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refactor(services): convert AppMode if/elif to match/case in generate and app service (#30001) #3

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refactor(services): convert AppMode if/elif to match/case in generate and app service (#30001) #3

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refactor(services): convert AppMode if/elif to match/case in generate…
agenthaulk Apr 5, 2026
b20664e
[autofix.ci] apply automated fixes
autofix-ci[bot] Apr 5, 2026
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312 changes: 173 additions & 139 deletions api/services/app_generate_service.py
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Original file line number Diff line number Diff line change
Expand Up @@ -116,139 +116,143 @@ def generate(
request_id = RateLimit.gen_request_key()
try:
request_id = rate_limit.enter(request_id)
if app_model.mode == AppMode.COMPLETION:
return rate_limit.generate(
CompletionAppGenerator.convert_to_event_stream(
CompletionAppGenerator().generate(
app_model=app_model, user=user, args=args, invoke_from=invoke_from, streaming=streaming
),
),
request_id=request_id,
)
elif app_model.mode == AppMode.AGENT_CHAT or app_model.is_agent:
return rate_limit.generate(
AgentChatAppGenerator.convert_to_event_stream(
AgentChatAppGenerator().generate(
app_model=app_model, user=user, args=args, invoke_from=invoke_from, streaming=streaming
effective_mode = (
AppMode.AGENT_CHAT if app_model.is_agent and app_model.mode != AppMode.AGENT_CHAT else app_model.mode
)
Comment on lines +119 to +121
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@chatgpt-codex-connector chatgpt-codex-connector Bot Apr 5, 2026

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P2 Badge Preserve mode short-circuit before evaluating is_agent

effective_mode now calls app_model.is_agent before dispatching on app_model.mode. That property is not a cheap flag read: it loads app_model_config from the DB and may even commit self.mode = AppMode.AGENT_CHAT. In the previous if/elif chain, COMPLETION and AGENT_CHAT requests short-circuited before touching is_agent, so this refactor adds avoidable DB I/O (and potential side effects) on hot paths. Dispatch should first branch on app_model.mode and only consult is_agent in the CHAT compatibility path.

Useful? React with 👍 / 👎.

match effective_mode:
case AppMode.COMPLETION:
return rate_limit.generate(
CompletionAppGenerator.convert_to_event_stream(
CompletionAppGenerator().generate(
app_model=app_model, user=user, args=args, invoke_from=invoke_from, streaming=streaming
),
),
),
request_id,
)
elif app_model.mode == AppMode.CHAT:
return rate_limit.generate(
ChatAppGenerator.convert_to_event_stream(
ChatAppGenerator().generate(
app_model=app_model, user=user, args=args, invoke_from=invoke_from, streaming=streaming
request_id=request_id,
)
case AppMode.AGENT_CHAT:
return rate_limit.generate(
AgentChatAppGenerator.convert_to_event_stream(
AgentChatAppGenerator().generate(
app_model=app_model, user=user, args=args, invoke_from=invoke_from, streaming=streaming
),
),
),
request_id=request_id,
)
elif app_model.mode == AppMode.ADVANCED_CHAT:
workflow_id = args.get("workflow_id")
workflow = cls._get_workflow(app_model, invoke_from, workflow_id)

if streaming:
# Streaming mode: subscribe to SSE and enqueue the execution on first subscriber
with rate_limit_context(rate_limit, request_id):
payload = AppExecutionParams.new(
app_model=app_model,
workflow=workflow,
user=user,
args=args,
invoke_from=invoke_from,
streaming=True,
call_depth=0,
)
payload_json = payload.model_dump_json()

def on_subscribe():
workflow_based_app_execution_task.delay(payload_json)

on_subscribe = cls._build_streaming_task_on_subscribe(on_subscribe)
generator = AdvancedChatAppGenerator()
request_id,
)
case AppMode.CHAT:
return rate_limit.generate(
generator.convert_to_event_stream(
generator.retrieve_events(
AppMode.ADVANCED_CHAT,
payload.workflow_run_id,
on_subscribe=on_subscribe,
ChatAppGenerator.convert_to_event_stream(
ChatAppGenerator().generate(
app_model=app_model, user=user, args=args, invoke_from=invoke_from, streaming=streaming
),
),
request_id=request_id,
)
else:
# Blocking mode: run synchronously and return JSON instead of SSE
# Keep behaviour consistent with WORKFLOW blocking branch.
advanced_generator = AdvancedChatAppGenerator()
return rate_limit.generate(
advanced_generator.convert_to_event_stream(
advanced_generator.generate(
case AppMode.ADVANCED_CHAT:
workflow_id = args.get("workflow_id")
workflow = cls._get_workflow(app_model, invoke_from, workflow_id)

if streaming:
# Streaming mode: subscribe to SSE and enqueue the execution on first subscriber
with rate_limit_context(rate_limit, request_id):
payload = AppExecutionParams.new(
app_model=app_model,
workflow=workflow,
user=user,
args=args,
invoke_from=invoke_from,
streaming=True,
call_depth=0,
)
payload_json = payload.model_dump_json()

def on_subscribe():
workflow_based_app_execution_task.delay(payload_json)

on_subscribe = cls._build_streaming_task_on_subscribe(on_subscribe)
generator = AdvancedChatAppGenerator()
return rate_limit.generate(
generator.convert_to_event_stream(
generator.retrieve_events(
AppMode.ADVANCED_CHAT,
payload.workflow_run_id,
on_subscribe=on_subscribe,
),
),
request_id=request_id,
)
else:
# Blocking mode: run synchronously and return JSON instead of SSE
# Keep behaviour consistent with WORKFLOW blocking branch.
advanced_generator = AdvancedChatAppGenerator()
return rate_limit.generate(
advanced_generator.convert_to_event_stream(
advanced_generator.generate(
app_model=app_model,
workflow=workflow,
user=user,
args=args,
invoke_from=invoke_from,
workflow_run_id=str(uuid.uuid4()),
streaming=False,
)
),
request_id=request_id,
)
case AppMode.WORKFLOW:
workflow_id = args.get("workflow_id")
workflow = cls._get_workflow(app_model, invoke_from, workflow_id)
if streaming:
with rate_limit_context(rate_limit, request_id):
payload = AppExecutionParams.new(
app_model=app_model,
workflow=workflow,
user=user,
args=args,
invoke_from=invoke_from,
streaming=True,
call_depth=0,
root_node_id=root_node_id,
workflow_run_id=str(uuid.uuid4()),
streaming=False,
)
),
request_id=request_id,
)
elif app_model.mode == AppMode.WORKFLOW:
workflow_id = args.get("workflow_id")
workflow = cls._get_workflow(app_model, invoke_from, workflow_id)
if streaming:
with rate_limit_context(rate_limit, request_id):
payload = AppExecutionParams.new(
app_model=app_model,
workflow=workflow,
user=user,
args=args,
invoke_from=invoke_from,
streaming=True,
call_depth=0,
root_node_id=root_node_id,
workflow_run_id=str(uuid.uuid4()),
payload_json = payload.model_dump_json()

def on_subscribe():
workflow_based_app_execution_task.delay(payload_json)

on_subscribe = cls._build_streaming_task_on_subscribe(on_subscribe)
return rate_limit.generate(
WorkflowAppGenerator.convert_to_event_stream(
MessageBasedAppGenerator.retrieve_events(
AppMode.WORKFLOW,
payload.workflow_run_id,
on_subscribe=on_subscribe,
),
),
request_id,
)
payload_json = payload.model_dump_json()

def on_subscribe():
workflow_based_app_execution_task.delay(payload_json)

on_subscribe = cls._build_streaming_task_on_subscribe(on_subscribe)
pause_config = PauseStateLayerConfig(
session_factory=session_factory.get_session_maker(),
state_owner_user_id=workflow.created_by,
)
return rate_limit.generate(
WorkflowAppGenerator.convert_to_event_stream(
MessageBasedAppGenerator.retrieve_events(
AppMode.WORKFLOW,
payload.workflow_run_id,
on_subscribe=on_subscribe,
WorkflowAppGenerator().generate(
app_model=app_model,
workflow=workflow,
user=user,
args=args,
invoke_from=invoke_from,
streaming=False,
root_node_id=root_node_id,
call_depth=0,
pause_state_config=pause_config,
),
),
request_id,
)

pause_config = PauseStateLayerConfig(
session_factory=session_factory.get_session_maker(),
state_owner_user_id=workflow.created_by,
)
return rate_limit.generate(
WorkflowAppGenerator.convert_to_event_stream(
WorkflowAppGenerator().generate(
app_model=app_model,
workflow=workflow,
user=user,
args=args,
invoke_from=invoke_from,
streaming=False,
root_node_id=root_node_id,
call_depth=0,
pause_state_config=pause_config,
),
),
request_id,
)
else:
raise ValueError(f"Invalid app mode {app_model.mode}")
case _:
raise ValueError(f"Invalid app mode {app_model.mode}")
except Exception:
quota_charge.refund()
rate_limit.exit(request_id)
Expand Down Expand Up @@ -280,43 +284,73 @@ def _get_max_active_requests(app: App) -> int:

@classmethod
def generate_single_iteration(cls, app_model: App, user: Account, node_id: str, args: Any, streaming: bool = True):
if app_model.mode == AppMode.ADVANCED_CHAT:
workflow = cls._get_workflow(app_model, InvokeFrom.DEBUGGER)
return AdvancedChatAppGenerator.convert_to_event_stream(
AdvancedChatAppGenerator().single_iteration_generate(
app_model=app_model, workflow=workflow, node_id=node_id, user=user, args=args, streaming=streaming
match app_model.mode:
case AppMode.COMPLETION | AppMode.CHAT | AppMode.AGENT_CHAT:
raise ValueError(f"Invalid app mode {app_model.mode}")
case AppMode.ADVANCED_CHAT:
workflow = cls._get_workflow(app_model, InvokeFrom.DEBUGGER)
return AdvancedChatAppGenerator.convert_to_event_stream(
AdvancedChatAppGenerator().single_iteration_generate(
app_model=app_model,
workflow=workflow,
node_id=node_id,
user=user,
args=args,
streaming=streaming,
)
)
)
elif app_model.mode == AppMode.WORKFLOW:
workflow = cls._get_workflow(app_model, InvokeFrom.DEBUGGER)
return AdvancedChatAppGenerator.convert_to_event_stream(
WorkflowAppGenerator().single_iteration_generate(
app_model=app_model, workflow=workflow, node_id=node_id, user=user, args=args, streaming=streaming
case AppMode.WORKFLOW:
workflow = cls._get_workflow(app_model, InvokeFrom.DEBUGGER)
return AdvancedChatAppGenerator.convert_to_event_stream(
WorkflowAppGenerator().single_iteration_generate(
app_model=app_model,
workflow=workflow,
node_id=node_id,
user=user,
args=args,
streaming=streaming,
)
)
)
else:
raise ValueError(f"Invalid app mode {app_model.mode}")
case AppMode.CHANNEL | AppMode.RAG_PIPELINE:
raise ValueError(f"Invalid app mode {app_model.mode}")
case _:
raise ValueError(f"Invalid app mode {app_model.mode}")

@classmethod
def generate_single_loop(
cls, app_model: App, user: Account, node_id: str, args: LoopNodeRunPayload, streaming: bool = True
):
if app_model.mode == AppMode.ADVANCED_CHAT:
workflow = cls._get_workflow(app_model, InvokeFrom.DEBUGGER)
return AdvancedChatAppGenerator.convert_to_event_stream(
AdvancedChatAppGenerator().single_loop_generate(
app_model=app_model, workflow=workflow, node_id=node_id, user=user, args=args, streaming=streaming
match app_model.mode:
case AppMode.COMPLETION | AppMode.CHAT | AppMode.AGENT_CHAT:
raise ValueError(f"Invalid app mode {app_model.mode}")
case AppMode.ADVANCED_CHAT:
workflow = cls._get_workflow(app_model, InvokeFrom.DEBUGGER)
return AdvancedChatAppGenerator.convert_to_event_stream(
AdvancedChatAppGenerator().single_loop_generate(
app_model=app_model,
workflow=workflow,
node_id=node_id,
user=user,
args=args,
streaming=streaming,
)
)
)
elif app_model.mode == AppMode.WORKFLOW:
workflow = cls._get_workflow(app_model, InvokeFrom.DEBUGGER)
return AdvancedChatAppGenerator.convert_to_event_stream(
WorkflowAppGenerator().single_loop_generate(
app_model=app_model, workflow=workflow, node_id=node_id, user=user, args=args, streaming=streaming
case AppMode.WORKFLOW:
workflow = cls._get_workflow(app_model, InvokeFrom.DEBUGGER)
return AdvancedChatAppGenerator.convert_to_event_stream(
WorkflowAppGenerator().single_loop_generate(
app_model=app_model,
workflow=workflow,
node_id=node_id,
user=user,
args=args,
streaming=streaming,
)
)
)
else:
raise ValueError(f"Invalid app mode {app_model.mode}")
case AppMode.CHANNEL | AppMode.RAG_PIPELINE:
raise ValueError(f"Invalid app mode {app_model.mode}")
case _:
raise ValueError(f"Invalid app mode {app_model.mode}")

@classmethod
def generate_more_like_this(
Expand Down
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