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https://github.com/langgenius/dify.git
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refactor: tool engine
This commit is contained in:
Yeuoly
@ -10,12 +10,10 @@ from core.app.apps.base_app_queue_manager import AppQueueManager
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from core.app.apps.base_app_runner import AppRunner
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from core.app.entities.app_invoke_entities import (
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AgentChatAppGenerateEntity,
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InvokeFrom,
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ModelConfigWithCredentialsEntity,
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)
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from core.callback_handler.agent_tool_callback_handler import DifyAgentCallbackHandler
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from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
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from core.file.message_file_parser import FileTransferMethod
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from core.memory.token_buffer_memory import TokenBufferMemory
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from core.model_manager import ModelInstance
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from core.model_runtime.entities.llm_entities import LLMUsage
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@ -32,7 +30,6 @@ from core.model_runtime.model_providers.__base.large_language_model import Large
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from core.model_runtime.utils.encoders import jsonable_encoder
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from core.tools.entities.tool_entities import (
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ToolInvokeMessage,
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ToolInvokeMessageBinary,
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ToolParameter,
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ToolRuntimeVariablePool,
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)
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@ -40,7 +37,7 @@ from core.tools.tool.dataset_retriever_tool import DatasetRetrieverTool
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from core.tools.tool.tool import Tool
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from core.tools.tool_manager import ToolManager
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from extensions.ext_database import db
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from models.model import Message, MessageAgentThought, MessageFile
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from models.model import Message, MessageAgentThought
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from models.tools import ToolConversationVariables
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logger = logging.getLogger(__name__)
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@ -156,7 +153,6 @@ class BaseAgentRunner(AppRunner):
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tool_entity = ToolManager.get_agent_tool_runtime(
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tenant_id=self.tenant_id,
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agent_tool=tool,
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agent_callback=self.agent_callback
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)
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tool_entity.load_variables(self.variables_pool)
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@ -270,87 +266,6 @@ class BaseAgentRunner(AppRunner):
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prompt_tool.parameters['required'].append(parameter.name)
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return prompt_tool
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def extract_tool_response_binary(self, tool_response: list[ToolInvokeMessage]) -> list[ToolInvokeMessageBinary]:
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"""
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Extract tool response binary
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"""
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result = []
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for response in tool_response:
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if response.type == ToolInvokeMessage.MessageType.IMAGE_LINK or \
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response.type == ToolInvokeMessage.MessageType.IMAGE:
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result.append(ToolInvokeMessageBinary(
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mimetype=response.meta.get('mime_type', 'octet/stream'),
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url=response.message,
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save_as=response.save_as,
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))
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elif response.type == ToolInvokeMessage.MessageType.BLOB:
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result.append(ToolInvokeMessageBinary(
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mimetype=response.meta.get('mime_type', 'octet/stream'),
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url=response.message,
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save_as=response.save_as,
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))
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elif response.type == ToolInvokeMessage.MessageType.LINK:
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# check if there is a mime type in meta
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if response.meta and 'mime_type' in response.meta:
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result.append(ToolInvokeMessageBinary(
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mimetype=response.meta.get('mime_type', 'octet/stream') if response.meta else 'octet/stream',
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url=response.message,
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save_as=response.save_as,
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))
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return result
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def create_message_files(self, messages: list[ToolInvokeMessageBinary]) -> list[tuple[MessageFile, bool]]:
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"""
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Create message file
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:param messages: messages
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:return: message files, should save as variable
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"""
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result = []
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for message in messages:
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file_type = 'bin'
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if 'image' in message.mimetype:
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file_type = 'image'
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elif 'video' in message.mimetype:
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file_type = 'video'
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elif 'audio' in message.mimetype:
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file_type = 'audio'
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elif 'text' in message.mimetype:
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file_type = 'text'
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elif 'pdf' in message.mimetype:
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file_type = 'pdf'
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elif 'zip' in message.mimetype:
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file_type = 'archive'
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# ...
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invoke_from = self.application_generate_entity.invoke_from
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message_file = MessageFile(
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message_id=self.message.id,
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type=file_type,
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transfer_method=FileTransferMethod.TOOL_FILE.value,
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belongs_to='assistant',
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url=message.url,
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upload_file_id=None,
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created_by_role=('account'if invoke_from in [InvokeFrom.EXPLORE, InvokeFrom.DEBUGGER] else 'end_user'),
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created_by=self.user_id,
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)
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db.session.add(message_file)
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db.session.commit()
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db.session.refresh(message_file)
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result.append((
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message_file,
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message.save_as
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))
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db.session.close()
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return result
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def create_agent_thought(self, message_id: str, message: str,
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tool_name: str, tool_input: str, messages_ids: list[str]
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@ -500,8 +415,12 @@ class BaseAgentRunner(AppRunner):
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try:
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tool_inputs = json.loads(agent_thought.tool_input)
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except Exception as e:
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logging.warning("tool execution error: {}, tool_input: {}.".format(str(e), agent_thought.tool_input))
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tool_inputs = { agent_thought.tool: agent_thought.tool_input }
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tool_inputs = { tool: {} for tool in tools }
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try:
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tool_responses = json.loads(agent_thought.observation)
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except Exception as e:
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tool_responses = { tool: agent_thought.observation for tool in tools }
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for tool in tools:
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# generate a uuid for tool call
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tool_call_id = str(uuid.uuid4())
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@ -514,7 +433,7 @@ class BaseAgentRunner(AppRunner):
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)
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))
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tool_call_response.append(ToolPromptMessage(
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content=agent_thought.observation,
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content=tool_responses.get(tool, agent_thought.observation),
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name=tool,
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tool_call_id=tool_call_id,
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))
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