Source-level recon of QwenLM/qwen-code (Apache-2.0) informed 4 lifts:
1. FAST_MODEL config: optional env var routes cheap LLM calls (titles,
summaries, labeling) to a smaller model on llama-swap. auto_name.ts
uses ctx.config.FAST_MODEL ?? session.model. Set FAST_MODEL=nemotron-
nano-4b to avoid loading the 35B model for 20-token title generation.
2. Tool-use summaries (services/inference/tool-summaries.ts): utility
that generates "git-commit-subject-style" labels for tool batches via
a fast-model LLM call. System prompt + truncation logic ported from
Qwen Code's toolUseSummary.ts. Exported via @boocode/server/inference
for BooCoder's dispatcher to call after task completion.
3. Qwen as dispatchable agent: added to agent-probe.ts KNOWN_AGENTS.
PTY dispatch builds: qwen -p "<task>" --output-format stream-json
(NDJSON structured events over stdout). Env: OPENAI_BASE_URL +
OPENAI_API_KEY points Qwen Code at llama-swap. execution_path CHECK
constraint extended with 'qwen'.
4. Arena routes (routes/arena.ts): POST /api/arena dispatches the same
task to N contestants (2-5, each with different agent/model), each
getting its own task row linked by arena_id UUID. GET /api/arena/:id
shows all contestants. POST /api/arena/:id/select/:task_id marks
winner. Schema: arena_id column added to tasks.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Phase 7 of v2.0. BooCoder gains a terminal-driven UX and subagent
isolation primitive.
CLI (src/cli.ts): standalone entry point for terminal use.
- boocode run "task" [--agent x] [--model y] — create + stream output
- boocode ls [--state x] — formatted task table
- boocode attach <id> — WS stream of running task
- boocode send <id> "msg" — follow-up message to task session
Connects to BOOCODER_URL (default http://100.114.205.53:9502).
Human inbox (routes/inbox.ts): GET /api/inbox (failed/blocked tasks),
POST /api/inbox/:id/retry (reset to pending for re-dispatch).
Cost tracking: dispatcher aggregates tokens_used from all messages in
the task's session after completion, stores in tasks.cost_tokens.
GET /api/stats/costs?group_by=project|agent|day for aggregation.
Boomerang subagent isolation (3 new tools):
- new_task: creates child task with parent_task_id linkage, runs in
fresh isolated session. Orchestrator sees only output_summary.
- list_tasks: query child tasks of current parent
- check_task_status: read task state + output_summary
The orchestrator pattern: an agent with tools: [new_task, list_tasks,
check_task_status] can ONLY dispatch — can't read files or MCP. This
is the Roo Code Boomerang Tasks capability-restriction principle.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Phase 4 of v2.0. BooCoder can now queue tasks and dispatch them
through the inference loop autonomously.
Dispatcher (services/dispatcher.ts): in-process setInterval(5s) polls
tasks WHERE state='pending', picks one at a time, creates an isolated
session+chat, enqueues inference with the task's input as the user
message, polls for completion, marks state completed/failed with
output_summary. Single-task-at-a-time for v2.0.0; parallel dispatch
is a Phase 5+ concern. Respects onClose hook for graceful shutdown.
Task routes (routes/tasks.ts): POST /api/tasks (create), GET /api/tasks
(list with state/project filters), GET /api/tasks/:id (detail),
POST /api/tasks/:id/cancel (marks cancelled, aborts if running).
Agent probe (services/agent-probe.ts): on startup, probes PATH for
opencode/goose/claude/pi via which + --version. UPSERTs into
available_agents table. Finds nothing inside the container (expected —
Phase 5 addresses host-agent access via ACP/PTY).
Schema: ALTER TABLE tasks ADD COLUMN IF NOT EXISTS session_id (links
task to its auto-created inference session for isolation).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Phase 2 of v2.0. BooCoder is now a functional write-capable chatbot.
Write-path guard: resolveWritePath() uses resolve() (no realpath — files may
not exist for creates) + prefix-check + secret-file deny list (.env, *.pem,
id_rsa*, etc.). 23 unit tests cover traversal attacks.
Pending-changes service: queueEdit/Create/Delete → applyOne/All →
rejectOne/All → rewindOne. Edit diffs stored as JSON {old, new}. All writes
queue before touching disk; apply re-validates the path guard.
5 write tools: edit_file, create_file, delete_file, apply_pending, rewind.
Registered alongside 25 read-only tools from BooChat (30 total, alpha-sorted).
Write tools use a module-level inference context for sql+sessionId injection.
Inference loop via workspace dependency: apps/coder imports
createInferenceRunner, createBroker, ALL_TOOLS from @boocode/server (dist/).
apps/server gains declaration: true + exports map with typed subpath entries.
No code duplication — one inference engine shared by both apps.
API routes: POST /api/sessions/:id/messages (user msg → inference), POST stop,
GET/POST pending-changes CRUD (5 endpoints), WebSocket session streaming.
Dockerfile updated to build apps/server first (coder depends on its .d.ts).
Health endpoint reports tool count: {"ok":true,"db":true,"tools":30}.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
