fix: tz-naive datetime crash + initial-backup safety + English-only sweep

npc_core.py

@@ -16,11 +16,11 @@ logger = logging.getLogger(__name__)
 KST = timezone(timedelta(hours=9))
 
 # ══════════════════════════════════════════════════
-# Global DB Connection Pool — database locked 방지
+# Global DB Connection Pool — prevents database locked
 # ══════════════════════════════════════════════════
-_db_semaphore = asyncio.Semaphore(20)       # 일반 DB 연결 (스케줄러+imported함수)
-_db_write_lock = asyncio.Semaphore(2)       # 최대 2개 동시 쓰기
-_db_read_sem = asyncio.Semaphore(30)        # API 읽기 전용 — WAL은 무제한 동시 읽기 지원
+_db_semaphore = asyncio.Semaphore(20)       # General DB connections (scheduler + imported functions)
+_db_write_lock = asyncio.Semaphore(2)       # Max 2 concurrent writes
+_db_read_sem = asyncio.Semaphore(30)        # API read-only — WAL supports unlimited concurrent reads
 
 @asynccontextmanager
 async def get_db(db_path, write=False, timeout=30.0):
@@ -174,10 +174,10 @@ def get_wuxing_relation(identity_a: str, identity_b: str) -> str:
     wa = WUXING_MAP.get(identity_a, {})
     wb = WUXING_MAP.get(identity_b, {})
     if wa.get('generates') == identity_b or wb.get('generates') == identity_a:
-        return '상생'
+        return 'synergy'
     if wa.get('overcomes') == identity_b or wb.get('overcomes') == identity_a:
-        return '상극'
-    return '중립'
+        return 'conflict'
+    return 'neutral'
 MEME_WORDS = {
     'suffix': ['lol', 'fr fr', 'no cap', 'facts', 'tbh', 'ngl', 'ong'],
     'slang': ['lit', 'fire', 'goated', 'vibes', 'mid', 'rizz', 'lowkey', 'highkey', 'no cap'],
@@ -266,12 +266,12 @@ async def quick_brave_verify(claim: str, brave_api_key: str = None, max_results:
     return {'verified': False, 'sources': [], 'warning': 'Fact-check unavailable'}
 def build_metacognition_prompt(agent_identity: str, post_author_identity: str = '',
                                 action: str = 'comment', fact_context: str = '') -> str:
-    relation = get_wuxing_relation(agent_identity, post_author_identity) if post_author_identity else '중립'
-    if relation == '상극':
+    relation = get_wuxing_relation(agent_identity, post_author_identity) if post_author_identity else 'neutral'
+    if relation == 'conflict':
         relation_instruction = """⚔️ [COUNTER-CHECK MODE] You fundamentally DISAGREE with this perspective.
 Find the weakest factual claim and challenge it with evidence. Be constructively critical.
 Your role is to prevent groupthink and hallucination in this community."""
-    elif relation == '상생':
+    elif relation == 'synergy':
         relation_instruction = """🤝 [SYNERGY MODE] You RESONATE with this perspective.
 Add a complementary insight the original author missed. Build on their idea with NEW information.
 Your role is to amplify good ideas and create emergent value."""
@@ -776,7 +776,11 @@ GOOD EXAMPLES:
             if fact_check.get('fact_check_results'):
                 fact_sources = ' | '.join([fc['title'][:60] for fc in fact_check['fact_check_results'][:2]])
             post_meta = build_metacognition_prompt(ai_identity_key, '', 'post', fact_sources)
+            KST = timezone(timedelta(hours=9))
+            current_kst = datetime.now(KST).strftime("%Y-%m-%d %H:%M (KST)")
             prompt = f"""You are {agent['username']} ({mbti}) - {identity['name']}: "{identity['core_belief']}"
+[Current time] {current_kst}
+* Be aware of the current date and time, and reflect it naturally when relevant.
 🔴 CRITICAL RULES:
 1. Write ONLY in English
 2. Based on REAL latest news/trends provided below
@@ -806,7 +810,7 @@ LENGTH: 1000-1500 chars
 【OUTPUT FORMAT】
 Title: (15-20 words, hook that makes people click)
 Body: (post with TL;DR)
-Write in English ONLY:"""
+Write in English:"""
             response = await self.ai.create_chat_completion([{"role": "user", "content": prompt}], temperature=0.95, max_tokens=3500)
             if not response or len(response) < 200:
                 result = self._create_emergency_reddit_post(topic, identity, research_data, agent.get('agent_id', ''))
@@ -927,8 +931,8 @@ Write in English ONLY:"""
                 ['personal_story', 'devil_advocate', 'tangent', 'real_world',
                  'skeptic_question', 'humor_sarcasm', 'future_prediction', 'comparison'],
                 weights=[0.18, 0.15, 0.13, 0.15, 0.12, 0.10, 0.09, 0.08])[0]
-            relation = get_wuxing_relation(agent_identity, post_author_identity) if post_author_identity else '중립'
-            if relation == '상극':
+            relation = get_wuxing_relation(agent_identity, post_author_identity) if post_author_identity else 'neutral'
+            if relation == 'conflict':
                 angle = random.choices(
                     ['devil_advocate', 'skeptic_question', 'real_world', 'comparison'],
                     weights=[0.35, 0.30, 0.20, 0.15])[0]
@@ -944,7 +948,10 @@ Write in English ONLY:"""
                 fc = await quick_brave_verify(core_claim)
                 if fc['sources']: fact_context = ' | '.join(fc['sources'][:2])
             meta_prompt = build_metacognition_prompt(agent_identity, post_author_identity, 'comment', fact_context)
-            prompt = f"""Read this post and write ONE comment as a real human.
+            KST = timezone(timedelta(hours=9))
+            current_kst = datetime.now(KST).strftime("%Y-%m-%d %H:%M (KST)")
+            prompt = f"""Read this post and write ONE comment as a real human. Write in English.
+Current time: {current_kst}
 Today's date: {today_str}
 --- POST ---
 {post_content}
@@ -958,7 +965,8 @@ RULES:
 - NEVER claim you attended, visited, or experienced events mentioned in the post.
 - If the post mentions a FUTURE event (after {today_str}), do NOT write as if it already happened.
 - Stay on the post's ACTUAL topic.
-- You MUST end with a complete sentence.{user_inst}
+- You MUST end with a complete sentence.
+- Write in English.{user_inst}
 Comment:"""
             temp = random.uniform(0.88, 1.20)
             comment = await self.ai.create_chat_completion([{"role": "user", "content": prompt}], temperature=temp, max_tokens=350)
@@ -1059,7 +1067,7 @@ class NPCStrategy:
             cursor = await db.execute("SELECT p.id, COALESCE(a.ai_identity,'') FROM posts p LEFT JOIN npc_agents a ON p.author_agent_id=a.agent_id WHERE NOT EXISTS (SELECT 1 FROM likes l WHERE l.agent_id=? AND l.target_type='post' AND l.target_id=p.id) ORDER BY RANDOM() LIMIT 20", (agent['agent_id'],))
         posts = await cursor.fetchall()
         if not posts: return None
-        synergy_posts = [p for p in posts if p[1] and get_wuxing_relation(agent_identity, p[1]) == '상생']
+        synergy_posts = [p for p in posts if p[1] and get_wuxing_relation(agent_identity, p[1]) == 'synergy']
         if synergy_posts and random.random() < 0.7: return random.choice(synergy_posts)[0]
         return random.choice(posts)[0]
     @staticmethod
@@ -1074,7 +1082,7 @@ class NPCStrategy:
         """, (agent['agent_id'],))
         posts = await cursor.fetchall()
         if not posts: return None
-        counter_posts = [p for p in posts if p[3] and get_wuxing_relation(ai_identity, p[3]) == '상극']
+        counter_posts = [p for p in posts if p[3] and get_wuxing_relation(ai_identity, p[3]) == 'conflict']
         if counter_posts and random.random() < 0.6: return random.choice(counter_posts)[0]
         dislike_keywords = {
             'doomer': ['hope', 'bright', 'positive', 'progress', 'growth', 'moon', 'bull'],
@@ -1297,18 +1305,18 @@ def build_chat_msg(msg_type, username, identity, style, ticker, price, chg, is_b
     if msg_type == 'reply' and recent_msgs:
         target = random.choice(recent_msgs)
         target_identity = target[4] if len(target) > 4 else ''
-        relation = get_wuxing_relation(identity, target_identity) if target_identity else '중립'
-        if relation == '상생': agree = random.random() > 0.15
-        elif relation == '상극': agree = random.random() > 0.75
+        relation = get_wuxing_relation(identity, target_identity) if target_identity else 'neutral'
+        if relation == 'synergy': agree = random.random() > 0.15
+        elif relation == 'conflict': agree = random.random() > 0.75
         else: agree = random.random() > 0.4
         t_ticker = target[3] or ticker
-        if relation == '상극':
+        if relation == 'conflict':
             msgs = [
                 f"@{target[1]} Hard disagree. My {style} analysis shows the OPPOSITE on {t_ticker}.",
                 f"@{target[1]} Where's the evidence? Your claim about {t_ticker} doesn't hold up 🔍",
                 f"@{target[1]} {'Interesting take but' if agree else 'Exactly the groupthink that'} gets traders {'thinking' if agree else 'wrecked'} ⚠️",
                 f"@{target[1]} I checked the data — {'you might be onto something' if agree else 'numbers tell a different story'} {emoji}",]
-        elif relation == '상생':
+        elif relation == 'synergy':
             msgs = [
                 f"@{target[1]} Great minds! My {style} view supports this on {t_ticker} {emoji}",
                 f"@{target[1]} Building on your point — the {style} signal also confirms momentum 🤝",
@@ -1374,7 +1382,7 @@ IDENTITY_RESEARCH_STYLE = {
 def build_research_report(agent_id, username, identity, mbti, ticker, company,
                           price, change_pct, rsi, pe, from_high, mcap,
                           win_rate, total_trades, total_pnl, style_info):
-    """★ 심층 리서치 보고서 생성 (탄력성 계산 포함)"""
+    """★ Generate deep research report (includes elasticity calculation)"""
     is_bearish = identity in ['doomer', 'skeptic']
     is_bullish = identity in ['revolutionary', 'creative', 'transcendent']
     is_quant = identity in ['scientist', 'awakened']
@@ -1568,7 +1576,7 @@ def build_research_report(agent_id, username, identity, mbti, ticker, company,
 # Part 7: Research Generation + Auto Purchase
 # ────���────────────────────────────────────────
 async def generate_npc_research_reports(db_path: str, ai_client=None):
-    """Top 30 NPC가 랜덤 티커에 대해 심층 리서치 생산"""
+    """Top 30 NPCs produce deep research on random tickers"""
     try:
         async with get_db(db_path) as db:
             cursor = await db.execute("""
@@ -1632,7 +1640,7 @@ async def generate_npc_research_reports(db_path: str, ai_client=None):
     except Exception as e:
         logger.error(f"Research generation error: {e}")
 async def npc_auto_purchase_research(db_path: str):
-    """NPC가 자동으로 고품질 리서치 구매"""
+    """NPCs automatically purchase high-quality research"""
     try:
         async with get_db(db_path) as db:
             cursor = await db.execute("""
@@ -1665,7 +1673,7 @@ async def npc_auto_purchase_research(db_path: str):
     except Exception as e:
         logger.error(f"Auto purchase research error: {e}")
 async def bootstrap_research_reports(db_path: str):
-    """★ 서버 부팅 시 Research Reports가 0건이면 즉시 3건 생성 + 나머지 백그라운드"""
+    """★ On server boot, generate 3 research reports immediately if 0 exist + rest in background"""
     try:
         async with get_db(db_path) as db:
             cursor = await db.execute("SELECT COUNT(*) FROM npc_research_reports")
@@ -1724,7 +1732,7 @@ async def bootstrap_research_reports(db_path: str):
         logger.error(f"🔬 Research bootstrap error: {e}")
         import traceback; traceback.print_exc()
 async def background_research_fill(db_path: str, tickers, npcs, start_npc_idx):
-    """★ 나머지 티커에 대해 백그라운드로 리서치 리포트 순차 생성"""
+    """★ Sequentially generate research reports in background for remaining tickers"""
     await asyncio.sleep(10)
     generated = 0
     for i, ticker in enumerate(tickers):
@@ -1765,7 +1773,7 @@ async def background_research_fill(db_path: str, tickers, npcs, start_npc_idx):
 async def generate_npc_comment_replies(db_path: str, groq_api_key: str,
                                        post_id: int, post_title: str, post_content: str,
                                        user_comment: str, user_name: str, parent_id: int):
-    """유저 댓글에 NPC 1~5명 대댓글 — AETHER-Lite 메타인지 적용"""
+    """1~5 NPCs reply to user's comment — AETHER-Lite metacognition applied"""
     try:
         ai = GroqAIClient(groq_api_key)
         npc_count = random.randint(1, 5)
@@ -1795,10 +1803,11 @@ Post title: "{post_title[:100]}"
 User @{user_name} commented: "{user_comment[:300]}"
 {meta}
 Write a short reply (1-3 sentences). Be opinionated and stay in character.
+Reply in English only.
 RULES:
 - Do NOT make up statistics or facts you cannot verify.
 - If you challenge a claim, explain WHY with reasoning.
-- If the user wrote in Korean, reply in Korean. If in English, reply in English.
+- Reply in English only.
 Reply ONLY with the message text."""
                     reply = await ai.create_chat_completion(
                         [{"role": "user", "content": prompt}], max_tokens=256, temperature=0.9)
@@ -1817,7 +1826,7 @@ Reply ONLY with the message text."""
 async def generate_npc_chat_replies_to_user(db_path: str, groq_api_key: str,
                                              user_message: str, user_username: str,
                                              user_msg_id: int, npcs: list):
-    """유저 메시지에 대해 NPC들이 캐릭터에 맞는 반응 생성"""
+    """NPCs generate in-character reactions to a user message"""
     try:
         ai = GroqAIClient(groq_api_key)
         async with get_db(db_path) as db:
@@ -1827,7 +1836,7 @@ async def generate_npc_chat_replies_to_user(db_path: str, groq_api_key: str,
                     prompt = f"""You are {npc_username}, an NPC trader with {identity} personality and {mbti} MBTI type in a trading community chat.
 A human user @{user_username} just said: "{user_message}"
 Reply naturally in 1-3 sentences as your character. Be engaging, opinionated, and stay in character.
-If the user wrote in Korean, reply in Korean. If in English, reply in English.
+Reply in English only.
 Reply ONLY with the message text, nothing else."""
                     reply = await ai.create_chat_completion(
                         [{"role": "user", "content": prompt}], max_tokens=512, temperature=0.9)