## 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>
6.9 KiB
title, summary
| title | summary |
|---|---|
| Adapters Overview | What adapters are and how they connect agents to Paperclip |
Adapters are the bridge between Paperclip's orchestration layer and agent runtimes. Each adapter knows how to invoke a specific type of AI agent and capture its results.
How Adapters Work
When a heartbeat fires, Paperclip:
- Looks up the agent's
adapterTypeandadapterConfig - Calls the adapter's
execute()function with the execution context - The adapter spawns or calls the agent runtime
- The adapter captures stdout, parses usage/cost data, and returns a structured result
Built-in Adapters
| Adapter | Type Key | Description |
|---|---|---|
| Claude Code | claude_local |
Runs Claude Code CLI locally |
| Codex | codex_local |
Runs OpenAI Codex CLI locally |
| ACPX Local | acpx_local |
Runs Claude, Codex, or a custom ACP agent through ACPX with live structured event streaming |
| Gemini CLI | gemini_local |
Runs Gemini CLI locally (experimental — adapter package exists, not yet in stable type enum) |
| OpenCode | opencode_local |
Runs OpenCode CLI locally (multi-provider provider/model) |
| Cursor | cursor |
Runs Cursor in background mode |
| Pi | pi_local |
Runs an embedded Pi agent locally |
| Hermes | hermes_local |
Runs the local Hermes CLI through @paperclipai/hermes-paperclip-adapter |
| Hermes Gateway | hermes_gateway |
Calls an already-running Hermes API server through @paperclipai/hermes-paperclip-adapter/gateway |
| OpenClaw Gateway | openclaw_gateway |
Connects to an OpenClaw gateway endpoint |
| Process | process |
Executes arbitrary shell commands |
| HTTP | http |
Sends webhooks to external agents |
Hermes local vs gateway
Use hermes_local when Paperclip should start the local hermes CLI on the
same host for each heartbeat. Use hermes_gateway when Hermes is already
running as an HTTP/SSE API server and Paperclip should call that server instead
of spawning a process. Both type keys are stable built-ins.
The unified Hermes package owns both built-in adapters. The older
@paperclipai/adapter-hermes-gateway package remains only as a deprecated
compatibility shim that re-exports the gateway entrypoints for one release.
New plugin overrides should target @paperclipai/hermes-paperclip-adapter and
set the desired type key (hermes_local or hermes_gateway).
External (plugin) adapters
These adapters ship as standalone npm packages and are installed via the plugin system:
| Adapter | Package | Type Key | Description |
|---|---|---|---|
| Droid | @henkey/droid-paperclip-adapter |
droid_local |
Runs Factory Droid locally |
External Adapters
You can build and distribute adapters as standalone packages — no changes to Paperclip's source code required. External adapters are loaded at startup via the plugin system.
# Install from npm via API
curl -X POST http://localhost:3102/api/adapters \
-d '{"packageName": "my-paperclip-adapter"}'
# Or link from a local directory
curl -X POST http://localhost:3102/api/adapters \
-d '{"localPath": "/home/user/my-adapter"}'
See External Adapters for the full guide.
Adapter Architecture
Each adapter is a package with modules consumed by three registries:
my-adapter/
src/
index.ts # Shared metadata (type, label, models)
server/
execute.ts # Core execution logic
parse.ts # Output parsing
test.ts # Environment diagnostics
ui-parser.ts # Self-contained UI transcript parser (for external adapters)
cli/
format-event.ts # Terminal output for `paperclipai run --watch`
| Registry | What it does | Source |
|---|---|---|
| Server | Executes agents, captures results | createServerAdapter() from package root |
| UI | Renders run transcripts, provides config forms | ui-parser.js (dynamic) or static import (built-in) |
| CLI | Formats terminal output for live watching | Static import |
Choosing an Adapter
- Need a coding agent? Use
claude_local,codex_local,acpx_local,opencode_local,hermes_local, or installdroid_localas an external plugin - Need the richest live run feedback (especially for sandbox workers)? Use
acpx_local— see Feedback granularity - Need Hermes on another host or already running as a service? Use
hermes_gateway - Need to run a script or command? Use
process - Need to call a custom external service? Use
http - Need something custom? Create your own adapter or build an external adapter plugin
Feedback Granularity
Adapter choice determines how much structured, live detail a run's transcript can show while the agent is still working. Every adapter's stdout is streamed to the run log and rendered live in the UI — including runs on sandbox execution targets, whose logs are tailed and delivered incrementally — but the granularity of what you see depends on the event stream the adapter emits.
Rough tiers, richest first:
acpx_local— full structured event stream. ACPX emits a JSONL event per meaningful runtime moment:acpx.session(agent, mode, session identity),acpx.status(progress text plus context-window usage),acpx.text_delta(assistant/thinking token deltas),acpx.tool_call(tool title, call id, and status updates as the call progresses),acpx.result(stop reason summary), andacpx.error(code, message, retryability). The transcript renders these as live-updating message, thinking, tool, and status blocks, and repeatedacpx.tool_callstatus updates fold into a single tool card instead of stacking duplicates.- CLI wrappers (
claude_local,codex_local,cursor,opencode_local, …). These parse each CLI's own streaming JSON output. You get assistant text, tool calls/results, and a final usage/cost summary, but granularity is limited to what the CLI prints — some emit tool progress, others only call/finish pairs. - Generic adapters (
process,http). Plain stdout/stderr lines with no structured transcript — you see raw output only.
Recommendation: for sandbox workers, prefer acpx_local. Sandbox run logs are streamed live, so the richer the event stream, the more useful the live transcript and status line are while a remote run is in flight. ACPX's status events (including context usage) and incremental tool-call updates give the closest thing to watching the agent work locally.
UI Parser Contract
External adapters can ship a self-contained UI parser that tells the Paperclip web UI how to render their stdout. Without it, the UI uses a generic shell parser. See the UI Parser Contract for details.