diff --git a/api/controllers/console/__init__.py b/api/controllers/console/__init__.py index 29eac070a08fcb..8c67fef95f5f4c 100644 --- a/api/controllers/console/__init__.py +++ b/api/controllers/console/__init__.py @@ -20,6 +20,7 @@ generator, message, model_config, + ops_trace, site, statistic, workflow, diff --git a/api/controllers/console/app/app.py b/api/controllers/console/app/app.py index 082838334ae040..1a38bcba7e48e3 100644 --- a/api/controllers/console/app/app.py +++ b/api/controllers/console/app/app.py @@ -1,4 +1,3 @@ -import json import uuid from flask_login import current_user @@ -9,17 +8,14 @@ from controllers.console.app.wraps import get_app_model from controllers.console.setup import setup_required from controllers.console.wraps import account_initialization_required, cloud_edition_billing_resource_check -from core.tools.tool_manager import ToolManager -from core.tools.utils.configuration import ToolParameterConfigurationManager +from core.ops.ops_trace_manager import OpsTraceManager from fields.app_fields import ( app_detail_fields, app_detail_fields_with_site, app_pagination_fields, ) from libs.login import login_required -from models.model import App, AppMode, AppModelConfig from services.app_service import AppService -from services.tag_service import TagService ALLOW_CREATE_APP_MODES = ['chat', 'agent-chat', 'advanced-chat', 'workflow', 'completion'] @@ -286,6 +282,39 @@ def post(self, app_model): return app_model +class AppTraceApi(Resource): + @setup_required + @login_required + @account_initialization_required + def get(self, app_id): + """Get app trace""" + app_trace_config = OpsTraceManager.get_app_tracing_config( + app_id=app_id + ) + + return app_trace_config + + @setup_required + @login_required + @account_initialization_required + def post(self, app_id): + # add app trace + if not current_user.is_admin_or_owner: + raise Forbidden() + parser = reqparse.RequestParser() + parser.add_argument('enabled', type=bool, required=True, location='json') + parser.add_argument('tracing_provider', type=str, required=True, location='json') + args = parser.parse_args() + + OpsTraceManager.update_app_tracing_config( + app_id=app_id, + enabled=args['enabled'], + tracing_provider=args['tracing_provider'], + ) + + return {"result": "success"} + + api.add_resource(AppListApi, '/apps') api.add_resource(AppImportApi, '/apps/import') api.add_resource(AppApi, '/apps/') @@ -295,3 +324,4 @@ def post(self, app_model): api.add_resource(AppIconApi, '/apps//icon') api.add_resource(AppSiteStatus, '/apps//site-enable') api.add_resource(AppApiStatus, '/apps//api-enable') +api.add_resource(AppTraceApi, '/apps//trace') diff --git a/api/controllers/console/app/error.py b/api/controllers/console/app/error.py index fbe42fbd2a7135..f6feed12217a85 100644 --- a/api/controllers/console/app/error.py +++ b/api/controllers/console/app/error.py @@ -97,3 +97,21 @@ class DraftWorkflowNotSync(BaseHTTPException): error_code = 'draft_workflow_not_sync' description = "Workflow graph might have been modified, please refresh and resubmit." code = 400 + + +class TracingConfigNotExist(BaseHTTPException): + error_code = 'trace_config_not_exist' + description = "Trace config not exist." + code = 400 + + +class TracingConfigIsExist(BaseHTTPException): + error_code = 'trace_config_is_exist' + description = "Trace config is exist." + code = 400 + + +class TracingConfigCheckError(BaseHTTPException): + error_code = 'trace_config_check_error' + description = "Invalid Credentials." + code = 400 diff --git a/api/controllers/console/app/ops_trace.py b/api/controllers/console/app/ops_trace.py new file mode 100644 index 00000000000000..c0cf7b9e33f32b --- /dev/null +++ b/api/controllers/console/app/ops_trace.py @@ -0,0 +1,101 @@ +from flask_restful import Resource, reqparse + +from controllers.console import api +from controllers.console.app.error import TracingConfigCheckError, TracingConfigIsExist, TracingConfigNotExist +from controllers.console.setup import setup_required +from controllers.console.wraps import account_initialization_required +from libs.login import login_required +from services.ops_service import OpsService + + +class TraceAppConfigApi(Resource): + """ + Manage trace app configurations + """ + + @setup_required + @login_required + @account_initialization_required + def get(self, app_id): + parser = reqparse.RequestParser() + parser.add_argument('tracing_provider', type=str, required=True, location='args') + args = parser.parse_args() + + try: + trace_config = OpsService.get_tracing_app_config( + app_id=app_id, tracing_provider=args['tracing_provider'] + ) + if not trace_config: + return {"has_not_configured": True} + return trace_config + except Exception as e: + raise e + + @setup_required + @login_required + @account_initialization_required + def post(self, app_id): + """Create a new trace app configuration""" + parser = reqparse.RequestParser() + parser.add_argument('tracing_provider', type=str, required=True, location='json') + parser.add_argument('tracing_config', type=dict, required=True, location='json') + args = parser.parse_args() + + try: + result = OpsService.create_tracing_app_config( + app_id=app_id, + tracing_provider=args['tracing_provider'], + tracing_config=args['tracing_config'] + ) + if not result: + raise TracingConfigIsExist() + if result.get('error'): + raise TracingConfigCheckError() + return result + except Exception as e: + raise e + + @setup_required + @login_required + @account_initialization_required + def patch(self, app_id): + """Update an existing trace app configuration""" + parser = reqparse.RequestParser() + parser.add_argument('tracing_provider', type=str, required=True, location='json') + parser.add_argument('tracing_config', type=dict, required=True, location='json') + args = parser.parse_args() + + try: + result = OpsService.update_tracing_app_config( + app_id=app_id, + tracing_provider=args['tracing_provider'], + tracing_config=args['tracing_config'] + ) + if not result: + raise TracingConfigNotExist() + return {"result": "success"} + except Exception as e: + raise e + + @setup_required + @login_required + @account_initialization_required + def delete(self, app_id): + """Delete an existing trace app configuration""" + parser = reqparse.RequestParser() + parser.add_argument('tracing_provider', type=str, required=True, location='args') + args = parser.parse_args() + + try: + result = OpsService.delete_tracing_app_config( + app_id=app_id, + tracing_provider=args['tracing_provider'] + ) + if not result: + raise TracingConfigNotExist() + return {"result": "success"} + except Exception as e: + raise e + + +api.add_resource(TraceAppConfigApi, '/apps//trace-config') diff --git a/api/core/agent/cot_agent_runner.py b/api/core/agent/cot_agent_runner.py index 6b22faabc7f134..9bd8f37d858a29 100644 --- a/api/core/agent/cot_agent_runner.py +++ b/api/core/agent/cot_agent_runner.py @@ -1,7 +1,7 @@ import json from abc import ABC, abstractmethod from collections.abc import Generator -from typing import Union +from typing import Optional, Union from core.agent.base_agent_runner import BaseAgentRunner from core.agent.entities import AgentScratchpadUnit @@ -15,6 +15,7 @@ ToolPromptMessage, UserPromptMessage, ) +from core.ops.ops_trace_manager import TraceQueueManager from core.prompt.agent_history_prompt_transform import AgentHistoryPromptTransform from core.tools.entities.tool_entities import ToolInvokeMeta from core.tools.tool.tool import Tool @@ -42,6 +43,8 @@ def run(self, message: Message, self._repack_app_generate_entity(app_generate_entity) self._init_react_state(query) + trace_manager = app_generate_entity.trace_manager + # check model mode if 'Observation' not in app_generate_entity.model_conf.stop: if app_generate_entity.model_conf.provider not in self._ignore_observation_providers: @@ -211,7 +214,8 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): tool_invoke_response, tool_invoke_meta = self._handle_invoke_action( action=scratchpad.action, tool_instances=tool_instances, - message_file_ids=message_file_ids + message_file_ids=message_file_ids, + trace_manager=trace_manager, ) scratchpad.observation = tool_invoke_response scratchpad.agent_response = tool_invoke_response @@ -237,8 +241,7 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): # update prompt tool message for prompt_tool in self._prompt_messages_tools: - self.update_prompt_message_tool( - tool_instances[prompt_tool.name], prompt_tool) + self.update_prompt_message_tool(tool_instances[prompt_tool.name], prompt_tool) iteration_step += 1 @@ -275,14 +278,15 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): message=AssistantPromptMessage( content=final_answer ), - usage=llm_usage['usage'] if llm_usage['usage'] else LLMUsage.empty_usage( - ), + usage=llm_usage['usage'] if llm_usage['usage'] else LLMUsage.empty_usage(), system_fingerprint='' )), PublishFrom.APPLICATION_MANAGER) def _handle_invoke_action(self, action: AgentScratchpadUnit.Action, tool_instances: dict[str, Tool], - message_file_ids: list[str]) -> tuple[str, ToolInvokeMeta]: + message_file_ids: list[str], + trace_manager: Optional[TraceQueueManager] = None + ) -> tuple[str, ToolInvokeMeta]: """ handle invoke action :param action: action @@ -312,7 +316,8 @@ def _handle_invoke_action(self, action: AgentScratchpadUnit.Action, tenant_id=self.tenant_id, message=self.message, invoke_from=self.application_generate_entity.invoke_from, - agent_tool_callback=self.agent_callback + agent_tool_callback=self.agent_callback, + trace_manager=trace_manager, ) # publish files diff --git a/api/core/agent/fc_agent_runner.py b/api/core/agent/fc_agent_runner.py index 1c05c546820976..bec76e7a246d12 100644 --- a/api/core/agent/fc_agent_runner.py +++ b/api/core/agent/fc_agent_runner.py @@ -50,6 +50,9 @@ def run(self, } final_answer = '' + # get tracing instance + trace_manager = app_generate_entity.trace_manager + def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): if not final_llm_usage_dict['usage']: final_llm_usage_dict['usage'] = usage @@ -243,6 +246,7 @@ def increase_usage(final_llm_usage_dict: dict[str, LLMUsage], usage: LLMUsage): message=self.message, invoke_from=self.application_generate_entity.invoke_from, agent_tool_callback=self.agent_callback, + trace_manager=trace_manager, ) # publish files for message_file_id, save_as in message_files: diff --git a/api/core/app/app_config/entities.py b/api/core/app/app_config/entities.py index d6b6d894166d7e..6b58df617d7825 100644 --- a/api/core/app/app_config/entities.py +++ b/api/core/app/app_config/entities.py @@ -183,6 +183,14 @@ class TextToSpeechEntity(BaseModel): language: Optional[str] = None +class TracingConfigEntity(BaseModel): + """ + Tracing Config Entity. + """ + enabled: bool + tracing_provider: str + + class FileExtraConfig(BaseModel): """ File Upload Entity. @@ -199,7 +207,7 @@ class AppAdditionalFeatures(BaseModel): more_like_this: bool = False speech_to_text: bool = False text_to_speech: Optional[TextToSpeechEntity] = None - + trace_config: Optional[TracingConfigEntity] = None class AppConfig(BaseModel): """ diff --git a/api/core/app/apps/advanced_chat/app_generator.py b/api/core/app/apps/advanced_chat/app_generator.py index 2483e9f66c9330..2fcc3255408ac0 100644 --- a/api/core/app/apps/advanced_chat/app_generator.py +++ b/api/core/app/apps/advanced_chat/app_generator.py @@ -20,6 +20,7 @@ from core.app.entities.task_entities import ChatbotAppBlockingResponse, ChatbotAppStreamResponse from core.file.message_file_parser import MessageFileParser from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError +from core.ops.ops_trace_manager import TraceQueueManager from extensions.ext_database import db from models.account import Account from models.model import App, Conversation, EndUser, Message @@ -29,13 +30,14 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator): - def generate(self, app_model: App, - workflow: Workflow, - user: Union[Account, EndUser], - args: dict, - invoke_from: InvokeFrom, - stream: bool = True) \ - -> Union[dict, Generator[dict, None, None]]: + def generate( + self, app_model: App, + workflow: Workflow, + user: Union[Account, EndUser], + args: dict, + invoke_from: InvokeFrom, + stream: bool = True, + ) -> Union[dict, Generator[dict, None, None]]: """ Generate App response. @@ -84,6 +86,9 @@ def generate(self, app_model: App, workflow=workflow ) + # get tracing instance + trace_manager = TraceQueueManager(app_id=app_model.id) + if invoke_from == InvokeFrom.DEBUGGER: # always enable retriever resource in debugger mode app_config.additional_features.show_retrieve_source = True @@ -99,7 +104,8 @@ def generate(self, app_model: App, user_id=user.id, stream=stream, invoke_from=invoke_from, - extras=extras + extras=extras, + trace_manager=trace_manager ) return self._generate( diff --git a/api/core/app/apps/advanced_chat/app_runner.py b/api/core/app/apps/advanced_chat/app_runner.py index de3632894de2ed..96e9319dda58d2 100644 --- a/api/core/app/apps/advanced_chat/app_runner.py +++ b/api/core/app/apps/advanced_chat/app_runner.py @@ -70,7 +70,8 @@ def run(self, application_generate_entity: AdvancedChatAppGenerateEntity, app_record=app_record, app_generate_entity=application_generate_entity, inputs=inputs, - query=query + query=query, + message_id=message.id ): return @@ -156,11 +157,14 @@ def get_workflow(self, app_model: App, workflow_id: str) -> Optional[Workflow]: # return workflow return workflow - def handle_input_moderation(self, queue_manager: AppQueueManager, - app_record: App, - app_generate_entity: AdvancedChatAppGenerateEntity, - inputs: dict, - query: str) -> bool: + def handle_input_moderation( + self, queue_manager: AppQueueManager, + app_record: App, + app_generate_entity: AdvancedChatAppGenerateEntity, + inputs: dict, + query: str, + message_id: str + ) -> bool: """ Handle input moderation :param queue_manager: application queue manager @@ -168,6 +172,7 @@ def handle_input_moderation(self, queue_manager: AppQueueManager, :param app_generate_entity: application generate entity :param inputs: inputs :param query: query + :param message_id: message id :return: """ try: @@ -178,6 +183,7 @@ def handle_input_moderation(self, queue_manager: AppQueueManager, app_generate_entity=app_generate_entity, inputs=inputs, query=query, + message_id=message_id, ) except ModerationException as e: self._stream_output( diff --git a/api/core/app/apps/advanced_chat/generate_task_pipeline.py b/api/core/app/apps/advanced_chat/generate_task_pipeline.py index 7c70afc2ae393c..5ca0fe21911c3f 100644 --- a/api/core/app/apps/advanced_chat/generate_task_pipeline.py +++ b/api/core/app/apps/advanced_chat/generate_task_pipeline.py @@ -42,6 +42,7 @@ from core.file.file_obj import FileVar from core.model_runtime.entities.llm_entities import LLMUsage from core.model_runtime.utils.encoders import jsonable_encoder +from core.ops.ops_trace_manager import TraceQueueManager from core.workflow.entities.node_entities import NodeType, SystemVariable from core.workflow.nodes.answer.answer_node import AnswerNode from core.workflow.nodes.answer.entities import TextGenerateRouteChunk, VarGenerateRouteChunk @@ -69,13 +70,15 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc _workflow_system_variables: dict[SystemVariable, Any] _iteration_nested_relations: dict[str, list[str]] - def __init__(self, application_generate_entity: AdvancedChatAppGenerateEntity, - workflow: Workflow, - queue_manager: AppQueueManager, - conversation: Conversation, - message: Message, - user: Union[Account, EndUser], - stream: bool) -> None: + def __init__( + self, application_generate_entity: AdvancedChatAppGenerateEntity, + workflow: Workflow, + queue_manager: AppQueueManager, + conversation: Conversation, + message: Message, + user: Union[Account, EndUser], + stream: bool + ) -> None: """ Initialize AdvancedChatAppGenerateTaskPipeline. :param application_generate_entity: application generate entity @@ -126,14 +129,16 @@ def process(self) -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStrea self._application_generate_entity.query ) - generator = self._process_stream_response() + generator = self._process_stream_response( + trace_manager=self._application_generate_entity.trace_manager + ) if self._stream: return self._to_stream_response(generator) else: return self._to_blocking_response(generator) def _to_blocking_response(self, generator: Generator[StreamResponse, None, None]) \ - -> ChatbotAppBlockingResponse: + -> ChatbotAppBlockingResponse: """ Process blocking response. :return: @@ -164,7 +169,7 @@ def _to_blocking_response(self, generator: Generator[StreamResponse, None, None] raise Exception('Queue listening stopped unexpectedly.') def _to_stream_response(self, generator: Generator[StreamResponse, None, None]) \ - -> Generator[ChatbotAppStreamResponse, None, None]: + -> Generator[ChatbotAppStreamResponse, None, None]: """ To stream response. :return: @@ -177,7 +182,9 @@ def _to_stream_response(self, generator: Generator[StreamResponse, None, None]) stream_response=stream_response ) - def _process_stream_response(self) -> Generator[StreamResponse, None, None]: + def _process_stream_response( + self, trace_manager: Optional[TraceQueueManager] = None + ) -> Generator[StreamResponse, None, None]: """ Process stream response. :return: @@ -249,7 +256,9 @@ def _process_stream_response(self) -> Generator[StreamResponse, None, None]: yield self._handle_iteration_to_stream_response(self._application_generate_entity.task_id, event) self._handle_iteration_operation(event) elif isinstance(event, QueueStopEvent | QueueWorkflowSucceededEvent | QueueWorkflowFailedEvent): - workflow_run = self._handle_workflow_finished(event) + workflow_run = self._handle_workflow_finished( + event, conversation_id=self._conversation.id, trace_manager=trace_manager + ) if workflow_run: yield self._workflow_finish_to_stream_response( task_id=self._application_generate_entity.task_id, @@ -292,7 +301,7 @@ def _process_stream_response(self) -> Generator[StreamResponse, None, None]: continue if not self._is_stream_out_support( - event=event + event=event ): continue @@ -361,7 +370,7 @@ def _message_end_to_stream_response(self) -> MessageEndStreamResponse: id=self._message.id, **extras ) - + def _get_stream_generate_routes(self) -> dict[str, ChatflowStreamGenerateRoute]: """ Get stream generate routes. @@ -391,9 +400,9 @@ def _get_stream_generate_routes(self) -> dict[str, ChatflowStreamGenerateRoute]: ) return stream_generate_routes - + def _get_answer_start_at_node_ids(self, graph: dict, target_node_id: str) \ - -> list[str]: + -> list[str]: """ Get answer start at node id. :param graph: graph @@ -414,14 +423,14 @@ def _get_answer_start_at_node_ids(self, graph: dict, target_node_id: str) \ target_node = next((node for node in nodes if node.get('id') == target_node_id), None) if not target_node: return [] - + node_iteration_id = target_node.get('data', {}).get('iteration_id') # get iteration start node id for node in nodes: if node.get('id') == node_iteration_id: if node.get('data', {}).get('start_node_id') == target_node_id: return [target_node_id] - + return [] start_node_ids = [] @@ -457,7 +466,7 @@ def _get_answer_start_at_node_ids(self, graph: dict, target_node_id: str) \ start_node_ids.extend(sub_start_node_ids) return start_node_ids - + def _get_iteration_nested_relations(self, graph: dict) -> dict[str, list[str]]: """ Get iteration nested relations. @@ -466,18 +475,18 @@ def _get_iteration_nested_relations(self, graph: dict) -> dict[str, list[str]]: """ nodes = graph.get('nodes') - iteration_ids = [node.get('id') for node in nodes + iteration_ids = [node.get('id') for node in nodes if node.get('data', {}).get('type') in [ NodeType.ITERATION.value, NodeType.LOOP.value, - ]] + ]] return { iteration_id: [ node.get('id') for node in nodes if node.get('data', {}).get('iteration_id') == iteration_id ] for iteration_id in iteration_ids } - + def _generate_stream_outputs_when_node_started(self) -> Generator: """ Generate stream outputs. @@ -485,8 +494,8 @@ def _generate_stream_outputs_when_node_started(self) -> Generator: """ if self._task_state.current_stream_generate_state: route_chunks = self._task_state.current_stream_generate_state.generate_route[ - self._task_state.current_stream_generate_state.current_route_position: - ] + self._task_state.current_stream_generate_state.current_route_position: + ] for route_chunk in route_chunks: if route_chunk.type == 'text': @@ -506,7 +515,8 @@ def _generate_stream_outputs_when_node_started(self) -> Generator: # all route chunks are generated if self._task_state.current_stream_generate_state.current_route_position == len( - self._task_state.current_stream_generate_state.generate_route): + self._task_state.current_stream_generate_state.generate_route + ): self._task_state.current_stream_generate_state = None def _generate_stream_outputs_when_node_finished(self) -> Optional[Generator]: @@ -519,7 +529,7 @@ def _generate_stream_outputs_when_node_finished(self) -> Optional[Generator]: route_chunks = self._task_state.current_stream_generate_state.generate_route[ self._task_state.current_stream_generate_state.current_route_position:] - + for route_chunk in route_chunks: if route_chunk.type == 'text': route_chunk = cast(TextGenerateRouteChunk, route_chunk) @@ -551,7 +561,8 @@ def _generate_stream_outputs_when_node_finished(self) -> Optional[Generator]: value = iteration_state.current_index elif value_selector[1] == 'item': value = iterator_selector[iteration_state.current_index] if iteration_state.current_index < len( - iterator_selector) else None + iterator_selector + ) else None else: # check chunk node id is before current node id or equal to current node id if route_chunk_node_id not in self._task_state.ran_node_execution_infos: @@ -562,14 +573,15 @@ def _generate_stream_outputs_when_node_finished(self) -> Optional[Generator]: # get route chunk node execution info route_chunk_node_execution_info = self._task_state.ran_node_execution_infos[route_chunk_node_id] if (route_chunk_node_execution_info.node_type == NodeType.LLM - and latest_node_execution_info.node_type == NodeType.LLM): + and latest_node_execution_info.node_type == NodeType.LLM): # only LLM support chunk stream output self._task_state.current_stream_generate_state.current_route_position += 1 continue # get route chunk node execution route_chunk_node_execution = db.session.query(WorkflowNodeExecution).filter( - WorkflowNodeExecution.id == route_chunk_node_execution_info.workflow_node_execution_id).first() + WorkflowNodeExecution.id == route_chunk_node_execution_info.workflow_node_execution_id + ).first() outputs = route_chunk_node_execution.outputs_dict @@ -631,7 +643,8 @@ def _generate_stream_outputs_when_node_finished(self) -> Optional[Generator]: # all route chunks are generated if self._task_state.current_stream_generate_state.current_route_position == len( - self._task_state.current_stream_generate_state.generate_route): + self._task_state.current_stream_generate_state.generate_route + ): self._task_state.current_stream_generate_state = None def _is_stream_out_support(self, event: QueueTextChunkEvent) -> bool: diff --git a/api/core/app/apps/agent_chat/app_generator.py b/api/core/app/apps/agent_chat/app_generator.py index 800dc1616da485..a9beeb3a5cd2c0 100644 --- a/api/core/app/apps/agent_chat/app_generator.py +++ b/api/core/app/apps/agent_chat/app_generator.py @@ -19,6 +19,7 @@ from core.app.entities.app_invoke_entities import AgentChatAppGenerateEntity, InvokeFrom from core.file.message_file_parser import MessageFileParser from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError +from core.ops.ops_trace_manager import TraceQueueManager from extensions.ext_database import db from models.account import Account from models.model import App, EndUser @@ -108,6 +109,9 @@ def generate(self, app_model: App, override_config_dict=override_model_config_dict ) + # get tracing instance + trace_manager = TraceQueueManager(app_model.id) + # init application generate entity application_generate_entity = AgentChatAppGenerateEntity( task_id=str(uuid.uuid4()), @@ -121,7 +125,8 @@ def generate(self, app_model: App, stream=stream, invoke_from=invoke_from, extras=extras, - call_depth=0 + call_depth=0, + trace_manager=trace_manager ) # init generate records @@ -158,7 +163,7 @@ def generate(self, app_model: App, conversation=conversation, message=message, user=user, - stream=stream + stream=stream, ) return AgentChatAppGenerateResponseConverter.convert( @@ -166,11 +171,13 @@ def generate(self, app_model: App, invoke_from=invoke_from ) - def _generate_worker(self, flask_app: Flask, - application_generate_entity: AgentChatAppGenerateEntity, - queue_manager: AppQueueManager, - conversation_id: str, - message_id: str) -> None: + def _generate_worker( + self, flask_app: Flask, + application_generate_entity: AgentChatAppGenerateEntity, + queue_manager: AppQueueManager, + conversation_id: str, + message_id: str, + ) -> None: """ Generate worker in a new thread. :param flask_app: Flask app @@ -192,7 +199,7 @@ def _generate_worker(self, flask_app: Flask, application_generate_entity=application_generate_entity, queue_manager=queue_manager, conversation=conversation, - message=message + message=message, ) except GenerateTaskStoppedException: pass diff --git a/api/core/app/apps/agent_chat/app_runner.py b/api/core/app/apps/agent_chat/app_runner.py index d6367300de26e3..6aa615a48de887 100644 --- a/api/core/app/apps/agent_chat/app_runner.py +++ b/api/core/app/apps/agent_chat/app_runner.py @@ -28,10 +28,13 @@ class AgentChatAppRunner(AppRunner): """ Agent Application Runner """ - def run(self, application_generate_entity: AgentChatAppGenerateEntity, - queue_manager: AppQueueManager, - conversation: Conversation, - message: Message) -> None: + + def run( + self, application_generate_entity: AgentChatAppGenerateEntity, + queue_manager: AppQueueManager, + conversation: Conversation, + message: Message, + ) -> None: """ Run assistant application :param application_generate_entity: application generate entity @@ -100,6 +103,7 @@ def run(self, application_generate_entity: AgentChatAppGenerateEntity, app_generate_entity=application_generate_entity, inputs=inputs, query=query, + message_id=message.id ) except ModerationException as e: self.direct_output( @@ -219,7 +223,7 @@ def run(self, application_generate_entity: AgentChatAppGenerateEntity, runner_cls = FunctionCallAgentRunner else: raise ValueError(f"Invalid agent strategy: {agent_entity.strategy}") - + runner = runner_cls( tenant_id=app_config.tenant_id, application_generate_entity=application_generate_entity, diff --git a/api/core/app/apps/base_app_runner.py b/api/core/app/apps/base_app_runner.py index 53f457cb116c02..58c7d04b8348f8 100644 --- a/api/core/app/apps/base_app_runner.py +++ b/api/core/app/apps/base_app_runner.py @@ -338,11 +338,14 @@ def _handle_invoke_result_stream(self, invoke_result: Generator, ), PublishFrom.APPLICATION_MANAGER ) - def moderation_for_inputs(self, app_id: str, - tenant_id: str, - app_generate_entity: AppGenerateEntity, - inputs: dict, - query: str) -> tuple[bool, dict, str]: + def moderation_for_inputs( + self, app_id: str, + tenant_id: str, + app_generate_entity: AppGenerateEntity, + inputs: dict, + query: str, + message_id: str, + ) -> tuple[bool, dict, str]: """ Process sensitive_word_avoidance. :param app_id: app id @@ -350,6 +353,7 @@ def moderation_for_inputs(self, app_id: str, :param app_generate_entity: app generate entity :param inputs: inputs :param query: query + :param message_id: message id :return: """ moderation_feature = InputModeration() @@ -358,7 +362,9 @@ def moderation_for_inputs(self, app_id: str, tenant_id=tenant_id, app_config=app_generate_entity.app_config, inputs=inputs, - query=query if query else '' + query=query if query else '', + message_id=message_id, + trace_manager=app_generate_entity.trace_manager ) def check_hosting_moderation(self, application_generate_entity: EasyUIBasedAppGenerateEntity, diff --git a/api/core/app/apps/chat/app_generator.py b/api/core/app/apps/chat/app_generator.py index b92eed82c36f28..94e862cb878a47 100644 --- a/api/core/app/apps/chat/app_generator.py +++ b/api/core/app/apps/chat/app_generator.py @@ -19,6 +19,7 @@ from core.app.entities.app_invoke_entities import ChatAppGenerateEntity, InvokeFrom from core.file.message_file_parser import MessageFileParser from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError +from core.ops.ops_trace_manager import TraceQueueManager from extensions.ext_database import db from models.account import Account from models.model import App, EndUser @@ -27,12 +28,13 @@ class ChatAppGenerator(MessageBasedAppGenerator): - def generate(self, app_model: App, - user: Union[Account, EndUser], - args: Any, - invoke_from: InvokeFrom, - stream: bool = True) \ - -> Union[dict, Generator[dict, None, None]]: + def generate( + self, app_model: App, + user: Union[Account, EndUser], + args: Any, + invoke_from: InvokeFrom, + stream: bool = True, + ) -> Union[dict, Generator[dict, None, None]]: """ Generate App response. @@ -105,6 +107,9 @@ def generate(self, app_model: App, override_config_dict=override_model_config_dict ) + # get tracing instance + trace_manager = TraceQueueManager(app_model.id) + # init application generate entity application_generate_entity = ChatAppGenerateEntity( task_id=str(uuid.uuid4()), @@ -117,7 +122,8 @@ def generate(self, app_model: App, user_id=user.id, stream=stream, invoke_from=invoke_from, - extras=extras + extras=extras, + trace_manager=trace_manager ) # init generate records @@ -154,7 +160,7 @@ def generate(self, app_model: App, conversation=conversation, message=message, user=user, - stream=stream + stream=stream, ) return ChatAppGenerateResponseConverter.convert( diff --git a/api/core/app/apps/chat/app_runner.py b/api/core/app/apps/chat/app_runner.py index 7d243d0726724e..89a498eb3607f9 100644 --- a/api/core/app/apps/chat/app_runner.py +++ b/api/core/app/apps/chat/app_runner.py @@ -96,6 +96,7 @@ def run(self, application_generate_entity: ChatAppGenerateEntity, app_generate_entity=application_generate_entity, inputs=inputs, query=query, + message_id=message.id ) except ModerationException as e: self.direct_output( @@ -154,7 +155,7 @@ def run(self, application_generate_entity: ChatAppGenerateEntity, application_generate_entity.invoke_from ) - dataset_retrieval = DatasetRetrieval() + dataset_retrieval = DatasetRetrieval(application_generate_entity) context = dataset_retrieval.retrieve( app_id=app_record.id, user_id=application_generate_entity.user_id, @@ -165,7 +166,8 @@ def run(self, application_generate_entity: ChatAppGenerateEntity, invoke_from=application_generate_entity.invoke_from, show_retrieve_source=app_config.additional_features.show_retrieve_source, hit_callback=hit_callback, - memory=memory + memory=memory, + message_id=message.id, ) # reorganize all inputs and template to prompt messages diff --git a/api/core/app/apps/completion/app_generator.py b/api/core/app/apps/completion/app_generator.py index 52d907b5353143..c4e1caf65a9679 100644 --- a/api/core/app/apps/completion/app_generator.py +++ b/api/core/app/apps/completion/app_generator.py @@ -19,6 +19,7 @@ from core.app.entities.app_invoke_entities import CompletionAppGenerateEntity, InvokeFrom from core.file.message_file_parser import MessageFileParser from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError +from core.ops.ops_trace_manager import TraceQueueManager from extensions.ext_database import db from models.account import Account from models.model import App, EndUser, Message @@ -94,6 +95,9 @@ def generate(self, app_model: App, override_config_dict=override_model_config_dict ) + # get tracing instance + trace_manager = TraceQueueManager(app_model.id) + # init application generate entity application_generate_entity = CompletionAppGenerateEntity( task_id=str(uuid.uuid4()), @@ -105,7 +109,8 @@ def generate(self, app_model: App, user_id=user.id, stream=stream, invoke_from=invoke_from, - extras=extras + extras=extras, + trace_manager=trace_manager ) # init generate records @@ -141,7 +146,7 @@ def generate(self, app_model: App, conversation=conversation, message=message, user=user, - stream=stream + stream=stream, ) return CompletionAppGenerateResponseConverter.convert( @@ -158,7 +163,6 @@ def _generate_worker(self, flask_app: Flask, :param flask_app: Flask app :param application_generate_entity: application generate entity :param queue_manager: queue manager - :param conversation_id: conversation ID :param message_id: message ID :return: """ @@ -300,7 +304,7 @@ def generate_more_like_this(self, app_model: App, conversation=conversation, message=message, user=user, - stream=stream + stream=stream, ) return CompletionAppGenerateResponseConverter.convert( diff --git a/api/core/app/apps/completion/app_runner.py b/api/core/app/apps/completion/app_runner.py index a3a9945bc0436b..f0e5f9ae173c39 100644 --- a/api/core/app/apps/completion/app_runner.py +++ b/api/core/app/apps/completion/app_runner.py @@ -77,6 +77,7 @@ def run(self, application_generate_entity: CompletionAppGenerateEntity, app_generate_entity=application_generate_entity, inputs=inputs, query=query, + message_id=message.id ) except ModerationException as e: self.direct_output( @@ -114,7 +115,7 @@ def run(self, application_generate_entity: CompletionAppGenerateEntity, if dataset_config and dataset_config.retrieve_config.query_variable: query = inputs.get(dataset_config.retrieve_config.query_variable, "") - dataset_retrieval = DatasetRetrieval() + dataset_retrieval = DatasetRetrieval(application_generate_entity) context = dataset_retrieval.retrieve( app_id=app_record.id, user_id=application_generate_entity.user_id, @@ -124,7 +125,8 @@ def run(self, application_generate_entity: CompletionAppGenerateEntity, query=query, invoke_from=application_generate_entity.invoke_from, show_retrieve_source=app_config.additional_features.show_retrieve_source, - hit_callback=hit_callback + hit_callback=hit_callback, + message_id=message.id ) # reorganize all inputs and template to prompt messages diff --git a/api/core/app/apps/message_based_app_generator.py b/api/core/app/apps/message_based_app_generator.py index 6acf5da8df4d2a..c5cd6864020b33 100644 --- a/api/core/app/apps/message_based_app_generator.py +++ b/api/core/app/apps/message_based_app_generator.py @@ -35,22 +35,23 @@ class MessageBasedAppGenerator(BaseAppGenerator): - def _handle_response(self, application_generate_entity: Union[ - ChatAppGenerateEntity, - CompletionAppGenerateEntity, - AgentChatAppGenerateEntity, - AdvancedChatAppGenerateEntity - ], - queue_manager: AppQueueManager, - conversation: Conversation, - message: Message, - user: Union[Account, EndUser], - stream: bool = False) \ - -> Union[ - ChatbotAppBlockingResponse, - CompletionAppBlockingResponse, - Generator[Union[ChatbotAppStreamResponse, CompletionAppStreamResponse], None, None] - ]: + def _handle_response( + self, application_generate_entity: Union[ + ChatAppGenerateEntity, + CompletionAppGenerateEntity, + AgentChatAppGenerateEntity, + AdvancedChatAppGenerateEntity + ], + queue_manager: AppQueueManager, + conversation: Conversation, + message: Message, + user: Union[Account, EndUser], + stream: bool = False, + ) -> Union[ + ChatbotAppBlockingResponse, + CompletionAppBlockingResponse, + Generator[Union[ChatbotAppStreamResponse, CompletionAppStreamResponse], None, None] + ]: """ Handle response. :param application_generate_entity: application generate entity diff --git a/api/core/app/apps/workflow/app_generator.py b/api/core/app/apps/workflow/app_generator.py index c4324978d81fc3..3eb0bcf3dafe7b 100644 --- a/api/core/app/apps/workflow/app_generator.py +++ b/api/core/app/apps/workflow/app_generator.py @@ -20,6 +20,7 @@ from core.app.entities.task_entities import WorkflowAppBlockingResponse, WorkflowAppStreamResponse from core.file.message_file_parser import MessageFileParser from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError +from core.ops.ops_trace_manager import TraceQueueManager from extensions.ext_database import db from models.account import Account from models.model import App, EndUser @@ -29,14 +30,15 @@ class WorkflowAppGenerator(BaseAppGenerator): - def generate(self, app_model: App, - workflow: Workflow, - user: Union[Account, EndUser], - args: dict, - invoke_from: InvokeFrom, - stream: bool = True, - call_depth: int = 0) \ - -> Union[dict, Generator[dict, None, None]]: + def generate( + self, app_model: App, + workflow: Workflow, + user: Union[Account, EndUser], + args: dict, + invoke_from: InvokeFrom, + stream: bool = True, + call_depth: int = 0, + ) -> Union[dict, Generator[dict, None, None]]: """ Generate App response. @@ -46,6 +48,7 @@ def generate(self, app_model: App, :param args: request args :param invoke_from: invoke from source :param stream: is stream + :param call_depth: call depth """ inputs = args['inputs'] @@ -68,6 +71,9 @@ def generate(self, app_model: App, workflow=workflow ) + # get tracing instance + trace_manager = TraceQueueManager(app_model.id) + # init application generate entity application_generate_entity = WorkflowAppGenerateEntity( task_id=str(uuid.uuid4()), @@ -77,7 +83,8 @@ def generate(self, app_model: App, user_id=user.id, stream=stream, invoke_from=invoke_from, - call_depth=call_depth + call_depth=call_depth, + trace_manager=trace_manager ) return self._generate( @@ -87,17 +94,18 @@ def generate(self, app_model: App, application_generate_entity=application_generate_entity, invoke_from=invoke_from, stream=stream, - call_depth=call_depth + call_depth=call_depth, ) - def _generate(self, app_model: App, - workflow: Workflow, - user: Union[Account, EndUser], - application_generate_entity: WorkflowAppGenerateEntity, - invoke_from: InvokeFrom, - stream: bool = True, - call_depth: int = 0) \ - -> Union[dict, Generator[dict, None, None]]: + def _generate( + self, app_model: App, + workflow: Workflow, + user: Union[Account, EndUser], + application_generate_entity: WorkflowAppGenerateEntity, + invoke_from: InvokeFrom, + stream: bool = True, + call_depth: int = 0 + ) -> Union[dict, Generator[dict, None, None]]: """ Generate App response. @@ -131,7 +139,7 @@ def _generate(self, app_model: App, workflow=workflow, queue_manager=queue_manager, user=user, - stream=stream + stream=stream, ) return WorkflowAppGenerateResponseConverter.convert( diff --git a/api/core/app/apps/workflow/generate_task_pipeline.py b/api/core/app/apps/workflow/generate_task_pipeline.py index 8d961e0993b96f..f4bd396f46b3ae 100644 --- a/api/core/app/apps/workflow/generate_task_pipeline.py +++ b/api/core/app/apps/workflow/generate_task_pipeline.py @@ -1,6 +1,6 @@ import logging from collections.abc import Generator -from typing import Any, Union +from typing import Any, Optional, Union from core.app.apps.base_app_queue_manager import AppQueueManager from core.app.entities.app_invoke_entities import ( @@ -36,6 +36,7 @@ ) from core.app.task_pipeline.based_generate_task_pipeline import BasedGenerateTaskPipeline from core.app.task_pipeline.workflow_cycle_manage import WorkflowCycleManage +from core.ops.ops_trace_manager import TraceQueueManager from core.workflow.entities.node_entities import NodeType, SystemVariable from core.workflow.nodes.end.end_node import EndNode from extensions.ext_database import db @@ -104,7 +105,9 @@ def process(self) -> Union[WorkflowAppBlockingResponse, Generator[WorkflowAppStr db.session.refresh(self._user) db.session.close() - generator = self._process_stream_response() + generator = self._process_stream_response( + trace_manager=self._application_generate_entity.trace_manager + ) if self._stream: return self._to_stream_response(generator) else: @@ -158,7 +161,10 @@ def _to_stream_response(self, generator: Generator[StreamResponse, None, None]) stream_response=stream_response ) - def _process_stream_response(self) -> Generator[StreamResponse, None, None]: + def _process_stream_response( + self, + trace_manager: Optional[TraceQueueManager] = None + ) -> Generator[StreamResponse, None, None]: """ Process stream response. :return: @@ -215,7 +221,9 @@ def _process_stream_response(self) -> Generator[StreamResponse, None, None]: yield self._handle_iteration_to_stream_response(self._application_generate_entity.task_id, event) self._handle_iteration_operation(event) elif isinstance(event, QueueStopEvent | QueueWorkflowSucceededEvent | QueueWorkflowFailedEvent): - workflow_run = self._handle_workflow_finished(event) + workflow_run = self._handle_workflow_finished( + event, trace_manager=trace_manager + ) # save workflow app log self._save_workflow_app_log(workflow_run) diff --git a/api/core/app/entities/app_invoke_entities.py b/api/core/app/entities/app_invoke_entities.py index f27a110870b111..1d2ad4a3735063 100644 --- a/api/core/app/entities/app_invoke_entities.py +++ b/api/core/app/entities/app_invoke_entities.py @@ -7,6 +7,7 @@ from core.entities.provider_configuration import ProviderModelBundle from core.file.file_obj import FileVar from core.model_runtime.entities.model_entities import AIModelEntity +from core.ops.ops_trace_manager import TraceQueueManager class InvokeFrom(Enum): @@ -89,6 +90,12 @@ class AppGenerateEntity(BaseModel): # extra parameters, like: auto_generate_conversation_name extras: dict[str, Any] = {} + # tracing instance + trace_manager: Optional[TraceQueueManager] = None + + class Config: + arbitrary_types_allowed = True + class EasyUIBasedAppGenerateEntity(AppGenerateEntity): """ diff --git a/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py b/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py index ccb684d84b0c8f..7d16d015bfcd41 100644 --- a/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py +++ b/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py @@ -44,6 +44,7 @@ ) from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel from core.model_runtime.utils.encoders import jsonable_encoder +from core.ops.ops_trace_manager import TraceQueueManager, TraceTask, TraceTaskName from core.prompt.utils.prompt_message_util import PromptMessageUtil from core.prompt.utils.prompt_template_parser import PromptTemplateParser from events.message_event import message_was_created @@ -100,7 +101,9 @@ def __init__(self, application_generate_entity: Union[ self._conversation_name_generate_thread = None - def process(self) -> Union[ + def process( + self, + ) -> Union[ ChatbotAppBlockingResponse, CompletionAppBlockingResponse, Generator[Union[ChatbotAppStreamResponse, CompletionAppStreamResponse], None, None] @@ -120,7 +123,9 @@ def process(self) -> Union[ self._application_generate_entity.query ) - generator = self._process_stream_response() + generator = self._process_stream_response( + trace_manager=self._application_generate_entity.trace_manager + ) if self._stream: return self._to_stream_response(generator) else: @@ -197,7 +202,9 @@ def _to_stream_response(self, generator: Generator[StreamResponse, None, None]) stream_response=stream_response ) - def _process_stream_response(self) -> Generator[StreamResponse, None, None]: + def _process_stream_response( + self, trace_manager: Optional[TraceQueueManager] = None + ) -> Generator[StreamResponse, None, None]: """ Process stream response. :return: @@ -224,7 +231,7 @@ def _process_stream_response(self) -> Generator[StreamResponse, None, None]: yield self._message_replace_to_stream_response(answer=output_moderation_answer) # Save message - self._save_message() + self._save_message(trace_manager) yield self._message_end_to_stream_response() elif isinstance(event, QueueRetrieverResourcesEvent): @@ -269,7 +276,9 @@ def _process_stream_response(self) -> Generator[StreamResponse, None, None]: if self._conversation_name_generate_thread: self._conversation_name_generate_thread.join() - def _save_message(self) -> None: + def _save_message( + self, trace_manager: Optional[TraceQueueManager] = None + ) -> None: """ Save message. :return: @@ -300,6 +309,15 @@ def _save_message(self) -> None: db.session.commit() + if trace_manager: + trace_manager.add_trace_task( + TraceTask( + TraceTaskName.MESSAGE_TRACE, + conversation_id=self._conversation.id, + message_id=self._message.id + ) + ) + message_was_created.send( self._message, application_generate_entity=self._application_generate_entity, diff --git a/api/core/app/task_pipeline/workflow_cycle_manage.py b/api/core/app/task_pipeline/workflow_cycle_manage.py index 978a318279165f..e79ac05a752e4e 100644 --- a/api/core/app/task_pipeline/workflow_cycle_manage.py +++ b/api/core/app/task_pipeline/workflow_cycle_manage.py @@ -22,6 +22,7 @@ from core.app.task_pipeline.workflow_iteration_cycle_manage import WorkflowIterationCycleManage from core.file.file_obj import FileVar from core.model_runtime.utils.encoders import jsonable_encoder +from core.ops.ops_trace_manager import TraceQueueManager, TraceTask, TraceTaskName from core.tools.tool_manager import ToolManager from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeType from core.workflow.nodes.tool.entities import ToolNodeData @@ -94,11 +95,15 @@ def _init_workflow_run(self, workflow: Workflow, return workflow_run - def _workflow_run_success(self, workflow_run: WorkflowRun, - start_at: float, - total_tokens: int, - total_steps: int, - outputs: Optional[str] = None) -> WorkflowRun: + def _workflow_run_success( + self, workflow_run: WorkflowRun, + start_at: float, + total_tokens: int, + total_steps: int, + outputs: Optional[str] = None, + conversation_id: Optional[str] = None, + trace_manager: Optional[TraceQueueManager] = None + ) -> WorkflowRun: """ Workflow run success :param workflow_run: workflow run @@ -106,6 +111,7 @@ def _workflow_run_success(self, workflow_run: WorkflowRun, :param total_tokens: total tokens :param total_steps: total steps :param outputs: outputs + :param conversation_id: conversation id :return: """ workflow_run.status = WorkflowRunStatus.SUCCEEDED.value @@ -119,14 +125,27 @@ def _workflow_run_success(self, workflow_run: WorkflowRun, db.session.refresh(workflow_run) db.session.close() + if trace_manager: + trace_manager.add_trace_task( + TraceTask( + TraceTaskName.WORKFLOW_TRACE, + workflow_run=workflow_run, + conversation_id=conversation_id, + ) + ) + return workflow_run - def _workflow_run_failed(self, workflow_run: WorkflowRun, - start_at: float, - total_tokens: int, - total_steps: int, - status: WorkflowRunStatus, - error: str) -> WorkflowRun: + def _workflow_run_failed( + self, workflow_run: WorkflowRun, + start_at: float, + total_tokens: int, + total_steps: int, + status: WorkflowRunStatus, + error: str, + conversation_id: Optional[str] = None, + trace_manager: Optional[TraceQueueManager] = None + ) -> WorkflowRun: """ Workflow run failed :param workflow_run: workflow run @@ -148,6 +167,14 @@ def _workflow_run_failed(self, workflow_run: WorkflowRun, db.session.refresh(workflow_run) db.session.close() + trace_manager.add_trace_task( + TraceTask( + TraceTaskName.WORKFLOW_TRACE, + workflow_run=workflow_run, + conversation_id=conversation_id, + ) + ) + return workflow_run def _init_node_execution_from_workflow_run(self, workflow_run: WorkflowRun, @@ -180,7 +207,8 @@ def _init_node_execution_from_workflow_run(self, workflow_run: WorkflowRun, title=node_title, status=WorkflowNodeExecutionStatus.RUNNING.value, created_by_role=workflow_run.created_by_role, - created_by=workflow_run.created_by + created_by=workflow_run.created_by, + created_at=datetime.now(timezone.utc).replace(tzinfo=None) ) db.session.add(workflow_node_execution) @@ -440,9 +468,9 @@ def _handle_node_finished(self, event: QueueNodeSucceededEvent | QueueNodeFailed current_node_execution = self._task_state.ran_node_execution_infos[event.node_id] workflow_node_execution = db.session.query(WorkflowNodeExecution).filter( WorkflowNodeExecution.id == current_node_execution.workflow_node_execution_id).first() - + execution_metadata = event.execution_metadata if isinstance(event, QueueNodeSucceededEvent) else None - + if self._iteration_state and self._iteration_state.current_iterations: if not execution_metadata: execution_metadata = {} @@ -470,7 +498,7 @@ def _handle_node_finished(self, event: QueueNodeSucceededEvent | QueueNodeFailed if execution_metadata and execution_metadata.get(NodeRunMetadataKey.TOTAL_TOKENS): self._task_state.total_tokens += ( int(execution_metadata.get(NodeRunMetadataKey.TOTAL_TOKENS))) - + if self._iteration_state: for iteration_node_id in self._iteration_state.current_iterations: data = self._iteration_state.current_iterations[iteration_node_id] @@ -496,13 +524,18 @@ def _handle_node_finished(self, event: QueueNodeSucceededEvent | QueueNodeFailed return workflow_node_execution - def _handle_workflow_finished(self, event: QueueStopEvent | QueueWorkflowSucceededEvent | QueueWorkflowFailedEvent) \ - -> Optional[WorkflowRun]: + def _handle_workflow_finished( + self, event: QueueStopEvent | QueueWorkflowSucceededEvent | QueueWorkflowFailedEvent, + conversation_id: Optional[str] = None, + trace_manager: Optional[TraceQueueManager] = None + ) -> Optional[WorkflowRun]: workflow_run = db.session.query(WorkflowRun).filter( WorkflowRun.id == self._task_state.workflow_run_id).first() if not workflow_run: return None + if conversation_id is None: + conversation_id = self._application_generate_entity.inputs.get('sys.conversation_id') if isinstance(event, QueueStopEvent): workflow_run = self._workflow_run_failed( workflow_run=workflow_run, @@ -510,7 +543,9 @@ def _handle_workflow_finished(self, event: QueueStopEvent | QueueWorkflowSucceed total_tokens=self._task_state.total_tokens, total_steps=self._task_state.total_steps, status=WorkflowRunStatus.STOPPED, - error='Workflow stopped.' + error='Workflow stopped.', + conversation_id=conversation_id, + trace_manager=trace_manager ) latest_node_execution_info = self._task_state.latest_node_execution_info @@ -531,7 +566,9 @@ def _handle_workflow_finished(self, event: QueueStopEvent | QueueWorkflowSucceed total_tokens=self._task_state.total_tokens, total_steps=self._task_state.total_steps, status=WorkflowRunStatus.FAILED, - error=event.error + error=event.error, + conversation_id=conversation_id, + trace_manager=trace_manager ) else: if self._task_state.latest_node_execution_info: @@ -546,7 +583,9 @@ def _handle_workflow_finished(self, event: QueueStopEvent | QueueWorkflowSucceed start_at=self._task_state.start_at, total_tokens=self._task_state.total_tokens, total_steps=self._task_state.total_steps, - outputs=outputs + outputs=outputs, + conversation_id=conversation_id, + trace_manager=trace_manager ) self._task_state.workflow_run_id = workflow_run.id diff --git a/api/core/app/task_pipeline/workflow_iteration_cycle_manage.py b/api/core/app/task_pipeline/workflow_iteration_cycle_manage.py index 69af81d02691f8..aff187071417c7 100644 --- a/api/core/app/task_pipeline/workflow_iteration_cycle_manage.py +++ b/api/core/app/task_pipeline/workflow_iteration_cycle_manage.py @@ -1,6 +1,7 @@ import json import time from collections.abc import Generator +from datetime import datetime, timezone from typing import Optional, Union from core.app.entities.queue_entities import ( @@ -131,7 +132,8 @@ def _init_iteration_execution_from_workflow_run(self, 'started_run_index': node_run_index + 1, 'current_index': 0, 'steps_boundary': [], - }) + }), + created_at=datetime.now(timezone.utc).replace(tzinfo=None) ) db.session.add(workflow_node_execution) diff --git a/api/core/callback_handler/agent_tool_callback_handler.py b/api/core/callback_handler/agent_tool_callback_handler.py index ac5076cd012d0d..f973b7e1cec511 100644 --- a/api/core/callback_handler/agent_tool_callback_handler.py +++ b/api/core/callback_handler/agent_tool_callback_handler.py @@ -3,6 +3,8 @@ from pydantic import BaseModel +from core.ops.ops_trace_manager import TraceQueueManager, TraceTask, TraceTaskName + _TEXT_COLOR_MAPPING = { "blue": "36;1", "yellow": "33;1", @@ -51,6 +53,9 @@ def on_tool_end( tool_name: str, tool_inputs: dict[str, Any], tool_outputs: str, + message_id: Optional[str] = None, + timer: Optional[Any] = None, + trace_manager: Optional[TraceQueueManager] = None ) -> None: """If not the final action, print out observation.""" print_text("\n[on_tool_end]\n", color=self.color) @@ -59,6 +64,18 @@ def on_tool_end( print_text("Outputs: " + str(tool_outputs)[:1000] + "\n", color=self.color) print_text("\n") + if trace_manager: + trace_manager.add_trace_task( + TraceTask( + TraceTaskName.TOOL_TRACE, + message_id=message_id, + tool_name=tool_name, + tool_inputs=tool_inputs, + tool_outputs=tool_outputs, + timer=timer, + ) + ) + def on_tool_error( self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any ) -> None: diff --git a/api/core/llm_generator/llm_generator.py b/api/core/llm_generator/llm_generator.py index 14de8649c637e7..70d3befbbdcb6f 100644 --- a/api/core/llm_generator/llm_generator.py +++ b/api/core/llm_generator/llm_generator.py @@ -1,5 +1,7 @@ import json import logging +import re +from typing import Optional from core.llm_generator.output_parser.errors import OutputParserException from core.llm_generator.output_parser.rule_config_generator import RuleConfigGeneratorOutputParser @@ -9,12 +11,16 @@ from core.model_runtime.entities.message_entities import SystemPromptMessage, UserPromptMessage from core.model_runtime.entities.model_entities import ModelType from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError +from core.ops.ops_trace_manager import TraceQueueManager, TraceTask, TraceTaskName +from core.ops.utils import measure_time from core.prompt.utils.prompt_template_parser import PromptTemplateParser class LLMGenerator: @classmethod - def generate_conversation_name(cls, tenant_id: str, query): + def generate_conversation_name( + cls, tenant_id: str, query, conversation_id: Optional[str] = None, app_id: Optional[str] = None + ): prompt = CONVERSATION_TITLE_PROMPT if len(query) > 2000: @@ -29,25 +35,39 @@ def generate_conversation_name(cls, tenant_id: str, query): tenant_id=tenant_id, model_type=ModelType.LLM, ) - prompts = [UserPromptMessage(content=prompt)] - response = model_instance.invoke_llm( - prompt_messages=prompts, - model_parameters={ - "max_tokens": 100, - "temperature": 1 - }, - stream=False - ) - answer = response.message.content - result_dict = json.loads(answer) + with measure_time() as timer: + response = model_instance.invoke_llm( + prompt_messages=prompts, + model_parameters={ + "max_tokens": 100, + "temperature": 1 + }, + stream=False + ) + answer = response.message.content + cleaned_answer = re.sub(r'^.*(\{.*\}).*$', r'\1', answer, flags=re.DOTALL) + result_dict = json.loads(cleaned_answer) answer = result_dict['Your Output'] name = answer.strip() if len(name) > 75: name = name[:75] + '...' + # get tracing instance + trace_manager = TraceQueueManager(app_id=app_id) + trace_manager.add_trace_task( + TraceTask( + TraceTaskName.GENERATE_NAME_TRACE, + conversation_id=conversation_id, + generate_conversation_name=name, + inputs=prompt, + timer=timer, + tenant_id=tenant_id, + ) + ) + return name @classmethod diff --git a/api/core/model_runtime/model_providers/tongyi/_common.py b/api/core/model_runtime/model_providers/tongyi/_common.py index dfc010266676df..fab18b41fd0487 100644 --- a/api/core/model_runtime/model_providers/tongyi/_common.py +++ b/api/core/model_runtime/model_providers/tongyi/_common.py @@ -1,4 +1,20 @@ -from core.model_runtime.errors.invoke import InvokeError +from dashscope.common.error import ( + AuthenticationError, + InvalidParameter, + RequestFailure, + ServiceUnavailableError, + UnsupportedHTTPMethod, + UnsupportedModel, +) + +from core.model_runtime.errors.invoke import ( + InvokeAuthorizationError, + InvokeBadRequestError, + InvokeConnectionError, + InvokeError, + InvokeRateLimitError, + InvokeServerUnavailableError, +) class _CommonTongyi: @@ -20,4 +36,20 @@ def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]] :return: Invoke error mapping """ - pass + return { + InvokeConnectionError: [ + RequestFailure, + ], + InvokeServerUnavailableError: [ + ServiceUnavailableError, + ], + InvokeRateLimitError: [], + InvokeAuthorizationError: [ + AuthenticationError, + ], + InvokeBadRequestError: [ + InvalidParameter, + UnsupportedModel, + UnsupportedHTTPMethod, + ] + } diff --git a/api/core/moderation/input_moderation.py b/api/core/moderation/input_moderation.py index 8fbc0c2d5003f6..3482d5c5cfd334 100644 --- a/api/core/moderation/input_moderation.py +++ b/api/core/moderation/input_moderation.py @@ -1,18 +1,25 @@ import logging +from typing import Optional from core.app.app_config.entities import AppConfig from core.moderation.base import ModerationAction, ModerationException from core.moderation.factory import ModerationFactory +from core.ops.ops_trace_manager import TraceQueueManager, TraceTask, TraceTaskName +from core.ops.utils import measure_time logger = logging.getLogger(__name__) class InputModeration: - def check(self, app_id: str, - tenant_id: str, - app_config: AppConfig, - inputs: dict, - query: str) -> tuple[bool, dict, str]: + def check( + self, app_id: str, + tenant_id: str, + app_config: AppConfig, + inputs: dict, + query: str, + message_id: str, + trace_manager: Optional[TraceQueueManager] = None + ) -> tuple[bool, dict, str]: """ Process sensitive_word_avoidance. :param app_id: app id @@ -20,6 +27,8 @@ def check(self, app_id: str, :param app_config: app config :param inputs: inputs :param query: query + :param message_id: message id + :param trace_manager: trace manager :return: """ if not app_config.sensitive_word_avoidance: @@ -35,8 +44,20 @@ def check(self, app_id: str, config=sensitive_word_avoidance_config.config ) - moderation_result = moderation_factory.moderation_for_inputs(inputs, query) + with measure_time() as timer: + moderation_result = moderation_factory.moderation_for_inputs(inputs, query) + if trace_manager: + trace_manager.add_trace_task( + TraceTask( + TraceTaskName.MODERATION_TRACE, + message_id=message_id, + moderation_result=moderation_result, + inputs=inputs, + timer=timer + ) + ) + if not moderation_result.flagged: return False, inputs, query diff --git a/api/requirements.txt b/api/core/ops/__init__.py similarity index 100% rename from api/requirements.txt rename to api/core/ops/__init__.py diff --git a/api/core/ops/base_trace_instance.py b/api/core/ops/base_trace_instance.py new file mode 100644 index 00000000000000..c7af8e296339c8 --- /dev/null +++ b/api/core/ops/base_trace_instance.py @@ -0,0 +1,26 @@ +from abc import ABC, abstractmethod + +from core.ops.entities.config_entity import BaseTracingConfig +from core.ops.entities.trace_entity import BaseTraceInfo + + +class BaseTraceInstance(ABC): + """ + Base trace instance for ops trace services + """ + + @abstractmethod + def __init__(self, trace_config: BaseTracingConfig): + """ + Abstract initializer for the trace instance. + Distribute trace tasks by matching entities + """ + self.trace_config = trace_config + + @abstractmethod + def trace(self, trace_info: BaseTraceInfo): + """ + Abstract method to trace activities. + Subclasses must implement specific tracing logic for activities. + """ + ... \ No newline at end of file diff --git a/api/core/ops/entities/__init__.py b/api/core/ops/entities/__init__.py new file mode 100644 index 00000000000000..e69de29bb2d1d6 diff --git a/api/core/ops/entities/config_entity.py b/api/core/ops/entities/config_entity.py new file mode 100644 index 00000000000000..566bbf51ac945c --- /dev/null +++ b/api/core/ops/entities/config_entity.py @@ -0,0 +1,51 @@ +from enum import Enum + +from pydantic import BaseModel, ValidationInfo, field_validator + + +class TracingProviderEnum(Enum): + LANGFUSE = 'langfuse' + LANGSMITH = 'langsmith' + + +class BaseTracingConfig(BaseModel): + """ + Base model class for tracing + """ + ... + + +class LangfuseConfig(BaseTracingConfig): + """ + Model class for Langfuse tracing config. + """ + public_key: str + secret_key: str + host: str = 'https://api.langfuse.com' + + @field_validator("host") + def set_value(cls, v, info: ValidationInfo): + if v is None or v == "": + v = 'https://api.langfuse.com' + if not v.startswith('https://'): + raise ValueError('host must start with https://') + + return v + + +class LangSmithConfig(BaseTracingConfig): + """ + Model class for Langsmith tracing config. + """ + api_key: str + project: str + endpoint: str = 'https://api.smith.langchain.com' + + @field_validator("endpoint") + def set_value(cls, v, info: ValidationInfo): + if v is None or v == "": + v = 'https://api.smith.langchain.com' + if not v.startswith('https://'): + raise ValueError('endpoint must start with https://') + + return v diff --git a/api/core/ops/entities/trace_entity.py b/api/core/ops/entities/trace_entity.py new file mode 100644 index 00000000000000..b615f21e6c99ff --- /dev/null +++ b/api/core/ops/entities/trace_entity.py @@ -0,0 +1,98 @@ +from datetime import datetime +from typing import Any, Optional, Union + +from pydantic import BaseModel, ConfigDict, field_validator + + +class BaseTraceInfo(BaseModel): + message_id: Optional[str] = None + message_data: Optional[Any] = None + inputs: Optional[Union[str, dict[str, Any], list]] = None + outputs: Optional[Union[str, dict[str, Any], list]] = None + start_time: Optional[datetime] = None + end_time: Optional[datetime] = None + metadata: dict[str, Any] + + @field_validator("inputs", "outputs") + def ensure_type(cls, v): + if v is None: + return None + if isinstance(v, str | dict | list): + return v + else: + return "" + +class WorkflowTraceInfo(BaseTraceInfo): + workflow_data: Any + conversation_id: Optional[str] = None + workflow_app_log_id: Optional[str] = None + workflow_id: str + tenant_id: str + workflow_run_id: str + workflow_run_elapsed_time: Union[int, float] + workflow_run_status: str + workflow_run_inputs: dict[str, Any] + workflow_run_outputs: dict[str, Any] + workflow_run_version: str + error: Optional[str] = None + total_tokens: int + file_list: list[str] + query: str + metadata: dict[str, Any] + + +class MessageTraceInfo(BaseTraceInfo): + conversation_model: str + message_tokens: int + answer_tokens: int + total_tokens: int + error: Optional[str] = None + file_list: Optional[Union[str, dict[str, Any], list]] = None + message_file_data: Optional[Any] = None + conversation_mode: str + + +class ModerationTraceInfo(BaseTraceInfo): + flagged: bool + action: str + preset_response: str + query: str + + +class SuggestedQuestionTraceInfo(BaseTraceInfo): + total_tokens: int + status: Optional[str] = None + error: Optional[str] = None + from_account_id: Optional[str] = None + agent_based: Optional[bool] = None + from_source: Optional[str] = None + model_provider: Optional[str] = None + model_id: Optional[str] = None + suggested_question: list[str] + level: str + status_message: Optional[str] = None + workflow_run_id: Optional[str] = None + + model_config = ConfigDict(protected_namespaces=()) + + +class DatasetRetrievalTraceInfo(BaseTraceInfo): + documents: Any + + +class ToolTraceInfo(BaseTraceInfo): + tool_name: str + tool_inputs: dict[str, Any] + tool_outputs: str + metadata: dict[str, Any] + message_file_data: Any + error: Optional[str] = None + tool_config: dict[str, Any] + time_cost: Union[int, float] + tool_parameters: dict[str, Any] + file_url: Union[str, None, list] + + +class GenerateNameTraceInfo(BaseTraceInfo): + conversation_id: str + tenant_id: str diff --git a/api/core/ops/langfuse_trace/__init__.py b/api/core/ops/langfuse_trace/__init__.py new file mode 100644 index 00000000000000..e69de29bb2d1d6 diff --git a/api/core/ops/langfuse_trace/entities/__init__.py b/api/core/ops/langfuse_trace/entities/__init__.py new file mode 100644 index 00000000000000..e69de29bb2d1d6 diff --git a/api/core/ops/langfuse_trace/entities/langfuse_trace_entity.py b/api/core/ops/langfuse_trace/entities/langfuse_trace_entity.py new file mode 100644 index 00000000000000..b90c05f4cbc605 --- /dev/null +++ b/api/core/ops/langfuse_trace/entities/langfuse_trace_entity.py @@ -0,0 +1,280 @@ +from datetime import datetime +from enum import Enum +from typing import Any, Optional, Union + +from pydantic import BaseModel, ConfigDict, Field, field_validator +from pydantic_core.core_schema import ValidationInfo + +from core.ops.utils import replace_text_with_content + + +def validate_input_output(v, field_name): + """ + Validate input output + :param v: + :param field_name: + :return: + """ + if v == {} or v is None: + return v + if isinstance(v, str): + return [ + { + "role": "assistant" if field_name == "output" else "user", + "content": v, + } + ] + elif isinstance(v, list): + if len(v) > 0 and isinstance(v[0], dict): + v = replace_text_with_content(data=v) + return v + else: + return [ + { + "role": "assistant" if field_name == "output" else "user", + "content": str(v), + } + ] + + return v + + +class LevelEnum(str, Enum): + DEBUG = "DEBUG" + WARNING = "WARNING" + ERROR = "ERROR" + DEFAULT = "DEFAULT" + + +class LangfuseTrace(BaseModel): + """ + Langfuse trace model + """ + id: Optional[str] = Field( + default=None, + description="The id of the trace can be set, defaults to a random id. Used to link traces to external systems " + "or when creating a distributed trace. Traces are upserted on id.", + ) + name: Optional[str] = Field( + default=None, + description="Identifier of the trace. Useful for sorting/filtering in the UI.", + ) + input: Optional[Union[str, dict[str, Any], list, None]] = Field( + default=None, description="The input of the trace. Can be any JSON object." + ) + output: Optional[Union[str, dict[str, Any], list, None]] = Field( + default=None, description="The output of the trace. Can be any JSON object." + ) + metadata: Optional[dict[str, Any]] = Field( + default=None, + description="Additional metadata of the trace. Can be any JSON object. Metadata is merged when being updated " + "via the API.", + ) + user_id: Optional[str] = Field( + default=None, + description="The id of the user that triggered the execution. Used to provide user-level analytics.", + ) + session_id: Optional[str] = Field( + default=None, + description="Used to group multiple traces into a session in Langfuse. Use your own session/thread identifier.", + ) + version: Optional[str] = Field( + default=None, + description="The version of the trace type. Used to understand how changes to the trace type affect metrics. " + "Useful in debugging.", + ) + release: Optional[str] = Field( + default=None, + description="The release identifier of the current deployment. Used to understand how changes of different " + "deployments affect metrics. Useful in debugging.", + ) + tags: Optional[list[str]] = Field( + default=None, + description="Tags are used to categorize or label traces. Traces can be filtered by tags in the UI and GET " + "API. Tags can also be changed in the UI. Tags are merged and never deleted via the API.", + ) + public: Optional[bool] = Field( + default=None, + description="You can make a trace public to share it via a public link. This allows others to view the trace " + "without needing to log in or be members of your Langfuse project.", + ) + + @field_validator("input", "output") + def ensure_dict(cls, v, info: ValidationInfo): + field_name = info.field_name + return validate_input_output(v, field_name) + + +class LangfuseSpan(BaseModel): + """ + Langfuse span model + """ + id: Optional[str] = Field( + default=None, + description="The id of the span can be set, otherwise a random id is generated. Spans are upserted on id.", + ) + session_id: Optional[str] = Field( + default=None, + description="Used to group multiple spans into a session in Langfuse. Use your own session/thread identifier.", + ) + trace_id: Optional[str] = Field( + default=None, + description="The id of the trace the span belongs to. Used to link spans to traces.", + ) + user_id: Optional[str] = Field( + default=None, + description="The id of the user that triggered the execution. Used to provide user-level analytics.", + ) + start_time: Optional[datetime | str] = Field( + default_factory=datetime.now, + description="The time at which the span started, defaults to the current time.", + ) + end_time: Optional[datetime | str] = Field( + default=None, + description="The time at which the span ended. Automatically set by span.end().", + ) + name: Optional[str] = Field( + default=None, + description="Identifier of the span. Useful for sorting/filtering in the UI.", + ) + metadata: Optional[dict[str, Any]] = Field( + default=None, + description="Additional metadata of the span. Can be any JSON object. Metadata is merged when being updated " + "via the API.", + ) + level: Optional[str] = Field( + default=None, + description="The level of the span. Can be DEBUG, DEFAULT, WARNING or ERROR. Used for sorting/filtering of " + "traces with elevated error levels and for highlighting in the UI.", + ) + status_message: Optional[str] = Field( + default=None, + description="The status message of the span. Additional field for context of the event. E.g. the error " + "message of an error event.", + ) + input: Optional[Union[str, dict[str, Any], list, None]] = Field( + default=None, description="The input of the span. Can be any JSON object." + ) + output: Optional[Union[str, dict[str, Any], list, None]] = Field( + default=None, description="The output of the span. Can be any JSON object." + ) + version: Optional[str] = Field( + default=None, + description="The version of the span type. Used to understand how changes to the span type affect metrics. " + "Useful in debugging.", + ) + parent_observation_id: Optional[str] = Field( + default=None, + description="The id of the observation the span belongs to. Used to link spans to observations.", + ) + + @field_validator("input", "output") + def ensure_dict(cls, v, info: ValidationInfo): + field_name = info.field_name + return validate_input_output(v, field_name) + + +class UnitEnum(str, Enum): + CHARACTERS = "CHARACTERS" + TOKENS = "TOKENS" + SECONDS = "SECONDS" + MILLISECONDS = "MILLISECONDS" + IMAGES = "IMAGES" + + +class GenerationUsage(BaseModel): + promptTokens: Optional[int] = None + completionTokens: Optional[int] = None + totalTokens: Optional[int] = None + input: Optional[int] = None + output: Optional[int] = None + total: Optional[int] = None + unit: Optional[UnitEnum] = None + inputCost: Optional[float] = None + outputCost: Optional[float] = None + totalCost: Optional[float] = None + + @field_validator("input", "output") + def ensure_dict(cls, v, info: ValidationInfo): + field_name = info.field_name + return validate_input_output(v, field_name) + + +class LangfuseGeneration(BaseModel): + id: Optional[str] = Field( + default=None, + description="The id of the generation can be set, defaults to random id.", + ) + trace_id: Optional[str] = Field( + default=None, + description="The id of the trace the generation belongs to. Used to link generations to traces.", + ) + parent_observation_id: Optional[str] = Field( + default=None, + description="The id of the observation the generation belongs to. Used to link generations to observations.", + ) + name: Optional[str] = Field( + default=None, + description="Identifier of the generation. Useful for sorting/filtering in the UI.", + ) + start_time: Optional[datetime | str] = Field( + default_factory=datetime.now, + description="The time at which the generation started, defaults to the current time.", + ) + completion_start_time: Optional[datetime | str] = Field( + default=None, + description="The time at which the completion started (streaming). Set it to get latency analytics broken " + "down into time until completion started and completion duration.", + ) + end_time: Optional[datetime | str] = Field( + default=None, + description="The time at which the generation ended. Automatically set by generation.end().", + ) + model: Optional[str] = Field( + default=None, description="The name of the model used for the generation." + ) + model_parameters: Optional[dict[str, Any]] = Field( + default=None, + description="The parameters of the model used for the generation; can be any key-value pairs.", + ) + input: Optional[Any] = Field( + default=None, + description="The prompt used for the generation. Can be any string or JSON object.", + ) + output: Optional[Any] = Field( + default=None, + description="The completion generated by the model. Can be any string or JSON object.", + ) + usage: Optional[GenerationUsage] = Field( + default=None, + description="The usage object supports the OpenAi structure with tokens and a more generic version with " + "detailed costs and units.", + ) + metadata: Optional[dict[str, Any]] = Field( + default=None, + description="Additional metadata of the generation. Can be any JSON object. Metadata is merged when being " + "updated via the API.", + ) + level: Optional[LevelEnum] = Field( + default=None, + description="The level of the generation. Can be DEBUG, DEFAULT, WARNING or ERROR. Used for sorting/filtering " + "of traces with elevated error levels and for highlighting in the UI.", + ) + status_message: Optional[str] = Field( + default=None, + description="The status message of the generation. Additional field for context of the event. E.g. the error " + "message of an error event.", + ) + version: Optional[str] = Field( + default=None, + description="The version of the generation type. Used to understand how changes to the span type affect " + "metrics. Useful in debugging.", + ) + + model_config = ConfigDict(protected_namespaces=()) + + @field_validator("input", "output") + def ensure_dict(cls, v, info: ValidationInfo): + field_name = info.field_name + return validate_input_output(v, field_name) + diff --git a/api/core/ops/langfuse_trace/langfuse_trace.py b/api/core/ops/langfuse_trace/langfuse_trace.py new file mode 100644 index 00000000000000..05d34c5527b0a3 --- /dev/null +++ b/api/core/ops/langfuse_trace/langfuse_trace.py @@ -0,0 +1,392 @@ +import json +import logging +import os +from datetime import datetime, timedelta +from typing import Optional + +from langfuse import Langfuse + +from core.ops.base_trace_instance import BaseTraceInstance +from core.ops.entities.config_entity import LangfuseConfig +from core.ops.entities.trace_entity import ( + BaseTraceInfo, + DatasetRetrievalTraceInfo, + GenerateNameTraceInfo, + MessageTraceInfo, + ModerationTraceInfo, + SuggestedQuestionTraceInfo, + ToolTraceInfo, + WorkflowTraceInfo, +) +from core.ops.langfuse_trace.entities.langfuse_trace_entity import ( + GenerationUsage, + LangfuseGeneration, + LangfuseSpan, + LangfuseTrace, + LevelEnum, + UnitEnum, +) +from core.ops.utils import filter_none_values +from extensions.ext_database import db +from models.model import EndUser +from models.workflow import WorkflowNodeExecution + +logger = logging.getLogger(__name__) + + +class LangFuseDataTrace(BaseTraceInstance): + def __init__( + self, + langfuse_config: LangfuseConfig, + ): + super().__init__(langfuse_config) + self.langfuse_client = Langfuse( + public_key=langfuse_config.public_key, + secret_key=langfuse_config.secret_key, + host=langfuse_config.host, + ) + self.file_base_url = os.getenv("FILES_URL", "http://127.0.0.1:5001") + + def trace(self, trace_info: BaseTraceInfo): + if isinstance(trace_info, WorkflowTraceInfo): + self.workflow_trace(trace_info) + if isinstance(trace_info, MessageTraceInfo): + self.message_trace(trace_info) + if isinstance(trace_info, ModerationTraceInfo): + self.moderation_trace(trace_info) + if isinstance(trace_info, SuggestedQuestionTraceInfo): + self.suggested_question_trace(trace_info) + if isinstance(trace_info, DatasetRetrievalTraceInfo): + self.dataset_retrieval_trace(trace_info) + if isinstance(trace_info, ToolTraceInfo): + self.tool_trace(trace_info) + if isinstance(trace_info, GenerateNameTraceInfo): + self.generate_name_trace(trace_info) + + def workflow_trace(self, trace_info: WorkflowTraceInfo): + trace_id = trace_info.workflow_app_log_id if trace_info.workflow_app_log_id else trace_info.workflow_run_id + if trace_info.message_id: + trace_id = trace_info.message_id + name = f"message_{trace_info.message_id}" + trace_data = LangfuseTrace( + id=trace_info.message_id, + user_id=trace_info.tenant_id, + name=name, + input=trace_info.workflow_run_inputs, + output=trace_info.workflow_run_outputs, + metadata=trace_info.metadata, + session_id=trace_info.conversation_id, + tags=["message", "workflow"], + ) + self.add_trace(langfuse_trace_data=trace_data) + workflow_span_data = LangfuseSpan( + id=trace_info.workflow_app_log_id if trace_info.workflow_app_log_id else trace_info.workflow_run_id, + name=f"workflow_{trace_info.workflow_app_log_id}" if trace_info.workflow_app_log_id else f"workflow_{trace_info.workflow_run_id}", + input=trace_info.workflow_run_inputs, + output=trace_info.workflow_run_outputs, + trace_id=trace_id, + start_time=trace_info.start_time, + end_time=trace_info.end_time, + metadata=trace_info.metadata, + level=LevelEnum.DEFAULT if trace_info.error == "" else LevelEnum.ERROR, + status_message=trace_info.error if trace_info.error else "", + ) + self.add_span(langfuse_span_data=workflow_span_data) + else: + trace_data = LangfuseTrace( + id=trace_id, + user_id=trace_info.tenant_id, + name=f"workflow_{trace_info.workflow_app_log_id}" if trace_info.workflow_app_log_id else f"workflow_{trace_info.workflow_run_id}", + input=trace_info.workflow_run_inputs, + output=trace_info.workflow_run_outputs, + metadata=trace_info.metadata, + session_id=trace_info.conversation_id, + tags=["workflow"], + ) + self.add_trace(langfuse_trace_data=trace_data) + + # through workflow_run_id get all_nodes_execution + workflow_nodes_executions = ( + db.session.query(WorkflowNodeExecution) + .filter(WorkflowNodeExecution.workflow_run_id == trace_info.workflow_run_id) + .order_by(WorkflowNodeExecution.index.desc()) + .all() + ) + + for node_execution in workflow_nodes_executions: + node_execution_id = node_execution.id + tenant_id = node_execution.tenant_id + app_id = node_execution.app_id + node_name = node_execution.title + node_type = node_execution.node_type + status = node_execution.status + if node_type == "llm": + inputs = json.loads(node_execution.process_data).get("prompts", {}) + else: + inputs = json.loads(node_execution.inputs) if node_execution.inputs else {} + outputs = ( + json.loads(node_execution.outputs) if node_execution.outputs else {} + ) + created_at = node_execution.created_at if node_execution.created_at else datetime.now() + elapsed_time = node_execution.elapsed_time + finished_at = created_at + timedelta(seconds=elapsed_time) + + metadata = json.loads(node_execution.execution_metadata) if node_execution.execution_metadata else {} + metadata.update( + { + "workflow_run_id": trace_info.workflow_run_id, + "node_execution_id": node_execution_id, + "tenant_id": tenant_id, + "app_id": app_id, + "node_name": node_name, + "node_type": node_type, + "status": status, + } + ) + + # add span + if trace_info.message_id: + span_data = LangfuseSpan( + name=f"{node_name}_{node_execution_id}", + input=inputs, + output=outputs, + trace_id=trace_id, + start_time=created_at, + end_time=finished_at, + metadata=metadata, + level=LevelEnum.DEFAULT if status == 'succeeded' else LevelEnum.ERROR, + status_message=trace_info.error if trace_info.error else "", + parent_observation_id=trace_info.workflow_app_log_id if trace_info.workflow_app_log_id else trace_info.workflow_run_id, + ) + else: + span_data = LangfuseSpan( + name=f"{node_name}_{node_execution_id}", + input=inputs, + output=outputs, + trace_id=trace_id, + start_time=created_at, + end_time=finished_at, + metadata=metadata, + level=LevelEnum.DEFAULT if status == 'succeeded' else LevelEnum.ERROR, + status_message=trace_info.error if trace_info.error else "", + ) + + self.add_span(langfuse_span_data=span_data) + + def message_trace( + self, trace_info: MessageTraceInfo, **kwargs + ): + # get message file data + file_list = trace_info.file_list + metadata = trace_info.metadata + message_data = trace_info.message_data + message_id = message_data.id + + user_id = message_data.from_account_id + if message_data.from_end_user_id: + end_user_data: EndUser = db.session.query(EndUser).filter( + EndUser.id == message_data.from_end_user_id + ).first().session_id + user_id = end_user_data.session_id + + trace_data = LangfuseTrace( + id=message_id, + user_id=user_id, + name=f"message_{message_id}", + input={ + "message": trace_info.inputs, + "files": file_list, + "message_tokens": trace_info.message_tokens, + "answer_tokens": trace_info.answer_tokens, + "total_tokens": trace_info.total_tokens, + "error": trace_info.error, + "provider_response_latency": message_data.provider_response_latency, + "created_at": trace_info.start_time, + }, + output=trace_info.outputs, + metadata=metadata, + session_id=message_data.conversation_id, + tags=["message", str(trace_info.conversation_mode)], + version=None, + release=None, + public=None, + ) + self.add_trace(langfuse_trace_data=trace_data) + + # start add span + generation_usage = GenerationUsage( + totalTokens=trace_info.total_tokens, + input=trace_info.message_tokens, + output=trace_info.answer_tokens, + total=trace_info.total_tokens, + unit=UnitEnum.TOKENS, + ) + + langfuse_generation_data = LangfuseGeneration( + name=f"generation_{message_id}", + trace_id=message_id, + start_time=trace_info.start_time, + end_time=trace_info.end_time, + model=message_data.model_id, + input=trace_info.inputs, + output=message_data.answer, + metadata=metadata, + level=LevelEnum.DEFAULT if message_data.status != 'error' else LevelEnum.ERROR, + status_message=message_data.error if message_data.error else "", + usage=generation_usage, + ) + + self.add_generation(langfuse_generation_data) + + def moderation_trace(self, trace_info: ModerationTraceInfo): + span_data = LangfuseSpan( + name="moderation", + input=trace_info.inputs, + output={ + "action": trace_info.action, + "flagged": trace_info.flagged, + "preset_response": trace_info.preset_response, + "inputs": trace_info.inputs, + }, + trace_id=trace_info.message_id, + start_time=trace_info.start_time or trace_info.message_data.created_at, + end_time=trace_info.end_time or trace_info.message_data.created_at, + metadata=trace_info.metadata, + ) + + self.add_span(langfuse_span_data=span_data) + + def suggested_question_trace(self, trace_info: SuggestedQuestionTraceInfo): + message_data = trace_info.message_data + generation_usage = GenerationUsage( + totalTokens=len(str(trace_info.suggested_question)), + input=len(trace_info.inputs), + output=len(trace_info.suggested_question), + total=len(trace_info.suggested_question), + unit=UnitEnum.CHARACTERS, + ) + + generation_data = LangfuseGeneration( + name="suggested_question", + input=trace_info.inputs, + output=str(trace_info.suggested_question), + trace_id=trace_info.message_id, + start_time=trace_info.start_time, + end_time=trace_info.end_time, + metadata=trace_info.metadata, + level=LevelEnum.DEFAULT if message_data.status != 'error' else LevelEnum.ERROR, + status_message=message_data.error if message_data.error else "", + usage=generation_usage, + ) + + self.add_generation(langfuse_generation_data=generation_data) + + def dataset_retrieval_trace(self, trace_info: DatasetRetrievalTraceInfo): + dataset_retrieval_span_data = LangfuseSpan( + name="dataset_retrieval", + input=trace_info.inputs, + output={"documents": trace_info.documents}, + trace_id=trace_info.message_id, + start_time=trace_info.start_time or trace_info.message_data.created_at, + end_time=trace_info.end_time or trace_info.message_data.updated_at, + metadata=trace_info.metadata, + ) + + self.add_span(langfuse_span_data=dataset_retrieval_span_data) + + def tool_trace(self, trace_info: ToolTraceInfo): + tool_span_data = LangfuseSpan( + name=trace_info.tool_name, + input=trace_info.tool_inputs, + output=trace_info.tool_outputs, + trace_id=trace_info.message_id, + start_time=trace_info.start_time, + end_time=trace_info.end_time, + metadata=trace_info.metadata, + level=LevelEnum.DEFAULT if trace_info.error == "" else LevelEnum.ERROR, + status_message=trace_info.error, + ) + + self.add_span(langfuse_span_data=tool_span_data) + + def generate_name_trace(self, trace_info: GenerateNameTraceInfo): + name_generation_trace_data = LangfuseTrace( + name="generate_name", + input=trace_info.inputs, + output=trace_info.outputs, + user_id=trace_info.tenant_id, + metadata=trace_info.metadata, + session_id=trace_info.conversation_id, + ) + + self.add_trace(langfuse_trace_data=name_generation_trace_data) + + name_generation_span_data = LangfuseSpan( + name="generate_name", + input=trace_info.inputs, + output=trace_info.outputs, + trace_id=trace_info.conversation_id, + start_time=trace_info.start_time, + end_time=trace_info.end_time, + metadata=trace_info.metadata, + ) + self.add_span(langfuse_span_data=name_generation_span_data) + + def add_trace(self, langfuse_trace_data: Optional[LangfuseTrace] = None): + format_trace_data = ( + filter_none_values(langfuse_trace_data.model_dump()) if langfuse_trace_data else {} + ) + try: + self.langfuse_client.trace(**format_trace_data) + logger.debug("LangFuse Trace created successfully") + except Exception as e: + raise ValueError(f"LangFuse Failed to create trace: {str(e)}") + + def add_span(self, langfuse_span_data: Optional[LangfuseSpan] = None): + format_span_data = ( + filter_none_values(langfuse_span_data.model_dump()) if langfuse_span_data else {} + ) + try: + self.langfuse_client.span(**format_span_data) + logger.debug("LangFuse Span created successfully") + except Exception as e: + raise ValueError(f"LangFuse Failed to create span: {str(e)}") + + def update_span(self, span, langfuse_span_data: Optional[LangfuseSpan] = None): + format_span_data = ( + filter_none_values(langfuse_span_data.model_dump()) if langfuse_span_data else {} + ) + + span.end(**format_span_data) + + def add_generation( + self, langfuse_generation_data: Optional[LangfuseGeneration] = None + ): + format_generation_data = ( + filter_none_values(langfuse_generation_data.model_dump()) + if langfuse_generation_data + else {} + ) + try: + self.langfuse_client.generation(**format_generation_data) + logger.debug("LangFuse Generation created successfully") + except Exception as e: + raise ValueError(f"LangFuse Failed to create generation: {str(e)}") + + def update_generation( + self, generation, langfuse_generation_data: Optional[LangfuseGeneration] = None + ): + format_generation_data = ( + filter_none_values(langfuse_generation_data.model_dump()) + if langfuse_generation_data + else {} + ) + + generation.end(**format_generation_data) + + def api_check(self): + try: + return self.langfuse_client.auth_check() + except Exception as e: + logger.debug(f"LangFuse API check failed: {str(e)}") + raise ValueError(f"LangFuse API check failed: {str(e)}") diff --git a/api/core/ops/langsmith_trace/__init__.py b/api/core/ops/langsmith_trace/__init__.py new file mode 100644 index 00000000000000..e69de29bb2d1d6 diff --git a/api/core/ops/langsmith_trace/entities/__init__.py b/api/core/ops/langsmith_trace/entities/__init__.py new file mode 100644 index 00000000000000..e69de29bb2d1d6 diff --git a/api/core/ops/langsmith_trace/entities/langsmith_trace_entity.py b/api/core/ops/langsmith_trace/entities/langsmith_trace_entity.py new file mode 100644 index 00000000000000..f3fc46d99a8692 --- /dev/null +++ b/api/core/ops/langsmith_trace/entities/langsmith_trace_entity.py @@ -0,0 +1,167 @@ +from datetime import datetime +from enum import Enum +from typing import Any, Optional, Union + +from pydantic import BaseModel, Field, field_validator +from pydantic_core.core_schema import ValidationInfo + +from core.ops.utils import replace_text_with_content + + +class LangSmithRunType(str, Enum): + tool = "tool" + chain = "chain" + llm = "llm" + retriever = "retriever" + embedding = "embedding" + prompt = "prompt" + parser = "parser" + + +class LangSmithTokenUsage(BaseModel): + input_tokens: Optional[int] = None + output_tokens: Optional[int] = None + total_tokens: Optional[int] = None + + +class LangSmithMultiModel(BaseModel): + file_list: Optional[list[str]] = Field(None, description="List of files") + + +class LangSmithRunModel(LangSmithTokenUsage, LangSmithMultiModel): + name: Optional[str] = Field(..., description="Name of the run") + inputs: Optional[Union[str, dict[str, Any], list, None]] = Field(None, description="Inputs of the run") + outputs: Optional[Union[str, dict[str, Any], list, None]] = Field(None, description="Outputs of the run") + run_type: LangSmithRunType = Field(..., description="Type of the run") + start_time: Optional[datetime | str] = Field(None, description="Start time of the run") + end_time: Optional[datetime | str] = Field(None, description="End time of the run") + extra: Optional[dict[str, Any]] = Field( + None, description="Extra information of the run" + ) + error: Optional[str] = Field(None, description="Error message of the run") + serialized: Optional[dict[str, Any]] = Field( + None, description="Serialized data of the run" + ) + parent_run_id: Optional[str] = Field(None, description="Parent run ID") + events: Optional[list[dict[str, Any]]] = Field( + None, description="Events associated with the run" + ) + tags: Optional[list[str]] = Field(None, description="Tags associated with the run") + trace_id: Optional[str] = Field( + None, description="Trace ID associated with the run" + ) + dotted_order: Optional[str] = Field(None, description="Dotted order of the run") + id: Optional[str] = Field(None, description="ID of the run") + session_id: Optional[str] = Field( + None, description="Session ID associated with the run" + ) + session_name: Optional[str] = Field( + None, description="Session name associated with the run" + ) + reference_example_id: Optional[str] = Field( + None, description="Reference example ID associated with the run" + ) + input_attachments: Optional[dict[str, Any]] = Field( + None, description="Input attachments of the run" + ) + output_attachments: Optional[dict[str, Any]] = Field( + None, description="Output attachments of the run" + ) + + @field_validator("inputs", "outputs") + def ensure_dict(cls, v, info: ValidationInfo): + field_name = info.field_name + values = info.data + if v == {} or v is None: + return v + usage_metadata = { + "input_tokens": values.get('input_tokens', 0), + "output_tokens": values.get('output_tokens', 0), + "total_tokens": values.get('total_tokens', 0), + } + file_list = values.get("file_list", []) + if isinstance(v, str): + if field_name == "inputs": + return { + "messages": { + "role": "user", + "content": v, + "usage_metadata": usage_metadata, + "file_list": file_list, + }, + } + elif field_name == "outputs": + return { + "choices": { + "role": "ai", + "content": v, + "usage_metadata": usage_metadata, + "file_list": file_list, + }, + } + elif isinstance(v, list): + data = {} + if len(v) > 0 and isinstance(v[0], dict): + # rename text to content + v = replace_text_with_content(data=v) + if field_name == "inputs": + data = { + "messages": v, + } + elif field_name == "outputs": + data = { + "choices": { + "role": "ai", + "content": v, + "usage_metadata": usage_metadata, + "file_list": file_list, + }, + } + return data + else: + return { + "choices": { + "role": "ai" if field_name == "outputs" else "user", + "content": str(v), + "usage_metadata": usage_metadata, + "file_list": file_list, + }, + } + if isinstance(v, dict): + v["usage_metadata"] = usage_metadata + v["file_list"] = file_list + return v + return v + + @field_validator("start_time", "end_time") + def format_time(cls, v, info: ValidationInfo): + if not isinstance(v, datetime): + raise ValueError(f"{info.field_name} must be a datetime object") + else: + return v.strftime("%Y-%m-%dT%H:%M:%S.%fZ") + + +class LangSmithRunUpdateModel(BaseModel): + run_id: str = Field(..., description="ID of the run") + trace_id: Optional[str] = Field( + None, description="Trace ID associated with the run" + ) + dotted_order: Optional[str] = Field(None, description="Dotted order of the run") + parent_run_id: Optional[str] = Field(None, description="Parent run ID") + end_time: Optional[datetime | str] = Field(None, description="End time of the run") + error: Optional[str] = Field(None, description="Error message of the run") + inputs: Optional[dict[str, Any]] = Field(None, description="Inputs of the run") + outputs: Optional[dict[str, Any]] = Field(None, description="Outputs of the run") + events: Optional[list[dict[str, Any]]] = Field( + None, description="Events associated with the run" + ) + tags: Optional[list[str]] = Field(None, description="Tags associated with the run") + extra: Optional[dict[str, Any]] = Field( + None, description="Extra information of the run" + ) + input_attachments: Optional[dict[str, Any]] = Field( + None, description="Input attachments of the run" + ) + output_attachments: Optional[dict[str, Any]] = Field( + None, description="Output attachments of the run" + ) diff --git a/api/core/ops/langsmith_trace/langsmith_trace.py b/api/core/ops/langsmith_trace/langsmith_trace.py new file mode 100644 index 00000000000000..422830fb1e4df4 --- /dev/null +++ b/api/core/ops/langsmith_trace/langsmith_trace.py @@ -0,0 +1,355 @@ +import json +import logging +import os +from datetime import datetime, timedelta + +from langsmith import Client + +from core.ops.base_trace_instance import BaseTraceInstance +from core.ops.entities.config_entity import LangSmithConfig +from core.ops.entities.trace_entity import ( + BaseTraceInfo, + DatasetRetrievalTraceInfo, + GenerateNameTraceInfo, + MessageTraceInfo, + ModerationTraceInfo, + SuggestedQuestionTraceInfo, + ToolTraceInfo, + WorkflowTraceInfo, +) +from core.ops.langsmith_trace.entities.langsmith_trace_entity import ( + LangSmithRunModel, + LangSmithRunType, + LangSmithRunUpdateModel, +) +from core.ops.utils import filter_none_values +from extensions.ext_database import db +from models.model import EndUser, MessageFile +from models.workflow import WorkflowNodeExecution + +logger = logging.getLogger(__name__) + + +class LangSmithDataTrace(BaseTraceInstance): + def __init__( + self, + langsmith_config: LangSmithConfig, + ): + super().__init__(langsmith_config) + self.langsmith_key = langsmith_config.api_key + self.project_name = langsmith_config.project + self.project_id = None + self.langsmith_client = Client( + api_key=langsmith_config.api_key, api_url=langsmith_config.endpoint + ) + self.file_base_url = os.getenv("FILES_URL", "http://127.0.0.1:5001") + + def trace(self, trace_info: BaseTraceInfo): + if isinstance(trace_info, WorkflowTraceInfo): + self.workflow_trace(trace_info) + if isinstance(trace_info, MessageTraceInfo): + self.message_trace(trace_info) + if isinstance(trace_info, ModerationTraceInfo): + self.moderation_trace(trace_info) + if isinstance(trace_info, SuggestedQuestionTraceInfo): + self.suggested_question_trace(trace_info) + if isinstance(trace_info, DatasetRetrievalTraceInfo): + self.dataset_retrieval_trace(trace_info) + if isinstance(trace_info, ToolTraceInfo): + self.tool_trace(trace_info) + if isinstance(trace_info, GenerateNameTraceInfo): + self.generate_name_trace(trace_info) + + def workflow_trace(self, trace_info: WorkflowTraceInfo): + if trace_info.message_id: + message_run = LangSmithRunModel( + id=trace_info.message_id, + name=f"message_{trace_info.message_id}", + inputs=trace_info.workflow_run_inputs, + outputs=trace_info.workflow_run_outputs, + run_type=LangSmithRunType.chain, + start_time=trace_info.start_time, + end_time=trace_info.end_time, + extra={ + "metadata": trace_info.metadata, + }, + tags=["message"], + error=trace_info.error + ) + self.add_run(message_run) + + langsmith_run = LangSmithRunModel( + file_list=trace_info.file_list, + total_tokens=trace_info.total_tokens, + id=trace_info.workflow_app_log_id if trace_info.workflow_app_log_id else trace_info.workflow_run_id, + name=f"workflow_{trace_info.workflow_app_log_id}" if trace_info.workflow_app_log_id else f"workflow_{trace_info.workflow_run_id}", + inputs=trace_info.workflow_run_inputs, + run_type=LangSmithRunType.tool, + start_time=trace_info.workflow_data.created_at, + end_time=trace_info.workflow_data.finished_at, + outputs=trace_info.workflow_run_outputs, + extra={ + "metadata": trace_info.metadata, + }, + error=trace_info.error, + tags=["workflow"], + parent_run_id=trace_info.message_id if trace_info.message_id else None, + ) + + self.add_run(langsmith_run) + + # through workflow_run_id get all_nodes_execution + workflow_nodes_executions = ( + db.session.query(WorkflowNodeExecution) + .filter(WorkflowNodeExecution.workflow_run_id == trace_info.workflow_run_id) + .order_by(WorkflowNodeExecution.index.desc()) + .all() + ) + + for node_execution in workflow_nodes_executions: + node_execution_id = node_execution.id + tenant_id = node_execution.tenant_id + app_id = node_execution.app_id + node_name = node_execution.title + node_type = node_execution.node_type + status = node_execution.status + if node_type == "llm": + inputs = json.loads(node_execution.process_data).get("prompts", {}) + else: + inputs = json.loads(node_execution.inputs) if node_execution.inputs else {} + outputs = ( + json.loads(node_execution.outputs) if node_execution.outputs else {} + ) + created_at = node_execution.created_at if node_execution.created_at else datetime.now() + elapsed_time = node_execution.elapsed_time + finished_at = created_at + timedelta(seconds=elapsed_time) + + execution_metadata = ( + json.loads(node_execution.execution_metadata) + if node_execution.execution_metadata + else {} + ) + node_total_tokens = execution_metadata.get("total_tokens", 0) + + metadata = json.loads(node_execution.execution_metadata) if node_execution.execution_metadata else {} + metadata.update( + { + "workflow_run_id": trace_info.workflow_run_id, + "node_execution_id": node_execution_id, + "tenant_id": tenant_id, + "app_id": app_id, + "app_name": node_name, + "node_type": node_type, + "status": status, + } + ) + + process_data = json.loads(node_execution.process_data) if node_execution.process_data else {} + if process_data and process_data.get("model_mode") == "chat": + run_type = LangSmithRunType.llm + elif node_type == "knowledge-retrieval": + run_type = LangSmithRunType.retriever + else: + run_type = LangSmithRunType.tool + + langsmith_run = LangSmithRunModel( + total_tokens=node_total_tokens, + name=f"{node_name}_{node_execution_id}", + inputs=inputs, + run_type=run_type, + start_time=created_at, + end_time=finished_at, + outputs=outputs, + file_list=trace_info.file_list, + extra={ + "metadata": metadata, + }, + parent_run_id=trace_info.workflow_app_log_id if trace_info.workflow_app_log_id else trace_info.workflow_run_id, + tags=["node_execution"], + ) + + self.add_run(langsmith_run) + + def message_trace(self, trace_info: MessageTraceInfo): + # get message file data + file_list = trace_info.file_list + message_file_data: MessageFile = trace_info.message_file_data + file_url = f"{self.file_base_url}/{message_file_data.url}" if message_file_data else "" + file_list.append(file_url) + metadata = trace_info.metadata + message_data = trace_info.message_data + message_id = message_data.id + + user_id = message_data.from_account_id + if message_data.from_end_user_id: + end_user_data: EndUser = db.session.query(EndUser).filter( + EndUser.id == message_data.from_end_user_id + ).first().session_id + end_user_id = end_user_data.session_id + metadata["end_user_id"] = end_user_id + metadata["user_id"] = user_id + + message_run = LangSmithRunModel( + input_tokens=trace_info.message_tokens, + output_tokens=trace_info.answer_tokens, + total_tokens=trace_info.total_tokens, + id=message_id, + name=f"message_{message_id}", + inputs=trace_info.inputs, + run_type=LangSmithRunType.chain, + start_time=trace_info.start_time, + end_time=trace_info.end_time, + outputs=message_data.answer, + extra={ + "metadata": metadata, + }, + tags=["message", str(trace_info.conversation_mode)], + error=trace_info.error, + file_list=file_list, + ) + self.add_run(message_run) + + # create llm run parented to message run + llm_run = LangSmithRunModel( + input_tokens=trace_info.message_tokens, + output_tokens=trace_info.answer_tokens, + total_tokens=trace_info.total_tokens, + name=f"llm_{message_id}", + inputs=trace_info.inputs, + run_type=LangSmithRunType.llm, + start_time=trace_info.start_time, + end_time=trace_info.end_time, + outputs=message_data.answer, + extra={ + "metadata": metadata, + }, + parent_run_id=message_id, + tags=["llm", str(trace_info.conversation_mode)], + error=trace_info.error, + file_list=file_list, + ) + self.add_run(llm_run) + + def moderation_trace(self, trace_info: ModerationTraceInfo): + langsmith_run = LangSmithRunModel( + name="moderation", + inputs=trace_info.inputs, + outputs={ + "action": trace_info.action, + "flagged": trace_info.flagged, + "preset_response": trace_info.preset_response, + "inputs": trace_info.inputs, + }, + run_type=LangSmithRunType.tool, + extra={ + "metadata": trace_info.metadata, + }, + tags=["moderation"], + parent_run_id=trace_info.message_id, + start_time=trace_info.start_time or trace_info.message_data.created_at, + end_time=trace_info.end_time or trace_info.message_data.updated_at, + ) + + self.add_run(langsmith_run) + + def suggested_question_trace(self, trace_info: SuggestedQuestionTraceInfo): + message_data = trace_info.message_data + suggested_question_run = LangSmithRunModel( + name="suggested_question", + inputs=trace_info.inputs, + outputs=trace_info.suggested_question, + run_type=LangSmithRunType.tool, + extra={ + "metadata": trace_info.metadata, + }, + tags=["suggested_question"], + parent_run_id=trace_info.message_id, + start_time=trace_info.start_time or message_data.created_at, + end_time=trace_info.end_time or message_data.updated_at, + ) + + self.add_run(suggested_question_run) + + def dataset_retrieval_trace(self, trace_info: DatasetRetrievalTraceInfo): + dataset_retrieval_run = LangSmithRunModel( + name="dataset_retrieval", + inputs=trace_info.inputs, + outputs={"documents": trace_info.documents}, + run_type=LangSmithRunType.retriever, + extra={ + "metadata": trace_info.metadata, + }, + tags=["dataset_retrieval"], + parent_run_id=trace_info.message_id, + start_time=trace_info.start_time or trace_info.message_data.created_at, + end_time=trace_info.end_time or trace_info.message_data.updated_at, + ) + + self.add_run(dataset_retrieval_run) + + def tool_trace(self, trace_info: ToolTraceInfo): + tool_run = LangSmithRunModel( + name=trace_info.tool_name, + inputs=trace_info.tool_inputs, + outputs=trace_info.tool_outputs, + run_type=LangSmithRunType.tool, + extra={ + "metadata": trace_info.metadata, + }, + tags=["tool", trace_info.tool_name], + parent_run_id=trace_info.message_id, + start_time=trace_info.start_time, + end_time=trace_info.end_time, + file_list=[trace_info.file_url], + ) + + self.add_run(tool_run) + + def generate_name_trace(self, trace_info: GenerateNameTraceInfo): + name_run = LangSmithRunModel( + name="generate_name", + inputs=trace_info.inputs, + outputs=trace_info.outputs, + run_type=LangSmithRunType.tool, + extra={ + "metadata": trace_info.metadata, + }, + tags=["generate_name"], + start_time=trace_info.start_time or datetime.now(), + end_time=trace_info.end_time or datetime.now(), + ) + + self.add_run(name_run) + + def add_run(self, run_data: LangSmithRunModel): + data = run_data.model_dump() + if self.project_id: + data["session_id"] = self.project_id + elif self.project_name: + data["session_name"] = self.project_name + + data = filter_none_values(data) + try: + self.langsmith_client.create_run(**data) + logger.debug("LangSmith Run created successfully.") + except Exception as e: + raise ValueError(f"LangSmith Failed to create run: {str(e)}") + + def update_run(self, update_run_data: LangSmithRunUpdateModel): + data = update_run_data.model_dump() + data = filter_none_values(data) + try: + self.langsmith_client.update_run(**data) + logger.debug("LangSmith Run updated successfully.") + except Exception as e: + raise ValueError(f"LangSmith Failed to update run: {str(e)}") + + def api_check(self): + try: + random_project_name = f"test_project_{datetime.now().strftime('%Y%m%d%H%M%S')}" + self.langsmith_client.create_project(project_name=random_project_name) + self.langsmith_client.delete_project(project_name=random_project_name) + return True + except Exception as e: + logger.debug(f"LangSmith API check failed: {str(e)}") + raise ValueError(f"LangSmith API check failed: {str(e)}") diff --git a/api/core/ops/ops_trace_manager.py b/api/core/ops/ops_trace_manager.py new file mode 100644 index 00000000000000..00750ab81f6302 --- /dev/null +++ b/api/core/ops/ops_trace_manager.py @@ -0,0 +1,687 @@ +import json +import os +import queue +import threading +from datetime import timedelta +from enum import Enum +from typing import Any, Optional, Union +from uuid import UUID + +from flask import Flask, current_app + +from core.helper.encrypter import decrypt_token, encrypt_token, obfuscated_token +from core.ops.base_trace_instance import BaseTraceInstance +from core.ops.entities.config_entity import ( + LangfuseConfig, + LangSmithConfig, + TracingProviderEnum, +) +from core.ops.entities.trace_entity import ( + DatasetRetrievalTraceInfo, + GenerateNameTraceInfo, + MessageTraceInfo, + ModerationTraceInfo, + SuggestedQuestionTraceInfo, + ToolTraceInfo, + WorkflowTraceInfo, +) +from core.ops.langfuse_trace.langfuse_trace import LangFuseDataTrace +from core.ops.langsmith_trace.langsmith_trace import LangSmithDataTrace +from core.ops.utils import get_message_data +from extensions.ext_database import db +from models.model import App, AppModelConfig, Conversation, Message, MessageAgentThought, MessageFile, TraceAppConfig +from models.workflow import WorkflowAppLog, WorkflowRun + +provider_config_map = { + TracingProviderEnum.LANGFUSE.value: { + 'config_class': LangfuseConfig, + 'secret_keys': ['public_key', 'secret_key'], + 'other_keys': ['host'], + 'trace_instance': LangFuseDataTrace + }, + TracingProviderEnum.LANGSMITH.value: { + 'config_class': LangSmithConfig, + 'secret_keys': ['api_key'], + 'other_keys': ['project', 'endpoint'], + 'trace_instance': LangSmithDataTrace + } +} + + +class OpsTraceManager: + @classmethod + def encrypt_tracing_config( + cls, tenant_id: str, tracing_provider: str, tracing_config: dict, current_trace_config=None + ): + """ + Encrypt tracing config. + :param tenant_id: tenant id + :param tracing_provider: tracing provider + :param tracing_config: tracing config dictionary to be encrypted + :param current_trace_config: current tracing configuration for keeping existing values + :return: encrypted tracing configuration + """ + # Get the configuration class and the keys that require encryption + config_class, secret_keys, other_keys = provider_config_map[tracing_provider]['config_class'], \ + provider_config_map[tracing_provider]['secret_keys'], provider_config_map[tracing_provider]['other_keys'] + + new_config = {} + # Encrypt necessary keys + for key in secret_keys: + if key in tracing_config: + if '*' in tracing_config[key]: + # If the key contains '*', retain the original value from the current config + new_config[key] = current_trace_config.get(key, tracing_config[key]) + else: + # Otherwise, encrypt the key + new_config[key] = encrypt_token(tenant_id, tracing_config[key]) + + for key in other_keys: + new_config[key] = tracing_config.get(key, "") + + # Create a new instance of the config class with the new configuration + encrypted_config = config_class(**new_config) + return encrypted_config.model_dump() + + @classmethod + def decrypt_tracing_config(cls, tenant_id: str, tracing_provider: str, tracing_config: dict): + """ + Decrypt tracing config + :param tenant_id: tenant id + :param tracing_provider: tracing provider + :param tracing_config: tracing config + :return: + """ + config_class, secret_keys, other_keys = provider_config_map[tracing_provider]['config_class'], \ + provider_config_map[tracing_provider]['secret_keys'], provider_config_map[tracing_provider]['other_keys'] + new_config = {} + for key in secret_keys: + if key in tracing_config: + new_config[key] = decrypt_token(tenant_id, tracing_config[key]) + + for key in other_keys: + new_config[key] = tracing_config.get(key, "") + + return config_class(**new_config).model_dump() + + @classmethod + def obfuscated_decrypt_token(cls, tracing_provider: str, decrypt_tracing_config:dict): + """ + Decrypt tracing config + :param tracing_provider: tracing provider + :param decrypt_tracing_config: tracing config + :return: + """ + config_class, secret_keys, other_keys = provider_config_map[tracing_provider]['config_class'], \ + provider_config_map[tracing_provider]['secret_keys'], provider_config_map[tracing_provider]['other_keys'] + new_config = {} + for key in secret_keys: + if key in decrypt_tracing_config: + new_config[key] = obfuscated_token(decrypt_tracing_config[key]) + + for key in other_keys: + new_config[key] = decrypt_tracing_config.get(key, "") + + return config_class(**new_config).model_dump() + + @classmethod + def get_decrypted_tracing_config(cls, app_id: str, tracing_provider: str): + """ + Get decrypted tracing config + :param app_id: app id + :param tracing_provider: tracing provider + :return: + """ + trace_config_data: TraceAppConfig = db.session.query(TraceAppConfig).filter( + TraceAppConfig.app_id == app_id, TraceAppConfig.tracing_provider == tracing_provider + ).first() + + if not trace_config_data: + return None + + # decrypt_token + tenant_id = db.session.query(App).filter(App.id == app_id).first().tenant_id + decrypt_tracing_config = cls.decrypt_tracing_config( + tenant_id, tracing_provider, trace_config_data.tracing_config + ) + + return decrypt_tracing_config + + @classmethod + def get_ops_trace_instance( + cls, + app_id: Optional[Union[UUID, str]] = None, + message_id: Optional[str] = None, + conversation_id: Optional[str] = None + ): + """ + Get ops trace through model config + :param app_id: app_id + :param message_id: message_id + :param conversation_id: conversation_id + :return: + """ + if conversation_id is not None: + conversation_data: Conversation = db.session.query(Conversation).filter( + Conversation.id == conversation_id + ).first() + if conversation_data: + app_id = conversation_data.app_id + + if message_id is not None: + record: Message = db.session.query(Message).filter(Message.id == message_id).first() + app_id = record.app_id + + if isinstance(app_id, UUID): + app_id = str(app_id) + + if app_id is None: + return None + + app: App = db.session.query(App).filter( + App.id == app_id + ).first() + app_ops_trace_config = json.loads(app.tracing) if app.tracing else None + + if app_ops_trace_config is not None: + tracing_provider = app_ops_trace_config.get('tracing_provider') + else: + return None + + # decrypt_token + decrypt_trace_config = cls.get_decrypted_tracing_config(app_id, tracing_provider) + if app_ops_trace_config.get('enabled'): + trace_instance, config_class = provider_config_map[tracing_provider]['trace_instance'], \ + provider_config_map[tracing_provider]['config_class'] + tracing_instance = trace_instance(config_class(**decrypt_trace_config)) + return tracing_instance + + return None + + @classmethod + def get_app_config_through_message_id(cls, message_id: str): + app_model_config = None + message_data = db.session.query(Message).filter(Message.id == message_id).first() + conversation_id = message_data.conversation_id + conversation_data = db.session.query(Conversation).filter(Conversation.id == conversation_id).first() + + if conversation_data.app_model_config_id: + app_model_config = db.session.query(AppModelConfig).filter( + AppModelConfig.id == conversation_data.app_model_config_id + ).first() + elif conversation_data.app_model_config_id is None and conversation_data.override_model_configs: + app_model_config = conversation_data.override_model_configs + + return app_model_config + + @classmethod + def update_app_tracing_config(cls, app_id: str, enabled: bool, tracing_provider: str): + """ + Update app tracing config + :param app_id: app id + :param enabled: enabled + :param tracing_provider: tracing provider + :return: + """ + # auth check + if tracing_provider not in provider_config_map.keys() and tracing_provider is not None: + raise ValueError(f"Invalid tracing provider: {tracing_provider}") + + app_config: App = db.session.query(App).filter(App.id == app_id).first() + app_config.tracing = json.dumps( + { + "enabled": enabled, + "tracing_provider": tracing_provider, + } + ) + db.session.commit() + + @classmethod + def get_app_tracing_config(cls, app_id: str): + """ + Get app tracing config + :param app_id: app id + :return: + """ + app: App = db.session.query(App).filter(App.id == app_id).first() + if not app.tracing: + return { + "enabled": False, + "tracing_provider": None + } + app_trace_config = json.loads(app.tracing) + return app_trace_config + + @staticmethod + def check_trace_config_is_effective(tracing_config: dict, tracing_provider: str): + """ + Check trace config is effective + :param tracing_config: tracing config + :param tracing_provider: tracing provider + :return: + """ + config_type, trace_instance = provider_config_map[tracing_provider]['config_class'], \ + provider_config_map[tracing_provider]['trace_instance'] + tracing_config = config_type(**tracing_config) + return trace_instance(tracing_config).api_check() + + +class TraceTaskName(str, Enum): + CONVERSATION_TRACE = 'conversation_trace' + WORKFLOW_TRACE = 'workflow_trace' + MESSAGE_TRACE = 'message_trace' + MODERATION_TRACE = 'moderation_trace' + SUGGESTED_QUESTION_TRACE = 'suggested_question_trace' + DATASET_RETRIEVAL_TRACE = 'dataset_retrieval_trace' + TOOL_TRACE = 'tool_trace' + GENERATE_NAME_TRACE = 'generate_name_trace' + + +class TraceTask: + def __init__( + self, + trace_type: Any, + message_id: Optional[str] = None, + workflow_run: Optional[WorkflowRun] = None, + conversation_id: Optional[str] = None, + timer: Optional[Any] = None, + **kwargs + ): + self.trace_type = trace_type + self.message_id = message_id + self.workflow_run = workflow_run + self.conversation_id = conversation_id + self.timer = timer + self.kwargs = kwargs + self.file_base_url = os.getenv("FILES_URL", "http://127.0.0.1:5001") + + def execute(self, trace_instance: BaseTraceInstance): + method_name, trace_info = self.preprocess() + if trace_instance: + method = trace_instance.trace + method(trace_info) + + def preprocess(self): + if self.trace_type == TraceTaskName.CONVERSATION_TRACE: + return TraceTaskName.CONVERSATION_TRACE, self.conversation_trace(**self.kwargs) + if self.trace_type == TraceTaskName.WORKFLOW_TRACE: + return TraceTaskName.WORKFLOW_TRACE, self.workflow_trace(self.workflow_run, self.conversation_id) + elif self.trace_type == TraceTaskName.MESSAGE_TRACE: + return TraceTaskName.MESSAGE_TRACE, self.message_trace(self.message_id) + elif self.trace_type == TraceTaskName.MODERATION_TRACE: + return TraceTaskName.MODERATION_TRACE, self.moderation_trace(self.message_id, self.timer, **self.kwargs) + elif self.trace_type == TraceTaskName.SUGGESTED_QUESTION_TRACE: + return TraceTaskName.SUGGESTED_QUESTION_TRACE, self.suggested_question_trace( + self.message_id, self.timer, **self.kwargs + ) + elif self.trace_type == TraceTaskName.DATASET_RETRIEVAL_TRACE: + return TraceTaskName.DATASET_RETRIEVAL_TRACE, self.dataset_retrieval_trace( + self.message_id, self.timer, **self.kwargs + ) + elif self.trace_type == TraceTaskName.TOOL_TRACE: + return TraceTaskName.TOOL_TRACE, self.tool_trace(self.message_id, self.timer, **self.kwargs) + elif self.trace_type == TraceTaskName.GENERATE_NAME_TRACE: + return TraceTaskName.GENERATE_NAME_TRACE, self.generate_name_trace( + self.conversation_id, self.timer, **self.kwargs + ) + else: + return '', {} + + # process methods for different trace types + def conversation_trace(self, **kwargs): + return kwargs + + def workflow_trace(self, workflow_run: WorkflowRun, conversation_id): + workflow_id = workflow_run.workflow_id + tenant_id = workflow_run.tenant_id + workflow_run_id = workflow_run.id + workflow_run_elapsed_time = workflow_run.elapsed_time + workflow_run_status = workflow_run.status + workflow_run_inputs = ( + json.loads(workflow_run.inputs) if workflow_run.inputs else {} + ) + workflow_run_outputs = ( + json.loads(workflow_run.outputs) if workflow_run.outputs else {} + ) + workflow_run_version = workflow_run.version + error = workflow_run.error if workflow_run.error else "" + + total_tokens = workflow_run.total_tokens + + file_list = workflow_run_inputs.get("sys.file") if workflow_run_inputs.get("sys.file") else [] + query = workflow_run_inputs.get("query") or workflow_run_inputs.get("sys.query") or "" + + # get workflow_app_log_id + workflow_app_log_data = db.session.query(WorkflowAppLog).filter_by(workflow_run_id=workflow_run.id).first() + workflow_app_log_id = str(workflow_app_log_data.id) if workflow_app_log_data else None + # get message_id + message_data = db.session.query(Message.id).filter_by(workflow_run_id=workflow_run_id).first() + message_id = str(message_data.id) if message_data else None + + metadata = { + "workflow_id": workflow_id, + "conversation_id": conversation_id, + "workflow_run_id": workflow_run_id, + "tenant_id": tenant_id, + "elapsed_time": workflow_run_elapsed_time, + "status": workflow_run_status, + "version": workflow_run_version, + "total_tokens": total_tokens, + "file_list": file_list, + "triggered_form": workflow_run.triggered_from, + } + + workflow_trace_info = WorkflowTraceInfo( + workflow_data=workflow_run, + conversation_id=conversation_id, + workflow_id=workflow_id, + tenant_id=tenant_id, + workflow_run_id=workflow_run_id, + workflow_run_elapsed_time=workflow_run_elapsed_time, + workflow_run_status=workflow_run_status, + workflow_run_inputs=workflow_run_inputs, + workflow_run_outputs=workflow_run_outputs, + workflow_run_version=workflow_run_version, + error=error, + total_tokens=total_tokens, + file_list=file_list, + query=query, + metadata=metadata, + workflow_app_log_id=workflow_app_log_id, + message_id=message_id, + start_time=workflow_run.created_at, + end_time=workflow_run.finished_at, + ) + + return workflow_trace_info + + def message_trace(self, message_id): + message_data = get_message_data(message_id) + if not message_data: + return {} + conversation_mode = db.session.query(Conversation.mode).filter_by(id=message_data.conversation_id).first() + conversation_mode = conversation_mode[0] + created_at = message_data.created_at + inputs = message_data.message + + # get message file data + message_file_data = db.session.query(MessageFile).filter_by(message_id=message_id).first() + file_list = [] + if message_file_data and message_file_data.url is not None: + file_url = f"{self.file_base_url}/{message_file_data.url}" if message_file_data else "" + file_list.append(file_url) + + metadata = { + "conversation_id": message_data.conversation_id, + "ls_provider": message_data.model_provider, + "ls_model_name": message_data.model_id, + "status": message_data.status, + "from_end_user_id": message_data.from_account_id, + "from_account_id": message_data.from_account_id, + "agent_based": message_data.agent_based, + "workflow_run_id": message_data.workflow_run_id, + "from_source": message_data.from_source, + "message_id": message_id, + } + + message_tokens = message_data.message_tokens + + message_trace_info = MessageTraceInfo( + message_data=message_data, + conversation_model=conversation_mode, + message_tokens=message_tokens, + answer_tokens=message_data.answer_tokens, + total_tokens=message_tokens + message_data.answer_tokens, + error=message_data.error if message_data.error else "", + inputs=inputs, + outputs=message_data.answer, + file_list=file_list, + start_time=created_at, + end_time=created_at + timedelta(seconds=message_data.provider_response_latency), + metadata=metadata, + message_file_data=message_file_data, + conversation_mode=conversation_mode, + ) + + return message_trace_info + + def moderation_trace(self, message_id, timer, **kwargs): + moderation_result = kwargs.get("moderation_result") + inputs = kwargs.get("inputs") + message_data = get_message_data(message_id) + if not message_data: + return {} + metadata = { + "message_id": message_id, + "action": moderation_result.action, + "preset_response": moderation_result.preset_response, + "query": moderation_result.query, + } + + # get workflow_app_log_id + workflow_app_log_id = None + if message_data.workflow_run_id: + workflow_app_log_data = db.session.query(WorkflowAppLog).filter_by( + workflow_run_id=message_data.workflow_run_id + ).first() + workflow_app_log_id = str(workflow_app_log_data.id) if workflow_app_log_data else None + + moderation_trace_info = ModerationTraceInfo( + message_id=workflow_app_log_id if workflow_app_log_id else message_id, + inputs=inputs, + message_data=message_data, + flagged=moderation_result.flagged, + action=moderation_result.action, + preset_response=moderation_result.preset_response, + query=moderation_result.query, + start_time=timer.get("start"), + end_time=timer.get("end"), + metadata=metadata, + ) + + return moderation_trace_info + + def suggested_question_trace(self, message_id, timer, **kwargs): + suggested_question = kwargs.get("suggested_question") + message_data = get_message_data(message_id) + if not message_data: + return {} + metadata = { + "message_id": message_id, + "ls_provider": message_data.model_provider, + "ls_model_name": message_data.model_id, + "status": message_data.status, + "from_end_user_id": message_data.from_account_id, + "from_account_id": message_data.from_account_id, + "agent_based": message_data.agent_based, + "workflow_run_id": message_data.workflow_run_id, + "from_source": message_data.from_source, + } + + # get workflow_app_log_id + workflow_app_log_id = None + if message_data.workflow_run_id: + workflow_app_log_data = db.session.query(WorkflowAppLog).filter_by( + workflow_run_id=message_data.workflow_run_id + ).first() + workflow_app_log_id = str(workflow_app_log_data.id) if workflow_app_log_data else None + + suggested_question_trace_info = SuggestedQuestionTraceInfo( + message_id=workflow_app_log_id if workflow_app_log_id else message_id, + message_data=message_data, + inputs=message_data.message, + outputs=message_data.answer, + start_time=timer.get("start"), + end_time=timer.get("end"), + metadata=metadata, + total_tokens=message_data.message_tokens + message_data.answer_tokens, + status=message_data.status, + error=message_data.error, + from_account_id=message_data.from_account_id, + agent_based=message_data.agent_based, + from_source=message_data.from_source, + model_provider=message_data.model_provider, + model_id=message_data.model_id, + suggested_question=suggested_question, + level=message_data.status, + status_message=message_data.error, + ) + + return suggested_question_trace_info + + def dataset_retrieval_trace(self, message_id, timer, **kwargs): + documents = kwargs.get("documents") + message_data = get_message_data(message_id) + if not message_data: + return {} + + metadata = { + "message_id": message_id, + "ls_provider": message_data.model_provider, + "ls_model_name": message_data.model_id, + "status": message_data.status, + "from_end_user_id": message_data.from_account_id, + "from_account_id": message_data.from_account_id, + "agent_based": message_data.agent_based, + "workflow_run_id": message_data.workflow_run_id, + "from_source": message_data.from_source, + } + + dataset_retrieval_trace_info = DatasetRetrievalTraceInfo( + message_id=message_id, + inputs=message_data.query if message_data.query else message_data.inputs, + documents=documents, + start_time=timer.get("start"), + end_time=timer.get("end"), + metadata=metadata, + message_data=message_data, + ) + + return dataset_retrieval_trace_info + + def tool_trace(self, message_id, timer, **kwargs): + tool_name = kwargs.get('tool_name') + tool_inputs = kwargs.get('tool_inputs') + tool_outputs = kwargs.get('tool_outputs') + message_data = get_message_data(message_id) + if not message_data: + return {} + tool_config = {} + time_cost = 0 + error = None + tool_parameters = {} + created_time = message_data.created_at + end_time = message_data.updated_at + agent_thoughts: list[MessageAgentThought] = message_data.agent_thoughts + for agent_thought in agent_thoughts: + if tool_name in agent_thought.tools: + created_time = agent_thought.created_at + tool_meta_data = agent_thought.tool_meta.get(tool_name, {}) + tool_config = tool_meta_data.get('tool_config', {}) + time_cost = tool_meta_data.get('time_cost', 0) + end_time = created_time + timedelta(seconds=time_cost) + error = tool_meta_data.get('error', "") + tool_parameters = tool_meta_data.get('tool_parameters', {}) + metadata = { + "message_id": message_id, + "tool_name": tool_name, + "tool_inputs": tool_inputs, + "tool_outputs": tool_outputs, + "tool_config": tool_config, + "time_cost": time_cost, + "error": error, + "tool_parameters": tool_parameters, + } + + file_url = "" + message_file_data = db.session.query(MessageFile).filter_by(message_id=message_id).first() + if message_file_data: + message_file_id = message_file_data.id if message_file_data else None + type = message_file_data.type + created_by_role = message_file_data.created_by_role + created_user_id = message_file_data.created_by + file_url = f"{self.file_base_url}/{message_file_data.url}" + + metadata.update( + { + "message_file_id": message_file_id, + "created_by_role": created_by_role, + "created_user_id": created_user_id, + "type": type, + } + ) + + tool_trace_info = ToolTraceInfo( + message_id=message_id, + message_data=message_data, + tool_name=tool_name, + start_time=timer.get("start") if timer else created_time, + end_time=timer.get("end") if timer else end_time, + tool_inputs=tool_inputs, + tool_outputs=tool_outputs, + metadata=metadata, + message_file_data=message_file_data, + error=error, + inputs=message_data.message, + outputs=message_data.answer, + tool_config=tool_config, + time_cost=time_cost, + tool_parameters=tool_parameters, + file_url=file_url, + ) + + return tool_trace_info + + def generate_name_trace(self, conversation_id, timer, **kwargs): + generate_conversation_name = kwargs.get("generate_conversation_name") + inputs = kwargs.get("inputs") + tenant_id = kwargs.get("tenant_id") + start_time = timer.get("start") + end_time = timer.get("end") + + metadata = { + "conversation_id": conversation_id, + "tenant_id": tenant_id, + } + + generate_name_trace_info = GenerateNameTraceInfo( + conversation_id=conversation_id, + inputs=inputs, + outputs=generate_conversation_name, + start_time=start_time, + end_time=end_time, + metadata=metadata, + tenant_id=tenant_id, + ) + + return generate_name_trace_info + + +class TraceQueueManager: + def __init__(self, app_id=None, conversation_id=None, message_id=None): + tracing_instance = OpsTraceManager.get_ops_trace_instance(app_id, conversation_id, message_id) + self.queue = queue.Queue() + self.is_running = True + self.thread = threading.Thread( + target=self.process_queue, kwargs={ + 'flask_app': current_app._get_current_object(), + 'trace_instance': tracing_instance + } + ) + self.thread.start() + + def stop(self): + self.is_running = False + + def process_queue(self, flask_app: Flask, trace_instance: BaseTraceInstance): + with flask_app.app_context(): + while self.is_running: + try: + task = self.queue.get(timeout=60) + task.execute(trace_instance) + self.queue.task_done() + except queue.Empty: + self.stop() + + def add_trace_task(self, trace_task: TraceTask): + self.queue.put(trace_task) diff --git a/api/core/ops/utils.py b/api/core/ops/utils.py new file mode 100644 index 00000000000000..2b12db0f482c6d --- /dev/null +++ b/api/core/ops/utils.py @@ -0,0 +1,43 @@ +from contextlib import contextmanager +from datetime import datetime + +from extensions.ext_database import db +from models.model import Message + + +def filter_none_values(data: dict): + for key, value in data.items(): + if value is None: + continue + if isinstance(value, datetime): + data[key] = value.isoformat() + return {key: value for key, value in data.items() if value is not None} + + +def get_message_data(message_id): + return db.session.query(Message).filter(Message.id == message_id).first() + + +@contextmanager +def measure_time(): + timing_info = {'start': datetime.now(), 'end': None} + try: + yield timing_info + finally: + timing_info['end'] = datetime.now() + print(f"Execution time: {timing_info['end'] - timing_info['start']}") + + +def replace_text_with_content(data): + if isinstance(data, dict): + new_data = {} + for key, value in data.items(): + if key == 'text': + new_data['content'] = value + else: + new_data[key] = replace_text_with_content(value) + return new_data + elif isinstance(data, list): + return [replace_text_with_content(item) for item in data] + else: + return data diff --git a/api/core/rag/retrieval/dataset_retrieval.py b/api/core/rag/retrieval/dataset_retrieval.py index 3f50427141c93e..8544d7c3c86c43 100644 --- a/api/core/rag/retrieval/dataset_retrieval.py +++ b/api/core/rag/retrieval/dataset_retrieval.py @@ -12,6 +12,8 @@ from core.model_runtime.entities.message_entities import PromptMessageTool from core.model_runtime.entities.model_entities import ModelFeature, ModelType from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel +from core.ops.ops_trace_manager import TraceTask, TraceTaskName +from core.ops.utils import measure_time from core.rag.datasource.retrieval_service import RetrievalService from core.rag.models.document import Document from core.rag.rerank.rerank import RerankRunner @@ -38,14 +40,20 @@ class DatasetRetrieval: - def retrieve(self, app_id: str, user_id: str, tenant_id: str, - model_config: ModelConfigWithCredentialsEntity, - config: DatasetEntity, - query: str, - invoke_from: InvokeFrom, - show_retrieve_source: bool, - hit_callback: DatasetIndexToolCallbackHandler, - memory: Optional[TokenBufferMemory] = None) -> Optional[str]: + def __init__(self, application_generate_entity=None): + self.application_generate_entity = application_generate_entity + + def retrieve( + self, app_id: str, user_id: str, tenant_id: str, + model_config: ModelConfigWithCredentialsEntity, + config: DatasetEntity, + query: str, + invoke_from: InvokeFrom, + show_retrieve_source: bool, + hit_callback: DatasetIndexToolCallbackHandler, + message_id: str, + memory: Optional[TokenBufferMemory] = None, + ) -> Optional[str]: """ Retrieve dataset. :param app_id: app_id @@ -57,6 +65,7 @@ def retrieve(self, app_id: str, user_id: str, tenant_id: str, :param invoke_from: invoke from :param show_retrieve_source: show retrieve source :param hit_callback: hit callback + :param message_id: message id :param memory: memory :return: """ @@ -113,15 +122,20 @@ def retrieve(self, app_id: str, user_id: str, tenant_id: str, all_documents = [] user_from = 'account' if invoke_from in [InvokeFrom.EXPLORE, InvokeFrom.DEBUGGER] else 'end_user' if retrieve_config.retrieve_strategy == DatasetRetrieveConfigEntity.RetrieveStrategy.SINGLE: - all_documents = self.single_retrieve(app_id, tenant_id, user_id, user_from, available_datasets, query, - model_instance, - model_config, planning_strategy) + all_documents = self.single_retrieve( + app_id, tenant_id, user_id, user_from, available_datasets, query, + model_instance, + model_config, planning_strategy, message_id + ) elif retrieve_config.retrieve_strategy == DatasetRetrieveConfigEntity.RetrieveStrategy.MULTIPLE: - all_documents = self.multiple_retrieve(app_id, tenant_id, user_id, user_from, - available_datasets, query, retrieve_config.top_k, - retrieve_config.score_threshold, - retrieve_config.reranking_model.get('reranking_provider_name'), - retrieve_config.reranking_model.get('reranking_model_name')) + all_documents = self.multiple_retrieve( + app_id, tenant_id, user_id, user_from, + available_datasets, query, retrieve_config.top_k, + retrieve_config.score_threshold, + retrieve_config.reranking_model.get('reranking_provider_name'), + retrieve_config.reranking_model.get('reranking_model_name'), + message_id, + ) document_score_list = {} for item in all_documents: @@ -189,16 +203,18 @@ def retrieve(self, app_id: str, user_id: str, tenant_id: str, return str("\n".join(document_context_list)) return '' - def single_retrieve(self, app_id: str, - tenant_id: str, - user_id: str, - user_from: str, - available_datasets: list, - query: str, - model_instance: ModelInstance, - model_config: ModelConfigWithCredentialsEntity, - planning_strategy: PlanningStrategy, - ): + def single_retrieve( + self, app_id: str, + tenant_id: str, + user_id: str, + user_from: str, + available_datasets: list, + query: str, + model_instance: ModelInstance, + model_config: ModelConfigWithCredentialsEntity, + planning_strategy: PlanningStrategy, + message_id: Optional[str] = None, + ): tools = [] for dataset in available_datasets: description = dataset.description @@ -251,27 +267,35 @@ def single_retrieve(self, app_id: str, if score_threshold_enabled: score_threshold = retrieval_model_config.get("score_threshold") - results = RetrievalService.retrieve(retrival_method=retrival_method, dataset_id=dataset.id, - query=query, - top_k=top_k, score_threshold=score_threshold, - reranking_model=reranking_model) + with measure_time() as timer: + results = RetrievalService.retrieve( + retrival_method=retrival_method, dataset_id=dataset.id, + query=query, + top_k=top_k, score_threshold=score_threshold, + reranking_model=reranking_model + ) self._on_query(query, [dataset_id], app_id, user_from, user_id) + if results: - self._on_retrival_end(results) + self._on_retrival_end(results, message_id, timer) + return results return [] - def multiple_retrieve(self, - app_id: str, - tenant_id: str, - user_id: str, - user_from: str, - available_datasets: list, - query: str, - top_k: int, - score_threshold: float, - reranking_provider_name: str, - reranking_model_name: str): + def multiple_retrieve( + self, + app_id: str, + tenant_id: str, + user_id: str, + user_from: str, + available_datasets: list, + query: str, + top_k: int, + score_threshold: float, + reranking_provider_name: str, + reranking_model_name: str, + message_id: Optional[str] = None, + ): threads = [] all_documents = [] dataset_ids = [dataset.id for dataset in available_datasets] @@ -297,15 +321,23 @@ def multiple_retrieve(self, ) rerank_runner = RerankRunner(rerank_model_instance) - all_documents = rerank_runner.run(query, all_documents, - score_threshold, - top_k) + + with measure_time() as timer: + all_documents = rerank_runner.run( + query, all_documents, + score_threshold, + top_k + ) self._on_query(query, dataset_ids, app_id, user_from, user_id) + if all_documents: - self._on_retrival_end(all_documents) + self._on_retrival_end(all_documents, message_id, timer) + return all_documents - def _on_retrival_end(self, documents: list[Document]) -> None: + def _on_retrival_end( + self, documents: list[Document], message_id: Optional[str] = None, timer: Optional[dict] = None + ) -> None: """Handle retrival end.""" for document in documents: query = db.session.query(DocumentSegment).filter( @@ -324,6 +356,18 @@ def _on_retrival_end(self, documents: list[Document]) -> None: db.session.commit() + # get tracing instance + trace_manager = self.application_generate_entity.trace_manager if self.application_generate_entity else None + if trace_manager: + trace_manager.add_trace_task( + TraceTask( + TraceTaskName.DATASET_RETRIEVAL_TRACE, + message_id=message_id, + documents=documents, + timer=timer + ) + ) + def _on_query(self, query: str, dataset_ids: list[str], app_id: str, user_from: str, user_id: str) -> None: """ Handle query. diff --git a/api/core/tools/tool/workflow_tool.py b/api/core/tools/tool/workflow_tool.py index 122b663f943be3..071081303c3b2a 100644 --- a/api/core/tools/tool/workflow_tool.py +++ b/api/core/tools/tool/workflow_tool.py @@ -31,9 +31,10 @@ def tool_provider_type(self) -> ToolProviderType: :return: the tool provider type """ return ToolProviderType.WORKFLOW - - def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) \ - -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: + + def _invoke( + self, user_id: str, tool_parameters: dict[str, Any] + ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: """ invoke the tool """ diff --git a/api/core/tools/tool_engine.py b/api/core/tools/tool_engine.py index 42e240b05164cf..7615368934bfe5 100644 --- a/api/core/tools/tool_engine.py +++ b/api/core/tools/tool_engine.py @@ -2,7 +2,7 @@ from copy import deepcopy from datetime import datetime, timezone from mimetypes import guess_type -from typing import Any, Union +from typing import Any, Optional, Union from yarl import URL @@ -10,6 +10,7 @@ from core.callback_handler.agent_tool_callback_handler import DifyAgentCallbackHandler from core.callback_handler.workflow_tool_callback_handler import DifyWorkflowCallbackHandler from core.file.file_obj import FileTransferMethod +from core.ops.ops_trace_manager import TraceQueueManager from core.tools.entities.tool_entities import ToolInvokeMessage, ToolInvokeMessageBinary, ToolInvokeMeta, ToolParameter from core.tools.errors import ( ToolEngineInvokeError, @@ -32,10 +33,12 @@ class ToolEngine: Tool runtime engine take care of the tool executions. """ @staticmethod - def agent_invoke(tool: Tool, tool_parameters: Union[str, dict], - user_id: str, tenant_id: str, message: Message, invoke_from: InvokeFrom, - agent_tool_callback: DifyAgentCallbackHandler) \ - -> tuple[str, list[tuple[MessageFile, bool]], ToolInvokeMeta]: + def agent_invoke( + tool: Tool, tool_parameters: Union[str, dict], + user_id: str, tenant_id: str, message: Message, invoke_from: InvokeFrom, + agent_tool_callback: DifyAgentCallbackHandler, + trace_manager: Optional[TraceQueueManager] = None + ) -> tuple[str, list[tuple[MessageFile, bool]], ToolInvokeMeta]: """ Agent invokes the tool with the given arguments. """ @@ -83,9 +86,11 @@ def agent_invoke(tool: Tool, tool_parameters: Union[str, dict], # hit the callback handler agent_tool_callback.on_tool_end( - tool_name=tool.identity.name, - tool_inputs=tool_parameters, - tool_outputs=plain_text + tool_name=tool.identity.name, + tool_inputs=tool_parameters, + tool_outputs=plain_text, + message_id=message.id, + trace_manager=trace_manager ) # transform tool invoke message to get LLM friendly message @@ -121,8 +126,8 @@ def agent_invoke(tool: Tool, tool_parameters: Union[str, dict], def workflow_invoke(tool: Tool, tool_parameters: dict, user_id: str, workflow_id: str, workflow_tool_callback: DifyWorkflowCallbackHandler, - workflow_call_depth: int) \ - -> list[ToolInvokeMessage]: + workflow_call_depth: int, + ) -> list[ToolInvokeMessage]: """ Workflow invokes the tool with the given arguments. """ @@ -140,9 +145,9 @@ def workflow_invoke(tool: Tool, tool_parameters: dict, # hit the callback handler workflow_tool_callback.on_tool_end( - tool_name=tool.identity.name, - tool_inputs=tool_parameters, - tool_outputs=response + tool_name=tool.identity.name, + tool_inputs=tool_parameters, + tool_outputs=response, ) return response diff --git a/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py b/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py index 8fceb3404ab039..bb0ccb5fc37116 100644 --- a/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py +++ b/api/core/workflow/nodes/parameter_extractor/parameter_extractor_node.py @@ -66,44 +66,43 @@ def get_default_config(cls, filters: Optional[dict] = None) -> dict: } } - def _run(self, variable_pool: VariablePool) -> NodeRunResult: """ Run the node. """ - node_data = cast(ParameterExtractorNodeData, self.node_data) query = variable_pool.get_variable_value(node_data.query) if not query: - raise ValueError("Query not found") - - inputs={ + raise ValueError("Input variable content not found or is empty") + + inputs = { 'query': query, 'parameters': jsonable_encoder(node_data.parameters), 'instruction': jsonable_encoder(node_data.instruction), } - + model_instance, model_config = self._fetch_model_config(node_data.model) if not isinstance(model_instance.model_type_instance, LargeLanguageModel): raise ValueError("Model is not a Large Language Model") - + llm_model = model_instance.model_type_instance model_schema = llm_model.get_model_schema(model_config.model, model_config.credentials) if not model_schema: raise ValueError("Model schema not found") - + # fetch memory memory = self._fetch_memory(node_data.memory, variable_pool, model_instance) - + if set(model_schema.features or []) & set([ModelFeature.TOOL_CALL, ModelFeature.MULTI_TOOL_CALL]) \ - and node_data.reasoning_mode == 'function_call': + and node_data.reasoning_mode == 'function_call': # use function call prompt_messages, prompt_message_tools = self._generate_function_call_prompt( node_data, query, variable_pool, model_config, memory ) else: # use prompt engineering - prompt_messages = self._generate_prompt_engineering_prompt(node_data, query, variable_pool, model_config, memory) + prompt_messages = self._generate_prompt_engineering_prompt(node_data, query, variable_pool, model_config, + memory) prompt_message_tools = [] process_data = { @@ -202,7 +201,7 @@ def _invoke_llm(self, node_data_model: ModelConfig, # handle invoke result if not isinstance(invoke_result, LLMResult): raise ValueError(f"Invalid invoke result: {invoke_result}") - + text = invoke_result.message.content usage = invoke_result.usage tool_call = invoke_result.message.tool_calls[0] if invoke_result.message.tool_calls else None @@ -212,21 +211,23 @@ def _invoke_llm(self, node_data_model: ModelConfig, return text, usage, tool_call - def _generate_function_call_prompt(self, - node_data: ParameterExtractorNodeData, - query: str, - variable_pool: VariablePool, - model_config: ModelConfigWithCredentialsEntity, - memory: Optional[TokenBufferMemory], - ) -> tuple[list[PromptMessage], list[PromptMessageTool]]: + def _generate_function_call_prompt(self, + node_data: ParameterExtractorNodeData, + query: str, + variable_pool: VariablePool, + model_config: ModelConfigWithCredentialsEntity, + memory: Optional[TokenBufferMemory], + ) -> tuple[list[PromptMessage], list[PromptMessageTool]]: """ Generate function call prompt. """ - query = FUNCTION_CALLING_EXTRACTOR_USER_TEMPLATE.format(content=query, structure=json.dumps(node_data.get_parameter_json_schema())) + query = FUNCTION_CALLING_EXTRACTOR_USER_TEMPLATE.format(content=query, structure=json.dumps( + node_data.get_parameter_json_schema())) prompt_transform = AdvancedPromptTransform(with_variable_tmpl=True) rest_token = self._calculate_rest_token(node_data, query, variable_pool, model_config, '') - prompt_template = self._get_function_calling_prompt_template(node_data, query, variable_pool, memory, rest_token) + prompt_template = self._get_function_calling_prompt_template(node_data, query, variable_pool, memory, + rest_token) prompt_messages = prompt_transform.get_prompt( prompt_template=prompt_template, inputs={}, @@ -259,8 +260,8 @@ def _generate_function_call_prompt(self, function=AssistantPromptMessage.ToolCall.ToolCallFunction( name=example['assistant']['function_call']['name'], arguments=json.dumps(example['assistant']['function_call']['parameters'] - ) - )) + ) + )) ] ), ToolPromptMessage( @@ -273,8 +274,8 @@ def _generate_function_call_prompt(self, ]) prompt_messages = prompt_messages[:last_user_message_idx] + \ - example_messages + prompt_messages[last_user_message_idx:] - + example_messages + prompt_messages[last_user_message_idx:] + # generate tool tool = PromptMessageTool( name=FUNCTION_CALLING_EXTRACTOR_NAME, @@ -284,13 +285,13 @@ def _generate_function_call_prompt(self, return prompt_messages, [tool] - def _generate_prompt_engineering_prompt(self, - data: ParameterExtractorNodeData, - query: str, - variable_pool: VariablePool, - model_config: ModelConfigWithCredentialsEntity, - memory: Optional[TokenBufferMemory], - ) -> list[PromptMessage]: + def _generate_prompt_engineering_prompt(self, + data: ParameterExtractorNodeData, + query: str, + variable_pool: VariablePool, + model_config: ModelConfigWithCredentialsEntity, + memory: Optional[TokenBufferMemory], + ) -> list[PromptMessage]: """ Generate prompt engineering prompt. """ @@ -308,18 +309,19 @@ def _generate_prompt_engineering_prompt(self, raise ValueError(f"Invalid model mode: {model_mode}") def _generate_prompt_engineering_completion_prompt(self, - node_data: ParameterExtractorNodeData, - query: str, - variable_pool: VariablePool, - model_config: ModelConfigWithCredentialsEntity, - memory: Optional[TokenBufferMemory], - ) -> list[PromptMessage]: + node_data: ParameterExtractorNodeData, + query: str, + variable_pool: VariablePool, + model_config: ModelConfigWithCredentialsEntity, + memory: Optional[TokenBufferMemory], + ) -> list[PromptMessage]: """ Generate completion prompt. """ prompt_transform = AdvancedPromptTransform(with_variable_tmpl=True) rest_token = self._calculate_rest_token(node_data, query, variable_pool, model_config, '') - prompt_template = self._get_prompt_engineering_prompt_template(node_data, query, variable_pool, memory, rest_token) + prompt_template = self._get_prompt_engineering_prompt_template(node_data, query, variable_pool, memory, + rest_token) prompt_messages = prompt_transform.get_prompt( prompt_template=prompt_template, inputs={ @@ -336,23 +338,23 @@ def _generate_prompt_engineering_completion_prompt(self, return prompt_messages def _generate_prompt_engineering_chat_prompt(self, - node_data: ParameterExtractorNodeData, - query: str, - variable_pool: VariablePool, - model_config: ModelConfigWithCredentialsEntity, - memory: Optional[TokenBufferMemory], - ) -> list[PromptMessage]: + node_data: ParameterExtractorNodeData, + query: str, + variable_pool: VariablePool, + model_config: ModelConfigWithCredentialsEntity, + memory: Optional[TokenBufferMemory], + ) -> list[PromptMessage]: """ Generate chat prompt. """ prompt_transform = AdvancedPromptTransform(with_variable_tmpl=True) rest_token = self._calculate_rest_token(node_data, query, variable_pool, model_config, '') prompt_template = self._get_prompt_engineering_prompt_template( - node_data, + node_data, CHAT_GENERATE_JSON_USER_MESSAGE_TEMPLATE.format( structure=json.dumps(node_data.get_parameter_json_schema()), text=query - ), + ), variable_pool, memory, rest_token ) @@ -387,7 +389,7 @@ def _generate_prompt_engineering_chat_prompt(self, ]) prompt_messages = prompt_messages[:last_user_message_idx] + \ - example_messages + prompt_messages[last_user_message_idx:] + example_messages + prompt_messages[last_user_message_idx:] return prompt_messages @@ -397,23 +399,23 @@ def _validate_result(self, data: ParameterExtractorNodeData, result: dict) -> di """ if len(data.parameters) != len(result): raise ValueError("Invalid number of parameters") - + for parameter in data.parameters: if parameter.required and parameter.name not in result: raise ValueError(f"Parameter {parameter.name} is required") - + if parameter.type == 'select' and parameter.options and result.get(parameter.name) not in parameter.options: raise ValueError(f"Invalid `select` value for parameter {parameter.name}") - + if parameter.type == 'number' and not isinstance(result.get(parameter.name), int | float): raise ValueError(f"Invalid `number` value for parameter {parameter.name}") - + if parameter.type == 'bool' and not isinstance(result.get(parameter.name), bool): raise ValueError(f"Invalid `bool` value for parameter {parameter.name}") - + if parameter.type == 'string' and not isinstance(result.get(parameter.name), str): raise ValueError(f"Invalid `string` value for parameter {parameter.name}") - + if parameter.type.startswith('array'): if not isinstance(result.get(parameter.name), list): raise ValueError(f"Invalid `array` value for parameter {parameter.name}") @@ -499,6 +501,7 @@ def _extract_complete_json_response(self, result: str) -> Optional[dict]: """ Extract complete json response. """ + def extract_json(text): """ From a given JSON started from '{' or '[' extract the complete JSON object. @@ -515,11 +518,11 @@ def extract_json(text): if (c == '}' and stack[-1] == '{') or (c == ']' and stack[-1] == '['): stack.pop() if not stack: - return text[:i+1] + return text[:i + 1] else: return text[:i] return None - + # extract json from the text for idx in range(len(result)): if result[idx] == '{' or result[idx] == '[': @@ -536,9 +539,9 @@ def _extract_json_from_tool_call(self, tool_call: AssistantPromptMessage.ToolCal """ if not tool_call or not tool_call.function.arguments: return None - + return json.loads(tool_call.function.arguments) - + def _generate_default_result(self, data: ParameterExtractorNodeData) -> dict: """ Generate default result. @@ -551,7 +554,7 @@ def _generate_default_result(self, data: ParameterExtractorNodeData) -> dict: result[parameter.name] = False elif parameter.type in ['string', 'select']: result[parameter.name] = '' - + return result def _render_instruction(self, instruction: str, variable_pool: VariablePool) -> str: @@ -562,13 +565,13 @@ def _render_instruction(self, instruction: str, variable_pool: VariablePool) -> inputs = {} for selector in variable_template_parser.extract_variable_selectors(): inputs[selector.variable] = variable_pool.get_variable_value(selector.value_selector) - + return variable_template_parser.format(inputs) def _get_function_calling_prompt_template(self, node_data: ParameterExtractorNodeData, query: str, - variable_pool: VariablePool, - memory: Optional[TokenBufferMemory], - max_token_limit: int = 2000) \ + variable_pool: VariablePool, + memory: Optional[TokenBufferMemory], + max_token_limit: int = 2000) \ -> list[ChatModelMessage]: model_mode = ModelMode.value_of(node_data.model.mode) input_text = query @@ -590,12 +593,12 @@ def _get_function_calling_prompt_template(self, node_data: ParameterExtractorNod return [system_prompt_messages, user_prompt_message] else: raise ValueError(f"Model mode {model_mode} not support.") - + def _get_prompt_engineering_prompt_template(self, node_data: ParameterExtractorNodeData, query: str, variable_pool: VariablePool, memory: Optional[TokenBufferMemory], max_token_limit: int = 2000) \ - -> list[ChatModelMessage]: + -> list[ChatModelMessage]: model_mode = ModelMode.value_of(node_data.model.mode) input_text = query @@ -620,8 +623,8 @@ def _get_prompt_engineering_prompt_template(self, node_data: ParameterExtractorN text=COMPLETION_GENERATE_JSON_PROMPT.format(histories=memory_str, text=input_text, instruction=instruction) - .replace('{γγγ', '') - .replace('}γγγ', '') + .replace('{γγγ', '') + .replace('}γγγ', '') ) else: raise ValueError(f"Model mode {model_mode} not support.") @@ -635,7 +638,7 @@ def _calculate_rest_token(self, node_data: ParameterExtractorNodeData, query: st model_instance, model_config = self._fetch_model_config(node_data.model) if not isinstance(model_instance.model_type_instance, LargeLanguageModel): raise ValueError("Model is not a Large Language Model") - + llm_model = model_instance.model_type_instance model_schema = llm_model.get_model_schema(model_config.model, model_config.credentials) if not model_schema: @@ -667,7 +670,7 @@ def _calculate_rest_token(self, node_data: ParameterExtractorNodeData, query: st model_config.model, model_config.credentials, prompt_messages - ) + 1000 # add 1000 to ensure tool call messages + ) + 1000 # add 1000 to ensure tool call messages max_tokens = 0 for parameter_rule in model_config.model_schema.parameter_rules: @@ -680,8 +683,9 @@ def _calculate_rest_token(self, node_data: ParameterExtractorNodeData, query: st rest_tokens = max(rest_tokens, 0) return rest_tokens - - def _fetch_model_config(self, node_data_model: ModelConfig) -> tuple[ModelInstance, ModelConfigWithCredentialsEntity]: + + def _fetch_model_config(self, node_data_model: ModelConfig) -> tuple[ + ModelInstance, ModelConfigWithCredentialsEntity]: """ Fetch model config. """ @@ -689,9 +693,10 @@ def _fetch_model_config(self, node_data_model: ModelConfig) -> tuple[ModelInstan self._model_instance, self._model_config = super()._fetch_model_config(node_data_model) return self._model_instance, self._model_config - + @classmethod - def _extract_variable_selector_to_variable_mapping(cls, node_data: ParameterExtractorNodeData) -> dict[str, list[str]]: + def _extract_variable_selector_to_variable_mapping(cls, node_data: ParameterExtractorNodeData) -> dict[ + str, list[str]]: """ Extract variable selector to variable mapping :param node_data: node data @@ -708,4 +713,4 @@ def _extract_variable_selector_to_variable_mapping(cls, node_data: ParameterExtr for selector in variable_template_parser.extract_variable_selectors(): variable_mapping[selector.variable] = selector.value_selector - return variable_mapping \ No newline at end of file + return variable_mapping diff --git a/api/fields/app_fields.py b/api/fields/app_fields.py index e314fa21a38bce..9de578544140f4 100644 --- a/api/fields/app_fields.py +++ b/api/fields/app_fields.py @@ -50,6 +50,7 @@ 'enable_site': fields.Boolean, 'enable_api': fields.Boolean, 'model_config': fields.Nested(model_config_fields, attribute='app_model_config', allow_null=True), + 'tracing': fields.Raw, 'created_at': TimestampField } diff --git a/api/migrations/versions/04c602f5dc9b_update_appmodelconfig_and_add_table_.py b/api/migrations/versions/04c602f5dc9b_update_appmodelconfig_and_add_table_.py new file mode 100644 index 00000000000000..a322b9f50290ce --- /dev/null +++ b/api/migrations/versions/04c602f5dc9b_update_appmodelconfig_and_add_table_.py @@ -0,0 +1,49 @@ +"""update AppModelConfig and add table TracingAppConfig + +Revision ID: 04c602f5dc9b +Revises: 4e99a8df00ff +Create Date: 2024-06-12 07:49:07.666510 + +""" +import sqlalchemy as sa +from alembic import op + +import models as models + +# revision identifiers, used by Alembic. +revision = '04c602f5dc9b' +down_revision = '4ff534e1eb11' +branch_labels = None +depends_on = None + + +def upgrade(): + # ### commands auto generated by Alembic - please adjust! ### + op.create_table('tracing_app_configs', + sa.Column('id', models.StringUUID(), server_default=sa.text('uuid_generate_v4()'), nullable=False), + sa.Column('app_id', models.StringUUID(), nullable=False), + sa.Column('tracing_provider', sa.String(length=255), nullable=True), + sa.Column('tracing_config', sa.JSON(), nullable=True), + sa.Column('created_at', sa.DateTime(), server_default=sa.text('now()'), nullable=False), + sa.Column('updated_at', sa.DateTime(), server_default=sa.text('now()'), nullable=False), + sa.PrimaryKeyConstraint('id', name='tracing_app_config_pkey') + ) + with op.batch_alter_table('tracing_app_configs', schema=None) as batch_op: + batch_op.create_index('tracing_app_config_app_id_idx', ['app_id'], unique=False) + + with op.batch_alter_table('app_model_configs', schema=None) as batch_op: + batch_op.add_column(sa.Column('trace_config', sa.Text(), nullable=True)) + + # ### end Alembic commands ### + + +def downgrade(): + # ### commands auto generated by Alembic - please adjust! ### + with op.batch_alter_table('app_model_configs', schema=None) as batch_op: + batch_op.drop_column('trace_config') + + with op.batch_alter_table('tracing_app_configs', schema=None) as batch_op: + batch_op.drop_index('tracing_app_config_app_id_idx') + + op.drop_table('tracing_app_configs') + # ### end Alembic commands ### diff --git a/api/migrations/versions/2a3aebbbf4bb_add_app_tracing.py b/api/migrations/versions/2a3aebbbf4bb_add_app_tracing.py new file mode 100644 index 00000000000000..09ef5e186cd089 --- /dev/null +++ b/api/migrations/versions/2a3aebbbf4bb_add_app_tracing.py @@ -0,0 +1,39 @@ +"""add app tracing + +Revision ID: 2a3aebbbf4bb +Revises: c031d46af369 +Create Date: 2024-06-17 10:08:54.803701 + +""" +import sqlalchemy as sa +from alembic import op + +import models as models + +# revision identifiers, used by Alembic. +revision = '2a3aebbbf4bb' +down_revision = 'c031d46af369' +branch_labels = None +depends_on = None + + +def upgrade(): + # ### commands auto generated by Alembic - please adjust! ### + with op.batch_alter_table('apps', schema=None) as batch_op: + batch_op.add_column(sa.Column('tracing', sa.Text(), nullable=True)) + + with op.batch_alter_table('trace_app_config', schema=None) as batch_op: + batch_op.create_index('tracing_app_config_app_id_idx', ['app_id'], unique=False) + + # ### end Alembic commands ### + + +def downgrade(): + # ### commands auto generated by Alembic - please adjust! ### + with op.batch_alter_table('trace_app_config', schema=None) as batch_op: + batch_op.drop_index('tracing_app_config_app_id_idx') + + with op.batch_alter_table('apps', schema=None) as batch_op: + batch_op.drop_column('tracing') + + # ### end Alembic commands ### diff --git a/api/migrations/versions/c031d46af369_remove_app_model_config_trace_config_.py b/api/migrations/versions/c031d46af369_remove_app_model_config_trace_config_.py new file mode 100644 index 00000000000000..20d9c5d1fb4524 --- /dev/null +++ b/api/migrations/versions/c031d46af369_remove_app_model_config_trace_config_.py @@ -0,0 +1,66 @@ +"""remove app model config trace config and rename trace app config + +Revision ID: c031d46af369 +Revises: 04c602f5dc9b +Create Date: 2024-06-17 10:01:00.255189 + +""" +import sqlalchemy as sa +from alembic import op +from sqlalchemy.dialects import postgresql + +import models as models + +# revision identifiers, used by Alembic. +revision = 'c031d46af369' +down_revision = '04c602f5dc9b' +branch_labels = None +depends_on = None + + +def upgrade(): + # ### commands auto generated by Alembic - please adjust! ### + op.create_table('trace_app_config', + sa.Column('id', models.StringUUID(), server_default=sa.text('uuid_generate_v4()'), nullable=False), + sa.Column('app_id', models.StringUUID(), nullable=False), + sa.Column('tracing_provider', sa.String(length=255), nullable=True), + sa.Column('tracing_config', sa.JSON(), nullable=True), + sa.Column('created_at', sa.DateTime(), server_default=sa.text('now()'), nullable=False), + sa.Column('updated_at', sa.DateTime(), server_default=sa.text('now()'), nullable=False), + sa.Column('is_active', sa.Boolean(), server_default=sa.text('true'), nullable=False), + sa.PrimaryKeyConstraint('id', name='trace_app_config_pkey') + ) + with op.batch_alter_table('trace_app_config', schema=None) as batch_op: + batch_op.create_index('trace_app_config_app_id_idx', ['app_id'], unique=False) + + with op.batch_alter_table('tracing_app_configs', schema=None) as batch_op: + batch_op.drop_index('tracing_app_config_app_id_idx') + + with op.batch_alter_table('app_model_configs', schema=None) as batch_op: + batch_op.drop_column('trace_config') + + # ### end Alembic commands ### + + +def downgrade(): + # ### commands auto generated by Alembic - please adjust! ### + with op.batch_alter_table('app_model_configs', schema=None) as batch_op: + batch_op.add_column(sa.Column('trace_config', sa.TEXT(), autoincrement=False, nullable=True)) + + op.create_table('tracing_app_configs', + sa.Column('id', sa.UUID(), server_default=sa.text('uuid_generate_v4()'), autoincrement=False, nullable=False), + sa.Column('app_id', sa.UUID(), autoincrement=False, nullable=False), + sa.Column('tracing_provider', sa.VARCHAR(length=255), autoincrement=False, nullable=True), + sa.Column('tracing_config', postgresql.JSON(astext_type=sa.Text()), autoincrement=False, nullable=True), + sa.Column('created_at', postgresql.TIMESTAMP(), server_default=sa.text('now()'), autoincrement=False, nullable=False), + sa.Column('updated_at', postgresql.TIMESTAMP(), server_default=sa.text('now()'), autoincrement=False, nullable=False), + sa.PrimaryKeyConstraint('id', name='trace_app_config_pkey') + ) + with op.batch_alter_table('tracing_app_configs', schema=None) as batch_op: + batch_op.create_index('trace_app_config_app_id_idx', ['app_id'], unique=False) + + with op.batch_alter_table('trace_app_config', schema=None) as batch_op: + batch_op.drop_index('trace_app_config_app_id_idx') + + op.drop_table('trace_app_config') + # ### end Alembic commands ### diff --git a/api/models/model.py b/api/models/model.py index 7c9fa0477fed61..c7768acbf3b4ea 100644 --- a/api/models/model.py +++ b/api/models/model.py @@ -6,7 +6,7 @@ from flask import current_app, request from flask_login import UserMixin -from sqlalchemy import Float, text +from sqlalchemy import Float, func, text from core.file.tool_file_parser import ToolFileParser from core.file.upload_file_parser import UploadFileParser @@ -73,6 +73,7 @@ class App(db.Model): is_demo = db.Column(db.Boolean, nullable=False, server_default=db.text('false')) is_public = db.Column(db.Boolean, nullable=False, server_default=db.text('false')) is_universal = db.Column(db.Boolean, nullable=False, server_default=db.text('false')) + tracing = db.Column(db.Text, nullable=True) created_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) updated_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) @@ -1328,3 +1329,38 @@ class TagBinding(db.Model): target_id = db.Column(StringUUID, nullable=True) created_by = db.Column(StringUUID, nullable=False) created_at = db.Column(db.DateTime, nullable=False, server_default=db.text('CURRENT_TIMESTAMP(0)')) + + +class TraceAppConfig(db.Model): + __tablename__ = 'trace_app_config' + __table_args__ = ( + db.PrimaryKeyConstraint('id', name='tracing_app_config_pkey'), + db.Index('tracing_app_config_app_id_idx', 'app_id'), + ) + + id = db.Column(StringUUID, server_default=db.text('uuid_generate_v4()')) + app_id = db.Column(StringUUID, nullable=False) + tracing_provider = db.Column(db.String(255), nullable=True) + tracing_config = db.Column(db.JSON, nullable=True) + created_at = db.Column(db.DateTime, nullable=False, server_default=func.now()) + updated_at = db.Column(db.DateTime, nullable=False, server_default=func.now(), onupdate=func.now()) + is_active = db.Column(db.Boolean, nullable=False, server_default=db.text('true')) + + @property + def tracing_config_dict(self): + return self.tracing_config if self.tracing_config else {} + + @property + def tracing_config_str(self): + return json.dumps(self.tracing_config_dict) + + def to_dict(self): + return { + 'id': self.id, + 'app_id': self.app_id, + 'tracing_provider': self.tracing_provider, + 'tracing_config': self.tracing_config_dict, + "is_active": self.is_active, + "created_at": self.created_at.__str__() if self.created_at else None, + 'updated_at': self.updated_at.__str__() if self.updated_at else None, + } diff --git a/api/poetry.lock b/api/poetry.lock index 89140ce75ec80a..d4060c0977c0d7 100644 --- a/api/poetry.lock +++ b/api/poetry.lock @@ -572,53 +572,54 @@ crt = ["awscrt (==0.19.12)"] [[package]] name = "bottleneck" -version 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-content-hash = "cac196b2ddb59d7873fb3380d87b622d002613d6dc1d271a5c15e46817a38c55" +content-hash = "59a9d41baa5454de6c9032c8d9ca81d79e5a7137c654b8765034aebb8ec29793" diff --git a/api/pyproject.toml b/api/pyproject.toml index 249113ddb9c1d7..b70f6be0d7c6fc 100644 --- a/api/pyproject.toml +++ b/api/pyproject.toml @@ -185,6 +185,8 @@ tcvectordb = "1.3.2" chromadb = "~0.5.1" tenacity = "~8.3.0" cos-python-sdk-v5 = "1.9.30" +langfuse = "^2.36.1" +langsmith = "^0.1.77" novita-client = "^0.5.6" opensearch-py = "2.4.0" oracledb = "~2.2.1" diff --git a/api/services/app_generate_service.py b/api/services/app_generate_service.py index f73a6dcbb686b1..f73a88fdd11451 100644 --- a/api/services/app_generate_service.py +++ b/api/services/app_generate_service.py @@ -18,7 +18,8 @@ def generate(cls, app_model: App, user: Union[Account, EndUser], args: Any, invoke_from: InvokeFrom, - streaming: bool = True) -> Union[dict, Generator[dict, None, None]]: + streaming: bool = True, + ) -> Union[dict, Generator[dict, None, None]]: """ App Content Generate :param app_model: app model diff --git a/api/services/conversation_service.py b/api/services/conversation_service.py index 5c2fb83b7249e5..82ee10ee78f095 100644 --- a/api/services/conversation_service.py +++ b/api/services/conversation_service.py @@ -96,7 +96,9 @@ def auto_generate_name(cls, app_model: App, conversation: Conversation): # generate conversation name try: - name = LLMGenerator.generate_conversation_name(app_model.tenant_id, message.query) + name = LLMGenerator.generate_conversation_name( + app_model.tenant_id, message.query, conversation.id, app_model.id + ) conversation.name = name except: pass diff --git a/api/services/message_service.py b/api/services/message_service.py index e826dcc6bf1455..e310d70d5314e7 100644 --- a/api/services/message_service.py +++ b/api/services/message_service.py @@ -7,6 +7,8 @@ from core.memory.token_buffer_memory import TokenBufferMemory from core.model_manager import ModelManager from core.model_runtime.entities.model_entities import ModelType +from core.ops.ops_trace_manager import TraceQueueManager, TraceTask, TraceTaskName +from core.ops.utils import measure_time from extensions.ext_database import db from libs.infinite_scroll_pagination import InfiniteScrollPagination from models.account import Account @@ -262,9 +264,21 @@ def get_suggested_questions_after_answer(cls, app_model: App, user: Optional[Uni message_limit=3, ) - questions = LLMGenerator.generate_suggested_questions_after_answer( - tenant_id=app_model.tenant_id, - histories=histories + with measure_time() as timer: + questions = LLMGenerator.generate_suggested_questions_after_answer( + tenant_id=app_model.tenant_id, + histories=histories + ) + + # get tracing instance + trace_manager = TraceQueueManager(app_id=app_model.id) + trace_manager.add_trace_task( + TraceTask( + TraceTaskName.SUGGESTED_QUESTION_TRACE, + message_id=message_id, + suggested_question=questions, + timer=timer + ) ) return questions diff --git a/api/services/ops_service.py b/api/services/ops_service.py new file mode 100644 index 00000000000000..ffc12a9acdb42c --- /dev/null +++ b/api/services/ops_service.py @@ -0,0 +1,130 @@ +from core.ops.ops_trace_manager import OpsTraceManager, provider_config_map +from extensions.ext_database import db +from models.model import App, TraceAppConfig + + +class OpsService: + @classmethod + def get_tracing_app_config(cls, app_id: str, tracing_provider: str): + """ + Get tracing app config + :param app_id: app id + :param tracing_provider: tracing provider + :return: + """ + trace_config_data: TraceAppConfig = db.session.query(TraceAppConfig).filter( + TraceAppConfig.app_id == app_id, TraceAppConfig.tracing_provider == tracing_provider + ).first() + + if not trace_config_data: + return None + + # decrypt_token and obfuscated_token + tenant_id = db.session.query(App).filter(App.id == app_id).first().tenant_id + decrypt_tracing_config = OpsTraceManager.decrypt_tracing_config(tenant_id, tracing_provider, trace_config_data.tracing_config) + decrypt_tracing_config = OpsTraceManager.obfuscated_decrypt_token(tracing_provider, decrypt_tracing_config) + + trace_config_data.tracing_config = decrypt_tracing_config + + return trace_config_data.to_dict() + + @classmethod + def create_tracing_app_config(cls, app_id: str, tracing_provider: str, tracing_config: dict): + """ + Create tracing app config + :param app_id: app id + :param tracing_provider: tracing provider + :param tracing_config: tracing config + :return: + """ + if tracing_provider not in provider_config_map.keys() and tracing_provider != None: + return {"error": f"Invalid tracing provider: {tracing_provider}"} + + config_class, other_keys = provider_config_map[tracing_provider]['config_class'], \ + provider_config_map[tracing_provider]['other_keys'] + default_config_instance = config_class(**tracing_config) + for key in other_keys: + if key in tracing_config and tracing_config[key] == "": + tracing_config[key] = getattr(default_config_instance, key, None) + + # api check + if not OpsTraceManager.check_trace_config_is_effective(tracing_config, tracing_provider): + return {"error": "Invalid Credentials"} + + # check if trace config already exists + trace_config_data: TraceAppConfig = db.session.query(TraceAppConfig).filter( + TraceAppConfig.app_id == app_id, TraceAppConfig.tracing_provider == tracing_provider + ).first() + + if trace_config_data: + return None + + # get tenant id + tenant_id = db.session.query(App).filter(App.id == app_id).first().tenant_id + tracing_config = OpsTraceManager.encrypt_tracing_config(tenant_id, tracing_provider, tracing_config) + trace_config_data = TraceAppConfig( + app_id=app_id, + tracing_provider=tracing_provider, + tracing_config=tracing_config, + ) + db.session.add(trace_config_data) + db.session.commit() + + return {"result": "success"} + + @classmethod + def update_tracing_app_config(cls, app_id: str, tracing_provider: str, tracing_config: dict): + """ + Update tracing app config + :param app_id: app id + :param tracing_provider: tracing provider + :param tracing_config: tracing config + :return: + """ + if tracing_provider not in provider_config_map.keys(): + raise ValueError(f"Invalid tracing provider: {tracing_provider}") + + # check if trace config already exists + current_trace_config = db.session.query(TraceAppConfig).filter( + TraceAppConfig.app_id == app_id, TraceAppConfig.tracing_provider == tracing_provider + ).first() + + if not current_trace_config: + return None + + # get tenant id + tenant_id = db.session.query(App).filter(App.id == app_id).first().tenant_id + tracing_config = OpsTraceManager.encrypt_tracing_config( + tenant_id, tracing_provider, tracing_config, current_trace_config.tracing_config + ) + + # api check + # decrypt_token + decrypt_tracing_config = OpsTraceManager.decrypt_tracing_config(tenant_id, tracing_provider, tracing_config) + if not OpsTraceManager.check_trace_config_is_effective(decrypt_tracing_config, tracing_provider): + raise ValueError("Invalid Credentials") + + current_trace_config.tracing_config = tracing_config + db.session.commit() + + return current_trace_config.to_dict() + + @classmethod + def delete_tracing_app_config(cls, app_id: str, tracing_provider: str): + """ + Delete tracing app config + :param app_id: app id + :param tracing_provider: tracing provider + :return: + """ + trace_config = db.session.query(TraceAppConfig).filter( + TraceAppConfig.app_id == app_id, TraceAppConfig.tracing_provider == tracing_provider + ).first() + + if not trace_config: + return None + + db.session.delete(trace_config) + db.session.commit() + + return True