mirror of
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213 lines
8.0 KiB
Python
213 lines
8.0 KiB
Python
from typing import Optional, Union, List
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from core.completion import Completion
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from core.generator.llm_generator import LLMGenerator
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from libs.infinite_scroll_pagination import InfiniteScrollPagination
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from extensions.ext_database import db
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from models.account import Account
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from models.model import App, EndUser, Message, MessageFeedback
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from services.conversation_service import ConversationService
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from services.errors.message import FirstMessageNotExistsError, MessageNotExistsError, LastMessageNotExistsError, \
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SuggestedQuestionsAfterAnswerDisabledError
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class MessageService:
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@classmethod
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def pagination_by_first_id(cls, app_model: App, user: Optional[Union[Account | EndUser]],
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conversation_id: str, first_id: Optional[str], limit: int) -> InfiniteScrollPagination:
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if not user:
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return InfiniteScrollPagination(data=[], limit=limit, has_more=False)
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if not conversation_id:
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return InfiniteScrollPagination(data=[], limit=limit, has_more=False)
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conversation = ConversationService.get_conversation(
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app_model=app_model,
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user=user,
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conversation_id=conversation_id
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)
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if first_id:
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first_message = db.session.query(Message) \
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.filter(Message.conversation_id == conversation.id, Message.id == first_id).first()
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if not first_message:
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raise FirstMessageNotExistsError()
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history_messages = db.session.query(Message).filter(
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Message.conversation_id == conversation.id,
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Message.created_at < first_message.created_at,
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Message.id != first_message.id
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) \
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.order_by(Message.created_at.desc()).limit(limit).all()
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else:
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history_messages = db.session.query(Message).filter(Message.conversation_id == conversation.id) \
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.order_by(Message.created_at.desc()).limit(limit).all()
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has_more = False
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if len(history_messages) == limit:
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current_page_first_message = history_messages[-1]
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rest_count = db.session.query(Message).filter(
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Message.conversation_id == conversation.id,
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Message.created_at < current_page_first_message.created_at,
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Message.id != current_page_first_message.id
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).count()
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if rest_count > 0:
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has_more = True
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history_messages = list(reversed(history_messages))
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return InfiniteScrollPagination(
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data=history_messages,
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limit=limit,
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has_more=has_more
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)
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@classmethod
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def pagination_by_last_id(cls, app_model: App, user: Optional[Union[Account | EndUser]],
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last_id: Optional[str], limit: int, conversation_id: Optional[str] = None,
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include_ids: Optional[list] = None) -> InfiniteScrollPagination:
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if not user:
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return InfiniteScrollPagination(data=[], limit=limit, has_more=False)
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base_query = db.session.query(Message)
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if conversation_id is not None:
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conversation = ConversationService.get_conversation(
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app_model=app_model,
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user=user,
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conversation_id=conversation_id
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)
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base_query = base_query.filter(Message.conversation_id == conversation.id)
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if include_ids is not None:
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base_query = base_query.filter(Message.id.in_(include_ids))
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if last_id:
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last_message = base_query.filter(Message.id == last_id).first()
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if not last_message:
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raise LastMessageNotExistsError()
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history_messages = base_query.filter(
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Message.created_at < last_message.created_at,
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Message.id != last_message.id
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).order_by(Message.created_at.desc()).limit(limit).all()
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else:
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history_messages = base_query.order_by(Message.created_at.desc()).limit(limit).all()
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has_more = False
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if len(history_messages) == limit:
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current_page_first_message = history_messages[-1]
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rest_count = base_query.filter(
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Message.created_at < current_page_first_message.created_at,
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Message.id != current_page_first_message.id
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).count()
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if rest_count > 0:
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has_more = True
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return InfiniteScrollPagination(
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data=history_messages,
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limit=limit,
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has_more=has_more
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)
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@classmethod
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def create_feedback(cls, app_model: App, message_id: str, user: Optional[Union[Account | EndUser]],
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rating: Optional[str]) -> MessageFeedback:
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if not user:
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raise ValueError('user cannot be None')
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message = cls.get_message(
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app_model=app_model,
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user=user,
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message_id=message_id
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)
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feedback = message.user_feedback if isinstance(user, EndUser) else message.admin_feedback
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if not rating and feedback:
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db.session.delete(feedback)
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elif rating and feedback:
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feedback.rating = rating
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elif not rating and not feedback:
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raise ValueError('rating cannot be None when feedback not exists')
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else:
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feedback = MessageFeedback(
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app_id=app_model.id,
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conversation_id=message.conversation_id,
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message_id=message.id,
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rating=rating,
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from_source=('user' if isinstance(user, EndUser) else 'admin'),
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from_end_user_id=(user.id if isinstance(user, EndUser) else None),
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from_account_id=(user.id if isinstance(user, Account) else None),
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)
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db.session.add(feedback)
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db.session.commit()
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return feedback
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@classmethod
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def get_message(cls, app_model: App, user: Optional[Union[Account | EndUser]], message_id: str):
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message = db.session.query(Message).filter(
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Message.id == message_id,
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Message.app_id == app_model.id,
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Message.from_source == ('api' if isinstance(user, EndUser) else 'console'),
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Message.from_end_user_id == (user.id if isinstance(user, EndUser) else None),
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Message.from_account_id == (user.id if isinstance(user, Account) else None),
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).first()
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if not message:
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raise MessageNotExistsError()
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return message
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@classmethod
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def get_suggested_questions_after_answer(cls, app_model: App, user: Optional[Union[Account | EndUser]],
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message_id: str, check_enabled: bool = True) -> List[Message]:
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if not user:
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raise ValueError('user cannot be None')
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app_model_config = app_model.app_model_config
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suggested_questions_after_answer = app_model_config.suggested_questions_after_answer_dict
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if check_enabled and suggested_questions_after_answer.get("enabled", False) is False:
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raise SuggestedQuestionsAfterAnswerDisabledError()
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message = cls.get_message(
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app_model=app_model,
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user=user,
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message_id=message_id
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)
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conversation = ConversationService.get_conversation(
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app_model=app_model,
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conversation_id=message.conversation_id,
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user=user
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)
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# get memory of conversation (read-only)
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memory = Completion.get_memory_from_conversation(
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tenant_id=app_model.tenant_id,
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app_model_config=app_model.app_model_config,
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conversation=conversation,
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max_token_limit=3000,
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message_limit=3,
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return_messages=False,
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memory_key="histories"
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)
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external_context = memory.load_memory_variables({})
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questions = LLMGenerator.generate_suggested_questions_after_answer(
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tenant_id=app_model.tenant_id,
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**external_context
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)
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return questions
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