c92400b195
Removed the fixed-value text detector. persona_reply no longer forces JSON meta; instead a per-turn evaluate_turn() calls the judge LLM after every customer reply to read the persona's current mood + whether it has decided (buy/walk/pending) + score_delta + reason. send_message consumes that context-based decision to (a) end the chat as won/lost and (b) move the score. This is what the user asked: the system evaluates EVERY turn and decides at the moment it's truly committed — not keyword matching (so 'ซื้อไม่ไหว แต่ว่ามีผ่อนไหม?' stays pending). Mock updated: judge returns buy on first send (keeps E2E deterministic). 11/11 suites pass.
401 lines
17 KiB
Python
401 lines
17 KiB
Python
"""Chat/session API: start a one-shot session, send messages, finish + debrief."""
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from __future__ import annotations
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from flask import Blueprint, jsonify, request
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from ..llm import LLMError
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from ..services.simulator import Simulator
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from .helpers import ApiError, current_user, require_auth, require_roles
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chat_bp = Blueprint("chat", __name__)
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def _stores():
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from flask import current_app
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return {
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"groups": current_app.extensions["group_store"],
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"sessions": current_app.extensions["session_store"],
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"llm": current_app.extensions["llm"],
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}
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def _sim(group, persona):
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llm = _stores()["llm"]
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if not llm:
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raise ApiError("LLM not configured", 500)
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return Simulator(llm)
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def _scenarios(locale: str = "th"):
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"""Scenario presets, localized. Returns {id: {label, init, adapt}}."""
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t = locale != "en"
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return {
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"social": {
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"label": "Social Media" if not t else "Social Media (แชท)",
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"init": "customer",
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"preamble": "💬 Social messaging — the customer messaged you first." if not t else "💬 ช่องทางข้อความโซเชียล — ลูกค้าทักมาหาคุณก่อน (โทนสั้น ทักๆ)",
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"adapt": (
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"Chat style: short, casual, quick social-messaging replies. The customer opened."
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if not t
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else "ลูกค้าทักมาหาคุณก่อน — โทนสั้น ทักๆ ตามสไตล์แชทโซเชียล"
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),
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},
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"f2f_call": {
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"label": "Face-to-face / Phone" if not t else "พบหน้า / โทรศัพท์",
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"init": "seller",
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"preamble": "📞 Face-to-face / phone — you must proactively open with this lead." if not t else "📞 สถานการณ์ พบหน้าหรือโทรศัพท์ — คุณต้องเป็นฝ่ายเปิดการสนทนาเชิงรุกกับลีด",
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"adapt": (
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"Natural, conversational like a live face-to-face or phone sales talk. The seller opens."
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if not t
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else "คุณต้องเป็นฝ่ายเปิดการสนทนาเชิงรุกกับลีด (ผู้ฝึกทักก่อน) โทนเหมือนคุยสด"
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),
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},
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}
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def _scenario_config(scenario: str, persona: dict, locale: str = "th"):
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cfg = _scenarios(locale).get(scenario, _scenarios(locale)["social"])
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return cfg, cfg["init"]
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def _build_abbrev_debrief(outcome: str, persona: dict, internal: dict, locale: str = "th") -> dict:
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"""Build a lightweight debrief from the persona's own decision + per-turn signals."""
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signals = internal.get("signals", [])
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en = locale == "en"
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turning_points = []
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for sig in signals:
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if sig.get("type") in ("annoy", "warm"):
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turn = sig.get("turn", "?")
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if sig.get("mood", 0) > 0:
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turning_points.append(
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f"Turn {turn}: customer warmed up" if en else f"รอบที่ {turn}: ลูกค้าเริ่มใจขึ้น"
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)
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else:
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turning_points.append(
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f"Turn {turn}: customer annoyed/hesitant" if en else f"รอบที่ {turn}: ลูกค้าเริ่มหงุดหงิด/ลังเล"
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)
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why = (
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("Customer decided to buy (pain resolved + offer accepted)" if en else "ลูกค้าตัดสินใจซื้อ (แก้ปัญหาและยอมรับข้อเสนอแล้ว)")
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if outcome == "won"
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else (
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"Customer decided not to buy — value not enough, or responses missed the need"
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if en
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else "ลูกค้าตัดสินใจไม่ซื้อ — ยังไม่เห็นคุณค่าพอ หรือการตอบไม่ตรงความต้องการ"
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)
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)
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coaching = (
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["Great job — the customer closed with you"] if en and outcome == "won"
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else ["ทำได้ดีมาก — ลูกค้าปิดการขายกับคุณ"] if outcome == "won"
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else (
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turning_points + ["Ask deeper about the need", "Handle objections more directly"]
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if en
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else turning_points + ["ลองถามความต้องการให้ลึกกว่าเดิม", "รับมือข้อโต้แย้งให้ตรงจุด"]
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)
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)
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return {
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"outcome": outcome,
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"score": 60 if outcome == "won" else 25,
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"pain": (persona.get("pains") or [{}])[0].get("description", "") if persona.get("pains") else "",
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"why": why,
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"failurePoints": [] if outcome == "won" else (
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["Failed to close the sale", "Customer walked away before deciding"]
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if en else ["ปิดการขายไม่สำเร็จ", "ลูกค้าถอยก่อนตัดสินใจซื้อ"]
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),
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"coaching": coaching,
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"turning_points": turning_points,
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"signals": signals,
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"revealed_persona": {
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"pains": persona.get("pains", []),
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"income": persona.get("income", ""),
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"personality": persona.get("personality", ""),
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"budget": persona.get("budget", ""),
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"negotiation_levers": persona.get("negotiation_levers", []),
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"opener": persona.get("opener", ""),
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"background": persona.get("background", ""),
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"tolerance": persona.get("tolerance", 3),
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},
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}
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def _get_ready_group(s, gid: str) -> dict:
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"""Org-scoped group access for trainees + require ready status (IDOR defense)."""
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group = s["groups"].get_or_none(gid)
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if not group or group.get("status") != "ready":
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raise ApiError("group not ready", 404)
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actor = current_user()
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# super_admin can access any; otherwise owner (for personal groups) + same org.
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owner = group.get("owner_user_id")
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if actor.get("role") != "super_admin":
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if owner and owner != actor["id"]:
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raise ApiError("permission denied", 403)
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if group.get("org_id") != actor.get("org_id"):
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raise ApiError("permission denied", 403)
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return group
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@chat_bp.post("/<gid>/personas/<pid>/chat/start")
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@require_auth
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@require_roles("user")
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def start_session(gid: str, pid: str):
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s = _stores()
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group = _get_ready_group(s, gid)
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persona = s["groups"].get_persona(gid, pid)
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if not persona:
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raise ApiError("persona not found", 404)
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actor = current_user()
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# Scenario chosen by the trainee at chat start (not baked into the persona).
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body = request.get_json(silent=True) or {}
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scenario = (body.get("scenario") or "social").strip().lower()
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if scenario not in ("social", "f2f_call"):
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scenario = "social"
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locale = (body.get("locale") or "th").strip().lower()
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if locale not in ("en", "th"):
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locale = "th"
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scenario_meta, init_mode = _scenario_config(scenario, persona, locale)
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# RESUME: if this user already has an ACTIVE (unfinished) session for this persona, keep
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# chatting it — do NOT create a new one and do NOT force re-picking the scenario.
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existing = s["sessions"].active_for_persona(actor["id"], pid)
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if existing and existing.get("group_id") == gid:
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return jsonify({
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"session": existing,
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"initiation_mode": existing.get("persona_meta", {}).get("initiation_mode") or "customer",
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"scenario": existing.get("scenario", scenario),
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"scenario_meta": _scenario_config(existing.get("scenario", scenario), persona, locale),
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})
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# One-shot: reject if already finished this persona
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try:
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session = s["sessions"].create(
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user_id=actor["id"], group_id=gid, persona_id=pid,
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persona_name=persona.get("name", "?"),
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persona_meta={
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"tier": persona.get("tier"),
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"initiation_mode": init_mode,
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"channel": persona.get("channel"),
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"scenario": scenario,
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"locale": locale,
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},
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)
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except ValueError as exc:
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raise ApiError(str(exc), 400)
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s["sessions"].update(
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session["id"],
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scenario=scenario,
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locale=locale,
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internal={**(session.get("internal") or {}), "turns": 0, "score": 50, "signals": []},
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)
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sim = _sim(group, persona)
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# Seed messages: localized scenario preamble, then customer opener for customer-first scenarios.
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seeded = list(session.get("messages", []))
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if scenario_meta.get("preamble"):
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seeded.append({"role": "system", "text": scenario_meta["preamble"]})
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if init_mode == "customer":
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opener = persona.get("opener") or "Hi, I saw your product and had a question."
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seeded.append({"role": "customer", "text": opener})
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s["sessions"].update(session["id"], messages=seeded)
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sess = s["sessions"].get(session["id"])
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return jsonify({
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"session": sess,
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"initiation_mode": init_mode,
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"scenario": scenario,
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"scenario_meta": scenario_meta,
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})
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@chat_bp.post("/<gid>/personas/<pid>/chat/send")
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@require_auth
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@require_roles("user")
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def send_message(gid: str, pid: str):
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s = _stores()
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actor = current_user()
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session = s["sessions"].active_for_persona(actor["id"], pid)
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if not session or session.get("group_id") != gid:
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raise ApiError("no active session for this persona", 404)
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data = request.get_json(silent=True) or {}
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text = (data.get("text") or "").strip()
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if not text:
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raise ApiError("message is empty")
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if len(text) > 2000:
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raise ApiError("message too long")
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# Protect LLM cost: per-user chat-send window.
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from ..services.rate_limit import check as ratelimit
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actor_rl = current_user()
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if not ratelimit("chat:user", actor_rl.get("id") or actor_rl.get("username") or "?", limit=30, window=60):
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raise ApiError("slow down — too many messages", 429)
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group = s["groups"].get_or_none(gid)
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persona = s["groups"].get_persona(gid, pid) if group else None
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if not group or not persona:
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raise ApiError("session context missing", 404)
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messages = list(session.get("messages", []))
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messages.append({"role": "seller", "text": text})
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scenario = session.get("scenario", "social") or "social"
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slocale = session.get("locale", "th") or "th"
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adapt = _scenarios(slocale).get(scenario, _scenarios(slocale)["social"]).get("adapt", "")
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sim = _sim(group, persona)
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try:
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reply, meta = sim.persona_reply(
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persona=persona,
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sales_kit=group.get("sales_kit") or {},
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messages=messages,
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internal=session.get("internal", {}),
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scenario=scenario,
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scenario_adapt=adapt,
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)
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except LLMError as exc:
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raise ApiError(f"LLM error: {exc}", 500)
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messages.append({"role": "customer", "text": reply})
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# Update internal state: track misses (poor answers) and mood trend.
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internal = session.get("internal", {}) or {}
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internal.setdefault("turns", 0)
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internal["turns"] = internal.get("turns", 0) + 1
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internal["signals"] = internal.get("signals", [])
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# Re-contact persona behavior: after enough info is exchanged (turn 2), the customer
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# goes quiet, a time-lapse system note is shown, and the customer re-engages warmer.
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if persona.get("recontact") and not internal.get("recontact_done") and internal["turns"] >= 2:
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unit = "สัปดาห์" if slocale != "en" else "weeks"
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sys_txt = (
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f"⏳ ผ่านไป 2-3 {unit} ... ลูกค้าที่เคยสอบถามไปเงียบไประยะหนึ่ง ตอนนี้กลับมาติดต่ออีกครั้ง (พร้อมตัดสินใจมากขึ้น)"
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if slocale != "en"
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else "⏳ 2-3 weeks later ... the customer who asked earlier went quiet; now they re-contact, more ready to decide."
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)
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messages.append({"role": "system", "text": sys_txt})
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internal["recontact_done"] = True
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# Save the time-lapse note immediately so the UI shows it even if send ends here.
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s["sessions"].update(session["id"], messages=messages, internal=internal)
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# Evaluate this turn via the (judge) LLM: how the persona feels + whether it has decided.
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# This is context-based (NOT fixed keywords), so e.g. "ซื้อไม่ไหว แต่ว่ามีผ่อนไหม?" stays
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# pending until the customer truly commits to (or abandons) the decision.
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turn_eval = sim.evaluate_turn(
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persona=persona, messages=messages, internal=internal
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)
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decision = turn_eval.get("decision", "pending")
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try:
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mood = int(turn_eval.get("mood", 0))
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except (TypeError, ValueError):
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mood = 0
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# Apply the judge's score delta to internal score trend.
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try:
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sd = int(turn_eval.get("score_delta", 0))
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except (TypeError, ValueError):
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sd = 0
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internal["score"] = max(0, min(100, int(internal.get("score", 50)) + sd))
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internal["last_reason"] = turn_eval.get("reason", "")
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# Track mood trend for debrief.
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if mood <= -1:
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internal["misses"] = internal.get("misses", 0) + 1
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internal["signals"].append({"turn": internal["turns"], "mood": mood, "type": "annoy"})
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elif mood >= 1:
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internal["signals"].append({"turn": internal["turns"], "mood": mood, "type": "warm"})
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if decision in ("buy", "walk"):
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outcome = "won" if decision == "buy" else "lost"
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debrief = _build_abbrev_debrief(outcome, persona, internal, slocale)
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s["sessions"].update(
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session["id"],
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status="finished",
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outcome=outcome,
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messages=messages,
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internal=internal,
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debrief=debrief,
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)
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return jsonify({
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"reply": reply,
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"messages": messages,
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"finished": True,
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"outcome": outcome,
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"debrief": debrief,
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"session": s["sessions"].get(session["id"]),
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})
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s["sessions"].update(session["id"], messages=messages, internal=internal)
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return jsonify({"reply": reply, "messages": messages})
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@chat_bp.post("/<gid>/personas/<pid>/chat/finish")
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@require_auth
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@require_roles("user")
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def finish_session(gid: str, pid: str):
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"""End the chat and produce the debrief via the judge-LLM (reveals latent fields)."""
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s = _stores()
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actor = current_user()
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session = s["sessions"].active_for_persona(actor["id"], pid)
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if not session or session.get("group_id") != gid:
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raise ApiError("no active session for this persona", 404)
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group = s["groups"].get_or_none(gid)
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persona = s["groups"].get_persona(gid, pid)
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sim = _sim(group, persona)
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messages = session.get("messages", [])
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try:
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verdict = sim.judge(
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persona=persona, messages=messages, internal=session.get("internal", {})
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)
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except LLMError as exc:
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raise ApiError(f"LLM error: {exc}", 500)
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outcome = "won" if verdict.get("outcome") == "won" else "lost"
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debrief = {
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**verdict,
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"revealed_persona": {
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"pains": persona.get("pains", []),
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"income": persona.get("income", ""),
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"personality": persona.get("personality", ""),
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"budget": persona.get("budget", ""),
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"negotiation_levers": persona.get("negotiation_levers", []),
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"opener": persona.get("opener", ""),
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"background": persona.get("background", ""),
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},
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}
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s["sessions"].update(
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session["id"],
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status="finished",
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outcome=outcome,
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debrief=debrief,
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internal=session.get("internal", {}),
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)
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return jsonify({"session": s["sessions"].get(session["id"]), "debrief": debrief})
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@chat_bp.get("/sessions")
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@require_auth
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def my_sessions():
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s = _stores()
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uid = current_user()["id"]
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sessions = s["sessions"].list_for_user(uid)
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return jsonify({"sessions": sessions})
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@chat_bp.get("/sessions/<sid>")
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@require_auth
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@require_roles("user")
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def get_session(sid: str):
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s = _stores()
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session = s["sessions"].get_or_none(sid)
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if not session or session.get("user_id") != current_user()["id"]:
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raise ApiError("session not found", 404)
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return jsonify({"session": session})
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@chat_bp.get("/<gid>/personas/<pid>/chat/resume")
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@require_auth
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@require_roles("user")
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def resume_session(gid: str, pid: str):
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"""Resume an active (unfinished) session for this persona so the trainee can continue."""
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s = _stores()
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actor = current_user()
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session = s["sessions"].active_for_persona(actor["id"], pid)
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if not session or session.get("group_id") != gid:
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raise ApiError("no active session for this persona", 404)
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return jsonify({"session": session, "scenario": session.get("scenario", "social")})
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