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feat(workflow): domain model for workflow node execution (#19430)

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Signed-off-by: -LAN- <laipz8200@outlook.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
This commit is contained in:
-LAN-
2025-05-17 00:56:16 +08:00
committed by GitHub
parent aeceb200ec
commit 4977bb21ec
31 changed files with 1108 additions and 483 deletions
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5
api/core/ops/langfuse_trace/entities/langfuse_trace_entity.py
View File

@@ -1,3 +1,4 @@
from collections.abc import Mapping
from datetime import datetime
from enum import StrEnum
from typing import Any, Optional, Union
@@ -155,10 +156,10 @@ class LangfuseSpan(BaseModel):
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(
input: Optional[Union[str, Mapping[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(
output: Optional[Union[str, Mapping[str, Any], list, None]] = Field(
default=None, description="The output of the span. Can be any JSON object."
)
version: Optional[str] = Field(

48
api/core/ops/langfuse_trace/langfuse_trace.py
View File

@@ -1,11 +1,10 @@
import json
import logging
import os
from datetime import datetime, timedelta
from typing import Optional
from langfuse import Langfuse # type: ignore
from sqlalchemy.orm import sessionmaker
from sqlalchemy.orm import Session, sessionmaker
from core.ops.base_trace_instance import BaseTraceInstance
from core.ops.entities.config_entity import LangfuseConfig
@@ -30,8 +29,9 @@ from core.ops.langfuse_trace.entities.langfuse_trace_entity import (
)
from core.ops.utils import filter_none_values
from core.repositories import SQLAlchemyWorkflowNodeExecutionRepository
from core.workflow.nodes.enums import NodeType
from extensions.ext_database import db
from models.model import EndUser
from models import Account, App, EndUser, WorkflowNodeExecutionTriggeredFrom
logger = logging.getLogger(__name__)
@@ -113,8 +113,29 @@ class LangFuseDataTrace(BaseTraceInstance):
# through workflow_run_id get all_nodes_execution using repository
session_factory = sessionmaker(bind=db.engine)
# Find the app's creator account
with Session(db.engine, expire_on_commit=False) as session:
# Get the app to find its creator
app_id = trace_info.metadata.get("app_id")
if not app_id:
raise ValueError("No app_id found in trace_info metadata")
app = session.query(App).filter(App.id == app_id).first()
if not app:
raise ValueError(f"App with id {app_id} not found")
if not app.created_by:
raise ValueError(f"App with id {app_id} has no creator (created_by is None)")
service_account = session.query(Account).filter(Account.id == app.created_by).first()
if not service_account:
raise ValueError(f"Creator account with id {app.created_by} not found for app {app_id}")
workflow_node_execution_repository = SQLAlchemyWorkflowNodeExecutionRepository(
session_factory=session_factory, tenant_id=trace_info.tenant_id
session_factory=session_factory,
user=service_account,
app_id=trace_info.metadata.get("app_id"),
triggered_from=WorkflowNodeExecutionTriggeredFrom.WORKFLOW_RUN,
)
# Get all executions for this workflow run
@@ -124,23 +145,22 @@ class LangFuseDataTrace(BaseTraceInstance):
for node_execution in workflow_node_executions:
node_execution_id = node_execution.id
tenant_id = node_execution.tenant_id
app_id = node_execution.app_id
tenant_id = trace_info.tenant_id # Use from trace_info instead
app_id = trace_info.metadata.get("app_id") # Use from trace_info instead
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", {}) if node_execution.process_data else {}
)
if node_type == NodeType.LLM:
inputs = node_execution.process_data.get("prompts", {}) if node_execution.process_data else {}
else:
inputs = json.loads(node_execution.inputs) if node_execution.inputs else {}
outputs = json.loads(node_execution.outputs) if node_execution.outputs else {}
inputs = node_execution.inputs if node_execution.inputs else {}
outputs = node_execution.outputs if node_execution.outputs else {}
created_at = node_execution.created_at or 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 {}
execution_metadata = node_execution.metadata if node_execution.metadata else {}
metadata = {str(k): v for k, v in execution_metadata.items()}
metadata.update(
{
"workflow_run_id": trace_info.workflow_run_id,
@@ -152,7 +172,7 @@ class LangFuseDataTrace(BaseTraceInstance):
"status": status,
}
)
process_data = json.loads(node_execution.process_data) if node_execution.process_data else {}
process_data = node_execution.process_data if node_execution.process_data else {}
model_provider = process_data.get("model_provider", None)
model_name = process_data.get("model_name", None)
if model_provider is not None and model_name is not None: