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https://github.com/langgenius/dify.git
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Merge branch 'main' into feat/memory-orchestration-be
# Conflicts: # api/core/app/apps/advanced_chat/app_runner.py # api/core/prompt/entities/advanced_prompt_entities.py # api/core/variables/segments.py
This commit is contained in:
Stream
@ -1,5 +1,4 @@
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from collections.abc import Sequence
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from typing import Optional
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from sqlalchemy import select
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@ -27,12 +26,76 @@ class TokenBufferMemory:
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self,
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conversation: Conversation,
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model_instance: ModelInstance,
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) -> None:
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):
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self.conversation = conversation
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self.model_instance = model_instance
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def _build_prompt_message_with_files(
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self,
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message_files: Sequence[MessageFile],
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text_content: str,
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message: Message,
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app_record,
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is_user_message: bool,
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) -> PromptMessage:
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"""
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Build prompt message with files.
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:param message_files: Sequence of MessageFile objects
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:param text_content: text content of the message
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:param message: Message object
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:param app_record: app record
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:param is_user_message: whether this is a user message
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:return: PromptMessage
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"""
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if self.conversation.mode in {AppMode.AGENT_CHAT, AppMode.COMPLETION, AppMode.CHAT}:
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file_extra_config = FileUploadConfigManager.convert(self.conversation.model_config)
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elif self.conversation.mode in {AppMode.ADVANCED_CHAT, AppMode.WORKFLOW}:
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workflow_run = db.session.scalar(select(WorkflowRun).where(WorkflowRun.id == message.workflow_run_id))
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if not workflow_run:
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raise ValueError(f"Workflow run not found: {message.workflow_run_id}")
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workflow = db.session.scalar(select(Workflow).where(Workflow.id == workflow_run.workflow_id))
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if not workflow:
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raise ValueError(f"Workflow not found: {workflow_run.workflow_id}")
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file_extra_config = FileUploadConfigManager.convert(workflow.features_dict, is_vision=False)
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else:
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raise AssertionError(f"Invalid app mode: {self.conversation.mode}")
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detail = ImagePromptMessageContent.DETAIL.HIGH
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if file_extra_config and app_record:
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# Build files directly without filtering by belongs_to
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file_objs = [
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file_factory.build_from_message_file(
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message_file=message_file, tenant_id=app_record.tenant_id, config=file_extra_config
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)
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for message_file in message_files
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]
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if file_extra_config.image_config and file_extra_config.image_config.detail:
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detail = file_extra_config.image_config.detail
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else:
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file_objs = []
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if not file_objs:
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if is_user_message:
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return UserPromptMessage(content=text_content)
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else:
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return AssistantPromptMessage(content=text_content)
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else:
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prompt_message_contents: list[PromptMessageContentUnionTypes] = []
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for file in file_objs:
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prompt_message = file_manager.to_prompt_message_content(
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file,
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image_detail_config=detail,
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)
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prompt_message_contents.append(prompt_message)
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prompt_message_contents.append(TextPromptMessageContent(data=text_content))
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if is_user_message:
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return UserPromptMessage(content=prompt_message_contents)
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else:
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return AssistantPromptMessage(content=prompt_message_contents)
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def get_history_prompt_messages(
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self, max_token_limit: int = 2000, message_limit: Optional[int] = None
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self, max_token_limit: int = 2000, message_limit: int | None = None
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) -> Sequence[PromptMessage]:
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"""
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Get history prompt messages.
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@ -51,9 +114,9 @@ class TokenBufferMemory:
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else:
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message_limit = 500
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stmt = stmt.limit(message_limit)
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msg_limit_stmt = stmt.limit(message_limit)
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messages = db.session.scalars(stmt).all()
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messages = db.session.scalars(msg_limit_stmt).all()
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# instead of all messages from the conversation, we only need to extract messages
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# that belong to the thread of last message
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@ -65,54 +128,45 @@ class TokenBufferMemory:
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messages = list(reversed(thread_messages))
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curr_message_tokens = 0
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prompt_messages: list[PromptMessage] = []
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for message in messages:
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files = db.session.query(MessageFile).where(MessageFile.message_id == message.id).all()
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if files:
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file_extra_config = None
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if self.conversation.mode in {AppMode.AGENT_CHAT, AppMode.COMPLETION, AppMode.CHAT}:
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file_extra_config = FileUploadConfigManager.convert(self.conversation.model_config)
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elif self.conversation.mode in {AppMode.ADVANCED_CHAT, AppMode.WORKFLOW}:
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workflow_run = db.session.scalar(
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select(WorkflowRun).where(WorkflowRun.id == message.workflow_run_id)
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)
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if not workflow_run:
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raise ValueError(f"Workflow run not found: {message.workflow_run_id}")
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workflow = db.session.scalar(select(Workflow).where(Workflow.id == workflow_run.workflow_id))
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if not workflow:
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raise ValueError(f"Workflow not found: {workflow_run.workflow_id}")
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file_extra_config = FileUploadConfigManager.convert(workflow.features_dict, is_vision=False)
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else:
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raise AssertionError(f"Invalid app mode: {self.conversation.mode}")
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detail = ImagePromptMessageContent.DETAIL.LOW
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if file_extra_config and app_record:
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file_objs = file_factory.build_from_message_files(
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message_files=files, tenant_id=app_record.tenant_id, config=file_extra_config
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)
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if file_extra_config.image_config and file_extra_config.image_config.detail:
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detail = file_extra_config.image_config.detail
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else:
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file_objs = []
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if not file_objs:
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prompt_messages.append(UserPromptMessage(content=message.query))
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else:
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prompt_message_contents: list[PromptMessageContentUnionTypes] = []
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for file in file_objs:
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prompt_message = file_manager.to_prompt_message_content(
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file,
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image_detail_config=detail,
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)
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prompt_message_contents.append(prompt_message)
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prompt_message_contents.append(TextPromptMessageContent(data=message.query))
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prompt_messages.append(UserPromptMessage(content=prompt_message_contents))
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# Process user message with files
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user_files = db.session.scalars(
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select(MessageFile).where(
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MessageFile.message_id == message.id,
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(MessageFile.belongs_to == "user") | (MessageFile.belongs_to.is_(None)),
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)
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).all()
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if user_files:
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user_prompt_message = self._build_prompt_message_with_files(
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message_files=user_files,
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text_content=message.query,
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message=message,
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app_record=app_record,
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is_user_message=True,
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)
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prompt_messages.append(user_prompt_message)
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else:
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prompt_messages.append(UserPromptMessage(content=message.query))
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prompt_messages.append(AssistantPromptMessage(content=message.answer))
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# Process assistant message with files
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assistant_files = db.session.scalars(
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select(MessageFile).where(MessageFile.message_id == message.id, MessageFile.belongs_to == "assistant")
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).all()
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if assistant_files:
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assistant_prompt_message = self._build_prompt_message_with_files(
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message_files=assistant_files,
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text_content=message.answer,
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message=message,
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app_record=app_record,
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is_user_message=False,
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)
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prompt_messages.append(assistant_prompt_message)
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else:
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prompt_messages.append(AssistantPromptMessage(content=message.answer))
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if not prompt_messages:
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return []
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@ -132,7 +186,7 @@ class TokenBufferMemory:
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human_prefix: str = "Human",
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ai_prefix: str = "Assistant",
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max_token_limit: int = 2000,
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message_limit: Optional[int] = None,
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message_limit: int | None = None,
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) -> str:
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"""
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Get history prompt text.
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