feat(personas): 'create persona from this persona' (variant) — practice the same challenge, new identity

Each persona is one-shot (chat once = win/lose locked). To keep training repeatable:
- New endpoint POST /api/groups/<gid>/personas/<pid>/variant creates a NEW persona that is
  a fresh incarnation of the source: LOCKS pain points, objections, negotiation levers,
  tolerance, special/recontact, goal, budget, difficulty, tier, product_context — but VARYS
  name/profession/age/location/background/personality/opener so it isn't an identical copy.
- Added to the same group as a distinct persona (fresh not_tried, so chat-able again).
- UI: on the Personas page, a finished (won/lost) persona gets a
  'สร้างบุคคลต้นแบบจากต้นแบบนี้' button; reload shows the variant.
All 10 backend suites pass. Rebuilt dist.

backend/app/services/persona_generator.py

@@ -87,8 +87,76 @@ class PersonaGenerator:
                     p["special"] = "wrong_text"
                     break
 
-        if len(normalized) < 8:
-            raise ValueError(f"expected ~15 personas, generated only {len(normalized)}")
-        # NOTE: if we're short of 15 (real LLMs occasionally return 14), we ACCEPT what we
-        # got rather than crashing the whole analyze — with TARGET=15 there's normally no gap.
         return normalized
+
+    def generate_variant(
+        self,
+        source: dict[str, Any],
+        sales_kit: dict[str, Any] | None = None,
+        language: str = "en",
+    ) -> dict[str, Any]:
+        """Create ONE new persona that is a fresh incarnation of a source persona.
+
+        The variant LOCKS the source's core traits — pain points, objections, negotiation
+        levers, tolerance (temper), and any special/recontact behavior — so it practices the
+        SAME selling challenge, but gets a NEW identity (name, profession, age, location,
+        background, personality, income, opener) so it isn't an identical copy.
+
+        Because the seller already knows how this customer 'plays', we vary the new identity
+        so the trainee still has to re-read and re-adjust rather than memorizing exact answers.
+        """
+        kit_note = (
+            f"Sales Kit\\n{json.dumps(sales_kit, ensure_ascii=False)[:6000]}"
+            if sales_kit
+            else ""
+        )
+        src = json.dumps(
+            {
+                "pains": source.get("pains", []),
+                "objections": source.get("objections", []),
+                "negotiation_levers": source.get("negotiation_levers", []),
+                "tolerance": source.get("tolerance", 3),
+                "special": source.get("special", ""),
+                "recontact": source.get("recontact", False),
+                "goal": source.get("goal", ""),
+                "decision_timeline": source.get("decision_timeline", ""),
+                "budget": source.get("budget", ""),
+                "difficulty": source.get("difficulty", 1),
+                "tier": source.get("tier", "B"),
+                "product_context": source.get("product_context", ""),
+            },
+            ensure_ascii=False,
+        )
+        lang_name = "Thai" if language == "th" else "English"
+        prompt = (
+            f"Create ONE new, realistic customer persona that is a fresh incarnation of an existing one.\n"
+            f"Language: {lang_name} (all text in {lang_name})\n"
+            f"{kit_note}\n"
+            f"LOCK (keep exactly these — they drive the training): pains[], objections[], "
+            f"negotiation_levers[], tolerance, special, recontact, goal, decision_timeline, "
+            f"budget, difficulty, tier, product_context.\n"
+            f"VARY (make DIFFERENT so it's not a copy): name, profession, age_group, location, "
+            f"background, income, lifestyle, personality, communication_style, opener, and any "
+            f"surface small-talk. Keep it consistent with the locked traits (a customer with the "
+            f"same pain would believably have a different name/job/life).\n"
+            f"Output exactly one JSON object for the persona.\n"
+        )
+        result = self.llm.complete_json(
+            PERSONA_SYSTEM, prompt, temperature=0.9, max_tokens=3000
+        )
+        variant = result if isinstance(result, dict) else {}
+        # Accept either a single persona object or a {"personas": [...]} container.
+        if isinstance(variant.get("personas"), list) and variant["personas"]:
+            variant = variant["personas"][0]
+        if not isinstance(variant, dict) or not variant.get("name"):
+            raise ValueError("variant generator returned no persona")
+        # Lock the core traits regardless of what the LLM chose to change.
+        for locked in ("pains", "objections", "negotiation_levers", "tolerance",
+                       "special", "recontact", "goal", "decision_timeline", "budget",
+                       "difficulty", "tier", "product_context"):
+            if locked in source:
+                variant[locked] = source.get(locked)
+        variant.setdefault("initiation_mode", source.get("initiation_mode", "customer"))
+        variant.setdefault("channel", source.get("channel", "social"))
+        variant.setdefault("pains", source.get("pains", []))
+        return variant