fix:chatbot route now matches new datamodel interface

List endpoint (/api/chatbot/threads without workflowId): Normalizes all workflows before returning, converting maxSteps: None to 10 (the default).
Single workflow endpoint (/api/chatbot/threads?workflowId=xxx): Normalizes the workflow dict, handling both Pydantic models and plain dicts.
This commit is contained in:
Ida Dittrich 2026-01-14 08:24:06 +01:00
parent 013de9e220
commit 6f6ee25ef2
3 changed files with 62 additions and 19 deletions

View file

@ -109,7 +109,7 @@ class StreamingEventManager:
Args:
context_id: Context ID to stream events from
event_categories: Optional list of event categories to filter by
timeout: Optional timeout in seconds (None = no timeout)
timeout: Optional timeout in seconds (None = no timeout, default: 300s for long-running streams)
Yields:
Event dictionaries
@ -119,26 +119,30 @@ class StreamingEventManager:
logger.warning(f"No queue found for context {context_id}")
return
start_time = asyncio.get_event_loop().time() if timeout else None
# Default timeout of 5 minutes for long-running streams if not specified
effective_timeout = timeout if timeout is not None else 300.0
start_time = asyncio.get_event_loop().time()
last_event_time = start_time
heartbeat_interval = 30.0 # Send heartbeat every 30 seconds to keep connection alive
while True:
# Check timeout
if timeout and start_time:
elapsed = asyncio.get_event_loop().time() - start_time
if elapsed > timeout:
logger.debug(f"Stream timeout for context {context_id}")
break
elapsed = asyncio.get_event_loop().time() - start_time
if elapsed > effective_timeout:
logger.debug(f"Stream timeout for context {context_id} after {effective_timeout}s")
break
try:
# Wait for event with timeout
wait_timeout = 1.0 # Check timeout every second
if timeout and start_time:
remaining = timeout - (asyncio.get_event_loop().time() - start_time)
# Wait for event with longer timeout to avoid premature closure
wait_timeout = heartbeat_interval # Check every 30 seconds
if effective_timeout:
remaining = effective_timeout - elapsed
if remaining <= 0:
break
wait_timeout = min(wait_timeout, remaining)
event = await asyncio.wait_for(queue.get(), timeout=wait_timeout)
last_event_time = asyncio.get_event_loop().time()
# Filter by category if specified
if event_categories and event.get("category") not in event_categories:
@ -147,11 +151,25 @@ class StreamingEventManager:
yield event
except asyncio.TimeoutError:
# Send heartbeat to keep connection alive if no events
time_since_last_event = asyncio.get_event_loop().time() - last_event_time
if time_since_last_event >= heartbeat_interval:
# Send heartbeat event to keep stream alive
heartbeat_event = {
"type": "heartbeat",
"category": "system",
"timestamp": datetime.now().timestamp(),
"data": {"status": "alive"},
"message": None,
"step": None
}
yield heartbeat_event
last_event_time = asyncio.get_event_loop().time()
# Check if we should continue or timeout
if timeout and start_time:
elapsed = asyncio.get_event_loop().time() - start_time
if elapsed >= timeout:
break
elapsed = asyncio.get_event_loop().time() - start_time
if elapsed >= effective_timeout:
break
continue
except Exception as e:
logger.error(f"Error in stream_events for context {context_id}: {e}")

View file

@ -1521,8 +1521,8 @@ async def _processChatbotMessage(
step="complete"
)
# Schedule cleanup
await event_manager.cleanup(workflowId)
# Schedule cleanup with longer delay to allow stream to stay open
await event_manager.cleanup(workflowId, delay=300.0) # 5 minutes delay
except Exception as e:
logger.error(f"Error processing chatbot message: {str(e)}", exc_info=True)

View file

@ -357,11 +357,26 @@ async def get_chatbot_threads(
detail=f"Workflow with ID {workflowId} not found"
)
# Normalize workflow data to match ChatWorkflow model requirements
# Convert workflow object to dict if needed, and normalize None values
if hasattr(workflow, 'model_dump'):
workflow_dict = workflow.model_dump()
elif hasattr(workflow, 'dict'):
workflow_dict = workflow.dict()
elif isinstance(workflow, dict):
workflow_dict = dict(workflow)
else:
workflow_dict = workflow
# Set maxSteps to default value of 10 if None (as per ChatWorkflow model)
if workflow_dict.get("maxSteps") is None:
workflow_dict["maxSteps"] = 10
# Get unified chat data for this workflow
chatData = interfaceDbChat.getUnifiedChatData(workflowId, None)
return {
"workflow": workflow,
"workflow": workflow_dict,
"chatData": chatData
}
@ -407,6 +422,16 @@ async def get_chatbot_threads(
totalItems = len(chatbot_workflows_data)
totalPages = 1
# Normalize workflow data to match ChatWorkflow model requirements
# Convert None values to defaults before response validation
normalized_workflows = []
for wf in workflows:
normalized_wf = dict(wf) # Create a copy
# Set maxSteps to default value of 10 if None (as per ChatWorkflow model)
if normalized_wf.get("maxSteps") is None:
normalized_wf["maxSteps"] = 10
normalized_workflows.append(normalized_wf)
# Create paginated response
from modules.datamodels.datamodelPagination import PaginationMetadata
metadata = PaginationMetadata(
@ -419,7 +444,7 @@ async def get_chatbot_threads(
)
return PaginatedResponse(
items=workflows,
items=normalized_workflows,
pagination=metadata
)