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
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Macky
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backend/app/services/simulator.py
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186
backend/app/services/simulator.py
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"""Sales chat simulator: the trainee's chat engine against one persona.
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Reuses the persona card + sales kit + chat history + internal state. A separate
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judge-LLM decides outcome (won/lost) + scoring + coaching. Hidden/latent data is
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never exposed mid-chat. Initiation is per-persona (customer or seller).
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"""
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from __future__ import annotations
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import json
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from typing import Any
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from ..llm import LLMClient, LLMError
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CHAT_SYSTEM = """You are playing a REALISTIC customer named {name} in a sales-training chat.
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Stay perfectly in character at ALL times. Use {tone}.
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CONTEXT ABOUT YOU (USE THIS — it is your truth, but DO NOT reveal latent details unless asked
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naturally and it makes sense for a real customer to reveal them):
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- Profession: {profession} | Age: {age_group} | Channel: {channel}
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- Background: {background}
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- Personality: {personality}
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- Lifestyle: {lifestyle} | Income: {income}
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- Budget: {budget} | Decision timeline: {decision_timeline}
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- Your pains (some may be product-solvable, some NOT): {pains}
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- Your negotiation levers: {levers}
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- Your goal/mood: {goal}
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Initiation mode: {init_mode}. {special_instr}
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BEHAVIOR RULES:
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1. You do NOT buy easily. You stall, ask questions, compare, and negotiate (price, freebies,
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delivery time, scope, payment).
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2. If the seller is rude, pushy, ignores your need, or mis-diagnoses your pain, your trust drops
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and you may refuse to continue / walk away — even if you wanted the product.
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3. You reveal pains only when the seller asks good questions or builds trust. Do not dump your
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pains unprompted.
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4. Respond in natural, in-character chat style ({channel} style, casual for LINE).
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5. Stay in character; never mention that you are a simulation or an AI persona.
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Reply with a JSON object: {{"reply": "<your message>"}}
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Only output that JSON.
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"""
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JUDGE_SYSTEM = """You are the JUDGE of a sales-training chat. Decide the outcome and score it.
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A sale is CLOSED only if BOTH:
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1. The seller resolved the customer's real pain(s) (the conditions that matter to this persona),
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AND
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2. The customer verbally accepts the offer/price (in the final exchange).
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Otherwise it is LOST (or abandoned if the user ended early).
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Scoring (0-100): painResolution + trust + objectionHandling are the only factors.
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Return JSON:
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{
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"outcome": "won" | "lost",
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"score": 0-100,
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"pain": "the persona's key pain",
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"why": "brief reason for won/lost",
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"failurePoints": ["what went wrong, or []"],
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"coaching": ["for each weak point, a concrete 'you should have said/asked this instead']",
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"painProgress": {"painName": 0-100}
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}
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"""
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class Simulator:
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def __init__(self, llm: LLMClient, judge_llm: LLMClient | None = None) -> None:
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self.llm = llm
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self.judge_llm = judge_llm or llm
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# ── persona reply ──────────────────────────────────────────────────
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def persona_reply(
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self,
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*,
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persona: dict[str, Any],
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sales_kit: dict[str, Any],
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messages: list[dict[str, str]],
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internal: dict[str, Any],
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) -> str:
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pains_txt = self._describe_pains(persona.get("pains", []))
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system = CHAT_SYSTEM.format(
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name=persona.get("name", "Customer"),
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tone=persona.get("communication_style", "natural, casual"),
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profession=persona.get("profession", "customer"),
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age_group=persona.get("age_group", "adult"),
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channel=persona.get("channel", "facebook"),
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background=persona.get("background", ""),
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personality=persona.get("personality", ""),
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lifestyle=persona.get("lifestyle", ""),
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income=persona.get("income", ""),
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budget=persona.get("budget", ""),
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decision_timeline=persona.get("decision_timeline", ""),
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pains=pains_txt,
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levers=", ".join(persona.get("negotiation_levers", [])) or "price, delivery time",
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goal=persona.get("goal", ""),
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init_mode="you contacted the seller first (customer-initiated)"
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if persona.get("initiation_mode") == "customer"
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else "the seller opened the sale to you (you are a lead)",
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special_instr=self._special_instr(persona),
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)
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msgs = [{"role": "system", "content": system}]
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# send a compact recap of internal state to the persona ad
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# (doesn't leak to trainee)
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msgs.append({
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"role": "system",
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"content": "Internal state (for your role-play only): "
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+ json.dumps(internal, ensure_ascii=False),
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})
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msgs.extend(messages[-30:]) # context window
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try:
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resp = self.llm.complete_conversation(msgs, temperature=0.7, max_tokens=400)
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except LLMError as exc:
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raise
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# extract {reply: ...}
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try:
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data = json.loads(self._extract_json(resp))
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reply = data.get("reply") or data.get("response") or str(resp)
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except Exception:
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reply = resp
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return reply.strip()
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# ── judge ──────────────────────────────────────────────────────────
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def judge(
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self,
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*,
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persona: dict[str, Any],
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messages: list[dict[str, str]],
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) -> dict[str, Any]:
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persona_summary = json.dumps({
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"name": persona.get("name"),
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"pains": persona.get("pains", []),
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"budget": persona.get("budget"),
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"negotiation_levers": persona.get("negotiation_levers"),
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"special": persona.get("special"),
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}, ensure_ascii=False)
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transcript = "\n".join(
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f"{m.get('role')}: {m.get('text')}" for m in messages[-40:]
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)
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user_prompt = f"PERSONA:\n{persona_summary}\n\nTRANSCRIPT:\n{transcript}"
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try:
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result = self.judge_llm.complete_json(
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JUDGE_SYSTEM, user_prompt, temperature=0.2, max_tokens=2000
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)
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except LLMError as exc:
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raise
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result.setdefault("outcome", "lost")
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result.setdefault("score", 0)
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result.setdefault("pain", "")
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result.setdefault("why", "")
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result.setdefault("failurePoints", [])
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result.setdefault("coaching", [])
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result.setdefault("painProgress", {})
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return result
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# ── helpers ────────────────────────────────────────────────────────
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def _describe_pains(self, pains: list[Any]) -> str:
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if not pains:
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return "(you have some personal frustrations, but the seller must find out)"
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out = []
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for p in pains:
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if isinstance(p, dict):
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out.append(
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f"{p.get('name','pain')} (fit={p.get('fit','?')}): {p.get('description','')} "
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f"root={p.get('rootCause','')}"
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)
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else:
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out.append(str(p))
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return "; ".join(out)
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def _special_instr(self, persona: dict[str, Any]) -> str:
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if persona.get("special") == "wrong_text":
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return (
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"SPECIAL: You opened as if ready to buy, but the moment the seller replies you act "
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"disinterested and try to end the chat (e.g. 'never mind, forget it'). Deep down your "
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"pain is still real. A seller who gently re-engages without pushing may earn a second "
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"chance; a pushy seller drives you away for good."
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)
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return ""
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def _extract_json(self, text: str) -> str:
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text = text.strip()
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start = text.find("{")
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end = text.rfind("}")
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if start != -1 and end != -1 and end > start:
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return text[start : end + 1]
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return text
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