1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112import json
import time
import uuid
from collections.abc import Callable, Generator, Mapping, Sequence
from typing import Any, cast
from sqlalchemy import exists, select
from sqlalchemy.orm import Session, sessionmaker
from configs import dify_config
from core.app.app_config.entities import VariableEntityType
from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfigManager
from core.app.apps.workflow.app_config_manager import WorkflowAppConfigManager
from core.file import File
from core.repositories import DifyCoreRepositoryFactory
from core.variables import VariableBase
from core.variables.variables import Variable
from core.workflow.entities import WorkflowNodeExecution
from core.workflow.enums import ErrorStrategy, WorkflowNodeExecutionMetadataKey, WorkflowNodeExecutionStatus
from core.workflow.errors import WorkflowNodeRunFailedError
from core.workflow.graph_events import GraphNodeEventBase, NodeRunFailedEvent, NodeRunSucceededEvent
from core.workflow.node_events import NodeRunResult
from core.workflow.nodes import NodeType
from core.workflow.nodes.base.node import Node
from core.workflow.nodes.node_mapping import LATEST_VERSION, NODE_TYPE_CLASSES_MAPPING
from core.workflow.nodes.start.entities import StartNodeData
from core.workflow.runtime import VariablePool
from core.workflow.system_variable import SystemVariable
from core.workflow.workflow_entry import WorkflowEntry
from enums.cloud_plan import CloudPlan
from events.app_event import app_draft_workflow_was_synced, app_published_workflow_was_updated
from extensions.ext_database import db
from extensions.ext_storage import storage
from factories.file_factory import build_from_mapping, build_from_mappings
from libs.datetime_utils import naive_utc_now
from models import Account
from models.model import App, AppMode
from models.tools import WorkflowToolProvider
from models.workflow import Workflow, WorkflowNodeExecutionModel, WorkflowNodeExecutionTriggeredFrom, WorkflowType
from repositories.factory import DifyAPIRepositoryFactory
from services.billing_service import BillingService
from services.enterprise.plugin_manager_service import PluginCredentialType
from services.errors.app import IsDraftWorkflowError, TriggerNodeLimitExceededError, WorkflowHashNotEqualError
from services.workflow.workflow_converter import WorkflowConverter
from .errors.workflow_service import DraftWorkflowDeletionError, WorkflowInUseError
from .workflow_draft_variable_service import DraftVariableSaver, DraftVarLoader, WorkflowDraftVariableService
class WorkflowService:
"""
Workflow Service
"""
def __init__(self, session_maker: sessionmaker | None = None):
"""Initialize WorkflowService with repository dependencies."""
if session_maker is None:
session_maker = sessionmaker(bind=db.engine, expire_on_commit=False)
self._node_execution_service_repo = DifyAPIRepositoryFactory.create_api_workflow_node_execution_repository(
session_maker
)
def get_node_last_run(self, app_model: App, workflow: Workflow, node_id: str) -> WorkflowNodeExecutionModel | None:
"""
Get the most recent execution for a specific node.
Args:
app_model: The application model
workflow: The workflow model
node_id: The node identifier
Returns:
The most recent WorkflowNodeExecutionModel for the node, or None if not found
"""
return self._node_execution_service_repo.get_node_last_execution(
tenant_id=app_model.tenant_id,
app_id=app_model.id,
workflow_id=workflow.id,
node_id=node_id,
)
def is_workflow_exist(self, app_model: App) -> bool:
stmt = select(
exists().where(
Workflow.tenant_id == app_model.tenant_id,
Workflow.app_id == app_model.id,
Workflow.version == Workflow.VERSION_DRAFT,
)
)
return db.session.execute(stmt).scalar_one()
def get_draft_workflow(self, app_model: App, workflow_id: str | None = None) -> Workflow | None:
"""
Get draft workflow
"""
if workflow_id:
return self.get_published_workflow_by_id(app_model, workflow_id)
# fetch draft workflow by app_model
workflow = (
db.session.query(Workflow)
.where(
Workflow.tenant_id == app_model.tenant_id,
Workflow.app_id == app_model.id,
Workflow.version == Workflow.VERSION_DRAFT,
)
.first()
)
# return draft workflow
return workflow
def get_published_workflow_by_id(self, app_model: App, workflow_id: str) -> Workflow | None:
"""
fetch published workflow by workflow_id
"""
workflow = (
db.session.query(Workflow)
.where(
Workflow.tenant_id == app_model.tenant_id,
Workflow.app_id == app_model.id,
Workflow.id == workflow_id,
)
.first()
)
if not workflow:
return None
if workflow.version == Workflow.VERSION_DRAFT:
raise IsDraftWorkflowError(
f"Cannot use draft workflow version. Workflow ID: {workflow_id}. "
f"Please use a published workflow version or leave workflow_id empty."
)
return workflow
def get_published_workflow(self, app_model: App) -> Workflow | None:
"""
Get published workflow
"""
if not app_model.workflow_id:
return None
# fetch published workflow by workflow_id
workflow = (
db.session.query(Workflow)
.where(
Workflow.tenant_id == app_model.tenant_id,
Workflow.app_id == app_model.id,
Workflow.id == app_model.workflow_id,
)
.first()
)
return workflow
def get_all_published_workflow(
self,
*,
session: Session,
app_model: App,
page: int,
limit: int,
user_id: str | None,
named_only: bool = False,
) -> tuple[Sequence[Workflow], bool]:
"""
Get published workflow with pagination
"""
if not app_model.workflow_id:
return [], False
stmt = (
select(Workflow)
.where(Workflow.app_id == app_model.id)
.order_by(Workflow.version.desc())
.limit(limit + 1)
.offset((page - 1) * limit)
)
if user_id:
stmt = stmt.where(Workflow.created_by == user_id)
if named_only:
stmt = stmt.where(Workflow.marked_name != "")
workflows = session.scalars(stmt).all()
has_more = len(workflows) > limit
if has_more:
workflows = workflows[:-1]
return workflows, has_more
def sync_draft_workflow(
self,
*,
app_model: App,
graph: dict,
features: dict,
unique_hash: str | None,
account: Account,
environment_variables: Sequence[VariableBase],
conversation_variables: Sequence[VariableBase],
) -> Workflow:
"""
Sync draft workflow
:raises WorkflowHashNotEqualError
"""
# fetch draft workflow by app_model
workflow = self.get_draft_workflow(app_model=app_model)
if workflow and workflow.unique_hash != unique_hash:
raise WorkflowHashNotEqualError()
# validate features structure
self.validate_features_structure(app_model=app_model, features=features)
# validate graph structure
self.validate_graph_structure(graph=graph)
# create draft workflow if not found
if not workflow:
workflow = Workflow(
tenant_id=app_model.tenant_id,
app_id=app_model.id,
type=WorkflowType.from_app_mode(app_model.mode).value,
version=Workflow.VERSION_DRAFT,
graph=json.dumps(graph),
features=json.dumps(features),
created_by=account.id,
environment_variables=environment_variables,
conversation_variables=conversation_variables,
)
db.session.add(workflow)
# update draft workflow if found
else:
workflow.graph = json.dumps(graph)
workflow.features = json.dumps(features)
workflow.updated_by = account.id
workflow.updated_at = naive_utc_now()
workflow.environment_variables = environment_variables
workflow.conversation_variables = conversation_variables
# commit db session changes
db.session.commit()
# trigger app workflow events
app_draft_workflow_was_synced.send(app_model, synced_draft_workflow=workflow)
# return draft workflow
return workflow
def publish_workflow(
self,
*,
session: Session,
app_model: App,
account: Account,
marked_name: str = "",
marked_comment: str = "",
) -> Workflow:
draft_workflow_stmt = select(Workflow).where(
Workflow.tenant_id == app_model.tenant_id,
Workflow.app_id == app_model.id,
Workflow.version == Workflow.VERSION_DRAFT,
)
draft_workflow = session.scalar(draft_workflow_stmt)
if not draft_workflow:
raise ValueError("No valid workflow found.")
# Validate credentials before publishing, for credential policy check
from services.feature_service import FeatureService
if FeatureService.get_system_features().plugin_manager.enabled:
self._validate_workflow_credentials(draft_workflow)
# validate graph structure
self.validate_graph_structure(graph=draft_workflow.graph_dict)
# billing check
if dify_config.BILLING_ENABLED:
limit_info = BillingService.get_info(app_model.tenant_id)
if limit_info["subscription"]["plan"] == CloudPlan.SANDBOX:
# Check trigger node count limit for SANDBOX plan
trigger_node_count = sum(
1
for _, node_data in draft_workflow.walk_nodes()
if (node_type_str := node_data.get("type"))
and isinstance(node_type_str, str)
and NodeType(node_type_str).is_trigger_node
)
if trigger_node_count > 2:
raise TriggerNodeLimitExceededError(count=trigger_node_count, limit=2)
# create new workflow
workflow = Workflow.new(
tenant_id=app_model.tenant_id,
app_id=app_model.id,
type=draft_workflow.type,
version=Workflow.version_from_datetime(naive_utc_now()),
graph=draft_workflow.graph,
created_by=account.id,
environment_variables=draft_workflow.environment_variables,
conversation_variables=draft_workflow.conversation_variables,
marked_name=marked_name,
marked_comment=marked_comment,
rag_pipeline_variables=draft_workflow.rag_pipeline_variables,
features=draft_workflow.features,
)
# commit db session changes
session.add(workflow)
# trigger app workflow events
app_published_workflow_was_updated.send(app_model, published_workflow=workflow)
# return new workflow
return workflow
def _validate_workflow_credentials(self, workflow: Workflow) -> None:
"""
Validate all credentials in workflow nodes before publishing.
:param workflow: The workflow to validate
:raises ValueError: If any credentials violate policy compliance
"""
graph_dict = workflow.graph_dict
nodes = graph_dict.get("nodes", [])
for node in nodes:
node_data = node.get("data", {})
node_type = node_data.get("type")
node_id = node.get("id", "unknown")
try:
# Extract and validate credentials based on node type
if node_type == "tool":
credential_id = node_data.get("credential_id")
provider = node_data.get("provider_id")
if provider:
if credential_id:
# Check specific credential
from core.helper.credential_utils import check_credential_policy_compliance
check_credential_policy_compliance(
credential_id=credential_id,
provider=provider,
credential_type=PluginCredentialType.TOOL,
)
else:
# Check default workspace credential for this provider
self._check_default_tool_credential(workflow.tenant_id, provider)
elif node_type == "agent":
agent_params = node_data.get("agent_parameters", {})
model_config = agent_params.get("model", {}).get("value", {})
if model_config.get("provider") and model_config.get("model"):
self._validate_llm_model_config(
workflow.tenant_id, model_config["provider"], model_config["model"]
)
# Validate load balancing credentials for agent model if load balancing is enabled
agent_model_node_data = {"model": model_config}
self._validate_load_balancing_credentials(workflow, agent_model_node_data, node_id)
# Validate agent tools
tools = agent_params.get("tools", {}).get("value", [])
for tool in tools:
# Agent tools store provider in provider_name field
provider = tool.get("provider_name")
credential_id = tool.get("credential_id")
if provider:
if credential_id:
from core.helper.credential_utils import check_credential_policy_compliance
check_credential_policy_compliance(credential_id, provider, PluginCredentialType.TOOL)
else:
self._check_default_tool_credential(workflow.tenant_id, provider)
elif node_type in ["llm", "knowledge_retrieval", "parameter_extractor", "question_classifier"]:
model_config = node_data.get("model", {})
provider = model_config.get("provider")
model_name = model_config.get("name")
if provider and model_name:
# Validate that the provider+model combination can fetch valid credentials
self._validate_llm_model_config(workflow.tenant_id, provider, model_name)
# Validate load balancing credentials if load balancing is enabled
self._validate_load_balancing_credentials(workflow, node_data, node_id)
else:
raise ValueError(f"Node {node_id} ({node_type}): Missing provider or model configuration")
except Exception as e:
if isinstance(e, ValueError):
raise e
else:
raise ValueError(f"Node {node_id} ({node_type}): {str(e)}")
def _validate_llm_model_config(self, tenant_id: str, provider: str, model_name: str) -> None:
"""
Validate that an LLM model configuration can fetch valid credentials and has active status.
This method attempts to get the model instance and validates that:
1. The provider exists and is configured
2. The model exists in the provider
3. Credentials can be fetched for the model
4. The credentials pass policy compliance checks
5. The model status is ACTIVE (not NO_CONFIGURE, DISABLED, etc.)
:param tenant_id: The tenant ID
:param provider: The provider name
:param model_name: The model name
:raises ValueError: If the model configuration is invalid or credentials fail policy checks
"""
try:
from core.model_manager import ModelManager
from core.model_runtime.entities.model_entities import ModelType
from core.provider_manager import ProviderManager
# Get model instance to validate provider+model combination
model_manager = ModelManager()
model_manager.get_model_instance(
tenant_id=tenant_id, provider=provider, model_type=ModelType.LLM, model=model_name
)
# The ModelInstance constructor will automatically check credential policy compliance
# via ProviderConfiguration.get_current_credentials() -> _check_credential_policy_compliance()
# If it fails, an exception will be raised
# Additionally, check the model status to ensure it's ACTIVE
provider_manager = ProviderManager()
provider_configurations = provider_manager.get_configurations(tenant_id)
models = provider_configurations.get_models(provider=provider, model_type=ModelType.LLM)
target_model = None
for model in models:
if model.model == model_name and model.provider.provider == provider:
target_model = model
break
if target_model:
target_model.raise_for_status()
else:
raise ValueError(f"Model {model_name} not found for provider {provider}")
except Exception as e:
raise ValueError(
f"Failed to validate LLM model configuration (provider: {provider}, model: {model_name}): {str(e)}"
)
def _check_default_tool_credential(self, tenant_id: str, provider: str) -> None:
"""
Check credential policy compliance for the default workspace credential of a tool provider.
This method finds the default credential for the given provider and validates it.
Uses the same fallback logic as runtime to handle deauthorized credentials.
:param tenant_id: The tenant ID
:param provider: The tool provider name
:raises ValueError: If no default credential exists or if it fails policy compliance
"""
try:
from models.tools import BuiltinToolProvider
# Use the same fallback logic as runtime: get the first available credential
# ordered by is_default DESC, created_at ASC (same as tool_manager.py)
default_provider = (
db.session.query(BuiltinToolProvider)
.where(
BuiltinToolProvider.tenant_id == tenant_id,
BuiltinToolProvider.provider == provider,
)
.order_by(BuiltinToolProvider.is_default.desc(), BuiltinToolProvider.created_at.asc())
.first()
)
if not default_provider:
# plugin does not require credentials, skip
return
# Check credential policy compliance using the default credential ID
from core.helper.credential_utils import check_credential_policy_compliance
check_credential_policy_compliance(
credential_id=default_provider.id,
provider=provider,
credential_type=PluginCredentialType.TOOL,
check_existence=False,
)
except Exception as e:
raise ValueError(f"Failed to validate default credential for tool provider {provider}: {str(e)}")
def _validate_load_balancing_credentials(self, workflow: Workflow, node_data: dict, node_id: str) -> None:
"""
Validate load balancing credentials for a workflow node.
:param workflow: The workflow being validated
:param node_data: The node data containing model configuration
:param node_id: The node ID for error reporting
:raises ValueError: If load balancing credentials violate policy compliance
"""
# Extract model configuration
model_config = node_data.get("model", {})
provider = model_config.get("provider")
model_name = model_config.get("name")
if not provider or not model_name:
return # No model config to validate
# Check if this model has load balancing enabled
if self._is_load_balancing_enabled(workflow.tenant_id, provider, model_name):
# Get all load balancing configurations for this model
load_balancing_configs = self._get_load_balancing_configs(workflow.tenant_id, provider, model_name)
# Validate each load balancing configuration
try:
for config in load_balancing_configs:
if config.get("credential_id"):
from core.helper.credential_utils import check_credential_policy_compliance
check_credential_policy_compliance(
config["credential_id"], provider, PluginCredentialType.MODEL
)
except Exception as e:
raise ValueError(f"Invalid load balancing credentials for {provider}/{model_name}: {str(e)}")
def _is_load_balancing_enabled(self, tenant_id: str, provider: str, model_name: str) -> bool:
"""
Check if load balancing is enabled for a specific model.
:param tenant_id: The tenant ID
:param provider: The provider name
:param model_name: The model name
:return: True if load balancing is enabled, False otherwise
"""
try:
from core.model_runtime.entities.model_entities import ModelType
from core.provider_manager import ProviderManager
# Get provider configurations
provider_manager = ProviderManager()
provider_configurations = provider_manager.get_configurations(tenant_id)
provider_configuration = provider_configurations.get(provider)
if not provider_configuration:
return False
# Get provider model setting
provider_model_setting = provider_configuration.get_provider_model_setting(
model_type=ModelType.LLM,
model=model_name,
)
return provider_model_setting is not None and provider_model_setting.load_balancing_enabled
except Exception:
# If we can't determine the status, assume load balancing is not enabled
return False
def _get_load_balancing_configs(self, tenant_id: str, provider: str, model_name: str) -> list[dict]:
"""
Get all load balancing configurations for a model.
:param tenant_id: The tenant ID
:param provider: The provider name
:param model_name: The model name
:return: List of load balancing configuration dictionaries
"""
try:
from services.model_load_balancing_service import ModelLoadBalancingService
model_load_balancing_service = ModelLoadBalancingService()
_, configs = model_load_balancing_service.get_load_balancing_configs(
tenant_id=tenant_id,
provider=provider,
model=model_name,
model_type="llm", # Load balancing is primarily used for LLM models
config_from="predefined-model", # Check both predefined and custom models
)
_, custom_configs = model_load_balancing_service.get_load_balancing_configs(
tenant_id=tenant_id, provider=provider, model=model_name, model_type="llm", config_from="custom-model"
)
all_configs = configs + custom_configs
return [config for config in all_configs if config.get("credential_id")]
except Exception:
# If we can't get the configurations, return empty list
# This will prevent validation errors from breaking the workflow
return []
def get_default_block_configs(self) -> Sequence[Mapping[str, object]]:
"""
Get default block configs
"""
# return default block config
default_block_configs: list[Mapping[str, object]] = []
for node_class_mapping in NODE_TYPE_CLASSES_MAPPING.values():
node_class = node_class_mapping[LATEST_VERSION]
default_config = node_class.get_default_config()
if default_config:
default_block_configs.append(default_config)
return default_block_configs
def get_default_block_config(
self, node_type: str, filters: Mapping[str, object] | None = None
) -> Mapping[str, object]:
"""
Get default config of node.
:param node_type: node type
:param filters: filter by node config parameters.
:return:
"""
node_type_enum = NodeType(node_type)
# return default block config
if node_type_enum not in NODE_TYPE_CLASSES_MAPPING:
return {}
node_class = NODE_TYPE_CLASSES_MAPPING[node_type_enum][LATEST_VERSION]
default_config = node_class.get_default_config(filters=filters)
if not default_config:
return {}
return default_config
def run_draft_workflow_node(
self,
app_model: App,
draft_workflow: Workflow,
node_id: str,
user_inputs: Mapping[str, Any],
account: Account,
query: str = "",
files: Sequence[File] | None = None,
) -> WorkflowNodeExecutionModel:
"""
Run draft workflow node
"""
files = files or []
with Session(bind=db.engine, expire_on_commit=False) as session, session.begin():
draft_var_srv = WorkflowDraftVariableService(session)
draft_var_srv.prefill_conversation_variable_default_values(draft_workflow)
node_config = draft_workflow.get_node_config_by_id(node_id)
node_type = Workflow.get_node_type_from_node_config(node_config)
node_data = node_config.get("data", {})
if node_type.is_start_node:
with Session(bind=db.engine) as session, session.begin():
draft_var_srv = WorkflowDraftVariableService(session)
conversation_id = draft_var_srv.get_or_create_conversation(
account_id=account.id,
app=app_model,
workflow=draft_workflow,
)
if node_type is NodeType.START:
start_data = StartNodeData.model_validate(node_data)
user_inputs = _rebuild_file_for_user_inputs_in_start_node(
tenant_id=draft_workflow.tenant_id, start_node_data=start_data, user_inputs=user_inputs
)
# init variable pool
variable_pool = _setup_variable_pool(
query=query,
files=files or [],
user_id=account.id,
user_inputs=user_inputs,
workflow=draft_workflow,
# NOTE(QuantumGhost): We rely on `DraftVarLoader` to load conversation variables.
conversation_variables=[],
node_type=node_type,
conversation_id=conversation_id,
)
else:
variable_pool = VariablePool(
system_variables=SystemVariable.empty(),
user_inputs=user_inputs,
environment_variables=draft_workflow.environment_variables,
conversation_variables=[],
)
variable_loader = DraftVarLoader(
engine=db.engine,
app_id=app_model.id,
tenant_id=app_model.tenant_id,
)
enclosing_node_type_and_id = draft_workflow.get_enclosing_node_type_and_id(node_config)
if enclosing_node_type_and_id:
_, enclosing_node_id = enclosing_node_type_and_id
else:
enclosing_node_id = None
run = WorkflowEntry.single_step_run(
workflow=draft_workflow,
node_id=node_id,
user_inputs=user_inputs,
user_id=account.id,
variable_pool=variable_pool,
variable_loader=variable_loader,
)
# run draft workflow node
start_at = time.perf_counter()
node_execution = self._handle_single_step_result(
invoke_node_fn=lambda: run,
start_at=start_at,
node_id=node_id,
)
# Set workflow_id on the NodeExecution
node_execution.workflow_id = draft_workflow.id
# Create repository and save the node execution
repository = DifyCoreRepositoryFactory.create_workflow_node_execution_repository(
session_factory=db.engine,
user=account,
app_id=app_model.id,
triggered_from=WorkflowNodeExecutionTriggeredFrom.SINGLE_STEP,
)
repository.save(node_execution)
workflow_node_execution = self._node_execution_service_repo.get_execution_by_id(node_execution.id)
if workflow_node_execution is None:
raise ValueError(f"WorkflowNodeExecution with id {node_execution.id} not found after saving")
with Session(db.engine) as session:
outputs = workflow_node_execution.load_full_outputs(session, storage)
with Session(bind=db.engine) as session, session.begin():
draft_var_saver = DraftVariableSaver(
session=session,
app_id=app_model.id,
node_id=workflow_node_execution.node_id,
node_type=NodeType(workflow_node_execution.node_type),
enclosing_node_id=enclosing_node_id,
node_execution_id=node_execution.id,
user=account,
)
draft_var_saver.save(process_data=node_execution.process_data, outputs=outputs)
session.commit()
return workflow_node_execution
def run_free_workflow_node(
self, node_data: dict, tenant_id: str, user_id: str, node_id: str, user_inputs: dict[str, Any]
) -> WorkflowNodeExecution:
"""
Run free workflow node
"""
# run free workflow node
start_at = time.perf_counter()
node_execution = self._handle_single_step_result(
invoke_node_fn=lambda: WorkflowEntry.run_free_node(
node_id=node_id,
node_data=node_data,
tenant_id=tenant_id,
user_id=user_id,
user_inputs=user_inputs,
),
start_at=start_at,
node_id=node_id,
)
return node_execution
def _handle_single_step_result(
self,
invoke_node_fn: Callable[[], tuple[Node, Generator[GraphNodeEventBase, None, None]]],
start_at: float,
node_id: str,
) -> WorkflowNodeExecution:
"""
Handle single step execution and return WorkflowNodeExecution.
Args:
invoke_node_fn: Function to invoke node execution
start_at: Execution start time
node_id: ID of the node being executed
Returns:
WorkflowNodeExecution: The execution result
"""
node, node_run_result, run_succeeded, error = self._execute_node_safely(invoke_node_fn)
# Create base node execution
node_execution = WorkflowNodeExecution(
id=str(uuid.uuid4()),
workflow_id="", # Single-step execution has no workflow ID
index=1,
node_id=node_id,
node_type=node.node_type,
title=node.title,
elapsed_time=time.perf_counter() - start_at,
created_at=naive_utc_now(),
finished_at=naive_utc_now(),
)
# Populate execution result data
self._populate_execution_result(node_execution, node_run_result, run_succeeded, error)
return node_execution
def _execute_node_safely(
self, invoke_node_fn: Callable[[], tuple[Node, Generator[GraphNodeEventBase, None, None]]]
) -> tuple[Node, NodeRunResult | None, bool, str | None]:
"""
Execute node safely and handle errors according to error strategy.
Returns:
Tuple of (node, node_run_result, run_succeeded, error)
"""
try:
node, node_events = invoke_node_fn()
node_run_result = next(
(
event.node_run_result
for event in node_events
if isinstance(event, (NodeRunSucceededEvent, NodeRunFailedEvent))
),
None,
)
if not node_run_result:
raise ValueError("Node execution failed - no result returned")
# Apply error strategy if node failed
if node_run_result.status == WorkflowNodeExecutionStatus.FAILED and node.error_strategy:
node_run_result = self._apply_error_strategy(node, node_run_result)
run_succeeded = node_run_result.status in (
WorkflowNodeExecutionStatus.SUCCEEDED,
WorkflowNodeExecutionStatus.EXCEPTION,
)
error = node_run_result.error if not run_succeeded else None
return node, node_run_result, run_succeeded, error
except WorkflowNodeRunFailedError as e:
node = e.node
run_succeeded = False
node_run_result = None
error = e.error
return node, node_run_result, run_succeeded, error
def _apply_error_strategy(self, node: Node, node_run_result: NodeRunResult) -> NodeRunResult:
"""Apply error strategy when node execution fails."""
# TODO(Novice): Maybe we should apply error strategy to node level?
error_outputs = {
"error_message": node_run_result.error,
"error_type": node_run_result.error_type,
}
# Add default values if strategy is DEFAULT_VALUE
if node.error_strategy is ErrorStrategy.DEFAULT_VALUE:
error_outputs.update(node.default_value_dict)
return NodeRunResult(
status=WorkflowNodeExecutionStatus.EXCEPTION,
error=node_run_result.error,
inputs=node_run_result.inputs,
metadata={WorkflowNodeExecutionMetadataKey.ERROR_STRATEGY: node.error_strategy},
outputs=error_outputs,
)
def _populate_execution_result(
self,
node_execution: WorkflowNodeExecution,
node_run_result: NodeRunResult | None,
run_succeeded: bool,
error: str | None,
) -> None:
"""Populate node execution with result data."""
if run_succeeded and node_run_result:
node_execution.inputs = (
WorkflowEntry.handle_special_values(node_run_result.inputs) if node_run_result.inputs else None
)
node_execution.process_data = (
WorkflowEntry.handle_special_values(node_run_result.process_data)
if node_run_result.process_data
else None
)
node_execution.outputs = node_run_result.outputs
node_execution.metadata = node_run_result.metadata
# Set status and error based on result
node_execution.status = node_run_result.status
if node_run_result.status == WorkflowNodeExecutionStatus.EXCEPTION:
node_execution.error = node_run_result.error
else:
node_execution.status = WorkflowNodeExecutionStatus.FAILED
node_execution.error = error
def convert_to_workflow(self, app_model: App, account: Account, args: dict) -> App:
"""
Basic mode of chatbot app(expert mode) to workflow
Completion App to Workflow App
:param app_model: App instance
:param account: Account instance
:param args: dict
:return:
"""
# chatbot convert to workflow mode
workflow_converter = WorkflowConverter()
if app_model.mode not in {AppMode.CHAT, AppMode.COMPLETION}:
raise ValueError(f"Current App mode: {app_model.mode} is not supported convert to workflow.")
# convert to workflow
new_app: App = workflow_converter.convert_to_workflow(
app_model=app_model,
account=account,
name=args.get("name", "Default Name"),
icon_type=args.get("icon_type", "emoji"),
icon=args.get("icon", "🤖"),
icon_background=args.get("icon_background", "#FFEAD5"),
)
return new_app
def validate_graph_structure(self, graph: Mapping[str, Any]):
"""
Validate workflow graph structure.
This performs a lightweight validation on the graph, checking for structural
inconsistencies such as the coexistence of start and trigger nodes.
"""
node_configs = graph.get("nodes", [])
node_configs = cast(list[dict[str, Any]], node_configs)
# is empty graph
if not node_configs:
return
node_types: set[NodeType] = set()
for node in node_configs:
node_type = node.get("data", {}).get("type")
if node_type:
node_types.add(NodeType(node_type))
# start node and trigger node cannot coexist
if NodeType.START in node_types:
if any(nt.is_trigger_node for nt in node_types):
raise ValueError("Start node and trigger nodes cannot coexist in the same workflow")
def validate_features_structure(self, app_model: App, features: dict):
if app_model.mode == AppMode.ADVANCED_CHAT:
return AdvancedChatAppConfigManager.config_validate(
tenant_id=app_model.tenant_id, config=features, only_structure_validate=True
)
elif app_model.mode == AppMode.WORKFLOW:
return WorkflowAppConfigManager.config_validate(
tenant_id=app_model.tenant_id, config=features, only_structure_validate=True
)
else:
raise ValueError(f"Invalid app mode: {app_model.mode}")
def update_workflow(
self, *, session: Session, workflow_id: str, tenant_id: str, account_id: str, data: dict
) -> Workflow | None:
"""
Update workflow attributes
:param session: SQLAlchemy database session
:param workflow_id: Workflow ID
:param tenant_id: Tenant ID
:param account_id: Account ID (for permission check)
:param data: Dictionary containing fields to update
:return: Updated workflow or None if not found
"""
stmt = select(Workflow).where(Workflow.id == workflow_id, Workflow.tenant_id == tenant_id)
workflow = session.scalar(stmt)
if not workflow:
return None
allowed_fields = ["marked_name", "marked_comment"]
for field, value in data.items():
if field in allowed_fields:
setattr(workflow, field, value)
workflow.updated_by = account_id
workflow.updated_at = naive_utc_now()
return workflow
def delete_workflow(self, *, session: Session, workflow_id: str, tenant_id: str) -> bool:
"""
Delete a workflow
:param session: SQLAlchemy database session
:param workflow_id: Workflow ID
:param tenant_id: Tenant ID
:return: True if successful
:raises: ValueError if workflow not found
:raises: WorkflowInUseError if workflow is in use
:raises: DraftWorkflowDeletionError if workflow is a draft version
"""
stmt = select(Workflow).where(Workflow.id == workflow_id, Workflow.tenant_id == tenant_id)
workflow = session.scalar(stmt)
if not workflow:
raise ValueError(f"Workflow with ID {workflow_id} not found")
# Check if workflow is a draft version
if workflow.version == Workflow.VERSION_DRAFT:
raise DraftWorkflowDeletionError("Cannot delete draft workflow versions")
# Check if this workflow is currently referenced by an app
app_stmt = select(App).where(App.workflow_id == workflow_id)
app = session.scalar(app_stmt)
if app:
# Cannot delete a workflow that's currently in use by an app
raise WorkflowInUseError(f"Cannot delete workflow that is currently in use by app '{app.id}'")
# Don't use workflow.tool_published as it's not accurate for specific workflow versions
# Check if there's a tool provider using this specific workflow version
tool_provider = (
session.query(WorkflowToolProvider)
.where(
WorkflowToolProvider.tenant_id == workflow.tenant_id,
WorkflowToolProvider.app_id == workflow.app_id,
WorkflowToolProvider.version == workflow.version,
)
.first()
)
if tool_provider:
# Cannot delete a workflow that's published as a tool
raise WorkflowInUseError("Cannot delete workflow that is published as a tool")
session.delete(workflow)
return True
def _setup_variable_pool(
query: str,
files: Sequence[File],
user_id: str,
user_inputs: Mapping[str, Any],
workflow: Workflow,
node_type: NodeType,
conversation_id: str,
conversation_variables: list[VariableBase],
):
# Only inject system variables for START node type.
if node_type == NodeType.START or node_type.is_trigger_node:
system_variable = SystemVariable(
user_id=user_id,
app_id=workflow.app_id,
timestamp=int(naive_utc_now().timestamp()),
workflow_id=workflow.id,
files=files or [],
workflow_execution_id=str(uuid.uuid4()),
)
# Only add chatflow-specific variables for non-workflow types
if workflow.type != WorkflowType.WORKFLOW:
system_variable.query = query
system_variable.conversation_id = conversation_id
system_variable.dialogue_count = 1
else:
system_variable = SystemVariable.empty()
# init variable pool
variable_pool = VariablePool(
system_variables=system_variable,
user_inputs=user_inputs,
environment_variables=workflow.environment_variables,
# Based on the definition of `Variable`,
# `VariableBase` instances can be safely used as `Variable` since they are compatible.
conversation_variables=cast(list[Variable], conversation_variables), #
)
return variable_pool
def _rebuild_file_for_user_inputs_in_start_node(
tenant_id: str, start_node_data: StartNodeData, user_inputs: Mapping[str, Any]
) -> Mapping[str, Any]:
inputs_copy = dict(user_inputs)
for variable in start_node_data.variables:
if variable.type not in (VariableEntityType.FILE, VariableEntityType.FILE_LIST):
continue
if variable.variable not in user_inputs:
continue
value = user_inputs[variable.variable]
file = _rebuild_single_file(tenant_id=tenant_id, value=value, variable_entity_type=variable.type)
inputs_copy[variable.variable] = file
return inputs_copy
def _rebuild_single_file(tenant_id: str, value: Any, variable_entity_type: VariableEntityType) -> File | Sequence[File]:
if variable_entity_type == VariableEntityType.FILE:
if not isinstance(value, dict):
raise ValueError(f"expected dict for file object, got {type(value)}")
return build_from_mapping(mapping=value, tenant_id=tenant_id)
elif variable_entity_type == VariableEntityType.FILE_LIST:
if not isinstance(value, list):
raise ValueError(f"expected list for file list object, got {type(value)}")
if len(value) == 0:
return []
if not isinstance(value[0], dict):
raise ValueError(f"expected dict for first element in the file list, got {type(value)}")
return build_from_mappings(mappings=value, tenant_id=tenant_id)
else:
raise Exception("unreachable")