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## Thinking Path > - Paperclip is the open source app people use to manage AI agents for work > - A core part of that experience is watching active agent runs without dropping into raw logs first > - Local and sandbox-backed adapters already record useful run output, progress, and tool activity > - But active issue threads could sit visually stale while the agent was syncing workspaces, tailing sandbox output, or emitting incremental tool-call updates > - Operators need timely, human-readable progress while preserving the raw transcript underneath > - This pull request streams sandbox run-log progress into runtime status, keeps visible issue threads refreshed, and folds repeated ACPX tool updates into stable transcript cards > - The benefit is that long-running agent work becomes easier to supervise without changing the task/comment control-plane model ## Linked Issues or Issue Description No public GitHub issue exists for this exact change. Problem/motivation: - During long-running sandboxed agent work, the issue UI can appear idle even though the agent is actively syncing, running tools, or producing incremental output. - Operators need realtime feedback at the issue-thread layer, not only after opening raw logs or waiting for the final heartbeat result. - Related public context: #1808 previously added live-run status dots to Projects; #4362 touches heartbeat wakeup behavior but is not a duplicate of this runtime/UI feedback change. ## What Changed - Added sandbox run-log streaming support and defaulted sandbox-capable local adapters into the richer live-feedback path. - Surfaced environment/sandbox sync progress through heartbeat runtime status with bounded, redacted snippets. - Added live issue-thread cache patching so visible active runs update as progress events arrive. - Folded repeated ACPX `tool_call` updates into one transcript card instead of stacking duplicate cards. - Updated adapter docs and added focused regression coverage for sandbox log streaming, runtime status, ACPX parsing, live updates, transcript rendering, and issue chat messages. ## Verification - `pnpm install --frozen-lockfile` - `pnpm exec vitest run ui/src/context/LiveUpdatesProvider.test.ts` - `pnpm exec vitest run server/src/services/heartbeat-run-runtime-status.test.ts server/src/__tests__/heartbeat-runtime-state.test.ts ui/src/context/LiveUpdatesProvider.test.ts` - `pnpm exec vitest run packages/adapter-utils/src/execution-target-sandbox.test.ts packages/adapter-utils/src/sandbox-managed-runtime.test.ts server/src/services/heartbeat-run-runtime-status.test.ts server/src/__tests__/agent-live-run-routes.test.ts server/src/__tests__/heartbeat-runtime-state.test.ts packages/adapters/acpx-local/src/ui/parse-stdout.test.ts ui/src/context/LiveUpdatesProvider.test.ts ui/src/components/transcript/RunTranscriptView.test.tsx ui/src/lib/issue-chat-messages.test.ts ui/src/components/IssueChatThread.test.tsx` - GitHub PR workflow on head `8397953e7b41ccd42e5d9457ee7e4dfb996e4ec5`: `verify`, build, typecheck/release-registry, e2e, general shards, serialized server shards, and canary dry run passed. - Greptile Review on head `8397953e7b41ccd42e5d9457ee7e4dfb996e4ec5`: Confidence Score 5/5, no unresolved review threads. ## Risks - Live issue-thread cache patching could miss an edge case for a route shape not covered by tests. - Surfacing active-run snippets needs continued care around redaction; this PR keeps snippets bounded and adds redaction-focused coverage. - More frequent active-run UI refreshes could expose performance issues on very large issue threads, though updates are scoped to visible run/query caches. ## Model Used OpenAI GPT-5 via Codex, operating as a tool-enabled coding agent with shell, git, and repository-editing capabilities. Context window size is not exposed in this runtime. ## Checklist - [x] I have included a thinking path that traces from project context to this change - [x] I have specified the model used (with version and capability details) - [x] I have checked ROADMAP.md and confirmed this PR does not duplicate planned core work - [x] I have searched GitHub for duplicate or related PRs and linked them above - [x] I have either (a) linked existing issues with `Fixes: #` / `Closes #` / `Refs #` OR (b) described the issue in-PR following the relevant issue template - [x] I have not referenced internal/instance-local Paperclip issues or links (only public GitHub `#NNN` / `github.com/paperclipai/paperclip` URLs) - [x] My branch name describes the change (e.g. `docs/...`, `fix/...`) and contains no internal Paperclip ticket id or instance-derived details - [x] I have run tests locally and they pass - [x] I have added or updated tests where applicable - [x] I have updated relevant documentation to reflect my changes - [x] I have considered and documented any risks above - [x] All Paperclip CI gates are green - [x] Greptile is 5/5 with no open P2s, recommendations, or follow-ups - [x] I will address all Greptile and reviewer comments before requesting merge Co-authored-by: Paperclip <noreply@paperclip.ing>
140 lines
5.2 KiB
TypeScript
140 lines
5.2 KiB
TypeScript
import type {
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HeartbeatRun,
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HeartbeatRunEvent,
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InstanceSchedulerHeartbeatAgent,
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WorkspaceOperation,
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} from "@paperclipai/shared";
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import { api } from "./client";
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export interface RunLivenessFields {
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livenessState: HeartbeatRun["livenessState"];
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livenessReason: string | null;
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continuationAttempt: number;
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lastUsefulActionAt: string | Date | null;
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nextAction: string | null;
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}
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export interface ActiveRunForIssue {
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id: string;
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status: string;
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invocationSource: string;
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triggerDetail: string | null;
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contextCommentId?: string | null;
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contextWakeCommentId?: string | null;
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startedAt: string | Date | null;
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finishedAt: string | Date | null;
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createdAt: string | Date;
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agentId: string;
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agentName: string;
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adapterType: string;
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logBytes?: number | null;
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lastOutputBytes?: number | null;
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issueId?: string | null;
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livenessState?: RunLivenessFields["livenessState"];
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livenessReason?: string | null;
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continuationAttempt?: number;
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lastUsefulActionAt?: string | Date | null;
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nextAction?: string | null;
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outputSilence?: HeartbeatRun["outputSilence"];
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currentStatusMessage?: string | null;
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currentStatusUpdatedAt?: string | Date | null;
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currentToolName?: string | null;
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lastAssistantSnippet?: string | null;
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lastEventAt?: string | Date | null;
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}
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export interface LiveRunForIssue {
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id: string;
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status: string;
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invocationSource: string;
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triggerDetail: string | null;
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contextCommentId?: string | null;
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contextWakeCommentId?: string | null;
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startedAt: string | null;
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finishedAt: string | null;
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createdAt: string;
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agentId: string;
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agentName: string;
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adapterType: string;
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logBytes?: number | null;
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lastOutputBytes?: number | null;
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issueId?: string | null;
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livenessState?: RunLivenessFields["livenessState"];
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livenessReason?: string | null;
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continuationAttempt?: number;
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lastUsefulActionAt?: string | null;
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nextAction?: string | null;
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outputSilence?: HeartbeatRun["outputSilence"];
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currentStatusMessage?: string | null;
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currentStatusUpdatedAt?: string | null;
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currentToolName?: string | null;
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lastAssistantSnippet?: string | null;
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lastEventAt?: string | null;
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}
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export interface WatchdogDecisionInput {
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runId: string;
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decision: "snooze" | "continue" | "dismissed_false_positive";
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evaluationIssueId?: string | null;
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reason?: string | null;
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snoozedUntil?: string | null;
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}
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export interface HeartbeatRunListOptions {
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summary?: boolean;
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}
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export const heartbeatsApi = {
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list: (companyId: string, agentId?: string, limit?: number, options: HeartbeatRunListOptions = {}) => {
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const searchParams = new URLSearchParams();
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if (agentId) searchParams.set("agentId", agentId);
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if (limit) searchParams.set("limit", String(limit));
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if (options.summary) searchParams.set("summary", "true");
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const qs = searchParams.toString();
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return api.get<HeartbeatRun[]>(`/companies/${companyId}/heartbeat-runs${qs ? `?${qs}` : ""}`);
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},
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get: (runId: string) => api.get<HeartbeatRun>(`/heartbeat-runs/${runId}`),
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events: (runId: string, afterSeq = 0, limit = 200) =>
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api.get<HeartbeatRunEvent[]>(
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`/heartbeat-runs/${runId}/events?afterSeq=${encodeURIComponent(String(afterSeq))}&limit=${encodeURIComponent(String(limit))}`,
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),
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log: (runId: string, offset = 0, limitBytes = 256000) =>
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api.get<{ runId: string; store: string; logRef: string; content: string; nextOffset?: number }>(
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`/heartbeat-runs/${runId}/log?offset=${encodeURIComponent(String(offset))}&limitBytes=${encodeURIComponent(String(limitBytes))}`,
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),
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workspaceOperations: (runId: string) =>
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api.get<WorkspaceOperation[]>(`/heartbeat-runs/${runId}/workspace-operations`),
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workspaceOperationLog: (operationId: string, offset = 0, limitBytes = 256000) =>
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api.get<{ operationId: string; store: string; logRef: string; content: string; nextOffset?: number }>(
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`/workspace-operations/${operationId}/log?offset=${encodeURIComponent(String(offset))}&limitBytes=${encodeURIComponent(String(limitBytes))}`,
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),
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cancel: (runId: string) => api.post<void>(`/heartbeat-runs/${runId}/cancel`, {}),
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recordWatchdogDecision: (input: WatchdogDecisionInput) =>
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api.post(`/heartbeat-runs/${input.runId}/watchdog-decisions`, {
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decision: input.decision,
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evaluationIssueId: input.evaluationIssueId ?? null,
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reason: input.reason ?? null,
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snoozedUntil: input.snoozedUntil ?? null,
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}),
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liveRunsForIssue: (issueId: string) =>
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api.get<LiveRunForIssue[]>(`/issues/${issueId}/live-runs`),
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activeRunForIssue: (issueId: string) =>
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api.get<ActiveRunForIssue | null>(`/issues/${issueId}/active-run`),
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liveRunsForCompany: (
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companyId: string,
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options?: number | { minCount?: number; limit?: number },
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) => {
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const searchParams = new URLSearchParams();
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if (typeof options === "number") {
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searchParams.set("minCount", String(options));
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} else if (options) {
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if (options.minCount) searchParams.set("minCount", String(options.minCount));
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if (options.limit) searchParams.set("limit", String(options.limit));
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}
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const qs = searchParams.toString();
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return api.get<LiveRunForIssue[]>(`/companies/${companyId}/live-runs${qs ? `?${qs}` : ""}`);
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},
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listInstanceSchedulerAgents: () =>
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api.get<InstanceSchedulerHeartbeatAgent[]>("/instance/scheduler-heartbeats"),
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};
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