lakehouse/scripts/mode_pass4_staffing.ts

#!/usr/bin/env bun
/**
 * Pass 4: staffing_inference_lakehouse cross-domain validation.
 *
 * Runs the staffing-domain mode against synthetic fill requests.
 * Validates that the modes-as-prompt-molders architecture generalizes
 * beyond code review — the composer pattern (file_content + bug
 * fingerprints + relevance-filtered matrix + domain framing) should
 * produce grounded staffing recommendations the same way it produces
 * grounded code reviews.
 *
 * Each fill request is posted as `file_content` (since the runner's
 * shape expects file content; for staffing it's the request payload).
 * file_path is set to a synthetic path under requests/ so pathway
 * memory bucketing groups requests by geo+role.
 *
 * Usage: bun run scripts/mode_pass4_staffing.ts
 */

const GATEWAY = process.env.LH_GATEWAY ?? "http://localhost:3100";
const MODEL = process.env.LH_MODEL ?? "openai/gpt-oss-120b:free";

interface FillRequest {
  city: string;
  state: string;
  role: string;
  count: number;
  deadline: string;
  notes?: string;
}

const REQUESTS: FillRequest[] = [
  { city: "Toledo", state: "OH", role: "Welder", count: 2, deadline: "2026-04-29", notes: "OSHA 10 required" },
  { city: "Nashville", state: "TN", role: "Forklift Operator", count: 3, deadline: "2026-05-01" },
  { city: "Chicago", state: "IL", role: "Assembler", count: 5, deadline: "2026-04-30", notes: "second shift" },
  { city: "South Bend", state: "IN", role: "Electrician", count: 1, deadline: "2026-04-28", notes: "journeyman license" },
  { city: "Murfreesboro", state: "TN", role: "Packaging Operator", count: 4, deadline: "2026-05-02" },
];

function requestToPayload(req: FillRequest): string {
  return [
    `# Fill Request`,
    `Role: ${req.role} × ${req.count}`,
    `Location: ${req.city}, ${req.state}`,
    `Deadline: ${req.deadline}`,
    req.notes ? `Notes: ${req.notes}` : "",
    "",
    "Recommend candidates from the matrix data. Cite playbook references.",
  ].filter(Boolean).join("\n");
}

interface Result {
  req: FillRequest;
  ok: boolean;
  response_chars?: number;
  bug_fingerprints?: number;
  matrix_kept?: number;
  matrix_dropped?: number;
  latency_ms?: number;
  error?: string;
  preview?: string;
}

async function runOne(req: FillRequest): Promise<Result> {
  const payload = requestToPayload(req);
  const file_path = `requests/${req.role.toLowerCase().replace(/\s+/g, "_")}_${req.city.toLowerCase().replace(/\s+/g, "_")}_${req.state}.md`;
  try {
    const r = await fetch(`${GATEWAY}/v1/mode/execute`, {
      method: "POST",
      headers: { "content-type": "application/json" },
      body: JSON.stringify({
        task_class: "staffing_inference",
        file_path,
        file_content: payload,
        force_mode: "staffing_inference_lakehouse",
        force_model: MODEL,
      }),
      signal: AbortSignal.timeout(180_000),
    });
    if (!r.ok) {
      const body = await r.text().catch(() => "");
      return { req, ok: false, error: `HTTP ${r.status}: ${body.slice(0, 200)}` };
    }
    const j: any = await r.json();
    return {
      req, ok: true,
      response_chars: (j.response ?? "").length,
      bug_fingerprints: j.sources?.bug_fingerprints_count,
      matrix_kept: j.sources?.matrix_chunks_kept,
      matrix_dropped: j.sources?.matrix_chunks_dropped,
      latency_ms: j.latency_ms,
      preview: (j.response ?? "").slice(0, 400),
    };
  } catch (e: any) {
    return { req, ok: false, error: e.message };
  }
}

async function main() {
  console.log(`[pass4] requests=${REQUESTS.length} model=${MODEL} mode=staffing_inference_lakehouse\n`);
  let i = 0;
  const results: Result[] = [];
  for (const req of REQUESTS) {
    i++;
    process.stdout.write(`  [${i}/${REQUESTS.length}] ${req.role.padEnd(22)} × ${req.count} in ${req.city}, ${req.state} ... `);
    const r = await runOne(req);
    results.push(r);
    if (r.ok) {
      console.log(`✓ resp=${r.response_chars} bug=${r.bug_fingerprints ?? 0} mtx=${r.matrix_kept ?? 0}/${(r.matrix_kept ?? 0) + (r.matrix_dropped ?? 0)} ${((r.latency_ms ?? 0) / 1000).toFixed(1)}s`);
    } else {
      console.log(`✗ ${r.error}`);
    }
  }

  console.log(`\n[pass4] complete · ${results.filter(r => r.ok).length}/${results.length} succeeded\n`);

  // Show first successful response head to verify the framing actually
  // produced staffing-style output (verdict + ranked candidates) not
  // generic prose.
  const first = results.find(r => r.ok && r.preview);
  if (first) {
    console.log(`[pass4] first successful response preview (${first.req.city} ${first.req.role}):`);
    console.log(first.preview!.split("\n").map(l => "  | " + l).join("\n"));
  }
}

main().catch(e => { console.error(e); process.exit(1); });