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291 lines
11 KiB
Python
291 lines
11 KiB
Python
import json
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import logging
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import warnings
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from typing import Any, List, Union, Dict
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from langchain_community.utilities import SQLDatabase
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from langchain_core.language_models import BaseLLM
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from langchain_core.messages import BaseMessage, SystemMessage, HumanMessage, AIMessage, AIMessageChunk
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from apps.ai_model.model_factory import LLMConfig, LLMFactory, get_llm_config
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from apps.chat.curd.chat import save_question, save_full_sql_message, save_full_sql_message_and_answer, save_sql, \
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save_error_message, save_sql_exec_data, save_full_chart_message, save_full_chart_message_and_answer, save_chart, \
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finish_record
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from apps.chat.models.chat_model import ChatQuestion, ChatRecord
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from apps.datasource.models.datasource import CoreDatasource
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from apps.db.db import exec_sql
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from apps.system.models.system_model import AiModelDetail
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from common.core.deps import SessionDep, CurrentUser
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warnings.filterwarnings("ignore")
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base_message_count_limit = 5
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class LLMService:
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ds: CoreDatasource
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chat_question: ChatQuestion
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record: ChatRecord
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config: LLMConfig
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llm: BaseLLM
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sql_message: List[Union[BaseMessage, dict[str, Any]]] = []
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chart_message: List[Union[BaseMessage, dict[str, Any]]] = []
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def __init__(self, chat_question: ChatQuestion, history_records: List[ChatRecord],
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ds: CoreDatasource, aimodel: AiModelDetail):
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self.ds = ds
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self.chat_question = chat_question
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self.config = get_llm_config(aimodel)
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# Create LLM instance through factory
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llm_instance = LLMFactory.create_llm(self.config)
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self.llm = llm_instance.llm
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# self.agent_executor = create_react_agent(self.llm)
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last_sql_messages = list(
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filter(lambda r: True if r.full_sql_message is not None and r.full_sql_message.strip() != '' else False,
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history_records))
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last_sql_message_str = "[]" if last_sql_messages is None or len(last_sql_messages) == 0 else last_sql_messages[
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-1].full_sql_message
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last_chart_messages = list(
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filter(
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lambda r: True if r.full_chart_message is not None and r.full_chart_message.strip() != '' else False,
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history_records))
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last_chart_message_str = "[]" if last_chart_messages is None or len(last_chart_messages) == 0 else \
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last_chart_messages[-1].full_chart_message
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last_sql_messages: List[dict[str, Any]] = json.loads(last_sql_message_str)
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# todo maybe can configure
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count_limit = 0 - base_message_count_limit
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self.sql_message = []
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if last_sql_messages is None or len(last_sql_messages) == 0:
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# add sys prompt
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self.sql_message.append(SystemMessage(content=self.chat_question.sql_sys_question()))
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else:
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# limit count
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for last_sql_message in last_sql_messages:
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if last_sql_message['type'] == 'system':
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_msg = SystemMessage(content=last_sql_message['content'])
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self.sql_message.append(_msg)
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break
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for last_sql_message in last_sql_messages[count_limit:]:
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_msg: BaseMessage
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if last_sql_message['type'] == 'human':
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_msg = HumanMessage(content=last_sql_message['content'])
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self.sql_message.append(_msg)
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elif last_sql_message['type'] == 'ai':
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_msg = AIMessage(content=last_sql_message['content'])
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self.sql_message.append(_msg)
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last_chart_messages: List[dict[str, Any]] = json.loads(last_chart_message_str)
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self.chart_message = []
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if last_chart_messages is None or len(last_chart_messages) == 0:
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# add sys prompt
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self.chart_message.append(SystemMessage(content=self.chat_question.chart_sys_question()))
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else:
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# limit count
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for last_chart_message in last_chart_messages:
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if last_chart_message['type'] == 'system':
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_msg = SystemMessage(content=last_chart_message['content'])
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self.chart_message.append(_msg)
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break
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for last_chart_message in last_chart_messages:
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_msg: BaseMessage
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if last_chart_message['type'] == 'human':
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_msg = HumanMessage(content=last_chart_message['content'])
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self.chart_message.append(_msg)
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elif last_chart_message['type'] == 'ai':
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_msg = AIMessage(content=last_chart_message['content'])
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self.chart_message.append(_msg)
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def init_record(self, session: SessionDep, current_user: CurrentUser) -> ChatRecord:
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self.record = save_question(session=session, current_user=current_user, question=self.chat_question)
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return self.record
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def get_record(self):
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return self.record
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def generate_sql(self, session: SessionDep):
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# append current question
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self.sql_message.append(HumanMessage(self.chat_question.sql_user_question()))
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self.record = save_full_sql_message(session=session, record_id=self.record.id,
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full_message=json.dumps(
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[{'type': msg.type, 'content': msg.content} for msg in
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self.sql_message], ensure_ascii=False))
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full_sql_text = ''
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res = self.llm.stream(self.sql_message)
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for chunk in res:
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print(chunk)
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if isinstance(chunk, dict):
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full_sql_text += chunk['content']
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yield chunk['content']
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continue
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if isinstance(chunk, AIMessageChunk):
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full_sql_text += chunk.content
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yield chunk.content
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continue
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self.sql_message.append(AIMessage(full_sql_text))
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self.record = save_full_sql_message_and_answer(session=session, record_id=self.record.id,
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answer=full_sql_text,
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full_message=json.dumps(
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[{'type': msg.type, 'content': msg.content} for msg in
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self.sql_message], ensure_ascii=False))
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def generate_chart(self, session: SessionDep):
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# append current question
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self.chart_message.append(HumanMessage(self.chat_question.chart_user_question()))
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self.record = save_full_chart_message(session=session, record_id=self.record.id,
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full_message=json.dumps(
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[{'type': msg.type, 'content': msg.content} for msg in
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self.chart_message], ensure_ascii=False))
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full_chart_text = ''
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res = self.llm.stream(self.chart_message)
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for chunk in res:
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if isinstance(chunk, dict):
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full_chart_text += chunk['content']
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yield chunk['content']
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continue
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if isinstance(chunk, AIMessageChunk):
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full_chart_text += chunk.content
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yield chunk.content
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continue
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self.chart_message.append(AIMessage(full_chart_text))
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self.record = save_full_chart_message_and_answer(session=session, record_id=self.record.id,
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answer=full_chart_text,
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full_message=json.dumps(
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[{'type': msg.type, 'content': msg.content} for msg in
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self.chart_message], ensure_ascii=False))
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def check_save_sql(self, session: SessionDep, res: str) -> str:
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json_str = extract_nested_json(res)
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data = json.loads(json_str)
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sql = ''
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message = ''
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error = False
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if data['success']:
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sql = data['sql']
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else:
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message = data['message']
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error = True
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if error:
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raise Exception(message)
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if sql.strip() == '':
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raise Exception("SQL query is empty")
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save_sql(session=session, sql=sql, record_id=self.record.id)
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self.chat_question.sql = sql
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return sql
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def check_save_chart(self, session: SessionDep, res: str) -> Dict[str, Any]:
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json_str = extract_nested_json(res)
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data = json.loads(json_str)
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chart: Dict[str, Any] = {}
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message = ''
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error = False
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if data['type'] and data['type'] != 'error':
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# todo type check
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chart = data
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elif data['type'] == 'error':
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message = data['reason']
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error = True
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else:
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message = 'Chart is empty'
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error = True
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if error:
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raise Exception(message)
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save_chart(session=session, chart=json.dumps(chart, ensure_ascii=False), record_id=self.record.id)
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return chart
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def save_error(self, session: SessionDep, message: str):
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return save_error_message(session=session, record_id=self.record.id, message=message)
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def save_sql_data(self, session: SessionDep, data_obj: Dict[str, Any]):
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return save_sql_exec_data(session=session, record_id=self.record.id,
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data=json.dumps(data_obj, ensure_ascii=False))
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def finish(self, session: SessionDep):
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return finish_record(session=session, record_id=self.record.id)
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def execute_sql(self, sql: str):
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"""Execute SQL query
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Args:
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ds: Data source instance
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sql: SQL query statement
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Returns:
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Query results
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"""
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print(f"Executing SQL on ds_id {self.ds.id}: {sql}")
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return exec_sql(self.ds, sql)
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def extract_nested_json(text):
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stack = []
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start_index = -1
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results = []
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for i, char in enumerate(text):
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if char in '{[':
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if not stack: # 记录起始位置
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start_index = i
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stack.append(char)
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elif char in '}]':
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if stack and ((char == '}' and stack[-1] == '{') or (char == ']' and stack[-1] == '[')):
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stack.pop()
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if not stack: # 栈空时截取完整JSON
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json_str = text[start_index:i + 1]
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try:
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json.loads(json_str) # 验证有效性
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results.append(json_str)
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except:
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pass
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else:
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stack = [] # 括号不匹配则重置
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if len(results) > 0 and results[0]:
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return results[0]
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return None
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def execute_sql_with_db(db: SQLDatabase, sql: str) -> str:
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"""Execute SQL query using SQLDatabase
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Args:
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db: SQLDatabase instance
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sql: SQL query statement
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Returns:
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str: Query results formatted as string
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"""
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try:
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# Execute query
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result = db.run(sql)
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if not result:
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return "Query executed successfully but returned no results."
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# Format results
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return str(result)
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except Exception as e:
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error_msg = f"SQL execution failed: {str(e)}"
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logging.error(error_msg)
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raise RuntimeError(error_msg)
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