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fix: prevent bigint data from displaying in scientific notation in MCP chat #397

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Merged
merged 1 commit into from
Nov 5, 2025
Merged

fix: prevent bigint data from displaying in scientific notation in MCP chat #397

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32 changes: 2 additions & 30 deletions backend/apps/chat/api/chat.py
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Original file line number Diff line number Diff line change
Expand Up @@ -206,42 +206,14 @@ def _err(_e: Exception):
@router.post("/excel/export")
async def export_excel(excel_data: ExcelData, trans: Trans):
def inner():
_fields_list = []
data = []

if not excel_data.data:
raise HTTPException(
status_code=500,
detail=trans("i18n_excel_export.data_is_empty")
)

# 预处理数据并记录每列的格式类型
col_formats = {} # 格式类型：'text'（文本）、'number'（数字）、'default'（默认）
for field_idx, field in enumerate(excel_data.axis):
_fields_list.append(field.name)
col_formats[field_idx] = 'default' # 默认不特殊处理

for _data in excel_data.data:
_row = []
for field_idx, field in enumerate(excel_data.axis):
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)
data, _fields_list, col_formats = LLMService.format_pd_data(excel_data.axis, excel_data.data)

df = pd.DataFrame(data, columns=_fields_list)

Expand Down
100 changes: 75 additions & 25 deletions backend/apps/chat/task/llm.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@
get_chat_chart_data, list_generate_sql_logs, list_generate_chart_logs, start_log, end_log, \
get_last_execute_sql_error
from apps.chat.models.chat_model import ChatQuestion, ChatRecord, Chat, RenameChat, ChatLog, OperationEnum, \
ChatFinishStep
ChatFinishStep, AxisObj
from apps.data_training.curd.data_training import get_training_template
from apps.datasource.crud.datasource import get_table_schema
from apps.datasource.crud.permission import get_row_permission_filters, is_normal_user
Expand Down Expand Up @@ -414,7 +414,7 @@ def select_datasource(self, _session: Session):
if settings.TABLE_EMBEDDING_ENABLED and (
not self.current_assistant or (self.current_assistant and self.current_assistant.type != 1)):
_ds_list = get_ds_embedding(_session, self.current_user, _ds_list, self.out_ds_instance,
self.chat_question.question, self.current_assistant)
self.chat_question.question, self.current_assistant)
# yield {'content': '{"id":' + str(ds.get('id')) + '}'}

_ds_list_dict = []
Expand Down Expand Up @@ -1056,23 +1056,18 @@ def run_task(self, in_chat: bool = True, stream: bool = True,
if in_chat:
yield 'data:' + orjson.dumps({'type': 'finish'}).decode() + '\n\n'
else:
data = []
_fields_list = []
_fields_skip = False
for _data in result.get('data'):
_row = []
for field in result.get('fields'):
_row.append(_data.get(field))
if not _fields_skip:
_fields_list.append(field)
data.append(_row)
_fields_skip = True
_column_list = []
for field in result.get('fields'):
_column_list.append(AxisObj(name=field, value=field))

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)
markdown_table = df.to_markdown(index=False)
df_safe = self.safe_convert_to_string(df)
markdown_table = df_safe.to_markdown(index=False)
yield markdown_table + '\n\n'
else:
yield json_result
Expand Down Expand Up @@ -1117,22 +1112,19 @@ def run_task(self, in_chat: bool = True, stream: bool = True,
if chart.get('axis').get('series'):
_fields[chart.get('axis').get('series').get('value')] = chart.get('axis').get('series').get(
'name')
_fields_list = []
_fields_skip = False
for _data in result.get('data'):
_row = []
for field in result.get('fields'):
_row.append(_data.get(field))
if not _fields_skip:
_fields_list.append(field if not _fields.get(field) else _fields.get(field))
data.append(_row)
_fields_skip = True
_column_list = []
for field in result.get('fields'):
_column_list.append(
AxisObj(name=field if not _fields.get(field) else _fields.get(field), value=field))

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)
markdown_table = df.to_markdown(index=False)
df_safe = self.safe_convert_to_string(df)
markdown_table = df_safe.to_markdown(index=False)
yield markdown_table + '\n\n'

if in_chat:
Expand Down Expand Up @@ -1179,6 +1171,64 @@ def run_task(self, in_chat: bool = True, stream: bool = True,
self.finish(_session)
session_maker.remove()

@staticmethod
def safe_convert_to_string(df):
"""
安全地将数值列转换为字符串，避免科学记数法
"""
df_copy = df.copy()

for col in df_copy.columns:
# 只处理数值类型的列
if pd.api.types.is_numeric_dtype(df_copy[col]):
try:
df_copy[col] = df_copy[col].astype(str)
except Exception as e:
print(f"列 {col} 转换失败: {e}")
# 如果转换失败，保持原样
continue

return df_copy

@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)

Expand Down