mirror of
https://github.com/1Panel-dev/MaxKB.git
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291 lines
14 KiB
Python
291 lines
14 KiB
Python
# coding=utf-8
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"""
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@project: MaxKB
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@Author：虎虎
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@file： common.py
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@date：2025/6/9 13:42
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@desc:
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"""
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from typing import List
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from django.core.cache import cache
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from django.db.models import QuerySet
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from django.utils.translation import gettext_lazy as _
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from django.utils import timezone
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from application.chat_pipeline.step.chat_step.i_chat_step import PostResponseHandler
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from application.models import Application, ChatRecord, Chat, ApplicationVersion, ChatUserType, ApplicationTypeChoices, \
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ApplicationKnowledgeMapping
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from application.serializers.application_chat import ChatCountSerializer
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from common.constants.cache_version import Cache_Version
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from common.database_model_manage.database_model_manage import DatabaseModelManage
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from common.exception.app_exception import ChatException
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from knowledge.models import Document
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from models_provider.models import Model
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from models_provider.tools import get_model_credential
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class ChatInfo:
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def __init__(self,
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chat_id: str,
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chat_user_id: str,
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chat_user_type: str,
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knowledge_id_list: List[str],
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exclude_document_id_list: list[str],
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application_id: str,
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debug=False):
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"""
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:param chat_id: 对话id
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:param chat_user_id 对话用户id
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:param chat_user_type 对话用户类型
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:param knowledge_id_list: 知识库列表
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:param exclude_document_id_list: 排除的文档
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:param application_id 应用id
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:param debug 是否是调试
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"""
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self.chat_id = chat_id
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self.chat_user_id = chat_user_id
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self.chat_user_type = chat_user_type
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self.knowledge_id_list = knowledge_id_list
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self.exclude_document_id_list = exclude_document_id_list
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self.application_id = application_id
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self.chat_record_list: List[ChatRecord] = []
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self.application = None
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self.chat_user = None
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self.debug = debug
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@staticmethod
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def get_no_references_setting(knowledge_setting, model_setting):
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no_references_setting = knowledge_setting.get(
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'no_references_setting', {
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'status': 'ai_questioning',
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'value': '{question}'})
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if no_references_setting.get('status') == 'ai_questioning':
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no_references_prompt = model_setting.get('no_references_prompt', '{question}')
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no_references_setting['value'] = no_references_prompt if len(no_references_prompt) > 0 else "{question}"
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return no_references_setting
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def get_application(self):
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if self.debug:
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application = QuerySet(Application).filter(id=self.application_id).first()
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if not application:
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raise ChatException(500, _('The application does not exist'))
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else:
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application = QuerySet(ApplicationVersion).filter(application_id=self.application_id).order_by(
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'-create_time')[0:1].first()
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if not application:
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raise ChatException(500, _("The application has not been published. Please use it after publishing."))
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if application.type == ApplicationTypeChoices.SIMPLE.value:
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# 数据集id列表
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knowledge_id_list = [str(row.knowledge_id) for row in
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QuerySet(ApplicationKnowledgeMapping).filter(
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application_id=self.application_id)]
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# 需要排除的文档
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exclude_document_id_list = [str(document.id) for document in
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QuerySet(Document).filter(
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knowledge_id__in=knowledge_id_list,
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is_active=False)]
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self.knowledge_id_list = knowledge_id_list
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self.exclude_document_id_list = exclude_document_id_list
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self.application = application
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return application
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def get_chat_user(self, asker=None):
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if self.chat_user:
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return self.chat_user
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chat_user_model = DatabaseModelManage.get_model("chat_user")
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if self.chat_user_type == ChatUserType.CHAT_USER.value and chat_user_model:
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chat_user = QuerySet(chat_user_model).filter(id=self.chat_user_id).first()
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return {
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'id': str(chat_user.id),
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'email': chat_user.email,
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'phone': chat_user.phone,
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'nick_name': chat_user.nick_name,
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'username': chat_user.username,
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'source': chat_user.source
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}
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else:
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if asker:
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if isinstance(asker, dict):
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self.chat_user = asker
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else:
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self.chat_user = {'username': asker}
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else:
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self.chat_user = {'username': '游客'}
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return self.chat_user
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def to_base_pipeline_manage_params(self):
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self.get_application()
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self.get_chat_user()
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knowledge_setting = self.application.knowledge_setting
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model_setting = self.application.model_setting
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model_id = self.application.model_id
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model_params_setting = None
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if model_id is not None:
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model = QuerySet(Model).filter(id=model_id).first()
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credential = get_model_credential(model.provider, model.model_type, model.model_name)
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model_params_setting = credential.get_model_params_setting_form(model.model_name).get_default_form_data()
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return {
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'knowledge_id_list': self.knowledge_id_list,
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'exclude_document_id_list': self.exclude_document_id_list,
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'exclude_paragraph_id_list': [],
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'top_n': 3 if knowledge_setting.get('top_n') is None else knowledge_setting.get('top_n'),
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'similarity': 0.6 if knowledge_setting.get('similarity') is None else knowledge_setting.get('similarity'),
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'max_paragraph_char_number': knowledge_setting.get('max_paragraph_char_number') or 5000,
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'history_chat_record': self.chat_record_list,
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'chat_id': self.chat_id,
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'dialogue_number': self.application.dialogue_number,
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'problem_optimization_prompt': self.application.problem_optimization_prompt if self.application.problem_optimization_prompt is not None and len(
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self.application.problem_optimization_prompt) > 0 else _(
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"() contains the user's question. Answer the guessed user's question based on the context ({question}) Requirement: Output a complete question and put it in the <data></data> tag"),
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'prompt': model_setting.get(
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'prompt') if 'prompt' in model_setting and len(model_setting.get(
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'prompt')) > 0 else Application.get_default_model_prompt(),
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'system': model_setting.get(
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'system', None),
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'model_id': model_id,
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'problem_optimization': self.application.problem_optimization,
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'stream': True,
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'model_setting': model_setting,
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'model_params_setting': model_params_setting if self.application.model_params_setting is None or len(
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self.application.model_params_setting.keys()) == 0 else self.application.model_params_setting,
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'search_mode': self.application.knowledge_setting.get('search_mode') or 'embedding',
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'no_references_setting': self.get_no_references_setting(self.application.knowledge_setting, model_setting),
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'workspace_id': self.application.workspace_id,
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'application_id': self.application_id,
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'mcp_enable': self.application.mcp_enable,
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'mcp_tool_ids': self.application.mcp_tool_ids,
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'mcp_servers': self.application.mcp_servers,
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'mcp_source': self.application.mcp_source,
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'tool_enable': self.application.tool_enable,
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'tool_ids': self.application.tool_ids,
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'mcp_output_enable': self.application.mcp_output_enable,
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}
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def to_pipeline_manage_params(self, problem_text: str, post_response_handler: PostResponseHandler,
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exclude_paragraph_id_list, chat_user_id: str, chat_user_type, stream=True,
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form_data=None):
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if form_data is None:
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form_data = {}
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params = self.to_base_pipeline_manage_params()
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return {**params, 'problem_text': problem_text, 'post_response_handler': post_response_handler,
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'exclude_paragraph_id_list': exclude_paragraph_id_list, 'stream': stream, 'chat_user_id': chat_user_id,
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'chat_user_type': chat_user_type, 'form_data': form_data}
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def set_chat(self, question):
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if not self.debug:
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if not QuerySet(Chat).filter(id=self.chat_id).exists():
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Chat(id=self.chat_id, application_id=self.application_id, abstract=question[0:1024],
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chat_user_id=self.chat_user_id, chat_user_type=self.chat_user_type,
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asker=self.get_chat_user()).save()
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def set_chat_variable(self, chat_context):
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if not self.debug:
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chat = QuerySet(Chat).filter(id=self.chat_id).first()
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if chat:
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chat.meta = {**(chat.meta if isinstance(chat.meta, dict) else {}), **chat_context}
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chat.save()
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else:
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cache.set(Cache_Version.CHAT_VARIABLE.get_key(key=self.chat_id), chat_context,
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version=Cache_Version.CHAT_VARIABLE.get_version(),
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timeout=60 * 30)
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def get_chat_variable(self):
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if not self.debug:
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chat = QuerySet(Chat).filter(id=self.chat_id).first()
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if chat:
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return chat.meta
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return {}
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else:
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return cache.get(Cache_Version.CHAT_VARIABLE.get_key(key=self.chat_id),
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version=Cache_Version.CHAT_VARIABLE.get_version()) or {}
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def append_chat_record(self, chat_record: ChatRecord):
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chat_record.problem_text = chat_record.problem_text[0:10240] if chat_record.problem_text is not None else ""
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chat_record.answer_text = chat_record.answer_text[0:40960] if chat_record.problem_text is not None else ""
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is_save = True
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# 存入缓存中
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for index in range(len(self.chat_record_list)):
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record = self.chat_record_list[index]
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if record.id == chat_record.id:
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self.chat_record_list[index] = chat_record
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is_save = False
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break
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if is_save:
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self.chat_record_list.append(chat_record)
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if not self.debug:
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if not QuerySet(Chat).filter(id=self.chat_id).exists():
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Chat(id=self.chat_id, application_id=self.application_id, abstract=chat_record.problem_text[0:1024],
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chat_user_id=self.chat_user_id, chat_user_type=self.chat_user_type,
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asker=self.get_chat_user()).save()
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else:
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QuerySet(Chat).filter(id=self.chat_id).update(update_time=timezone.now())
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# 插入会话记录
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chat_record.save()
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ChatCountSerializer(data={'chat_id': self.chat_id}).update_chat()
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def to_dict(self):
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return {
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'chat_id': self.chat_id,
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'chat_user_id': self.chat_user_id,
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'chat_user_type': self.chat_user_type,
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'knowledge_id_list': self.knowledge_id_list,
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'exclude_document_id_list': self.exclude_document_id_list,
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'application_id': self.application_id,
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'chat_record_list': [self.chat_record_to_map(c) for c in self.chat_record_list],
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'debug': self.debug
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}
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def chat_record_to_map(self, chat_record):
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return {'id': chat_record.id,
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'chat_id': chat_record.chat_id,
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'vote_status': chat_record.vote_status,
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'problem_text': chat_record.problem_text,
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'answer_text': chat_record.answer_text,
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'answer_text_list': chat_record.answer_text_list,
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'message_tokens': chat_record.message_tokens,
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'answer_tokens': chat_record.answer_tokens,
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'const': chat_record.const,
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'details': chat_record.details,
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'improve_paragraph_id_list': chat_record.improve_paragraph_id_list,
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'run_time': chat_record.run_time,
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'index': chat_record.index}
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@staticmethod
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def map_to_chat_record(chat_record_dict):
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ChatRecord(id=chat_record_dict.get('id'),
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chat_id=chat_record_dict.get('chat_id'),
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vote_status=chat_record_dict.get('vote_status'),
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problem_text=chat_record_dict.get('problem_text'),
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answer_text=chat_record_dict.get('answer_text'),
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answer_text_list=chat_record_dict.get('answer_text_list'),
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message_tokens=chat_record_dict.get('message_tokens'),
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answer_tokens=chat_record_dict.get('answer_tokens'),
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const=chat_record_dict.get('const'),
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details=chat_record_dict.get('details'),
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improve_paragraph_id_list=chat_record_dict.get('improve_paragraph_id_list'),
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run_time=chat_record_dict.get('run_time'),
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index=chat_record_dict.get('index'), )
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def set_cache(self):
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cache.set(Cache_Version.CHAT.get_key(key=self.chat_id), self.to_dict(),
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version=Cache_Version.CHAT_INFO.get_version(),
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timeout=60 * 30)
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@staticmethod
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def map_to_chat_info(chat_info_dict):
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return ChatInfo(chat_info_dict.get('chat_id'), chat_info_dict.get('chat_user_id'),
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chat_info_dict.get('chat_user_type'), chat_info_dict.get('knowledge_id_list'),
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chat_info_dict.get('exclude_document_id_list'),
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chat_info_dict.get('application_id'),
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[ChatInfo.map_to_chat_record(c_r) for c_r in chat_info_dict.get('chat_record_list')])
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@staticmethod
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def get_cache(chat_id):
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chat_info_dict = cache.get(Cache_Version.CHAT.get_key(key=chat_id), version=Cache_Version.CHAT_INFO.get_version())
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if chat_info_dict:
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return ChatInfo.map_to_chat_info(chat_info_dict)
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return None
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