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>
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