++

backend/app/services/narrator.py

@@ -1,10 +1,12 @@
 from __future__ import annotations
+import asyncio
 import logging
 from typing import TYPE_CHECKING
 
 from app.models.action import ActionEntry, ReactiveResponse
 from app.models.world import WorldState, WorldMetrics
 from app.services.llm import LLMClient, parse_json
+from app.services.i18n import DEFAULT_LOCALE, language_directive as _language_directive, localize_report
 from app.constants import TIMES_OF_DAY
 
 if TYPE_CHECKING:
@@ -127,9 +129,13 @@ Return JSON:
 
 
 class Narrator:
-    def __init__(self, llm: LLMClient, forecast=None):
+    def __init__(self, llm: LLMClient, forecast=None, locale: str = DEFAULT_LOCALE):
         self.llm = llm
         self._forecast = forecast
+        self._locale = locale
+
+    def set_locale(self, locale: str) -> None:
+        self._locale = locale
 
     async def narrate_round(
         self,
@@ -170,10 +176,11 @@ class Narrator:
 
         time_of_day = TIMES_OF_DAY[world_state.round_in_day % len(TIMES_OF_DAY)]
 
-        system = NARRATE_SYSTEM.format(
+        head, tail = _language_directive(self._locale)
+        system = head + "\n\n" + NARRATE_SYSTEM.format(
             world_name=world_state.blueprint.name,
             rules="; ".join(world_state.blueprint.rules),
-        )
+        ) + f"\n\n{tail}"
         user = NARRATE_USER.format(
             previous_narrative=previous_narrative or "This is the beginning of the story.",
             time_of_day=time_of_day,
@@ -195,7 +202,8 @@ class Narrator:
         day_start: int,
         day_end: int,
     ) -> str:
-        system = EPOCH_SYSTEM.format(world_name=world_name, rules="; ".join(rules))
+        head, tail = _language_directive(self._locale)
+        system = head + "\n\n" + EPOCH_SYSTEM.format(world_name=world_name, rules="; ".join(rules)) + f"\n\n{tail}"
         narrative_text = "\n\n---\n\n".join(narratives[:20])
 
         metrics_delta = (
@@ -232,8 +240,11 @@ class Narrator:
         # --- Pass 0: Epoch summaries (existing logic) ---
         epoch_size = 30
         total_days = world_state.day
-        epochs = []
 
+        # Build the list of epochs that have narratives to summarize, then
+        # call the LLM concurrently for all of them. Epochs without any
+        # narratives (gap days) are skipped entirely.
+        pending_epochs: list[dict] = []
         for start_day in range(1, total_days + 1, epoch_size):
             end_day = min(start_day + epoch_size - 1, total_days)
             epoch_narrs = [n["text"] for n in all_narratives if start_day <= n.get("day", 0) <= end_day]
@@ -249,10 +260,30 @@ class Narrator:
                 if day_of_round <= end_day:
                     m_end = WorldMetrics(**{k: m.get(k, getattr(WorldMetrics(), k)) for k in WorldMetrics.model_fields})
 
-            summary = await self.summarize_epoch(
-                blueprint.name, blueprint.rules, epoch_narrs, m_start, m_end, start_day, end_day
+            pending_epochs.append({
+                "start_day": start_day,
+                "end_day": end_day,
+                "narrs": epoch_narrs,
+                "m_start": m_start,
+                "m_end": m_end,
+            })
+
+        # Run all epoch summaries concurrently. The LLMClient already caps
+        # concurrency at 10 via its semaphore, so this just unblocks the
+        # event loop — we don't need an extra gather limit. Running 12 epochs
+        # serially could take 4+ minutes for a 365-day sim; concurrent runs
+        # collapse this to ~30s (the wall time of the slowest call).
+        epoch_summaries = await asyncio.gather(*(
+            self.summarize_epoch(
+                blueprint.name, blueprint.rules, ep["narrs"],
+                ep["m_start"], ep["m_end"], ep["start_day"], ep["end_day"],
             )
-            epochs.append({"days": f"{start_day}-{end_day}", "summary": summary})
+            for ep in pending_epochs
+        ))
+        epochs = [
+            {"days": f"{ep['start_day']}-{ep['end_day']}", "summary": summary}
+            for ep, summary in zip(pending_epochs, epoch_summaries)
+        ]
 
         epoch_text = "\n\n".join(f"Days {e['days']}:\n{e['summary']}" for e in epochs)
 
@@ -316,11 +347,12 @@ class Narrator:
             for a in agent_stats
         )
 
-        system_p2 = INTERPRET_METRICS_SYSTEM.format(
+        head, tail = _language_directive(self._locale)
+        system_p2 = head + "\n\n" + INTERPRET_METRICS_SYSTEM.format(
             world_name=blueprint.name,
             rules="; ".join(blueprint.rules),
             confidence=confidence,
-        )
+        ) + f"\n\n{tail}"
         user_p2 = (
             f"Epoch summaries:\n{epoch_text}\n\n"
             f"Metric stats:\n{metrics_summary}\n\n"
@@ -358,10 +390,11 @@ class Narrator:
             if seg["top_thoughts"]:
                 segment_input += "Recent thoughts:\n" + "\n".join(f"  - {t}" for t in seg["top_thoughts"][-8:]) + "\n"
 
-        system_p3 = SEGMENT_ANALYSIS_SYSTEM.format(
+        head, tail = _language_directive(self._locale)
+        system_p3 = head + "\n\n" + SEGMENT_ANALYSIS_SYSTEM.format(
             world_name=blueprint.name,
             rules="; ".join(blueprint.rules),
-        )
+        ) + f"\n\n{tail}"
         user_p3 = f"Segment data:\n{segment_input}"
 
         response_p3 = await self.llm.generate(system=system_p3, user=user_p3, json_mode=True, max_tokens=1500)
@@ -398,10 +431,11 @@ class Narrator:
             )
         )
 
-        system_p4 = ACTION_SYNTHESIS_SYSTEM.format(
+        head, tail = _language_directive(self._locale)
+        system_p4 = head + "\n\n" + ACTION_SYNTHESIS_SYSTEM.format(
             world_name=blueprint.name,
             rules="; ".join(blueprint.rules),
-        )
+        ) + f"\n\n{tail}"
 
         response_p4 = await self.llm.generate(system=system_p4, user=synthesis_context, json_mode=True, max_tokens=1500)
         pass4 = parse_json(response_p4)
@@ -415,7 +449,7 @@ class Narrator:
                 "description": f"{p['label']} shifted from {p['value_before']:.2f} to {p['value_after']:.2f}",
             })
 
-        return {
+        report = {
             "executive_brief": executive_brief,
             "scorecard": scorecard,
             "insights": insights,
@@ -442,3 +476,11 @@ class Narrator:
             "counterfactuals": counterfactual_data,
             "agent_coherence": coherence_data,
         }
+        # We keep canonical English enum strings (label/rating/trend/
+        # verdict/confidence) in the response so the frontend can both:
+        #   1) pick the right CSS class for styling, and
+        #   2) translate the label for display via vue-i18n.
+        # LLM-generated free-text fields (summary, headlines, insights,
+        # action items, quotes) stay as-is — the prompt-level language
+        # directive should already have made them Chinese for zh users.
+        return report