From 373d7f8201dba67b9f167993766dbd5302847e59 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E9=99=88=E5=AD=90=E9=BB=98?= <925456043@qq.com> Date: Wed, 11 Mar 2026 20:33:04 +0800 Subject: [PATCH] =?UTF-8?q?perf:=20=E6=A8=A1=E5=9E=8B=E7=AE=A1=E7=90=86?= =?UTF-8?q?=E7=95=8C=E9=9D=A2=E9=87=8D=E5=81=9A?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../admin/controller/ai/ModelController.java | 31 +- .../easyflow/ai/entity/base/ModelBase.java | 15 +- .../easyflow/ai/service/ModelService.java | 5 +- .../ai/service/impl/ModelServiceImpl.java | 13 +- .../src/main/resources/application-prod.yml | 4 +- .../app/public/model-providers/aliyun.png | Bin 0 -> 7399 bytes .../app/public/model-providers/deepseek.png | Bin 0 -> 8803 bytes .../app/public/model-providers/kimi.png | Bin 0 -> 7295 bytes .../app/public/model-providers/minimax.png | Bin 0 -> 1877 bytes .../app/public/model-providers/ollama.png | Bin 0 -> 1797 bytes .../app/public/model-providers/openai.ico | 1 + .../app/public/model-providers/openai.svg | 10 + .../public/model-providers/self-hosted.svg | 8 + .../public/model-providers/siliconflow.png | Bin 0 -> 583 bytes .../app/public/model-providers/zhipu.png | Bin 0 -> 2747 bytes easyflow-ui-admin/app/src/api/ai/llm.ts | 16 +- .../app/src/components/page/ListPageShell.vue | 14 +- .../page/__tests__/CardList.test.ts | 112 ++ .../app/src/locales/langs/en-US/llm.json | 1 - .../app/src/locales/langs/zh-CN/llm.json | 1 - .../views/ai/model/ActiveModelWorkspace.vue | 774 ++++++++ .../app/src/views/ai/model/AddModelModal.vue | 552 +++--- .../views/ai/model/AddModelProviderModal.vue | 470 +++-- .../src/views/ai/model/ManageModelModal.vue | 350 ---- .../app/src/views/ai/model/Model.vue | 1601 +++++++++++------ .../src/views/ai/model/ModelProviderBadge.vue | 155 ++ .../src/views/ai/model/ModelVerifyConfig.vue | 297 ++- .../views/ai/model/ModelViewItemOperation.vue | 452 +++-- .../modelUtils/__tests__/defaultIcon.test.ts | 17 + .../__tests__/providerDraft.test.ts | 67 + .../views/ai/model/modelUtils/defaultIcon.ts | 65 +- .../ai/model/modelUtils/providerDraft.ts | 72 + .../ai/model/modelUtils/providerList.json | 714 +++----- .../ui/authentication/__tests__/login.test.ts | 152 ++ sql/02-easyflow-v2.data.sql | 89 +- ...-easyflow-v2.p4-model-provider-refresh.sql | 81 + sql/initdb/02-easyflow-v2.data.sql | 89 +- 37 files changed, 4120 insertions(+), 2108 deletions(-) create mode 100644 easyflow-ui-admin/app/public/model-providers/aliyun.png create mode 100644 easyflow-ui-admin/app/public/model-providers/deepseek.png create mode 100644 easyflow-ui-admin/app/public/model-providers/kimi.png create mode 100644 easyflow-ui-admin/app/public/model-providers/minimax.png create mode 100644 easyflow-ui-admin/app/public/model-providers/ollama.png create mode 100644 easyflow-ui-admin/app/public/model-providers/openai.ico create mode 100644 easyflow-ui-admin/app/public/model-providers/openai.svg create mode 100644 easyflow-ui-admin/app/public/model-providers/self-hosted.svg create mode 100644 easyflow-ui-admin/app/public/model-providers/siliconflow.png create mode 100644 easyflow-ui-admin/app/public/model-providers/zhipu.png create mode 100644 easyflow-ui-admin/app/src/components/page/__tests__/CardList.test.ts create mode 100644 easyflow-ui-admin/app/src/views/ai/model/ActiveModelWorkspace.vue delete mode 100644 easyflow-ui-admin/app/src/views/ai/model/ManageModelModal.vue create mode 100644 easyflow-ui-admin/app/src/views/ai/model/ModelProviderBadge.vue create mode 100644 easyflow-ui-admin/app/src/views/ai/model/modelUtils/__tests__/defaultIcon.test.ts create mode 100644 easyflow-ui-admin/app/src/views/ai/model/modelUtils/__tests__/providerDraft.test.ts create mode 100644 easyflow-ui-admin/app/src/views/ai/model/modelUtils/providerDraft.ts create mode 100644 easyflow-ui-admin/packages/effects/common-ui/src/ui/authentication/__tests__/login.test.ts create mode 100644 sql/07-easyflow-v2.p4-model-provider-refresh.sql diff --git a/easyflow-api/easyflow-api-admin/src/main/java/tech/easyflow/admin/controller/ai/ModelController.java b/easyflow-api/easyflow-api-admin/src/main/java/tech/easyflow/admin/controller/ai/ModelController.java index 95b22da..6f248f3 100644 --- a/easyflow-api/easyflow-api-admin/src/main/java/tech/easyflow/admin/controller/ai/ModelController.java +++ b/easyflow-api/easyflow-api-admin/src/main/java/tech/easyflow/admin/controller/ai/ModelController.java @@ -92,13 +92,6 @@ public class ModelController extends BaseCurdController { return Result.ok(); } - @PostMapping("/updateByEntity") - @SaCheckPermission("/api/v1/model/save") - public Result updateByEntity(@RequestBody Model entity) { - modelService.updateByEntity(entity); - return Result.ok(); - } - @GetMapping("/selectLlmByProviderCategory") @SaCheckPermission("/api/v1/model/query") public Result>> selectLlmByProviderCategory(Model entity, String sortKey, String sortType) { @@ -129,19 +122,6 @@ public class ModelController extends BaseCurdController { } - /** - * 添加所有模型 - * - * @param entity - * @return - */ - @PostMapping("addAllLlm") - public Result addAllLlm(@JsonBody Model entity) { - QueryWrapper queryWrapper = QueryWrapper.create().eq(Model::getProviderId, entity.getProviderId()); - service.update(entity, queryWrapper); - return Result.ok(); - } - @GetMapping("/selectLlmList") @SaCheckPermission("/api/v1/model/query") public Result> selectLlmList(Model entity, Boolean asTree, String sortKey, String sortType) { @@ -154,15 +134,6 @@ public class ModelController extends BaseCurdController { return Result.ok(totalList); } - @Override - protected Result onSaveOrUpdateBefore(Model entity, boolean isSave) { - if (isSave) { - entity.setWithUsed(true); - } - return super.onSaveOrUpdateBefore(entity, isSave); - } - - @PostMapping("removeLlmByIds") @Transactional public Result removeLlm(@JsonBody(value = "id", required = true) Serializable id) { @@ -171,4 +142,4 @@ public class ModelController extends BaseCurdController { service.remove(queryWrapper); return Result.ok(); } -} \ No newline at end of file +} diff --git a/easyflow-modules/easyflow-module-ai/src/main/java/tech/easyflow/ai/entity/base/ModelBase.java b/easyflow-modules/easyflow-module-ai/src/main/java/tech/easyflow/ai/entity/base/ModelBase.java index 7547c62..a71e627 100644 --- a/easyflow-modules/easyflow-module-ai/src/main/java/tech/easyflow/ai/entity/base/ModelBase.java +++ b/easyflow-modules/easyflow-module-ai/src/main/java/tech/easyflow/ai/entity/base/ModelBase.java @@ -4,6 +4,7 @@ import com.mybatisflex.annotation.Column; import com.mybatisflex.annotation.Id; import com.mybatisflex.annotation.KeyType; import com.mybatisflex.core.handler.FastjsonTypeHandler; + import java.io.Serializable; import java.math.BigInteger; import java.util.Map; @@ -103,12 +104,6 @@ public class ModelBase implements Serializable { @Column(comment = "模型类型: chatModel/embeddingModel/rerankModel/orc..") private String modelType; - /** - * 是否使用 - */ - @Column(comment = "是否使用") - private Boolean withUsed; - /** * 是否支持推理 */ @@ -277,14 +272,6 @@ public class ModelBase implements Serializable { this.modelType = modelType; } - public Boolean getWithUsed() { - return withUsed; - } - - public void setWithUsed(Boolean withUsed) { - this.withUsed = withUsed; - } - public Boolean getSupportThinking() { return supportThinking; } diff --git a/easyflow-modules/easyflow-module-ai/src/main/java/tech/easyflow/ai/service/ModelService.java b/easyflow-modules/easyflow-module-ai/src/main/java/tech/easyflow/ai/service/ModelService.java index cc2368e..b9b1f2a 100644 --- a/easyflow-modules/easyflow-module-ai/src/main/java/tech/easyflow/ai/service/ModelService.java +++ b/easyflow-modules/easyflow-module-ai/src/main/java/tech/easyflow/ai/service/ModelService.java @@ -1,8 +1,7 @@ package tech.easyflow.ai.service; -import tech.easyflow.ai.entity.Model; import com.mybatisflex.core.service.IService; -import tech.easyflow.common.domain.Result; +import tech.easyflow.ai.entity.Model; import java.math.BigInteger; import java.util.List; @@ -25,6 +24,4 @@ public interface ModelService extends IService { void removeByEntity(Model entity); Model getModelInstance(BigInteger modelId); - - void updateByEntity(Model entity); } diff --git a/easyflow-modules/easyflow-module-ai/src/main/java/tech/easyflow/ai/service/impl/ModelServiceImpl.java b/easyflow-modules/easyflow-module-ai/src/main/java/tech/easyflow/ai/service/impl/ModelServiceImpl.java index 6f932ed..9a102b3 100644 --- a/easyflow-modules/easyflow-module-ai/src/main/java/tech/easyflow/ai/service/impl/ModelServiceImpl.java +++ b/easyflow-modules/easyflow-module-ai/src/main/java/tech/easyflow/ai/service/impl/ModelServiceImpl.java @@ -2,13 +2,13 @@ package tech.easyflow.ai.service.impl; import cn.hutool.core.util.StrUtil; +import com.alicp.jetcache.Cache; import com.easyagents.core.document.Document; import com.easyagents.core.model.chat.ChatModel; import com.easyagents.core.model.chat.ChatOptions; import com.easyagents.core.model.embedding.EmbeddingModel; import com.easyagents.core.model.rerank.RerankModel; import com.easyagents.core.store.VectorData; -import com.alicp.jetcache.Cache; import com.mybatisflex.core.query.QueryWrapper; import com.mybatisflex.spring.service.impl.ServiceImpl; import org.slf4j.Logger; @@ -21,7 +21,6 @@ import tech.easyflow.ai.entity.ModelProvider; import tech.easyflow.ai.mapper.ModelMapper; import tech.easyflow.ai.service.ModelProviderService; import tech.easyflow.ai.service.ModelService; -import tech.easyflow.common.domain.Result; import tech.easyflow.common.web.exceptions.BusinessException; import javax.annotation.Resource; @@ -92,7 +91,6 @@ public class ModelServiceImpl extends ServiceImpl implements QueryWrapper queryWrapper = new QueryWrapper() .eq(Model::getProviderId, entity.getProviderId()); - queryWrapper.eq(Model::getWithUsed, entity.getWithUsed()); List totalList = modelMapper.selectListWithRelationsByQuery(queryWrapper); for (String modelType : Model.MODEL_TYPES) { Map> groupMap = groupLlmByGroupName(totalList, modelType); @@ -212,13 +210,4 @@ public class ModelServiceImpl extends ServiceImpl implements return model; } - - @Override - public void updateByEntity(Model entity) { - QueryWrapper queryWrapper = QueryWrapper.create().eq(Model::getProviderId, entity.getProviderId()) - .eq(Model::getGroupName, entity.getGroupName()); - Model model = new Model(); - model.setWithUsed(entity.getWithUsed()); - modelMapper.updateByQuery(model, queryWrapper); - } } diff --git a/easyflow-starter/easyflow-starter-all/src/main/resources/application-prod.yml b/easyflow-starter/easyflow-starter-all/src/main/resources/application-prod.yml index 758c530..ec41fd3 100644 --- a/easyflow-starter/easyflow-starter-all/src/main/resources/application-prod.yml +++ b/easyflow-starter/easyflow-starter-all/src/main/resources/application-prod.yml @@ -3,9 +3,9 @@ spring: activate: on-profile: prod datasource: - url: jdbc:mysql://127.0.0.1:3306/easyflow?useInformationSchema=true&characterEncoding=utf-8 + url: jdbc:mysql://127.0.0.1:23306/easyflow?useInformationSchema=true&characterEncoding=utf-8 username: easyflow - password: 123456 + password: root data: redis: host: 127.0.0.1 diff --git a/easyflow-ui-admin/app/public/model-providers/aliyun.png b/easyflow-ui-admin/app/public/model-providers/aliyun.png new file mode 100644 index 0000000000000000000000000000000000000000..29fbfa6813e74ecd2aab527b125f57af8dacadfe GIT binary patch literal 7399 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+import {api} from '#/api/request.js'; // 获取LLM供应商 export async function getLlmProviderList() { return api.get('/api/v1/modelProvider/list'); } +export interface ModelListQuery { + modelType?: string; + providerId?: string; +} + +export async function getModelList(params: ModelListQuery = {}) { + return api.get('/api/v1/model/list', { params }); +} + // 保存LLM export async function saveLlm(data: string) { return api.post('/api/v1/model/save', data); @@ -20,6 +29,10 @@ export async function updateLlm(data: any) { return api.post(`/api/v1/model/update`, data); } +export async function verifyModelConfig(id: string) { + return api.get('/api/v1/model/verifyLlmConfig', { params: { id } }); +} + // 一键添加LLM export async function quickAddLlm(data: any) { return api.post(`/api/v1/model/quickAdd`, data); @@ -33,7 +46,6 @@ export interface llmType { providerName: string; providerType: string; }; - withUsed: boolean; llmModel: string; icon: string; description: string; diff --git a/easyflow-ui-admin/app/src/components/page/ListPageShell.vue b/easyflow-ui-admin/app/src/components/page/ListPageShell.vue index 3f2ccf7..1e62cd1 100644 --- a/easyflow-ui-admin/app/src/components/page/ListPageShell.vue +++ b/easyflow-ui-admin/app/src/components/page/ListPageShell.vue @@ -6,7 +6,7 @@ interface Props { contentPadding?: number | string; dense?: boolean; stickyToolbar?: boolean; - surface?: 'panel' | 'subtle'; + surface?: 'panel' | 'plain' | 'subtle'; } const props = withDefaults(defineProps(), { @@ -141,6 +141,18 @@ const contentStyle = computed((): CSSProperties => { box-shadow: none; } +.list-page-shell.is-plain .list-page-shell__content { + background: hsl(var(--surface-panel) / 0.96); + border: 1px solid hsl(var(--divider-faint) / 0.58); + border-radius: 20px; + box-shadow: none; + backdrop-filter: none; +} + +.list-page-shell.is-plain .list-page-shell__content::before { + display: none; +} + .list-page-shell__content::before { position: absolute; inset: 0 0 auto; diff --git a/easyflow-ui-admin/app/src/components/page/__tests__/CardList.test.ts b/easyflow-ui-admin/app/src/components/page/__tests__/CardList.test.ts new file mode 100644 index 0000000..ef6629c --- /dev/null +++ b/easyflow-ui-admin/app/src/components/page/__tests__/CardList.test.ts @@ -0,0 +1,112 @@ +import {mount} from '@vue/test-utils'; + +import {describe, expect, it, vi} from 'vitest'; +import CardList from '../CardList.vue'; + +const { hasAccessByCodes } = vi.hoisted(() => ({ + hasAccessByCodes: vi.fn((codes: string[]) => codes[0] !== 'blocked'), +})); + +vi.mock('@easyflow/access', () => ({ + useAccess: () => ({ + hasAccessByCodes, + }), +})); + +describe('CardList', () => { + function mountCardList(props: Record) { + return mount(CardList, { + props: { + data: [ + { + id: 'bot-1', + title: '演示卡片', + description: '用于验证主次交互是否正常工作', + }, + ], + defaultIcon: '/favicon.svg', + ...props, + }, + global: { + stubs: { + IconifyIcon: { + props: ['icon'], + template: '{{ icon }}', + }, + }, + }, + }); + } + + it('点击卡片空白区域时触发主动作', async () => { + const primaryAction = vi.fn(); + const wrapper = mountCardList({ + primaryAction: { + text: '进入设置', + onClick: primaryAction, + }, + }); + + await wrapper.get('.card-item').trigger('click'); + + expect(primaryAction).toHaveBeenCalledTimes(1); + expect(primaryAction).toHaveBeenCalledWith( + expect.objectContaining({ id: 'bot-1' }), + ); + }); + + it('点击次级按钮时不会冒泡触发主动作', async () => { + const primaryAction = vi.fn(); + const inlineAction = vi.fn(); + const wrapper = mountCardList({ + primaryAction: { + text: '进入设置', + onClick: primaryAction, + }, + actions: [ + { + text: '编辑', + placement: 'inline', + onClick: inlineAction, + }, + ], + }); + + await wrapper.get('.card-action-btn').trigger('click'); + + expect(inlineAction).toHaveBeenCalledTimes(1); + expect(primaryAction).not.toHaveBeenCalled(); + }); + + it('键盘 Enter 可以触发主动作', async () => { + const primaryAction = vi.fn(); + const wrapper = mountCardList({ + primaryAction: { + text: '进入设计', + onClick: primaryAction, + }, + }); + + await wrapper.get('.card-item').trigger('keydown.enter'); + + expect(primaryAction).toHaveBeenCalledTimes(1); + }); + + it('未提供主动作时保持旧卡片模式，不会把卡片变成可点击入口', async () => { + const legacyAction = vi.fn(); + const wrapper = mountCardList({ + actions: [ + { + text: '编辑', + onClick: legacyAction, + }, + ], + }); + + await wrapper.get('.card-item').trigger('click'); + await wrapper.get('.card-action-btn').trigger('click'); + + expect(wrapper.get('.card-item').attributes('role')).toBeUndefined(); + expect(legacyAction).toHaveBeenCalledTimes(1); + }); +}); diff --git a/easyflow-ui-admin/app/src/locales/langs/en-US/llm.json b/easyflow-ui-admin/app/src/locales/langs/en-US/llm.json index 3548087..659534f 100644 --- a/easyflow-ui-admin/app/src/locales/langs/en-US/llm.json +++ b/easyflow-ui-admin/app/src/locales/langs/en-US/llm.json @@ -58,7 +58,6 @@ "button": { "management": "Management", "test": "Test", - "addAllLlm": "Add models from the list", "RetrieveAgain": "Retrieve the model list again" }, "all": "All", diff --git a/easyflow-ui-admin/app/src/locales/langs/zh-CN/llm.json b/easyflow-ui-admin/app/src/locales/langs/zh-CN/llm.json index fe1febd..6f02d5e 100644 --- a/easyflow-ui-admin/app/src/locales/langs/zh-CN/llm.json +++ b/easyflow-ui-admin/app/src/locales/langs/zh-CN/llm.json @@ -55,7 +55,6 @@ "button": { "management": "管理", "test": "检测", - "addAllLlm": "添加列表中的所有模型", "RetrieveAgain": "重新获取模型列表" }, "all": "全部", diff --git a/easyflow-ui-admin/app/src/views/ai/model/ActiveModelWorkspace.vue b/easyflow-ui-admin/app/src/views/ai/model/ActiveModelWorkspace.vue new file mode 100644 index 0000000..6c9972f --- /dev/null +++ b/easyflow-ui-admin/app/src/views/ai/model/ActiveModelWorkspace.vue @@ -0,0 +1,774 @@ + + + + + diff --git a/easyflow-ui-admin/app/src/views/ai/model/AddModelModal.vue b/easyflow-ui-admin/app/src/views/ai/model/AddModelModal.vue index c8d627a..9207508 100644 --- a/easyflow-ui-admin/app/src/views/ai/model/AddModelModal.vue +++ b/easyflow-ui-admin/app/src/views/ai/model/AddModelModal.vue @@ -1,31 +1,31 @@ diff --git a/easyflow-ui-admin/app/src/views/ai/model/AddModelProviderModal.vue b/easyflow-ui-admin/app/src/views/ai/model/AddModelProviderModal.vue index f0dc272..5798675 100644 --- a/easyflow-ui-admin/app/src/views/ai/model/AddModelProviderModal.vue +++ b/easyflow-ui-admin/app/src/views/ai/model/AddModelProviderModal.vue @@ -1,41 +1,25 @@ diff --git a/easyflow-ui-admin/app/src/views/ai/model/ManageModelModal.vue b/easyflow-ui-admin/app/src/views/ai/model/ManageModelModal.vue deleted file mode 100644 index 4677552..0000000 --- a/easyflow-ui-admin/app/src/views/ai/model/ManageModelModal.vue +++ /dev/null @@ -1,350 +0,0 @@ - - - - - diff --git a/easyflow-ui-admin/app/src/views/ai/model/Model.vue b/easyflow-ui-admin/app/src/views/ai/model/Model.vue index ad7c714..eb0bc00 100644 --- a/easyflow-ui-admin/app/src/views/ai/model/Model.vue +++ b/easyflow-ui-admin/app/src/views/ai/model/Model.vue @@ -1,622 +1,1163 @@ - diff --git a/easyflow-ui-admin/app/src/views/ai/model/ModelProviderBadge.vue b/easyflow-ui-admin/app/src/views/ai/model/ModelProviderBadge.vue new file mode 100644 index 0000000..50afe15 --- /dev/null +++ b/easyflow-ui-admin/app/src/views/ai/model/ModelProviderBadge.vue @@ -0,0 +1,155 @@ + + + + + diff --git a/easyflow-ui-admin/app/src/views/ai/model/ModelVerifyConfig.vue b/easyflow-ui-admin/app/src/views/ai/model/ModelVerifyConfig.vue index ed11e36..c46f579 100644 --- a/easyflow-ui-admin/app/src/views/ai/model/ModelVerifyConfig.vue +++ b/easyflow-ui-admin/app/src/views/ai/model/ModelVerifyConfig.vue @@ -1,44 +1,61 @@ @@ -80,54 +120,147 @@ const getModelInfo = (id: string) => { :centered="true" :closable="!btnLoading" :title="$t('llm.verifyLlmTitle')" - width="482" + width="560" :confirm-loading="btnLoading" :confirm-text="$t('button.confirm')" :submitting="btnLoading" @confirm="save" > - - - - - - - - {{ vectorDimension }} - - +
+
+
+

1. 选择待验证模型

+

+ 会用当前保存的服务商配置发起一次真实请求，帮助你确认密钥和路径是否正确。 +

+
+ + + + + + + + +
+ +
+
+

2. 查看验证结果

+

成功后会返回可用状态；如果是向量模型，还会展示向量维度。

+
+ +
+
+ + +
+
+

{{ resultTitle }}

+

{{ verifyMessage }}

+
+ 向量维度：{{ vectorDimension }} +
+
+
+
+
diff --git a/easyflow-ui-admin/app/src/views/ai/model/ModelViewItemOperation.vue b/easyflow-ui-admin/app/src/views/ai/model/ModelViewItemOperation.vue index 157f7c2..566136c 100644 --- a/easyflow-ui-admin/app/src/views/ai/model/ModelViewItemOperation.vue +++ b/easyflow-ui-admin/app/src/views/ai/model/ModelViewItemOperation.vue @@ -1,201 +1,377 @@ diff --git a/easyflow-ui-admin/app/src/views/ai/model/modelUtils/__tests__/defaultIcon.test.ts b/easyflow-ui-admin/app/src/views/ai/model/modelUtils/__tests__/defaultIcon.test.ts new file mode 100644 index 0000000..2618973 --- /dev/null +++ b/easyflow-ui-admin/app/src/views/ai/model/modelUtils/__tests__/defaultIcon.test.ts @@ -0,0 +1,17 @@ +import {describe, expect, it} from 'vitest'; + +import {getProviderBadgeText, getProviderPresetByValue} from '../defaultIcon'; + +describe('defaultIcon helpers', () => { + it('可以读取新的服务商预设', () => { + const preset = getProviderPresetByValue('self-hosted'); + + expect(preset?.label).toBe('自部署'); + expect(preset?.mode).toBe('self-hosted'); + }); + + it('未知服务商类型会回退到 providerName 文本', () => { + expect(getProviderBadgeText('历史服务商', 'legacy')).toBe('历史'); + expect(getProviderBadgeText('', 'legacy-provider')).toBe('LE'); + }); +}); diff --git a/easyflow-ui-admin/app/src/views/ai/model/modelUtils/__tests__/providerDraft.test.ts b/easyflow-ui-admin/app/src/views/ai/model/modelUtils/__tests__/providerDraft.test.ts new file mode 100644 index 0000000..97458f6 --- /dev/null +++ b/easyflow-ui-admin/app/src/views/ai/model/modelUtils/__tests__/providerDraft.test.ts @@ -0,0 +1,67 @@ +import {describe, expect, it} from 'vitest'; + +import { + createProviderDraft, + getProviderConfigMetrics, + isProviderDraftDirty, +} from '../providerDraft'; + +describe('providerDraft helpers', () => { + it('相同配置不会被识别为脏数据', () => { + const provider = { + apiKey: 'key', + endpoint: 'https://api.example.com', + chatPath: '/v1/chat/completions', + embedPath: '/v1/embeddings', + rerankPath: '', + }; + + expect(isProviderDraftDirty(provider, createProviderDraft(provider))).toBe( + false, + ); + }); + + it('修改任一关键字段后会被识别为脏数据', () => { + const provider = { + apiKey: 'key', + endpoint: 'https://api.example.com', + chatPath: '/v1/chat/completions', + embedPath: '', + rerankPath: '', + }; + + expect( + isProviderDraftDirty(provider, { + ...createProviderDraft(provider), + apiKey: 'next-key', + }), + ).toBe(true); + }); + + it('会根据预设路径计算配置完成度', () => { + const metrics = getProviderConfigMetrics( + { + apiKey: 'key', + endpoint: 'https://api.example.com', + chatPath: '/v1/chat/completions', + embedPath: '/v1/embeddings', + rerankPath: '', + }, + { + label: '示例', + value: 'demo', + description: '', + icon: '', + mode: 'hosted', + options: { + chatPath: '/v1/chat/completions', + embedPath: '/v1/embeddings', + }, + }, + ); + + expect(metrics.completed).toBe(4); + expect(metrics.total).toBe(4); + expect(metrics.complete).toBe(true); + }); +}); diff --git a/easyflow-ui-admin/app/src/views/ai/model/modelUtils/defaultIcon.ts b/easyflow-ui-admin/app/src/views/ai/model/modelUtils/defaultIcon.ts index 34b42ba..0984990 100644 --- a/easyflow-ui-admin/app/src/views/ai/model/modelUtils/defaultIcon.ts +++ b/easyflow-ui-admin/app/src/views/ai/model/modelUtils/defaultIcon.ts @@ -1,27 +1,66 @@ -import { ref } from 'vue'; - import providerList from './providerList.json'; -const providerOptions = - ref>( - providerList, - ); +export interface ProviderModelPreset { + description: string; + label: string; + llmModel: string; + supportChat?: boolean; + supportEmbed?: boolean; + supportFunctionCalling?: boolean; + supportRerank?: boolean; +} + +export interface ProviderPreset { + description: string; + icon: string; + label: string; + mode: 'hosted' | 'self-hosted'; + options: { + chatPath?: string; + embedPath?: string; + llmEndpoint?: string; + modelList?: ProviderModelPreset[]; + rerankPath?: string; + }; + tags?: string[]; + value: string; +} + +const providerOptions = providerList as ProviderPreset[]; + +export const getProviderPresetByValue = (targetValue?: string) => + providerOptions.find((item) => item.value === targetValue); /** * 根据传入的value，返回对应的icon属性 * @param targetValue 要匹配的value值 * @returns 匹配到的icon字符串，未匹配到返回空字符串 */ -export const getIconByValue = (targetValue: string): string => { - const matchItem = providerOptions.value.find( - (item) => item.value === targetValue, - ); - - return matchItem?.icon || ''; -}; +export const getIconByValue = (targetValue: string): string => + getProviderPresetByValue(targetValue)?.icon || ''; export const isSvgString = (icon: any) => { if (typeof icon !== 'string') return false; // 简单判断：是否包含 SVG 根标签 return icon.trim().startsWith(''); }; + +export const getProviderBadgeText = ( + providerName?: string, + providerType?: string, +) => { + const preset = getProviderPresetByValue(providerType); + const source = providerName || preset?.label || providerType || 'AI'; + const ascii = source + .replaceAll(/[^a-z]/gi, '') + .slice(0, 2) + .toUpperCase(); + + if (ascii) { + return ascii; + } + + return source.replaceAll(/\s+/g, '').slice(0, 2).toUpperCase(); +}; + +export const providerPresets = providerOptions; diff --git a/easyflow-ui-admin/app/src/views/ai/model/modelUtils/providerDraft.ts b/easyflow-ui-admin/app/src/views/ai/model/modelUtils/providerDraft.ts new file mode 100644 index 0000000..907a309 --- /dev/null +++ b/easyflow-ui-admin/app/src/views/ai/model/modelUtils/providerDraft.ts @@ -0,0 +1,72 @@ +import type {ProviderPreset} from './defaultIcon'; + +export const PROVIDER_EDITABLE_FIELDS = [ + 'apiKey', + 'endpoint', + 'chatPath', + 'embedPath', + 'rerankPath', +] as const; + +export type ProviderEditableField = (typeof PROVIDER_EDITABLE_FIELDS)[number]; + +export interface ProviderDraft { + apiKey: string; + endpoint: string; + chatPath: string; + embedPath: string; + rerankPath: string; +} + +type ProviderLike = Partial> & { + providerType?: string; +}; + +export const createProviderDraft = ( + provider?: null | ProviderLike, +): ProviderDraft => ({ + apiKey: provider?.apiKey || '', + endpoint: provider?.endpoint || '', + chatPath: provider?.chatPath || '', + embedPath: provider?.embedPath || '', + rerankPath: provider?.rerankPath || '', +}); + +export const isProviderDraftDirty = ( + provider?: null | ProviderLike, + draft?: null | ProviderLike, +) => + PROVIDER_EDITABLE_FIELDS.some( + (field) => (provider?.[field] || '') !== (draft?.[field] || ''), + ); + +export const getProviderConfigMetrics = ( + provider?: null | ProviderLike, + preset?: ProviderPreset, +) => { + const requiredFields: ProviderEditableField[] = [ + 'apiKey', + 'endpoint', + 'chatPath', + ]; + + if (preset?.options?.embedPath || provider?.embedPath) { + requiredFields.push('embedPath'); + } + + if (preset?.options?.rerankPath || provider?.rerankPath) { + requiredFields.push('rerankPath'); + } + + const completed = requiredFields.filter((field) => + Boolean((provider?.[field] || '').trim()), + ).length; + const total = requiredFields.length; + + return { + completed, + total, + ratio: total === 0 ? 0 : Math.round((completed / total) * 100), + complete: total > 0 && completed === total, + }; +}; diff --git a/easyflow-ui-admin/app/src/views/ai/model/modelUtils/providerList.json b/easyflow-ui-admin/app/src/views/ai/model/modelUtils/providerList.json index 1c7b213..764fb76 100644 --- a/easyflow-ui-admin/app/src/views/ai/model/modelUtils/providerList.json +++ b/easyflow-ui-admin/app/src/views/ai/model/modelUtils/providerList.json @@ -2,576 +2,292 @@ { "label": "DeepSeek", "value": "deepseek", - "options":{ - "llmEndpoint":"https://api.deepseek.com", - "chatPath":"/chat/completions", - "modelList":[ + "description": "推理与代码能力表现稳定，适合对话、推理和工具调用场景。", + "tags": ["推理", "函数调用", "高性价比"], + "mode": "hosted", + "options": { + "llmEndpoint": "https://api.deepseek.com", + "chatPath": "/chat/completions", + "modelList": [ { - "llmModel":"deepseek-reasoner", - "supportChat":true, - "supportFunctionCalling":true, - "label":"DeepSeek-R1-0528", - "description":"DeepSeek-R1-0528 是一款强化学习（RL）驱动的推理模型，解决了模型中的重复性和可读性问题。在 RL 之前，DeepSeek-R1 引入了冷启动数据，进一步优化了推理性能。它在数学、代码和推理任务中与 OpenAI-o1 表现相当，并且通过精心设计的训练方法，提升了整体效果" + "llmModel": "deepseek-chat", + "supportChat": true, + "supportFunctionCalling": true, + "label": "DeepSeek-V3", + "description": "通用对话与代码任务表现均衡，适合作为默认大模型。" }, { - "llmModel":"deepseek-chat", - "supportChat":true, - "supportFunctionCalling":true, - "label":"DeepSeek-V3-0324", - "description":"新版 DeepSeek-V3 （DeepSeek-V3-0324）与之前的 DeepSeek-V3-1226 使用同样的 base 模型，仅改进了后训练方法。新版 V3 模型借鉴 DeepSeek-R1 模型训练过程中所使用的强化学习技术，大幅提高了在推理类任务上的表现水平，在数学、代码类相关评测集上取得了超过 GPT-4.5 的得分成绩。此外该模型在工具调用、角色扮演、问答闲聊等方面也得到了一定幅度的能力提升。" + "llmModel": "deepseek-reasoner", + "supportChat": true, + "supportFunctionCalling": true, + "label": "DeepSeek-R1", + "description": "面向复杂推理、数学和长链路分析场景。" } ] }, - "icon": "\n \n \n \n \n \n \n \n \n \n \n \n" - + "icon": "/model-providers/deepseek.png" }, { - "label": "Open AI", + "label": "OpenAI", "value": "openai", - "options":{ - "llmEndpoint":"https://api.openai.com", - "chatPath":"/v1/chat/completions", - "embedPath":"/v1/embeddings", - - "modelList":[ + "description": "标准 OpenAI 兼容接口，适合多模态、推理与通用对话场景。", + "tags": ["标准兼容", "多模态", "推理"], + "mode": "hosted", + "options": { + "llmEndpoint": "https://api.openai.com", + "chatPath": "/v1/chat/completions", + "embedPath": "/v1/embeddings", + "modelList": [ { - "llmModel":"o4-mini", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"o4-mini", - "description":"O4-mini 是OpenAi最新的小型 O 系列型号。它针对快速、有效的推理进行了优化，在编码和可视化任务中具有非常高效的性能。" + "llmModel": "o4-mini", + "supportChat": true, + "supportFunctionCalling": true, + "multimodal": true, + "label": "o4-mini", + "description": "适合推理和通用生产任务的轻量模型。" }, { - "llmModel":"o3", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"o3", - "description":"O3 是一个全面而强大的跨领域模型。它为数学、科学、编码和视觉推理任务设定了新标准。它还擅长技术写作和指导遵循。使用它来思考涉及跨文本、代码和图像分析的多步骤问题。" + "llmModel": "gpt-4.1", + "supportChat": true, + "supportFunctionCalling": true, + "multimodal": true, + "label": "GPT-4.1", + "description": "复杂任务和多模态理解的旗舰模型。" }, { - "llmModel":"o3-pro", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"o3-pro", - "description":"o 系列模型经过强化学习训练，在回答和执行复杂推理之前先思考。o3-pro 模型使用更多的计算来更深入地思考并始终提供更好的答案。" - }, - { - "llmModel":"o3-mini", - "supportChat":true, - "supportFunctionCalling":true, - "label":"o3-mini", - "description":"O3-mini 是OpenAi最新的小型推理模型，以与 O1-mini 相同的成本和延迟目标提供高智能。o3-mini 支持关键的开发人员功能，如结构化输出、函数调用和批处理 API。" - }, - { - "llmModel":"GPT-4.1", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"GPT-4.1", - "description":"GPT-4.1 是OpenAi用于复杂任务的旗舰模型。它非常适合跨领域解决问题。" - }, - { - "llmModel":"GPT-4o", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"GPT-4o", - "description":"GPT-4o（“o”代表“omni”）是OpenAi多功能、高智能的旗舰模型。它接受文本和图像输入，并生成文本输出（包括结构化输出）。它是大多数任务的最佳模型，也是 o 系列模型之外功能最强大的模型" - }, - { - "llmModel":"text-embedding-3-small", - "supportEmbed":true, - "label":"text-embedding-3-small", - "description":"text-embedding-3-small 是 ADA 嵌入模型的改进版，性能更高。嵌入是文本的数字表示形式，可用于度量两段文本之间的相关性。嵌入对于搜索、聚类、推荐、异常检测和分类任务非常有用" - }, - { - "llmModel":"text-embedding-3-large", - "supportEmbed":true, - "label":"text-embedding-3-large", - "description":"text-embedding-3-large 是OpenAi最强大的嵌入模型，适用于英语和非英语任务。嵌入是文本的数字表示形式，可用于度量两段文本之间的相关性。嵌入对于搜索、聚类、推荐、异常检测和分类任务非常有用。" - }, - { - "llmModel":"text-embedding-ada-002", - "supportEmbed":true, - "label":"text-embedding-ada-002", - "description":"text-embedding-ada-002 是 ADA 嵌入模型的改进版，性能更高。嵌入是文本的数字表示形式，可用于度量两段文本之间的相关性。嵌入对于搜索、聚类、推荐、异常检测和分类任务非常有用。" + "llmModel": "text-embedding-3-large", + "supportEmbed": true, + "label": "text-embedding-3-large", + "description": "高质量文本向量模型。" } - ] }, - "icon": "\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n" + "icon": "/model-providers/openai.svg" }, { "label": "阿里百炼", "value": "aliyun", - "options":{ - "llmEndpoint":"https://dashscope.aliyuncs.com", - "chatPath":"/compatible-mode/v1/chat/completions", - "embedPath":"/compatible-mode/v1/embeddings", - "rerankPath":"/api/v1/services/rerank/text-rerank/text-rerank", - "modelList":[ + "description": "兼容 OpenAI 的云端模型平台，覆盖对话、向量与 Rerank 能力。", + "tags": ["通义", "Embedding", "Rerank"], + "mode": "hosted", + "options": { + "llmEndpoint": "https://dashscope.aliyuncs.com", + "chatPath": "/compatible-mode/v1/chat/completions", + "embedPath": "/compatible-mode/v1/embeddings", + "rerankPath": "/api/v1/services/rerank/text-rerank/text-rerank", + "modelList": [ { - "llmModel":"qwen-plus", - "supportChat":true, - "supportFunctionCalling":true, - "label":"通义千问-Plus", - "description":"Qwen3系列Plus模型，实现思考模式和非思考模式的有效融合，可在对话中切换模式。推理能力显著超过QwQ、通用能力显著超过Qwen2.5-Plus，达到同规模业界SOTA水平。" - + "llmModel": "qwen-plus", + "supportChat": true, + "supportFunctionCalling": true, + "label": "通义千问 Plus", + "description": "适合通用问答、工具调用和企业应用集成。" }, { - "llmModel":"qwen-turbo", - "supportChat":true, - "supportFunctionCalling":true, - "label":"通义千问-Turbo", - "description":"Qwen3系列Turbo模型，实现思考模式和非思考模式的有效融合，可在对话中切换模式。推理能力以更小参数规模比肩QwQ-32B、通用能力显著超过Qwen2.5-Turbo，达到同规模业界SOTA水平。" + "llmModel": "qwen-max", + "supportChat": true, + "supportFunctionCalling": true, + "label": "通义千问 Max", + "description": "更强的综合能力与复杂任务处理能力。" }, { - "llmModel":"qwen-max", - "supportChat":true, - "supportFunctionCalling":true, - "label":"通义千问-Max", - "description":"通义千问2.5系列千亿级别超大规模语言模型，支持中文、英文等不同语言输入。随着模型的升级，qwen-max将滚动更新升级。" - }, - { - "llmModel":"deepseek-r1-distill-qwen-7b", - "supportChat":true, - "supportFunctionCalling":true, - "label":"DeepSeek-R1-Distill-Qwen-7B", - "description":"DeepSeek-R1-Distill-Qwen-7B是一个基于Qwen2.5-Math-7B的蒸馏大型语言模型，使用了 DeepSeek R1 的输出。" - }, - { - "llmModel":"deepseek-r1-distill-qwen-14b", - "supportChat":true, - "supportFunctionCalling":true, - "label":"DeepSeek-R1-Distill-Qwen-14B", - "description":"DeepSeek-R1-Distill-Qwen-14B是一个基于Qwen2.5-14B的蒸馏大型语言模型，使用了 DeepSeek R1 的输出。" - }, - { - "llmModel":"deepseek-r1-distill-qwen-32b", - "supportChat":true, - "supportFunctionCalling":true, - "label":"DeepSeek-R1-Distill-Qwen-32B", - "description":"DeepSeek-R1-Distill-Qwen-32B是一个基于Qwen2.5-32B的蒸馏大型语言模型，使用了 DeepSeek R1 的输出。" - }, - { - "llmModel":"qwen-vl-max", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"通义千问VL-Max", - "description":"通义千问VL-Max（qwen-vl-max），即通义千问超大规模视觉语言模型。相比增强版，再次提升视觉推理能力和指令遵循能力，提供更高的视觉感知和认知水平。在更多复杂任务上提供最佳的性能。" - }, - { - "llmModel":"qwen-vl-plus", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"通义千问VL-Plus", - "description":"通义千问VL-Plus（qwen-vl-plus），即通义千问大规模视觉语言模型增强版。大幅提升细节识别能力和文字识别能力，支持超百万像素分辨率和任意长宽比规格的图像。在广泛的视觉任务上提供卓越的性能。" - }, - { - "llmModel":"qvq-max", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"通义千问-QVQ-Max", - "description":"通义千问QVQ视觉推理模型，支持视觉输入及思维链输出，在数学、编程、视觉分析、创作以及通用任务上都表现了更强的能力。" - }, - { - "llmModel":"qvq-plus", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"通义千问-QVQ-Plus", - "description":"通义千问QVQ视觉推理模型增强版，支持视觉输入及思维链输出，在数学、编程、视觉分析、创作以及通用任务上都表现了更强的能力。" - }, - { - "llmModel":"text-embedding-v4", - "supportEmbed":true, - "label":"通用文本向量-v4", - "description":"通义实验室基于Qwen3训练的多语言文本统一向量模型，相较V3版本在文本检索、聚类、分类性能大幅提升；在MTEB多语言、中英、Code检索等评测任务上效果提升15%~40%；支持64~2048维用户自定义向量维度。" - }, - { - "llmModel":"text-embedding-v3", - "supportEmbed":true, - "label":"通用文本向量-v3", - "description":"通用文本向量，是通义实验室基于LLM底座的多语言文本统一向量模型，面向全球多个主流语种，提供高水准的向量服务，帮助开发者将文本数据快速转换为高质量的向量数据。" + "llmModel": "text-embedding-v4", + "supportEmbed": true, + "label": "text-embedding-v4", + "description": "支持多语言和可配置维度的文本向量模型。" } ] }, - "icon": "\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n" + "icon": "/model-providers/aliyun.png" }, { - "label": "火山引擎", - "value": "volcengine", - "options":{ - "llmEndpoint":"https://ark.cn-beijing.volces.com", - "chatPath":"/api/v3/chat/completions", - "embedPath":"/api/v3/embeddings", - "modelList":[ + "label": "智谱", + "value": "zhipu", + "description": "提供 OpenAI 兼容接入，适合中文场景、推理和视觉理解。", + "tags": ["GLM", "中文", "OpenAI 兼容"], + "mode": "hosted", + "options": { + "llmEndpoint": "https://open.bigmodel.cn", + "chatPath": "/api/paas/v4/chat/completions", + "embedPath": "/api/paas/v4/embeddings", + "modelList": [ { - "llmModel":"doubao-seed-1-6-250615", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"doubao-seed-1.6", - "description":"全新多模态深度思考模型，同时支持 thinking、non-thinking、auto三种思考模式。其中 non-thinking 模型对比 doubao-1-5-pro-32k-250115 模型大幅提升。" - + "llmModel": "glm-4.5", + "supportChat": true, + "supportFunctionCalling": true, + "label": "GLM-4.5", + "description": "适合复杂对话、知识问答和中文推理任务。" }, { - "llmModel":"doubao-seed-1-6-flash-250615", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"doubao-seed-1.6-flash", - "description":"有极致推理速度的多模态深度思考模型；同时支持文本和视觉理解。文本理解能力超过上一代 Lite 系列模型，视觉理解比肩友商 Pro 系列模型。" + "llmModel": "glm-4.5-air", + "supportChat": true, + "supportFunctionCalling": true, + "label": "GLM-4.5-Air", + "description": "更轻量的通用模型，适合低延迟场景。" }, { - "llmModel":"doubao-seed-1-6-thinking-250715", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"doubao-seed-1.6-thinking", - "description":"在思考能力上进行了大幅强化， 对比 doubao 1.5 代深度理解模型，在编程、数学、逻辑推理等基础能力上进一步提升， 支持视觉理解。" - }, - { - "llmModel":"deepseek-r1-250528", - "supportChat":true, - "supportFunctionCalling":true, - "label":"deepseek-r1", - "description":"deepseek-r1 在后训练阶段大规模使用了强化学习技术，在数学、代码、自然语言推理等任务上，能力比肩 OpenAI o1 正式版。" + "llmModel": "embedding-3", + "supportEmbed": true, + "label": "Embedding-3", + "description": "用于检索、召回和知识库向量化。" } ] }, - "icon": "\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n" + "icon": "/model-providers/zhipu.png" }, { - "label": "百度千帆", - "value": "baidu", - "options":{ - "llmEndpoint":"https://qianfan.baidubce.com", - "chatPath":"/v2/chat/completions", - "embedPath":"/v2/embeddings", - "rerankPath":"/v2/rerank", - "modelList":[ + "label": "MiniMax", + "value": "minimax", + "description": "面向长上下文和高吞吐推理任务的 OpenAI 兼容模型服务。", + "tags": ["长上下文", "OpenAI 兼容", "推理"], + "mode": "hosted", + "options": { + "llmEndpoint": "https://api.minimax.io", + "chatPath": "/v1/chat/completions", + "modelList": [ { - "llmModel":"ernie-x1-turbo-32k", - "supportChat":true, - "supportFunctionCalling":true, - "label":"ERNIE X1 Turbo", - "description":"核心定位：深度思考模型，具备更强的理解、规划、反思、进化能力。适用场景： 在中文知识问答、文学创作、文稿写作、日常对话、逻辑推理、复杂计算及工具调用等方面表现尤为出色。" - + "llmModel": "MiniMax-M2.5", + "supportChat": true, + "supportFunctionCalling": true, + "label": "MiniMax-M2.5", + "description": "适合需要长上下文和推理能力的复杂场景。" }, { - "llmModel":"ernie-4.5-turbo-128k", - "supportChat":true, - "supportFunctionCalling":true, - "label":"ERNIE 4.5 Turbo", - "description":"​核心定位：更好的满足多轮长历史对话处理、长文档理解问答任务。适用场景：​1)复杂语义理解：支持中文知识问答、文学创作，尤其擅长文档理解（如DocVQA任务）。 ​2)数学推理：在中文数学问题（CMath基准）表现突出。" - }, - { - "llmModel":"ernie-4.5-turbo-vl-32k", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"ERNIE 4.5 Turbo VL", - "description":"​核心定位：多模态基础模型，支持文本、图像跨模态输入与生成。​适用场景：结合图文生成营销文案、视频脚本设计等。" - }, - { - "llmModel":"deepseek-r1-250528", - "supportChat":true, - "supportFunctionCalling":true, - "label":"DeepSeek-R1", - "description":"核心定位：专业优化推理模型，聚焦数学与逻辑任务。 ​适用场景： ​复杂数学问题：如高等数学题求解、科学计算模拟。 ​逻辑拆解与规划：业务流程自动化、学术研究中的假设验证。 ​STEM领域应用：物理建模、金融量化分析等需高精度推理的场景。" + "llmModel": "MiniMax-M2.5-highspeed", + "supportChat": true, + "supportFunctionCalling": true, + "label": "MiniMax-M2.5-highspeed", + "description": "更高吞吐的快速对话与 Agent 场景。" } ] }, - "icon": "\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n" + "icon": "/model-providers/minimax.png" }, { - "label": "星火大模型", - "value": "spark", - "options":{ - "llmEndpoint":"https://spark-api-open.xf-yun.com", - "chatPath":"/v1/chat/completions", - "modelList":[ + "label": "Kimi", + "value": "kimi", + "description": "Moonshot 提供的长上下文对话模型，适合知识问答与通用助手场景。", + "tags": ["长上下文", "Moonshot", "对话"], + "mode": "hosted", + "options": { + "llmEndpoint": "https://api.moonshot.cn", + "chatPath": "/v1/chat/completions", + "modelList": [ { - "llmModel":"generalv3.5", - "supportChat":true, - "supportFunctionCalling":true, - "label":"Spark Max", - "description":"旗舰级大语言模型，具有千亿级参数，核心能力全面升级，具备更强的数学、中文、代码和多模态能力。适用数理计算、逻辑推理等对效果有更高要求的业务场景。" + "llmModel": "moonshot-v1-8k", + "supportChat": true, + "supportFunctionCalling": true, + "label": "moonshot-v1-8k", + "description": "低延迟通用对话模型。" }, { - "llmModel":"4.0Ultra", - "supportChat":true, - "supportFunctionCalling":true, - "label":"Spark4.0 Ultra", - "description":"最强大的大语言模型版本，文本生成、语言理解、知识问答、逻辑推理、数学能力等方面实现超越GPT4 Turbo，优化联网搜索链路，提供更精准回答。" + "llmModel": "moonshot-v1-128k", + "supportChat": true, + "supportFunctionCalling": true, + "label": "moonshot-v1-128k", + "description": "适合长文档理解和大上下文场景。" } ] }, - "icon": "\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n" - }, - { - "label": "Gitee", - "value": "gitee", - "options":{ - "llmEndpoint":"https://ai.gitee.com", - "chatPath":"/v1/chat/completions", - "embedPath":"/v1/embeddings", - "rerankPath":"/v1/rerank", - "modelList":[ - { - "llmModel":"kimi-k2-instruct", - "supportChat":true, - "supportFunctionCalling":true, - "label":"kimi-k2-instruct", - "description":"Kimi K2 是一个最先进的混合专家 (MoE) 语言模型，激活参数为 320 亿，总参数为 1 万亿。通过 Muon 优化器进行训练，Kimi K2 在前沿知识、推理和编码任务上表现出色，同时在智能体能力方面进行了精心优化" - - }, - { - "llmModel":"ERNIE-4.5-Turbo", - "supportChat":true, - "supportFunctionCalling":true, - "label":"ERNIE-4.5-Turbo", - "description":"文心4.5 Turbo在去幻觉、逻辑推理和代码能力等方面也有着明显增强。对比文心4.5，速度更快、价格更低。" - - }, - { - "llmModel":"ERNIE-X1-Turbo", - "supportChat":true, - "supportFunctionCalling":true, - "label":"ERNIE-X1-Turbo", - "description":"文心ERNIE X1 Turbo具备更长的思维链，更强的深度思考能力，进一步增强了多模态和工具调用能力，擅长文学创作、逻辑推理等" - - }, - { - "llmModel":"DeepSeek-R1", - "supportChat":true, - "supportFunctionCalling":true, - "label":"DeepSeek-R1", - "description":"DeepSeek-R1 是一款采用强化学习技术的推理模型，凭借少量标注数据大幅提升推理能力，性能媲美 OpenAI o1。" - - }, - { - "llmModel":"DeepSeek-V3", - "supportChat":true, - "supportFunctionCalling":true, - "label":"DeepSeek-V3", - "description":"DeepSeek-V3 是 685B 参数的高效 MoE 语言模型，性能优越，训练稳定，超越开源模型，并接近顶级闭源模型。" - - }, - { - "llmModel":"Qwen3-235B-A22B", - "supportChat":true, - "supportFunctionCalling":true, - "label":"Qwen3-235B-A22B", - "description":"Qwen3 是 Qwen 系列中的最新一代大型语言模型，提供了一系列密集型和混合专家（MoE）模型。基于在训练数据、模型架构和优化技术方面的广泛进步。" - - }, - { - "llmModel":"Qwen3-30B-A3B", - "supportChat":true, - "supportFunctionCalling":true, - "label":"Qwen3-30B-A3B", - "description":"Qwen3 是 Qwen 系列中的最新一代大型语言模型，提供了一系列密集型和混合专家（MoE）模型。基于在训练数据、模型架构和优化技术方面的广泛进步。" - - }, - { - "llmModel":"Qwen3-32B", - "supportChat":true, - "supportFunctionCalling":true, - "label":"Qwen3-32B", - "description":"Qwen3 是 Qwen 系列中的最新一代大型语言模型，提供了一系列密集型和混合专家（MoE）模型。基于在训练数据、模型架构和优化技术方面的广泛进步。" - - }, - { - "llmModel":"ERNIE-4.5-Turbo-VL", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"ERNIE-4.5-Turbo-VL", - "description":"文心一言大模型全新版本，图片理解、创作、翻译、代码等能力显著提升，首次支持32K上下文长度，首Token时延显著降低。" - - }, - { - "llmModel":"Qwen2.5-VL-32B-Instruct", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"Qwen2.5-VL-32B-Instruct", - "description":"Qwen2.5-VL-32B-Instruct 是一款拥有 320 亿参数、支持多图输入与复杂图文推理的大规模多模态指令微调模型。" - - }, - { - "llmModel":"InternVL3-78B", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"InternVL3-78B", - "description":"InternVL3-78B 是一款支持中英文、多图多轮对话的大规模多模态模型，具备超强图文理解、推理与生成能力，广泛适用于复杂 AI 应用场景。" - - }, - { - "llmModel":"InternVL3-38B", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"InternVL3-38B", - "description":"InternVL3-38B 是一款支持中英双语、多模态对话与图像理解的大规模视觉语言模型，具备强大的跨模态推理与视觉问答能力。" - }, - { - "llmModel":"Qwen3-Embedding-8B", - "supportEmbed":true, - "label":"Qwen3-Embedding-8B", - "description":"Qwen3‑Embedding‑8B 是 Qwen 系列推出的大规模嵌入模型，专注于生成高质量、多语言及代码向量，支持多种下游任务中的语义匹配与信息检索需求。" - }, - { - "llmModel":"Qwen3-Embedding-4B", - "supportEmbed":true, - "label":"Qwen3-Embedding-4B", - "description":"Qwen3-Embedding-4B 是由 Qwen 团队开发的一款高性能文本和代码嵌入模型，专为多语言、多模态任务设计，能够将文本和代码内容转换为语义丰富的向量表示。它广泛适用于语义搜索、跨语言检索、信息匹配、文本相似度分析等多种自然语言处理和代码理解场景。" - } - ] - }, - "icon": "\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n" + "icon": "/model-providers/kimi.png" }, { "label": "硅基流动", "value": "siliconlow", - "options":{ - "llmEndpoint":"https://api.siliconflow.cn", - "chatPath":"/v1/chat/completions", - "embedPath":"/v1/embeddings", - "rerankPath":"/v1/rerank", - "modelList":[ + "description": "聚合多家开源模型能力，适合快速接入主流开源生态。", + "tags": ["开源模型", "聚合平台", "Embeddings"], + "mode": "hosted", + "options": { + "llmEndpoint": "https://api.siliconflow.cn", + "chatPath": "/v1/chat/completions", + "embedPath": "/v1/embeddings", + "rerankPath": "/v1/rerank", + "modelList": [ { - "llmModel":"deepseek-ai/DeepSeek-R1", - "supportChat":true, - "supportFunctionCalling":true, - "label":"DeepSeek-R1", - "description":"DeepSeek-R1-0528 是一款强化学习（RL）驱动的推理模型，解决了模型中的重复性和可读性问题。在 RL 之前，DeepSeek-R1 引入了冷启动数据，进一步优化了推理性能。它在数学、代码和推理任务中与 OpenAI-o1 表现相当，并且通过精心设计的训练方法，提升了整体效果。" - + "llmModel": "deepseek-ai/DeepSeek-V3", + "supportChat": true, + "supportFunctionCalling": true, + "label": "DeepSeek-V3", + "description": "便于通过统一平台接入主流开源对话模型。" }, { - "llmModel":"deepseek-ai/DeepSeek-V3", - "supportChat":true, - "supportFunctionCalling":true, - "label":"DeepSeek-V3", - "description":"新版 DeepSeek-V3 （DeepSeek-V3-0324）与之前的 DeepSeek-V3-1226 使用同样的 base 模型，仅改进了后训练方法。新版 V3 模型借鉴 DeepSeek-R1 模型训练过程中所使用的强化学习技术，大幅提高了在推理类任务上的表现水平，在数学、代码类相关评测集上取得了超过 GPT-4.5 的得分成绩。此外该模型在工具调用、角色扮演、问答闲聊等方面也得到了一定幅度的能力提升。" - + "llmModel": "moonshotai/Kimi-K2-Instruct", + "supportChat": true, + "supportFunctionCalling": true, + "label": "Kimi-K2-Instruct", + "description": "适合代码和 Agent 型工作流场景。" }, { - "llmModel":"moonshotai/Kimi-K2-Instruct", - "supportChat":true, - "supportFunctionCalling":true, - "label":"Kimi-K2-Instruct", - "description":"Kimi K2 是一款具备超强代码和 Agent 能力的 MoE 架构基础模型，总参数 1T，激活参数 32B。在通用知识推理、编程、数学、Agent 等主要类别的基准性能测试中，K2 模型的性能超过其他主流开源模型" - - }, - { - "llmModel":"Tongyi-Zhiwen/QwenLong-L1-32B", - "supportChat":true, - "supportFunctionCalling":true, - "label":"QwenLong-L1-32B", - "description":"QwenLong-L1-32B 是首个使用强化学习训练的长上下文大型推理模型（LRM），专门针对长文本推理任务进行优化。该模型通过渐进式上下文扩展的强化学习框架，实现了从短上下文到长上下文的稳定迁移。在七个长上下文文档问答基准测试中，QwenLong-L1-32B 超越了 OpenAI-o3-mini 和 Qwen3-235B-A22B 等旗舰模型，性能可媲美 Claude-3.7-Sonnet-Thinking。该模型特别擅长数学推理、逻辑推理和多跳推理等复杂任务" - - }, - { - "llmModel":"Qwen/Qwen3-30B-A3B", - "supportChat":true, - "supportFunctionCalling":true, - "label":"Qwen3-30B-A3B", - "description":"Qwen3-30B-A3B 是通义千问系列的最新大语言模型，采用混合专家（MoE）架构，拥有 30.5B 总参数量和 3.3B 激活参数量。该模型独特地支持在思考模式（适用于复杂逻辑推理、数学和编程）和非思考模式（适用于高效的通用对话）之间无缝切换，显著增强了推理能力。模型在数学、代码生成和常识逻辑推理上表现优异，并在创意写作、角色扮演和多轮对话等方面展现出卓越的人类偏好对齐能力。此外，该模型支持 100 多种语言和方言，具备出色的多语言指令遵循和翻译能力" - - }, - { - "llmModel":"Qwen/Qwen3-32B", - "supportChat":true, - "supportFunctionCalling":true, - "label":"Qwen3-32B", - "description":"Qwen3-32B 是通义千问系列的最新大语言模型，拥有 32.8B 参数量。该模型独特地支持在思考模式（适用于复杂逻辑推理、数学和编程）和非思考模式（适用于高效的通用对话）之间无缝切换，显著增强了推理能力。模型在数学、代码生成和常识逻辑推理上表现优异，并在创意写作、角色扮演和多轮对话等方面展现出卓越的人类偏好对齐能力。此外，该模型支持 100 多种语言和方言，具备出色的多语言指令遵循和翻译能力" - - }, - { - "llmModel":"MiniMaxAI/MiniMax-M1-80k", - "supportChat":true, - "supportFunctionCalling":true, - "label":"MiniMax-M1-80k", - "description":"MiniMax-M1 是开源权重的大规模混合注意力推理模型，拥有 4560 亿参数，每个 Token 可激活约 459 亿参数。模型原生支持 100 万 Token 的超长上下文，并通过闪电注意力机制，在 10 万 Token 的生成任务中相比 DeepSeek R1 节省 75% 的浮点运算量。同时，MiniMax-M1 采用 MoE（混合专家）架构，结合 CISPO 算法与混合注意力设计的高效强化学习训练，在长输入推理与真实软件工程场景中实现了业界领先的性能。" - - }, - { - "llmModel":"THUDM/GLM-4.1V-9B-Thinking", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"GLM-4.1V-9B-Thinking", - "description":"GLM-4.1V-9B-Thinking 是由智谱 AI 和清华大学 KEG 实验室联合发布的一款开源视觉语言模型（VLM），专为处理复杂的多模态认知任务而设计。该模型基于 GLM-4-9B-0414 基础模型，通过引入“思维链”（Chain-of-Thought）推理机制和采用强化学习策略，显著提升了其跨模态的推理能力和稳定性。作为一个 9B 参数规模的轻量级模型，它在部署效率和性能之间取得了平衡，在 28 项权威评测基准中，有 18 项的表现持平甚至超越了 72B 参数规模的 Qwen-2.5-VL-72B。该模型不仅在图文理解、数学科学推理、视频理解等任务上表现卓越，还支持高达 4K 分辨率的图像和任意宽高比输入" - }, - { - "llmModel":"Qwen/Qwen2.5-VL-32B-Instruct", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"Qwen2.5-VL-32B-Instruct", - "description":"Qwen2.5-VL-32B-Instruct 是通义千问团队推出的多模态大模型，是 Qwen2.5-VL 系列的一部分。该模型不仅精通识别常见物体，还能分析图像中的文本、图表、图标、图形和布局。它可作为视觉智能体，能够推理并动态操控工具，具备使用电脑和手机的能力。此外，这个模型可以精确定位图像中的对象，并为发票、表格等生成结构化输出。相比前代模型 Qwen2-VL，该版本在数学和问题解决能力方面通过强化学习得到了进一步提升，响应风格也更符合人类偏好" - }, - { - "llmModel":"Qwen/Qwen2.5-VL-72B-Instruct", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"Qwen2.5-VL-72B-Instruct", - "description":"Qwen2.5-VL 是 Qwen2.5 系列中的视觉语言模型。该模型在多方面有显著提升：具备更强的视觉理解能力，能够识别常见物体、分析文本、图表和布局；作为视觉代理能够推理并动态指导工具使用；支持理解超过 1 小时的长视频并捕捉关键事件；能够通过生成边界框或点准确定位图像中的物体；支持生成结构化输出，尤其适用于发票、表格等扫描数据。模型在多项基准测试中表现出色，包括图像、视频和代理任务评测" - }, - { - "llmModel":"deepseek-ai/deepseek-vl2", - "supportChat":true, - "supportFunctionCalling":true, - "multimodal":true, - "label":"deepseek-vl2", - "description":"DeepSeek-VL2 是一个基于 DeepSeekMoE-27B 开发的混合专家（MoE）视觉语言模型，采用稀疏激活的 MoE 架构，在仅激活 4.5B 参数的情况下实现了卓越性能。该模型在视觉问答、光学字符识别、文档/表格/图表理解和视觉定位等多个任务中表现优异，与现有的开源稠密模型和基于 MoE 的模型相比，在使用相同或更少的激活参数的情况下，实现了具有竞争力的或最先进的性能表现" - }, - { - "llmModel":"Qwen/Qwen3-Embedding-8B", - "supportEmbed":true, - "label":"Qwen3-Embedding-8B", - "description":"Qwen3-Embedding-8B 是 Qwen3 嵌入模型系列的最新专有模型，专为文本嵌入和排序任务设计。该模型基于 Qwen3 系列的密集基础模型，具有 80 亿参数规模，支持长达 32K 的上下文长度，可生成最高 4096 维的嵌入向量。该模型继承了基础模型卓越的多语言能力，支持超过 100 种语言，具备长文本理解和推理能力。在 MTEB 多语言排行榜上排名第一（截至 2025 年 6 月 5 日，得分 70.58），在文本检索、代码检索、文本分类、文本聚类和双语挖掘等多项任务中表现出色。模型支持用户自定义输出维度（32 到 4096）和指令感知功能，可根据特定任务、语言或场景进行优化" - }, - { - "llmModel":"Qwen/Qwen3-Embedding-4B", - "supportEmbed":true, - "label":"Qwen3-Embedding-4B", - "description":"Qwen3-Embedding-4B 是 Qwen3 嵌入模型系列的最新专有模型，专为文本嵌入和排序任务设计。该模型基于 Qwen3 系列的密集基础模型，具有 40 亿参数规模，支持长达 32K 的上下文长度，可生成最高 2560 维的嵌入向量。模型继承了基础模型卓越的多语言能力，支持超过 100 种语言，具备长文本理解和推理能力。在 MTEB 多语言排行榜上表现卓越（得分 69.45），在文本检索、代码检索、文本分类、文本聚类和双语挖掘等多项任务中表现出色。模型支持用户自定义输出维度（32 到 2560）和指令感知功能，可根据特定任务、语言或场景进行优化，在效率和效果之间达到良好平衡" - }, - { - "llmModel":"BAAI/bge-m3", - "supportEmbed":true, - "label":"bge-m3", - "description":"BGE-M3 是一个多功能、多语言、多粒度的文本嵌入模型。它支持三种常见的检索功能：密集检索、多向量检索和稀疏检索。该模型可以处理超过100种语言，并且能够处理从短句到长达8192个词元的长文档等不同粒度的输入。BGE-M3在多语言和跨语言检索任务中表现出色，在 MIRACL 和 MKQA 等基准测试中取得了领先结果。它还具有处理长文档检索的能力，在 MLDR 和 NarritiveQA 等数据集上展现了优秀性能" - }, - { - "llmModel":"netease-youdao/bce-embedding-base_v1", - "supportEmbed":true, - "label":"bce-embedding-base_v1", - "description":"bce-embedding-base_v1 是由网易有道开发的双语和跨语言嵌入模型。该模型在中英文语义表示和检索任务中表现出色，尤其擅长跨语言场景。它是为检索增强生成（RAG）系统优化的，可以直接应用于教育、医疗、法律等多个领域。该模型不需要特定指令即可使用，能够高效地生成语义向量，为语义搜索和问答系统提供关键支持" + "llmModel": "BAAI/bge-m3", + "supportEmbed": true, + "label": "BAAI/bge-m3", + "description": "多语言检索与向量召回场景常用模型。" } - ] }, - "icon": "\n \n \n \n \n \n \n \n \n \n \n \n \n \n" + "icon": "/model-providers/siliconflow.png" }, { "label": "Ollama", "value": "ollama", - "options":{ - + "description": "本地部署和开发调试友好的模型运行环境，适合单机快速验证。", + "tags": ["本地开发", "轻量部署", "实验环境"], + "mode": "self-hosted", + "options": { + "llmEndpoint": "http://127.0.0.1:11434", + "chatPath": "/v1/chat/completions", + "embedPath": "/api/embed", + "modelList": [ + { + "llmModel": "qwen3:8b", + "supportChat": true, + "supportFunctionCalling": true, + "label": "qwen3:8b", + "description": "本地开发中常见的通用对话模型。" + }, + { + "llmModel": "bge-m3", + "supportEmbed": true, + "label": "bge-m3", + "description": "适合本地向量化和检索验证。" + } + ] }, - "icon": "\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n" + "icon": "/model-providers/ollama.png" + }, + { + "label": "自部署", + "value": "self-hosted", + "description": "统一承载 vLLM、SGLang 与其他 OpenAI 兼容网关的自部署入口。", + "tags": ["vLLM", "SGLang", "OpenAI 兼容"], + "mode": "self-hosted", + "options": { + "llmEndpoint": "http://127.0.0.1:8000", + "chatPath": "/v1/chat/completions", + "embedPath": "/v1/embeddings", + "rerankPath": "/v1/score", + "modelList": [ + { + "llmModel": "Qwen/Qwen3-32B", + "supportChat": true, + "supportFunctionCalling": true, + "label": "Qwen/Qwen3-32B", + "description": "适合自部署通用对话与工具调用。" + }, + { + "llmModel": "BAAI/bge-m3", + "supportEmbed": true, + "label": "BAAI/bge-m3", + "description": "适合自部署检索和知识库向量化。" + }, + { + "llmModel": "jinaai/jina-reranker-m0", + "supportRerank": true, + "label": "jinaai/jina-reranker-m0", + "description": "适合自部署重排和召回优化。" + } + ] + }, + "icon": "/model-providers/self-hosted.svg" } ] diff --git a/easyflow-ui-admin/packages/effects/common-ui/src/ui/authentication/__tests__/login.test.ts b/easyflow-ui-admin/packages/effects/common-ui/src/ui/authentication/__tests__/login.test.ts new file mode 100644 index 0000000..ae25abe --- /dev/null +++ b/easyflow-ui-admin/packages/effects/common-ui/src/ui/authentication/__tests__/login.test.ts @@ -0,0 +1,152 @@ +import {mount} from '@vue/test-utils'; +import {nextTick} from 'vue'; + +import {beforeEach, describe, expect, it, vi} from 'vitest'; +import AuthenticationLogin from '../login.vue'; + +const { formApi, routerPush } = vi.hoisted(() => ({ + formApi: { + getValues: vi.fn(), + setFieldValue: vi.fn(), + validate: vi.fn(), + }, + routerPush: vi.fn(), +})); + +vi.mock('vue-router', () => ({ + useRouter: () => ({ + push: routerPush, + }), +})); + +vi.mock('@easyflow/locales', () => ({ + $t: (key: string) => key, +})); + +vi.mock('@easyflow-core/form-ui', async () => { + const vue = await import('vue'); + + return { + useEasyFlowForm: () => [ + vue.defineComponent({ + name: 'MockEasyFlowForm', + setup() { + return () => vue.h('div', { class: 'mock-form' }); + }, + }), + formApi, + ], + }; +}); + +vi.mock('@easyflow-core/shadcn-ui', async (importOriginal) => { + const vue = await import('vue'); + const actual = await importOriginal(); + + return { + ...actual, + EasyFlowButton: vue.defineComponent({ + name: 'EasyFlowButton', + props: { + loading: { + default: false, + type: Boolean, + }, + }, + emits: ['click'], + setup(props, { attrs, emit, slots }) { + return () => + vue.h( + 'button', + { + ...attrs, + 'data-loading': String(props.loading), + type: 'button', + onClick: () => emit('click'), + }, + slots.default?.(), + ); + }, + }), + EasyFlowCheckbox: vue.defineComponent({ + name: 'EasyFlowCheckbox', + props: { + modelValue: { + default: false, + type: Boolean, + }, + name: { + default: '', + type: String, + }, + }, + emits: ['update:modelValue'], + setup(props, { emit, slots }) { + return () => + vue.h('label', [ + vue.h('input', { + checked: props.modelValue, + name: props.name, + type: 'checkbox', + onChange: (event: Event) => { + emit( + 'update:modelValue', + (event.target as HTMLInputElement).checked, + ); + }, + }), + slots.default?.(), + ]); + }, + }), + }; +}); + +describe('AuthenticationLogin', () => { + const rememberKey = `REMEMBER_ME_ACCOUNT_${location.hostname}`; + + beforeEach(() => { + localStorage.clear(); + vi.clearAllMocks(); + formApi.validate.mockResolvedValue({ valid: true }); + formApi.getValues.mockResolvedValue({ account: 'admin' }); + }); + + it('restores remembered account into the account field', async () => { + localStorage.setItem(rememberKey, 'remembered-user'); + + mount(AuthenticationLogin, { + props: { + formSchema: [], + }, + }); + + await nextTick(); + + expect(formApi.setFieldValue).toHaveBeenCalledWith( + 'account', + 'remembered-user', + ); + }); + + it('persists remembered account using the account field and renders overlay slot', async () => { + localStorage.setItem(rememberKey, 'remembered-user'); + + const wrapper = mount(AuthenticationLogin, { + props: { + formSchema: [], + showRememberMe: true, + }, + slots: { + overlay: '
', + }, + }); + + await nextTick(); + await wrapper.get('button').trigger('click'); + + expect(localStorage.getItem(rememberKey)).toBe('admin'); + expect(wrapper.emitted('submit')?.[0]).toEqual([{ account: 'admin' }]); + expect(wrapper.find('#captcha-box').exists()).toBe(true); + }); +}); diff --git a/sql/02-easyflow-v2.data.sql b/sql/02-easyflow-v2.data.sql index 22a759b..01959b3 100644 --- a/sql/02-easyflow-v2.data.sql +++ b/sql/02-easyflow-v2.data.sql @@ -176,66 +176,43 @@ INSERT INTO `tb_sys_role_menu` (`id`, `role_id`, `menu_id`) VALUES (365314364334 -- ---------------------------- -- Records of tb_model_provider -- ---------------------------- -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (358906187162456064, 'Gitee', 'gitee', '', '', 'https://ai.gitee.com', '/v1/chat/completions', '/v1/embeddings', '/v1/rerank', '2025-12-17 22:26:03', 1, '2025-12-17 22:26:03', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359109019710914560, '百度千帆', 'baidu', '', '', 'https://qianfan.baidubce.com', '/v2/chat/completions', '/v2/embeddings', '', '2025-12-18 11:52:02', 1, '2025-12-18 11:52:02', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359110565693620224, '火山引擎', 'volcengine', '', '', 'https://ark.cn-beijing.volces.com', '/api/v3/chat/completions', '/api/v3/embeddings', '', '2025-12-18 11:58:11', 1, '2025-12-18 11:58:11', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359110640402563072, '星火大模型', 'spark', '', '', 'https://spark-api-open.xf-yun.com', '/v1/chat/completions', NULL, '', '2025-12-18 11:58:29', 1, '2025-12-18 11:58:29', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359110667376132096, '硅基流动', 'siliconlow', '', '', 'https://api.siliconflow.cn', '/v1/chat/completions', '/v1/embeddings', '/v1/rerank', '2025-12-18 11:58:35', 1, '2025-12-18 11:58:35', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359110690079899648, 'Ollama', 'ollama', '', '', NULL, NULL, NULL, '', '2025-12-18 11:58:40', 1, '2025-12-18 11:58:40', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359111120310632448, 'DeepSeek', 'deepseek', '', '', 'https://api.deepseek.com', '/compatible-mode/v1/chat/completions', '/compatible-mode/v1/embeddings', '', '2025-12-18 12:00:23', 1, '2025-12-18 12:00:23', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359111228158771200, 'Open AI', 'openai', '', '', 'https://api.openai.com', '/v1/chat/completions', '/v1/embeddings', '', '2025-12-18 12:00:49', 1, '2025-12-18 12:00:49', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359111448204541952, '阿里百炼', 'aliyun', '', '', 'https://dashscope.aliyuncs.com', '/compatible-mode/v1/chat/completions', '/compatible-mode/v1/embeddings', '', '2025-12-18 12:01:41', 1, '2025-12-18 12:01:41', 1); +INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359110667376132096, '硅基流动', 'siliconlow', '', '', 'https://api.siliconflow.cn', '/v1/chat/completions', '/v1/embeddings', '/v1/rerank', '2026-03-10 10:00:00', 1, '2026-03-10 10:00:00', 1); +INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359110690079899648, 'Ollama', 'ollama', '', '', 'http://127.0.0.1:11434', '/v1/chat/completions', '/api/embed', '', '2026-03-10 10:00:00', 1, '2026-03-10 10:00:00', 1); +INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359111120310632448, 'DeepSeek', 'deepseek', '', '', 'https://api.deepseek.com', '/chat/completions', '', '', '2026-03-10 10:00:00', 1, '2026-03-10 10:00:00', 1); +INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359111228158771200, 'OpenAI', 'openai', '', '', 'https://api.openai.com', '/v1/chat/completions', '/v1/embeddings', '', '2026-03-10 10:00:00', 1, '2026-03-10 10:00:00', 1); 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+INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010007, 1, 1000000, 359111448204541952, '通义千问 Max', NULL, '综合能力更强的主力模型。', NULL, NULL, 'qwen-max', NULL, NULL, '{"llmEndpoint":"https://dashscope.aliyuncs.com","chatPath":"/compatible-mode/v1/chat/completions","embedPath":"/compatible-mode/v1/embeddings","rerankPath":"/api/v1/services/rerank/text-rerank/text-rerank"}', 'Qwen', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010008, 1, 1000000, 359111448204541952, 'text-embedding-v4', NULL, '阿里百炼默认向量模型。', NULL, NULL, 'text-embedding-v4', NULL, NULL, '{"llmEndpoint":"https://dashscope.aliyuncs.com","chatPath":"/compatible-mode/v1/chat/completions","embedPath":"/compatible-mode/v1/embeddings","rerankPath":"/api/v1/services/rerank/text-rerank/text-rerank"}', 'Embedding', 'embeddingModel', 1, 0, 0, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010009, 1, 1000000, 359111448204541952, 'gte-rerank-v2', NULL, '阿里百炼默认重排模型。', NULL, NULL, 'gte-rerank-v2', NULL, NULL, '{"llmEndpoint":"https://dashscope.aliyuncs.com","chatPath":"/compatible-mode/v1/chat/completions","embedPath":"/compatible-mode/v1/embeddings","rerankPath":"/api/v1/services/rerank/text-rerank/text-rerank"}', 'Rerank', 'rerankModel', 1, 0, 0, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010010, 1, 1000000, 366100000000000001, 'GLM-4.5', NULL, '中文与推理能力表现均衡。', NULL, NULL, 'glm-4.5', NULL, NULL, '{"llmEndpoint":"https://open.bigmodel.cn","chatPath":"/api/paas/v4/chat/completions","embedPath":"/api/paas/v4/embeddings","rerankPath":""}', 'GLM', 'chatModel', 1, 1, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010011, 1, 1000000, 366100000000000001, 'GLM-4.5-Air', NULL, '低延迟通用模型。', NULL, NULL, 'glm-4.5-air', NULL, NULL, '{"llmEndpoint":"https://open.bigmodel.cn","chatPath":"/api/paas/v4/chat/completions","embedPath":"/api/paas/v4/embeddings","rerankPath":""}', 'GLM', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010012, 1, 1000000, 366100000000000001, 'Embedding-3', NULL, '知识库与检索常用向量模型。', NULL, NULL, 'embedding-3', NULL, NULL, '{"llmEndpoint":"https://open.bigmodel.cn","chatPath":"/api/paas/v4/chat/completions","embedPath":"/api/paas/v4/embeddings","rerankPath":""}', 'Embedding', 'embeddingModel', 1, 0, 0, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010013, 1, 1000000, 366100000000000002, 'MiniMax-M2.5', NULL, '长上下文与复杂推理场景。', NULL, NULL, 'MiniMax-M2.5', NULL, NULL, '{"llmEndpoint":"https://api.minimax.io","chatPath":"/v1/chat/completions","embedPath":"","rerankPath":""}', 'MiniMax', 'chatModel', 1, 1, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010014, 1, 1000000, 366100000000000002, 'MiniMax-M2.5-highspeed', NULL, '更高吞吐的快速对话模型。', NULL, NULL, 'MiniMax-M2.5-highspeed', NULL, NULL, '{"llmEndpoint":"https://api.minimax.io","chatPath":"/v1/chat/completions","embedPath":"","rerankPath":""}', 'MiniMax', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010015, 1, 1000000, 366100000000000003, 'moonshot-v1-8k', NULL, '低延迟通用对话模型。', NULL, NULL, 'moonshot-v1-8k', NULL, NULL, '{"llmEndpoint":"https://api.moonshot.cn","chatPath":"/v1/chat/completions","embedPath":"","rerankPath":""}', 'Kimi', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010016, 1, 1000000, 366100000000000003, 'moonshot-v1-128k', NULL, '长文档理解与大上下文任务。', NULL, NULL, 'moonshot-v1-128k', NULL, NULL, '{"llmEndpoint":"https://api.moonshot.cn","chatPath":"/v1/chat/completions","embedPath":"","rerankPath":""}', 'Kimi', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010017, 1, 1000000, 359110667376132096, 'DeepSeek-V3', NULL, '统一平台接入的开源对话模型。', NULL, NULL, 'deepseek-ai/DeepSeek-V3', NULL, NULL, '{"llmEndpoint":"https://api.siliconflow.cn","chatPath":"/v1/chat/completions","embedPath":"/v1/embeddings","rerankPath":"/v1/rerank"}', 'DeepSeek', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010018, 1, 1000000, 359110667376132096, 'Kimi-K2-Instruct', NULL, '代码与 Agent 工作流场景常用模型。', NULL, NULL, 'moonshotai/Kimi-K2-Instruct', NULL, NULL, '{"llmEndpoint":"https://api.siliconflow.cn","chatPath":"/v1/chat/completions","embedPath":"/v1/embeddings","rerankPath":"/v1/rerank"}', 'Kimi', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010019, 1, 1000000, 359110667376132096, 'BAAI/bge-m3', NULL, '多语言检索与向量召回模型。', NULL, NULL, 'BAAI/bge-m3', NULL, NULL, '{"llmEndpoint":"https://api.siliconflow.cn","chatPath":"/v1/chat/completions","embedPath":"/v1/embeddings","rerankPath":"/v1/rerank"}', 'Embedding', 'embeddingModel', 1, 0, 0, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010020, 1, 1000000, 359110690079899648, 'qwen3:8b', NULL, '本地开发常用的通用对话模型。', NULL, NULL, 'qwen3:8b', NULL, NULL, '{"llmEndpoint":"http://127.0.0.1:11434","chatPath":"/v1/chat/completions","embedPath":"/api/embed","rerankPath":""}', 'Ollama', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010021, 1, 1000000, 359110690079899648, 'bge-m3', NULL, '本地向量化与检索验证。', NULL, NULL, 'bge-m3', NULL, NULL, '{"llmEndpoint":"http://127.0.0.1:11434","chatPath":"/v1/chat/completions","embedPath":"/api/embed","rerankPath":""}', 'Embedding', 'embeddingModel', 1, 0, 0, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010022, 1, 1000000, 366100000000000004, 'Qwen/Qwen3-32B', NULL, '适合自部署对话与工具调用。', NULL, NULL, 'Qwen/Qwen3-32B', NULL, NULL, '{"llmEndpoint":"http://127.0.0.1:8000","chatPath":"/v1/chat/completions","embedPath":"/v1/embeddings","rerankPath":"/v1/score"}', 'Qwen', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010023, 1, 1000000, 366100000000000004, 'BAAI/bge-m3', NULL, '自部署检索和知识库向量化。', NULL, NULL, 'BAAI/bge-m3', NULL, NULL, '{"llmEndpoint":"http://127.0.0.1:8000","chatPath":"/v1/chat/completions","embedPath":"/v1/embeddings","rerankPath":"/v1/score"}', 'Embedding', 'embeddingModel', 1, 0, 0, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010024, 1, 1000000, 366100000000000004, 'jinaai/jina-reranker-m0', NULL, '自部署召回重排模型。', NULL, NULL, 'jinaai/jina-reranker-m0', NULL, NULL, '{"llmEndpoint":"http://127.0.0.1:8000","chatPath":"/v1/chat/completions","embedPath":"/v1/embeddings","rerankPath":"/v1/score"}', 'Rerank', 'rerankModel', 1, 0, 0, NULL, NULL, NULL, NULL, 0); -- ---------------------------- -- Records of tb_sys_option diff --git a/sql/07-easyflow-v2.p4-model-provider-refresh.sql b/sql/07-easyflow-v2.p4-model-provider-refresh.sql new file mode 100644 index 0000000..13fc921 --- /dev/null +++ b/sql/07-easyflow-v2.p4-model-provider-refresh.sql @@ -0,0 +1,81 @@ +-- 模型服务商集合刷新脚本 +-- 用途： +-- 1. 清理已下线的旧服务商及其关联模型（星火、火山、千帆、Gitee） +-- 2. 对保留服务商做默认路径对齐 +-- 3. 补齐新的服务商预设（智谱、MiniMax、Kimi、自部署） + +START TRANSACTION; + +DELETE m +FROM tb_model AS m +INNER JOIN tb_model_provider AS p ON p.id = m.provider_id +WHERE p.provider_type IN ('gitee', 'baidu', 'volcengine', 'spark'); + +DELETE FROM tb_model_provider +WHERE provider_type IN ('gitee', 'baidu', 'volcengine', 'spark'); + +UPDATE tb_model_provider +SET provider_name = 'DeepSeek', + endpoint = 'https://api.deepseek.com', + chat_path = '/chat/completions', + embed_path = '', + rerank_path = '' +WHERE provider_type = 'deepseek'; + +UPDATE tb_model_provider +SET provider_name = 'OpenAI', + endpoint = 'https://api.openai.com', + chat_path = '/v1/chat/completions', + embed_path = '/v1/embeddings', + rerank_path = '' +WHERE provider_type = 'openai'; + +UPDATE tb_model_provider +SET provider_name = '阿里百炼', + endpoint = 'https://dashscope.aliyuncs.com', + chat_path = '/compatible-mode/v1/chat/completions', + embed_path = '/compatible-mode/v1/embeddings', + rerank_path = '/api/v1/services/rerank/text-rerank/text-rerank' +WHERE provider_type = 'aliyun'; + +UPDATE tb_model_provider +SET provider_name = '硅基流动', + endpoint = 'https://api.siliconflow.cn', + chat_path = '/v1/chat/completions', + embed_path = '/v1/embeddings', + rerank_path = '/v1/rerank' +WHERE provider_type = 'siliconlow'; + +UPDATE tb_model_provider +SET provider_name = 'Ollama', + endpoint = 'http://127.0.0.1:11434', + chat_path = '/v1/chat/completions', + embed_path = '/api/embed', + rerank_path = '' +WHERE provider_type = 'ollama'; + +INSERT INTO tb_model_provider (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) +SELECT 366100000000000001, '智谱', 'zhipu', '', '', 'https://open.bigmodel.cn', '/api/paas/v4/chat/completions', '/api/paas/v4/embeddings', '', NOW(), 1, NOW(), 1 +WHERE NOT EXISTS ( + SELECT 1 FROM tb_model_provider WHERE provider_type = 'zhipu' +); + +INSERT INTO tb_model_provider (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) +SELECT 366100000000000002, 'MiniMax', 'minimax', '', '', 'https://api.minimax.io', '/v1/chat/completions', '', '', NOW(), 1, NOW(), 1 +WHERE NOT EXISTS ( + SELECT 1 FROM tb_model_provider WHERE provider_type = 'minimax' +); + +INSERT INTO tb_model_provider (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) +SELECT 366100000000000003, 'Kimi', 'kimi', '', '', 'https://api.moonshot.cn', '/v1/chat/completions', '', '', NOW(), 1, NOW(), 1 +WHERE NOT EXISTS ( + SELECT 1 FROM tb_model_provider WHERE provider_type = 'kimi' +); + +INSERT INTO tb_model_provider (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) +SELECT 366100000000000004, '自部署', 'self-hosted', '', '', 'http://127.0.0.1:8000', '/v1/chat/completions', '/v1/embeddings', '/v1/score', NOW(), 1, NOW(), 1 +WHERE NOT EXISTS ( + SELECT 1 FROM tb_model_provider WHERE provider_type = 'self-hosted' +); + +COMMIT; diff --git a/sql/initdb/02-easyflow-v2.data.sql b/sql/initdb/02-easyflow-v2.data.sql index 22a759b..01959b3 100644 --- a/sql/initdb/02-easyflow-v2.data.sql +++ b/sql/initdb/02-easyflow-v2.data.sql @@ -176,66 +176,43 @@ INSERT INTO `tb_sys_role_menu` (`id`, `role_id`, `menu_id`) VALUES (365314364334 -- ---------------------------- -- Records of tb_model_provider -- ---------------------------- -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (358906187162456064, 'Gitee', 'gitee', '', '', 'https://ai.gitee.com', '/v1/chat/completions', '/v1/embeddings', '/v1/rerank', '2025-12-17 22:26:03', 1, '2025-12-17 22:26:03', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359109019710914560, '百度千帆', 'baidu', '', '', 'https://qianfan.baidubce.com', '/v2/chat/completions', '/v2/embeddings', '', '2025-12-18 11:52:02', 1, '2025-12-18 11:52:02', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359110565693620224, '火山引擎', 'volcengine', '', '', 'https://ark.cn-beijing.volces.com', '/api/v3/chat/completions', '/api/v3/embeddings', '', '2025-12-18 11:58:11', 1, '2025-12-18 11:58:11', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359110640402563072, '星火大模型', 'spark', '', '', 'https://spark-api-open.xf-yun.com', '/v1/chat/completions', NULL, '', '2025-12-18 11:58:29', 1, '2025-12-18 11:58:29', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359110667376132096, '硅基流动', 'siliconlow', '', '', 'https://api.siliconflow.cn', '/v1/chat/completions', '/v1/embeddings', '/v1/rerank', '2025-12-18 11:58:35', 1, '2025-12-18 11:58:35', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359110690079899648, 'Ollama', 'ollama', '', '', NULL, NULL, NULL, '', '2025-12-18 11:58:40', 1, '2025-12-18 11:58:40', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359111120310632448, 'DeepSeek', 'deepseek', '', '', 'https://api.deepseek.com', '/compatible-mode/v1/chat/completions', '/compatible-mode/v1/embeddings', '', '2025-12-18 12:00:23', 1, '2025-12-18 12:00:23', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359111228158771200, 'Open AI', 'openai', '', '', 'https://api.openai.com', '/v1/chat/completions', '/v1/embeddings', '', '2025-12-18 12:00:49', 1, '2025-12-18 12:00:49', 1); -INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359111448204541952, '阿里百炼', 'aliyun', '', '', 'https://dashscope.aliyuncs.com', '/compatible-mode/v1/chat/completions', '/compatible-mode/v1/embeddings', '', '2025-12-18 12:01:41', 1, '2025-12-18 12:01:41', 1); +INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359110667376132096, '硅基流动', 'siliconlow', '', '', 'https://api.siliconflow.cn', '/v1/chat/completions', '/v1/embeddings', '/v1/rerank', '2026-03-10 10:00:00', 1, '2026-03-10 10:00:00', 1); +INSERT INTO `tb_model_provider` (`id`, `provider_name`, `provider_type`, `icon`, `api_key`, `endpoint`, `chat_path`, `embed_path`, `rerank_path`, `created`, `created_by`, `modified`, `modified_by`) VALUES (359110690079899648, 'Ollama', 'ollama', '', '', 'http://127.0.0.1:11434', '/v1/chat/completions', '/api/embed', '', '2026-03-10 10:00:00', 1, '2026-03-10 10:00:00', 1); 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+INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010011, 1, 1000000, 366100000000000001, 'GLM-4.5-Air', NULL, '低延迟通用模型。', NULL, NULL, 'glm-4.5-air', NULL, NULL, '{"llmEndpoint":"https://open.bigmodel.cn","chatPath":"/api/paas/v4/chat/completions","embedPath":"/api/paas/v4/embeddings","rerankPath":""}', 'GLM', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010012, 1, 1000000, 366100000000000001, 'Embedding-3', NULL, '知识库与检索常用向量模型。', NULL, NULL, 'embedding-3', NULL, NULL, '{"llmEndpoint":"https://open.bigmodel.cn","chatPath":"/api/paas/v4/chat/completions","embedPath":"/api/paas/v4/embeddings","rerankPath":""}', 'Embedding', 'embeddingModel', 1, 0, 0, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010013, 1, 1000000, 366100000000000002, 'MiniMax-M2.5', NULL, '长上下文与复杂推理场景。', NULL, NULL, 'MiniMax-M2.5', NULL, NULL, '{"llmEndpoint":"https://api.minimax.io","chatPath":"/v1/chat/completions","embedPath":"","rerankPath":""}', 'MiniMax', 'chatModel', 1, 1, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010014, 1, 1000000, 366100000000000002, 'MiniMax-M2.5-highspeed', NULL, '更高吞吐的快速对话模型。', NULL, NULL, 'MiniMax-M2.5-highspeed', NULL, NULL, '{"llmEndpoint":"https://api.minimax.io","chatPath":"/v1/chat/completions","embedPath":"","rerankPath":""}', 'MiniMax', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010015, 1, 1000000, 366100000000000003, 'moonshot-v1-8k', NULL, '低延迟通用对话模型。', NULL, NULL, 'moonshot-v1-8k', NULL, NULL, '{"llmEndpoint":"https://api.moonshot.cn","chatPath":"/v1/chat/completions","embedPath":"","rerankPath":""}', 'Kimi', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010016, 1, 1000000, 366100000000000003, 'moonshot-v1-128k', NULL, '长文档理解与大上下文任务。', NULL, NULL, 'moonshot-v1-128k', NULL, NULL, '{"llmEndpoint":"https://api.moonshot.cn","chatPath":"/v1/chat/completions","embedPath":"","rerankPath":""}', 'Kimi', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010017, 1, 1000000, 359110667376132096, 'DeepSeek-V3', NULL, '统一平台接入的开源对话模型。', NULL, NULL, 'deepseek-ai/DeepSeek-V3', NULL, NULL, '{"llmEndpoint":"https://api.siliconflow.cn","chatPath":"/v1/chat/completions","embedPath":"/v1/embeddings","rerankPath":"/v1/rerank"}', 'DeepSeek', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010018, 1, 1000000, 359110667376132096, 'Kimi-K2-Instruct', NULL, '代码与 Agent 工作流场景常用模型。', NULL, NULL, 'moonshotai/Kimi-K2-Instruct', NULL, NULL, '{"llmEndpoint":"https://api.siliconflow.cn","chatPath":"/v1/chat/completions","embedPath":"/v1/embeddings","rerankPath":"/v1/rerank"}', 'Kimi', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010019, 1, 1000000, 359110667376132096, 'BAAI/bge-m3', NULL, '多语言检索与向量召回模型。', NULL, NULL, 'BAAI/bge-m3', NULL, NULL, '{"llmEndpoint":"https://api.siliconflow.cn","chatPath":"/v1/chat/completions","embedPath":"/v1/embeddings","rerankPath":"/v1/rerank"}', 'Embedding', 'embeddingModel', 1, 0, 0, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010020, 1, 1000000, 359110690079899648, 'qwen3:8b', NULL, '本地开发常用的通用对话模型。', NULL, NULL, 'qwen3:8b', NULL, NULL, '{"llmEndpoint":"http://127.0.0.1:11434","chatPath":"/v1/chat/completions","embedPath":"/api/embed","rerankPath":""}', 'Ollama', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010021, 1, 1000000, 359110690079899648, 'bge-m3', NULL, '本地向量化与检索验证。', NULL, NULL, 'bge-m3', NULL, NULL, '{"llmEndpoint":"http://127.0.0.1:11434","chatPath":"/v1/chat/completions","embedPath":"/api/embed","rerankPath":""}', 'Embedding', 'embeddingModel', 1, 0, 0, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010022, 1, 1000000, 366100000000000004, 'Qwen/Qwen3-32B', NULL, '适合自部署对话与工具调用。', NULL, NULL, 'Qwen/Qwen3-32B', NULL, NULL, '{"llmEndpoint":"http://127.0.0.1:8000","chatPath":"/v1/chat/completions","embedPath":"/v1/embeddings","rerankPath":"/v1/score"}', 'Qwen', 'chatModel', 1, 0, 1, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010023, 1, 1000000, 366100000000000004, 'BAAI/bge-m3', NULL, '自部署检索和知识库向量化。', NULL, NULL, 'BAAI/bge-m3', NULL, NULL, '{"llmEndpoint":"http://127.0.0.1:8000","chatPath":"/v1/chat/completions","embedPath":"/v1/embeddings","rerankPath":"/v1/score"}', 'Embedding', 'embeddingModel', 1, 0, 0, NULL, NULL, NULL, NULL, 0); +INSERT INTO `tb_model` (`id`, `dept_id`, `tenant_id`, `provider_id`, `title`, `icon`, `description`, `endpoint`, `request_path`, `model_name`, `api_key`, `extra_config`, `options`, `group_name`, `model_type`, `with_used`, `support_thinking`, `support_tool`, `support_image`, `support_image_b64_only`, `support_video`, `support_audio`, `support_free`) VALUES (366100000000010024, 1, 1000000, 366100000000000004, 'jinaai/jina-reranker-m0', NULL, '自部署召回重排模型。', NULL, NULL, 'jinaai/jina-reranker-m0', NULL, NULL, '{"llmEndpoint":"http://127.0.0.1:8000","chatPath":"/v1/chat/completions","embedPath":"/v1/embeddings","rerankPath":"/v1/score"}', 'Rerank', 'rerankModel', 1, 0, 0, NULL, NULL, NULL, NULL, 0); -- ---------------------------- -- Records of tb_sys_option