Use DictService for type name**: Replace hardcoded TYPE_NAME_MAPPING with DictService lookup.\n\nc) **Return counterparty with full name info**: Already done for matched ones, but the \"unknown\" fallback could be improved.\n\nd) **Use searchSimilar from the design doc**: Apply the priority-based matching instead of the current fallback chain.\n\nLet me implement this step by step.\n\nActually, wait. Let me re-think the scope. The user said:\n\n- \"返回前端id但无法填充页面\" - The front end gets IDs but can't fill. This implies the current code does return IDs but doesn't return the associated display data that the frontend needs.\n\nLooking at the current code again for `RecognitionItem`:\n```java\n.materialId(best.getId())\n.materialName(info != null ? info.getMaterialName() : best.getMaterialName())\n.materialCode(info != null ? info.getMaterialCode() : null)\n.spec(info != null ? info.getSpec() : best.getSpec())\n.unit(info != null ? info.getUnit() : best.getUnit())\n```\n\nThis looks correct. Unless the `materialFillService.getMaterialInfo()` returns null, in which case materialCode would be null but materialName and spec would still come from the Material entity.\n\nHmm, maybe the issue is simpler. Let me look at what the frontend expects...\n\nActually I think I'm overthinking this. The user is telling me what needs to be improved, and I should just implement it. Let me code the changes:\n\n1. **Refactor `matchMaterialItem` to batch fill** - Instead of calling `getMaterialInfo` per item, collect all matched material IDs first, batch query, then fill.\n\n2. **Replace hardcoded type mapping with DictService** - Query `inbound_type` dict for the labels.\n\n3. **Refactor the fuzzy matching to use the priority-based approach** from the design doc.\n\n4. **Verify supplier/customer name return**.\n\nLet me start coding.\n\nFirst, let me understand the full current `AiRecognitionServiceImpl.java`:\n\nThe current implementation:\n- `recognize()` - Main entry point\n- Calls `matchSupplier` / `matchCustomer` for counterparty\n- Calls `matchMaterialItem` per item\n\nThe material matching flow:\n1. Normalize name (remove spaces, half-width)\n2. `materialService.searchByNameLike(normalized)` - LIKE search\n3. If no results and spec exists: search `normalized + \" \" + spec` \n4. If still none: tokenize and try each token\n5. If still none: extract Chinese parts\n6. If still none: return unmatched item\n7. If matched: fill with `materialFillService.getMaterialInfo(best.getId())`\n\nThe counterparty matching flow:\n1. Normalize name\n2. `searchByNameLike(normalized)` - LIKE search\n3. If none: tokenize, try longest token\n4. If still none: try combined tokens\n5. If still none: return unmatched\n\nOK, let me now implement the changes. I'll refactor `AiRecognitionServiceImpl.java` to:\n\n1. **Use the priority-based `searchSimilar()` matching** (from design doc) for materials\n2. **Batch fill all matched materials** using `MaterialFillService.getMaterialInfoMap()`\n3. **Use DictService** for type name lookup instead of hardcoded values\n4. **Ensure counterparty returns proper names** (should already work)\n\nI also need to:\n- Add `searchSimilar()` to `MaterialService` and `MaterialServiceImpl`\n- Add `MatchPriority` enum and `MaterialMatchResult` DTO\n\nLet me check what files I need to create/modify:\n\n**New files:**\n1. `MatchPriority.java` - enum\n2. `MaterialMatchResult.java` - DTO\n\n**Modified files:**\n1. `MaterialService.java` - add `searchSimilar()` method\n2. `MaterialServiceImpl.java` - implement `searchSimilar()` with priority-based search\n3. `AiRecognitionServiceImpl.java` - major refactor\n4. `AiRecognitionResultDTO.java` - maybe add matchType to RecognitionItem\n\nActually, let me check if MaterialServiceImpl already uses `LikeEscapeUtil.escapeLike` - yes it does.\n\nLet me think about the `searchSimilar` implementation more carefully.\n\n```java\n@Override\npublic List<MaterialMatchResult> searchSimilar(String keyword) {\n if (!StringUtils.hasText(keyword) || keyword.trim().length() < 2) {\n return Collections.emptyList();\n }\n \n String escaped = escapeLike(keyword.trim());\n List<MaterialMatchResult> results = new ArrayList<>();\n Set<Long> addedIds = new HashSet<>();\n \n // Step 1: 名称精确匹配\n addIfAbsent(results, addedIds, \n wrapper -> wrapper.eq(Material::getMaterialName, keyword.trim()), \n MatchPriority.EXACT_NAME);\n \n // Step 2: 名称前缀匹配\n addIfAbsent(results, addedIds, \n wrapper -> wrapper.apply(\"material_name LIKE {0}\", escaped + \"%\"), \n MatchPriority.PREFIX_NAME);\n \n // Step 3: 名称模糊匹配\n addIfAbsent(results, addedIds, \n wrapper -> wrapper.apply(\"material_name LIKE {0}\", \"%\" + escaped + \"%\"), \n MatchPriority.FUZZY_NAME);\n \n // Step 4: 规格模糊匹配\n addIfAbsent(results, addedIds, \n wrapper -> wrapper.apply(\"spec LIKE {0}\", \"%\" + escaped + \"%\"), \n MatchPriority.FUZZY_SPEC);\n \n // Step 5: 编码模糊匹配\n addIfAbsent(results, addedIds, \n wrapper -> wrapper.apply(\"material_code LIKE {0}\", \"%\" + escaped + \"%\"), \n MatchPriority.FUZZY_CODE);\n \n // Limit total results\n if (results.size() > 50) {\n results = results.subList(0, 50);\n }\n \n // Fill with material info\n List<Long> materialIds = results.stream().map(MaterialMatchResult::getId).toList();\n Map<Long, MaterialInfoDTO> infoMap = materialFillService.getMaterialInfoMap(materialIds);\n for (MaterialMatchResult r : results) {\n r.setMaterialInfo(infoMap.get(r.getId()));\n }\n \n return results;\n}\n\nprivate void addIfAbsent(List<MaterialMatchResult> results, Set<Long> addedIds,\n Consumer<LambdaQueryWrapper<Material>> condition, MatchPriority priority) {\n LambdaQueryWrapper<Material> wrapper = new LambdaQueryWrapper<>();\n condition.accept(wrapper);\n wrapper.eq(Material::getStatus, 0);\n wrapper.orderByDesc(Material::getCreateTime);\n wrapper.last(\"LIMIT 20\");\n \n List<Material> list = baseMapper.selectList(wrapper);\n for (Material m : list) {\n if (addedIds.add(m.getId())) {\n MaterialMatchResult r = new MaterialMatchResult();\n r.setId(m.getId());\n r.setMaterialCode(m.getMaterialCode());\n r.setMaterialName(m.getMaterialName());\n r.setSpec(m.getSpec());\n r.setUnit(m.getUnit());\n r.setMatchType(priority);\n r.setMatchRank(priority.rank);\n results.add(r);\n }\n }\n}\n```\n\nWait, but `MaterialServiceImpl` extends `ServiceImpl<MaterialMapper, Material>`, so it has access to `baseMapper`. For the `searchSimilar` method, I'll use `baseMapper` directly.\n\nActually, there's a concern: `eq(Material::getStatus, 0)` - this assumes status 0 is \"有效\". Let me check the entity - `private Integer status;` with comment `物料状态（0-有效，1-无效）`. Yes, 0 is valid.\n\nNow, I also need to think about the AI recognition service refactoring. The current code has a lot of fallback logic that tries to find materials. Let me simplify it to use `searchSimilar()` instead.\n\nFor `matchMaterialItem()`:\n1. Normalize name\n2. Call `materialService.searchSimilar(normalized)`\n3. If no results and spec exists: call `materialService.searchSimilar(normalized + specNoSpace)`\n4. If still none: use the existing tokenize/fallback searchSimilar\n5. Take the best match\n6. Return RecognitionItem with full info (already filled by searchSimilar's MaterialFillService)\n\nActually, `searchSimilar` already fills with MaterialFillService, so the returned MaterialMatchResult already has the material info. I just need the best match.\n\nLet me now also think about DictService. I need to replace:\n```java\nprivate static final Map<String, Integer> TYPE_MAPPING = ...\nprivate static final Map<Integer, String> TYPE_NAME_MAPPING = ...\n```\n\nWith DictService:\n```java\nprivate final DictService dictService;\n\n// In recognize():\n// 查询 inbound_type 字典\nList<DictData> inboundTypes = dictService.listData(\"inbound_type\");\nMap<String, String> typeNameMap = inboundTypes.stream()\n .collect(Collectors.toMap(DictData::getDictValue, DictData::getDictLabel));\n```\n\nBut wait, the AI recognition currently just returns typeValue and typeName. The typeValue comes from the AI's classification. The `TYPE_MAPPING` is just `{\"purchase_inbound\": 10, \"sales_outbound\": 10}` - which seems wrong (both point to 10?). Let me check...\n\nActually looking at the current code:\n```java\nprivate static final Map<String, Integer> TYPE_MAPPING = Map.of(\n \"purchase_inbound\", 10,\n \"sales_outbound\", 10\n);\n```\n\nBoth map to 10?? Then in `toTypeName`:\n```java\nprivate String toTypeName(Integer typeValue) {\n if (typeValue == null) return null;\n if (typeValue == 10) return \"采购入库\";\n if (typeValue == 20) return \"退货入库\";\n if (typeValue == 30) return \"其他入库\";\n return null;\n}\n```\n\nThis always returns \"采购入库\" regardless of whether it's purchase_inbound or sales_outbound! That's a bug. The AI should differentiate.\n\nOK so the proper fix would be:\n- `purchase_inbound` → inbound_type = 10 → \"采购入库\"\n- `sales_outbound` → outbound_type = 10 → \"销售出库\"\n\nBut the current code seems incomplete. Let me check the AI prompt again:\n\n```\n\"如果是采购入库单/到货单，格式如下...\"\n\"如果是销售出库单，格式如下...\"\n```\n\nAnd the TYPE_MAPPING:\n```java\nMap.of(\"purchase_inbound\", 10, \"sales_outbound\", 10)\n```\n\nBoth point to value 10? That can't be right for the typeValue. Maybe the intent is that both inbound and outbound use value 10 for their first subtype. But then the typeName mapping only returns inbound names...\n\nThis looks like a bug/incomplete implementation. The user wants me to use DictService, so let me fix it properly:\n\nFor purchase_inbound:\n- typeValue = 10 (采购入库)\n- Use dict `inbound_type` to get label\n\nFor sales_outbound:\n- typeValue = 10 (销售出库) \n- Use dict `outbound_type` to get label\n\nBut wait, the DictService approach means I need to know the dict type and lookup the label. Let me simplify:\n\nFor `purchase_inbound`: dict type = `inbound_type`, dict value = `10`\nFor `sales_outbound`: dict type = `outbound_type`, dict value = `10`\n\nActually, I think the better approach is:\n1. Keep the TYPE_MAPPING from AI string → (dictType, dictValue)\n2. Use DictService to look up the label from dictType + dictValue\n\nLet me refactor:\n\n```java\nprivate static final Map<String, BillTypeInfo> TYPE_MAPPING = Map.of(\n \"purchase_inbound\", new BillTypeInfo(\"inbound_type\", \"10\"),\n \"sales_outbound\", new BillTypeInfo(\"outbound_type\", \"10\")\n);\n\n@Value\nprivate static class BillTypeInfo {\n String dictType;\n String dictValue;\n}\n```\n\nThen in the recognize method:\n```java\nBillTypeInfo typeInfo = TYPE_MAPPING.get(type);\nif (typeInfo != null) {\n builder.typeValue(Integer.valueOf(typeInfo.getDictValue()));\n // 从字典查询类型名称\n DictData dictData = dictService.listData(typeInfo.getDictType()).stream()\n .filter(d -> d.getDictValue().equals(typeInfo.getDictValue()))\n .findFirst().orElse(null);\n builder.typeName(dictData != null ? dictData.getDictLabel() : typeInfo.getDictValue());\n}\n```\n\nHmm, but DictService already returns a list, and I'd need to find the matching value. Actually, DictData already has DictType.Data, dictValue, dictLabel fields. Let me check...\n\nLooking at DictServiceImpl:\n```java\nList<DictData> listData(String dictType);\n```\n\nI can just use this.\n\nNow let me think about the full plan and start coding.\n\nLet me also check if DictData has getDictValue, getDictLabel methods.\n\nLet me check the DictData entity:\nActually, I saw earlier that MaterialFillServiceImpl already uses `DictDataMapper` directly. It doesn't use DictService. The DictService is the interface used by controllers.\n\nI think using DictService directly in AiRecognitionServiceImpl is fine since it's a service layer.\n\nLet me plan the files I need to create/modify:\n\n**Create:**\n1. `material/dto/MaterialMatchResult.java`\n2. `material/enums/MatchPriority.java`\n\n**Modify:**\n1. `MaterialService.java` - add `searchSimilar()`\n2. `MaterialServiceImpl.java` - implement `searchSimilar()`\n3. `AiRecognitionResultDTO.java` - add `DictService`, refactor\n4. `AiRecognitionServiceImpl.java` - major refactor\n5. `AiControllerTest.java` - update if needed\n\nActually wait, let me check if the `AiRecognitionServiceImpl.java` needs DictService. Yes it does for type naming.\n\nLet me also think about the package structure. `MatchPriority` and `MaterialMatchResult` - where to put them?\n\n`MatchPriority` is an enum specific to material search. Put it in `com.witsoft.erp.module.md.material.enums`.\n`MaterialMatchResult` is a DTO. Put it in `com.witsoft.erp.module.md.material.dto`.\n\nLet me check if there's an enums package already:\nActually, I'll just create the files and see.\n\nLet me start coding now. I'll do it step by step.\n\nFirst, let me check the directory structure:\n- `com.witsoft.erp.module.md.material.enums` - probably doesn't exist yet\n- `com.witsoft.erp.module.md.material.dto` - exists (MaterialInfoDTO, MaterialPageDTO, etc.)\n\nLet me code each file now.\n\nFor the `searchSimilar` method, since `MaterialServiceImpl` extends `ServiceImpl<MaterialMapper, Material>`, I can use `baseMapper` directly. But I need to be careful - the status filter should match existing convention.\n\nActually, looking at the existing code, `searchByNameLike` doesn't filter by status:\n```java\npublic List<Material> searchByNameLike(String keyword) {\n ...\n wrapper.and(w -> w\n .apply(\"material_code LIKE {0}\", \"%\" + escaped + \"%\")\n .or()\n .apply(\"material_name LIKE {0}\", \"%\" + escaped + \"%\")\n .or()\n .apply(\"spec LIKE {0}\", \"%\" + escaped + \"%\")\n );\n wrapper.last(\"LIMIT 20\");\n return list(wrapper);\n}\n```\n\nFor `searchSimilar`, I'll add a status filter for valid materials only (status = 0).\n\nOK let me start implementing. I'll create the files and make the modifications.\n\nAlso, for the test - the user wants to use the local library for testing. I need to check if the test has `@SpringBootTest` which should use the application context. As long as the test runs against the local database config, it should work.\n\nLet me check the application-local config to ensure test will connect to local:\nActually I shouldn't touch config files. The test uses `@SpringBootTest` which loads the application context. As long as the active profile is set correctly, it should use local.\n\nLet me just code it now.\n\nLet me also re-examine: The user said \"使用local 库测试\". Maybe they mean I should run the test to verify? But I can't really run tests without a database connection. Let me focus on the code changes and tell the user to test.\n\nActually, let me check - can I run tests?\n\nLet me first set up the plan, then code everything.\n\nPlan:\n1. Create `MatchPriority` enum\n2. Create `MaterialMatchResult` DTO\n3. Add `searchSimilar` to `MaterialService` + `MaterialServiceImpl`\n4. Refactor `AiRecognitionServiceImpl.java`:\n a. Inject DictService\n b. Use DictService for type name lookup\n c. Use searchSimilar for material matching\n d. Batch fill materials using MaterialFillService.getMaterialInfoMap()\n5. Verify/update test\n\nLet me start.","thinkingSignature":"reasoning_content"},{"type":"text","text":"让我把整个方案梳理清楚。先看看需要改哪些文件和目录结构。\n\n"},{"type":"toolCall","id":"call_aa67b58da6734d198bfda712","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -path \"*/md/material/*\" -type d | sort","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -path \\\"*/md/material/*\\\" -type d | sort\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"},{"type":"toolCall","id":"call_ad88d71fabd7451fb957f727","name":"exec","arguments":{"command":"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -path \"*/enums/*\" -type f | head -10","workdir":"/home/yangxuan/Projects/IdeaProjects/tiny-erp"},"partialArgs":"{\"command\": \"find /home/yangxuan/Projects/IdeaProjects/tiny-erp/src -path \\\"*/enums/*\\\" -type f | head -10\", \"workdir\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":640,"output":5483,"cacheRead":51712,"cacheWrite":0,"reasoningTokens":5273,"totalTokens":57835,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018724048,"responseId":"chatcmpl-bfb6b4f6-9b6d-49c5-983b-312e2814e762"}}
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{"type":"message","id":"6badc248","parentId":"9bc9ddad","timestamp":"2026-05-29T01:40:19.720Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"The user wants me to:\n\n1. Return supplier/customer names alongside their IDs (for front-end form filling)\n2. Use `MaterialFillService.getMaterialInfoMap()` to fill material info (name, code, spec, unit)\n3. Use data dictionary for the bill type (inbound_type/outbound_type)\n4. Use local database for testing (`test_png.png` which is a test image for AI recognition)\n\nLet me look at the current AiRecognitionServiceImpl in more detail to understand exactly what needs to change.\n\nThe current `AiRecognitionResultDTO` structure:\n- `Counterparty` already has `id`, `name`, `recognizedName`, `exactMatch` ✓\n- `RecognitionItem` already has `materialId`, `materialName`, `materialCode`, `spec`, `unit` ✓\n- Bill type - currently hardcoded to typeValue=10 for both purchase_inbound and sales_outbound, using simple map. Should use DictService instead.\n\nWait, the user says:\n- \"返回前端id无法填充页面\" - returning just id doesn't let the front-end fill the form. They need names too.\n- \"客户供应商需要查询名称\" - customer/supplier need name queries (already done)\n- \"物料使用MaterialFillService.getMaterialInfoMap填充\" - already using it per-item, but not using the batch method\n- \"单据类型使用数据字典中类型\" - use dict system\n- \"使用local库测试\" - use local database for testing\n\nLet me re-read the AiRecognitionServiceImpl:\n\n1. **Type mapping**: Currently hardcoded in `TYPE_MAPPING` and `TYPE_NAME_MAPPING`. The `toTypeName` method doesn't even properly map `sales_outbound`. Should use DictService `listData(\"inbound_type\")` or `listData(\"outbound_type\")`.\n\n2. **Match material**: Currently finds best match then calls `materialFillService.getMaterialInfo(best.getId())` individually. Could use batch but it's fine.\n\n3. **Match counterparty**: Returns `name` already from the database match result. But when no match, it returns `name=recognizedName` without id. That's correct.\n\nSo the main issues to fix:\n1. **Type mapping**: Use DictService instead of hardcoded mapping\n2. **Material matching**: Improve to use `searchSimilar()` approach from the design doc\n3. **Testing**: Make tests work with local DB (test_png.png)\n\nLet me look at the type mapping more carefully. The current code:\n```java\nprivate static final Map<String, Integer> TYPE_MAPPING = Map.of(\n \"purchase_inbound\", 10,\n \"sales_outbound\", 10\n);\n```\n\nThis maps both to 10, which is wrong. `purchase_inbound` should map to inbound_type=10 (采购入库), and `sales_outbound` should map to outbound_type=10 (销售出库). But the DTO only has `typeValue` without distinguishing whether it's inbound_type or outbound_type.\n\nLooking at the DTO and controller, `typeValue` and `typeName` are returned. But 10 could be both inbound_type and outbound_type. I think we need a `billType` field or similar to differentiate.\n\nActually wait, looking at the test, it checks `data.getTypeValue()` without checking what dict type it is. But this seems wrong. Let me look more carefully...\n\nActually, the problem is more nuanced. When the front-end gets typeValue=10, it doesn't know whether that's an inbound or outbound type. We need a way to distinguish.\n\nBut the user said to use DictService. Let me check what dict data is available.\n\nFrom 99-data.sql:\n- `inbound_type`: 10-采购入库, 20-退货入库, 30-其他入库\n- `outbound_type`: 10-销售出库, 20-领料出库, 30-其他出库\n\nSo we need to return both the dict type and the value. The current DTO has `typeValue` and `typeName`. I think we should add a `dictType` or `billType` field.\n\nLet me now also look at what the MaterialSelectorReqDTO / matchMaterialItem does more carefully. Actually, I think the main thing the user wants is this interaction optimization:\n\nCurrent problem: After AI recognition, the result is returned to the frontend with IDs, but the front-end can't use just IDs to populate the form fields because the form needs names, codes, specs, etc.\n\nLet me trace through the current flow:\n1. AI recognizes the image, gets text\n2. Text is parsed into material names, specs, quantities, prices\n3. For each material name, fuzzy match against the database\n4. Return `materialId`, `materialName`, `materialCode`, `spec`, `unit`, `quantity`, `price`\n\nThe `materialName` and `spec` returned are from the database (via MaterialInfoDTO), so they're already correct for populating the front-end form. So what's the issue?\n\nWait, let me re-read more carefully. The user said:\n- \"返回前端id无法填充页面\" - returning just IDs can't fill the page\n\nMaybe the issue is in another part of the system? Not specifically in AI recognition? Or maybe the issue is that the current implementation doesn't properly use MaterialFillService's batch method (getMaterialInfoMap) but instead calls getMaterialInfo one-by-one per item.\n\nActually, looking at the AiRecognitionServiceImpl.matchMaterialItem more carefully, it does:\n```java\nMaterialInfoDTO info = materialFillService.getMaterialInfo(best.getId());\n```\n\nThis calls the single-item version. For multiple items, this results in N+1 queries. We should batch all matched materials together. But that's a performance optimization, not a correctness issue.\n\nLet me re-read user's requirements again:\n1. ✅ Customer/supplier names are already returned as `name` field \n2. ❓ MaterialFillService - currently using per-item call, should use batch\n3. ❓ Bill type using dict - currently hardcoded\n4. ✅ Local DB test\n\nHmm, maybe the user wants me to:\n1. Refactor the AI recognition to properly use DictService for type transitions\n2. Use MaterialFillService batch approach\n3. Make the test work against local DB\n\nLet me also look at what the MaterialSelectorReqDTO interaction is. The user mentioned returning id not filling the page. Maybe the problem is in a different flow, like the material selector dialog - the user selects from available materials but it doesn't populate the form properly.\n\nActually wait - I need to re-read the user's message more carefully. They said:\n\n### 交互优化\n- 返回前端id无法填充页面\n- 客户供应商需要查询名称\n- 物料使用MaterialFillService.getMaterialInfoMap填充\n- 单据类型使用数据字典中类型\n- 使用local库测试\n- [02-物料近似查询方案.md](yangxuan/设计/02-物料近似查询方案.md)\n\nThese are **requirements**. They want me to:\n1. The current implementation returns IDs, but the front-end needs names to fill the page\n2. Customer/supplier need name lookups\n3. Material uses MaterialFillService.getMaterialInfoMap for filling\n4. Bill type uses data dictionary\n5. Test against local DB\n\nWait, I think there might be an issue with the CurrentCounterparty matching - when it returns `recognizedName` as the name but without a proper id, the front-end might not be able to fill the form. Let me re-check...\n\nActually looking at the matchCounterparty method:\n- `name` = database name when matched, `recognizedName` = AI recognized name, `id` = database id\n- When no match: `name` = recognizedName, `id` = null\n\nSo the front-end gets the supplier/customer name. That seems fine.\n\nBut the user says \"返回前端id无法填充页面\" - returning just IDs can't fill the page. Maybe the issue is that some parts of the system return just IDs without names.\n\nHmm, I think I might be overthinking this. Let me just look at the current state and fix the obvious issues:\n\n1. **Bill type**: Replace hardcoded type mapping with DictService\n2. **Material matching**: Use batch MaterialFillService where possible\n3. **Test**: Make it work against local DB\n\nActually, I realize I should look at the test carefully. The test file `AiControllerTest.java` uses `test_png.png` from classpath. Let me check if that file exists.\n\nActually, let me look at what the AiRecognitionServiceImpl does wrong vs what the front-end expects. Let me just look at the full service first since I only read part of it.\n\nLet me read the full AiRecognitionServiceImpl to understand the complete flow.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_641e69f491cc4343890a720e","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":551,"output":1963,"cacheRead":52224,"cacheWrite":0,"reasoningTokens":1882,"totalTokens":54738,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018788674,"responseId":"chatcmpl-1b6dc390-f281-45ae-af01-6197c823d049"}}
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{"type":"message","id":"956f2d62","parentId":"6badc248","timestamp":"2026-05-29T01:40:20.207Z","message":{"role":"toolResult","toolCallId":"call_641e69f491cc4343890a720e","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.ai.service.impl;\n\nimport com.witsoft.erp.common.core.BusinessException;\nimport com.witsoft.erp.module.ai.dto.*;\nimport com.witsoft.erp.module.ai.service.AiRecognitionService;\nimport com.witsoft.erp.module.ai.service.AiService;\nimport com.witsoft.erp.module.md.customer.entity.Customer;\nimport com.witsoft.erp.module.md.customer.service.CustomerService;\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\nimport com.witsoft.erp.module.md.material.entity.Material;\nimport com.witsoft.erp.module.md.material.service.MaterialFillService;\nimport com.witsoft.erp.module.md.material.service.MaterialService;\nimport com.witsoft.erp.module.md.supplier.entity.Supplier;\nimport com.witsoft.erp.module.md.supplier.service.SupplierService;\nimport lombok.RequiredArgsConstructor;\nimport lombok.extern.slf4j.Slf4j;\nimport org.springframework.stereotype.Service;\nimport org.springframework.web.multipart.MultipartFile;\n\nimport java.math.BigDecimal;\nimport java.util.*;\nimport java.util.stream.Collectors;\n\n/**\n * AI 单据识别服务实现\n *\n * 流程：\n * 1. 调用 AI 识别单据图片\n * 2. 解析 AI 返回的 JSON\n * 3. 单据类型：purchase_inbound → typeValue=10, typeName=采购入库\n * 4. 模糊匹配供应商/客户（去空格 + 分词片段 + 降级匹配）\n * 5. 模糊匹配物料（去空格 + 分词 + MaterialFillService 填充）\n * 6. 返回前端可用的 id + name\n */\n@Slf4j\n@Service\n@RequiredArgsConstructor\npublic class AiRecognitionServiceImpl implements AiRecognitionService {\n\n private final AiService aiService;\n private final SupplierService supplierService;\n private final CustomerService customerService;\n private final MaterialService materialService;\n private final MaterialFillService materialFillService;\n\n private static final String RECOGNITION_PROMPT =\n \"请识别图片中的单据内容，严格按照 JSON 格式返回，不要包含 Markdown 代码块标记，不要有其他文字。\\n\" +\n \"\\n\" +\n \"如果是采购入库单/到货单，格式如下：\\n\" +\n \"{\\n\" +\n \" \\\"type\\\": \\\"purchase_inbound\\\",\\n\" +\n \" \\\"supplier_name\\\": \\\"供应商名称\\\",\\n\" +\n \" \\\"warehouse_name\\\": \\\"仓库名称（可选）\\\",\\n\" +\n \" \\\"date\\\": \\\"日期\\\",\\n\" +\n \" \\\"total_amount\\\": 总金额,\\n\" +\n \" \\\"remark\\\": \\\"备注\\\",\\n\" +\n \" \\\"items\\\": [\\n\" +\n \" {\\n\" +\n \" \\\"material_name\\\": \\\"物料名称\\\",\\n\" +\n \" \\\"spec\\\": \\\"规格（可选）\\\",\\n\" +\n \" \\\"quantity\\\": 数量,\\n\" +\n \" \\\"unit\\\": \\\"单位（可选）\\\",\\n\" +\n \" \\\"price\\\": 单价\\n\" +\n \" }\\n\" +\n \" ]\\n\" +\n \"}\\n\" +\n \"\\n\" +\n \"如果是销售出库单，格式如下：\\n\" +\n \"{\\n\" +\n \" \\\"type\\\": \\\"sales_outbound\\\",\\n\" +\n \" \\\"customer_name\\\": \\\"客户名称\\\",\\n\" +\n \" \\\"warehouse_name\\\": \\\"仓库名称（可选）\\\",\\n\" +\n \" \\\"date\\\": \\\"日期\\\",\\n\" +\n \" \\\"total_amount\\\": 总金额,\\n\" +\n \" \\\"remark\\\": \\\"备注\\\",\\n\" +\n \" \\\"items\\\": [\\n\" +\n \" {\\n\" +\n \" \\\"material_name\\\": \\\"物料名称\\\",\\n\" +\n \" \\\"spec\\\": \\\"规格（可选）\\\",\\n\" +\n \" \\\"quantity\\\": 数量,\\n\" +\n \" \\\"unit\\\": \\\"单位（可选）\\\",\\n\" +\n \" \\\"price\\\": 单价\\n\" +\n \" }\\n\" +\n \" ]\\n\" +\n \"}\";\n\n @Override\n public AiRecognitionResultDTO recognize(MultipartFile file) {\n // 1. 调用 AI 识别图片\n AiChatResponseDTO aiResponse = aiService.chatWithImages(RECOGNITION_PROMPT, Collections.singletonList(file));\n String rawReply = aiResponse.getReply();\n log.info(\"AI 识别原始回复：{}\", rawReply);\n\n // 2. 提取 JSON\n String json = extractJson(rawReply);\n if (json == null) {\n throw new BusinessException(500, \"AI 回复格式异常，无法解析为 JSON\");\n }\n\n // 3. 解析 JSON\n Map<String, Object> parsed = parseSimpleJson(json);\n String type = (String) parsed.get(\"type\");\n if (type == null) {\n throw new BusinessException(400, \"AI 未能识别单据类型\");\n }\n\n // 4. 转换单据类型 → 字典值\n Integer typeValue = toTypeValue(type);\n String typeName = toTypeName(typeValue);\n\n // 5. 构建返回结果\n AiRecognitionResultDTO.AiRecognitionResultDTOBuilder builder = AiRecognitionResultDTO.builder()\n .typeValue(typeValue)\n .typeName(typeName)\n .warehouseName((String) parsed.get(\"warehouse_name\"))\n .remark((String) parsed.get(\"remark\"));\n\n // 6. 模糊匹配供应商或客户（去空格 + 分词片段匹配）\n if (\"purchase_inbound\".equals(type)) {\n String supplierName = (String) parsed.get(\"supplier_name\");\n if (supplierName != null) {\n builder.counterparty(matchSupplier(supplierName));\n }\n } else if (\"sales_outbound\".equals(type)) {\n String customerName = (String) parsed.get(\"customer_name\");\n if (customerName != null) {\n builder.counterparty(matchCustomer(customerName));\n }\n }\n\n // 7. 模糊匹配物料明细（去空格 + 分词 + MaterialFillService 填充）\n @SuppressWarnings(\"unchecked\")\n List<Map<String, Object>> rawItems = (List<Map<String, Object>>) parsed.get(\"items\");\n if (rawItems != null && !rawItems.isEmpty()) {\n List<AiRecognitionResultDTO.RecognitionItem> items = rawItems.stream()\n .map(this::matchMaterialItem)\n .filter(Objects::nonNull)\n .collect(Collectors.toList());\n builder.items(items);\n }\n\n return builder.build();\n }\n\n // ========== 单据类型转换 ==========\n\n private static final Map<String, Integer> TYPE_MAPPING = Map.of(\n \"purchase_inbound\", 10,\n \"sales_outbound\", 10\n );\n\n private static final Map<Integer, String> TYPE_NAME_MAPPING = Map.of(\n 10, \"采购入库\",\n 20, \"退货入库\",\n 30, \"其他入库\"\n );\n\n private Integer toTypeValue(String type) {\n return TYPE_MAPPING.getOrDefault(type, 10);\n }\n\n private String toTypeName(Integer typeValue) {\n if (typeValue == null) return null;\n // 入库类型\n if (typeValue == 10) return \"采购入库\";\n if (typeValue == 20) return \"退货入库\";\n if (typeValue == 30) return \"其他入库\";\n return null;\n }\n\n // ========== 模糊匹配供应商/客户（去空格 + 分词） ==========\n\n private AiRecognitionResultDTO.Counterparty matchSupplier(String recognizedName) {\n return matchCounterparty(recognizedName,\n keyword -> supplierService.searchByNameLike(keyword),\n s -> AiRecognitionResultDTO.Counterparty.builder()\n .id(s.getId()).name(s.getName()));\n }\n\n private AiRecognitionResultDTO.Counterparty matchCustomer(String recognizedName) {\n return matchCounterparty(recognizedName,\n keyword -> customerService.searchByNameLike(keyword),\n c -> AiRecognitionResultDTO.Counterparty.builder()\n .id(c.getId()).name(c.getName()));\n }\n\n /**\n * 通用模糊匹配：\n * 1. 直接 LIKE 搜索（AI 识别的名称与原版去空格后 LIKE）\n * 2. 如果无结果，分词后每个片段单独 LIKE\n * 3. 如果仍无结果，返回原始名称（exactMatch=false）\n */\n private <T> AiRecognitionResultDTO.Counterparty matchCounterparty(\n String recognizedName,\n FuzzySearch<T> searcher,\n java.util.function.Function<T, AiRecognitionResultDTO.Counterparty.CounterpartyBuilder> mapper) {\n\n // 归一化：去空格\n String normalized = normalizeName(recognizedName);\n log.debug(\"供应商/客户模糊匹配：原始='{}', 归一='{}'\", recognizedName, normalized);\n\n // 1. 直接 LIKE 搜索（使用归一化后的名称）\n List<T> candidates = searcher.search(normalized);\n if (!candidates.isEmpty()) {\n T best = candidates.get(0);\n return mapper.apply(best)\n .recognizedName(recognizedName)\n .exactMatch(true)\n .build();\n }\n\n // 2. 分词后每个片段单独搜索\n List<String> tokens = tokenize(normalized);\n if (tokens.size() >= 2) {\n // 用最长分段词搜索\n String longestToken = tokens.stream()\n .max(Comparator.comparingInt(String::length))\n .orElse(\"\");\n if (longestToken.length() >= 2) {\n candidates = searcher.search(longestToken);\n if (!candidates.isEmpty()) {\n T best = candidates.get(0);\n return mapper.apply(best)\n .recognizedName(recognizedName)\n .exactMatch(false)\n .build();\n }\n }\n\n // 两个词组合搜索\n for (int i = 0; i < tokens.size() && candidates.isEmpty(); i++) {\n for (int j = i + 1; j < tokens.size(); j++) {\n String combined = tokens.get(i) + tokens.get(j).replace(tokens.get(i), \"\");\n if (combined.length() >= 2) {\n candidates = searcher.search(combined);\n if (!candidates.isEmpty()) break;\n }\n }\n }\n if (!candidates.isEmpty()) {\n T best = candidates.get(0);\n return mapper.apply(best)\n .recognizedName(recognizedName)\n .exactMatch(false)\n .build();\n }\n }\n\n // 3. 完全无法匹配，返回识别到的原始名称\n return AiRecognitionResultDTO.Counterparty.builder()\n .name(recognizedName)\n .recognizedName(recognizedName)\n .exactMatch(false)\n .build();\n }\n\n @FunctionalInterface\n private interface FuzzySearch<T> {\n List<T> search(String keyword);\n }\n\n // ========== 模糊匹配物料（去空格 + 分词 + MaterialFillService 填充） ==========\n\n private AiRecognitionResultDTO.RecognitionItem matchMaterialItem(Map<String, Object> raw) {\n String materialName = (String) raw.get(\"material_name\");\n String spec = (String) raw.get(\"spec\");\n Object qtyObj = raw.get(\"quantity\");\n Object priceObj = raw.get(\"price\");\n String unit = (String) raw.get(\"unit\");\n\n if (materialName == null || materialName.trim().isEmpty()) {\n return null;\n }\n\n BigDecimal quantity = toBigDecimal(qtyObj);\n BigDecimal price = toBigDecimal(priceObj);\n\n // 模糊匹配物料（多重降级）\n String normalized = normalizeName(materialName);\n\n List<Material> candidates = materialService.searchByNameLike(normalized);\n\n // 如果 combined 无结果，尝试只搜物料名称（去空格后）\n if (candidates.isEmpty() && spec != null) {\n candidates = materialService.searchByNameLike(normalized + \" \" + spec.replaceAll(\"\\\\s+\", \"\"));\n }\n\n // 如果仍无结果，分词匹配（按非字母数字分割）\n if (candidates.isEmpty()) {\n List<String> tokens = tokenize(normalized);\n // 依次用最长片段搜索\n tokens.sort((a, b) -> Integer.compare(b.length(), a.length()));\n for (String token : tokens) {\n if (token.length() >= 2) {\n candidates = materialService.searchByNameLike(token);\n if (!candidates.isEmpty()) break;\n }\n }\n }\n\n // 如果仍无结果，尝试数字+汉字分离匹配（如\"8.5玻璃棒\"→搜\"玻璃棒\"）\n if (candidates.isEmpty()) {\n String[] parts = normalized.split(\"(?<=\\\\d)(?=\\\\D)|(?<=\\\\D)(?=\\\\d)\");\n // 用最长的汉字片段搜索\n List<String> chineseParts = new ArrayList<>();\n for (String part : parts) {\n if (part.codePoints().anyMatch(cp -> Character.isIdeographic(cp))) {\n chineseParts.add(part);\n }\n }\n chineseParts.sort((a, b) -> Integer.compare(b.length(), a.length()));\n for (String cp : chineseParts) {\n if (cp.length() >= 2) {\n candidates = materialService.searchByNameLike(cp);\n if (!candidates.isEmpty()) break;\n }\n }\n }\n\n if (candidates.isEmpty()) {\n // 完全无法匹配：返回 AI 识别的原始信息\n return AiRecognitionResultDTO.RecognitionItem.builder()\n .materialName(materialName)\n .spec(spec)\n .recognizedName(materialName)\n .quantity(quantity)\n\n⚠️ [... middle content omitted — showing head and tail ...]\n\n }\n return null;\n }\n\n @SuppressWarnings(\"unchecked\")\n private Map<String, Object> parseSimpleJson(String json) {\n Map<String, Object> result = new LinkedHashMap<>();\n json = json.trim();\n if (json.startsWith(\"{\") && json.endsWith(\"}\")) {\n json = json.substring(1, json.length() - 1).trim();\n }\n List<String> segments = splitTopLevel(json);\n for (String seg : segments) {\n int colonIdx = seg.indexOf(':');\n if (colonIdx < 0) continue;\n String key = seg.substring(0, colonIdx).trim();\n String value = seg.substring(colonIdx + 1).trim();\n key = unquote(key);\n if (value.startsWith(\"\\\"\")) {\n result.put(key, unquote(value));\n } else if (value.startsWith(\"[\")) {\n result.put(key, parseArray(value));\n } else if (value.startsWith(\"{\")) {\n result.put(key, parseSimpleJson(value));\n } else if (value.equals(\"null\")) {\n result.put(key, null);\n } else {\n try {\n if (value.contains(\".\")) {\n result.put(key, new BigDecimal(value));\n } else {\n result.put(key, Long.parseLong(value));\n }\n } catch (NumberFormatException e) {\n result.put(key, value);\n }\n }\n }\n return result;\n }\n\n private List<Map<String, Object>> parseArray(String arrayStr) {\n List<Map<String, Object>> list = new ArrayList<>();\n arrayStr = arrayStr.trim();\n if (arrayStr.startsWith(\"[\") && arrayStr.endsWith(\"]\")) {\n arrayStr = arrayStr.substring(1, arrayStr.length() - 1).trim();\n }\n int braceDepth = 0;\n int start = 0;\n for (int i = 0; i < arrayStr.length(); i++) {\n char c = arrayStr.charAt(i);\n if (c == '{') braceDepth++;\n else if (c == '}') braceDepth--;\n else if (c == ',' && braceDepth == 0) {\n String item = arrayStr.substring(start, i).trim();\n if (!item.isEmpty()) list.add(parseSimpleJson(item));\n start = i + 1;\n }\n }\n String last = arrayStr.substring(start).trim();\n if (!last.isEmpty()) list.add(parseSimpleJson(last));\n return list;\n }\n\n private List<String> splitTopLevel(String s) {\n List<String> parts = new ArrayList<>();\n int depth = 0, bracketDepth = 0;\n boolean inString = false;\n int start = 0;\n for (int i = 0; i < s.length(); i++) {\n char c = s.charAt(i);\n if (c == '\"' && (i == 0 || s.charAt(i - 1) != '\\\\')) inString = !inString;\n else if (!inString) {\n if (c == '{') depth++;\n else if (c == '}') depth--;\n else if (c == '[') bracketDepth++;\n else if (c == ']') bracketDepth--;\n else if (c == ',' && depth == 0 && bracketDepth == 0) {\n parts.add(s.substring(start, i));\n start = i + 1;\n }\n }\n }\n String last = s.substring(start).trim();\n if (!last.isEmpty()) parts.add(last);\n return parts;\n }\n\n private String unquote(String s) {\n s = s.trim();\n if (s.startsWith(\"\\\"\") && s.endsWith(\"\\\"\")) {\n return s.substring(1, s.length() - 1);\n }\n return s;\n }\n\n private BigDecimal toBigDecimal(Object obj) {\n if (obj == null) return null;\n if (obj instanceof BigDecimal) return (BigDecimal) obj;\n if (obj instanceof Number) return BigDecimal.valueOf(((Number) obj).doubleValue());\n if (obj instanceof String) {\n try { return new BigDecimal((String) obj); }\n catch (NumberFormatException e) { return null; }\n }\n return null;\n }\n}[... 2662 more characters truncated]"}],"isError":false,"timestamp":1780018820206}}
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{"type":"message","id":"2f38564f","parentId":"956f2d62","timestamp":"2026-05-29T01:40:54.428Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now I have a full picture. Let me analyze what needs to change:\n\n**Current problems in `AiRecognitionServiceImpl.recognize()`:**\n\n1. **单据类型 (typeValue/typeName)**: Currently hardcoded in `TYPE_MAPPING` and `TYPE_NAME_MAPPING`, with `sales_outbound` mapped to `10` too — that's wrong. Needs to use DictService from sys_dict_data.\n\n2. **客户/供应商匹配**: Only returns `id + name`, not sufficient for frontend fill. Same issue — only returns the matching entity's ID and name but may not have enough info for the frontend.\n\n3. **物料匹配**: Uses `MaterialFillService.getMaterialInfo()` which is already correct, but the matching logic is complex multi-level fallback. Should also use the `searchSimilar` approach from the document.\n\n4. **单据类型字典**: Need to distinguish between inbound types (inbound_type: 10-采购入库, 20-退货入库, 30-其他入库) and outbound types (outbound_type: 10-销售出库, 20-领料出库, 30-其他出库).\n\nLet me look at the return DTO again to understand what the frontend needs.\n\nThe DTO already has:\n- typeValue, typeName\n- counterparty (id, name, recognizedName, exactMatch)\n- items (materialId, materialName, materialCode, spec, unit, recognizedName, quantity, price, exactMatch)\n\nThe issues according to the user:\n1. **返回前端id无法填充页面** — Only returning ID is not enough, need name/display info\n2. **客户供应商需要查询名称** — Already has name, but needs full info from DB\n3. **物料使用MaterialFillService填充** — Already done, but match logic can be improved\n4. **单据类型使用数据字典中类型** — Use DictService instead of hardcoded Map\n5. **使用local库测试** — Test with local database\n\nLet me understand the actual problem:\n- Frontend receives an ID but cannot fill the form because it needs the name. Actually looking at the DTO, it already returns name (counterparty.name, items.materialName). The issue might be that the frontend component expects a display name or full object, not just an ID. Let me re-read...\n\n\"返回前端id无法填充页面\" — This suggests the frontend gets an ID and tries to use it to look up the name, but the name is not available. Or maybe the frontend expects both ID and name already populated? Looking at the DTO, counterparty has both id and name, items have materialId, materialName, materialCode, spec, unit — that should be enough.\n\nWait, maybe the issue is that the current code actually returns ID-only objects in some cases and the frontend needs the full display info to populate the form. Looking at the code more carefully:\n\nIn `matchCounterparty`, when there's no match, the fallback is:\n```java\nreturn AiRecognitionResultDTO.Counterparty.builder()\n .name(recognizedName)\n .recognizedName(recognizedName)\n .exactMatch(false)\n .build();\n```\nNo ID — that's okay for unmatched. When matched, it returns `id` and `name` from the DB.\n\nIn `matchMaterialItem`, when matched, it uses `MaterialFillService.getMaterialInfo()` which returns `materialCode`, `materialName`, `spec`, `unit`. That should be enough.\n\nSo what's the actual issue? Let me think again...\n\nMaybe the problem is that the current code doesn't return enough info. Let me look at the AiRecognitionResultDTO again:\n\n```java\n@Data\n@Builder\n@NoArgsConstructor\n@AllArgsConstructor\npublic class AiRecognitionResultDTO {\n private Integer typeValue;\n private String typeName;\n private Counterparty counterparty;\n private String warehouseName;\n private String remark;\n private List<RecognitionItem> items;\n \n @Data @Builder ...\n public static class Counterparty {\n private Long id;\n private String name;\n private String recognizedName;\n private boolean exactMatch;\n }\n \n @Data @Builder ...\n public static class RecognitionItem {\n private Long materialId;\n private String materialName;\n private String materialCode;\n private String spec;\n private String unit;\n private String recognizedName;\n private BigDecimal quantity;\n private BigDecimal price;\n private boolean exactMatch;\n }\n}\n```\n\nOK, I think the real issue is:\n1. **单据类型** should use DictService to look up actual dictionary values, not hardcoded maps\n2. **客户/供应商** should return full info (not just id+name), plus the frontend needs to be able to populate fields\n3. **物料** should use MaterialFillService (it already does) but also improve the matching\n\nLet me look at how inbound_type and outbound_type dictionaries are defined:\n- inbound_type: 10-采购入库, 20-退货入库, 30-其他入库 \n- outbound_type: 10-销售出库, 20-领料出库, 30-其他出库\n\nThe current code conflates inbound and outbound types. `sales_outbound` is mapped to typeValue=10 and typeName=\"采购入库\" — that's wrong!\n\nLet me also check if there's a DictService that can do dictionary lookups.\n\nFrom DictService: `listData(String dictType)` returns `List<DictData>`. DictData has `dictValue` and `dictLabel`.\n\nSo the fix should be:\n1. Inject DictService\n2. For inbound: look up `inbound_type` dict, get label for value 10/20/30\n3. For outbound: look up `outbound_type` dict, get label for value 10/20/30\n4. For unmatched: let AI-given type pass through with the raw type string\n\nAnd for counterparty and material, they already look reasonable, but maybe need to improve the match logic.\n\nLet me also check what the test expects — it expects supplier name \"老兵水晶店\" with matched ID. So the test file should be updated accordingly.\n\nNow, the user wants me to **implement the code changes** based on the document. Let me plan:\n\n1. **Inject DictService** into AiRecognitionServiceImpl\n2. **Rework type mapping** to use DictService for `inbound_type` and `outbound_type`\n3. **Improve counterparty matching** to use full name search\n4. **Improve material matching** using the searchSimilar approach from the doc\n5. **Update AiRecognitionResultDTO** if needed\n6. **Run tests** with local database\n\nLet me also look at the AiRecognitionResultDTO to see if it needs changes for the type field to support both inbound and outbound.\n\nActually, looking at the current code again:\n```java\nprivate static final Map<String, Integer> TYPE_MAPPING = Map.of(\n \"purchase_inbound\", 10,\n \"sales_outbound\", 10\n);\n```\n\nBoth map to 10, but for sales_outbound, the typeName is \"采购入库\" which is wrong. It should be \"销售出库\" (which is outbound_type=10).\n\nSo the type system needs to be split:\n- inbound types use `inbound_type` dictionary (10/20/30)\n- outbound types use `outbound_type` dictionary (10/20/30)\n\nBut if we use typeValue=10 for both inbound and outbound, they'd conflict. We need to either:\n- Use different value ranges (e.g., inbound 10/20/30, outbound 110/120/130)\n- Or add a type category field\n\nLooking at the current DTO: `typeValue` and `typeName` — this is fine, but we need to know which dict to look up. Let me add a `typeCategory` field or infer it from the type.\n\nSimpler approach: keep `typeValue` as the raw dict value (10/20/30), and add `typeDictType` to distinguish which dictionary it belongs to (inbound_type / outbound_type). But that changes the DTO.\n\nOr even simpler: just have `typeValue` use different ranges:\n- Inbound: 10, 20, 30 (same as dict values)\n- Outbound: 10, 20, 30 (same as dict values)\n\nAnd distinguish by the `typeName` field which is the dict label. This would mean the frontend relies on typeName rather than typeValue alone.\n\nWait, let me re-look at how the frontend uses this. The frontend uses the recognition result to pre-fill a form. For inbound forms, the type dropdown uses `inbound_type` dict. For outbound, `outbound_type`. So the backend needs to return both the value and which dictionary it belongs to.\n\nI think the cleanest is:\n- Add `typeDictType` field: \"inbound_type\" or \"outbound_type\"\n- Keep `typeValue` as the dict value (10/20/30)\n- Keep `typeName` as the dict label\n\nActually, let me simplify. Let me look at what fields the DTO currently returns:\n\n```java\nprivate Integer typeValue;\nprivate String typeName;\n```\n\nThe frontend knows whether it's creating an inbound or outbound order (it picks the form). So typeValue alone should be enough if it's unambiguous. But with 10 being both \"采购入库\" and \"销售出库\", the frontend can't distinguish.\n\nI'll add `typeDictType` to help the frontend know which dict to use.\n\nLet me now plan the implementation:\n\n### Changes to make:\n\n1. **`AiRecognitionResultDTO.java`** - Add `typeDictType` field\n2. **`AiRecognitionServiceImpl.java`** - Major rewrite:\n - Inject DictService\n - Use DictService for type→dict mapping\n - Improve counterparty matching (use searchByNameLike already)\n - Improve material matching using the document's approach\n3. **`AiControllerTest.java`** - Update test expectations to match new logic\n\nLet me start implementing.\n\nFor the material matching improvement, I need to implement `searchSimilar` on MaterialService first (as per the document), then use it. But the user said \"使用local库测试\" — let me focus on the key changes that address the user's requirements, not implement the full document in one go.\n\nActually, the user said:\n- 返回前端id无法填充页面 — The frontend can't populate using just IDs\n- 客户供应商需要查询名称 — Need to look up customer/supplier names\n- 物料使用MaterialFillService填充 — Already using it, but improve\n- 单据类型使用数据字典中类型 — Use DictService\n- 使用local库测试 — Test locally\n\nLet me implement these changes step by step.\n\nLet me start with the code changes.","thinkingSignature":"reasoning_content"},{"type":"text","text":"现在看清全貌了。我来梳理所有根因并动手改。\n\n**核心问题定位：**\n\n1. **单据类型**：`sales_outbound` 硬编码映射为 `typeValue=10, typeName=\"采购入库\"` — 这是错的，应该查 `outbound_type` 字典得到\"销售出库\"\n2. **客户/供应商**：只返回 id+name，前端组件需要完整显示信息才填充\n3. **物料**：用 `MaterialFillService` 正确，但匹配逻辑需要按优先级排序\n4. **整体**：缺少 `typeDictType` 字段，前端无法区分单据类型归属哪个字典\n\n开工。\n\n"},{"type":"toolCall","id":"call_3989b20412fe44079a019e0c","name":"update_plan","arguments":{"plan":[{"step":"修改 AiRecognitionResultDTO - 增加 typeDictType 字段","status":"in_progress"},{"step":"重写 AiRecognitionServiceImpl - 使用 DictService 解析单据类型 + searchSimilar 物料匹配","status":"pending"},{"step":"更新测试文件 - AiControllerTest 适配新逻辑","status":"pending"},{"step":"运行 local 库测试验证","status":"pending"}]},"partialArgs":"{\"plan\": [{\"step\": \"修改 AiRecognitionResultDTO - 增加 typeDictType 字段\", \"status\": \"in_progress\"}, {\"step\": \"重写 AiRecognitionServiceImpl - 使用 DictService 解析单据类型 + searchSimilar 物料匹配\", \"status\": \"pending\"}, {\"step\": \"更新测试文件 - AiControllerTest 适配新逻辑\", \"status\": \"pending\"}, {\"step\": \"运行 local 库测试验证\", \"status\": \"pending\"}]}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":4799,"output":2618,"cacheRead":52736,"cacheWrite":0,"reasoningTokens":2331,"totalTokens":60153,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018820209,"responseId":"chatcmpl-40138266-2618-491a-a1ae-a67b16dcdb71"}}
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{"type":"message","id":"e31438ad","parentId":"2f38564f","timestamp":"2026-05-29T01:40:54.984Z","message":{"role":"toolResult","toolCallId":"call_3989b20412fe44079a019e0c","toolName":"update_plan","content":[],"details":{"status":"updated","plan":[{"step":"修改 AiRecognitionResultDTO - 增加 typeDictType 字段","status":"in_progress"},{"step":"重写 AiRecognitionServiceImpl - 使用 DictService 解析单据类型 + searchSimilar 物料匹配","status":"pending"},{"step":"更新测试文件 - AiControllerTest 适配新逻辑","status":"pending"},{"step":"运行 local 库测试验证","status":"pending"}]},"isError":false,"timestamp":1780018854983}}
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{"type":"message","id":"b2bb386d","parentId":"e31438ad","timestamp":"2026-05-29T01:40:59.042Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Let me plan the changes carefully:\n\n1. **AiRecognitionResultDTO**: Add `typeDictType` field (\"inbound_type\" or \"outbound_type\") so frontend knows which dict to use.\n\n2. **AiRecognitionServiceImpl**: \n - Fix type mapping: use DictService to look up dict values instead of hardcoded maps\n - `purchase_inbound` → inbound_type=10, `sales_outbound` → outbound_type=10\n - Rewrite material matching to use prioritised search\n \nLet me also check the DictService.listData() method to see how it works.\n\nActually, let me look at what DictServiceImpl does.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_b5a043aa095844d49fec7f71","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/system/dict/service/impl/DictServiceImpl.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/system/dict/service/impl/DictServiceImpl.java\"}"},{"type":"toolCall","id":"call_2e8085f6c3ee422ca0a47ca8","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/system/dict/entity/DictData.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/system/dict/entity/DictData.java\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":493,"output":284,"cacheRead":57344,"cacheWrite":0,"reasoningTokens":140,"totalTokens":58121,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018854991,"responseId":"chatcmpl-ad17dd8d-7851-4b3e-aba9-fdae6c3b2fbd"}}
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{"type":"message","id":"e5b5dbca","parentId":"b2bb386d","timestamp":"2026-05-29T01:41:00.001Z","message":{"role":"toolResult","toolCallId":"call_b5a043aa095844d49fec7f71","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.system.dict.service.impl;\n\nimport com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;\nimport com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;\nimport com.witsoft.erp.module.system.dict.entity.DictData;\nimport com.witsoft.erp.module.system.dict.entity.DictType;\nimport com.witsoft.erp.module.system.dict.mapper.DictDataMapper;\nimport com.witsoft.erp.module.system.dict.mapper.DictTypeMapper;\nimport com.witsoft.erp.module.system.dict.service.DictService;\nimport lombok.RequiredArgsConstructor;\nimport org.springframework.stereotype.Service;\n\nimport java.util.*;\nimport java.util.stream.Collectors;\n\n/**\n * 字典服务实现类\n */\n@Service\n@RequiredArgsConstructor\npublic class DictServiceImpl extends ServiceImpl<DictTypeMapper, DictType> implements DictService {\n\n private final DictDataMapper dictDataMapper;\n\n @Override\n public List<DictType> listTypes(DictType dictType) {\n return this.list(new LambdaQueryWrapper<DictType>()\n .like(dictType.getDictName() != null, DictType::getDictName, dictType.getDictName())\n .eq(dictType.getDictType() != null, DictType::getDictType, dictType.getDictType())\n .eq(dictType.getStatus() != null, DictType::getStatus, dictType.getStatus())\n .orderByAsc(DictType::getSort)\n );\n }\n\n @Override\n public List<DictData> listData(String dictType) {\n return dictDataMapper.selectList(new LambdaQueryWrapper<DictData>()\n .eq(DictData::getDictType, dictType)\n .eq(DictData::getStatus, 0)\n .orderByAsc(DictData::getSort)\n );\n }\n\n @Override\n public Map<String, List<DictData>> listDataBatch(List<String> dictTypes) {\n if (dictTypes == null || dictTypes.isEmpty()) {\n return Collections.emptyMap();\n }\n \n List<DictData> allData = dictDataMapper.selectList(new LambdaQueryWrapper<DictData>()\n .in(DictData::getDictType, dictTypes)\n .eq(DictData::getStatus, 0)\n .orderByAsc(DictData::getSort)\n );\n \n return allData.stream()\n .collect(Collectors.groupingBy(DictData::getDictType));\n }\n\n @Override\n public List<Map<String, Object>> listOptions(String dictType) {\n List<DictData> dataList = listData(dictType);\n return dataList.stream()\n .map(data -> {\n Map<String, Object> option = new LinkedHashMap<>();\n option.put(\"label\", data.getDictLabel());\n option.put(\"value\", data.getDictValue());\n return option;\n })\n .collect(Collectors.toList());\n }\n\n @Override\n public Map<String, List<Map<String, Object>>> listOptionsBatch(List<String> dictTypes) {\n Map<String, List<DictData>> dataMap = listDataBatch(dictTypes);\n Map<String, List<Map<String, Object>>> result = new LinkedHashMap<>();\n \n for (String dictType : dictTypes) {\n List<DictData> dataList = dataMap.getOrDefault(dictType, Collections.emptyList());\n List<Map<String, Object>> options = dataList.stream()\n .map(data -> {\n Map<String, Object> option = new LinkedHashMap<>();\n option.put(\"label\", data.getDictLabel());\n option.put(\"value\", data.getDictValue());\n return option;\n })\n .collect(Collectors.toList());\n result.put(dictType, options);\n }\n \n return result;\n }\n\n}\n"}],"isError":false,"timestamp":1780018860001}}
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{"type":"message","id":"55233a86","parentId":"e5b5dbca","timestamp":"2026-05-29T01:41:00.002Z","message":{"role":"toolResult","toolCallId":"call_2e8085f6c3ee422ca0a47ca8","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.system.dict.entity;\n\nimport com.witsoft.erp.common.entity.BaseEntity;\nimport com.baomidou.mybatisplus.annotation.TableName;\nimport lombok.Data;\nimport lombok.EqualsAndHashCode;\n\n/**\n * 字典数据实体\n */\n@Data\n@EqualsAndHashCode(callSuper = true)\n@TableName(\"sys_dict_data\")\npublic class DictData extends BaseEntity {\n\n private static final long serialVersionUID = 1L;\n\n /**\n * 字典类型标识\n */\n private String dictType;\n\n /**\n * 字典标签\n */\n private String dictLabel;\n\n /**\n * 字典值\n */\n private String dictValue;\n\n /**\n * 排序\n */\n private Integer sort;\n\n /**\n * 状态（0-正常，1-停用）\n */\n private Integer status;\n\n /**\n * 备注\n */\n private String remark;\n\n}\n"}],"isError":false,"timestamp":1780018860002}}
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{"type":"message","id":"a46f6b45","parentId":"55233a86","timestamp":"2026-05-29T01:41:22.705Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now I understand the full picture. Let me analyze the problems one by one:\n\n1. **单据类型硬编码问题**: In `AiRecognitionServiceImpl`, the type mapping is hardcoded:\n - `purchase_inbound` → 10 (\"采购入库\") — but 10 in `inbound_type` is \"采购入库\"\n - `sales_outbound` → 10 (\"采购入库\") — WRONG! This should map to `outbound_type` dict where 10 = \"销售出库\"\n \n The current code doesn't distinguish between `inbound_type` and `outbound_type` dictionaries. Need to:\n - Map to dict type + dict value\n - Return both `typeDictType` (e.g., \"inbound_type\" or \"outbound_type\") and `typeValue` (e.g., \"10\")\n\n2. **客户/供应商**: Currently only returns `id` and `name`. The frontend needs supplier code, contact info, etc. But actually, let me re-read the user's requirement: \"客户供应商需要查询名称\" — this means the counterparty matching needs to also return... wait, it currently returns name. Let me re-read.\n\n \"返回前端id 无法填充页面\" — the frontend gets back an id but can't populate the page. So the issue is that the frontend receives an AI recognition result with just `materialId`, `materialName`, `materialCode`, etc. and needs to populate the form. Currently the backend returns the matched info correctly...\n\n Wait, maybe the issue is that `typeName` is wrong? For `sales_outbound`, it returns \"采购入库\" instead of \"销售出库\". The frontend can't display the correct bill type.\n\n3. **物料填充**: Already uses `MaterialFillService.getMaterialInfo()` — this is correct.\n\n4. **单据类型**: Should use `DictService.listData()` to get the label from the dictionary.\n\nLet me re-read the user's requirements more carefully:\n\n> - 返回前端id 无法填充页面\n> - 客户供应商需要查询名称\n> - 物料使用com.witsoft.erp.module.md.material.service.MaterialFillService.getMaterialInfoMap填充\n> - 单据类型使用 数据字典中类型\n> - 使用local 库测试\n\nOK so the core issues:\n1. Returned `id` doesn't help the frontend fill the page — the frontend needs display names. But currently the code already returns `materialName`, `materialCode`, `spec`, `unit`, `counterparty.name`. So maybe the issue is that when `exactMatch=false`, the frontend can't display useful info? Or when there's no match at all?\n\n2. \"客户供应商需要查询名称\" — the counterparty already returns name. Maybe the issue is the `sales_outbound` type returns wrong type name \"采购入库\", which confuses the frontend?\n\n3. MaterialFillService is already used for material filling.\n\n4. Bill type should use DictService instead of hardcoded maps.\n\nLet me focus on what needs to change:\n\n### Changes needed:\n\n**1. AiRecognitionResultDTO**: \n- Add `typeDictType` field (\"inbound_type\" / \"outbound_type\")\n- Change `typeValue` from Integer to String (since dict values are strings)\n\n**2. AiRecognitionServiceImpl**:\n- Inject `DictService`\n- Use DictService to resolve type name from dict data\n- Fix `sales_outbound` → `outbound_type` dictionary\n\n**3. Maybe add supplier/customer info fields to Counterparty**\n\nLet me look at what the frontend actually needs. The test expects `cp.getName()` to equal \"老兵水晶店\" and `cp.getId()` not null. Currently that works.\n\nBut the issue is with sales_outbound → the current code maps `sales_outbound` to typeValue=10 and typeName=\"采购入库\" which is wrong. It should be typeValue=10 and typeName=\"销售出库\" from the `outbound_type` dict.\n\nLet me now implement the changes:\n\n1. `AiRecognitionResultDTO`: Add `typeDictType` (String), change typeValue to String\n2. `AiRecognitionServiceImpl`: Inject DictService, use it for type name lookup\n3. `AiControllerTest`: Fix test expectations\n\nActually, looking more carefully at the dict values in 99-data.sql:\n- `inbound_type`: \"10\"→\"采购入库\", \"20\"→\"退货入库\", \"30\"→\"其他入库\"\n- `outbound_type`: \"10\"→\"销售出库\", \"20\"→\"领料出库\", \"30\"→\"其他出库\"\n\nCurrent code:\n```java\nprivate static final Map<String, Integer> TYPE_MAPPING = Map.of(\n \"purchase_inbound\", 10,\n \"sales_outbound\", 10\n);\n```\n\nBoth map to 10, but the type name is always \"采购入库\" — wrong for outbound.\n\nNew approach:\n- Map `\"purchase_inbound\"` → `{dictType: \"inbound_type\", value: \"10\"}`\n- Map `\"sales_outbound\"` → `{dictType: \"outbound_type\", value: \"10\"}`\n- Use DictService to look up the label\n\nLet me also consider: should `typeValue` stay as Integer? The dict stores it as String. For the frontend, it's consumed as the dict value. I'll change it to String to match dict storage.\n\nFor Counterparty: \"客户供应商需要查询名称\" — the issue might be that when there's no exact match, the `name` field is set to the recognized name (which might have extra chars). Actually looking at the code, if match fails, it returns `name(recognizedName)` — so the frontend gets the raw AI name. That seems intentional.\n\nWait, maybe the actual issue is that the returned `id` alone can't populate the page—the frontend needs to look up the supplier/customer by id to get the full info. So the Counterparty DTO might need more fields? Let me check the existing fields: id, name, recognizedName, exactMatch. The name is already there. So what's missing?\n\nActually, I think the user is saying: when they get back just `id` for a counterparty that wasn't matched (exactMatch=false), they need the name to populate. But `name` is already there for the non-matched case too.\n\nHmm, let me re-read: \"返回前端id 无法填充页面\" — maybe this is about something else entirely. Maybe the frontend component requires both an identifier (code or id) AND a display name to populate, and currently the code is set up in a way that it can't populate?\n\nActually, I think the original problem is clear now: the `sales_outbound` returns `typeName = \"采购入库\"`, so the frontend shows \"采购入库\" for a sales outbound document. That's the main bug.\n\nLet me just fix the core issues cleanly:\n\n1. Fix type mapping to use DictService properly\n2. Add typeDictType to distinguish inbound/outbound\n3. typeValue as String (dict value)\n\nLet me start coding.\n\nFor the \"供应商名称\" and \"客户名称\" — looking at the prompt passed to AI:\n- purchase_inbound → asks for `supplier_name`\n- sales_outbound → asks for `customer_name`\n\nThe AI returns those. Then the code matches against supplier/customer DB. The issue is just that for sales, the typeName is wrong.\n\nLet me also check: is `typeValue` used as Integer or String in the frontend? The dict stores values as strings. Let me change it to String to be consistent with dict storage.\n\nNow let me also think about the Counterparty issue. The user says \"客户供应商需要查询名称\" — I think this means: when matching a customer/supplier, return the name from the database so the frontend can show it. Currently the code already does this in the match case. In the no-match case, it returns the raw recognized name. This seems fine.\n\nLet me also check the test: the test expects `cp.getName()` to equal \"老兵水晶店\". In the current code, when `searchByNameLike(\"老兵水晶店\")` returns results, the first one is taken and `name` is set to `s.getName()` which is the DB name. So this should work.\n\nOK so the actual bugs to fix:\n\n1. `sales_outbound` type → currently shows \"采购入库\", should show \"销售出库\"\n2. Type mapping should use DictService, not hardcoded Map\n3. `typeValue` should be String to match dict storage\n4. Add `typeDictType` field\n\nLet me code it up now.\n\nFor the DTO, I need to also check what the frontend expects for `typeValue`. It's currently Integer type. The dict stores it as String. I'll change to String. But I need to check if any frontend code depends on it being Integer...\n\nActually, I'll keep it as String since dict values are stored as String in the database. The current Integer \"10\" and \"20\" are accidentially convertible.\n\nWait, the test checks:\n```java\nassertNotNull(data.getTypeValue(), \"应识别单据类型\");\n```\n\nAnd doesn't check the value. So changing to String is safe.\n\nLet me write all the changes now.","thinkingSignature":"reasoning_content"},{"type":"text","text":"OK, 确认清楚问题了。我来逐个分析并修改。\n\n"},{"type":"toolCall","id":"call_ec120d81669542b88990d3fc","name":"read","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/dto/AiRecognitionResultDTO.java"},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/dto/AiRecognitionResultDTO.java\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":1420,"output":2094,"cacheRead":57600,"cacheWrite":0,"reasoningTokens":2001,"totalTokens":61114,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018860004,"responseId":"chatcmpl-2989564a-2a0b-478e-a706-475ee1d8f614"}}
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{"type":"message","id":"9c5939fc","parentId":"a46f6b45","timestamp":"2026-05-29T01:41:23.245Z","message":{"role":"toolResult","toolCallId":"call_ec120d81669542b88990d3fc","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.ai.dto;\n\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\nimport lombok.AllArgsConstructor;\nimport lombok.Builder;\nimport lombok.Data;\nimport lombok.NoArgsConstructor;\n\nimport java.math.BigDecimal;\nimport java.util.List;\n\n/**\n * AI 识别单据返回 DTO\n * 供前端自动填充表单\n *\n * typeValue/typeName 使用数据字典格式（10-采购入库 / 10-销售出库）\n * counterparty 返回 name（供前端填充输入框）\n * items 使用 MaterialInfoDTO 风格字段（materialCode/spec/unit）\n */\n@Data\n@Builder\n@NoArgsConstructor\n@AllArgsConstructor\npublic class AiRecognitionResultDTO {\n\n /** 单据类型字典值（10-采购入库，20-退货入库 / 10-销售出库，20-领料出库） */\n private Integer typeValue;\n\n /** 单据类型名称（采购入库 / 销售出库） */\n private String typeName;\n\n /** 供应商/客户（含 id + name） */\n private Counterparty counterparty;\n\n /** 仓库名称（可选） */\n private String warehouseName;\n\n /** 备注 */\n private String remark;\n\n /** 物料明细 */\n private List<RecognitionItem> items;\n\n @Data\n @Builder\n @NoArgsConstructor\n @AllArgsConstructor\n public static class Counterparty {\n /** 匹配到的 ID */\n private Long id;\n /** 匹配到的名称（数据库中名称，前端直接填充） */\n private String name;\n /** AI 识别的原始名称 */\n private String recognizedName;\n /** 是否精确匹配 */\n private boolean exactMatch;\n }\n\n @Data\n @Builder\n @NoArgsConstructor\n @AllArgsConstructor\n public static class RecognitionItem {\n /** 匹配到的物料 ID */\n private Long materialId;\n /** 物料名称 */\n private String materialName;\n /** 物料编码（来自 MaterialInfoDTO） */\n private String materialCode;\n /** 规格 */\n private String spec;\n /** 单位（来自 MaterialInfoDTO） */\n private String unit;\n /** AI 识别的原始名称 */\n private String recognizedName;\n /** 数量 */\n private BigDecimal quantity;\n /** 单价 */\n private BigDecimal price;\n /** 是否精确匹配 */\n private boolean exactMatch;\n }\n}"}],"isError":false,"timestamp":1780018883245}}
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{"type":"message","id":"1092a9d4","parentId":"9c5939fc","timestamp":"2026-05-29T01:42:21.471Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now I have a clear picture of all the issues. Let me plan the changes:\n\n**Issues to fix:**\n\n1. **单据类型有问题**:\n - `sales_outbound` 硬编码映射为 `typeValue=10, typeName=\"采购入库\"` — 完全错误\n - 应该查数据字典 `inbound_type` 和 `outbound_type`，用 DictService\n - 需要把 `typeDictType` 字段传给前端，让前端知道用哪个字典\n\n2. **客户/供应商**：\n - `Counterparty` 已经有 id + name，看起来前端只需要这些就能填充\n - 但现有匹配逻辑只返回 `id+name`，前端需要 `name` 来填充输入框 — 这点看代码已经有 name 了，但可能前端组件还需要更多辅助字段\n\n3. **物料使用 MaterialFillService**：\n - 现有代码已经在用 `materialFillService.getMaterialInfo()` 填充物料信息\n - 但匹配逻辑需要改为按优先级排序的 `searchSimilar`\n\n4. **local 库测试**：需要确保测试文件里的断言和本地数据库数据匹配\n\nLet me also check what the test expects to understand what data exists locally.\n\nThe test says:\n- AI 识别 test_png.png → 供应商匹配为\"老兵水晶店\"，而且 `cp.getId()` 不能为空\n- 物料明细都要匹配成功，有 materialId\n\nLet me check what the test file looks like for the supplier assertion - it says the supplier name should be \"老兵水晶店\" and ID should not be null.\n\nNow let me think about what specific changes to make:\n\n### 1. AiRecognitionResultDTO changes:\n- 加 `typeDictType` 字段: `\"inbound_type\"` 或 `\"outbound_type\"`\n- `Counterparty` 不需要改，已经有 id + name 了\n- `RecognitionItem` 可能需要加 `matchType/匹配类型` 字段\n\n### 2. AiRecognitionServiceImpl changes:\n- 引入 `DictService` 而不是硬编码映射\n- `sales_outbound` 应该映射为 `outbound_type=10`（销售出库）\n- 根据识别类型决定用哪个字典类型\n- 物料匹配改为结构化方式\n\n### 3. Controller test - 这个测试需要检查 test_png.png 的识别结果，需要确保 test_png.png 对应的图片能被 AI 识别出正确的数据\n\nLet me also check what `test_png.png` is supposed to be.\n\nLet me look at the test more carefully:\n\n```java\nassertNotNull(cp.getId(), \"应匹配到供应商 ID\");\nassertEquals(\"老兵水晶店\", cp.getName(), \"供应商名称应一致\");\n```\n\nSo the test expects the AI to recognize the image as a purchase inbound document from supplier \"老兵水晶店\" with known materials.\n\nThe mock data has \"老兵水晶店\" as a supplier. Let me verify.\n\nOK, let me plan the actual code changes now:\n\n### 1. AiRecognitionResultDTO\nAdd `typeDictType` field.\n\n### 2. AiRecognitionServiceImpl\n- Inject `DictService`\n- Replace the hardcoded TYPE_MAPPING and TYPE_NAME_MAPPING with DictService lookup\n- `purchase_inbound` → dictType=\"inbound_type\", dictValue=\"10\"\n- `sales_outbound` → dictType=\"outbound_type\", dictValue=\"10\"\n- Also need to return `typeDictType` so frontend knows which dict to render\n\n### 3. For the customer/supplier:\nThe existing `Counterparty` already has `id` and `name`. The issue mentioned \"返回前端id 但客户供应商需要查询名称\" - let me check if this is about the AI recognition service or another place.\n\nLooking at the recognition service: `matchCounterparty` returns a `Counterparty` with `id` and `name`. The `name` is set to the database name. So it already returns both ID and name. \n\nWait, re-reading the original request:\n- \"返回前端id 但客户供应商需要查询名称\" - I think this means: currently the recognition returns a supplier/customer with just an ID but the frontend also needs the name to fill the input field.\n\nActually looking at the code, `matchCounterparty` already returns both `id` and `name`. Let me check the `Counterparty` builder:\n\n```java\nreturn AiRecognitionResultDTO.Counterparty.builder()\n .id(s.getId()).name(s.getName())\n .recognizedName(recognizedName)\n .exactMatch(true)\n .build();\n```\n\nThis already sets `name = s.getName()` which is the database name, so name is available. So the customer/supplier name issue is already handled by the existing code. Unless there's something specific the frontend needs.\n\nLet me look at what the frontend actually uses. The issue says \"客户供应商需要查询名称\" - this might mean that when showing the recognition result, the frontend needs the counterparty name to pre-fill the input field. The current code already does this.\n\nBut wait - maybe the original attribute in the frontend input is a TextField where the user types, and it needs the `name` text. The `Counterparty` has `name` so this should work.\n\nOK, I think the main changes needed are:\n\n1. **Fix the type mapping bug**: `sales_outbound` mapped to `10` (same as purchase_inbound!) but named \"采购入库\" — it should be `outbound_type` dict, value `10`, name \"销售出库\"\n2. **Use DictService** instead of hardcoded mappings\n3. **Add `typeDictType`** to DTO so frontend knows which dict to use\n4. **物料匹配** use the structured searchSimilar approach for better prioritization\n5. **测试** update test to match new expected output\n\nLet me make these changes now.\n\nFor the type mapping, the correct mapping should be:\n- `purchase_inbound` → dictType: `inbound_type`, dictValue: `10` (采购入库)\n- `sales_outbound` → dictType: `outbound_type`, dictValue: `10` (销售出库)\n\nAnd the DictService needs to be called to get the dictLabel from dictValue.\n\nActually, simpler approach: I can look up the dict data by dictType + dictValue.\n\n```java\nList<DictData> inboundData = dictService.listData(\"inbound_type\");\n// find where dictValue = \"10\" → dictLabel = \"采购入库\"\nList<DictData> outboundData = dictService.listData(\"outbound_type\");\n// find where dictValue = \"10\" → dictLabel = \"销售出库\"\n```\n\nOr even simpler, keep a static map for the type → dictType mapping, and use DictService to look up the label:\n\n```java\nprivate static final Map<String, String> TYPE_DICT_TYPE_MAP = Map.of(\n \"purchase_inbound\", \"inbound_type\",\n \"sales_outbound\", \"outbound_type\"\n);\n```\n\nAnd then use:\n```java\nString dictType = TYPE_DICT_TYPE_MAP.get(type);\n// Look up dictValue = \"10\" in dictType\n```\n\nFor the AI prompt, I should also update it to include `sales_outbound` type properly.\n\nLet me now code all the changes.\n\nFor the `RecognitionItem` - I should add a `matchType` field to show the matching priority to the frontend. But let me first check if the existing test expects specific fields...\n\nThe test just checks `materialId` is not null, `materialName`, `materialCode`, `spec`, `unit`, `recognizedName`, `quantity`, `price`, `exactMatch`. So adding a `matchType` field won't break the test.\n\nLet me code it up. I'll make these files:\n\n1. Update `AiRecognitionResultDTO` - add `typeDictType`, add `matchType` to RecognitionItem\n2. Update `AiRecognitionServiceImpl` - restructure with DictService\n3. Update `AiControllerTest` - fix assertions to expect correct types\n\nLet me also think about what the test expects more carefully.\n\nThe test test_png.png goes through the AI service, so the actual result depends on what the AI returns. In the test it checks:\n- typeValue should not be null\n- counterparty name = \"老兵水晶店\"\n- items should have materialId (all matched)\n\nFor the local DB test, I need to make sure the DB has the right data.\n\nActually looking at the test more carefully, the `test_png.png` file is read from classpath. The AI recognition returns whatever the AI model recognizes. The test expects \"老兵水晶店\" as supplier name - this is hardcoded in the test assertion. This means either:\n1. The test image is specifically designed to be recognized as a \"老兵水晶店\" purchase order\n2. Or the test is meant to run with mock AI response\n\nI think the test is designed to run with the actual AI model, and the test image is a receipt from 老兵水晶店.\n\nOK let me just make the code changes and update the test accordingly. The key changes:\n\n### AiRecognitionResultDTO changes:\n```java\npublic class AiRecognitionResultDTO {\n private Integer typeValue;\n private String typeName;\n private String typeDictType; // NEW: \"inbound_type\" or \"outbound_type\"\n private Counterparty counterparty;\n private String warehouseName;\n private String remark;\n private List<RecognitionItem> items;\n \n // RecognitionItem adds:\n private String matchType; // NEW: \"EXACT_NAME\", \"FUZZY_SPEC\", etc.\n}\n```\n\n### AiRecognitionServiceImpl changes:\n```java\n@RequiredArgsConstructor\n@Slf4j\n@Service\npublic class AiRecognitionServiceImpl implements AiRecognitionService {\n private final AiService aiService;\n private final SupplierService supplierService;\n private final CustomerService customerService;\n private final MaterialService materialService;\n private final MaterialFillService materialFillService;\n private final DictService dictService; // NEW\n \n // Type → dictType mapping\n private static final Map<String, String> TYPE_DICT_TYPE_MAP = Map.of(\n \"purchase_inbound\", \"inbound_type\",\n \"sales_outbound\", \"outbound_type\"\n );\n \n // Type → default dictValue\n private static final String DEFAULT_DICT_VALUE = \"10\";\n \n // In recognize():\n // 1. Get dictType from TYPE_DICT_TYPE_MAP\n // 2. Look up dictLabel from dictService\n // 3. Return typeDictType + typeValue + typeName\n \n // In matchMaterialItem():\n // Use searchSimilar instead of searchByNameLike\n}\n```\n\nWait, for the test - the typeValue should be 10 for both purchase_inbound and sales_outbound, that's correct per the dictionary data:\n- inbound_type: 10 = \"采购入库\"\n- outbound_type: 10 = \"销售出库\"\n\nSo the typeValue stays 10 for both, but the typeName changes based on dictType.\n\nThe current test asserts:\n```java\nassertNotNull(data.getTypeValue(), \"应识别单据类型\");\n```\n\nThat's fine - typeValue is still 10. But the typeName would now be correctly \"采购入库\" for purchase_inbound and \"销售出库\" for sales_outbound.\n\nLet me check - the test_png.png is a purchase order (到货单), so it would be identified as \"purchase_inbound\" by AI → dictType=\"inbound_type\" → typeValue=10 → typeName=\"采购入库\". The test doesn't check typeName string value, so it should pass.\n\nOK, let me write all the code now.\n\nFor the `RecognitionItem`, I'll add a `matchType` field as a string (the enum name), so the frontend knows the match quality.\n\nLet me also think about what `searchSimilar` method would look like for the MaterialService. According to the design doc:\n\n```java\nList<MaterialMatchResult> searchSimilar(String keyword);\n```\n\nBut `MaterialMatchResult` doesn't exist yet. I need to create it. Or, I can keep it simpler for now and just return `List<Material>` with ordering by priority.\n\nActually, for the AI recognition scenario, the key issue is that when there are multiple results, we want the best one. The current code already picks `candidates.get(0)`, but the `searchByNameLike` method doesn't order by priority — it's a blanket OR query.\n\nFor a simpler approach that doesn't require adding a new DTO and enum in this change:\n1. Keep using `searchByNameLike` but add ordering by match priority\n2. Or create a simple implementation similar to what we designed\n\nI think the cleanest approach is to add a simple `searchSimilar` method that returns `Material` entities in priority order. Let me add it directly to `MaterialService` and `MaterialServiceImpl`.\n\nActually, let me re-read the user's request:\n- \"物料使用com.witsoft.erp.module.md.material.service.MaterialFillService.getMaterialInfoMap填充\"\n- This is already happening in the code.\n\nThe main changes are:\n1. Fix type mapping (the big bug)\n2. Use DictService for types\n3. Add typeDictType field\n4. Improve material matching priority\n\nLet me focus on the concrete changes and produce them.\n\nFor `MaterialServiceImpl.searchSimilar`, I'll implement it directly:\n\n```java\n@Override\npublic List<Material> searchSimilar(String keyword) {\n if (!StringUtils.hasText(keyword)) {\n return Collections.emptyList();\n }\n String escaped = escapeLike(keyword);\n Set<Long> addedIds = new LinkedHashSet<>();\n List<Material> results = new ArrayList<>();\n \n // Priority 1: Exact name match\n LambdaQueryWrapper<Material> w1 = new LambdaQueryWrapper<>();\n w1.eq(Material::getMaterialName, keyword);\n w1.eq(Material::getStatus, 0);\n w1.last(\"LIMIT 5\");\n List<Material> r1 = list(w1);\n for (Material m : r1) {\n if (addedIds.add(m.getId())) results.add(m);\n }\n \n // Priority 2: Name prefix match\n if (results.size() < 20) {\n LambdaQueryWrapper<Material> w2 = new LambdaQueryWrapper<>();\n w2.apply(\"material_name LIKE {0}\", escaped + \"%\");\n w2.eq(Material::getStatus, 0);\n w2.last(\"LIMIT 20\");\n for (Material m : list(w2)) {\n if (addedIds.add(m.getId())) results.add(m);\n }\n }\n \n // Priority 3: Name fuzzy match\n ...\n \n // Priority 4: Spec fuzzy match\n ...\n \n // Priority 5: Code fuzzy match\n ...\n \n return results;\n}\n```\n\nActually this is a lot of code. Let me make this a separate helper method in `MaterialServiceImpl`.\n\nNow let me actually write the code changes.\n\nPlan:\n1. AiRecognitionResultDTO - add typeDictType, add matchType to RecognitionItem\n2. AiRecognitionServiceImpl - the big rewrite\n3. MaterialService - add searchSimilar\n4. MaterialServiceImpl - implement searchSimilar\n5. AiControllerTest - update test\n6. Then run the test\n\nLet me code this step by step.\n\nFor the AiRecognitionServiceImpl, the key change in the type mapping:\n\n```java\n// Replace hardcoded TYPE_MAPPING and TYPE_NAME_MAPPING\nprivate static final Map<String, String> TYPE_DICT_TYPE_MAP = Map.of(\n \"purchase_inbound\", \"inbound_type\",\n \"sales_outbound\", \"outbound_type\"\n);\n```\n\nAnd in `recognize()`:\n```java\n// 4. 转换单据类型 → 字典值\nString dictType = TYPE_DICT_TYPE_MAP.get(type);\nif (dictType == null) {\n throw new BusinessException(400, \"不支持的识别单据类型: \" + type);\n}\n\n// 查找字典值 10 对应的标签\nList<DictData> dictDataList = dictService.listData(dictType);\nDictData matchedDict = dictDataList.stream()\n .filter(d -> d.getDictValue().equals(\"10\"))\n .findFirst().orElse(null);\n\nString typeName = matchedDict != null ? matchedDict.getDictLabel() : \"采购入库\";\n\n// 5. 构建返回结果\nAiRecognitionResultDTO.AiRecognitionResultDTOBuilder builder = AiRecognitionResultDTO.builder()\n .typeValue(10)\n .typeName(typeName)\n .typeDictType(dictType)\n .warehouseName((String) parsed.get(\"warehouse_name\"))\n .remark((String) parsed.get(\"remark\"));\n```\n\nWait, but for sales_outbound, the dictType would be \"outbound_type\" with value \"10\" → label \"销售出库\". That's correct.\n\nFor purchase_inbound, the dictType would be \"inbound_type\" with value \"10\" → label \"采购入库\". That's correct.\n\nAnd for the frontend to know which dict to render, they need typeDictType. \n\nBut wait, I also need to handle the TO_TYPE_NAME_MAPPING removal since the existing `toTypeName` and `TYPE_NAME_MAPPING` are based on the inbound types. Let me just replace the whole section.\n\nAlso, I realize `toTypeValue()` just returns 10 for both types, which is the dictValue. So I can just hardcode 10 or compute it. Let me keep it as 10 for now.\n\nFor the material matching, I'll replace `matchMaterialItem` to use `searchSimilar`:\n\n```java\nprivate AiRecognitionResultDTO.RecognitionItem matchMaterialItem(Map<String, Object> raw) {\n String materialName = (String) raw.get(\"material_name\");\n String spec = (String) raw.get(\"spec\");\n // ... same parsing ...\n \n String normalized = normalizeName(materialName);\n List<Material> candidates = materialService.searchSimilar(normalized);\n \n // If no results, try with spec\n if (candidates.isEmpty() && spec != null) {\n candidates = materialService.searchSimilar(normalized + spec.replaceAll(\"\\\\s+\", \"\"));\n }\n \n // Fallback: tokenize and search\n if (candidates.isEmpty()) {\n List<String> tokens = tokenize(normalized);\n tokens.sort((a, b) -> Integer.compare(b.length(), a.length()));\n for (String token : tokens) {\n if (token.length() >= 2) {\n candidates = materialService.searchSimilar(token);\n if (!candidates.isEmpty()) break;\n }\n }\n }\n \n // If still empty, return raw info\n if (candidates.isEmpty()) {\n return AiRecognitionResultDTO.RecognitionItem.builder()\n .materialName(materialName)\n .spec(spec)\n .recognizedName(materialName)\n .quantity(quantity)\n .price(price)\n .unit(unit)\n .exactMatch(false)\n .build();\n }\n \n Material best = candidates.get(0);\n MaterialInfoDTO info = materialFillService.getMaterialInfo(best.getId());\n \n return AiRecognitionResultDTO.RecognitionItem.builder()\n .materialId(best.getId())\n .materialName(info != null ? info.getMaterialName() : best.getMaterialName())\n .materialCode(info != null ? info.getMaterialCode() : null)\n .spec(info != null ? info.getSpec() : best.getSpec())\n .unit(info != null ? info.getUnit() : best.getUnit())\n .recognizedName(materialName)\n .quantity(quantity)\n .price(price)\n .exactMatch(best.getMaterialName().replaceAll(\"\\\\s+\", \"\").equals(normalized))\n .build();\n}\n```\n\nWait, the `RecognitionItem` already has all the fields from `MaterialInfoDTO`. The user says \"物料使用...MaterialFillService...填充\" which is already being done. I just need to make sure the matching is correct.\n\nLet me write all the changes now. Let me start coding.\n\nAlso for the `toTypeValue` and `toTypeName` methods - let me clean them up. Since we now have `dictType` and look up the dict, we don't need the old `TYPE_MAPPING` and `TYPE_NAME_MAPPING`. Let me just keep a simple AITYPE_TO_DICTTYPE mapping.\n\nI also need to check: does the old `toTypeValue` method also handle sales_outbound? Looking at the original code:\n\n```java\nprivate static final Map<String, Integer> TYPE_MAPPING = Map.of(\n \"purchase_inbound\", 10,\n \"sales_outbound\", 10 // BUG: should be outbound_type=10 dict\n);\n```\n\nBoth return 10. The typeValue is always 10 for both inbound and outbound (they share the same dict value). The difference is in the dictType - inbound_type vs outbound_type. So the fix is:\n- typeValue stays 10\n- typeDictType is \"inbound_type\" or \"outbound_type\"\n- typeName is looked up from the dict\n\nOK let me now write all the code.\n\nFor the `MaterialServiceImpl.searchSimilar`, I need to be careful about not exceeding the result limit. Let me implement a clean version.\n\nActually, I should also think about whether to create a `MaterialMatchResult` DTO or just return `List<Material>`. For simplicity and to minimize changes, I'll return `List<Material>` with priority ordering. The caller just wants the best match anyway.\n\nLet me write the `searchSimilar` implementation in `MaterialServiceImpl`:\n\n```java\n@Override\npublic List<Material> searchSimilar(String keyword) {\n if (!StringUtils.hasText(keyword)) {\n return Collections.emptyList();\n }\n String escaped = escapeLike(keyword);\n Set<Long> addedIds = new LinkedHashSet<>();\n List<Material> results = new ArrayList<>();\n int maxResults = 20;\n\n // 1. 名称精确匹配\n LambdaQueryWrapper<Material> w1 = new LambdaQueryWrapper<>();\n w1.eq(Material::getMaterialName, keyword);\n w1.eq(Material::getStatus, 0);\n w1.last(\"LIMIT \" + maxResults);\n addUnique(results, addedIds, list(w1));\n\n // 2. 名称前缀匹配\n if (results.size() < maxResults) {\n LambdaQueryWrapper<Material> w2 = new LambdaQueryWrapper<>();\n w2.apply(\"material_name LIKE {0}\", escaped + \"%\");\n w2.eq(Material::getStatus, 0);\n w2.last(\"LIMIT \" + maxResults);\n addUnique(results, addedIds, list(w2));\n }\n\n // 3. 名称模糊匹配\n if (results.size() < maxResults) {\n LambdaQueryWrapper<Material> w3 = new LambdaQueryWrapper<>();\n w3.apply(\"material_name LIKE {0}\", \"%\" + escaped + \"%\");\n w3.eq(Material::getStatus, 0);\n w3.last(\"LIMIT \" + maxResults);\n addUnique(results, addedIds, list(w3));\n }\n\n // 4. 规格模糊匹配\n if (results.size() < maxResults) {\n LambdaQueryWrapper<Material> w4 = new LambdaQueryWrapper<>();\n w4.apply(\"spec LIKE {0}\", \"%\" + escaped + \"%\");\n w4.eq(Material::getStatus, 0);\n w4.last(\"LIMIT \" + maxResults);\n addUnique(results, addedIds, list(w4));\n }\n\n // 5. 编码模糊匹配\n if (results.size() < maxResults) {\n LambdaQueryWrapper<Material> w5 = new LambdaQueryWrapper<>();\n w5.apply(\"material_code LIKE {0}\", \"%\" + escaped + \"%\");\n w5.eq(Material::getStatus, 0);\n w5.last(\"LIMIT \" + maxResults);\n addUnique(results, addedIds, list(w5));\n }\n\n return results.stream().limit(maxResults).collect(Collectors.toList());\n}\n\nprivate void addUnique(List<Material> results, Set<Long> addedIds, List<Material> candidates) {\n for (Material m : candidates) {\n if (addedIds.add(m.getId())) {\n results.add(m);\n }\n }\n}\n```\n\nWait, I can't use `w1.eq(Material::getMaterialName, keyword)` because `Material::getMaterialName` is a lambda reference that MyBatis Plus will convert to `material_name = ?`. But actually, MyBatis-Plus can do this. Let me check... yes, `eq(R column, Object val)` works for exact match.\n\nFor the `apply` with LIKE, I'm using raw SQL which also works.\n\nBut wait, in `pageWithStock`, the LIKE queries use:\n```java\n.apply(\"material_code LIKE {0}\", \"%\" + escaped + \"%\")\n```\n\nSo the same format is fine. The `{0}` placeholder is MyBatis-Plus's parameter substitution.\n\nBut for `eq` with `Material::getMaterialName`, the query would be `material_name = #{param}` which is exact match. Good.\n\nLet me check if `Material::getStatus` exists... yes, `status` field is in Material entity.\n\nOne concern: I need to add `like` import... already have it via `LambdaQueryWrapper`.\n\nOK let me now write all the changes. I'll do multiple edits.\n\nActually, wait - I realize I should also add the `searchSimilar` method to the `MaterialService` interface.\n\nLet me just write everything now:\n\n1. MaterialService interface - add `searchSimilar`\n2. MaterialServiceImpl - implement `searchSimilar`\n3. AiRecognitionResultDTO - add `typeDictType`, add `matchType` to RecognitionItem\n4. AiRecognitionServiceImpl - rewrite type mapping + use searchSimilar\n5. AiControllerTest - minor updates\n\nFor the `matchType` in RecognitionItem, I think the simplest approach is to add a String field. Let me add it.\n\nLet me write all the changes.","thinkingSignature":"reasoning_content"},{"type":"text","text":"现在我完全理解了问题全貌。先理清核心要改的 bug 和不足，再动手。\n\n**4 个问题：**\n\n1. **`sales_outbound` 映射为 `typeValue=10, typeName=\"采购入库\"`** — 完全错了，应该是 `outbound_type` 字典的 10→\"销售出库\"\n2. **缺少 `typeDictType`** — 前端不知道用 `inbound_type` 还是 `outbound_type` 字典\n3. **物料匹配** — 需要按优先级排序\n4. **客户/供应商已有 `id+name`** — 已满足前端填充需求，不用动\n\n"},{"type":"toolCall","id":"call_c6b673b3ca99435fa4f010a4","name":"edit","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/MaterialService.java","edits":[{"oldText":" /**\n * 根据关键字模糊搜索物料（返回完整实体）\n *\n * @param keyword 关键字\n * @return 匹配的物料列表\n */\n List<Material> searchByNameLike(String keyword);\n\n}","newText":" /**\n * 根据关键字模糊搜索物料（返回完整实体）\n *\n * @param keyword 关键字\n * @return 匹配的物料列表\n */\n List<Material> searchByNameLike(String keyword);\n\n /**\n * 结构化近似查询：按匹配优先级排序（精确名称 > 名称前缀 > 名称模糊 > 规格模糊 > 编码模糊）\n *\n * @param keyword 关键字\n * @return 按优先级排序的物料列表\n */\n List<Material> searchSimilar(String keyword);\n\n}"}]},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/MaterialService.java\", \"edits\": [{\"oldText\": \" /**\\n * 根据关键字模糊搜索物料（返回完整实体）\\n *\\n * @param keyword 关键字\\n * @return 匹配的物料列表\\n */\\n List<Material> searchByNameLike(String keyword);\\n\\n}\", \"newText\": \" /**\\n * 根据关键字模糊搜索物料（返回完整实体）\\n *\\n * @param keyword 关键字\\n * @return 匹配的物料列表\\n */\\n List<Material> searchByNameLike(String keyword);\\n\\n /**\\n * 结构化近似查询：按匹配优先级排序（精确名称 > 名称前缀 > 名称模糊 > 规格模糊 > 编码模糊）\\n *\\n * @param keyword 关键字\\n * @return 按优先级排序的物料列表\\n */\\n List<Material> searchSimilar(String keyword);\\n\\n}\"}]}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":755,"output":6089,"cacheRead":58880,"cacheWrite":0,"reasoningTokens":5643,"totalTokens":65724,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018883248,"responseId":"chatcmpl-a5facf66-a0e1-4091-8468-a0579860aa37"}}
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{"type":"message","id":"e8449a02","parentId":"b3992bb6","timestamp":"2026-05-29T01:42:41.391Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now I need to implement the `searchSimilar` method in `MaterialServiceImpl`. Let me also add the needed imports.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_da4bc91b7bff4fad8ebc51ff","name":"edit","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialServiceImpl.java","edits":[{"oldText":"import java.math.BigDecimal;\nimport java.util.Collections;\nimport java.util.HashMap;\nimport java.util.List;\nimport java.util.Map;\nimport java.util.stream.Collectors;\n\nimport static com.witsoft.erp.common.util.LikeEscapeUtil.escapeLike;","newText":"import java.math.BigDecimal;\nimport java.util.*;\nimport java.util.stream.Collectors;\n\nimport static com.witsoft.erp.common.util.LikeEscapeUtil.escapeLike;"},{"oldText":" @Override\n public List<Material> searchByNameLike(String keyword) {\n if (!StringUtils.hasText(keyword)) {\n return Collections.emptyList();\n }\n String escaped = escapeLike(keyword);\n LambdaQueryWrapper<Material> wrapper = new LambdaQueryWrapper<>();\n wrapper.and(w -> w\n .apply(\"material_code LIKE {0}\", \"%\" + escaped + \"%\")\n .or()\n .apply(\"material_name LIKE {0}\", \"%\" + escaped + \"%\")\n .or()\n .apply(\"spec LIKE {0}\", \"%\" + escaped + \"%\")\n );\n wrapper.last(\"LIMIT 20\");\n return list(wrapper);\n }\n\n}","newText":" @Override\n public List<Material> searchByNameLike(String keyword) {\n if (!StringUtils.hasText(keyword)) {\n return Collections.emptyList();\n }\n String escaped = escapeLike(keyword);\n LambdaQueryWrapper<Material> wrapper = new LambdaQueryWrapper<>();\n wrapper.and(w -> w\n .apply(\"material_code LIKE {0}\", \"%\" + escaped + \"%\")\n .or()\n .apply(\"material_name LIKE {0}\", \"%\" + escaped + \"%\")\n .or()\n .apply(\"spec LIKE {0}\", \"%\" + escaped + \"%\")\n );\n wrapper.last(\"LIMIT 20\");\n return list(wrapper);\n }\n\n @Override\n public List<Material> searchSimilar(String keyword) {\n if (!StringUtils.hasText(keyword)) {\n return Collections.emptyList();\n }\n\n String escaped = escapeLike(keyword);\n Set<Long> addedIds = new LinkedHashSet<>();\n List<Material> results = new ArrayList<>();\n\n // 1. 名称精确匹配\n searchDistinct(results, addedIds, w -> w.eq(Material::getMaterialName, keyword), 1);\n\n // 2. 名称前缀匹配\n if (results.size() < 30) {\n searchDistinct(results, addedIds, w -> w.apply(\"material_name LIKE {0}\", escaped + \"%\"), 30 - results.size());\n }\n\n // 3. 名称模糊匹配\n if (results.size() < 30) {\n searchDistinct(results, addedIds, w -> w.apply(\"material_name LIKE {0}\", \"%\" + escaped + \"%\"), 30 - results.size());\n }\n\n // 4. 规格模糊匹配\n if (results.size() < 30) {\n searchDistinct(results, addedIds, w -> w.apply(\"spec LIKE {0}\", \"%\" + escaped + \"%\"), 30 - results.size());\n }\n\n // 5. 编码模糊匹配\n if (results.size() < 30) {\n searchDistinct(results, addedIds, w -> w.apply(\"material_code LIKE {0}\", \"%\" + escaped + \"%\"), 30 - results.size());\n }\n\n return results;\n }\n\n /**\n * 按条件搜索物料，跳过已添加的 ID，将新结果追加到结果列表\n */\n private void searchDistinct(List<Material> results, Set<Long> addedIds,\n java.util.function.Consumer<LambdaQueryWrapper<Material>> condition,\n int limit) {\n LambdaQueryWrapper<Material> wrapper = new LambdaQueryWrapper<>();\n condition.accept(wrapper);\n wrapper.eq(Material::getStatus, 0);\n wrapper.orderByDesc(Material::getCreateTime);\n wrapper.last(\"LIMIT \" + limit);\n\n List<Material> list = baseMapper.selectList(wrapper);\n for (Material m : list) {\n if (addedIds.add(m.getId())) {\n results.add(m);\n }\n }\n }\n\n}"}]},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialServiceImpl.java\", \"edits\": [{\"oldText\": \"import java.math.BigDecimal;\\nimport java.util.Collections;\\nimport java.util.HashMap;\\nimport java.util.List;\\nimport java.util.Map;\\nimport java.util.stream.Collectors;\\n\\nimport static com.witsoft.erp.common.util.LikeEscapeUtil.escapeLike;\", \"newText\": \"import java.math.BigDecimal;\\nimport java.util.*;\\nimport java.util.stream.Collectors;\\n\\nimport static com.witsoft.erp.common.util.LikeEscapeUtil.escapeLike;\"}, {\"oldText\": \" @Override\\n public List<Material> searchByNameLike(String keyword) {\\n if (!StringUtils.hasText(keyword)) {\\n return Collections.emptyList();\\n }\\n String escaped = escapeLike(keyword);\\n LambdaQueryWrapper<Material> wrapper = new LambdaQueryWrapper<>();\\n wrapper.and(w -> w\\n .apply(\\\"material_code LIKE {0}\\\", \\\"%\\\" + escaped + \\\"%\\\")\\n .or()\\n .apply(\\\"material_name LIKE {0}\\\", \\\"%\\\" + escaped + \\\"%\\\")\\n .or()\\n .apply(\\\"spec LIKE {0}\\\", \\\"%\\\" + escaped + \\\"%\\\")\\n );\\n wrapper.last(\\\"LIMIT 20\\\");\\n return list(wrapper);\\n }\\n\\n}\", \"newText\": \" @Override\\n public List<Material> searchByNameLike(String keyword) {\\n if (!StringUtils.hasText(keyword)) {\\n return Collections.emptyList();\\n }\\n String escaped = escapeLike(keyword);\\n LambdaQueryWrapper<Material> wrapper = new LambdaQueryWrapper<>();\\n wrapper.and(w -> w\\n .apply(\\\"material_code LIKE {0}\\\", \\\"%\\\" + escaped + \\\"%\\\")\\n .or()\\n .apply(\\\"material_name LIKE {0}\\\", \\\"%\\\" + escaped + \\\"%\\\")\\n .or()\\n .apply(\\\"spec LIKE {0}\\\", \\\"%\\\" + escaped + \\\"%\\\")\\n );\\n wrapper.last(\\\"LIMIT 20\\\");\\n return list(wrapper);\\n }\\n\\n @Override\\n public List<Material> searchSimilar(String keyword) {\\n if (!StringUtils.hasText(keyword)) {\\n return Collections.emptyList();\\n }\\n\\n String escaped = escapeLike(keyword);\\n Set<Long> addedIds = new LinkedHashSet<>();\\n List<Material> results = new ArrayList<>();\\n\\n // 1. 名称精确匹配\\n searchDistinct(results, addedIds, w -> w.eq(Material::getMaterialName, keyword), 1);\\n\\n // 2. 名称前缀匹配\\n if (results.size() < 30) {\\n searchDistinct(results, addedIds, w -> w.apply(\\\"material_name LIKE {0}\\\", escaped + \\\"%\\\"), 30 - results.size());\\n }\\n\\n // 3. 名称模糊匹配\\n if (results.size() < 30) {\\n searchDistinct(results, addedIds, w -> w.apply(\\\"material_name LIKE {0}\\\", \\\"%\\\" + escaped + \\\"%\\\"), 30 - results.size());\\n }\\n\\n // 4. 规格模糊匹配\\n if (results.size() < 30) {\\n searchDistinct(results, addedIds, w -> w.apply(\\\"spec LIKE {0}\\\", \\\"%\\\" + escaped + \\\"%\\\"), 30 - results.size());\\n }\\n\\n // 5. 编码模糊匹配\\n if (results.size() < 30) {\\n searchDistinct(results, addedIds, w -> w.apply(\\\"material_code LIKE {0}\\\", \\\"%\\\" + escaped + \\\"%\\\"), 30 - results.size());\\n }\\n\\n return results;\\n }\\n\\n /**\\n * 按条件搜索物料，跳过已添加的 ID，将新结果追加到结果列表\\n */\\n private void searchDistinct(List<Material> results, Set<Long> addedIds,\\n java.util.function.Consumer<LambdaQueryWrapper<Material>> condition,\\n int limit) {\\n LambdaQueryWrapper<Material> wrapper = new LambdaQueryWrapper<>();\\n condition.accept(wrapper);\\n wrapper.eq(Material::getStatus, 0);\\n wrapper.orderByDesc(Material::getCreateTime);\\n wrapper.last(\\\"LIMIT \\\" + limit);\\n\\n List<Material> list = baseMapper.selectList(wrapper);\\n for (Material m : list) {\\n if (addedIds.add(m.getId())) {\\n results.add(m);\\n }\\n }\\n }\\n\\n}\"}]}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":744,"output":1206,"cacheRead":59392,"cacheWrite":0,"reasoningTokens":24,"totalTokens":61342,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018942001,"responseId":"chatcmpl-5449c446-60cb-417d-9fd7-32817858a4bb"}}
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{"type":"message","id":"bda9660f","parentId":"e8449a02","timestamp":"2026-05-29T01:42:41.901Z","message":{"role":"toolResult","toolCallId":"call_da4bc91b7bff4fad8ebc51ff","toolName":"edit","content":[{"type":"text","text":"Successfully replaced 2 block(s) in /home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/md/material/service/impl/MaterialServiceImpl.java."}],"details":{"diff":" ...\n 17 import org.springframework.stereotype.Service;\n 18 import org.springframework.util.StringUtils;\n 19 \n 20 import java.math.BigDecimal;\n- 21 import java.util.Collections;\n- 22 import java.util.HashMap;\n- 23 import java.util.List;\n- 24 import java.util.Map;\n+ 21 import java.util.*;\n 25 import java.util.stream.Collectors;\n 26 \n 27 import static com.witsoft.erp.common.util.LikeEscapeUtil.escapeLike;\n 28 \n ...\n 168 wrapper.last(\"LIMIT 20\");\n 169 return list(wrapper);\n 170 }\n 171 \n+169 @Override\n+170 public List<Material> searchSimilar(String keyword) {\n+171 if (!StringUtils.hasText(keyword)) {\n+172 return Collections.emptyList();\n+173 }\n+174 \n+175 String escaped = escapeLike(keyword);\n+176 Set<Long> addedIds = new LinkedHashSet<>();\n+177 List<Material> results = new ArrayList<>();\n+178 \n+179 // 1. 名称精确匹配\n+180 searchDistinct(results, addedIds, w -> w.eq(Material::getMaterialName, keyword), 1);\n+181 \n+182 // 2. 名称前缀匹配\n+183 if (results.size() < 30) {\n+184 searchDistinct(results, addedIds, w -> w.apply(\"material_name LIKE {0}\", escaped + \"%\"), 30 - results.size());\n+185 }\n+186 \n+187 // 3. 名称模糊匹配\n+188 if (results.size() < 30) {\n+189 searchDistinct(results, addedIds, w -> w.apply(\"material_name LIKE {0}\", \"%\" + escaped + \"%\"), 30 - results.size());\n+190 }\n+191 \n+192 // 4. 规格模糊匹配\n+193 if (results.size() < 30) {\n+194 searchDistinct(results, addedIds, w -> w.apply(\"spec LIKE {0}\", \"%\" + escaped + \"%\"), 30 - results.size());\n+195 }\n+196 \n+197 // 5. 编码模糊匹配\n+198 if (results.size() < 30) {\n+199 searchDistinct(results, addedIds, w -> w.apply(\"material_code LIKE {0}\", \"%\" + escaped + \"%\"), 30 - results.size());\n+200 }\n+201 \n+202 return results;\n+203 }\n+204 \n+205 /**\n+206 * 按条件搜索物料，跳过已添加的 ID，将新结果追加到结果列表\n+207 */\n+208 private void searchDistinct(List<Material> results, Set<Long> addedIds,\n+209 java.util.function.Consumer<LambdaQueryWrapper<Material>> condition,\n+210 int limit) {\n+211 LambdaQueryWrapper<Material> wrapper = new LambdaQueryWrapper<>();\n+212 condition.accept(wrapper);\n+213 wrapper.eq(Material::getStatus, 0);\n+214 wrapper.orderByDesc(Material::getCreateTime);\n+215 wrapper.last(\"LIMIT \" + limit);\n+216 \n+217 List<Material> list = baseMapper.selectList(wrapper);\n+218 for (Material m : list) {\n+219 if (addedIds.add(m.getId())) {\n+220 results.add(m);\n+221 }\n+222 }\n+223 }\n+224 \n 172 }","firstChangedLine":21},"isError":false,"timestamp":1780018961901}}
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{"type":"message","id":"429f5c03","parentId":"bda9660f","timestamp":"2026-05-29T01:42:45.873Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now I need to:\n1. Add `typeDictType` to `AiRecognitionResultDTO`\n2. Rewrite `AiRecognitionServiceImpl` to:\n - Use `DictService` to resolve inbound_type/outbound_type from dictionary\n - Fix `sales_outbound` → outbound_type → \"销售出库\"\n - Add `typeDictType` field\n - Use `searchSimilar` for material matching\n3. Update test`AiControllerTest`\n\nLet me do the DTO first, then the service impl, then the test.","thinkingSignature":"reasoning_content"},{"type":"toolCall","id":"call_7d43a9a920d3419c81b454a0","name":"update_plan","arguments":{"plan":[{"status":"completed","step":"MaterialService + MaterialServiceImpl - 新增 searchSimilar()"},{"status":"in_progress","step":"修改 AiRecognitionResultDTO - 增加 typeDictType 字段"},{"status":"pending","step":"重写 AiRecognitionServiceImpl - 用 DictService + searchSimilar"},{"status":"pending","step":"更新测试文件 - AiControllerTest 适配新逻辑"},{"status":"pending","step":"运行 local 库测试验证"}]},"partialArgs":"{\"plan\": [{\"status\": \"completed\", \"step\": \"MaterialService + MaterialServiceImpl - 新增 searchSimilar()\"}, {\"status\": \"in_progress\", \"step\": \"修改 AiRecognitionResultDTO - 增加 typeDictType 字段\"}, {\"status\": \"pending\", \"step\": \"重写 AiRecognitionServiceImpl - 用 DictService + searchSimilar\"}, {\"status\": \"pending\", \"step\": \"更新测试文件 - AiControllerTest 适配新逻辑\"}, {\"status\": \"pending\", \"step\": \"运行 local 库测试验证\"}]}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":1471,"output":276,"cacheRead":59904,"cacheWrite":0,"reasoningTokens":116,"totalTokens":61651,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018961904,"responseId":"chatcmpl-9a7c1aa1-e065-4d02-9fe4-cb6b7627863a"}}
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{"type":"message","id":"68b4f955","parentId":"429f5c03","timestamp":"2026-05-29T01:42:46.388Z","message":{"role":"toolResult","toolCallId":"call_7d43a9a920d3419c81b454a0","toolName":"update_plan","content":[],"details":{"status":"updated","plan":[{"step":"MaterialService + MaterialServiceImpl - 新增 searchSimilar()","status":"completed"},{"step":"修改 AiRecognitionResultDTO - 增加 typeDictType 字段","status":"in_progress"},{"step":"重写 AiRecognitionServiceImpl - 用 DictService + searchSimilar","status":"pending"},{"step":"更新测试文件 - AiControllerTest 适配新逻辑","status":"pending"},{"step":"运行 local 库测试验证","status":"pending"}]},"isError":false,"timestamp":1780018966387}}
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{"type":"message","id":"19db19da","parentId":"68b4f955","timestamp":"2026-05-29T01:43:00.177Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now I need to modify the AiRecognitionResultDTO to add the typeDictType field, then rewrite the AiRecognitionServiceImpl to use DictService for type resolution and searchSimilar for material matching.\n\nLet me think about the approach:\n\n1. `AiRecognitionResultDTO`: add `typeDictType` field (inbound_type / outbound_type)\n2. `AiRecognitionServiceImpl`: \n - Inject DictService\n - Use `inbound_type` dictionary for purchase_inbound, `outbound_type` dictionary for sales_outbound\n - Use `materialService.searchSimilar()` for material matching (with MaterialFillService filling)\n - Counterparty matching already uses service methods, just need to keep it\n\nLet me also think about the test file - it hardcodes `assertEquals(\"老兵水晶店\", cp.getName())`. Need to check what the test data looks like - from `mock-inout-data.sql` I can see the supplier name is \"老兵水晶店\". The test uses a test image `test_png.png` from classpath. The AI will recognize whatever is in that image, so the test might need updating or we just run it and see.\n\nBut first, let me get the DTO right, then the service, then handle the test.\n\nFor the DTO, I need to add:\n- `typeDictType`: String - \"inbound_type\" or \"outbound_type\" so frontend knows which dict to use\n\nFor the service, the key changes:\n1. Remove hardcoded TYPE_MAPPING / TYPE_NAME_MAPPING\n2. Inject DictService\n3. After AI returns the type string:\n - \"purchase_inbound\" → dictType=\"inbound_type\", lookup dict data for value=10? Wait, the current code returns typeValue=10 for both inbound and outbound. But actually looking at the test, the assertion checks typeValue only.\n \n Actually looking more carefully at the existing code:\n - \"purchase_inbound\" → typeValue=10 (from TYPE_MAPPING)\n - \"sales_outbound\" → typeValue=10 (from TYPE_MAPPING, same!)\n \n This is wrong because they should belong to different dict types. Let me think about what the right approach is:\n \n - \"purchase_inbound\" → dictType=\"inbound_type\", typeValue=10 (采购入库 from dict data)\n - \"sales_outbound\" → dictType=\"outbound_type\", typeValue=10 (销售出库 from dict data)\n \n The frontend needs:\n - `typeDictType` to know which dictionary to use for displaying options\n - `typeValue` (the dict value)\n - `typeName` (the dict label)\n\nSo the new approach: \n- Map \"purchase_inbound\" → dictType = \"inbound_type\", dictValue = \"10\"\n- Map \"sales_outbound\" → dictType = \"outbound_type\", dictValue = \"10\"\n- Query DictService.listData(dictType) to find the label for that value\n- Return typeDictType, typeValue (Integer), typeName\n\nLet me also check: DictData's dictValue is String but currently typeValue is Integer. Let me keep it as Integer for backward compatibility since frontend likely depends on it.\n\nActually let me check - the existing test expects `data.getTypeValue()` to be non-null. And in the mock data:\n- inbound_type has: 10→采购入库, 20→退货入库, 30→其他入库\n- outbound_type has: 10→销售出库, 20→领料出库, 30→其他出库\n\nSo for purchase_inbound: typeDictType=\"inbound_type\", typeValue=10, typeName=\"采购入库\"\nFor sales_outbound: typeDictType=\"outbound_type\", typeValue=10, typeName=\"销售出库\"\n\nNow for the test, it asserts `assertEquals(\"老兵水晶店\", cp.getName())`. This is testing against the test image which presumably contains a 老兵水晶店 to arrive. The supplier service searchByNameLike should find it. This should still work. The test also checks `assertNotNull(cp.getId())`.\n\nFor materials, the test expects materialId != null for matched items. With searchSimilar this should still work.\n\nLet me think about unit test more: the test reads `test_png.png` from classpath resources. I need to check what that image is. Let me look at the test resource path.\n\nOK, let me just write the code and see. Let me also handle making `typeValue` a String to match the dictionary, or keep Integer. Since the dict value is stored as String (e.g. \"10\") and the existing code uses Integer, I'll keep Integer for backward compat and just parse it.\n\nActually, let me be more careful. The DictData has dictValue as String. If I query DictService to get the label, I need to match by dict value string. And then parse to Integer for typeValue.\n\nLet me proceed with the implementation.","thinkingSignature":"reasoning_content"},{"type":"text","text":"Now modify the DTO to add `typeDictType`"},{"type":"toolCall","id":"call_7db777d584054402ac317659","name":"edit","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/dto/AiRecognitionResultDTO.java","edits":[{"oldText":" /** 单据类型字典值（10-采购入库，20-退货入库 / 10-销售出库，20-领料出库） */\n private Integer typeValue;\n\n /** 单据类型名称（采购入库 / 销售出库） */\n private String typeName;","newText":" /** 单据类型字典值（10-采购入库，20-退货入库 / 10-销售出库，20-领料出库） */\n private Integer typeValue;\n\n /** 单据类型名称（采购入库 / 销售出库） */\n private String typeName;\n\n /** 单据类型字典标识（inbound_type / outbound_type），前端据此刻别使用哪个字典 */\n private String typeDictType;"}]},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/dto/AiRecognitionResultDTO.java\", \"edits\": [{\"oldText\": \" /** 单据类型字典值（10-采购入库，20-退货入库 / 10-销售出库，20-领料出库） */\\n private Integer typeValue;\\n\\n /** 单据类型名称（采购入库 / 销售出库） */\\n private String typeName;\", \"newText\": \" /** 单据类型字典值（10-采购入库，20-退货入库 / 10-销售出库，20-领料出库） */\\n private Integer typeValue;\\n\\n /** 单据类型名称（采购入库 / 销售出库） */\\n private String typeName;\\n\\n /** 单据类型字典标识（inbound_type / outbound_type），前端据此刻别使用哪个字典 */\\n private String typeDictType;\"}]}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":365,"output":1350,"cacheRead":61184,"cacheWrite":0,"reasoningTokens":1059,"totalTokens":62899,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018966391,"responseId":"chatcmpl-19ea315d-28e2-4e67-9e43-3616c25a6847"}}
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{"type":"message","id":"f4ad6e9d","parentId":"19db19da","timestamp":"2026-05-29T01:43:00.691Z","message":{"role":"toolResult","toolCallId":"call_7db777d584054402ac317659","toolName":"edit","content":[{"type":"text","text":"Successfully replaced 1 block(s) in /home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/dto/AiRecognitionResultDTO.java."}],"details":{"diff":" ...\n 28 \n 29 /** 单据类型名称（采购入库 / 销售出库） */\n 30 private String typeName;\n 31 \n+32 /** 单据类型字典标识（inbound_type / outbound_type），前端据此刻别使用哪个字典 */\n+33 private String typeDictType;\n+34 \n 32 /** 供应商/客户（含 id + name） */\n 33 private Counterparty counterparty;\n 34 \n 35 /** 仓库名称（可选） */\n ...","firstChangedLine":32},"isError":false,"timestamp":1780018980690}}
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||
{"type":"message","id":"81d8fae4","parentId":"f4ad6e9d","timestamp":"2026-05-29T01:43:55.660Z","message":{"role":"assistant","content":[{"type":"thinking","thinking":"Now I need to rewrite `AiRecognitionServiceImpl`. The key changes:\n\n1. Replace the hardcoded `TYPE_MAPPING` / `TYPE_NAME_MAPPING` with DictService to look up `inbound_type` and `outbound_type` dictionaries\n2. Add `typeDictType` to the response\n3. Keep `typeValue` as Integer, but need to handle that dict values in DB are stored as String\n4. Use `searchSimilar()` for material matching instead of `searchByNameLike()`\n5. Keep the existing tokenization/fallback logic but layer it on top of searchSimilar\n\nLet me think about the dict lookup more carefully:\n\nCurrent code:\n- `purchase_inbound` → `typeValue=10, typeName=\"采购入库\"` (correct)\n- `sales_outbound` → `typeValue=10, typeName=\"采购入库\"` (BROKEN - should be `typeValue=10, typeName=\"销售出库\"` with `typeDictType=\"outbound_type\"`)\n\nThe fix:\n- `purchase_inbound` → `typeDictType=\"inbound_type\"`, look up `inbound_type` dict for each value\n- `sales_outbound` → `typeDictType=\"outbound_type\"`, look up `outbound_type` dict for each value\n\nBut wait, the test expects specific supplier names and checks for typeValue. Let me look at what the test expects again:\n\nFrom the test:\n```java\nassertEquals(\"老兵水晶店\", cp.getName(), \"供应商名称应一致\");\n```\n\nAnd the type assertion is:\n```java\nassertNotNull(data.getTypeValue(), \"应识别单据类型\");\n```\n\nSo it just asserts non-null.\n\nThe test sends a PNG image (test_png.png) which is a fake image - the AI will hallucinate. The test just verifies the process runs without error.\n\nBut actually looking at the mock data:\n- `purchase_inbound` → typeValue=10 → inbound_type dictionary has \"10=采购入库\"\n- `sales_outbound` → should map to outbound_type dictionary \"10=销售出库\"\n\nSo for `sales_outbound`, we need:\n- `typeDictType = \"outbound_type\"`\n- Look up `outbound_type` dict for value 10 → \"销售出库\"\n- `typeValue = 10`\n\nFor `purchase_inbound`, same but with `inbound_type`:\n- `typeDictType = \"inbound_type\"`\n- Look up `inbound_type` dict for value 10 → \"采购入库\"\n- `typeValue = 10`\n\nThe hardcoded mappings should be replaced by a map from AI type string to (dictType, dictValue). But actually the AI returns the type string, and for both purchase_inbound and sales_outbound the dictValue is 10. Let me think about this more carefully.\n\nActually, the current design maps:\n- `purchase_inbound` → inbound (typeValue=10)\n- `sales_outbound` → outbound (typeValue=10)\n\nThe bug is just that `sales_outbound` was mapped to typeValue=10 but typeName was hardcoded as \"采购入库\".\n\nThe fix should be:\n1. Map AI type to (dictType, defaultDictValue)\n2. Look up the dict to get the label\n\nActually, let me simplify: the current hardcoded mapping just maps AI types to base values. We should extend this to also include the dict type.\n\nLet me write the new implementation:\n\n```java\n// 单据类型映射：AI 返回类型 → (字典标识, 默认字典值)\nprivate static final Map<String, TypeMapping> TYPE_MAPPING = Map.of(\n \"purchase_inbound\", new TypeMapping(\"inbound_type\", 10),\n \"sales_outbound\", new TypeMapping(\"outbound_type\", 10)\n);\n\nprivate record TypeMapping(String dictType, int defaultDictValue) {}\n\nprivate final DictService dictService;\n\n// Then in recognize():\nTypeMapping tm = TYPE_MAPPING.get(type);\nString dictType = tm.dictType();\nint typeValue = tm.defaultDictValue();\n\n// Look up dict label\nList<DictData> dictData = dictService.listData(dictType);\nString typeName = dictData.stream()\n .filter(d -> String.valueOf(typeValue).equals(d.getDictValue()))\n .map(DictData::getDictLabel)\n .findFirst()\n .orElse(null);\n\n// builder\nbuilder.typeValue(typeValue)\n .typeName(typeName)\n .typeDictType(dictType)\n```\n\nWait, but `typeValue` is `Integer`. Dict values in the DB are stored as String. So comparison needs to handle String-to-Integer conversion.\n\nActually there's a subtlety: the existing code had `TYPE_NAME_MAPPING` which defined mapping from 10→\"采购入库\", 20→\"退货入库\" etc. These are inbound_type labels. For outbound_type, the dict in the DB has different labels for the same value 10. So we should just look up from the database.\n\nBut there's a problem: the `TYPE_NAME_MAPPING` was also used as a fallback when DB lookup fails. Let me keep that but use DB first.\n\nActually, let me simplify: just use DictService to look up the label. If it fails, use a minimal hardcoded fallback.\n\nLet me also think about the material matching. The current logic:\n1. Try `searchByNameLike(normalized)` \n2. Try `searchByNameLike(name + spec)` \n3. Tokenize and try longest token\n4. Try Chinese-only parts\n\nI should change step 1 to use `searchSimilar()` instead, but keep the fallback logic as-is.\n\nActually, the searchSimilar already covers: exact name, prefix, fuzzy name, fuzzy spec, fuzzy code. So step 1 (searchByNameLike) which does OR across name/code/spec can be replaced by searchSimilar which is better prioritized.\n\nBut steps 2-4 are fallback using tokenized parts - these use searchByNameLike which is the \"OR everything\" approach. For these fallbacks, I should keep using searchByNameLike since they're searching partial tokens.\n\nActually, I think a better approach: replace ONLY the first search attempt with searchSimilar, keep the rest of the fallbacks as-is using searchByNameLike. This way:\n- Primary attempt: structured ranked search\n- Fallback tokenization: original OR search (good enough for partial matches)\n\nLet me also handle the DictService injection.\n\nLet me write the full replacement.","thinkingSignature":"reasoning_content"},{"type":"text","text":"Now rewrite `AiRecognitionServiceImpl` — the biggest change:\n\n"},{"type":"toolCall","id":"call_2b23ee520c9c49bc8d44e22f","name":"edit","arguments":{"path":"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java","edits":[{"oldText":"package com.witsoft.erp.module.ai.service.impl;\n\nimport com.witsoft.erp.common.core.BusinessException;\nimport com.witsoft.erp.module.ai.dto.*;\nimport com.witsoft.erp.module.ai.service.AiRecognitionService;\nimport com.witsoft.erp.module.ai.service.AiService;\nimport com.witsoft.erp.module.md.customer.entity.Customer;\nimport com.witsoft.erp.module.md.customer.service.CustomerService;\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\nimport com.witsoft.erp.module.md.material.entity.Material;\nimport com.witsoft.erp.module.md.material.service.MaterialFillService;\nimport com.witsoft.erp.module.md.material.service.MaterialService;\nimport com.witsoft.erp.module.md.supplier.entity.Supplier;\nimport com.witsoft.erp.module.md.supplier.service.SupplierService;\nimport lombok.RequiredArgsConstructor;\nimport lombok.extern.slf4j.Slf4j;\nimport org.springframework.stereotype.Service;\nimport org.springframework.web.multipart.MultipartFile;\n\nimport java.math.BigDecimal;\nimport java.util.*;\nimport java.util.stream.Collectors;\n\n/**\n * AI 单据识别服务实现\n *\n * 流程：\n * 1. 调用 AI 识别单据图片\n * 2. 解析 AI 返回的 JSON\n * 3. 单据类型：purchase_inbound → typeValue=10, typeName=采购入库\n * 4. 模糊匹配供应商/客户（去空格 + 分词片段 + 降级匹配）\n * 5. 模糊匹配物料（去空格 + 分词 + MaterialFillService 填充）\n * 6. 返回前端可用的 id + name\n */\n@Slf4j\n@Service\n@RequiredArgsConstructor\npublic class AiRecognitionServiceImpl implements AiRecognitionService {\n\n private final AiService aiService;\n private final SupplierService supplierService;\n private final CustomerService customerService;\n private final MaterialService materialService;\n private final MaterialFillService materialFillService;\n\n private static final String RECOGNITION_PROMPT =\n \"请识别图片中的单据内容，严格按照 JSON 格式返回，不要包含 Markdown 代码块标记，不要有其他文字。\\n\" +\n \"\\n\" +\n \"如果是采购入库单/到货单，格式如下：\\n\" +\n \"{\\n\" +\n \" \\\"type\\\": \\\"purchase_inbound\\\",\\n\" +\n \" \\\"supplier_name\\\": \\\"供应商名称\\\",\\n\" +\n \" \\\"warehouse_name\\\": \\\"仓库名称（可选）\\\",\\n\" +\n \" \\\"date\\\": \\\"日期\\\",\\\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"warehouse_name\\\\\\\": \\\\\\\"仓库名称（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"date\\\\\\\": \\\\\\\"日期\\\\\\\",\\\\\\n\" +\n \" \\\\\\\"total_amount\\\\\\\": 总金额,\\\\n\\\" +\\n \\\" \\\\\\\"remark\\\\\\\": \\\\\\\"备注\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"items\\\\\\\": [\\\\n\\\" +\\n \\\" {\\\\n\\\" +\\n \\\" \\\\\\\"material_name\\\\\\\": \\\\\\\"物料名称\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"spec\\\\\\\": \\\\\\\"规格（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"quantity\\\\\\\": 数量,\\\\n\\\" +\\n \\\" \\\\\\\"unit\\\\\\\": \\\\\\\"单位（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"price\\\\\\\": 单价\\\\n\\\" +\\n \\\" }\\\\n\\\" +\\n \\\" ]\\\\n\\\" +\\n \\\"}\\\\n\\\" +\\n \\\"\\\\n\\\" +\\n \\\"如果是销售出库单，格式如下：\\\\n\\\" +\\n \\\"{\\\\n\\\" +\\n \\\" \\\\\\\"type\\\\\\\": \\\\\\\"sales_outbound\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"customer_name\\\\\\\": \\\\\\\"客户名称\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"warehouse_name\\\\\\\": \\\\\\\"仓库名称（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"date\\\\\\\": \\\\\\\"日期\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"total_amount\\\\\\\": 总金额,\\\\n\\\" +\\n \\\" \\\\\\\"remark\\\\\\\": \\\\\\\"备注\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"items\\\\\\\": [\\\\n\\\" +\\n \\\" {\\\\n\\\" +\\n \\\" \\\\\\\"material_name\\\\\\\": \\\\\\\"物料名称\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"spec\\\\\\\": \\\\\\\"规格（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"quantity\\\\\\\": 数量,\\\\n\\\" +\\n \\\" \\\\\\\"unit\\\\\\\": \\\\\\\"单位（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"price\\\\\\\": 单价\\\\n\\\" +\\n \\\" }\\\\n\\\" +\\n \\\" ]\\\\n\\\" +\\n \\\"}\\\";\", \"newText\": \"package com.witsoft.erp.module.ai.service.impl;\\n\\nimport com.witsoft.erp.common.core.BusinessException;\\nimport com.witsoft.erp.module.ai.dto.*;\\nimport com.witsoft.erp.module.ai.service.AiRecognitionService;\\nimport com.witsoft.erp.module.ai.service.AiService;\\nimport com.witsoft.erp.module.md.customer.entity.Customer;\\nimport com.witsoft.erp.module.md.customer.service.CustomerService;\\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\\nimport com.witsoft.erp.module.md.material.entity.Material;\\nimport com.witsoft.erp.module.md.material.service.MaterialFillService;\\nimport com.witsoft.erp.module.md.material.service.MaterialService;\\nimport com.witsoft.erp.module.md.supplier.entity.Supplier;\\nimport com.witsoft.erp.module.md.supplier.service.SupplierService;\\nimport com.witsoft.erp.module.system.dict.entity.DictData;\\nimport com.witsoft.erp.module.system.dict.service.DictService;\\nimport lombok.RequiredArgsConstructor;\\nimport lombok.extern.slf4j.Slf4j;\\nimport org.springframework.stereotype.Service;\\nimport org.springframework.web.multipart.MultipartFile;\\n\\nimport java.math.BigDecimal;\\nimport java.util.*;\\nimport java.util.stream.Collectors;\\n\\n/**\\n * AI 单据识别服务实现\\n *\\n * 流程：\\n * 1. 调用 AI 识别单据图片\\n * 2. 解析 AI 返回的 JSON\\n * 3. 单据类型：通过 DictService 查找字典，返回 typeValue + typeName + typeDictType\\n * 4. 模糊匹配供应商/客户（去空格 + 分词片段 + 降级匹配），返回 id + name\\n * 5. 模糊匹配物料（优先级排序 + 分词降级 + MaterialFillService 填充）\\n * 6. 返回前端可直接填充的数据\\n */\\n@Slf4j\\n@Service\\n@RequiredArgsConstructor\\npublic class AiRecognitionServiceImpl implements AiRecognitionService {\\n\\n private final AiService aiService;\\n private final SupplierService supplierService;\\n private final CustomerService customerService;\\n private final MaterialService materialService;\\n private final MaterialFillService materialFillService;\\n private final DictService dictService;\\n\\n private static final String RECOGNITION_PROMPT =\\n \\\"请识别图片中的单据内容，严格按照 JSON 格式返回，不要包含 Markdown 代码块标记，不要有其他文字。\\\\n\\\" +\\n \\\"\\\\n\\\" +\\n \\\"如果是采购入库单/到货单，格式如下：\\\\n\\\" +\\n \\\"{\\\\n\\\" +\\n \\\" \\\\\\\"type\\\\\\\": \\\\\\\"purchase_inbound\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"supplier_name\\\\\\\": \\\\\\\"供应商名称\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"warehouse_name\\\\\\\": \\\\\\\"仓库名称（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"date\\\\\\\": \\\\\\\"日期\\\\\\\",\\\\\\n\" +\n \" \\\\\\\"total_amount\\\\\\\": 总金额,\\\\n\\\" +\\n \\\" \\\\\\\"remark\\\\\\\": \\\\\\\"备注\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"items\\\\\\\": [\\\\n\\\" +\\n \\\" {\\\\n\\\" +\\n \\\" \\\\\\\"material_name\\\\\\\": \\\\\\\"物料名称\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"spec\\\\\\\": \\\\\\\"规格（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"quantity\\\\\\\": 数量,\\\\n\\\" +\\n \\\" \\\\\\\"unit\\\\\\\": \\\\\\\"单位（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"price\\\\\\\": 单价\\\\n\\\" +\\n \\\" }\\\\n\\\" +\\n \\\" ]\\\\n\\\" +\\n \\\"}\\\\n\\\" +\\n \\\"\\\\n\\\" +\\n \\\"如果是销售出库单，格式如下：\\\\n\\\" +\\n \\\"{\\\\n\\\" +\\n \\\" \\\\\\\"type\\\\\\\": \\\\\\\"sales_outbound\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"customer_name\\\\\\\": \\\\\\\"客户名称\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"warehouse_name\\\\\\\": \\\\\\\"仓库名称（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"date\\\\\\\": \\\\\\\"日期\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"total_amount\\\\\\\": 总金额,\\\\n\\\" +\\n \\\" \\\\\\\"remark\\\\\\\": \\\\\\\"备注\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"items\\\\\\\": [\\\\n\\\" +\\n \\\" {\\\\n\\\" +\\n \\\" \\\\\\\"material_name\\\\\\\": \\\\\\\"物料名称\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"spec\\\\\\\": \\\\\\\"规格（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"quantity\\\\\\\": 数量,\\\\n\\\" +\\n \\\" \\\\\\\"unit\\\\\\\": \\\\\\\"单位（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"price\\\\\\\": 单价\\\\n\\\" +\\n \\\" }\\\\n\\\" +\\n \\\" ]\\\\n\\\" +\\n \\\"}\\\";\"}, {\"oldText\": \" // ========== 单据类型转换 ==========\\n\\n private static final Map<String, Integer> TYPE_MAPPING = Map.of(\\n \\\"purchase_inbound\\\", 10,\\n \\\"sales_outbound\\\", 10\\n );\\n\\n private static final Map<Integer, String> TYPE_NAME_MAPPING = Map.of(\\n 10, \\\"采购入库\\\",\\n 20, \\\"退货入库\\\",\\n 30, \\\"其他入库\\\"\\n );\\n\\n private Integer toTypeValue(String type) {\\n return TYPE_MAPPING.getOrDefault(type, 10);\\n }\\n\\n private String toTypeName(Integer typeValue) {\\n if (typeValue == null) return null;\\n // 入库类型\\n if (typeValue == 10) return \\\"采购入库\\\";\\n if (typeValue == 20) return \\\"退货入库\\\";\\n if (typeValue == 30) return \\\"其他入库\\\";\\n return null;\\n }\", \"newText\": \" // ========== 单据类型转换 ==========\\n\\n /** AI 返回类型 → (字典标识, 默认字典值) */\\n private static final Map<String, TypeMapping> TYPE_DICT_MAP = Map.of(\\n \\\"purchase_inbound\\\", new TypeMapping(\\\"inbound_type\\\", 10),\\n \\\"sales_outbound\\\", new TypeMapping(\\\"outbound_type\\\", 10)\\n );\\n\\n private record TypeMapping(String dictType, int defaultDictValue) {}\\n\\n /**\\n * 查找单据类型：根据 AI 识别结果和字典，返回 typeValue + typeName + typeDictType\\n */\\n private TypeLookupResult lookupOrderType(String aiType) {\\n TypeMapping tm = TYPE_DICT_MAP.get(aiType);\\n if (tm == null) {\\n // 兜底：默认为入库类型\\n return new TypeLookupResult(10, \\\"采购入库\\\", \\\"inbound_type\\\");\\n }\\n\\n int dictValue = tm.defaultDictValue();\\n String dictLabel = null;\\n\\n // 从字典中查询标签\\n List<DictData> dictDataList = dictService.listData(tm.dictType());\\n for (DictData d : dictDataList) {\\n if (String.valueOf(dictValue).equals(d.getDictValue())) {\\n dictLabel = d.getDictLabel();\\n break;\\n }\\n }\\n\\n // 兜底：字典查询不到时用英文标记\\n if (dictLabel == null) {\\n dictLabel = dictValue == 10 ? \\\"采购入库\\\" : \\\"未知类型\\\";\\n }\\n\\n return new TypeLookupResult(dictValue, dictLabel, tm.dictType());\\n }\\n\\n private record TypeLookupResult(Integer typeValue, String typeName, String typeDictType) {}\"}, {\"oldText\": \" // 4. 转换单据类型 → 字典值\\n Integer typeValue = toTypeValue(type);\\n String typeName = toTypeName(typeValue);\\n\\n // 5. 构建返回结果\\n AiRecognitionResultDTO.AiRecognitionResultDTOBuilder builder = AiRecognitionResultDTO.builder()\\n .typeValue(typeValue)\\n .typeName(typeName)\\n .warehouseName((String) parsed.get(\\\"warehouse_name\\\"))\\n .remark((String) parsed.get(\\\"remark\\\"));\", \"newText\": \" // 4. 通过字典查找单据类型\\n TypeLookupResult typeResult = lookupOrderType(type);\\n\\n // 5. 构建返回结果\\n AiRecognitionResultDTO.AiRecognitionResultDTOBuilder builder = AiRecognitionResultDTO.builder()\\n .typeValue(typeResult.typeValue())\\n .typeName(typeResult.typeName())\\n .typeDictType(typeResult.typeDictType())\\n .warehouseName((String) parsed.get(\\\"warehouse_name\\\"))\\n .remark((String) parsed.get(\\\"remark\\\"));\"}, {\"oldText\": \" // 模糊匹配物料（多重降级）\\n String normalized = normalizeName(materialName);\\n\\n List<Material> candidates = materialService.searchByNameLike(normalized);\\n\\n // 如果 combined 无结果，尝试只搜物料名称（去空格后）\\n if (candidates.isEmpty() && spec != null) {\\n candidates = materialService.searchByNameLike(normalized + \\\" \\\" + spec.replaceAll(\\\"\\\\\\\\s+\\\", \\\"\\\"));\\n }\\n\\n // 如果仍无结果，分词匹配（按非字母数字分割）\\n if (candidates.isEmpty()) {\\n List<String> tokens = tokenize(normalized);\\n // 依次用最长片段搜索\\n tokens.sort((a, b) -> Integer.compare(b.length(), a.length()));\\n for (String token : tokens) {\\n if (token.length() >= 2) {\\n candidates = materialService.searchByNameLike(token);\\n if (!candidates.isEmpty()) break;\\n }\\n }\\n }\\n\\n // 如果仍无结果，尝试数字+汉字分离匹配（如\\\"8.5玻璃棒\\\"→搜\\\"玻璃棒\\\"）\\n if (candidates.isEmpty()) {\\n String[] parts = normalized.split(\\\"(?<=\\\\\\\\d)(?=\\\\\\\\D)|(?<=\\\\\\\\D)(?=\\\\\\\\d)\\\");\\n // 用最长的汉字片段搜索\\n List<String> chineseParts = new ArrayList<>();\\n for (String part : parts) {\\n if (part.codePoints().anyMatch(cp -> Character.isIdeographic(cp))) {\\n chineseParts.add(part);\\n }\\n }\\n chineseParts.sort((a, b) -> Integer.compare(b.length(), a.length()));\\n for (String cp : chineseParts) {\\n if (cp.length() >= 2) {\\n candidates = materialService.searchByNameLike(cp);\\n if (!candidates.isEmpty()) break;\\n }\\n }\\n }\\n\\n if (candidates.isEmpty()) {\\n // 完全无法匹配：返回 AI 识别的原始信息\\n return AiRecognitionResultDTO.RecognitionItem.builder()\\n .materialName(materialName)\\n .spec(spec)\\n .recognizedName(materialName)\\n .quantity(quantity)\\n .price(price)\\n .unit(unit)\\n .exactMatch(false)\\n .build();\\n }\\n\\n // 取最佳匹配，并用 MaterialFillService 补充信息\\n Material best = candidates.get(0);\\n MaterialInfoDTO info = materialFillService.getMaterialInfo(best.getId());\", \"newText\": \" // 模糊匹配物料（优先级排序 + 分词降级）\\n String normalized = normalizeName(materialName);\\n\\n // 第一优先：按优先级排序的结构化搜索\\n List<Material> candidates = materialService.searchSimilar(normalized);\\n\\n // 第二优先：结合规格一起搜索\\n if (candidates.isEmpty() && spec != null) {\\n candidates = materialService.searchSimilar(normalized + spec.replaceAll(\\\"\\\\\\\\s+\\\", \\\"\\\"));\\n }\\n\\n // 第三优先：分词匹配（按非字母数字分割）\\n if (candidates.isEmpty()) {\\n List<String> tokens = tokenize(normalized);\\n // 依次用最长片段搜索\\n tokens.sort((a, b) -> Integer.compare(b.length(), a.length()));\\n for (String token : tokens) {\\n if (token.length() >= 2) {\\n candidates = materialService.searchByNameLike(token);\\n if (!candidates.isEmpty()) break;\\n }\\n }\\n }\\n\\n // 第四优先：数字+汉字分离匹配（如\\\"8.5玻璃棒\\\"→搜\\\"玻璃棒\\\"）\\n if (candidates.isEmpty()) {\\n String[] parts = normalized.split(\\\"(?<=\\\\\\\\d)(?=\\\\\\\\D)|(?<=\\\\\\\\D)(?=\\\\\\\\d)\\\");\\n // 用最长的汉字片段搜索\\n List<String> chineseParts = new ArrayList<>();\\n for (String part : parts) {\\n if (part.codePoints().anyMatch(cp -> Character.isIdeographic(cp))) {\\n chineseParts.add(part);\\n }\\n }\\n chineseParts.sort((a, b) -> Integer.compare(b.length(), a.length()));\\n for (String cp : chineseParts) {\\n if (cp.length() >= 2) {\\n candidates = materialService.searchByNameLike(cp);\\n if (!candidates.isEmpty()) break;\\n }\\n }\\n }\\n\\n if (candidates.isEmpty()) {\\n // 完全无法匹配：返回 AI 识别的原始信息\\n return AiRecognitionResultDTO.RecognitionItem.builder()\\n .materialName(materialName)\\n .spec(spec)\\n .recognizedName(materialName)\\n .quantity(quantity)\\n .price(price)\\n .unit(unit)\\n .exactMatch(false)\\n .build();\\n }\\n\\n // 取最佳匹配（优先级最高的第一个），并用 MaterialFillService 补充信息\\n Material best = candidates.get(0);\\n MaterialInfoDTO info = materialFillService.getMaterialInfo(best.getId());\"}]"}]},"partialArgs":"{\"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java\", \"edits\": [{\"oldText\": \"package com.witsoft.erp.module.ai.service.impl;\\n\\nimport com.witsoft.erp.common.core.BusinessException;\\nimport com.witsoft.erp.module.ai.dto.*;\\nimport com.witsoft.erp.module.ai.service.AiRecognitionService;\\nimport com.witsoft.erp.module.ai.service.AiService;\\nimport com.witsoft.erp.module.md.customer.entity.Customer;\\nimport com.witsoft.erp.module.md.customer.service.CustomerService;\\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\\nimport com.witsoft.erp.module.md.material.entity.Material;\\nimport com.witsoft.erp.module.md.material.service.MaterialFillService;\\nimport com.witsoft.erp.module.md.material.service.MaterialService;\\nimport com.witsoft.erp.module.md.supplier.entity.Supplier;\\nimport com.witsoft.erp.module.md.supplier.service.SupplierService;\\nimport lombok.RequiredArgsConstructor;\\nimport lombok.extern.slf4j.Slf4j;\\nimport org.springframework.stereotype.Service;\\nimport org.springframework.web.multipart.MultipartFile;\\n\\nimport java.math.BigDecimal;\\nimport java.util.*;\\nimport java.util.stream.Collectors;\\n\\n/**\\n * AI 单据识别服务实现\\n *\\n * 流程：\\n * 1. 调用 AI 识别单据图片\\n * 2. 解析 AI 返回的 JSON\\n * 3. 单据类型：purchase_inbound → typeValue=10, typeName=采购入库\\n * 4. 模糊匹配供应商/客户（去空格 + 分词片段 + 降级匹配）\\n * 5. 模糊匹配物料（去空格 + 分词 + MaterialFillService 填充）\\n * 6. 返回前端可用的 id + name\\n */\\n@Slf4j\\n@Service\\n@RequiredArgsConstructor\\npublic class AiRecognitionServiceImpl implements AiRecognitionService {\\n\\n private final AiService aiService;\\n private final SupplierService supplierService;\\n private final CustomerService customerService;\\n private final MaterialService materialService;\\n private final MaterialFillService materialFillService;\\n\\n private static final String RECOGNITION_PROMPT =\\n \\\"请识别图片中的单据内容，严格按照 JSON 格式返回，不要包含 Markdown 代码块标记，不要有其他文字。\\\\n\\\" +\\n \\\"\\\\n\\\" +\\n \\\"如果是采购入库单/到货单，格式如下：\\\\n\\\" +\\n \\\"{\\\\n\\\" +\\n \\\" \\\\\\\"type\\\\\\\": \\\\\\\"purchase_inbound\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"supplier_name\\\\\\\": \\\\\\\"供应商名称\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"warehouse_name\\\\\\\": \\\\\\\"仓库名称（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"date\\\\\\\": \\\\\\\"日期\\\\\\\",\\\\\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"warehouse_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"仓库名称（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"date\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"日期\\\\\\\\\\\\\\\",\\\\\\\\\\\\n\\\" +\\n \\\" \\\\\\\\\\\\\\\"total_amount\\\\\\\\\\\\\\\": 总金额,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"remark\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"备注\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"items\\\\\\\\\\\\\\\": [\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" {\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"material_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"物料名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"spec\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"规格（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"quantity\\\\\\\\\\\\\\\": 数量,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"unit\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"单位（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"price\\\\\\\\\\\\\\\": 单价\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" }\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" ]\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"}\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"如果是销售出库单，格式如下：\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"{\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"type\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"sales_outbound\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"customer_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"客户名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"warehouse_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"仓库名称（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"date\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"日期\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"total_amount\\\\\\\\\\\\\\\": 总金额,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"remark\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"备注\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"items\\\\\\\\\\\\\\\": [\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" {\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"material_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"物料名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"spec\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"规格（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"quantity\\\\\\\\\\\\\\\": 数量,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"unit\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"单位（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"price\\\\\\\\\\\\\\\": 单价\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" }\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" ]\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"}\\\\\\\";\\\", \\\"newText\\\": \\\"package com.witsoft.erp.module.ai.service.impl;\\\\n\\\\nimport com.witsoft.erp.common.core.BusinessException;\\\\nimport com.witsoft.erp.module.ai.dto.*;\\\\nimport com.witsoft.erp.module.ai.service.AiRecognitionService;\\\\nimport com.witsoft.erp.module.ai.service.AiService;\\\\nimport com.witsoft.erp.module.md.customer.entity.Customer;\\\\nimport com.witsoft.erp.module.md.customer.service.CustomerService;\\\\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\\\\nimport com.witsoft.erp.module.md.material.entity.Material;\\\\nimport com.witsoft.erp.module.md.material.service.MaterialFillService;\\\\nimport com.witsoft.erp.module.md.material.service.MaterialService;\\\\nimport com.witsoft.erp.module.md.supplier.entity.Supplier;\\\\nimport com.witsoft.erp.module.md.supplier.service.SupplierService;\\\\nimport com.witsoft.erp.module.system.dict.entity.DictData;\\\\nimport com.witsoft.erp.module.system.dict.service.DictService;\\\\nimport lombok.RequiredArgsConstructor;\\\\nimport lombok.extern.slf4j.Slf4j;\\\\nimport org.springframework.stereotype.Service;\\\\nimport org.springframework.web.multipart.MultipartFile;\\\\n\\\\nimport java.math.BigDecimal;\\\\nimport java.util.*;\\\\nimport java.util.stream.Collectors;\\\\n\\\\n/**\\\\n * AI 单据识别服务实现\\\\n *\\\\n * 流程：\\\\n * 1. 调用 AI 识别单据图片\\\\n * 2. 解析 AI 返回的 JSON\\\\n * 3. 单据类型：通过 DictService 查找字典，返回 typeValue + typeName + typeDictType\\\\n * 4. 模糊匹配供应商/客户（去空格 + 分词片段 + 降级匹配），返回 id + name\\\\n * 5. 模糊匹配物料（优先级排序 + 分词降级 + MaterialFillService 填充）\\\\n * 6. 返回前端可直接填充的数据\\\\n */\\\\n@Slf4j\\\\n@Service\\\\n@RequiredArgsConstructor\\\\npublic class AiRecognitionServiceImpl implements AiRecognitionService {\\\\n\\\\n private final AiService aiService;\\\\n private final SupplierService supplierService;\\\\n private final CustomerService customerService;\\\\n private final MaterialService materialService;\\\\n private final MaterialFillService materialFillService;\\\\n private final DictService dictService;\\\\n\\\\n private static final String RECOGNITION_PROMPT =\\\\n \\\\\\\"请识别图片中的单据内容，严格按照 JSON 格式返回，不要包含 Markdown 代码块标记，不要有其他文字。\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"如果是采购入库单/到货单，格式如下：\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"{\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"type\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"purchase_inbound\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"supplier_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"供应商名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"warehouse_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"仓库名称（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"date\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"日期\\\\\\\\\\\\\\\",\\\\\\\\\\\\n\\\" +\\n \\\" \\\\\\\\\\\\\\\"total_amount\\\\\\\\\\\\\\\": 总金额,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"remark\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"备注\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"items\\\\\\\\\\\\\\\": [\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" {\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"material_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"物料名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"spec\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"规格（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"quantity\\\\\\\\\\\\\\\": 数量,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"unit\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"单位（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"price\\\\\\\\\\\\\\\": 单价\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" }\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" ]\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"}\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"如果是销售出库单，格式如下：\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"{\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"type\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"sales_outbound\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"customer_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"客户名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"warehouse_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"仓库名称（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"date\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"日期\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"total_amount\\\\\\\\\\\\\\\": 总金额,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"remark\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"备注\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"items\\\\\\\\\\\\\\\": [\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" {\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"material_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"物料名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"spec\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"规格（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"quantity\\\\\\\\\\\\\\\": 数量,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"unit\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"单位（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"price\\\\\\\\\\\\\\\": 单价\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" }\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" ]\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"}\\\\\\\";\\\"}, {\\\"oldText\\\": \\\" // ========== 单据类型转换 ==========\\\\n\\\\n private static final Map<String, Integer> TYPE_MAPPING = Map.of(\\\\n \\\\\\\"purchase_inbound\\\\\\\", 10,\\\\n \\\\\\\"sales_outbound\\\\\\\", 10\\\\n );\\\\n\\\\n private static final Map<Integer, String> TYPE_NAME_MAPPING = Map.of(\\\\n 10, \\\\\\\"采购入库\\\\\\\",\\\\n 20, \\\\\\\"退货入库\\\\\\\",\\\\n 30, \\\\\\\"其他入库\\\\\\\"\\\\n );\\\\n\\\\n private Integer toTypeValue(String type) {\\\\n return TYPE_MAPPING.getOrDefault(type, 10);\\\\n }\\\\n\\\\n private String toTypeName(Integer typeValue) {\\\\n if (typeValue == null) return null;\\\\n // 入库类型\\\\n if (typeValue == 10) return \\\\\\\"采购入库\\\\\\\";\\\\n if (typeValue == 20) return \\\\\\\"退货入库\\\\\\\";\\\\n if (typeValue == 30) return \\\\\\\"其他入库\\\\\\\";\\\\n return null;\\\\n }\\\", \\\"newText\\\": \\\" // ========== 单据类型转换 ==========\\\\n\\\\n /** AI 返回类型 → (字典标识, 默认字典值) */\\\\n private static final Map<String, TypeMapping> TYPE_DICT_MAP = Map.of(\\\\n \\\\\\\"purchase_inbound\\\\\\\", new TypeMapping(\\\\\\\"inbound_type\\\\\\\", 10),\\\\n \\\\\\\"sales_outbound\\\\\\\", new TypeMapping(\\\\\\\"outbound_type\\\\\\\", 10)\\\\n );\\\\n\\\\n private record TypeMapping(String dictType, int defaultDictValue) {}\\\\n\\\\n /**\\\\n * 查找单据类型：根据 AI 识别结果和字典，返回 typeValue + typeName + typeDictType\\\\n */\\\\n private TypeLookupResult lookupOrderType(String aiType) {\\\\n TypeMapping tm = TYPE_DICT_MAP.get(aiType);\\\\n if (tm == null) {\\\\n // 兜底：默认为入库类型\\\\n return new TypeLookupResult(10, \\\\\\\"采购入库\\\\\\\", \\\\\\\"inbound_type\\\\\\\");\\\\n }\\\\n\\\\n int dictValue = tm.defaultDictValue();\\\\n String dictLabel = null;\\\\n\\\\n // 从字典中查询标签\\\\n List<DictData> dictDataList = dictService.listData(tm.dictType());\\\\n for (DictData d : dictDataList) {\\\\n if (String.valueOf(dictValue).equals(d.getDictValue())) {\\\\n dictLabel = d.getDictLabel();\\\\n break;\\\\n }\\\\n }\\\\n\\\\n // 兜底：字典查询不到时用英文标记\\\\n if (dictLabel == null) {\\\\n dictLabel = dictValue == 10 ? \\\\\\\"采购入库\\\\\\\" : \\\\\\\"未知类型\\\\\\\";\\\\n }\\\\n\\\\n return new TypeLookupResult(dictValue, dictLabel, tm.dictType());\\\\n }\\\\n\\\\n private record TypeLookupResult(Integer typeValue, String typeName, String typeDictType) {}\\\"}, {\\\"oldText\\\": \\\" // 4. 转换单据类型 → 字典值\\\\n Integer typeValue = toTypeValue(type);\\\\n String typeName = toTypeName(typeValue);\\\\n\\\\n // 5. 构建返回结果\\\\n AiRecognitionResultDTO.AiRecognitionResultDTOBuilder builder = AiRecognitionResultDTO.builder()\\\\n .typeValue(typeValue)\\\\n .typeName(typeName)\\\\n .warehouseName((String) parsed.get(\\\\\\\"warehouse_name\\\\\\\"))\\\\n .remark((String) parsed.get(\\\\\\\"remark\\\\\\\"));\\\", \\\"newText\\\": \\\" // 4. 通过字典查找单据类型\\\\n TypeLookupResult typeResult = lookupOrderType(type);\\\\n\\\\n // 5. 构建返回结果\\\\n AiRecognitionResultDTO.AiRecognitionResultDTOBuilder builder = AiRecognitionResultDTO.builder()\\\\n .typeValue(typeResult.typeValue())\\\\n .typeName(typeResult.typeName())\\\\n .typeDictType(typeResult.typeDictType())\\\\n .warehouseName((String) parsed.get(\\\\\\\"warehouse_name\\\\\\\"))\\\\n .remark((String) parsed.get(\\\\\\\"remark\\\\\\\"));\\\"}, {\\\"oldText\\\": \\\" // 模糊匹配物料（多重降级）\\\\n String normalized = normalizeName(materialName);\\\\n\\\\n List<Material> candidates = materialService.searchByNameLike(normalized);\\\\n\\\\n // 如果 combined 无结果，尝试只搜物料名称（去空格后）\\\\n if (candidates.isEmpty() && spec != null) {\\\\n candidates = materialService.searchByNameLike(normalized + \\\\\\\" \\\\\\\" + spec.replaceAll(\\\\\\\"\\\\\\\\\\\\\\\\s+\\\\\\\", \\\\\\\"\\\\\\\"));\\\\n }\\\\n\\\\n // 如果仍无结果，分词匹配（按非字母数字分割）\\\\n if (candidates.isEmpty()) {\\\\n List<String> tokens = tokenize(normalized);\\\\n // 依次用最长片段搜索\\\\n tokens.sort((a, b) -> Integer.compare(b.length(), a.length()));\\\\n for (String token : tokens) {\\\\n if (token.length() >= 2) {\\\\n candidates = materialService.searchByNameLike(token);\\\\n if (!candidates.isEmpty()) break;\\\\n }\\\\n }\\\\n }\\\\n\\\\n // 如果仍无结果，尝试数字+汉字分离匹配（如\\\\\\\"8.5玻璃棒\\\\\\\"→搜\\\\\\\"玻璃棒\\\\\\\"）\\\\n if (candidates.isEmpty()) {\\\\n String[] parts = normalized.split(\\\\\\\"(?<=\\\\\\\\\\\\\\\\d)(?=\\\\\\\\\\\\\\\\D)|(?<=\\\\\\\\\\\\\\\\D)(?=\\\\\\\\\\\\\\\\d)\\\\\\\");\\\\n // 用最长的汉字片段搜索\\\\n List<String> chineseParts = new ArrayList<>();\\\\n for (String part : parts) {\\\\n if (part.codePoints().anyMatch(cp -> Character.isIdeographic(cp))) {\\\\n chineseParts.add(part);\\\\n }\\\\n }\\\\n chineseParts.sort((a, b) -> Integer.compare(b.length(), a.length()));\\\\n for (String cp : chineseParts) {\\\\n if (cp.length() >= 2) {\\\\n candidates = materialService.searchByNameLike(cp);\\\\n if (!candidates.isEmpty()) break;\\\\n }\\\\n }\\\\n }\\\\n\\\\n if (candidates.isEmpty()) {\\\\n // 完全无法匹配：返回 AI 识别的原始信息\\\\n return AiRecognitionResultDTO.RecognitionItem.builder()\\\\n .materialName(materialName)\\\\n .spec(spec)\\\\n .recognizedName(materialName)\\\\n .quantity(quantity)\\\\n .price(price)\\\\n .unit(unit)\\\\n .exactMatch(false)\\\\n .build();\\\\n }\\\\n\\\\n // 取最佳匹配，并用 MaterialFillService 补充信息\\\\n Material best = candidates.get(0);\\\\n MaterialInfoDTO info = materialFillService.getMaterialInfo(best.getId());\\\", \\\"newText\\\": \\\" // 模糊匹配物料（优先级排序 + 分词降级）\\\\n String normalized = normalizeName(materialName);\\\\n\\\\n // 第一优先：按优先级排序的结构化搜索\\\\n List<Material> candidates = materialService.searchSimilar(normalized);\\\\n\\\\n // 第二优先：结合规格一起搜索\\\\n if (candidates.isEmpty() && spec != null) {\\\\n candidates = materialService.searchSimilar(normalized + spec.replaceAll(\\\\\\\"\\\\\\\\\\\\\\\\s+\\\\\\\", \\\\\\\"\\\\\\\"));\\\\n }\\\\n\\\\n // 第三优先：分词匹配（按非字母数字分割）\\\\n if (candidates.isEmpty()) {\\\\n List<String> tokens = tokenize(normalized);\\\\n // 依次用最长片段搜索\\\\n tokens.sort((a, b) -> Integer.compare(b.length(), a.length()));\\\\n for (String token : tokens) {\\\\n if (token.length() >= 2) {\\\\n candidates = materialService.searchByNameLike(token);\\\\n if (!candidates.isEmpty()) break;\\\\n }\\\\n }\\\\n }\\\\n\\\\n // 第四优先：数字+汉字分离匹配（如\\\\\\\"8.5玻璃棒\\\\\\\"→搜\\\\\\\"玻璃棒\\\\\\\"）\\\\n if (candidates.isEmpty()) {\\\\n String[] parts = normalized.split(\\\\\\\"(?<=\\\\\\\\\\\\\\\\d)(?=\\\\\\\\\\\\\\\\D)|(?<=\\\\\\\\\\\\\\\\D)(?=\\\\\\\\\\\\\\\\d)\\\\\\\");\\\\n // 用最长的汉字片段搜索\\\\n List<String> chineseParts = new ArrayList<>();\\\\n for (String part : parts) {\\\\n if (part.codePoints().anyMatch(cp -> Character.isIdeographic(cp))) {\\\\n chineseParts.add(part);\\\\n }\\\\n }\\\\n chineseParts.sort((a, b) -> Integer.compare(b.length(), a.length()));\\\\n for (String cp : chineseParts) {\\\\n if (cp.length() >= 2) {\\\\n candidates = materialService.searchByNameLike(cp);\\\\n if (!candidates.isEmpty()) break;\\\\n }\\\\n }\\\\n }\\\\n\\\\n if (candidates.isEmpty()) {\\\\n // 完全无法匹配：返回 AI 识别的原始信息\\\\n return AiRecognitionResultDTO.RecognitionItem.builder()\\\\n .materialName(materialName)\\\\n .spec(spec)\\\\n .recognizedName(materialName)\\\\n .quantity(quantity)\\\\n .price(price)\\\\n .unit(unit)\\\\n .exactMatch(false)\\\\n .build();\\\\n }\\\\n\\\\n // 取最佳匹配（优先级最高的第一个），并用 MaterialFillService 补充信息\\\\n Material best = candidates.get(0);\\\\n MaterialInfoDTO info = materialFillService.getMaterialInfo(best.getId());\\\"}]\"}"}],"api":"openai-completions","provider":"new-api","model":"deepseek-v4-flash","usage":{"input":457,"output":5970,"cacheRead":61440,"cacheWrite":0,"reasoningTokens":1385,"totalTokens":67867,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"toolUse","timestamp":1780018980693,"responseId":"chatcmpl-38d65a5c-0ddc-4e17-9788-7a028c8351c0"}}
|
||
{"type":"message","id":"0d3fefd8","parentId":"81d8fae4","timestamp":"2026-05-29T01:43:56.168Z","message":{"role":"toolResult","toolCallId":"call_2b23ee520c9c49bc8d44e22f","toolName":"edit","content":[{"type":"text","text":"Validation failed for tool \"edit\":\n - edits.0.newText: must have required properties newText\n\nReceived arguments:\n{\n \"path\": \"/home/yangxuan/Projects/IdeaProjects/tiny-erp/src/main/java/com/witsoft/erp/module/ai/service/impl/AiRecognitionServiceImpl.java\",\n \"edits\": [\n {\n \"oldText\": \"package com.witsoft.erp.module.ai.service.impl;\\n\\nimport com.witsoft.erp.common.core.BusinessException;\\nimport com.witsoft.erp.module.ai.dto.*;\\nimport com.witsoft.erp.module.ai.service.AiRecognitionService;\\nimport com.witsoft.erp.module.ai.service.AiService;\\nimport com.witsoft.erp.module.md.customer.entity.Customer;\\nimport com.witsoft.erp.module.md.customer.service.CustomerService;\\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\\nimport com.witsoft.erp.module.md.material.entity.Material;\\nimport com.witsoft.erp.module.md.material.service.MaterialFillService;\\nimport com.witsoft.erp.module.md.material.service.MaterialService;\\nimport com.witsoft.erp.module.md.supplier.entity.Supplier;\\nimport com.witsoft.erp.module.md.supplier.service.SupplierService;\\nimport lombok.RequiredArgsConstructor;\\nimport lombok.extern.slf4j.Slf4j;\\nimport org.springframework.stereotype.Service;\\nimport org.springframework.web.multipart.MultipartFile;\\n\\nimport java.math.BigDecimal;\\nimport java.util.*;\\nimport java.util.stream.Collectors;\\n\\n/**\\n * AI 单据识别服务实现\\n *\\n * 流程：\\n * 1. 调用 AI 识别单据图片\\n * 2. 解析 AI 返回的 JSON\\n * 3. 单据类型：purchase_inbound → typeValue=10, typeName=采购入库\\n * 4. 模糊匹配供应商/客户（去空格 + 分词片段 + 降级匹配）\\n * 5. 模糊匹配物料（去空格 + 分词 + MaterialFillService 填充）\\n * 6. 返回前端可用的 id + name\\n */\\n@Slf4j\\n@Service\\n@RequiredArgsConstructor\\npublic class AiRecognitionServiceImpl implements AiRecognitionService {\\n\\n private final AiService aiService;\\n private final SupplierService supplierService;\\n private final CustomerService customerService;\\n private final MaterialService materialService;\\n private final MaterialFillService materialFillService;\\n\\n private static final String RECOGNITION_PROMPT =\\n \\\"请识别图片中的单据内容，严格按照 JSON 格式返回，不要包含 Markdown 代码块标记，不要有其他文字。\\\\n\\\" +\\n \\\"\\\\n\\\" +\\n \\\"如果是采购入库单/到货单，格式如下：\\\\n\\\" +\\n \\\"{\\\\n\\\" +\\n \\\" \\\\\\\"type\\\\\\\": \\\\\\\"purchase_inbound\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"supplier_name\\\\\\\": \\\\\\\"供应商名称\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"warehouse_name\\\\\\\": \\\\\\\"仓库名称（可选）\\\\\\\",\\\\n\\\" +\\n \\\" \\\\\\\"date\\\\\\\": \\\\\\\"日期\\\\\\\",\\\\\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"warehouse_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"仓库名称（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"date\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"日期\\\\\\\\\\\\\\\",\\\\\\\\\\\\n\\\" +\\n \\\" \\\\\\\\\\\\\\\"total_amount\\\\\\\\\\\\\\\": 总金额,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"remark\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"备注\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"items\\\\\\\\\\\\\\\": [\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" {\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"material_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"物料名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"spec\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"规格（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"quantity\\\\\\\\\\\\\\\": 数量,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"unit\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"单位（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"price\\\\\\\\\\\\\\\": 单价\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" }\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" ]\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"}\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"如果是销售出库单，格式如下：\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"{\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"type\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"sales_outbound\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"customer_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"客户名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"warehouse_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"仓库名称（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"date\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"日期\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"total_amount\\\\\\\\\\\\\\\": 总金额,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"remark\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"备注\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"items\\\\\\\\\\\\\\\": [\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" {\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"material_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"物料名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"spec\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"规格（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"quantity\\\\\\\\\\\\\\\": 数量,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"unit\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"单位（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"price\\\\\\\\\\\\\\\": 单价\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" }\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" ]\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"}\\\\\\\";\\\", \\\"newText\\\": \\\"package com.witsoft.erp.module.ai.service.impl;\\\\n\\\\nimport com.witsoft.erp.common.core.BusinessException;\\\\nimport com.witsoft.erp.module.ai.dto.*;\\\\nimport com.witsoft.erp.module.ai.service.AiRecognitionService;\\\\nimport com.witsoft.erp.module.ai.service.AiService;\\\\nimport com.witsoft.erp.module.md.customer.entity.Customer;\\\\nimport com.witsoft.erp.module.md.customer.service.CustomerService;\\\\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\\\\nimport com.witsoft.erp.module.md.material.entity.Material;\\\\nimport com.witsoft.erp.module.md.material.service.MaterialFillService;\\\\nimport com.witsoft.erp.module.md.material.service.MaterialService;\\\\nimport com.witsoft.erp.module.md.supplier.entity.Supplier;\\\\nimport com.witsoft.erp.module.md.supplier.service.SupplierService;\\\\nimport com.witsoft.erp.module.system.dict.entity.DictData;\\\\nimport com.witsoft.erp.module.system.dict.service.DictService;\\\\nimport lombok.RequiredArgsConstructor;\\\\nimport lombok.extern.slf4j.Slf4j;\\\\nimport org.springframework.stereotype.Service;\\\\nimport org.springframework.web.multipart.MultipartFile;\\\\n\\\\nimport java.math.BigDecimal;\\\\nimport java.util.*;\\\\nimport java.util.stream.Collectors;\\\\n\\\\n/**\\\\n * AI 单据识别服务实现\\\\n *\\\\n * 流程：\\\\n * 1. 调用 AI 识别单据图片\\\\n * 2. 解析 AI 返回的 JSON\\\\n * 3. 单据类型：通过 DictService 查找字典，返回 typeValue + typeName + typeDictType\\\\n * 4. 模糊匹配供应商/客户（去空格 + 分词片段 + 降级匹配），返回 id + name\\\\n * 5. 模糊匹配物料（优先级排序 + 分词降级 + MaterialFillService 填充）\\\\n * 6. 返回前端可直接填充的数据\\\\n */\\\\n@Slf4j\\\\n@Service\\\\n@RequiredArgsConstructor\\\\npublic class AiRecognitionServiceImpl implements AiRecognitionService {\\\\n\\\\n private final AiService aiService;\\\\n private final SupplierService supplierService;\\\\n private final CustomerService customerService;\\\\n private final MaterialService materialService;\\\\n private final MaterialFillService materialFillService;\\\\n private final DictService dictService;\\\\n\\\\n private static final String RECOGNITION_PROMPT =\\\\n \\\\\\\"请识别图片中的单据内容，严格按照 JSON 格式返回，不要包含 Markdown 代码块标记，不要有其他文字。\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"如果是采购入库单/到货单，格式如下：\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"{\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"type\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"purchase_inbound\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"supplier_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"供应商名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"warehouse_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"仓库名称（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"date\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"日期\\\\\\\\\\\\\\\",\\\\\\\\\\\\n\\\" +\\n \\\" \\\\\\\\\\\\\\\"total_amount\\\\\\\\\\\\\\\": 总金额,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"remark\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"备注\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"items\\\\\\\\\\\\\\\": [\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" {\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"material_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"物料名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"spec\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"规格（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"quantity\\\\\\\\\\\\\\\": 数量,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"unit\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"单位（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"price\\\\\\\\\\\\\\\": 单价\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" }\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" ]\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"}\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"如果是销售出库单，格式如下：\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"{\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"type\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"sales_outbound\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"customer_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"客户名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"warehouse_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"仓库名称（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"date\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"日期\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"total_amount\\\\\\\\\\\\\\\": 总金额,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"remark\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"备注\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"items\\\\\\\\\\\\\\\": [\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" {\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"material_name\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"物料名称\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"spec\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"规格（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"quantity\\\\\\\\\\\\\\\": 数量,\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"unit\\\\\\\\\\\\\\\": \\\\\\\\\\\\\\\"单位（可选）\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" \\\\\\\\\\\\\\\"price\\\\\\\\\\\\\\\": 单价\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" }\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\" ]\\\\\\\\n\\\\\\\" +\\\\n \\\\\\\"}\\\\\\\";\\\"}, {\\\"oldText\\\": \\\" // ========== 单据类型转换 ==========\\\\n\\\\n private static final Map<String, Integer> TYPE_MAPPING = Map.of(\\\\n \\\\\\\"purchase_inbound\\\\\\\", 10,\\\\n \\\\\\\"sales_outbound\\\\\\\", 10\\\\n );\\\\n\\\\n private static final Map<Integer, String> TYPE_NAME_MAPPING = Map.of(\\\\n 10, \\\\\\\"采购入库\\\\\\\",\\\\n 20, \\\\\\\"退货入库\\\\\\\",\\\\n 30, \\\\\\\"其他入库\\\\\\\"\\\\n );\\\\n\\\\n private Integer toTypeValue(String type) {\\\\n return TYPE_MAPPING.getOrDefault(type, 10);\\\\n }\\\\n\\\\n private String toTypeName(Integer typeValue) {\\\\n if (typeValue == null) return null;\\\\n // 入库类型\\\\n if (typeValue == 10) return \\\\\\\"采购入库\\\\\\\";\\\\n if (typeValue == 20) return \\\\\\\"退货入库\\\\\\\";\\\\n if (typeValue == 30) return \\\\\\\"其他入库\\\\\\\";\\\\n return null;\\\\n }\\\", \\\"newText\\\": \\\" // ========== 单据类型转换 ==========\\\\n\\\\n /** AI 返回类型 → (字典标识, 默认字典值) */\\\\n private static final Map<String, TypeMapping> TYPE_DICT_MAP = Map.of(\\\\n \\\\\\\"purchase_inbound\\\\\\\", new TypeMapping(\\\\\\\"inbound_type\\\\\\\", 10),\\\\n \\\\\\\"sales_outbound\\\\\\\", new TypeMapping(\\\\\\\"outbound_type\\\\\\\", 10)\\\\n );\\\\n\\\\n private record TypeMapping(String dictType, int defaultDictValue) {}\\\\n\\\\n /**\\\\n * 查找单据类型：根据 AI 识别结果和字典，返回 typeValue + typeName + typeDictType\\\\n */\\\\n private TypeLookupResult lookupOrderType(String aiType) {\\\\n TypeMapping tm = TYPE_DICT_MAP.get(aiType);\\\\n if (tm == null) {\\\\n // 兜底：默认为入库类型\\\\n return new TypeLookupResult(10, \\\\\\\"采购入库\\\\\\\", \\\\\\\"inbound_type\\\\\\\");\\\\n }\\\\n\\\\n int dictValue = tm.defaultDictValue();\\\\n String dictLabel = null;\\\\n\\\\n // 从字典中查询标签\\\\n List<DictData> dictDataList = dictService.listData(tm.dictType());\\\\n for (DictData d : dictDataList) {\\\\n if (String.valueOf(dictValue).equals(d.getDictValue())) {\\\\n dictLabel = d.getDictLabel();\\\\n break;\\\\n }\\\\n }\\\\n\\\\n // 兜底：字典查询不到时用英文标记\\\\n if (dictLabel == null) {\\\\n dictLabel = dictValue == 10 ? \\\\\\\"采购入库\\\\\\\" : \\\\\\\"未知类型\\\\\\\";\\\\n }\\\\n\\\\n return new TypeLookupResult(dictValue, dictLabel, tm.dictType());\\\\n }\\\\n\\\\n private record TypeLookupResult(Integer typeValue, String typeName, String typeDictType) {}\\\"}, {\\\"oldText\\\": \\\" // 4. 转换单据类型 → 字典值\\\\n Integer typeValue = toTypeValue(type);\\\\n String typeName = toTypeName(typeValue);\\\\n\\\\n // 5. 构建返回结果\\\\n AiRecognitionResultDTO.AiRecognitionResultDTOBuilder builder = AiRecognitionResultDTO.builder()\\\\n .typeValue(typeValue)\\\\n .typeName(typeName)\\\\n .warehouseName((String) parsed.get(\\\\\\\"warehouse_name\\\\\\\"))\\\\n .remark((String) parsed.get(\\\\\\\"remark\\\\\\\"));\\\", \\\"newText\\\": \\\" // 4. 通过字典查找单据类型\\\\n TypeLookupResult typeResult = lookupOrderType(type);\\\\n\\\\n // 5. 构建返回结果\\\\n AiRecognitionResultDTO.AiRecognitionResultDTOBuilder builder = AiRecognitionResultDTO.builder()\\\\n .typeValue(typeResult.typeValue())\\\\n .typeName(typeResult.typeName())\\\\n .typeDictType(typeResult.typeDictType())\\\\n .warehouseName((String) parsed.get(\\\\\\\"warehouse_name\\\\\\\"))\\\\n .remark((String) parsed.get(\\\\\\\"remark\\\\\\\"));\\\"}, {\\\"oldText\\\": \\\" // 模糊匹配物料（多重降级）\\\\n String norm\n\n⚠️ [... middle content omitted — showing head and tail ...]\n\n }\\\\n }\\\\n }\\\\n\\\\n // 如果仍无结果，尝试数字+汉字分离匹配（如\\\\\\\"8.5玻璃棒\\\\\\\"→搜\\\\\\\"玻璃棒\\\\\\\"）\\\\n if (candidates.isEmpty()) {\\\\n String[] parts = normalized.split(\\\\\\\"(?<=\\\\\\\\\\\\\\\\d)(?=\\\\\\\\\\\\\\\\D)|(?<=\\\\\\\\\\\\\\\\D)(?=\\\\\\\\\\\\\\\\d)\\\\\\\");\\\\n // 用最长的汉字片段搜索\\\\n List<String> chineseParts = new ArrayList<>();\\\\n for (String part : parts) {\\\\n if (part.codePoints().anyMatch(cp -> Character.isIdeographic(cp))) {\\\\n chineseParts.add(part);\\\\n }\\\\n }\\\\n chineseParts.sort((a, b) -> Integer.compare(b.length(), a.length()));\\\\n for (String cp : chineseParts) {\\\\n if (cp.length() >= 2) {\\\\n candidates = materialService.searchByNameLike(cp);\\\\n if (!candidates.isEmpty()) break;\\\\n }\\\\n }\\\\n }\\\\n\\\\n if (candidates.isEmpty()) {\\\\n // 完全无法匹配：返回 AI 识别的原始信息\\\\n return AiRecognitionResultDTO.RecognitionItem.builder()\\\\n .materialName(materialName)\\\\n .spec(spec)\\\\n .recognizedName(materialName)\\\\n .quantity(quantity)\\\\n .price(price)\\\\n .unit(unit)\\\\n .exactMatch(false)\\\\n .build();\\\\n }\\\\n\\\\n // 取最佳匹配，并用 MaterialFillService 补充信息\\\\n Material best = candidates.get(0);\\\\n MaterialInfoDTO info = materialFillService.getMaterialInfo(best.getId());\\\", \\\"newText\\\": \\\" // 模糊匹配物料（优先级排序 + 分词降级）\\\\n String normalized = normalizeName(materialName);\\\\n\\\\n // 第一优先：按优先级排序的结构化搜索\\\\n List<Material> candidates = materialService.searchSimilar(normalized);\\\\n\\\\n // 第二优先：结合规格一起搜索\\\\n if (candidates.isEmpty() && spec != null) {\\\\n candidates = materialService.searchSimilar(normalized + spec.replaceAll(\\\\\\\"\\\\\\\\\\\\\\\\s+\\\\\\\", \\\\\\\"\\\\\\\"));\\\\n }\\\\n\\\\n // 第三优先：分词匹配（按非字母数字分割）\\\\n if (candidates.isEmpty()) {\\\\n List<String> tokens = tokenize(normalized);\\\\n // 依次用最长片段搜索\\\\n tokens.sort((a, b) -> Integer.compare(b.length(), a.length()));\\\\n for (String token : tokens) {\\\\n if (token.length() >= 2) {\\\\n candidates = materialService.searchByNameLike(token);\\\\n if (!candidates.isEmpty()) break;\\\\n }\\\\n }\\\\n }\\\\n\\\\n // 第四优先：数字+汉字分离匹配（如\\\\\\\"8.5玻璃棒\\\\\\\"→搜\\\\\\\"玻璃棒\\\\\\\"）\\\\n if (candidates.isEmpty()) {\\\\n String[] parts = normalized.split(\\\\\\\"(?<=\\\\\\\\\\\\\\\\d)(?=\\\\\\\\\\\\\\\\D)|(?<=\\\\\\\\\\\\\\\\D)(?=\\\\\\\\\\\\\\\\d)\\\\\\\");\\\\n // 用最长的汉字片段搜索\\\\n List<String> chineseParts = new ArrayList<>();\\\\n for (String part : parts) {\\\\n if (part.codePoints().anyMatch(cp -> Character.isIdeographic(cp))) {\\\\n chineseParts.add(part);\\\\n }\\\\n }\\\\n chineseParts.sort((a, b) -> Integer.compare(b.length(), a.length()));\\\\n for (String cp : chineseParts) {\\\\n if (cp.length() >= 2) {\\\\n candidates = materialService.searchByNameLike(cp);\\\\n if (!candidates.isEmpty()) break;\\\\n }\\\\n }\\\\n }\\\\n\\\\n if (candidates.isEmpty()) {\\\\n // 完全无法匹配：返回 AI 识别的原始信息\\\\n return AiRecognitionResultDTO.RecognitionItem.builder()\\\\n .materialName(materialName)\\\\n .spec(spec)\\\\n .recognizedName(materialName)\\\\n .quantity(quantity)\\\\n .price(price)\\\\n .unit(unit)\\\\n .exactMatch(false)\\\\n .build();\\\\n }\\\\n\\\\n // 取最佳匹配（优先级最高的第一个），并用 MaterialFillService 补充信息\\\\n Material best = candidates.get(0);\\\\n MaterialInfoDTO info = materialFillService.getMaterialInfo(best.getId());\\\"}]\"\n }\n ]\n}[... 775 more characters truncated]"}],"details":{},"isError":true,"timestamp":1780019036167}}
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{"type":"message","id":"1f3cb15e","parentId":"d7d1b71e","timestamp":"2026-05-29T01:44:16.404Z","message":{"role":"toolResult","toolCallId":"call_3fe965747cde4e1a8ed1893c","toolName":"read","content":[{"type":"text","text":"package com.witsoft.erp.module.ai.service.impl;\n\nimport com.witsoft.erp.common.core.BusinessException;\nimport com.witsoft.erp.module.ai.dto.*;\nimport com.witsoft.erp.module.ai.service.AiRecognitionService;\nimport com.witsoft.erp.module.ai.service.AiService;\nimport com.witsoft.erp.module.md.customer.entity.Customer;\nimport com.witsoft.erp.module.md.customer.service.CustomerService;\nimport com.witsoft.erp.module.md.material.dto.MaterialInfoDTO;\nimport com.witsoft.erp.module.md.material.entity.Material;\nimport com.witsoft.erp.module.md.material.service.MaterialFillService;\nimport com.witsoft.erp.module.md.material.service.MaterialService;\nimport com.witsoft.erp.module.md.supplier.entity.Supplier;\nimport com.witsoft.erp.module.md.supplier.service.SupplierService;\nimport lombok.RequiredArgsConstructor;\nimport lombok.extern.slf4j.Slf4j;\nimport org.springframework.stereotype.Service;\nimport org.springframework.web.multipart.MultipartFile;\n\nimport java.math.BigDecimal;\nimport java.util.*;\nimport java.util.stream.Collectors;\n\n/**\n * AI 单据识别服务实现\n *\n * 流程：\n * 1. 调用 AI 识别单据图片\n * 2. 解析 AI 返回的 JSON\n * 3. 单据类型：purchase_inbound → typeValue=10, typeName=采购入库\n * 4. 模糊匹配供应商/客户（去空格 + 分词片段 + 降级匹配）\n * 5. 模糊匹配物料（去空格 + 分词 + MaterialFillService 填充）\n * 6. 返回前端可用的 id + name\n */\n@Slf4j\n@Service\n@RequiredArgsConstructor\npublic class AiRecognitionServiceImpl implements AiRecognitionService {\n\n private final AiService aiService;\n private final SupplierService supplierService;\n private final CustomerService customerService;\n private final MaterialService materialService;\n private final MaterialFillService materialFillService;\n\n private static final String RECOGNITION_PROMPT =\n \"请识别图片中的单据内容，严格按照 JSON 格式返回，不要包含 Markdown 代码块标记，不要有其他文字。\\n\" +\n \"\\n\" +\n \"如果是采购入库单/到货单，格式如下：\\n\" +\n \"{\\n\" +\n \" \\\"type\\\": \\\"purchase_inbound\\\",\\n\" +\n \" \\\"supplier_name\\\": \\\"供应商名称\\\",\\n\" +\n \" \\\"warehouse_name\\\": \\\"仓库名称（可选）\\\",\\n\" +\n \" \\\"date\\\": \\\"日期\\\",\\n\" +\n \" \\\"total_amount\\\": 总金额,\\n\" +\n \" \\\"remark\\\": \\\"备注\\\",\\n\" +\n \" \\\"items\\\": [\\n\" +\n \" {\\n\" +\n \" \\\"material_name\\\": \\\"物料名称\\\",\\n\" +\n \" \\\"spec\\\": \\\"规格（可选）\\\",\\n\" +\n \" \\\"quantity\\\": 数量,\\n\" +\n \" \\\"unit\\\": \\\"单位（可选）\\\",\\n\" +\n \" \\\"price\\\": 单价\\n\" +\n \" }\\n\" +\n \" ]\\n\" +\n \"}\\n\" +\n \"\\n\" +\n \"如果是销售出库单，格式如下：\\n\" +\n \"{\\n\" +\n \" \\\"type\\\": \\\"sales_outbound\\\",\\n\" +\n \" \\\"customer_name\\\": \\\"客户名称\\\",\\n\" +\n \" \\\"warehouse_name\\\": \\\"仓库名称（可选）\\\",\\n\" +\n \" \\\"date\\\": \\\"日期\\\",\\n\" +\n \" \\\"total_amount\\\": 总金额,\\n\" +\n \" \\\"remark\\\": \\\"备注\\\",\\n\" +\n \" \\\"items\\\": [\\n\" +\n \" {\\n\" +\n \" \\\"material_name\\\": \\\"物料名称\\\",\\n\" +\n \" \\\"spec\\\": \\\"规格（可选）\\\",\\n\" +\n \" \\\"quantity\\\": 数量,\\n\" +\n \" \\\"unit\\\": \\\"单位（可选）\\\",\\n\" +\n \" \\\"price\\\": 单价\\n\" +\n \" }\\n\" +\n \" ]\\n\" +\n \"}\";\n\n @Override\n public AiRecognitionResultDTO recognize(MultipartFile file) {\n // 1. 调用 AI 识别图片\n AiChatResponseDTO aiResponse = aiService.chatWithImages(RECOGNITION_PROMPT, Collections.singletonList(file));\n String rawReply = aiResponse.getReply();\n log.info(\"AI 识别原始回复：{}\", rawReply);\n\n // 2. 提取 JSON\n String json = extractJson(rawReply);\n if (json == null) {\n throw new BusinessException(500, \"AI 回复格式异常，无法解析为 JSON\");\n }\n\n // 3. 解析 JSON\n Map<String, Object> parsed = parseSimpleJson(json);\n String type = (String) parsed.get(\"type\");\n if (type == null) {\n throw new BusinessException(400, \"AI 未能识别单据类型\");\n }\n\n // 4. 转换单据类型 → 字典值\n Integer typeValue = toTypeValue(type);\n String typeName = toTypeName(typeValue);\n\n // 5. 构建返回结果\n AiRecognitionResultDTO.AiRecognitionResultDTOBuilder builder = AiRecognitionResultDTO.builder()\n .typeValue(typeValue)\n .typeName(typeName)\n .warehouseName((String) parsed.get(\"warehouse_name\"))\n .remark((String) parsed.get(\"remark\"));\n\n // 6. 模糊匹配供应商或客户（去空格 + 分词片段匹配）\n if (\"purchase_inbound\".equals(type)) {\n String supplierName = (String) parsed.get(\"supplier_name\");\n if (supplierName != null) {\n builder.counterparty(matchSupplier(supplierName));\n }\n } else if (\"sales_outbound\".equals(type)) {\n String customerName = (String) parsed.get(\"customer_name\");\n if (customerName != null) {\n builder.counterparty(matchCustomer(customerName));\n }\n }\n\n // 7. 模糊匹配物料明细（去空格 + 分词 + MaterialFillService 填充）\n @SuppressWarnings(\"unchecked\")\n List<Map<String, Object>> rawItems = (List<Map<String, Object>>) parsed.get(\"items\");\n if (rawItems != null && !rawItems.isEmpty()) {\n List<AiRecognitionResultDTO.RecognitionItem> items = rawItems.stream()\n .map(this::matchMaterialItem)\n .filter(Objects::nonNull)\n .collect(Collectors.toList());\n builder.items(items);\n }\n\n return builder.build();\n }\n\n // ========== 单据类型转换 ==========\n\n private static final Map<String, Integer> TYPE_MAPPING = Map.of(\n \"purchase_inbound\", 10,\n \"sales_outbound\", 10\n );\n\n private static final Map<Integer, String> TYPE_NAME_MAPPING = Map.of(\n 10, \"采购入库\",\n 20, \"退货入库\",\n 30, \"其他入库\"\n );\n\n private Integer toTypeValue(String type) {\n return TYPE_MAPPING.getOrDefault(type, 10);\n }\n\n private String toTypeName(Integer typeValue) {\n if (typeValue == null) return null;\n // 入库类型\n if (typeValue == 10) return \"采购入库\";\n if (typeValue == 20) return \"退货入库\";\n if (typeValue == 30) return \"其他入库\";\n return null;\n }\n\n // ========== 模糊匹配供应商/客户（去空格 + 分词） ==========\n\n private AiRecognitionResultDTO.Counterparty matchSupplier(String recognizedName) {\n return matchCounterparty(recognizedName,\n keyword -> supplierService.searchByNameLike(keyword),\n s -> AiRecognitionResultDTO.Counterparty.builder()\n .id(s.getId()).name(s.getName()));\n }\n\n private AiRecognitionResultDTO.Counterparty matchCustomer(String recognizedName) {\n return matchCounterparty(recognizedName,\n keyword -> customerService.searchByNameLike(keyword),\n c -> AiRecognitionResultDTO.Counterparty.builder()\n .id(c.getId()).name(c.getName()));\n }\n\n /**\n * 通用模糊匹配：\n * 1. 直接 LIKE 搜索（AI 识别的名称与原版去空格后 LIKE）\n * 2. 如果无结果，分词后每个片段单独 LIKE\n * 3. 如果仍无结果，返回原始名称（exactMatch=false）\n */\n private <T> AiRecognitionResultDTO.Counterparty matchCounterparty(\n String recognizedName,\n FuzzySearch<T> searcher,\n java.util.function.Function<T, AiRecognitionResultDTO.Counterparty.CounterpartyBuilder> mapper) {\n\n // 归一化：去空格\n String normalized = normalizeName(recognizedName);\n log.debug(\"供应商/客户模糊匹配：原始='{}', 归一='{}'\", recognizedName, normalized);\n\n // 1. 直接 LIKE 搜索（使用归一化后的名称）\n List<T> candidates = searcher.search(normalized);\n if (!candidates.isEmpty()) {\n T best = candidates.get(0);\n return mapper.apply(best)\n .recognizedName(recognizedName)\n .exactMatch(true)\n .build();\n }\n\n // 2. 分词后每个片段单独搜索\n List<String> tokens = tokenize(normalized);\n if (tokens.size() >= 2) {\n // 用最长分段词搜索\n String longestToken = tokens.stream()\n .max(Comparator.comparingInt(String::length))\n .orElse(\"\");\n if (longestToken.length() >= 2) {\n candidates = searcher.search(longestToken);\n if (!candidates.isEmpty()) {\n T best = candidates.get(0);\n return mapper.apply(best)\n .recognizedName(recognizedName)\n .exactMatch(false)\n .build();\n }\n }\n\n // 两个词组合搜索\n for (int i = 0; i < tokens.size() && candidates.isEmpty(); i++) {\n for (int j = i + 1; j < tokens.size(); j++) {\n String combined = tokens.get(i) + tokens.get(j).replace(tokens.get(i), \"\");\n if (combined.length() >= 2) {\n candidates = searcher.search(combined);\n if (!candidates.isEmpty()) break;\n }\n }\n }\n if (!candidates.isEmpty()) {\n T best = candidates.get(0);\n return mapper.apply(best)\n .recognizedName(recognizedName)\n .exactMatch(false)\n .build();\n }\n }\n\n // 3. 完全无法匹配，返回识别到的原始名称\n return AiRecognitionResultDTO.Counterparty.builder()\n .name(recognizedName)\n .recognizedName(recognizedName)\n .exactMatch(false)\n .build();\n }\n\n @FunctionalInterface\n private interface FuzzySearch<T> {\n List<T> search(String keyword);\n }\n\n // ========== 模糊匹配物料（去空格 + 分词 + MaterialFillService 填充） ==========\n\n private AiRecognitionResultDTO.RecognitionItem matchMaterialItem(Map<String, Object> raw) {\n String materialName = (String) raw.get(\"material_name\");\n String spec = (String) raw.get(\"spec\");\n Object qtyObj = raw.get(\"quantity\");\n Object priceObj = raw.get(\"price\");\n String unit = (String) raw.get(\"unit\");\n\n if (materialName == null || materialName.trim().isEmpty()) {\n return null;\n }\n\n BigDecimal quantity = toBigDecimal(qtyObj);\n BigDecimal price = toBigDecimal(priceObj);\n\n // 模糊匹配物料（多重降级）\n String normalized = normalizeName(materialName);\n\n List<Material> candidates = materialService.searchByNameLike(normalized);\n\n // 如果 combined 无结果，尝试只搜物料名称（去空格后）\n if (candidates.isEmpty() && spec != null) {\n candidates = materialService.searchByNameLike(normalized + \" \" + spec.replaceAll(\"\\\\s+\", \"\"));\n }\n\n // 如果仍无结果，分词匹配（按非字母数字分割）\n if (candidates.isEmpty()) {\n List<String> tokens = tokenize(normalized);\n // 依次用最长片段搜索\n tokens.sort((a, b) -> Integer.compare(b.length(), a.length()));\n for (String token : tokens) {\n if (token.length() >= 2) {\n candidates = materialService.searchByNameLike(token);\n if (!candidates.isEmpty()) break;\n }\n }\n }\n\n // 如果仍无结果，尝试数字+汉字分离匹配（如\"8.5玻璃棒\"→搜\"玻璃棒\"）\n if (candidates.isEmpty()) {\n String[] parts = normalized.split(\"(?<=\\\\d)(?=\\\\D)|(?<=\\\\D)(?=\\\\d)\");\n // 用最长的汉字片段搜索\n List<String> chineseParts = new ArrayList<>();\n for (String part : parts) {\n if (part.codePoints().anyMatch(cp -> Character.isIdeographic(cp))) {\n chineseParts.add(part);\n }\n }\n chineseParts.sort((a, b) -> Integer.compare(b.length(), a.length()));\n for (String cp : chineseParts) {\n if (cp.length() >= 2) {\n candidates = materialService.searchByNameLike(cp);\n if (!candidates.isEmpty()) break;\n }\n }\n }\n\n if (candidates.isEmpty()) {\n // 完全无法匹配：返回 AI 识别的原始信息\n return AiRecognitionResultDTO.RecognitionItem.builder()\n .materialName(materialName)\n .spec(spec)\n .recognizedName(materialName)\n .quantity(quantity)\n\n⚠️ [... middle content omitted — showing head and tail ...]\n\n }\n return null;\n }\n\n @SuppressWarnings(\"unchecked\")\n private Map<String, Object> parseSimpleJson(String json) {\n Map<String, Object> result = new LinkedHashMap<>();\n json = json.trim();\n if (json.startsWith(\"{\") && json.endsWith(\"}\")) {\n json = json.substring(1, json.length() - 1).trim();\n }\n List<String> segments = splitTopLevel(json);\n for (String seg : segments) {\n int colonIdx = seg.indexOf(':');\n if (colonIdx < 0) continue;\n String key = seg.substring(0, colonIdx).trim();\n String value = seg.substring(colonIdx + 1).trim();\n key = unquote(key);\n if (value.startsWith(\"\\\"\")) {\n result.put(key, unquote(value));\n } else if (value.startsWith(\"[\")) {\n result.put(key, parseArray(value));\n } else if (value.startsWith(\"{\")) {\n result.put(key, parseSimpleJson(value));\n } else if (value.equals(\"null\")) {\n result.put(key, null);\n } else {\n try {\n if (value.contains(\".\")) {\n result.put(key, new BigDecimal(value));\n } else {\n result.put(key, Long.parseLong(value));\n }\n } catch (NumberFormatException e) {\n result.put(key, value);\n }\n }\n }\n return result;\n }\n\n private List<Map<String, Object>> parseArray(String arrayStr) {\n List<Map<String, Object>> list = new ArrayList<>();\n arrayStr = arrayStr.trim();\n if (arrayStr.startsWith(\"[\") && arrayStr.endsWith(\"]\")) {\n arrayStr = arrayStr.substring(1, arrayStr.length() - 1).trim();\n }\n int braceDepth = 0;\n int start = 0;\n for (int i = 0; i < arrayStr.length(); i++) {\n char c = arrayStr.charAt(i);\n if (c == '{') braceDepth++;\n else if (c == '}') braceDepth--;\n else if (c == ',' && braceDepth == 0) {\n String item = arrayStr.substring(start, i).trim();\n if (!item.isEmpty()) list.add(parseSimpleJson(item));\n start = i + 1;\n }\n }\n String last = arrayStr.substring(start).trim();\n if (!last.isEmpty()) list.add(parseSimpleJson(last));\n return list;\n }\n\n private List<String> splitTopLevel(String s) {\n List<String> parts = new ArrayList<>();\n int depth = 0, bracketDepth = 0;\n boolean inString = false;\n int start = 0;\n for (int i = 0; i < s.length(); i++) {\n char c = s.charAt(i);\n if (c == '\"' && (i == 0 || s.charAt(i - 1) != '\\\\')) inString = !inString;\n else if (!inString) {\n if (c == '{') depth++;\n else if (c == '}') depth--;\n else if (c == '[') bracketDepth++;\n else if (c == ']') bracketDepth--;\n else if (c == ',' && depth == 0 && bracketDepth == 0) {\n parts.add(s.substring(start, i));\n start = i + 1;\n }\n }\n }\n String last = s.substring(start).trim();\n if (!last.isEmpty()) parts.add(last);\n return parts;\n }\n\n private String unquote(String s) {\n s = s.trim();\n if (s.startsWith(\"\\\"\") && s.endsWith(\"\\\"\")) {\n return s.substring(1, s.length() - 1);\n }\n return s;\n }\n\n private BigDecimal toBigDecimal(Object obj) {\n if (obj == null) return null;\n if (obj instanceof BigDecimal) return (BigDecimal) obj;\n if (obj instanceof Number) return BigDecimal.valueOf(((Number) obj).doubleValue());\n if (obj instanceof String) {\n try { return new BigDecimal((String) obj); }\n catch (NumberFormatException e) { return null; }\n }\n return null;\n }\n}[... 2662 more characters truncated]"}],"isError":false,"timestamp":1780019056403}}
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