Files
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

82 lines
2.7 KiB
Python

"""Trainee loop: win/lose board, weak-area analysis, user-generated personas.
A user never re-chats a persona. To keep training, they generate new personas —
either auto from their weak areas ("lock") or from a manual form. Generated
personas are private to the user.
"""
from __future__ import annotations
import datetime
from pathlib import Path
from typing import Any
from ..storage.store import JsonStore, new_id
from .store import ensure_persona_shape
class MyPersonaStore:
def __init__(self, data_dir: Path) -> None:
self.personas = JsonStore(data_dir / "my_personas")
def _path_key(self, user_id: str, pid: str) -> str:
return f"{user_id}__{pid}"
def create(self, *, user_id: str, persona: dict[str, Any]) -> dict[str, Any]:
p = ensure_persona_shape(persona)
if "id" not in p or not p["id"]:
p["id"] = new_id("myp")
record = {
"key": self._path_key(user_id, p["id"]),
"user_id": user_id,
"persona": p,
"created_at": datetime.datetime.now(datetime.timezone.utc).isoformat(),
}
return self.personas.create(record, key=record["key"])
def list_for(self, user_id: str) -> list[dict[str, Any]]:
return [
r.get("persona")
for r in self.personas.where(lambda x: x.get("user_id") == user_id)
]
def analyze_weak_areas(sessions: list[dict[str, Any]]) -> dict[str, Any]:
"""Summarize which persona attributes a user tends to lose against."""
losses, wins = [], []
for ses in sessions:
if ses.get("outcome") == "won":
wins.append(ses)
elif ses.get("outcome") == "lost":
losses.append(ses)
def tally(key: str, label: str) -> list[dict[str, Any]]:
from collections import Counter
c = Counter()
for l in losses:
meta = l.get("persona_meta") or {}
v = meta.get(key)
if v is not None:
c[v] += 1
return [{"value": k, "losses": v} for k, v in c.most_common(3)]
return {
"total_sessions": len(sessions),
"wins": len(wins),
"losses": len(losses),
"by_tier": tally("tier", "tier"),
"by_initiation": tally("initiation_mode", "initiation"),
"by_channel": tally("channel", "channel"),
"top_loss_personas": [
{
"persona_id": l.get("persona_id"),
"persona_name": l.get("persona_name"),
"score": (l.get("debrief") or {}).get("score", 0),
"why": (l.get("debrief") or {}).get("why", ""),
}
for l in sorted(
losses, key=lambda x: (x.get("debrief") or {}).get("score", 0)
)[:5]
],
}