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>
48 lines
2.0 KiB
TypeScript
48 lines
2.0 KiB
TypeScript
import { z } from 'zod';
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// BooCoder's config is a superset of the server's Config type so it can be
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// passed directly into the inference runner's InferenceContext. Fields the
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// inference loop reads: LLAMA_SWAP_URL, PROJECT_ROOT_WHITELIST. The rest
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// default to values that satisfy the server's Zod schema without BooCoder
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// needing to supply them in its environment.
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const ConfigSchema = z.object({
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NODE_ENV: z.enum(['development', 'production', 'test']).default('development'),
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PORT: z.coerce.number().int().positive().default(3000),
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HOST: z.string().default('0.0.0.0'),
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DATABASE_URL: z.string().url(),
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LLAMA_SWAP_URL: z.string().url(),
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PROJECT_ROOT_WHITELIST: z.string().default('/opt'),
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BOOTSTRAP_ROOT: z.string().default('/opt/projects'),
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DEFAULT_MODEL: z.string().default('qwen3.6-35b-a3b-mxfp4'),
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LOG_LEVEL: z.string().default('info'),
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CONTAINER_GUIDANCE_FILE: z.string().optional(),
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// Fields needed to satisfy the server's Config type but unused by BooCoder:
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SEARXNG_URL: z.string().url().default('http://100.114.205.53:8888'),
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GITEA_BASE_URL: z.string().url().default('https://git.indifferentketchup.com'),
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GITEA_USER: z.string().default('indifferentketchup'),
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GITEA_TOKEN: z.string().optional(),
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GITEA_SSH_HOST: z.string().default('100.114.205.53:2222'),
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MCP_CONFIG_PATH: z.string().optional(),
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// v2.0.5: cheaper model for titles, summaries, labeling.
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FAST_MODEL: z.string().optional(),
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// SSH access to the host for external agent dispatch (Phase 5)
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BOOCODER_SSH_HOST: z.string().default('100.114.205.53'),
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BOOCODER_SSH_USER: z.string().default('samkintop'),
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});
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export type Config = z.infer<typeof ConfigSchema>;
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let cached: Config | null = null;
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export function loadConfig(): Config {
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if (cached) return cached;
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const parsed = ConfigSchema.safeParse(process.env);
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if (!parsed.success) {
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console.error('Invalid environment configuration:');
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console.error(parsed.error.flatten().fieldErrors);
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process.exit(1);
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}
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cached = parsed.data;
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return cached;
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}
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