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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>
118 lines
6.9 KiB
Markdown
118 lines
6.9 KiB
Markdown
---
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title: Adapters Overview
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summary: What adapters are and how they connect agents to Paperclip
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---
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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.
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## How Adapters Work
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When a heartbeat fires, Paperclip:
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1. Looks up the agent's `adapterType` and `adapterConfig`
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2. Calls the adapter's `execute()` function with the execution context
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3. The adapter spawns or calls the agent runtime
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4. The adapter captures stdout, parses usage/cost data, and returns a structured result
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## Built-in Adapters
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| Adapter | Type Key | Description |
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|---------|----------|-------------|
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| [Claude Code](/adapters/claude-local) | `claude_local` | Runs Claude Code CLI locally |
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| [Codex](/adapters/codex-local) | `codex_local` | Runs OpenAI Codex CLI locally |
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| ACPX Local | `acpx_local` | Runs Claude, Codex, or a custom ACP agent through ACPX with live structured event streaming |
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| [Gemini CLI](/adapters/gemini-local) | `gemini_local` | Runs Gemini CLI locally (experimental — adapter package exists, not yet in stable type enum) |
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| OpenCode | `opencode_local` | Runs OpenCode CLI locally (multi-provider `provider/model`) |
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| Cursor | `cursor` | Runs Cursor in background mode |
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| Pi | `pi_local` | Runs an embedded Pi agent locally |
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| Hermes | `hermes_local` | Runs the local Hermes CLI through `@paperclipai/hermes-paperclip-adapter` |
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| Hermes Gateway | `hermes_gateway` | Calls an already-running Hermes API server through `@paperclipai/hermes-paperclip-adapter/gateway` |
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| OpenClaw Gateway | `openclaw_gateway` | Connects to an OpenClaw gateway endpoint |
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| [Process](/adapters/process) | `process` | Executes arbitrary shell commands |
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| [HTTP](/adapters/http) | `http` | Sends webhooks to external agents |
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### Hermes local vs gateway
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Use `hermes_local` when Paperclip should start the local `hermes` CLI on the
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same host for each heartbeat. Use `hermes_gateway` when Hermes is already
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running as an HTTP/SSE API server and Paperclip should call that server instead
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of spawning a process. Both type keys are stable built-ins.
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The unified Hermes package owns both built-in adapters. The older
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`@paperclipai/adapter-hermes-gateway` package remains only as a deprecated
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compatibility shim that re-exports the gateway entrypoints for one release.
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New plugin overrides should target `@paperclipai/hermes-paperclip-adapter` and
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set the desired type key (`hermes_local` or `hermes_gateway`).
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### External (plugin) adapters
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These adapters ship as standalone npm packages and are installed via the plugin system:
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| Adapter | Package | Type Key | Description |
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|---------|---------|----------|-------------|
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| Droid | `@henkey/droid-paperclip-adapter` | `droid_local` | Runs Factory Droid locally |
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## External Adapters
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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.
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```sh
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# Install from npm via API
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curl -X POST http://localhost:3102/api/adapters \
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-d '{"packageName": "my-paperclip-adapter"}'
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# Or link from a local directory
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curl -X POST http://localhost:3102/api/adapters \
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-d '{"localPath": "/home/user/my-adapter"}'
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```
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See [External Adapters](/adapters/external-adapters) for the full guide.
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## Adapter Architecture
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Each adapter is a package with modules consumed by three registries:
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```
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my-adapter/
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src/
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index.ts # Shared metadata (type, label, models)
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server/
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execute.ts # Core execution logic
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parse.ts # Output parsing
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test.ts # Environment diagnostics
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ui-parser.ts # Self-contained UI transcript parser (for external adapters)
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cli/
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format-event.ts # Terminal output for `paperclipai run --watch`
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```
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| Registry | What it does | Source |
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|----------|-------------|--------|
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| **Server** | Executes agents, captures results | `createServerAdapter()` from package root |
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| **UI** | Renders run transcripts, provides config forms | `ui-parser.js` (dynamic) or static import (built-in) |
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| **CLI** | Formats terminal output for live watching | Static import |
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## Choosing an Adapter
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- **Need a coding agent?** Use `claude_local`, `codex_local`, `acpx_local`, `opencode_local`, `hermes_local`, or install `droid_local` as an external plugin
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- **Need the richest live run feedback (especially for sandbox workers)?** Use `acpx_local` — see [Feedback granularity](#feedback-granularity)
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- **Need Hermes on another host or already running as a service?** Use `hermes_gateway`
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- **Need to run a script or command?** Use `process`
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- **Need to call a custom external service?** Use `http`
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- **Need something custom?** [Create your own adapter](/adapters/creating-an-adapter) or [build an external adapter plugin](/adapters/external-adapters)
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## Feedback Granularity
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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.
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Rough tiers, richest first:
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1. **`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), and `acpx.error` (code, message, retryability). The transcript renders these as live-updating message, thinking, tool, and status blocks, and repeated `acpx.tool_call` status updates fold into a single tool card instead of stacking duplicates.
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2. **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.
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3. **Generic adapters (`process`, `http`).** Plain stdout/stderr lines with no structured transcript — you see raw output only.
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**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.
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## UI Parser Contract
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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](/adapters/adapter-ui-parser) for details.
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