diff --git a/backend/apps/data_training/api/data_training.py b/backend/apps/data_training/api/data_training.py index 540eaf84..58f4a1f9 100644 --- a/backend/apps/data_training/api/data_training.py +++ b/backend/apps/data_training/api/data_training.py @@ -1,9 +1,15 @@ +import asyncio +import io from typing import Optional +import pandas as pd from fastapi import APIRouter, Query +from fastapi.responses import StreamingResponse +from apps.chat.models.chat_model import AxisObj +from apps.chat.task.llm import LLMService from apps.data_training.curd.data_training import page_data_training, create_training, update_training, delete_training, \ - enable_training + enable_training, get_all_data_training from apps.data_training.models.data_training_model import DataTrainingInfo from common.core.deps import SessionDep, CurrentUser, Trans @@ -43,3 +49,44 @@ async def delete(session: SessionDep, id_list: list[int]): @router.get("/{id}/enable/{enabled}") async def enable(session: SessionDep, id: int, enabled: bool, trans: Trans): enable_training(session, id, enabled, trans) + + +@router.get("/export") +async def export_excel(session: SessionDep, trans: Trans, current_user: CurrentUser, + word: Optional[str] = Query(None, description="搜索术语(可选)")): + def inner(): + _list = get_all_data_training(session, word, oid=current_user.oid) + + data_list = [] + for obj in _list: + _data = { + "question": obj.question, + "description": obj.description, + "datasource_name": obj.datasource_name, + "advanced_application_name": obj.advanced_application_name, + } + data_list.append(_data) + + fields = [] + fields.append(AxisObj(name=trans('i18n_data_training.data_training'), value='question')) + fields.append(AxisObj(name=trans('i18n_data_training.problem_description'), value='description')) + fields.append(AxisObj(name=trans('i18n_data_training.effective_data_sources'), value='datasource_name')) + if current_user.oid == 1: + fields.append( + AxisObj(name=trans('i18n_data_training.advanced_application'), value='advanced_application_name')) + + md_data, _fields_list = LLMService.convert_object_array_for_pandas(fields, data_list) + + df = pd.DataFrame(md_data, columns=_fields_list) + + buffer = io.BytesIO() + + with pd.ExcelWriter(buffer, engine='xlsxwriter', + engine_kwargs={'options': {'strings_to_numbers': False}}) as writer: + df.to_excel(writer, sheet_name='Sheet1', index=False) + + buffer.seek(0) + return io.BytesIO(buffer.getvalue()) + + result = await asyncio.to_thread(inner) + return StreamingResponse(result, media_type="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet") diff --git a/backend/apps/data_training/curd/data_training.py b/backend/apps/data_training/curd/data_training.py index 011b7fdb..13291e56 100644 --- a/backend/apps/data_training/curd/data_training.py +++ b/backend/apps/data_training/curd/data_training.py @@ -18,42 +18,61 @@ from common.utils.embedding_threads import run_save_data_training_embeddings -def page_data_training(session: SessionDep, current_page: int = 1, page_size: int = 10, name: Optional[str] = None, - oid: Optional[int] = 1): - _list: List[DataTrainingInfoResult] = [] - - current_page = max(1, current_page) - page_size = max(10, page_size) - - total_count = 0 - total_pages = 0 - +def get_data_training_base_query(oid: int, name: Optional[str] = None): + """ + 获取数据训练查询的基础查询结构 + """ if name and name.strip() != "": keyword_pattern = f"%{name.strip()}%" parent_ids_subquery = ( select(DataTraining.id) - .where(and_(DataTraining.question.ilike(keyword_pattern), DataTraining.oid == oid)) # LIKE查询条件 + .where(and_(DataTraining.question.ilike(keyword_pattern), DataTraining.oid == oid)) ) else: parent_ids_subquery = ( select(DataTraining.id).where(and_(DataTraining.oid == oid)) ) + return parent_ids_subquery + + +def build_data_training_query(session: SessionDep, oid: int, name: Optional[str] = None, + paginate: bool = True, current_page: int = 1, page_size: int = 10): + """ + 构建数据训练查询的通用方法 + """ + parent_ids_subquery = get_data_training_base_query(oid, name) + + # 计算总数 count_stmt = select(func.count()).select_from(parent_ids_subquery.subquery()) total_count = session.execute(count_stmt).scalar() - total_pages = (total_count + page_size - 1) // page_size - if current_page > total_pages: + if paginate: + # 分页处理 + page_size = max(10, page_size) + total_pages = (total_count + page_size - 1) // page_size + current_page = max(1, min(current_page, total_pages)) if total_pages > 0 else 1 + + paginated_parent_ids = ( + parent_ids_subquery + .order_by(DataTraining.create_time.desc()) + .offset((current_page - 1) * page_size) + .limit(page_size) + .subquery() + ) + else: + # 不分页，获取所有数据 + total_pages = 1 current_page = 1 + page_size = total_count if total_count > 0 else 1 - paginated_parent_ids = ( - parent_ids_subquery - .order_by(DataTraining.create_time.desc()) - .offset((current_page - 1) * page_size) - .limit(page_size) - .subquery() - ) + paginated_parent_ids = ( + parent_ids_subquery + .order_by(DataTraining.create_time.desc()) + .subquery() + ) + # 构建主查询 stmt = ( select( DataTraining.id, @@ -74,6 +93,14 @@ def page_data_training(session: SessionDep, current_page: int = 1, page_size: in .order_by(DataTraining.create_time.desc()) ) + return stmt, total_count, total_pages, current_page, page_size + + +def execute_data_training_query(session: SessionDep, stmt) -> List[DataTrainingInfoResult]: + """ + 执行查询并返回数据训练信息列表 + """ + _list = [] result = session.execute(stmt) for row in result: @@ -90,9 +117,34 @@ def page_data_training(session: SessionDep, current_page: int = 1, page_size: in advanced_application_name=row.advanced_application_name, )) + return _list + + +def page_data_training(session: SessionDep, current_page: int = 1, page_size: int = 10, + name: Optional[str] = None, oid: Optional[int] = 1): + """ + 分页查询数据训练（原方法保持不变） + """ + stmt, total_count, total_pages, current_page, page_size = build_data_training_query( + session, oid, name, True, current_page, page_size + ) + _list = execute_data_training_query(session, stmt) + return current_page, page_size, total_count, total_pages, _list +def get_all_data_training(session: SessionDep, name: Optional[str] = None, oid: Optional[int] = 1): + """ + 获取所有数据训练（不分页） + """ + stmt, total_count, total_pages, current_page, page_size = build_data_training_query( + session, oid, name, False + ) + _list = execute_data_training_query(session, stmt) + + return _list + + def create_training(session: SessionDep, info: DataTrainingInfo, oid: int, trans: Trans): create_time = datetime.datetime.now() if info.datasource is None and info.advanced_application is None: diff --git a/backend/locales/en.json b/backend/locales/en.json index 131a5ec7..44cc60ed 100644 --- a/backend/locales/en.json +++ b/backend/locales/en.json @@ -53,7 +53,12 @@ "datasource_cannot_be_none": "Datasource cannot be empty", "datasource_assistant_cannot_be_none": "Datasource or advanced application cannot both be empty", "data_training_not_exists": "This example does not exist", - "exists_in_db": "This question already exists" + "exists_in_db": "This question already exists", + "data_training": "SQL Example Library", + "problem_description": "Problem Description", + "sample_sql": "Sample SQL", + "effective_data_sources": "Effective Data Sources", + "advanced_application": "Advanced Application" }, "i18n_custom_prompt": { "exists_in_db": "Template name already exists", diff --git a/backend/locales/ko-KR.json b/backend/locales/ko-KR.json index e7a06ba3..ce87967f 100644 --- a/backend/locales/ko-KR.json +++ b/backend/locales/ko-KR.json @@ -53,7 +53,12 @@ "datasource_cannot_be_none": "데이터 소스는 비울 수 없습니다", "datasource_assistant_cannot_be_none": "데이터 소스와 고급 애플리케이션을 모두 비울 수 없습니다", "data_training_not_exists": "이 예시가 존재하지 않습니다", - "exists_in_db": "이 질문이 이미 존재합니다" + "exists_in_db": "이 질문이 이미 존재합니다", + "data_training": "SQL 예시 라이브러리", + "problem_description": "문제 설명", + "sample_sql": "예시 SQL", + "effective_data_sources": "유효 데이터 소스", + "advanced_application": "고급 애플리케이션" }, "i18n_custom_prompt": { "exists_in_db": "템플릿 이름이 이미 존재합니다", diff --git a/backend/locales/zh-CN.json b/backend/locales/zh-CN.json index c2dbdcaf..1b057e0a 100644 --- a/backend/locales/zh-CN.json +++ b/backend/locales/zh-CN.json @@ -53,7 +53,12 @@ "datasource_cannot_be_none": "数据源不能为空", "datasource_assistant_cannot_be_none": "数据源或高级应用不能都为空", "data_training_not_exists": "该示例不存在", - "exists_in_db": "该问题已存在" + "exists_in_db": "该问题已存在", + "data_training": "SQL 示例库", + "problem_description": "问题描述", + "sample_sql": "示例 SQL", + "effective_data_sources": "生效数据源", + "advanced_application": "高级应用" }, "i18n_custom_prompt": { "exists_in_db": "模版名称已存在", diff --git a/frontend/src/api/training.ts b/frontend/src/api/training.ts index a4342145..ebc68e69 100644 --- a/frontend/src/api/training.ts +++ b/frontend/src/api/training.ts @@ -9,4 +9,10 @@ export const trainingApi = { deleteEmbedded: (params: any) => request.delete('/system/data-training', { data: params }), getOne: (id: any) => request.get(`/system/data-training/${id}`), enable: (id: any, enabled: any) => request.get(`/system/data-training/${id}/enable/${enabled}`), + export2Excel: (params: any) => + request.get(`/system/data-training/export`, { + params, + responseType: 'blob', + requestOptions: { customError: true }, + }), } diff --git a/frontend/src/i18n/en.json b/frontend/src/i18n/en.json index e12906dd..f0c0edcd 100644 --- a/frontend/src/i18n/en.json +++ b/frontend/src/i18n/en.json @@ -40,6 +40,7 @@ "training_data_items": "Do you want to delete the {msg} selected SQL Sample items?", "sql_statement": "SQL Statement", "edit_training_data": "Edit SQL Sample", + "all_236_terms": "Export all {msg} sample SQL records?", "sales_this_year": "Do you want to delete the SQL Sample: {msg}?" }, "professional": { diff --git a/frontend/src/i18n/ko-KR.json b/frontend/src/i18n/ko-KR.json index 342b47ba..09f19bbd 100644 --- a/frontend/src/i18n/ko-KR.json +++ b/frontend/src/i18n/ko-KR.json @@ -40,6 +40,7 @@ "training_data_items": "선택된 {msg}개의 예제 SQL을 삭제하시겠습니까?", "sql_statement": "SQL 문", "edit_training_data": "예제 SQL 편집", + "all_236_terms": "모든 {msg}개의 예시 SQL 기록을 내보내시겠습니까?", "sales_this_year": "예제 SQL을 삭제하시겠습니까: {msg}?" }, "professional": { diff --git a/frontend/src/i18n/zh-CN.json b/frontend/src/i18n/zh-CN.json index 4ffb3f58..e95b659b 100644 --- a/frontend/src/i18n/zh-CN.json +++ b/frontend/src/i18n/zh-CN.json @@ -40,6 +40,7 @@ "training_data_items": "是否删除选中的 {msg} 条示例 SQL？", "sql_statement": "SQL 语句", "edit_training_data": "编辑示例 SQL", + "all_236_terms": "是否导出全部 {msg} 条示例 SQL？", "sales_this_year": "是否删除示例 SQL：{msg}？" }, "professional": { diff --git a/frontend/src/views/system/training/index.vue b/frontend/src/views/system/training/index.vue index 381ee218..772e489a 100644 --- a/frontend/src/views/system/training/index.vue +++ b/frontend/src/views/system/training/index.vue @@ -85,46 +85,60 @@ const cancelDelete = () => { checkAll.value = false isIndeterminate.value = false } -const exportBatchUser = () => { - ElMessageBox.confirm( - t('professional.selected_2_terms_de', { msg: multipleSelectionAll.value.length }), - { - confirmButtonType: 'primary', - confirmButtonText: t('professional.export'), - cancelButtonText: t('common.cancel'), - customClass: 'confirm-no_icon', - autofocus: false, - } - ).then(() => { - trainingApi.deleteEmbedded(multipleSelectionAll.value.map((ele) => ele.id)).then(() => { - ElMessage({ - type: 'success', - message: t('dashboard.delete_success'), - }) - multipleSelectionAll.value = [] - search() - }) - }) -} -const exportAllUser = () => { - ElMessageBox.confirm(t('professional.all_236_terms', { msg: pageInfo.total }), { +const exportExcel = () => { + ElMessageBox.confirm(t('training.all_236_terms', { msg: pageInfo.total }), { confirmButtonType: 'primary', confirmButtonText: t('professional.export'), cancelButtonText: t('common.cancel'), customClass: 'confirm-no_icon', autofocus: false, }).then(() => { - trainingApi.deleteEmbedded(multipleSelectionAll.value.map((ele) => ele.id)).then(() => { - ElMessage({ - type: 'success', - message: t('dashboard.delete_success'), + searchLoading.value = true + trainingApi + .export2Excel(keywords.value ? { question: keywords.value } : {}) + .then((res) => { + const blob = new Blob([res], { + type: 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet', + }) + const link = document.createElement('a') + link.href = URL.createObjectURL(blob) + link.download = `${t('training.data_training')}.xlsx` + document.body.appendChild(link) + link.click() + document.body.removeChild(link) + }) + .catch(async (error) => { + if (error.response) { + try { + let text = await error.response.data.text() + try { + text = JSON.parse(text) + } finally { + ElMessage({ + message: text, + type: 'error', + showClose: true, + }) + } + } catch (e) { + console.error('Error processing error response:', e) + } + } else { + console.error('Other error:', error) + ElMessage({ + message: error, + type: 'error', + showClose: true, + }) + } + }) + .finally(() => { + searchLoading.value = false }) - multipleSelectionAll.value = [] - search() - }) }) } + const deleteBatchUser = () => { ElMessageBox.confirm( t('training.training_data_items', { msg: multipleSelectionAll.value.length }), @@ -363,20 +377,18 @@ const onRowFormClose = () => { - + + + {{ $t('professional.export_all') }} + + + + {{ $t('user.batch_import') }} +