Commit Graph

2 Commits

Author SHA1 Message Date
Macky
bd6a7ffa32 feat(chat): scenario-based training — choice of channel/Situation + realistic per-turn evaluation
Backend:
- Channel/initiation now driven by a SCENARIO chosen at chat start, not baked into the
  persona: social (customer opens), f2f_call (seller must open, proactive), recontact
  (customer re-contacts after 1-3 months).
- /chat/start accepts {scenario}; session stores scenario + internal{turns,score}.
- persona_reply takes scenario + adapts tone; system-role transcript entries are fed to
  the persona as hidden scene notes.
- JUDGE updated for realism: good response can WIN even in hard/tough-text scenarios;
  long/no-close chats (turns >~12) lose; pushy/ignoring-need loses. Efficiency rewarded.

Frontend:
- Scenario picker before chat (choose Social / Face-to-face-call / Re-contact).
- Chat thread renders role=system as a centered time-lapse/scene note.
- Choose-scenario i18n (EN+TH).
Rebuilt dist.
2026-08-08 11:27:05 +07:00
Macky
c3d31c06e2 Sales Trainer v0.1: corporate sales-training simulator (Flask+Vue, 15 personas, chat simulator, judge, analytics)
- Auth/roles (no self-reg), admin user provision, JWT
- Analyze: sales kit + initial pain-fit from form/upload
- Persona generator: 15 personas (5/tier) w/ pain variety, negotiation, init mode, channel, latent/revealable, wrong_text special
- Chat simulator: per-mode initiation, one-shot, hidden signals, judge-LLM debrief+coaching
- Trainee loop: win/lose board, weak-areas, user-generated personas
- Admin analytics; EN+TH Vue SPA served by Flask
- Deploy: Dockerfile, docker-compose, README, eng-log + HANDOFF
- Tests (mock LLM): m0/m1/routes/e2e all pass
2026-08-07 15:31:06 +07:00