30be6636c2
* feat(diagnostics): active connect-failure triage + Sentry + in-app share Replaces the opaque "Connection Failed" / "Network request failed" dead-end with on-device diagnostics that classify *why* a connect attempt failed. On failure (quick connect and edit-connection test), the app now: - runs parallel probes: target /global/health, target root, and a public 204 endpoint (internet reachability check) - classifies the cause: malformed-url, no-internet, server-unreachable, health-failed, tls-error, timeout - shows a plain-English summary + a "Share report" button that copies a full report (target URL, per-probe results w/ error.cause, device/app info, recent log ring-buffer) to the clipboard and opens the share sheet - captures the same structured context to Sentry (auto-upload), gated on EXPO_PUBLIC_SENTRY_DSN so dev/CI builds work without secrets New: src/lib/logbuffer.ts (ring buffer + logger), src/lib/diagnostics.ts (regex URL parse — Hermes URL is incomplete — probe + report + share), src/lib/sentry.ts (no-op-without-DSN wrapper, scrubs basic-auth from URLs). Wired Sentry.wrap around RootLayout and initSentry() at module load. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * ci(sentry): wire Sentry DSN + source-map upload env into build; bump to 0.2.2 Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
84 lines
4.4 KiB
Markdown
84 lines
4.4 KiB
Markdown
# Handoff: OpenCode Mobile App
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## Status: CUA E2E Tests Working, v0.2.0 Release Triggered
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## What Was Done
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### 1. CUA (Computer-Use Agent) E2E Test Infrastructure
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- Built `scripts/android-cua-smoke.py` — a vision-LLM-powered Android E2E test that drives the app via ADB screenshots + AI actions
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- Two scenarios pass reliably: `send_message` (7 steps) and `multi_turn` (13 steps)
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- Added custom `{"type": "send"}` action that auto-locates the send button via uiautomator XML (solves coordinate accuracy issues with vision models)
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- Uses **Azure AI Services gpt-5.4** for vision inference
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### 2. CI/CD
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- `.github/workflows/cua-smoke.yml` — GitHub Actions workflow for emulator + CUA test
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- `.github/workflows/build.yml` — Builds APK, creates GitHub Release on tag push
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- `.github/workflows/publish-play-store.yml` — Fastlane Play Store publish
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- GitHub secrets set: `AZURE_OPENAI_API_KEY`, `AZURE_OPENAI_ENDPOINT`
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- Tagged `v0.2.0` — CI build + release workflow triggered
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### 3. App Features (prior sessions)
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- SSE reconnect with exponential backoff
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- Notification support
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- Message deduplication
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- Biometric auth gate (disabled on emulator)
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- Server connection management UI
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## Key Technical Details
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### Azure AI Services (LLM API)
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- **Correct endpoint**: `https://info-mjnxtt51-eastus2.cognitiveservices.azure.com`
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- **DO NOT USE**: `vibe-dev-ai.cognitiveservices.azure.com` (has no deployments, only model catalog)
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- **Env file**: `~/.env.d/azure-openai.env`
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- **Available models**: gpt-5.4, gpt-5.2, gpt-5.1, gpt-4.1, grok-4, deepseek-r1, kimi-k2.5
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- **API quirk**: Use `max_completion_tokens` (NOT `max_tokens`) for gpt-5.x models
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### Android Emulator
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- SDK at `/tmp/android-sdk/` (may need reinstall if /tmp is cleared)
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- AVD name: `test`, API 34 x86_64, KVM required
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- Start: `emulator -avd test -no-window -no-audio -no-boot-anim -gpu swiftshader_indirect -no-snapshot`
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- Package: `ai.opencode.mobile`
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### CUA Script Learnings
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- Vision models (gpt-5.4) consistently mis-estimate Y coordinates by ~80px for bottom-of-screen elements
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- Solution: `{"type": "send"}` action uses uiautomator XML to find the rightmost clickable element in the bottom bar
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- Enter key inserts newline in this app (doesn't send) — model must dismiss keyboard + tap send button
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- Screen resolution (1080x2400) included in prompt context helps coordinate accuracy
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- Screenshot retry (3 attempts, 30s timeout) needed for emulator under load
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### Server Connection
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- OpenCode server: `100.108.64.76:4096` (Tailscale, hostname `openclaw-dev-1`)
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- Must dismiss keyboard before tapping Connect button (keyboard obscures it)
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- Model: `gpt-5.3-chat-latest` (via GitHub Copilot provider)
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## What's Next
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1. **Verify v0.2.0 release** — check CI at https://github.com/dzianisv/opencode-mobile/actions
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2. **Run CUA in CI** — the `cua-smoke.yml` workflow needs a running opencode server to connect to (currently targets Tailscale IP which won't be reachable from GitHub runners). Options:
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- Mock server in CI
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- Use a public opencode server endpoint
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- Run as self-hosted runner on the dev VM
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3. **Add accessibility labels** — add `content-desc="Send"` to the send button in the app for better CUA reliability
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4. **More scenarios** — settings toggle, reconnect after server restart, slash commands
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## Connection Diagnostics (added in feat/connection-diagnostics-sentry)
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When a connect attempt fails, the app now runs an **active triage probe** instead of
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showing a generic error. It classifies the cause: `malformed-url`, `no-internet`,
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`server-unreachable`, `health-failed`, `tls-error`, `timeout`. The dialog shows a
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plain-English summary plus a **Share report** button (copies a full report —
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target URL, per-probe results, device/app info, recent logs — to clipboard + share sheet).
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- Code: `src/lib/diagnostics.ts` (probe + report), `src/lib/logbuffer.ts` (ring buffer),
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`src/lib/sentry.ts` (auto-upload wrapper).
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- **Sentry auto-upload** is opt-in via env var: set `EXPO_PUBLIC_SENTRY_DSN` at build time.
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Without it, Sentry is a no-op and only the in-app Share report works (fully offline).
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For source-map upload at build, also set `SENTRY_AUTH_TOKEN` / `SENTRY_ORG` / `SENTRY_PROJECT`.
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- The probe runs on-device, so it reports the *phone's* real network reality —
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unlike the co-located emulator, it can distinguish a true remote-peer tailnet failure.
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## Repo & Auth
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- Repo: `dzianisv/opencode-mobile`
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- GitHub auth: `source ~/.env.d/github-dzianisv.env`
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- Upstream issue: `anomalyco/opencode#10288`
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