feat: improve regenerate SQL chat feature

backend/alembic/env.py

@@ -24,7 +24,7 @@ config = context.config
 
 # from apps.system.models.user import SQLModel  # noqa
 # from apps.settings.models.setting_models import SQLModel
-# from apps.chat.models.chat_model import SQLModel
+from apps.chat.models.chat_model import SQLModel
 from apps.terminology.models.terminology_model import SQLModel
 #from apps.custom_prompt.models.custom_prompt_model import SQLModel
 from apps.data_training.models.data_training_model import SQLModel

backend/alembic/versions/054_update_chat_record_dll.py

@@ -0,0 +1,29 @@
+"""054_update_chat_record_dll
+
+Revision ID: 24e961f6326b
+Revises: 5755c0b95839
+Create Date: 2025-12-04 15:51:42.900778
+
+"""
+from alembic import op
+import sqlalchemy as sa
+import sqlmodel.sql.sqltypes
+from sqlalchemy.dialects import postgresql
+
+# revision identifiers, used by Alembic.
+revision = '24e961f6326b'
+down_revision = '5755c0b95839'
+branch_labels = None
+depends_on = None
+
+
+def upgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.add_column('chat_record', sa.Column('regenerate_record_id', sa.BigInteger(), nullable=True))
+    # ### end Alembic commands ###
+
+
+def downgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_column('chat_record', 'regenerate_record_id')
+    # ### end Alembic commands ###

backend/apps/chat/api/chat.py

@@ -12,9 +12,10 @@ from sqlalchemy import and_, select
 from apps.chat.curd.chat import list_chats, get_chat_with_records, create_chat, rename_chat, \
     delete_chat, get_chat_chart_data, get_chat_predict_data, get_chat_with_records_with_data, get_chat_record_by_id, \
     format_json_data, format_json_list_data, get_chart_config, list_recent_questions
-from apps.chat.models.chat_model import CreateChat, ChatRecord, RenameChat, ChatQuestion, AxisObj
+from apps.chat.models.chat_model import CreateChat, ChatRecord, RenameChat, ChatQuestion, AxisObj, QuickCommand
 from apps.chat.task.llm import LLMService
 from common.core.deps import CurrentAssistant, SessionDep, CurrentUser, Trans
+from common.utils.command_utils import parse_quick_command
 from common.utils.data_format import DataFormat
 
 router = APIRouter(tags=["Data Q&A"], prefix="/chat")
@@ -141,20 +142,99 @@ async def recommend_questions(session: SessionDep, current_user: CurrentUser, da
     return list_recent_questions(session=session, current_user=current_user, datasource_id=datasource_id)
 
 
+def find_base_question(record_id: int, session: SessionDep):
+    stmt = select(ChatRecord.question, ChatRecord.regenerate_record_id).where(
+        and_(ChatRecord.id == record_id))
+    _record = session.execute(stmt).fetchone()
+    if not _record:
+        raise Exception(f'Cannot find base chat record')
+    rec_question, rec_regenerate_record_id = _record
+    if rec_regenerate_record_id:
+        return find_base_question(rec_regenerate_record_id, session)
+    else:
+        return rec_question
+
+
 @router.post("/question")
+async def question_answer(session: SessionDep, current_user: CurrentUser, request_question: ChatQuestion,
+                          current_assistant: CurrentAssistant):
+    try:
+        command, text_before_command, record_id, warning_info = parse_quick_command(request_question.question)
+        if command:
+            # todo 暂不支持分析和预测，需要改造前端
+            if command == QuickCommand.ANALYSIS or command == QuickCommand.PREDICT_DATA:
+                raise Exception(f'Command: {command.value} temporary not supported')
+
+            if record_id is not None:
+                # 排除analysis和predict
+                stmt = select(ChatRecord.id, ChatRecord.chat_id, ChatRecord.analysis_record_id,
+                              ChatRecord.predict_record_id, ChatRecord.regenerate_record_id,
+                              ChatRecord.first_chat).where(
+                    and_(ChatRecord.id == record_id))
+                _record = session.execute(stmt).fetchone()
+                if not _record:
+                    raise Exception(f'Record id: {record_id} does not exist')
+
+                rec_id, rec_chat_id, rec_analysis_record_id, rec_predict_record_id, rec_regenerate_record_id, rec_first_chat = _record
+
+                if rec_chat_id != request_question.chat_id:
+                    raise Exception(f'Record id: {record_id} does not belong to this chat')
+                if rec_first_chat:
+                    raise Exception(f'Record id: {record_id} does not support this operation')
+
+                if command == QuickCommand.REGENERATE:
+                    if rec_analysis_record_id:
+                        raise Exception('Analysis record does not support this operation')
+                    if rec_predict_record_id:
+                        raise Exception('Predict data record does not support this operation')
+
+            else:  # get last record id
+                stmt = select(ChatRecord.id, ChatRecord.chat_id, ChatRecord.regenerate_record_id).where(
+                    and_(ChatRecord.chat_id == request_question.chat_id,
+                         ChatRecord.first_chat == False,
+                         ChatRecord.analysis_record_id.is_(None),
+                         ChatRecord.predict_record_id.is_(None))).order_by(
+                    ChatRecord.create_time.desc()).limit(1)
+                _record = session.execute(stmt).fetchone()
+
+                if not _record:
+                    raise Exception(f'You have not ask any question')
+
+                rec_id, rec_chat_id, rec_regenerate_record_id = _record
+
+            # 没有指定的，就查询上一个
+            if not rec_regenerate_record_id:
+                rec_regenerate_record_id = rec_id
+
+            # 针对已经是重新生成的提问，需要找到原来的提问是什么
+            base_question_text = find_base_question(rec_regenerate_record_id, session)
+            text_before_command = text_before_command + ("\n" if text_before_command else "") + base_question_text
+
+            if command == QuickCommand.REGENERATE:
+                request_question.question = text_before_command
+                request_question.regenerate_record_id = rec_id
+                return await stream_sql(session, current_user, request_question, current_assistant)
+
+            elif command == QuickCommand.ANALYSIS:
+                return await analysis_or_predict(session, current_user, rec_id, 'analysis', current_assistant)
+
+            elif command == QuickCommand.PREDICT_DATA:
+                return await analysis_or_predict(session, current_user, rec_id, 'predict', current_assistant)
+            else:
+                raise Exception(f'Unknown command: {command.value}')
+        else:
+            return await stream_sql(session, current_user, request_question, current_assistant)
+    except Exception as e:
+        traceback.print_exc()
+
+        def _err(_e: Exception):
+            yield 'data:' + orjson.dumps({'content': str(_e), 'type': 'error'}).decode() + '\n\n'
+
+        return StreamingResponse(_err(e), media_type="text/event-stream")
+
+
 async def stream_sql(session: SessionDep, current_user: CurrentUser, request_question: ChatQuestion,
                      current_assistant: CurrentAssistant):
-    """Stream SQL analysis results
-    
-    Args:
-        session: Database session
-        current_user: CurrentUser
-        request_question: User question model
-        
-    Returns:
-        Streaming response with analysis results
-    """
-
     try:
         llm_service = await LLMService.create(session, current_user, request_question, current_assistant,
                                               embedding=True)
@@ -172,6 +252,12 @@ async def stream_sql(session: SessionDep, current_user: CurrentUser, request_que
 
 
 @router.post("/record/{chat_record_id}/{action_type}")
+async def analysis_or_predict_question(session: SessionDep, current_user: CurrentUser, chat_record_id: int,
+                                       action_type: str,
+                                       current_assistant: CurrentAssistant):
+    return await analysis_or_predict(session, current_user, chat_record_id, action_type, current_assistant)
+
+
 async def analysis_or_predict(session: SessionDep, current_user: CurrentUser, chat_record_id: int, action_type: str,
                               current_assistant: CurrentAssistant):
     try:

backend/apps/chat/curd/chat.py

@@ -1,16 +1,16 @@
 import datetime
 from typing import List
-from sqlalchemy import desc, func
 
 import orjson
 import sqlparse
 from sqlalchemy import and_, select, update
+from sqlalchemy import desc, func
 from sqlalchemy.orm import aliased
 
 from apps.chat.models.chat_model import Chat, ChatRecord, CreateChat, ChatInfo, RenameChat, ChatQuestion, ChatLog, \
     TypeEnum, OperationEnum, ChatRecordResult
-from apps.datasource.crud.recommended_problem import get_datasource_recommended, get_datasource_recommended_chart
-from apps.datasource.models.datasource import CoreDatasource, DsRecommendedProblem
+from apps.datasource.crud.recommended_problem import get_datasource_recommended_chart
+from apps.datasource.models.datasource import CoreDatasource
 from apps.system.crud.assistant import AssistantOutDsFactory
 from common.core.deps import CurrentAssistant, SessionDep, CurrentUser, Trans
 from common.utils.utils import extract_nested_json
@@ -28,11 +28,13 @@ def get_chat_record_by_id(session: SessionDep, record_id: int):
                             engine_type=r.engine_type, ai_modal_id=r.ai_modal_id, create_by=r.create_by)
     return record
 
+
 def get_chat(session: SessionDep, chat_id: int) -> Chat:
     statement = select(Chat).where(Chat.id == chat_id)
     chat = session.exec(statement).scalars().first()
     return chat
 
+
 def list_chats(session: SessionDep, current_user: CurrentUser) -> List[Chat]:
     oid = current_user.oid if current_user.oid is not None else 1
     chart_list = session.query(Chat).filter(and_(Chat.create_by == current_user.id, Chat.oid == oid)).order_by(
@@ -57,6 +59,7 @@ def list_recent_questions(session: SessionDep, current_user: CurrentUser, dataso
     )
     return [record[0] for record in chat_records] if chat_records else []
 
+
 def rename_chat(session: SessionDep, rename_object: RenameChat) -> str:
     chat = session.get(Chat, rename_object.id)
     if not chat:
@@ -191,7 +194,8 @@ dynamic_ds_types = [1, 3]
 
 
 def get_chat_with_records(session: SessionDep, chart_id: int, current_user: CurrentUser,
-                          current_assistant: CurrentAssistant, with_data: bool = False,trans: Trans = None) -> ChatInfo:
+                          current_assistant: CurrentAssistant, with_data: bool = False,
+                          trans: Trans = None) -> ChatInfo:
     chat = session.get(Chat, chart_id)
     if not chat:
         raise Exception(f"Chat with id {chart_id} not found")
@@ -200,7 +204,7 @@ def get_chat_with_records(session: SessionDep, chart_id: int, current_user: Curr
 
     if current_assistant and current_assistant.type in dynamic_ds_types:
         out_ds_instance = AssistantOutDsFactory.get_instance(current_assistant)
-        ds = out_ds_instance.get_ds(chat.datasource,trans)
+        ds = out_ds_instance.get_ds(chat.datasource, trans)
     else:
         ds = session.get(CoreDatasource, chat.datasource) if chat.datasource else None
 
@@ -221,6 +225,7 @@ def get_chat_with_records(session: SessionDep, chart_id: int, current_user: Curr
                    ChatRecord.question, ChatRecord.sql_answer, ChatRecord.sql,
                    ChatRecord.chart_answer, ChatRecord.chart, ChatRecord.analysis, ChatRecord.predict,
                    ChatRecord.datasource_select_answer, ChatRecord.analysis_record_id, ChatRecord.predict_record_id,
+                   ChatRecord.regenerate_record_id,
                    ChatRecord.recommended_question, ChatRecord.first_chat,
                    ChatRecord.finish, ChatRecord.error,
                    sql_alias_log.reasoning_content.label('sql_reasoning_content'),
@@ -247,6 +252,7 @@ def get_chat_with_records(session: SessionDep, chart_id: int, current_user: Curr
                       ChatRecord.question, ChatRecord.sql_answer, ChatRecord.sql,
                       ChatRecord.chart_answer, ChatRecord.chart, ChatRecord.analysis, ChatRecord.predict,
                       ChatRecord.datasource_select_answer, ChatRecord.analysis_record_id, ChatRecord.predict_record_id,
+                      ChatRecord.regenerate_record_id,
                       ChatRecord.recommended_question, ChatRecord.first_chat,
                       ChatRecord.finish, ChatRecord.error, ChatRecord.data, ChatRecord.predict_data).where(
             and_(ChatRecord.create_by == current_user.id, ChatRecord.chat_id == chart_id)).order_by(
@@ -264,6 +270,7 @@ def get_chat_with_records(session: SessionDep, chart_id: int, current_user: Curr
                                  analysis=row.analysis, predict=row.predict,
                                  datasource_select_answer=row.datasource_select_answer,
                                  analysis_record_id=row.analysis_record_id, predict_record_id=row.predict_record_id,
+                                 regenerate_record_id=row.regenerate_record_id,
                                  recommended_question=row.recommended_question, first_chat=row.first_chat,
                                  finish=row.finish, error=row.error,
                                  sql_reasoning_content=row.sql_reasoning_content,
@@ -280,6 +287,7 @@ def get_chat_with_records(session: SessionDep, chart_id: int, current_user: Curr
                                  analysis=row.analysis, predict=row.predict,
                                  datasource_select_answer=row.datasource_select_answer,
                                  analysis_record_id=row.analysis_record_id, predict_record_id=row.predict_record_id,
+                                 regenerate_record_id=row.regenerate_record_id,
                                  recommended_question=row.recommended_question, first_chat=row.first_chat,
                                  finish=row.finish, error=row.error, data=row.data, predict_data=row.predict_data))
 
@@ -347,8 +355,9 @@ def format_record(record: ChatRecordResult):
 
     return _dict
 
+
 def get_chat_brief_generate(session: SessionDep, chat_id: int):
-    chat  = get_chat(session=session,chat_id=chat_id)
+    chat = get_chat(session=session, chat_id=chat_id)
     if chat is not None and chat.brief_generate is not None:
         return chat.brief_generate
     else:
@@ -468,6 +477,7 @@ def save_question(session: SessionDep, current_user: CurrentUser, question: Chat
     record.datasource = chat.datasource
     record.engine_type = chat.engine_type
     record.ai_modal_id = question.ai_modal_id
+    record.regenerate_record_id = question.regenerate_record_id
 
     result = ChatRecord(**record.model_dump())
 

backend/apps/chat/models/chat_model.py

@@ -48,6 +48,12 @@ class ChatFinishStep(Enum):
     GENERATE_CHART = 3
 
 
+class QuickCommand(Enum):
+    REGENERATE = '/regenerate'
+    ANALYSIS = '/analysis'
+    PREDICT_DATA = '/predict'
+
+
 #     TODO choose table / check connection / generate description
 
 class ChatLog(SQLModel, table=True):
@@ -78,7 +84,7 @@ class Chat(SQLModel, table=True):
     datasource: int = Field(sa_column=Column(BigInteger, nullable=True))
     engine_type: str = Field(max_length=64)
     origin: Optional[int] = Field(
-        sa_column=Column(Integer, nullable=False, default=0)) # 0: default, 1: mcp, 2: assistant
+        sa_column=Column(Integer, nullable=False, default=0))  # 0: default, 1: mcp, 2: assistant
     brief_generate: bool = Field(default=False)
 
 
@@ -110,6 +116,7 @@ class ChatRecord(SQLModel, table=True):
     error: str = Field(sa_column=Column(Text, nullable=True))
     analysis_record_id: int = Field(sa_column=Column(BigInteger, nullable=True))
     predict_record_id: int = Field(sa_column=Column(BigInteger, nullable=True))
+    regenerate_record_id: int = Field(sa_column=Column(BigInteger, nullable=True))
 
 
 class ChatRecordResult(BaseModel):
@@ -134,6 +141,7 @@ class ChatRecordResult(BaseModel):
     error: Optional[str] = None
     analysis_record_id: Optional[int] = None
     predict_record_id: Optional[int] = None
+    regenerate_record_id: Optional[int] = None
     sql_reasoning_content: Optional[str] = None
     chart_reasoning_content: Optional[str] = None
     analysis_reasoning_content: Optional[str] = None
@@ -184,6 +192,7 @@ class AiModelQuestion(BaseModel):
     data_training: str = ""
     custom_prompt: str = ""
     error_msg: str = ""
+    regenerate_record_id: Optional[int] = None
 
     def sql_sys_question(self, db_type: Union[str, DB], enable_query_limit: bool = True):
         _sql_template = get_sql_example_template(db_type)
@@ -213,7 +222,10 @@ class AiModelQuestion(BaseModel):
                                                example_answer_3=_example_answer_3)
 
     def sql_user_question(self, current_time: str, change_title: bool):
-        return get_sql_template()['user'].format(engine=self.engine, schema=self.db_schema, question=self.question,
+        _question = self.question
+        if self.regenerate_record_id:
+            _question = get_sql_template()['regenerate_hint'] + self.question
+        return get_sql_template()['user'].format(engine=self.engine, schema=self.db_schema, question=_question,
                                                  rule=self.rule, current_time=current_time, error_msg=self.error_msg,
                                                  change_title=change_title)
 

backend/apps/chat/task/llm.py

@@ -167,6 +167,11 @@ class LLMService:
     def init_messages(self):
         last_sql_messages: List[dict[str, Any]] = self.generate_sql_logs[-1].messages if len(
             self.generate_sql_logs) > 0 else []
+        if self.chat_question.regenerate_record_id:
+            # filter record before regenerate_record_id
+            _temp_log = next(
+                filter(lambda obj: obj.pid == self.chat_question.regenerate_record_id, self.generate_sql_logs), None)
+            last_sql_messages: List[dict[str, Any]] = _temp_log.messages if _temp_log else []
 
         # todo maybe can configure
         count_limit = 0 - base_message_count_limit
@@ -947,6 +952,11 @@ class LLMService:
             # return id
             if in_chat:
                 yield 'data:' + orjson.dumps({'type': 'id', 'id': self.get_record().id}).decode() + '\n\n'
+                if self.get_record().regenerate_record_id:
+                    yield 'data:' + orjson.dumps({'type': 'regenerate_record_id',
+                                                  'regenerate_record_id': self.get_record().regenerate_record_id}).decode() + '\n\n'
+                yield 'data:' + orjson.dumps(
+                    {'type': 'question', 'question': self.get_record().question}).decode() + '\n\n'
             if not stream:
                 json_result['record_id'] = self.get_record().id
 

backend/common/utils/command_utils.py

@@ -0,0 +1,99 @@
+import re
+from typing import Optional, Tuple
+
+from apps.chat.models.chat_model import QuickCommand
+
+
+def parse_quick_command(input_str: str) -> Tuple[Optional[QuickCommand], str, Optional[int], Optional[str]]:
+    """
+    解析字符串中的快速命令
+
+    Args:
+        input_str: 输入字符串
+
+    Returns:
+        Tuple[Optional[QuickCommand], str, Optional[int], Optional[str]]:
+        (命令枚举, 去除命令的字符串, 数字参数, 警告信息)
+        如果解析成功: (命令, 文本, 数字, None)
+        如果解析失败: (None, 原字符串, None, 警告信息)
+    """
+
+    # 获取所有命令值
+    command_values = [cmd.value for cmd in QuickCommand]
+
+    # 1. 检查字符串中是否包含任何命令
+    found_commands = []
+    for cmd_value in command_values:
+        # 使用正则表达式查找独立的命令（前后是单词边界或空格）
+        pattern = r'(?<!\S)' + re.escape(cmd_value) + r'(?!\S)'
+        if re.search(pattern, input_str):
+            found_commands.append(cmd_value)
+
+    # 如果没有找到任何命令，直接返回原字符串
+    if not found_commands:
+        return None, input_str, None, None
+
+    # 2. 检查是否包含多个命令
+    if len(found_commands) > 1:
+        return None, input_str, None, f"错误: 字符串中包含多个命令: {', '.join(found_commands)}"
+
+    # 此时只有一个命令
+    command_str = found_commands[0]
+
+    # 3. 构建完整匹配模式，匹配命令及其后的可选数字
+    # 模式: 命令 + 可选的空格 + 可选的数字
+    full_pattern = r'(?<!\S)(' + re.escape(command_str) + r')(?:\s+(\d+))?(?!\S)'
+    match = re.search(full_pattern, input_str)
+
+    if not match:
+        return None, input_str, None, f"错误: 命令格式不正确"
+
+    command_part = match.group(1)
+    number_part = match.group(2)
+
+    # 4. 检查命令是否在字符串末尾
+    # 计算命令的结束位置
+    command_end_pos = match.end()
+
+    # 如果命令不在字符串的末尾（忽略尾部空格）
+    if command_end_pos < len(input_str.rstrip()):
+        # 检查命令后面是否有非空格字符
+        remaining_text = input_str[command_end_pos:].strip()
+        if remaining_text:
+            return None, input_str, None, f"错误: 命令不在字符串末尾，命令后还有内容: '{remaining_text}'"
+
+    # 5. 检查命令前面是否有内容，但中间没有空格
+    # 找到命令前面的部分
+    before_command = input_str[:match.start()]
+
+    # 如果命令前面有内容，检查是否有空格分隔
+    if before_command and not before_command.endswith(' '):
+        # 检查命令是否在字符串开头
+        if match.start() > 0:
+            return None, input_str, None, f"错误: 命令与前面的文本没有用空格分隔"
+
+    # 6. 获取命令枚举
+    command = None
+    for cmd in QuickCommand:
+        if cmd.value == command_part:
+            command = cmd
+            break
+
+    if not command:
+        return None, input_str, None, f"错误: 未识别的命令: {command_part}"
+
+    # 7. 提取去除命令和数字后的文本
+    # 获取命令前的文本
+    text_before_command = input_str[:match.start()].rstrip()
+
+    # 8. 处理数字参数
+    record_id = None
+    if number_part:
+        try:
+            record_id = int(number_part)
+        except ValueError:
+            return None, input_str, None, f"错误: 数字参数格式不正确: {number_part}"
+
+    return command, text_before_command, record_id, None
+
+

backend/templates/template.yaml

@@ -6,16 +6,20 @@ template:
     
     {data_training}
   sql:
+    regenerate_hint: |
+      你之前生成的回答不符合预期或者系统出现了其他问题，请再次检查提示词内要求的规则和提供的信息，重新回答：
+
     process_check: |
       <SQL-Generation-Process>
         <step>1. 分析用户问题，确定查询需求</step>
         <step>2. 根据表结构生成基础SQL</step>
-        <step>3. <strong>强制检查：应用数据量限制规则</strong></step>
-        <step>4. 应用其他规则（引号、别名等）</step>
-        <step>5. <strong>强制检查：检查语法是否正确？</strong></step>
-        <step>6. 确定图表类型</step>
-        <step>7. 确定对话标题</step>
-        <step>8. 返回JSON结果</step>
+        <step>3. <strong>强制检查：验证SQL中使用的表名和字段名是否在<m-schema>中定义</strong></step>
+        <step>4. <strong>强制检查：应用数据量限制规则（默认限制或用户指定数量）</strong></step>
+        <step>5. 应用其他规则（引号、别名、格式化等）</step>
+        <step>6. <strong>强制检查：验证SQL语法是否符合<db-engine>规范</strong></step>
+        <step>7. 确定图表类型（根据规则选择table/column/bar/line/pie）</step>
+        <step>8. 确定对话标题</step>
+        <step>9. 返回JSON结果</step>
       </SQL-Generation-Process>
     query_limit: |
       <rule priority="critical" id="data-limit-policy">

frontend/src/api/chat.ts

@@ -51,6 +51,7 @@ export class ChatRecord {
   recommended_question?: string
   analysis_record_id?: number
   predict_record_id?: number
+  regenerate_record_id?: number
 
   constructor()
   constructor(
@@ -75,7 +76,8 @@ export class ChatRecord {
     first_chat: boolean,
     recommended_question: string | undefined,
     analysis_record_id: number | undefined,
-    predict_record_id: number | undefined
+    predict_record_id: number | undefined,
+    regenerate_record_id: number | undefined
   )
   constructor(
     id?: number,
@@ -99,7 +101,8 @@ export class ChatRecord {
     first_chat?: boolean,
     recommended_question?: string,
     analysis_record_id?: number,
-    predict_record_id?: number
+    predict_record_id?: number,
+    regenerate_record_id?: number
   ) {
     this.id = id
     this.chat_id = chat_id
@@ -123,6 +126,7 @@ export class ChatRecord {
     this.recommended_question = recommended_question
     this.analysis_record_id = analysis_record_id
     this.predict_record_id = predict_record_id
+    this.regenerate_record_id = regenerate_record_id
   }
 }
 
@@ -252,7 +256,8 @@ const toChatRecord = (data?: any): ChatRecord | undefined => {
     data.first_chat,
     data.recommended_question,
     data.analysis_record_id,
-    data.predict_record_id
+    data.predict_record_id,
+    data.regenerate_record_id
   )
 }
 const toChatRecordList = (list: any = []): ChatRecord[] => {

frontend/src/i18n/en.json

@@ -235,6 +235,7 @@
     "continue_to_ask": "Continue asking:",
     "data_analysis": "Data Analysis",
     "data_predict": "Data Prediction",
+    "data_regenerated": "Regenerate",
     "chat_search": "Search",
     "thinking": "Thinking",
     "thinking_step": "Thought Process",

frontend/src/i18n/ko-KR.json

@@ -235,6 +235,7 @@
     "continue_to_ask": "계속 질문하기:",
     "data_analysis": "데이터 분석",
     "data_predict": "데이터 예측",
+    "data_regenerated": "재생성",
     "chat_search": "검색",
     "thinking": "생각 중",
     "thinking_step": "사고 과정",

frontend/src/i18n/zh-CN.json

@@ -236,6 +236,7 @@
     "continue_to_ask": "继续提问:",
     "data_analysis": "数据分析",
     "data_predict": "数据预测",
+    "data_regenerated": "重新生成",
     "chat_search": "搜索",
     "thinking": "思考中",
     "thinking_step": "思考过程",

frontend/src/views/chat/answer/ChartAnswer.vue

@@ -163,6 +163,15 @@ const sendMessage = async () => {
                 currentRecord.id = data.id
                 _currentChat.value.records[index.value].id = data.id
                 break
+              case 'regenerate_record_id':
+                currentRecord.regenerate_record_id = data.regenerate_record_id
+                _currentChat.value.records[index.value].regenerate_record_id =
+                  data.regenerate_record_id
+                break
+              case 'question':
+                currentRecord.question = data.question
+                _currentChat.value.records[index.value].question = data.question
+                break
               case 'info':
                 console.info(data.msg)
                 break

frontend/src/views/chat/chat-block/UserChat.vue

@@ -3,9 +3,11 @@ import type { ChatMessage } from '@/api/chat.ts'
 import icon_copy_outlined from '@/assets/embedded/icon_copy_outlined.svg'
 import { useI18n } from 'vue-i18n'
 import { useClipboard } from '@vueuse/core'
+import { computed } from 'vue'
 
 const props = defineProps<{
   message?: ChatMessage
+  allMessages?: ChatMessage[]
 }>()
 const { t } = useI18n()
 const { copy } = useClipboard({ legacy: true })
@@ -16,6 +18,13 @@ function clickAnalysis() {
 function clickPredict() {
   console.info('predict_record_id: ' + props.message?.record?.predict_record_id)
 }
+function clickRegenerated() {
+  console.info('regenerate_record_id: ' + props.message?.record?.regenerate_record_id)
+}
+
+const isRegenerated = computed(() => {
+  return !!props.message?.record?.regenerate_record_id
+})
 
 const copyCode = () => {
   const str = props.message?.content || ''
@@ -37,6 +46,9 @@ const copyCode = () => {
     <span v-else-if="message?.record?.predict_record_id" class="prefix-title" @click="clickPredict">
       {{ t('qa.data_predict') }}
     </span>
+    <span v-else-if="isRegenerated" class="prefix-title" @click="clickRegenerated">
+      {{ t('qa.data_regenerated') }}
+    </span>
     <span style="width: 100%">{{ message?.content }}</span>
     <div style="position: absolute; right: 12px; bottom: -24px">
       <el-tooltip :offset="12" effect="dark" :content="t('datasource.copy')" placement="top">

frontend/src/views/chat/index.vue

@@ -211,7 +211,11 @@
                 <!--                  @stop="onChatStop"-->
                 <!--                  @loading-over="loadingOver"-->
                 <!--                />-->
-                <UserChat v-if="message.role === 'user'" :message="message" />
+                <UserChat
+                  v-if="message.role === 'user'"
+                  :message="message"
+                  :all-messages="computedMessages"
+                />
                 <template v-if="message.role === 'assistant' && !message.first_chat">
                   <ChartAnswer
                     v-if="
@@ -397,7 +401,7 @@
             type="textarea"
             :autosize="{ minRows: 1, maxRows: 8.583 }"
             :placeholder="t('qa.question_placeholder')"
-            @keydown.enter.exact.prevent="($event: any) => sendMessage($event)"
+            @keydown.enter.exact.prevent="($event: any) => sendMessage(undefined, $event)"
             @keydown.ctrl.enter.exact.prevent="handleCtrlEnter"
           />
 
@@ -764,7 +768,10 @@ const assistantPrepareSend = async () => {
     }
   }
 }
-const sendMessage = async ($event: any = {}) => {
+const sendMessage = async (
+  regenerate_record_id: number | undefined = undefined,
+  $event: any = {}
+) => {
   if ($event?.isComposing) {
     return
   }
@@ -783,6 +790,7 @@ const sendMessage = async ($event: any = {}) => {
   currentRecord.create_time = new Date()
   currentRecord.chat_id = currentChatId.value
   currentRecord.question = inputMessage.value
+  currentRecord.regenerate_record_id = regenerate_record_id
   currentRecord.sql_answer = ''
   currentRecord.sql = ''
   currentRecord.chart_answer = ''
@@ -829,9 +837,21 @@ function onAnalysisAnswerError() {
 }
 
 function askAgain(message: ChatMessage) {
-  inputMessage.value = message.record?.question ?? ''
+  if (message.record?.question?.trim() === '') {
+    return
+  }
+  // regenerate
+  inputMessage.value = '/regenerate'
+  let regenerate_record_id = message.record?.id
+  if (message.record?.id == undefined && message.record?.regenerate_record_id) {
+    //只有当前对话内，上一次执行失败的重试会进这里
+    regenerate_record_id = message.record?.regenerate_record_id
+  }
+  if (regenerate_record_id) {
+    inputMessage.value = inputMessage.value + ' ' + regenerate_record_id
+  }
   nextTick(() => {
-    sendMessage()
+    sendMessage(regenerate_record_id)
   })
 }