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* fix(acp): flush straggler chunks promptly after session/prompt returns After session/prompt returns, HAPI drains buffered agentMessageChunk text and marks the turn complete, but leaves the message handler alive. Models with long streaming tails (DeepSeek, GPT-5.5) continue to push chunks after that drain, causing text to accumulate in the buffer and only appear when the next user prompt triggers the pre-prompt drain — showing up in the wrong turn with broken markdown. Start a 50ms interval timer after the post-prompt drain that keeps calling drainBuffers() on the live handler for up to 6 seconds, so straggler chunks are emitted within one poll tick instead of waiting for the next prompt. The timer is cancelled when the next prompt starts (pre-prompt drain replaces the handler) or on disconnect. Fixes #609. Also applies to Gemini and Kimi which share the same AcpSdkBackend code path. via [HAPI](https://hapi.run) Co-Authored-By: HAPI <noreply@hapi.run> * fix(acp): gate next turn's handler swap on previous turn's late drain Addresses the github-actions review on #730: the fire-and-forget late-flush timer let `prompt()` resolve while stragglers were still possibly arriving, so a rapid follow-up prompt could either drop those chunks (during the old null-handler gap) or leak them into the new turn's onUpdate. Pre-prompt phase now keeps the previous turn's handler alive across the quiet wait (bounded by LATE_FLUSH_WINDOW_MS) and swaps in a single phase immediately before sending the new session/prompt. The post-prompt late flush timer is unchanged — it still emits idle-window stragglers promptly without delaying the ready signal or `setModel` / `setConfigOption`. Adds three regression tests: late-chunk flushing within the window, pre-prompt straggler attribution to the previous turn's onUpdate, and disconnect cancelling the timer. Removes now-unused PRE_PROMPT_UPDATE_DRAIN_TIMEOUT_MS. via [HAPI](https://hapi.run) Co-Authored-By: HAPI <noreply@hapi.run> * fix(acp): await late drain so ready never fires before stragglers emit Follow-up to bot's repeated MAJOR on #730: even with the pre-prompt gate, the fire-and-forget late-flush timer let `prompt()` resolve before slow tails finished, so the launcher's `ready` signal (and any user follow-up queued against it) raced with text still being emitted to the current turn's onUpdate. Replace the setInterval timer with a synchronous `drainLateBuffers()` awaited in `prompt()`'s finally before turn_complete is sent. It polls drainBuffers every LATE_FLUSH_INTERVAL_MS so the UI keeps streaming smoothly during the wait, and exits early once the model has been quiet for LATE_FLUSH_QUIET_PERIOD_MS (250 ms — adds negligible latency to fast models like Claude whose tail is typically <100 ms) or the LATE_FLUSH_WINDOW_MS upper bound (6 s) elapses. Side effects: - Restore PRE_PROMPT_UPDATE_DRAIN_TIMEOUT_MS (1200 ms): the pre-prompt drain is now just a safety net since the post-prompt wait guarantees the previous turn is quiet by the time the next prompt starts. - Drop the `lateFlushTimer` field, `startLateFlushTimer`, `stopLateFlushTimer`, and their disconnect/pre-prompt cleanup calls. - Update the "emits straggler chunks" test to assert ordering before turn_complete, and add a fast-path test confirming the drain exits promptly when the model is quiet. via [HAPI](https://hapi.run) Co-Authored-By: HAPI <noreply@hapi.run> * fix(acp): anchor late-flush quiet window to entry, not stale lastSessionUpdateAt Bot's third MAJOR on #730: drainLateBuffers() compared elapsed time against lastSessionUpdateAt, which can already be older than LATE_FLUSH_QUIET_PERIOD_MS by the time the method starts — e.g. when the model emits chunks early in the turn, pauses, then sends stopReason. In that case the first loop iteration sees a stale "quiet" reading and returns immediately, missing any straggler that arrives just after session/prompt resolves; the chunk then sits in the buffer until the next prompt's pre-prompt drain. Anchor the quiet check to max(lastSessionUpdateAt, entry time) so we always observe at least one quiet period from method entry regardless of when the last chunk was. Adds a regression test that fires a chunk early, awaits a 200ms pause, schedules a post-resolution straggler, and asserts it lands before turn_complete. via [HAPI](https://hapi.run) Co-Authored-By: HAPI <noreply@hapi.run> * docs(acp): correct LATE_FLUSH_QUIET_PERIOD_MS comment after entry-anchor fix The previous note claimed the 250ms quiet check "exits early for fast models, adding negligible latency". That was true before commit 512d6a4 when the check compared against lastSessionUpdateAt; with the entry-time anchor, drainLateBuffers always observes at least one full quiet period. Document that this minimum wait is the price of catching post-resolution stragglers from paused-mid-turn models. via [HAPI](https://hapi.run) Co-Authored-By: HAPI <noreply@hapi.run> --------- Co-authored-by: HAPI <noreply@hapi.run>
HAPI
Run official Claude Code / Codex / Gemini / OpenCode sessions locally and control them remotely through a Web / PWA / Telegram Mini App.
Why HAPI? HAPI is a local-first alternative to Happy. See Why Not Happy? for the key differences.
Features
- Seamless Handoff - Work locally, switch to remote when needed, switch back anytime. No context loss, no session restart.
- Native First - HAPI wraps your AI agent instead of replacing it. Same terminal, same experience, same muscle memory.
- AFK Without Stopping - Step away from your desk? Approve AI requests from your phone with one tap.
- Your AI, Your Choice - Claude Code, Codex, Cursor Agent, Gemini, OpenCode—different models, one unified workflow.
- Terminal Anywhere - Run commands from your phone or browser, directly connected to the working machine.
- Voice Control - Talk to your AI agent hands-free using the built-in voice assistant.
- Workspace Browser - Opt-in via one or more
hapi runner start --workspace-root <path>flags: browse scoped file trees from the web and start sessions in allowed subdirectories.
Demo
https://github.com/user-attachments/assets/38230353-94c6-4dbe-9c29-b2a2cc457546
Getting Started
npx @twsxtd/hapi hub --relay # start hub with E2E encrypted relay
npx @twsxtd/hapi # run claude code
hapi server remains supported as an alias.
The terminal will display a URL and QR code. Scan the QR code with your phone or open the URL to access.
The relay uses WireGuard + TLS for end-to-end encryption. Your data is encrypted from your device to your machine.
For self-hosted options (Cloudflare Tunnel, Tailscale), see Installation
Docs
Build from source
bun install
bun run build:single-exe
Credits
HAPI means "哈皮" a Chinese transliteration of Happy. Great credit to the original project.