-Puter 8b36dd4e99 fix(staging): unify matchmaking-v2 network topology + redact Apify token
Root cause: the VPS ran two Compose projects from the same file — api under
-p matchmaking-v2-staging, postgres/redis under -p matchmaking-v2 — creating
two disjoint <project>_default bridges. Every dependency hostname (postgres,
redis) was NXDOMAIN from the api container, so feed store init, pool_load,
save_feed, and RedisStreamWorker all failed with [Errno -2].

Fix: standardize on a single project (matchmaking-v2) for all three services
with an external shared bridge (matchmaking-v2_default) and inline DB/Redis
host pinning. The deploy script (sync-staging.sh) now brings up all three
services, pre-creates the external network, and has a public_health_url case.

Apify: moved the token from query params (4 sites) to an Authorization header
so no request URL can leak it. All raise_for_status() paths now raise
token-free _ApifyHTTPError. The live 403 (platform-feature-disabled: monthly
usage cap exceeded) is an external blocker — no code fix.

Tests: 15 focused regression tests covering network topology, volume config,
deploy-script alignment, and Apify token redaction (with call-counters).
2026-07-11 05:56:14 +05:30

matchmaking-v2 (Scout)

Fresh, on-demand matchmaking service replacing the dead nightly aggregator. Same agent-mesh mold as the other GrowQR services (FastAPI · a2a card · /a2a/tasks · orchestrator-routed). Not a drop-in — it keeps the existing 4 skills working and adds new actions from scratch.

Layout

app/
  main.py              FastAPI app (card + /a2a/tasks + /api/v1/health), lifespan worker
  config.py            lean settings (no corpus DB, no scrape schedule)
  a2a/                 card.py (discovery), auth.py (bearer), tasks.py (orchestrator entry)
  agent/session.py     Session: on_session_start / on_user_action dispatch  ← the brain
  adk/worker.py        Redis-Streams worker (graceful no-op without Redis)
  api/v1/health.py     /api/v1/health
  engine/
    board_adapters/    ScoutPrefs → Apify actor inputs (Naukri-first, verified maps)
    ...                the §3 cascade (normalize→filter→utility→fusion→rerank) lands here
  contracts/           Pydantic contracts (user_context, transport, …) — added per slice
research/              docs/ (ENGINE_DESIGN, SIGNAL_AUDIT_V2, ENGINE_INPUTS, …) + poc/ (auto-apply)

Contract (how it connects)

Frontend useAgentSession (page "job-matching") → orchestrator (routes by card name = matchmaking-service) → POST /a2a/tasks {action, params, user_context}Session pushes agent_data{action,data} → orchestrator → frontend latestData[action].

Skills: existing get_feed · sync_preferences · record_feedback · get_opportunity_detail; new run_search · tailor_resume · submit_application · get_apply_proof (stubbed). Each new action needs: card skill (here) + orchestrator action-map entry + frontend sendAction wiring.

Run (local)

pip install -r requirements.txt
uvicorn app.main:app --reload --port 8006
# card:    GET http://localhost:8006/.well-known/agent-card.json
# health:  GET http://localhost:8006/api/v1/health
# action:  POST http://localhost:8006/a2a/tasks  (Bearer dev-a2a-key)

Build order (full-stack slices)

  1. scaffold (this) — bootable skeleton, contract wired, handlers stubbed.
  2. on-demand run_search — board_adapters → Apify → engine cascade → ranked feed (+ frontend wire).
  3. feedback labels + record_feedback. 3. tailor_resume. 4. submit_application + get_apply_proof.
  4. cut over from old :8006, decommission corpus.
Description
GrowQR matchmaking v2 service synced from GitHub
Readme 9 MiB
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Python 99.7%
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Dockerfile 0.1%