Files
matchmaking-v2/app/agent/session.py
2026-06-25 13:26:09 +00:00

247 lines
14 KiB
Python

"""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)