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feat(embedding): support multi-turn conversation context for table RAG #678

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33 changes: 33 additions & 0 deletions backend/apps/chat/curd/chat.py
View file Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -891,3 +891,36 @@ def get_old_questions(session: SessionDep, datasource: int):
for r in result:
records.append(r.question)
return records


def get_chat_history_questions(session: SessionDep, chat_id: int, limit: int = 3) -> List[str]:
"""
获取当前chat的历史问题列表(按时间正序,最旧的在前)

Args:
session: 数据库会话
chat_id: 当前对话ID
limit: 获取的历史问题数量

Returns:
历史问题列表,按时间正序排列
"""
stmt = (
select(ChatRecord.question)
.where(
and_(
ChatRecord.chat_id == chat_id,
ChatRecord.question.isnot(None),
ChatRecord.question != '',
ChatRecord.error.is_(None)
)
)
.order_by(ChatRecord.create_time.desc())
.limit(limit)
)

result = session.execute(stmt)
questions = [row.question for row in result if row.question and row.question.strip()]

# 反转列表,使最旧的在前
return list(reversed(questions))
11 changes: 9 additions & 2 deletions backend/apps/chat/task/llm.py
View file Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -31,7 +31,7 @@
get_old_questions, save_analysis_predict_record, rename_chat, get_chart_config, \
get_chat_chart_data, list_generate_sql_logs, list_generate_chart_logs, start_log, end_log, \
get_last_execute_sql_error, format_json_data, format_chart_fields, get_chat_brief_generate, get_chat_predict_data, \
get_chat_chart_config
get_chat_chart_config, get_chat_history_questions
from apps.chat.models.chat_model import ChatQuestion, ChatRecord, Chat, RenameChat, ChatLog, OperationEnum, \
ChatFinishStep, AxisObj
from apps.data_training.curd.data_training import get_training_template
Expand Down Expand Up @@ -106,6 +106,12 @@ def __init__(self, session: Session, current_user: CurrentUser, chat_question: C
chat: Chat | None = session.get(Chat, chat_id)
if not chat:
raise SingleMessageError(f"Chat with id {chat_id} not found")

# 获取历史问题(用于多轮对话embedding)
history_questions = []
if settings.MULTI_TURN_EMBEDDING_ENABLED:
history_questions = get_chat_history_questions(session, chat_id, settings.MULTI_TURN_HISTORY_COUNT)

ds: CoreDatasource | AssistantOutDsSchema | None = None
if chat.datasource:
# Get available datasource
Expand All @@ -122,7 +128,8 @@ def __init__(self, session: Session, current_user: CurrentUser, chat_question: C
raise SingleMessageError("No available datasource configuration found")
chat_question.engine = (ds.type_name if ds.type != 'excel' else 'PostgreSQL') + get_version(ds)
chat_question.db_schema = get_table_schema(session=session, current_user=current_user, ds=ds,
question=chat_question.question, embedding=embedding)
question=chat_question.question, embedding=embedding,
history_questions=history_questions)

self.generate_sql_logs = list_generate_sql_logs(session=session, chart_id=chat_id)
self.generate_chart_logs = list_generate_chart_logs(session=session, chart_id=chat_id)
Expand Down
4 changes: 2 additions & 2 deletions backend/apps/datasource/crud/datasource.py
View file Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -425,7 +425,7 @@ def get_table_obj_by_ds(session: SessionDep, current_user: CurrentUser, ds: Core


def get_table_schema(session: SessionDep, current_user: CurrentUser, ds: CoreDatasource, question: str,
embedding: bool = True) -> str:
embedding: bool = True, history_questions: List[str] = None) -> str:
schema_str = ""
table_objs = get_table_obj_by_ds(session=session, current_user=current_user, ds=ds)
if len(table_objs) == 0:
Expand Down Expand Up @@ -464,7 +464,7 @@ def get_table_schema(session: SessionDep, current_user: CurrentUser, ds: CoreDat

# do table embedding
if embedding and tables and settings.TABLE_EMBEDDING_ENABLED:
tables = calc_table_embedding(tables, question)
tables = calc_table_embedding(tables, question, history_questions)
# splice schema
if tables:
for s in tables:
Expand Down
55 changes: 51 additions & 4 deletions backend/apps/datasource/embedding/table_embedding.py
View file Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3,14 +3,46 @@
import json
import time
import traceback
from typing import List

from apps.ai_model.embedding import EmbeddingModelCache
from apps.datasource.embedding.utils import cosine_similarity
from common.core.config import settings
from common.utils.utils import SQLBotLogUtil


def get_table_embedding(tables: list[dict], question: str):
def build_context_query(current_question: str, history_questions: List[str] = None) -> str:
"""
构建包含上下文的查询文本

Args:
current_question: 当前问题
history_questions: 历史问题列表(按时间正序,最旧的在前)

Returns:
拼接后的查询文本
"""
if not settings.MULTI_TURN_EMBEDDING_ENABLED or not history_questions:
return current_question

max_history = settings.MULTI_TURN_HISTORY_COUNT
recent_history = history_questions[-max_history:] if history_questions else []

if not recent_history:
return current_question

# 拼接:历史问题 + 当前问题
context_parts = recent_history + [current_question]

# 使用分隔符拼接,保持语义连贯
context_query = " | ".join(context_parts)

SQLBotLogUtil.info(f"Context query for embedding: {context_query}")

return context_query


def get_table_embedding(tables: list[dict], question: str, history_questions: List[str] = None):
_list = []
for table in tables:
_list.append({"id": table.get('id'), "schema_table": table.get('schema_table'), "cosine_similarity": 0.0})
Expand All @@ -25,7 +57,9 @@ def get_table_embedding(tables: list[dict], question: str):
end_time = time.time()
SQLBotLogUtil.info(str(end_time - start_time))

q_embedding = model.embed_query(question)
# 构建包含上下文的查询
context_query = build_context_query(question, history_questions)
q_embedding = model.embed_query(context_query)
for index in range(len(results)):
item = results[index]
_list[index]['cosine_similarity'] = cosine_similarity(q_embedding, item)
Expand All @@ -40,7 +74,18 @@ def get_table_embedding(tables: list[dict], question: str):
return _list


def calc_table_embedding(tables: list[dict], question: str):
def calc_table_embedding(tables: list[dict], question: str, history_questions: List[str] = None):
"""
计算表结构与问题的embedding相似度

Args:
tables: 表结构列表
question: 当前问题
history_questions: 历史问题列表(可选,用于多轮对话)

Returns:
按相似度排序的表列表
"""
_list = []
for table in tables:
_list.append(
Expand All @@ -58,7 +103,9 @@ def calc_table_embedding(tables: list[dict], question: str):
# SQLBotLogUtil.info(str(end_time - start_time))
results = [item.get('embedding') for item in _list]

q_embedding = model.embed_query(question)
# 构建包含上下文的查询
context_query = build_context_query(question, history_questions)
q_embedding = model.embed_query(context_query)
for index in range(len(results)):
item = results[index]
if item:
Expand Down
5 changes: 5 additions & 0 deletions backend/common/core/config.py
View file Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -115,6 +115,10 @@ def SQLALCHEMY_DATABASE_URI(self) -> PostgresDsn | str:
TABLE_EMBEDDING_COUNT: int = 10
DS_EMBEDDING_COUNT: int = 10

# Multi-turn embedding settings
MULTI_TURN_EMBEDDING_ENABLED: bool = True
MULTI_TURN_HISTORY_COUNT: int = 3

ORACLE_CLIENT_PATH: str = '/opt/sqlbot/db_client/oracle_instant_client'

@field_validator('SQL_DEBUG',
Expand All @@ -123,6 +127,7 @@ def SQLALCHEMY_DATABASE_URI(self) -> PostgresDsn | str:
'PARSE_REASONING_BLOCK_ENABLED',
'PG_POOL_PRE_PING',
'TABLE_EMBEDDING_ENABLED',
'MULTI_TURN_EMBEDDING_ENABLED',
mode='before')
@classmethod
def lowercase_bool(cls, v: Any) -> Any:
Expand Down

AltStyle によって変換されたページ (->オリジナル) /