gateway/modules/workflows/automation2/executionEngine.py

376 lines
17 KiB
Python

# Copyright (c) 2025 Patrick Motsch
# Main execution engine for automation2 graphs.
import logging
from datetime import datetime, timezone
from typing import Dict, Any, List, Set, Optional
from modules.workflows.automation2.graphUtils import (
parseGraph,
buildConnectionMap,
validateGraph,
topoSort,
getInputSources,
getLoopBodyNodeIds,
)
from modules.workflows.automation2.executors import (
TriggerExecutor,
FlowExecutor,
ActionNodeExecutor,
InputExecutor,
PauseForHumanTaskError,
PauseForEmailWaitError,
)
from modules.features.automation2.nodeDefinitions import STATIC_NODE_TYPES
from modules.workflows.automation2.runEnvelope import normalize_run_envelope
logger = logging.getLogger(__name__)
def _getNodeTypeIds(services: Any = None) -> Set[str]:
"""Collect all known node type IDs from static definitions."""
return {n["id"] for n in STATIC_NODE_TYPES}
def _is_node_on_active_path(
nodeId: str,
connectionMap: Dict[str, List],
nodeOutputs: Dict[str, Any],
) -> bool:
"""
Return True if this node receives input only from active branches.
- flow.ifElse: only one output (0=yes, 1=no) is active; uses "branch".
- flow.switch: only one output (0, 1, 2, ...) is active; uses "match".
Nodes connected to inactive outputs must be skipped.
Also skip when a predecessor was skipped (not in nodeOutputs).
"""
for src, source_output, _ in connectionMap.get(nodeId, []):
out = nodeOutputs.get(src)
if out is None:
return False
if not isinstance(out, dict):
continue
branch = out.get("branch")
match = out.get("match")
active_output = None
if branch is not None:
active_output = branch
elif match is not None:
if match < 0:
return False # switch: no case matched, skip all downstream
active_output = match
if active_output is not None and source_output != active_output:
return False
return True
def _getExecutor(
nodeType: str,
services: Any,
automation2_interface: Optional[Any] = None,
) -> Any:
"""Dispatch to correct executor based on node type."""
if nodeType.startswith("trigger."):
return TriggerExecutor()
if nodeType.startswith("flow."):
return FlowExecutor()
if nodeType.startswith("ai.") or nodeType.startswith("email.") or nodeType.startswith("sharepoint.") or nodeType.startswith("clickup.") or nodeType.startswith("file."):
return ActionNodeExecutor(services)
if nodeType.startswith("input.") and automation2_interface:
return InputExecutor(automation2_interface)
return None
async def executeGraph(
graph: Dict[str, Any],
services: Any,
workflowId: str = None,
instanceId: str = None,
userId: str = None,
mandateId: str = None,
automation2_interface: Optional[Any] = None,
initialNodeOutputs: Optional[Dict[str, Any]] = None,
startAfterNodeId: Optional[str] = None,
runId: Optional[str] = None,
run_envelope: Optional[Dict[str, Any]] = None,
) -> Dict[str, Any]:
"""
Execute automation2 graph. Returns { success, nodeOutputs, error?, stopped? }.
When an input node is reached and automation2_interface is provided, creates a task,
pauses the run, and returns { success: False, paused: True, taskId, runId }.
For resume: pass initialNodeOutputs (with result for the human node) and startAfterNodeId.
For fresh runs: pass run_envelope (unified start payload for the start node); normalized with userId into context.runEnvelope.
"""
logger.info(
"executeGraph start: instanceId=%s workflowId=%s userId=%s mandateId=%s resume=%s",
instanceId,
workflowId,
userId,
mandateId,
startAfterNodeId is not None,
)
from modules.workflows.processing.shared.methodDiscovery import discoverMethods
discoverMethods(services)
nodeTypeIds = _getNodeTypeIds(services)
logger.debug("executeGraph nodeTypeIds (%d): %s", len(nodeTypeIds), sorted(nodeTypeIds))
errors = validateGraph(graph, nodeTypeIds)
if errors:
logger.warning("executeGraph validation failed: %s", errors)
return {"success": False, "error": "; ".join(errors), "nodeOutputs": {}}
nodes, connections = parseGraph(graph)[:2]
connectionMap = buildConnectionMap(connections)
inputSources = {n["id"]: getInputSources(n["id"], connectionMap) for n in nodes if n.get("id")}
logger.info(
"executeGraph parsed: nodes=%d connections=%d connectionMap_targets=%s",
len(nodes),
len(connections),
list(connectionMap.keys()),
)
ordered = topoSort(nodes, connectionMap)
ordered_ids = [n.get("id") for n in ordered if n.get("id")]
logger.info("executeGraph topoSort order: %s", ordered_ids)
nodeOutputs: Dict[str, Any] = dict(initialNodeOutputs or {})
is_resume = startAfterNodeId is not None
if not runId and automation2_interface and workflowId and not is_resume:
run_context = {
"connectionMap": connectionMap,
"inputSources": inputSources,
"orderedNodeIds": ordered_ids,
}
if userId:
run_context["ownerId"] = userId
if mandateId:
run_context["mandateId"] = mandateId
if instanceId:
run_context["instanceId"] = instanceId
run = automation2_interface.createRun(
workflowId=workflowId,
nodeOutputs=nodeOutputs,
context=run_context,
)
runId = run.get("id") if run else None
logger.info("executeGraph created run %s", runId)
env_for_run = normalize_run_envelope(run_envelope, user_id=userId)
context = {
"workflowId": workflowId,
"instanceId": instanceId,
"userId": userId,
"mandateId": mandateId,
"nodeOutputs": nodeOutputs,
"connectionMap": connectionMap,
"inputSources": inputSources,
"services": services,
"_runId": runId,
"_orderedNodes": ordered,
"runEnvelope": env_for_run,
}
skip_until_passed = bool(startAfterNodeId)
processed_in_loop: Set[str] = set()
# Check for loop resume: run was paused inside a loop, we're resuming for next iteration
run = automation2_interface.getRun(runId) if (runId and automation2_interface) else None
loop_resume_state = (run.get("context") or {}).get("_loopState") if run else None
if loop_resume_state and startAfterNodeId:
loop_node_id = loop_resume_state.get("loopNodeId")
next_index = loop_resume_state.get("currentIndex", -1) + 1
items = loop_resume_state.get("items") or []
body_ids = getLoopBodyNodeIds(loop_node_id, connectionMap) if loop_node_id else set()
body_ordered = [n for n in ordered if n.get("id") in body_ids]
processed_in_loop = set(body_ids) | {loop_node_id} if loop_node_id else set()
while next_index < len(items) and loop_node_id:
nodeOutputs[loop_node_id] = {
"items": items,
"count": len(items),
"currentItem": items[next_index],
"currentIndex": next_index,
}
context["_loopState"] = {"loopNodeId": loop_node_id, "currentIndex": next_index, "items": items}
for body_node in body_ordered:
bnid = body_node.get("id")
if not bnid or context.get("_stopped"):
break
if not _is_node_on_active_path(bnid, connectionMap, nodeOutputs):
continue
executor = _getExecutor(body_node.get("type", ""), services, automation2_interface)
if not executor:
nodeOutputs[bnid] = None
continue
try:
result = await executor.execute(body_node, context)
nodeOutputs[bnid] = result
logger.info("executeGraph loop resume body node %s done (iter %d)", bnid, next_index)
except PauseForHumanTaskError as e:
if automation2_interface:
run_ctx = dict(run.get("context") or {})
run_ctx["_loopState"] = {"loopNodeId": loop_node_id, "currentIndex": next_index, "items": items}
automation2_interface.updateRun(e.runId, status="paused", nodeOutputs=dict(nodeOutputs), currentNodeId=e.nodeId, context=run_ctx)
return {"success": False, "paused": True, "taskId": e.taskId, "runId": e.runId, "nodeId": e.nodeId, "nodeOutputs": dict(nodeOutputs)}
except Exception as ex:
logger.exception("executeGraph loop body node %s FAILED: %s", bnid, ex)
nodeOutputs[bnid] = {"error": str(ex), "success": False}
if runId and automation2_interface:
automation2_interface.updateRun(runId, status="failed", nodeOutputs=nodeOutputs)
return {"success": False, "error": str(ex), "nodeOutputs": nodeOutputs, "failedNode": bnid}
next_index += 1
if loop_node_id:
nodeOutputs[loop_node_id] = {"items": items, "count": len(items)}
processed_in_loop = set(body_ids) | {loop_node_id}
for i, node in enumerate(ordered):
if skip_until_passed:
if node.get("id") == startAfterNodeId:
skip_until_passed = False
continue
if node.get("id") in processed_in_loop:
continue
if context.get("_stopped"):
logger.info("executeGraph stopped early at step %d", i)
break
nodeId = node.get("id")
nodeType = node.get("type", "")
if not _is_node_on_active_path(nodeId, connectionMap, nodeOutputs):
logger.info("executeGraph step %d/%d: nodeId=%s SKIP (inactive branch)", i + 1, len(ordered), nodeId)
continue
executor = _getExecutor(nodeType, services, automation2_interface)
logger.info(
"executeGraph step %d/%d: nodeId=%s nodeType=%s executor=%s",
i + 1,
len(ordered),
nodeId,
nodeType,
type(executor).__name__ if executor else "None",
)
if not executor:
nodeOutputs[nodeId] = None
logger.debug("executeGraph node %s: no executor, output=None", nodeId)
continue
try:
if nodeType == "flow.loop":
result = await executor.execute(node, context)
items = result.get("items") or []
body_ids = getLoopBodyNodeIds(nodeId, connectionMap)
body_ordered = [n for n in ordered if n.get("id") in body_ids]
processed_in_loop.update(body_ids)
processed_in_loop.add(nodeId)
for idx, item in enumerate(items):
nodeOutputs[nodeId] = {"items": items, "count": len(items), "currentItem": item, "currentIndex": idx}
context["_loopState"] = {"loopNodeId": nodeId, "currentIndex": idx, "items": items}
for body_node in body_ordered:
bnid = body_node.get("id")
if not bnid or context.get("_stopped"):
break
if not _is_node_on_active_path(bnid, connectionMap, nodeOutputs):
continue
bexec = _getExecutor(body_node.get("type", ""), services, automation2_interface)
if not bexec:
nodeOutputs[bnid] = None
continue
try:
bres = await bexec.execute(body_node, context)
nodeOutputs[bnid] = bres
logger.info("executeGraph loop body node %s done (iter %d)", bnid, idx)
except PauseForHumanTaskError as e:
if runId and automation2_interface:
run = automation2_interface.getRun(runId) or {}
run_ctx = dict(run.get("context") or {})
run_ctx["_loopState"] = {"loopNodeId": nodeId, "currentIndex": idx, "items": items}
automation2_interface.updateRun(e.runId, status="paused", nodeOutputs=dict(nodeOutputs), currentNodeId=e.nodeId, context=run_ctx)
return {"success": False, "paused": True, "taskId": e.taskId, "runId": e.runId, "nodeId": e.nodeId, "nodeOutputs": dict(nodeOutputs)}
except Exception as ex:
logger.exception("executeGraph loop body node %s FAILED: %s", bnid, ex)
nodeOutputs[bnid] = {"error": str(ex), "success": False}
if runId and automation2_interface:
automation2_interface.updateRun(runId, status="failed", nodeOutputs=nodeOutputs)
return {"success": False, "error": str(ex), "nodeOutputs": nodeOutputs, "failedNode": bnid}
nodeOutputs[nodeId] = {"items": items, "count": len(items)}
logger.info("executeGraph flow.loop done: %d iterations", len(items))
else:
result = await executor.execute(node, context)
nodeOutputs[nodeId] = result
logger.info(
"executeGraph node %s done: result_type=%s result_keys=%s",
nodeId,
type(result).__name__,
list(result.keys()) if isinstance(result, dict) else "n/a",
)
except PauseForHumanTaskError as e:
logger.info("executeGraph paused for human task %s", e.taskId)
return {
"success": False,
"paused": True,
"taskId": e.taskId,
"runId": e.runId,
"nodeId": e.nodeId,
"nodeOutputs": dict(nodeOutputs),
}
except PauseForEmailWaitError as e:
logger.info("executeGraph paused for email wait (run %s, node %s)", e.runId, e.nodeId)
# Start email poller on-demand (only runs while workflows wait for email)
try:
from modules.interfaces.interfaceDbApp import getRootInterface
from modules.features.automation2.emailPoller import ensureRunning
root = getRootInterface()
event_user = root.getUserByUsername("event") if root else None
if event_user:
ensureRunning(event_user)
except Exception as poll_err:
logger.warning("Could not start email poller: %s", poll_err)
paused_at = datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%SZ")
run_ctx = {
"connectionMap": context.get("connectionMap"),
"inputSources": context.get("inputSources"),
"orderedNodeIds": [n.get("id") for n in context.get("_orderedNodes", []) if n.get("id")],
"waitReason": "email",
"waitConfig": e.waitConfig,
"pausedAt": paused_at,
"lastCheckedAt": None,
"ownerId": context.get("userId"),
"mandateId": context.get("mandateId"),
"instanceId": context.get("instanceId"),
}
automation2_interface.updateRun(
e.runId,
status="paused",
nodeOutputs=dict(nodeOutputs),
currentNodeId=e.nodeId,
context=run_ctx,
)
return {
"success": False,
"paused": True,
"waitReason": "email",
"runId": e.runId,
"nodeId": e.nodeId,
"nodeOutputs": dict(nodeOutputs),
}
except Exception as e:
logger.exception("executeGraph node %s (%s) FAILED: %s", nodeId, nodeType, e)
nodeOutputs[nodeId] = {"error": str(e), "success": False}
if runId and automation2_interface:
automation2_interface.updateRun(runId, status="failed", nodeOutputs=nodeOutputs)
return {
"success": False,
"error": str(e),
"nodeOutputs": nodeOutputs,
"failedNode": nodeId,
}
if runId and automation2_interface:
automation2_interface.updateRun(runId, status="completed", nodeOutputs=nodeOutputs)
logger.info(
"executeGraph complete: success=True nodeOutputs_keys=%s stopped=%s",
list(nodeOutputs.keys()),
context.get("_stopped", False),
)
return {
"success": True,
"nodeOutputs": nodeOutputs,
"stopped": context.get("_stopped", False),
}