"""Matchmaking-v2 agent session. Mirrors the mesh contract: the orchestrator calls /a2a/tasks, which drives on_session_start / on_user_action; handlers `push` messages back (agent_thinking, agent_data{action,data}, agent_error) that the orchestrator forwards to the frontend. Step-0 scaffold: the dispatch + contract are wired; handlers are honest stubs that say "not implemented yet" so we can fill them in one full-stack slice at a time. """ from __future__ import annotations import asyncio import logging logger = logging.getLogger(__name__) class MatchmakingAgentSession: def __init__(self, websocket, user_id: str): self.ws = websocket self.user_id = user_id self.context: dict = {} async def push(self, msg_type: str, **kwargs): await self.ws.send_json({"type": msg_type, **kwargs}) async def _with_heartbeat(self, awaitable, messages: list[str], interval: float = 5.0): """Await `awaitable` while emitting a rotating progress message every `interval`s. A live search runs ~30-40s (Apify scrape + Opus curation). Without a steady trickle of messages, the Redis pub/sub channel that relays the result back to the browser idles out and the final `search_complete` is dropped — which is why users were seeing 0 matches. The heartbeat keeps that channel warm AND gives the user real progress during the wait. """ task = asyncio.ensure_future(awaitable) i = 0 while True: done, _ = await asyncio.wait({task}, timeout=interval) if task in done: return task.result() await self.push("agent_thinking", message=messages[i % len(messages)]) i += 1 async def _stub(self, action: str, note: str): await self.push("agent_data", action=action, data={"status": "not_implemented", "note": note}) async def on_session_start(self, params: dict): self.context["user_context"] = params.get("user_context") await self.push("agent_thinking", message="Scout is warming up…") # Real flow lands in a later slice: resolve prefs → run_search → emit feed. await self.push("agent_data", action="session_ready", data={"service": "matchmaking-v2", "version": "2.0.0"}) async def on_user_action(self, action: str, params: dict): handlers = { # existing contract "sync_preferences": self.handle_sync_preferences, "get_feed": self.handle_get_feed, "get_scout_feed": self.handle_get_feed, # unique name (avoids the course-service "get_feed" collision) "record_feedback": self.handle_record_feedback, "get_opportunity_detail": self.handle_get_opportunity_detail, # new in v2 "generate_matches": self.handle_run_search, "run_search": self.handle_run_search, "suggest_bubbles": self.handle_suggest_bubbles, # the Fine-tune "pathway finder" engine "tailor_resume": self.handle_tailor_resume, "submit_application": self.handle_submit_application, "get_apply_proof": self.handle_get_apply_proof, # per-opportunity state — persists across deck refreshes (applied / dismissed / saved docs) "dismiss_opportunity": self.handle_dismiss_opportunity, "restore_opportunity": self.handle_restore_opportunity, "mark_applied": self.handle_mark_applied, "save_apply_docs": self.handle_save_apply_docs, # activity tracking → the dashboard funnel + engagement rank "mark_viewed": self.handle_mark_viewed, "mark_saved": self.handle_mark_saved, "get_scout_stats": self.handle_get_scout_stats, } handler = handlers.get(action) if not handler: await self.push("agent_error", message=f"Unknown action: {action}") return try: await handler(params) except Exception as e: # noqa: BLE001 — surface to the client, log the trace logger.error("action '%s' failed: %s", action, e, exc_info=True) await self.push("agent_error", message=f"Failed to {action}: {e}") # ── handlers (stubs — replaced one full-stack slice at a time) ── async def handle_sync_preferences(self, params: dict): await self._stub("preferences_synced", "persist ScoutPrefs → label store") async def handle_get_feed(self, params: dict): """Replay the user's last persisted feed so matches survive navigation (no re-search).""" from app.db.repo import get_feed feed = await get_feed(self.user_id) await self.push("agent_data", action="feed_loaded", data=feed or {"opportunities": [], "cached": False}) async def handle_record_feedback(self, params: dict): await self._stub("feedback_recorded", "store SAVE/DISMISS/APPLY label") async def handle_get_opportunity_detail(self, params: dict): await self._stub("opportunity_detail", "return match-score breakdown") async def handle_run_search(self, params: dict): """Slice-1a: ScoutPrefs → live multi-board fetch → cards. No engine, no user-arm.""" from app.engine import search prefs = params # the frontend's ScoutPrefs arrive as params (user_context, if present, is ignored) fresh = bool(prefs.get("_fresh")) # dev toggle: force a live sweep instead of replaying cache if not search.has_mvq(prefs): await self.push("agent_data", action="search_complete", data={"opportunities": [], "needs": ["title", "location"]}) return await self.push("agent_thinking", message="Fetching fresh roles across job boards…" if fresh else "Scanning live roles across job boards…") # Per-board search cursors: re-running the SAME query advances EACH board's own page so every # run fetches GENUINELY NEW jobs. Resets when the query changes OR >24h (boards refresh ~daily). # Dedup is the per-user seen-net below — never cross-user, no opaque actor-side state. from app.db import repo as _repo sig = _repo.search_signature(prefs) cursors = await _repo.get_search_cursors(self.user_id, sig) prefs["_cursors"] = cursors # Heartbeat through the long Apify scrape so the relay channel stays alive (see _with_heartbeat). sweep = await self._with_heartbeat( search.run_sweep(prefs, fresh=fresh), ["Scanning live roles across the boards…", "Pulling the latest Naukri + LinkedIn + Foundit roles…", "Gathering fresh postings for you…"]) # Safety net: drop anything already shown / applied / dismissed (covers boards that can't # paginate, so the same posting never reappears even if a board re-returns it). seen = await _repo.get_seen_ids(self.user_id) candidates = [o for o in sweep["opportunities"] if o.get("id") not in seen] # Engine: assemble FULL context (profile + prefs). Cheap rankers SIFT 90 → top ~18 (white-box ‖ # embedding vibe); then Opus reads only those and curates the honest shortlist + report cards. from app.engine import curate as _curate from app.engine import rank as _rank from app.engine import sift as _sift user_context = params.get("user_context") # resume skills / experience / education / QScore await self.push("agent_thinking", message="Scoring roles against your profile…") # Run the blocking LLM work (embeddings + Opus) OFF the event loop, or the long sync OpenAI # call freezes the loop and the Redis response can't publish (→ the loader hangs forever). top, dbg = await asyncio.to_thread(_sift.sift, prefs, user_context, candidates) # Heartbeat through the long Opus curation (the other 30-40s gap that was dropping responses). curated = await self._with_heartbeat( asyncio.to_thread(_curate.curate, prefs, user_context, top), # Opus's call is final ["Scout is reading your top roles…", "Scoring fit + writing your report cards…", "Ranking your strongest matches…", "Almost there…"]) if curated is None: # safety net: sift + templated cards curated = _rank.select(top, prefs.get("stretch", "balanced")) engine = f"fallback:{dbg['mode']}" else: engine = "opus" result = {"opportunities": curated, "sources": sweep["sources"], "shortlisted": len(curated), "scanned": dbg["scored"], "engine": engine, "has_profile": bool(user_context and user_context.get("skills"))} # Persist the RAW deck + ADVANCE every board that ran (its page +1) so the next run of this # query fetches new jobs. Per-opportunity state (applied/dismissed/docs) lives separately. clean_prefs = {k: v for k, v in prefs.items() if k not in ("user_context", "_fresh", "_cursors")} # Store the LAST page fetched per paginating board (last + 1 = the page we just pulled). So a # NEW query's first search stores 1 (page 1), not 2. Naukri/Foundit have no page param → no # cursor (they dedup via the per-user seen-net). next_cursors = {b: int(cursors.get(b, 0)) + 1 for b in (sweep.get("sources") or {}) if b in search.PAGINATING_BOARDS} await _repo.save_feed(self.user_id, clean_prefs, result, query_sig=sig, cursors=next_cursors) # Accumulate the salary band — each deck contributes its peak salary, averaged over decks # (survives decks that disclose nothing, like Naukri "Not disclosed"). await _repo.update_salary_band(self.user_id, [o.get("salary_lpa") for o in (result["opportunities"] or [])]) # Mark the shown deck as SEEN so it never reappears in a future run. await _repo.mark_seen(self.user_id, [o.get("id") for o in (result["opportunities"] or []) if o.get("id")]) # Hand the UI a state-aware view: dismissed dropped, applied + saved-doc ids annotated. states = await _repo.get_opportunity_states(self.user_id) result["opportunities"] = _repo.annotate_and_filter(result["opportunities"], states) result["shortlisted"] = len(result["opportunities"]) await self.push("agent_data", action="search_complete", data=result) async def handle_suggest_bubbles(self, params: dict): """Fine-tune bubbling — stage-aware (broad→narrow→role) bubbles from the picks so far.""" from app.engine import suggest stage = params.get("stage", "role") items = await asyncio.to_thread( suggest.suggest, stage, params.get("picks") or {}, params.get("profile") or {} ) await self.push("agent_data", action="bubbles_suggested", data={"stage": stage, "items": items or []}) async def handle_tailor_resume(self, params: dict): await self._stub("resume_tailored", "resume-builder: tailor resume to the chosen role") async def handle_submit_application(self, params: dict): await self._stub("application_submitted", "master-key auto-apply (tier-aware)") async def handle_get_apply_proof(self, params: dict): await self._stub("apply_proof", "return captured confirmation screenshots") # ── per-opportunity state (persists across deck refreshes) ── async def handle_dismiss_opportunity(self, params: dict): """Mark a posting stale/dismissed → it never resurfaces in the deck.""" from app.db.repo import set_opportunity_state await set_opportunity_state(self.user_id, params.get("opportunity_id", ""), status="dismissed") await self.push("agent_data", action="opportunity_state_saved", data={"opportunity_id": params.get("opportunity_id"), "status": "dismissed"}) async def handle_restore_opportunity(self, params: dict): """Undo a dismiss/pass → clear the status so the role returns to the deck.""" from app.db.repo import set_opportunity_state await set_opportunity_state(self.user_id, params.get("opportunity_id", ""), status=None) await self.push("agent_data", action="opportunity_state_saved", data={"opportunity_id": params.get("opportunity_id"), "status": None}) async def handle_mark_applied(self, params: dict): """Record that the user applied to a role (sticks across reloads).""" from app.db.repo import set_opportunity_state await set_opportunity_state(self.user_id, params.get("opportunity_id", ""), status="applied") await self.push("agent_data", action="opportunity_state_saved", data={"opportunity_id": params.get("opportunity_id"), "status": "applied"}) async def handle_save_apply_docs(self, params: dict): """Remember the resume-builder document ids generated for a role so we never re-pay to re-tailor / re-generate them. Only the provided ids are written.""" from app.db.repo import set_opportunity_state fields = {k: params[k] for k in ("tailored_resume_id", "tailored_version_id", "cover_letter_id") if params.get(k)} await set_opportunity_state(self.user_id, params.get("opportunity_id", ""), **fields) await self.push("agent_data", action="opportunity_state_saved", data={"opportunity_id": params.get("opportunity_id"), **fields}) # ── activity tracking (dashboard funnel + engagement rank) ── async def handle_mark_viewed(self, params: dict): """The user opened a job → funnel 'Viewed'. Fire-and-forget (no response needed).""" from app.db.repo import set_opportunity_state await set_opportunity_state(self.user_id, params.get("opportunity_id", ""), viewed=True) async def handle_mark_saved(self, params: dict): """The user saved/swiped-right a job → funnel 'Shortlisted'.""" from app.db.repo import set_opportunity_state await set_opportunity_state(self.user_id, params.get("opportunity_id", ""), saved=True) async def handle_get_scout_stats(self, params: dict): """Assemble the REAL Summary dashboard metrics (Phase 2 fills the cross-service bits).""" from app.engine import stats data = await stats.build_scout_stats( self.user_id, user_uuid=params.get("user_uuid"), ) await self.push("agent_data", action="scout_stats", data=data)