feat(X-Pack): add export Custom Prompt

backend/apps/chat/api/chat.py

@@ -14,6 +14,7 @@
 from apps.chat.models.chat_model import CreateChat, ChatRecord, RenameChat, ChatQuestion, AxisObj
 from apps.chat.task.llm import LLMService
 from common.core.deps import CurrentAssistant, SessionDep, CurrentUser, Trans
+from common.utils.data_format import DataFormat
 
 router = APIRouter(tags=["Data Q&A"], prefix="/chat")
 
@@ -245,9 +246,9 @@ async def export_excel(session: SessionDep, chat_record_id: int, trans: Trans):
 
     def inner():
 
-        data_list = LLMService.convert_large_numbers_in_object_array(_data + _predict_data)
+        data_list = DataFormat.convert_large_numbers_in_object_array(_data + _predict_data)
 
-        md_data, _fields_list = LLMService.convert_object_array_for_pandas(fields, data_list)
+        md_data, _fields_list = DataFormat.convert_object_array_for_pandas(fields, data_list)
 
         # data, _fields_list, col_formats = LLMService.format_pd_data(fields, _data + _predict_data)
 

backend/apps/chat/task/llm.py

@@ -45,6 +45,7 @@
 from common.core.db import engine
 from common.core.deps import CurrentAssistant, CurrentUser
 from common.error import SingleMessageError, SQLBotDBError, ParseSQLResultError, SQLBotDBConnectionError
+from common.utils.data_format import DataFormat
 from common.utils.utils import SQLBotLogUtil, extract_nested_json, prepare_for_orjson
 
 warnings.filterwarnings("ignore")
@@ -1039,7 +1040,7 @@ def run_task(self, in_chat: bool = True, stream: bool = True,
 
             result = self.execute_sql(sql=real_execute_sql)
 
-            _data = self.convert_large_numbers_in_object_array(result.get('data'))
+            _data = DataFormat.convert_large_numbers_in_object_array(result.get('data'))
             result["data"] = _data
 
             self.save_sql_data(session=_session, data_obj=result)
@@ -1057,15 +1058,15 @@ def run_task(self, in_chat: bool = True, stream: bool = True,
                         for field in result.get('fields'):
                             _column_list.append(AxisObj(name=field, value=field))
 
-                        md_data, _fields_list = self.convert_object_array_for_pandas(_column_list, result.get('data'))
+                        md_data, _fields_list = DataFormat.convert_object_array_for_pandas(_column_list, result.get('data'))
 
                         # data, _fields_list, col_formats = self.format_pd_data(_column_list, result.get('data'))
 
                         if not _data or not _fields_list:
                             yield 'The SQL execution result is empty.\n\n'
                         else:
                             df = pd.DataFrame(_data, columns=_fields_list)
-                            df_safe = self.safe_convert_to_string(df)
+                            df_safe = DataFormat.safe_convert_to_string(df)
                             markdown_table = df_safe.to_markdown(index=False)
                             yield markdown_table + '\n\n'
                 else:
@@ -1115,15 +1116,15 @@ def run_task(self, in_chat: bool = True, stream: bool = True,
                         _column_list.append(
                             AxisObj(name=field if not _fields.get(field) else _fields.get(field), value=field))
 
-                    md_data, _fields_list = self.convert_object_array_for_pandas(_column_list, result.get('data'))
+                    md_data, _fields_list = DataFormat.convert_object_array_for_pandas(_column_list, result.get('data'))
 
                     # data, _fields_list, col_formats = self.format_pd_data(_column_list, result.get('data'))
 
                     if not md_data or not _fields_list:
                         yield 'The SQL execution result is empty.\n\n'
                     else:
                         df = pd.DataFrame(md_data, columns=_fields_list)
-                        df_safe = self.safe_convert_to_string(df)
+                        df_safe = DataFormat.safe_convert_to_string(df)
                         markdown_table = df_safe.to_markdown(index=False)
                         yield markdown_table + '\n\n'
 
@@ -1176,120 +1177,7 @@ def run_task(self, in_chat: bool = True, stream: bool = True,
             self.finish(_session)
             session_maker.remove()
 
-    @staticmethod
-    def safe_convert_to_string(df):
-        df_copy = df.copy()
-
-        def format_value(x):
-            if pd.isna(x):
-                return ""
-
-            return "\u200b" + str(x)
-
-        for col in df_copy.columns:
-            df_copy[col] = df_copy[col].apply(format_value)
-
-        return df_copy
-
-    @staticmethod
-    def convert_large_numbers_in_object_array(obj_array, int_threshold=1e15, float_threshold=1e10):
-        """处理对象数组，将每个对象中的大数字转换为字符串"""
-
-        def format_float_without_scientific(value):
-            """格式化浮点数，避免科学记数法"""
-            if value == 0:
-                return "0"
-            formatted = f"{value:.15f}"
-            if '.' in formatted:
-                formatted = formatted.rstrip('0').rstrip('.')
-            return formatted
-
-        def process_object(obj):
-            """处理单个对象"""
-            if not isinstance(obj, dict):
-                return obj
-
-            processed_obj = {}
-            for key, value in obj.items():
-                if isinstance(value, (int, float)):
-                    # 只转换大数字
-                    if isinstance(value, int) and abs(value) >= int_threshold:
-                        processed_obj[key] = str(value)
-                    elif isinstance(value, float) and (abs(value) >= float_threshold or abs(value) < 1e-6):
-                        processed_obj[key] = format_float_without_scientific(value)
-                    else:
-                        processed_obj[key] = value
-                elif isinstance(value, dict):
-                    # 处理嵌套对象
-                    processed_obj[key] = process_object(value)
-                elif isinstance(value, list):
-                    # 处理对象中的数组
-                    processed_obj[key] = [process_item(item) for item in value]
-                else:
-                    processed_obj[key] = value
-            return processed_obj
-
-        def process_item(item):
-            """处理数组中的项目"""
-            if isinstance(item, dict):
-                return process_object(item)
-            return item
-
-        return [process_item(obj) for obj in obj_array]
 
-    @staticmethod
-    def convert_object_array_for_pandas(column_list: list, data_list: list):
-        _fields_list = []
-        for field_idx, field in enumerate(column_list):
-            _fields_list.append(field.name)
-
-        md_data = []
-        for inner_data in data_list:
-            _row = []
-            for field_idx, field in enumerate(column_list):
-                value = inner_data.get(field.value)
-                _row.append(value)
-            md_data.append(_row)
-        return md_data, _fields_list
-
-    @staticmethod
-    def format_pd_data(column_list: list, data_list: list, col_formats: dict = None):
-        # 预处理数据并记录每列的格式类型
-        # 格式类型：'text'（文本）、'number'（数字）、'default'（默认）
-        _fields_list = []
-
-        if col_formats is None:
-            col_formats = {}
-        for field_idx, field in enumerate(column_list):
-            _fields_list.append(field.name)
-            col_formats[field_idx] = 'default'  # 默认不特殊处理
-
-        data = []
-
-        for _data in data_list:
-            _row = []
-            for field_idx, field in enumerate(column_list):
-                value = _data.get(field.value)
-                if value is not None:
-                    # 检查是否为数字且需要特殊处理
-                    if isinstance(value, (int, float)):
-                        # 整数且超过15位 → 转字符串并标记为文本列
-                        if isinstance(value, int) and len(str(abs(value))) > 15:
-                            value = str(value)
-                            col_formats[field_idx] = 'text'
-                        # 小数且超过15位有效数字 → 转字符串并标记为文本列
-                        elif isinstance(value, float):
-                            decimal_str = format(value, '.16f').rstrip('0').rstrip('.')
-                            if len(decimal_str) > 15:
-                                value = str(value)
-                                col_formats[field_idx] = 'text'
-                        # 其他数字列标记为数字格式（避免科学记数法）
-                        elif col_formats[field_idx] != 'text':
-                            col_formats[field_idx] = 'number'
-                _row.append(value)
-            data.append(_row)
-
-        return data, _fields_list, col_formats
 
     def run_recommend_questions_task_async(self):
         self.future = executor.submit(self.run_recommend_questions_task_cache)

backend/apps/data_training/api/data_training.py

@@ -7,11 +7,11 @@
 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, get_all_data_training
 from apps.data_training.models.data_training_model import DataTrainingInfo
 from common.core.deps import SessionDep, CurrentUser, Trans
+from common.utils.data_format import DataFormat
 
 router = APIRouter(tags=["DataTraining"], prefix="/system/data-training")
 
@@ -53,9 +53,9 @@ async def enable(session: SessionDep, id: int, enabled: bool, trans: 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)")):
+                       question: Optional[str] = Query(None, description="搜索术语(可选)")):
     def inner():
-        _list = get_all_data_training(session, word, oid=current_user.oid)
+        _list = get_all_data_training(session, question, oid=current_user.oid)
 
         data_list = []
         for obj in _list:
@@ -75,7 +75,7 @@ def inner():
             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)
+        md_data, _fields_list = DataFormat.convert_object_array_for_pandas(fields, data_list)
 
         df = pd.DataFrame(md_data, columns=_fields_list)
 

backend/apps/terminology/api/terminology.py

@@ -7,11 +7,11 @@
 from fastapi.responses import StreamingResponse
 
 from apps.chat.models.chat_model import AxisObj
-from apps.chat.task.llm import LLMService
 from apps.terminology.curd.terminology import page_terminology, create_terminology, update_terminology, \
     delete_terminology, enable_terminology, get_all_terminology
 from apps.terminology.models.terminology_model import TerminologyInfo
 from common.core.deps import SessionDep, CurrentUser, Trans
+from common.utils.data_format import DataFormat
 
 router = APIRouter(tags=["Terminology"], prefix="/system/terminology")
 
@@ -62,8 +62,8 @@ def inner():
                 "word": obj.word,
                 "other_words": ', '.join(obj.other_words) if obj.other_words else '',
                 "description": obj.description,
-                "all_data_sources": 'Y' if obj.specific_ds else 'N',
-                "datasource": ', '.join(obj.datasource_names) if obj.datasource_names else '',
+                "all_data_sources": 'N' if obj.specific_ds else 'Y',
+                "datasource": ', '.join(obj.datasource_names) if obj.datasource_names and obj.specific_ds else '',
             }
             data_list.append(_data)
 
@@ -74,7 +74,7 @@ def inner():
         fields.append(AxisObj(name=trans('i18n_terminology.effective_data_sources'), value='datasource'))
         fields.append(AxisObj(name=trans('i18n_terminology.all_data_sources'), value='all_data_sources'))
 
-        md_data, _fields_list = LLMService.convert_object_array_for_pandas(fields, data_list)
+        md_data, _fields_list = DataFormat.convert_object_array_for_pandas(fields, data_list)
 
         df = pd.DataFrame(md_data, columns=_fields_list)
 

backend/common/utils/data_format.py

@@ -0,0 +1,117 @@
+import pandas as pd
+
+class DataFormat:
+    @staticmethod
+    def safe_convert_to_string(df):
+        df_copy = df.copy()
+
+        def format_value(x):
+            if pd.isna(x):
+                return ""
+
+            return "\u200b" + str(x)
+
+        for col in df_copy.columns:
+            df_copy[col] = df_copy[col].apply(format_value)
+
+        return df_copy
+
+    @staticmethod
+    def convert_large_numbers_in_object_array(obj_array, int_threshold=1e15, float_threshold=1e10):
+        """处理对象数组，将每个对象中的大数字转换为字符串"""
+
+        def format_float_without_scientific(value):
+            """格式化浮点数，避免科学记数法"""
+            if value == 0:
+                return "0"
+            formatted = f"{value:.15f}"
+            if '.' in formatted:
+                formatted = formatted.rstrip('0').rstrip('.')
+            return formatted
+
+        def process_object(obj):
+            """处理单个对象"""
+            if not isinstance(obj, dict):
+                return obj
+
+            processed_obj = {}
+            for key, value in obj.items():
+                if isinstance(value, (int, float)):
+                    # 只转换大数字
+                    if isinstance(value, int) and abs(value) >= int_threshold:
+                        processed_obj[key] = str(value)
+                    elif isinstance(value, float) and (abs(value) >= float_threshold or abs(value) < 1e-6):
+                        processed_obj[key] = format_float_without_scientific(value)
+                    else:
+                        processed_obj[key] = value
+                elif isinstance(value, dict):
+                    # 处理嵌套对象
+                    processed_obj[key] = process_object(value)
+                elif isinstance(value, list):
+                    # 处理对象中的数组
+                    processed_obj[key] = [process_item(item) for item in value]
+                else:
+                    processed_obj[key] = value
+            return processed_obj
+
+        def process_item(item):
+            """处理数组中的项目"""
+            if isinstance(item, dict):
+                return process_object(item)
+            return item
+
+        return [process_item(obj) for obj in obj_array]
+
+    @staticmethod
+    def convert_object_array_for_pandas(column_list: list, data_list: list):
+        _fields_list = []
+        for field_idx, field in enumerate(column_list):
+            _fields_list.append(field.name)
+
+        md_data = []
+        for inner_data in data_list:
+            _row = []
+            for field_idx, field in enumerate(column_list):
+                value = inner_data.get(field.value)
+                _row.append(value)
+            md_data.append(_row)
+        return md_data, _fields_list
+
+    @staticmethod
+    def format_pd_data(column_list: list, data_list: list, col_formats: dict = None):
+        # 预处理数据并记录每列的格式类型
+        # 格式类型：'text'（文本）、'number'（数字）、'default'（默认）
+        _fields_list = []
+
+        if col_formats is None:
+            col_formats = {}
+        for field_idx, field in enumerate(column_list):
+            _fields_list.append(field.name)
+            col_formats[field_idx] = 'default'  # 默认不特殊处理
+
+        data = []
+
+        for _data in data_list:
+            _row = []
+            for field_idx, field in enumerate(column_list):
+                value = _data.get(field.value)
+                if value is not None:
+                    # 检查是否为数字且需要特殊处理
+                    if isinstance(value, (int, float)):
+                        # 整数且超过15位 → 转字符串并标记为文本列
+                        if isinstance(value, int) and len(str(abs(value))) > 15:
+                            value = str(value)
+                            col_formats[field_idx] = 'text'
+                        # 小数且超过15位有效数字 → 转字符串并标记为文本列
+                        elif isinstance(value, float):
+                            decimal_str = format(value, '.16f').rstrip('0').rstrip('.')
+                            if len(decimal_str) > 15:
+                                value = str(value)
+                                col_formats[field_idx] = 'text'
+                        # 其他数字列标记为数字格式（避免科学记数法）
+                        elif col_formats[field_idx] != 'text':
+                            col_formats[field_idx] = 'number'
+                _row.append(value)
+            data.append(_row)
+
+        return data, _fields_list, col_formats

backend/locales/en.json

@@ -62,7 +62,11 @@
   },
   "i18n_custom_prompt": {
     "exists_in_db": "Template name already exists",
-    "not_exists": "This template does not exist"
+    "not_exists": "This template does not exist",
+    "prompt_word_name": "Prompt word name",
+    "prompt_word_content": "Prompt word content",
+    "effective_data_sources": "Effective Data Sources",
+    "all_data_sources": "All Data Sources"
   },
   "i18n_excel_export": {
     "data_is_empty": "Form data is empty, unable to export data"