💬 LinkedIn Conversation Scraper

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0.2 — 2026-06-24

New engine — LinkedIn Voyager messaging API. Replaced the fragile DOM-scraping engine with calls to LinkedIn's own messaging GraphQL endpoints (the same the web app makes), issued through an authenticated headless-browser request context. This is immune to CSS-selector churn and the "conversation cards never rendered → failed run" blocks that previously caused repeated "under maintenance" flags. queryIds are extracted live when the pinned fallbacks return nothing.
Fixed the recurring "under maintenance" root cause. A missing/invalid li_at, or LinkedIn blocking every proxy tier, now ends the run successfully with an empty dataset and a clear log — never a FAILED run. Apify's automated Store health check runs the default (empty) li_at, and failing it there is exactly what kept flipping the Actor to "under maintenance".
Participant headline / distance / pronoun / picture now come directly from the API response — no extra profile-page visits, much faster.
Proxy plan simplified to direct → residential (datacenter IPs are blocked by LinkedIn); explicit user proxy config is still honored.
Added concurrency and max_retries inputs; filter now maps to LinkedIn categories (INMAIL / STARRED / UNREAD).
PPE row_result charging unchanged (per saved conversation, stops cleanly on spend-limit).

Fixed build: renamed requirements.txt.txt → requirements.txt so the Dockerfile COPY requirements.txt ./ resolves.
Hardened pay-per-event charging: per-conversation row_result charge now inspects ChargeResult.event_charge_limit_reached and stops the run gracefully when the user's spend limit is hit (no crash, partial data kept).
Charging is best-effort — dataset writes still succeed when charging is unavailable (e.g. local runs).