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Python: DevUI Fix Serialization, Timestamp and Other Issues (#1584)
* refactor(devui): adopt standard OpenAI lifecycle events for agents and workflows - Replace custom workflow events with OpenAI Responses API standard lifecycle events - Add AgentStartedEvent, AgentCompletedEvent, AgentFailedEvent for clean separation - Implement ExecutorActionItem for workflow executor tracking - Convert informational events to trace events to reduce noise - Update README mapper table with comprehensive event mappings - Maintain full backward compatibility with legacy events * fix(devui): resolve timestamp overwriting and Content serialization errors - Fix tool call timestamps being overwritten on each render (#1483) - Add recursive Content serialization to handle ChatMessage and nested objects (#1548) - Implement proper MCP tool cleanup on server shutdown - Add timestamp field to function_result.complete events - Enhance credential and client resource cleanup Fixes #1483, #1548 Partial improvements for #1476
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Victor Dibia
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@@ -408,46 +408,82 @@ export function WorkflowView({
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// This preserves the workflow's final output for display
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};
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// Extract workflow events from OpenAI events for executor tracking
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// Extract workflow and output item events from OpenAI events for executor tracking
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const workflowEvents = useMemo(() => {
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return openAIEvents.filter(
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(event) => event.type === "response.workflow_event.complete"
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(event) =>
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event.type === "response.output_item.added" ||
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event.type === "response.output_item.done" ||
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event.type === "response.created" ||
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event.type === "response.in_progress" ||
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event.type === "response.completed" ||
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event.type === "response.failed" ||
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// Keep legacy support for older backends
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event.type === "response.workflow_event.complete"
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);
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}, [openAIEvents]);
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// Extract executor history from workflow events (filter out workflow-level events)
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const executorHistory = useMemo(() => {
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return workflowEvents
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.filter((event) => {
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if ("data" in event && event.data && typeof event.data === "object") {
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const data = event.data as Record<string, unknown>;
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// Filter out workflow-level events (those without executor_id)
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// These include: WorkflowStartedEvent, WorkflowOutputEvent, WorkflowStatusEvent, etc.
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return data.executor_id != null;
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const history: Array<{
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executorId: string;
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message: string;
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timestamp: string;
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status: "running" | "completed" | "error";
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}> = [];
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workflowEvents.forEach((event) => {
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// Handle new standard OpenAI events
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if (
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event.type === "response.output_item.added" ||
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event.type === "response.output_item.done"
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) {
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const item = (event as any).item;
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if (item && item.type === "executor_action" && item.executor_id) {
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history.push({
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executorId: item.executor_id,
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message:
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event.type === "response.output_item.added"
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? "Executor started"
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: item.status === "completed"
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? "Executor completed"
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: item.status === "failed"
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? "Executor failed"
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: "Executor processing",
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timestamp: new Date().toISOString(),
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status:
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item.status === "completed"
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? "completed"
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: item.status === "failed"
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? "error"
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: "running",
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});
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}
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return false;
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})
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.map((event) => {
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if ("data" in event && event.data && typeof event.data === "object") {
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const data = event.data as Record<string, unknown>;
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return {
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}
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// Legacy support for older backends
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else if (
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event.type === "response.workflow_event.complete" &&
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"data" in event &&
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event.data &&
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typeof event.data === "object"
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) {
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const data = event.data as Record<string, unknown>;
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if (data.executor_id != null) {
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history.push({
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executorId: String(data.executor_id),
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message: String(data.event_type || "Processing"),
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timestamp: String(data.timestamp || new Date().toISOString()),
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status: String(data.event_type || "").includes("Completed")
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? ("completed" as const)
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? "completed"
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: String(data.event_type || "").includes("Error")
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? ("error" as const)
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: ("running" as const),
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};
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? "error"
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: "running",
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});
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}
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return {
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executorId: "unknown",
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message: "Processing",
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timestamp: new Date().toISOString(),
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status: "running" as const,
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};
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});
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}
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});
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return history;
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}, [workflowEvents]);
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// Track active executors
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@@ -525,16 +561,51 @@ export function WorkflowView({
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);
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for await (const openAIEvent of streamGenerator) {
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// Only store workflow events in state for performance
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// Text deltas are processed directly without state updates
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if (openAIEvent.type === "response.workflow_event.complete") {
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// Store workflow-related events for tracking
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if (
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openAIEvent.type === "response.output_item.added" ||
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openAIEvent.type === "response.output_item.done" ||
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openAIEvent.type === "response.created" ||
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openAIEvent.type === "response.in_progress" ||
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openAIEvent.type === "response.completed" ||
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openAIEvent.type === "response.failed" ||
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openAIEvent.type === "response.workflow_event.complete" // Legacy
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) {
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setOpenAIEvents((prev) => [...prev, openAIEvent]);
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}
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// Pass to debug panel
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onDebugEvent(openAIEvent);
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// Handle workflow events to track current executor
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// Handle new standard OpenAI events
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if (openAIEvent.type === "response.output_item.added") {
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const item = (openAIEvent as any).item;
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if (item && item.type === "executor_action" && item.executor_id) {
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currentStreamingExecutor.current = item.executor_id;
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// Initialize output for this executor if not exists
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if (!executorOutputs.current[item.executor_id]) {
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executorOutputs.current[item.executor_id] = "";
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}
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}
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}
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// Handle workflow completion
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if (openAIEvent.type === "response.completed") {
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// Workflow completed successfully
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// Final output is already in workflowResult from text streaming
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}
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// Handle workflow failure
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if (openAIEvent.type === "response.failed") {
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const error = (openAIEvent as any).response?.error;
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if (error) {
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setWorkflowError(
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typeof error === "string" ? error : JSON.stringify(error)
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);
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}
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}
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// Legacy support for older backends
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if (
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openAIEvent.type === "response.workflow_event.complete" &&
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"data" in openAIEvent &&
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