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import json |
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from typing import Optional, Union |
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from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfigManager |
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from core.app.entities.app_invoke_entities import InvokeFrom |
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from core.llm_generator.llm_generator import LLMGenerator |
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from core.memory.token_buffer_memory import TokenBufferMemory |
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from core.model_manager import ModelManager |
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from core.model_runtime.entities.model_entities import ModelType |
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from core.ops.entities.trace_entity import TraceTaskName |
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from core.ops.ops_trace_manager import TraceQueueManager, TraceTask |
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from core.ops.utils import measure_time |
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from extensions.ext_database import db |
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from libs.infinite_scroll_pagination import InfiniteScrollPagination |
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from models.account import Account |
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from models.model import App, AppMode, AppModelConfig, EndUser, Message, MessageFeedback |
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from services.conversation_service import ConversationService |
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from services.errors.conversation import ConversationCompletedError, ConversationNotExistsError |
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from services.errors.message import ( |
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FirstMessageNotExistsError, |
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LastMessageNotExistsError, |
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MessageNotExistsError, |
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SuggestedQuestionsAfterAnswerDisabledError, |
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) |
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from services.workflow_service import WorkflowService |
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class MessageService: |
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@classmethod |
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def pagination_by_first_id( |
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cls, |
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app_model: App, |
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user: Optional[Union[Account, EndUser]], |
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conversation_id: str, |
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first_id: Optional[str], |
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limit: int, |
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order: str = "asc", |
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) -> 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, user=user, conversation_id=conversation_id |
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) |
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if first_id: |
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first_message = ( |
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db.session.query(Message) |
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.filter(Message.conversation_id == conversation.id, Message.id == first_id) |
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.first() |
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) |
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if not first_message: |
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raise FirstMessageNotExistsError() |
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history_messages = ( |
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db.session.query(Message) |
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.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()) |
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.limit(limit) |
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.all() |
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) |
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else: |
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history_messages = ( |
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db.session.query(Message) |
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.filter(Message.conversation_id == conversation.id) |
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.order_by(Message.created_at.desc()) |
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.limit(limit) |
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.all() |
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) |
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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 = ( |
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db.session.query(Message) |
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.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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) |
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.count() |
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) |
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if rest_count > 0: |
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has_more = True |
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if order == "asc": |
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history_messages = list(reversed(history_messages)) |
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return InfiniteScrollPagination(data=history_messages, limit=limit, has_more=has_more) |
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@classmethod |
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def pagination_by_last_id( |
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cls, |
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app_model: App, |
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user: Optional[Union[Account, EndUser]], |
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last_id: Optional[str], |
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limit: int, |
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conversation_id: Optional[str] = None, |
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include_ids: Optional[list] = None, |
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) -> 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, user=user, 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 = ( |
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base_query.filter(Message.created_at < last_message.created_at, Message.id != last_message.id) |
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.order_by(Message.created_at.desc()) |
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.limit(limit) |
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.all() |
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) |
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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, 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(data=history_messages, limit=limit, has_more=has_more) |
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@classmethod |
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def create_feedback( |
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cls, app_model: App, message_id: str, user: Optional[Union[Account, EndUser]], rating: Optional[str] |
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) -> 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(app_model=app_model, user=user, message_id=message_id) |
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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 = ( |
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db.session.query(Message) |
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.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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) |
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.first() |
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) |
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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( |
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cls, app_model: App, user: Optional[Union[Account, EndUser]], message_id: str, invoke_from: InvokeFrom |
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) -> list[Message]: |
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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(app_model=app_model, user=user, message_id=message_id) |
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conversation = ConversationService.get_conversation( |
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app_model=app_model, conversation_id=message.conversation_id, user=user |
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) |
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if not conversation: |
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raise ConversationNotExistsError() |
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if conversation.status != "normal": |
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raise ConversationCompletedError() |
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model_manager = ModelManager() |
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if app_model.mode == AppMode.ADVANCED_CHAT.value: |
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workflow_service = WorkflowService() |
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if invoke_from == InvokeFrom.DEBUGGER: |
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workflow = workflow_service.get_draft_workflow(app_model=app_model) |
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else: |
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workflow = workflow_service.get_published_workflow(app_model=app_model) |
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if workflow is None: |
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return [] |
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app_config = AdvancedChatAppConfigManager.get_app_config(app_model=app_model, workflow=workflow) |
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if not app_config.additional_features.suggested_questions_after_answer: |
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raise SuggestedQuestionsAfterAnswerDisabledError() |
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model_instance = model_manager.get_default_model_instance( |
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tenant_id=app_model.tenant_id, model_type=ModelType.LLM |
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) |
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else: |
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if not conversation.override_model_configs: |
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app_model_config = ( |
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db.session.query(AppModelConfig) |
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.filter( |
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AppModelConfig.id == conversation.app_model_config_id, AppModelConfig.app_id == app_model.id |
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) |
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.first() |
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) |
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else: |
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conversation_override_model_configs = json.loads(conversation.override_model_configs) |
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app_model_config = AppModelConfig( |
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id=conversation.app_model_config_id, |
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app_id=app_model.id, |
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) |
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app_model_config = app_model_config.from_model_config_dict(conversation_override_model_configs) |
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suggested_questions_after_answer = app_model_config.suggested_questions_after_answer_dict |
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if suggested_questions_after_answer.get("enabled", False) is False: |
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raise SuggestedQuestionsAfterAnswerDisabledError() |
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model_instance = model_manager.get_model_instance( |
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tenant_id=app_model.tenant_id, |
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provider=app_model_config.model_dict["provider"], |
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model_type=ModelType.LLM, |
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model=app_model_config.model_dict["name"], |
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) |
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memory = TokenBufferMemory(conversation=conversation, model_instance=model_instance) |
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histories = memory.get_history_prompt_text( |
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max_token_limit=3000, |
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message_limit=3, |
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) |
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with measure_time() as timer: |
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questions = LLMGenerator.generate_suggested_questions_after_answer( |
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tenant_id=app_model.tenant_id, histories=histories |
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) |
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trace_manager = TraceQueueManager(app_id=app_model.id) |
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trace_manager.add_trace_task( |
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TraceTask( |
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TraceTaskName.SUGGESTED_QUESTION_TRACE, message_id=message_id, suggested_question=questions, timer=timer |
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) |
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) |
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return questions |
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