dia-source-analysis

name

dia-source-analysis

description

Analyze / reverse-engineer the locally installed Dia Browser mac app (The Browser Company; bundle id company.thebrowser.dia; shares ArcCore with Arc). Inspect its app bundle, extract its Bun/TypeScript agent-server source from shipped source maps, fingerprint the runtime, read native-Swift symbols, and map its AI-agent / sandbox / on-device-ML architecture. Invoke when the user wants to study how Dia works internally, extract Dia's agent code, or compare Dia's agent/terminal approach against termio. (User sometimes voice-types the name as 'DotBrowser' — same app.)

Analyze Dia Browser source

Dia (/Applications/Dia.app, The Browser Company, company.thebrowser.dia) is a WebKit-based browser (~1.4 GB) that shares ArcCore.framework with Arc. termio uses it as a reference for how a shipping product drives AI coding agents as sandboxed child processes (Dia shells to the real Claude Code CLI under Seatbelt) and for its agent-server / IPC architecture. This skill captures how to dig into it and what's already known, so analysis doesn't start from scratch each time.

Golden rules

• Read-only, on the user's own machine, for research. This is proprietary code shipped to the user. Use it to understand and learn, never to copy/redistribute verbatim or ship lifted code. State this caveat when sharing recovered source.
• Verify before trusting old findings. The "Established facts" below are version-stamped. Dia auto-updates (Sparkle); bundle layout, file hashes, runtime versions, and even whether source maps ship can all change. Always re-read info.json + CFBundleShortVersionString first and treat mismatches as "re-derive from scratch."
• Two recoverability tiers: the Bun/TS agent backend is near-fully recoverable (source maps); the native Swift app is symbols/structure only (no real source).

Established facts (as of Dia 1.34.2 — RE-VERIFY)

Agent-server info.json (1.34.2): version 1.0.0, buildDate 2026-06-10, commit 47de9fbe6c4, claudeCodeVersion 2.1.131. (Was 1.32.0 / commit 55d9d2e174b / buildDate 2026-05-20.)

• ⚠️ Source maps NO LONGER SHIP as of 1.34.2. extract-sourcemaps.py returns "No .map files found" — the Bun/TS agent-server backend is no longer recoverable as near-original TS (only logic compiled into the Mach-O remains). The native-Swift tier is unchanged: symbols + embedded source paths only. So "the big win" in §1 below is gone on current builds; keep the procedure for older installs / in case they return.
• Agent backend = Bun-compiled standalone Mach-O (agent-server, handler) + the real Claude Code CLI (claude, 206 MB, itself a Bun binary). No separate Node/Bun runtime is installed — each binary embeds Bun. They run as child processes under Seatbelt sandbox (sandbox-exec -f agent.sb / agent-claude-code.sb, params via -D DATA_DIR=…), talking to the native UI over SSE/IPC (transport/sse.ts, ipc-gateway.ts). Per-context workspace at data/contexts/{contextId} with resumable disk buffers (session/buffer.ts, JSONL). This is the part most relevant to termio — termio runs agents in real PTYs (.exec) instead, but the child-process-under-sandbox + resumable-buffer + IPC design is the directly comparable bit.
• Streaming smoothness comes from native rendering + session/update-batcher.ts: deltas are coalesced and flushed only on ≥256 B OR 250 ms idle OR completion — so the UI updates a few times/sec, not per token. The Bun agent-server is backend orchestration and does NOT touch UI perf.
• AI chat ("AssistantPanel") renders NATIVELY, not in a webview. Markdown parsed by cmark (swift-markdown), code highlighted by Highlightr (CodeAttributedString → NSAttributedString), math by SwiftMath (MTMathListDisplay, CoreText). UI is AppKit NSViewControllers (source paths Frameworks/BoostBrowser/Sources/AssistantPanel/*.swift).
• The AI input is the native AppKit module BoostCommandBar (Frameworks/BoostBrowser/ Sources/BoostCommandBar/*): a token/pill TokenTextView w/ SkillPillTokenViewProvider; Skills = SkillsV3; @-mentions (: @Search/@Slack/@Gmail/@Notion) insert context/tool pills. On-device (3-label intent) + classifier rank proactive suggestions.

Bundle map

Path	Size	What
Contents/Frameworks/ArcCore.framework	~548 M	browser engine core (WebKit + Arc)
Contents/Resources/agent-server-resources/dist	~371 M	Bun agent backend + bundled claude CLI (206 M)
Contents/Resources/OnDeviceLoRAadaptors_…bundle	~152 M	DistilBERT base + 3 LoRA classifiers
Contents/MacOS/Dia	~106 M	native Swift app binary (AssistantPanel etc.)
Contents/Frameworks/libAIInfra.dylib	~21 M	on-device classification (LocalClassification)
Contents/Resources/*.bundle	—	Highlightr, SwiftMath, SwiftProtobuf, mlx-swift, swift-transformers, ARC/BoostBrowser feature bundles
dist/*.sb	—	Seatbelt sandbox profiles

Procedure

0. Identify version (always first)

/usr/libexec/PlistBuddy -c "Print :CFBundleShortVersionString" /Applications/Dia.app/Contents/Info.plist
cat "/Applications/Dia.app/Contents/Resources/agent-server-resources/dist/info.json"

1. Recover the agent-server source (the big win)

The .js bundles are compiled into the Mach-O binaries and NOT shipped, but entrypoint.js.map and handler-entrypoint.js.map ship with sourcesContent populated → near-original TS.

python3 skills/dia-source-analysis/scripts/extract-sourcemaps.py --out /tmp/dia-src

Yields ~40 "own" TS files (non-node_modules): agent/harness/claude-sdk/* (how it drives the Claude SDK — prompt-template.ts, proxy-tools.ts, claude-sdk-in-process.ts, sandbox.ts), session/*, transport/*, handler/*, runtime.ts, watchdog.ts, main.ts. Also readable without extraction: dist/agents/*/spec.yaml, dist/agents/*/.claude/, dist/resources/tool-schemas/*.json.

2. Fingerprint the runtime

D=/Applications/Dia.app/Contents/Resources/agent-server-resources/dist
for f in agent-server handler claude; do echo "== $f"; \
  strings -a "$D/$f" | grep -iE "Bun v[0-9]|Bun/[0-9]|node\.js v[0-9]"|sort -u|head; done

3. Native Swift binary — structure recoverable via ipsw class-dump --swift (no bodies)

The symbol table is stripped (nm ≈ 8.5k symbols, no Swift method-body symbols; debugger attach is blocked by hardened runtime flags=0x10000(runtime) + no get-task-allow). But the Swift reflection metadata survives and gives field-level structure — the closest thing to source:

brew install ipsw   # one-time
BIN=/Applications/Dia.app/Contents/MacOS/Dia
strings -a "$BIN" | grep -iE "AssistantPanel|Highlightr|SwiftMath|cmark|MarkdownText" | sort -u | head
ipsw class-dump "$BIN" --class 'AssistantPanel'                    # response/content view controllers
ipsw macho info  "$BIN" --swift-all | grep -i <Type>              # generics

This yields class/struct instance-variable layouts, superclasses, protocol conformances, and method signatures — NOT bodies, and NOT the numeric values of fields. strings still gives demangled type names + embedded source paths (/Users/admin/actions-runner/_work/arc/arc/…). For deeper work use Hopper/Ghidra, but Swift ABI makes UI/animation bodies near-unreadable.

4. On-device models

B=/Applications/Dia.app/Contents/Resources/OnDeviceLoRAadaptors_OnDeviceLoRAadaptors.bundle/Contents/Resources
cat "$B/config.json"; ls -lhS "$B"/*.safetensors
strings -a /Applications/Dia.app/Contents/Frameworks/libAIInfra.dylib | grep -iE "cmd_t|router|sensitive|skills_|distilbert|lora" | sort -u | head

5. Sandbox profiles (most relevant to termio)

cat /Applications/Dia.app/Contents/Resources/agent-server-resources/dist/agent.sb
cat /Applications/Dia.app/Contents/Resources/agent-server-resources/dist/agent-claude-code.sb

These are Seatbelt (sandbox-exec) profiles — read them to see exactly what the agent / Claude Code subprocess may touch.

Relevance to termio

termio is a native Swift + libghostty terminal for AI coding agents (unpeel-style): it runs each agent/session in a real PTY (.exec) via a libghostty surface, unsandboxed. Dia solves an adjacent problem — driving the same Claude Code CLI — but from a browser, sandboxed, over IPC. When comparing, borrow narrowly (termio is deliberately simple/minimal — do not import Dia's ~370 M Bun agent-server, on-device ML stack, or browser surface):

• Sandbox profiles (§5) are the highest-value takeaway: if termio ever wants to constrain what an agent session can touch beyond the PTY, Dia's agent.sb / agent-claude-code.sb Seatbelt profiles are a concrete, shipping reference for sandbox-exec.
• Child-process + resumable buffer + IPC design (session/buffer.ts JSONL, per-context workspace) is the architecture analog to termio keeping a TerminalController alive per session in the SurfaceCache — same goal (survive view rebuilds / resume), different mechanism.
• Delta coalescing (update-batcher.ts: flush on ≥256 B / 250 ms idle / completion) is a generic perf lesson if termio ever renders agent output outside the raw terminal grid.
• Skip: the native AssistantPanel renderer and on-device LoRA classifiers — termio shows a real terminal, not a native chat surface, so those don't map.