diff --git a/admin/dashboard/templates/contacts_management.html b/admin/dashboard/templates/contacts_management.html
index 0d53d1c..834a1a1 100644
--- a/admin/dashboard/templates/contacts_management.html
+++ b/admin/dashboard/templates/contacts_management.html
@@ -294,6 +294,26 @@
{% raw %}{{ item }}{% endraw %}
-
+
+ {% raw %}{{ item }}{% endraw %}
+ -
+
+
+ {% raw %}{{ item }}{% endraw %}
+ -
+
+
+ {% raw %}{{ item }}{% endraw %}
+ -
+
+
+ {% raw %}{{ item }}{% endraw %}
+ -
+
+
+ {% raw %}{{ item }}{% endraw %}
+ -
+
{% raw %}{{ item }}{% endraw %}
-
@@ -306,6 +326,8 @@
{% raw %}{{ item }}{% endraw %}
-
+ {% raw %}{{ ((memberContext.meta || {}).group_role) || '-' }}{% endraw %}
+ {% raw %}{{ ((memberContext.meta || {}).decision_profile) || '-' }}{% endraw %}
{% raw %}{{ item }}{% endraw %}
-
diff --git a/db/message_storage.py b/db/message_storage.py
index 22b9dd0..56d20ab 100644
--- a/db/message_storage.py
+++ b/db/message_storage.py
@@ -43,21 +43,39 @@ class MessageStorageDB(BaseDBOperator):
params = (hours_ago, group_id, min_content_length)
return self.execute_query(sql, params) or []
- def get_member_recent_messages(self, group_id: str, wxid: str, days: int = 30, limit: int = 200) -> List[Dict]:
+ def get_member_recent_messages(self, group_id: str, wxid: str, days: int = 30,
+ limit: int = 200, include_today: bool = True) -> List[Dict]:
"""获取指定群成员近期消息"""
- sql = """
- SELECT timestamp, sender, content, message_type
- FROM messages
- WHERE timestamp >= DATE_SUB(NOW(), INTERVAL %s DAY)
- AND group_id = %s
- AND sender = %s
- AND message_type IN (1, 49)
- AND CHAR_LENGTH(content) BETWEEN 2 AND 500
- AND content NOT LIKE '/%%'
- ORDER BY timestamp DESC
- LIMIT %s
- """
- results = self.execute_query(sql, (days, group_id, wxid, limit)) or []
+ if include_today:
+ sql = """
+ SELECT timestamp, sender, content, message_type
+ FROM messages
+ WHERE timestamp >= DATE_SUB(NOW(), INTERVAL %s DAY)
+ AND group_id = %s
+ AND sender = %s
+ AND message_type IN (1, 49)
+ AND CHAR_LENGTH(content) BETWEEN 2 AND 500
+ AND content NOT LIKE '/%%'
+ ORDER BY timestamp DESC
+ LIMIT %s
+ """
+ params = (days, group_id, wxid, limit)
+ else:
+ sql = """
+ SELECT timestamp, sender, content, message_type
+ FROM messages
+ WHERE timestamp >= DATE_SUB(CURDATE(), INTERVAL %s DAY)
+ AND timestamp < CURDATE()
+ AND group_id = %s
+ AND sender = %s
+ AND message_type IN (1, 49)
+ AND CHAR_LENGTH(content) BETWEEN 2 AND 500
+ AND content NOT LIKE '/%%'
+ ORDER BY timestamp DESC
+ LIMIT %s
+ """
+ params = (days, group_id, wxid, limit)
+ results = self.execute_query(sql, params) or []
return list(reversed(results))
def get_member_messages_since(self, group_id: str, wxid: str, since_time, limit: int = 200) -> List[Dict]:
@@ -122,6 +140,23 @@ class MessageStorageDB(BaseDBOperator):
"""
return self.execute_query(sql, (target_date, group_id, wxid, limit)) or []
+ def get_member_messages_for_group_date(self, group_id: str, target_date: str, limit: int = 5000) -> List[Dict]:
+ """获取群在某一天的全部文本消息"""
+ sql = """
+ SELECT timestamp, sender, content, message_type
+ FROM messages
+ WHERE DATE(timestamp) = %s
+ AND group_id = %s
+ AND sender IS NOT NULL
+ AND sender <> ''
+ AND message_type IN (1, 49)
+ AND CHAR_LENGTH(content) BETWEEN 2 AND 500
+ AND content NOT LIKE '/%%'
+ ORDER BY timestamp ASC
+ LIMIT %s
+ """
+ return self.execute_query(sql, (target_date, group_id, limit)) or []
+
def get_message_count_by_date(self, date: str) -> List[Dict]:
"""获取指定日期的消息统计"""
sql = """
diff --git a/plugins/member_context/config.toml b/plugins/member_context/config.toml
index 46974ef..413bfb8 100644
--- a/plugins/member_context/config.toml
+++ b/plugins/member_context/config.toml
@@ -12,21 +12,22 @@ request_timeout = 60
sample_days = 30
sample_message_limit = 80
refresh_limit_per_member = 200
-long_term_days = 365
+long_term_days = 60
long_term_message_limit = 600
-bootstrap_days = 365
+bootstrap_days = 60
bootstrap_message_limit = 600
incremental_message_limit = 80
incremental_recent_days = 7
recalibration_days = 30
daily_message_limit = 120
daily_digest_min_messages = 6
-max_daily_digests_per_run = 45
+max_daily_digests_per_run = 0
weekly_digest_limit = 16
monthly_digest_limit = 12
final_daily_limit = 8
final_weekly_limit = 6
final_monthly_limit = 6
+group_digest_days = 1
ai_min_member_messages = 12
active_member_hours = 72
min_member_messages = 3
diff --git a/plugins/member_context/digest_service.py b/plugins/member_context/digest_service.py
index 310a65a..87b8dfc 100644
--- a/plugins/member_context/digest_service.py
+++ b/plugins/member_context/digest_service.py
@@ -12,6 +12,7 @@ from db.contacts_db import ContactsDBOperator
from db.member_digest_db import MemberDigestDBOperator
from db.message_storage import MessageStorageDB
from plugins.member_context.prompt_builder import MemberContextPromptBuilder
+from utils.compress_chat_data import compress_chat_data
class MemberDigestService:
@@ -37,28 +38,47 @@ class MemberDigestService:
self.bootstrap_days = int(profile_config.get("bootstrap_days", 365))
self.daily_message_limit = int(profile_config.get("daily_message_limit", 120))
self.daily_digest_min_messages = int(profile_config.get("daily_digest_min_messages", 6))
- self.max_daily_digests_per_run = int(profile_config.get("max_daily_digests_per_run", 45))
+ self.max_daily_digests_per_run = int(profile_config.get("max_daily_digests_per_run", 0))
self.weekly_digest_limit = int(profile_config.get("weekly_digest_limit", 16))
self.monthly_digest_limit = int(profile_config.get("monthly_digest_limit", 12))
self.final_daily_limit = int(profile_config.get("final_daily_limit", 8))
self.final_weekly_limit = int(profile_config.get("final_weekly_limit", 6))
self.final_monthly_limit = int(profile_config.get("final_monthly_limit", 6))
+ self.group_digest_days = int(profile_config.get("group_digest_days", 1))
+
+ def ensure_recent_group_daily_digests(self, chatroom_id: str, days: Optional[int] = None,
+ force: bool = False) -> Dict:
+ days = days or self.group_digest_days
+ built_daily = 0
+ touched_members = set()
+
+ for offset in range(days):
+ target_date = (datetime.now() - timedelta(days=offset + 1)).strftime("%Y-%m-%d")
+ digests = self._build_group_daily_digests(chatroom_id, target_date, force=force)
+ for digest in digests:
+ self.digest_db.save_digest(digest)
+ built_daily += 1
+ touched_members.add(digest.get("wxid"))
+
+ return {
+ "built_daily": built_daily,
+ "touched_members": list(touched_members),
+ }
def ensure_member_digest_pipeline(self, chatroom_id: str, wxid: str, force: bool = False) -> Dict:
member = self.contacts_db.get_chatroom_member_info(chatroom_id, wxid) or {}
display_name = member.get("display_name") or member.get("nick_name") or wxid
- active_dates = self.message_db.get_member_active_dates(chatroom_id, wxid, days=self.bootstrap_days)
- if not active_dates:
+ daily_digests = self.digest_db.list_digests(chatroom_id, wxid, "daily", limit=400)
+ if not daily_digests:
return {
"display_name": display_name,
"daily_digests": [],
"weekly_digests": [],
"monthly_digests": [],
- "stats": {"daily": 0, "weekly": 0, "monthly": 0, "active_days": 0},
+ "stats": {"daily": 0, "weekly": 0, "monthly": 0, "active_days": 0, "built_daily": 0},
}
- built_daily = self._ensure_daily_digests(chatroom_id, wxid, display_name, active_dates, force=force)
built_weekly = self._ensure_weekly_digests(chatroom_id, wxid, display_name, force=force)
built_monthly = self._ensure_monthly_digests(chatroom_id, wxid, display_name, force=force)
@@ -75,45 +95,37 @@ class MemberDigestService:
"daily": len(daily_digests),
"weekly": len(weekly_digests),
"monthly": len(monthly_digests),
- "active_days": len(active_dates),
- "built_daily": built_daily,
+ "active_days": len(self.digest_db.list_digest_keys(chatroom_id, wxid, "daily")),
+ "built_daily": 0,
"built_weekly": built_weekly,
"built_monthly": built_monthly,
},
}
- def _ensure_daily_digests(self, chatroom_id: str, wxid: str, display_name: str,
- active_dates: List[Dict], force: bool = False) -> int:
- existing_keys = set(self.digest_db.list_digest_keys(chatroom_id, wxid, "daily"))
- built = 0
- processed = 0
- sorted_dates = sorted(active_dates, key=lambda item: str(item.get("message_date")))
- current_day = datetime.now().strftime("%Y-%m-%d")
-
- for item in sorted_dates:
- period_key = str(item.get("message_date"))
- msg_count = int(item.get("msg_count", 0))
- if msg_count < self.daily_digest_min_messages:
- continue
- if not force and period_key in existing_keys and period_key != current_day:
- continue
- messages = self.message_db.get_member_messages_on_date(
- chatroom_id, wxid, period_key, limit=self.daily_message_limit
- )
- if len(messages) < self.daily_digest_min_messages:
- continue
- digest = self._build_daily_digest(chatroom_id, wxid, display_name, period_key, messages)
- if digest:
- self.digest_db.save_digest(digest)
- built += 1
- processed += 1
- self.LOG.info(
- f"[成员交互摘要][日摘要] 完成: group={chatroom_id}, wxid={wxid}, "
- f"date={period_key}, messages={len(messages)}"
- )
- if not force and processed >= self.max_daily_digests_per_run:
- break
- return built
+ @staticmethod
+ def _normalize_profile_item(item: Dict) -> Dict:
+ normalized = {}
+ list_keys = {
+ "topics", "identity_clues", "skill_signals", "family_signals", "life_stage_signals",
+ "value_preferences", "habit_signals", "engagement_traits", "reply_taboos",
+ "representative_messages", "stable_topics", "identity_traits", "skill_profile",
+ "family_profile", "life_stage_profile", "value_profile", "stable_traits",
+ "habit_patterns", "reply_preferences", "long_term_topics", "long_term_reply_preferences",
+ "phase_state", "recent_state"
+ }
+ for key, value in item.items():
+ if key in list_keys:
+ if isinstance(value, list):
+ normalized[key] = [str(v).strip() for v in value if str(v).strip()]
+ elif value:
+ normalized[key] = [str(value).strip()]
+ else:
+ normalized[key] = []
+ elif isinstance(value, (int, float)):
+ normalized[key] = value
+ else:
+ normalized[key] = str(value).strip()
+ return normalized
def _ensure_weekly_digests(self, chatroom_id: str, wxid: str, display_name: str, force: bool = False) -> int:
daily_digests = self.digest_db.list_digests(chatroom_id, wxid, "daily", limit=400)
@@ -123,7 +135,7 @@ class MemberDigestService:
grouped[week_key].append(item)
existing_keys = set(self.digest_db.list_digest_keys(chatroom_id, wxid, "weekly"))
- current_week_key, _, _ = self._week_period_bounds(datetime.now().strftime("%Y-%m-%d"))
+ current_week_key, _, _ = self._week_period_bounds((datetime.now() - timedelta(days=1)).strftime("%Y-%m-%d"))
built = 0
for week_key, items in sorted(grouped.items()):
if len(items) < 2:
@@ -151,7 +163,7 @@ class MemberDigestService:
grouped[month_key].append(item)
existing_keys = set(self.digest_db.list_digest_keys(chatroom_id, wxid, "monthly"))
- current_month_key, _, _ = self._month_period_bounds(datetime.now().strftime("%Y-%m-%d"))
+ current_month_key, _, _ = self._month_period_bounds((datetime.now() - timedelta(days=1)).strftime("%Y-%m-%d"))
built = 0
for month_key, items in sorted(grouped.items()):
if len(items) < 2:
@@ -171,6 +183,83 @@ class MemberDigestService:
)
return built
+ def _build_group_daily_digests(self, chatroom_id: str, digest_date: str, force: bool = False) -> List[Dict]:
+ members = self.contacts_db.get_chatroom_member_list(chatroom_id) or []
+ member_name_map = {}
+ for member in members:
+ wxid = member.get("wxid")
+ if not wxid:
+ continue
+ member_name_map[wxid] = member.get("display_name") or member.get("nick_name") or wxid
+
+ messages = self.message_db.get_member_messages_for_group_date(chatroom_id, digest_date)
+ if not messages:
+ return []
+
+ sender_messages = defaultdict(list)
+ for msg in messages:
+ wxid = msg.get("sender")
+ if not wxid:
+ continue
+ sender_messages[wxid].append(msg)
+
+ candidate_wxids = [
+ wxid for wxid, items in sender_messages.items()
+ if len(items) >= self.daily_digest_min_messages
+ ]
+ if not candidate_wxids:
+ return []
+
+ pending_wxids = []
+ for wxid in candidate_wxids:
+ if not force and self.digest_db.get_digest(chatroom_id, wxid, "daily", digest_date):
+ continue
+ pending_wxids.append(wxid)
+ if not pending_wxids:
+ self.LOG.info(
+ f"[成员交互摘要][群日批处理] 跳过: group={chatroom_id}, date={digest_date}, "
+ f"reason=all_candidates_already_built, candidates={len(candidate_wxids)}"
+ )
+ return []
+
+ member_labels = [f"{wxid} | {member_name_map.get(wxid, wxid)}" for wxid in pending_wxids]
+ compact_chat = self._format_group_messages_optimized(messages, member_name_map)
+ try:
+ compact_chat = compress_chat_data(compact_chat)
+ except Exception as e:
+ self.LOG.warning(f"[成员交互摘要] 压缩群日消息失败: group={chatroom_id}, date={digest_date}, error={e}")
+
+ parsed_members = self._request_group_daily_json(chatroom_id, digest_date, member_labels, compact_chat)
+ parsed_map = {item.get("wxid"): item for item in parsed_members if item.get("wxid")} if parsed_members else {}
+
+ digests = []
+ for wxid in pending_wxids:
+ parsed = parsed_map.get(wxid) or self._build_daily_digest_fallback(sender_messages.get(wxid, []))
+ if not parsed:
+ continue
+ parsed = self._normalize_profile_item(parsed)
+ digests.append({
+ "chatroom_id": chatroom_id,
+ "wxid": wxid,
+ "digest_type": "daily",
+ "period_key": digest_date,
+ "period_start": f"{digest_date} 00:00:00",
+ "period_end": f"{digest_date} 23:59:59",
+ "display_name": member_name_map.get(wxid, wxid),
+ "source_count": len(sender_messages.get(wxid, [])),
+ "summary_text": parsed.get("summary_text", ""),
+ "structured": parsed,
+ "meta": {
+ "source_type": "group_daily_messages",
+ "representative_messages": parsed.get("representative_messages", []),
+ },
+ })
+ self.LOG.info(
+ f"[成员交互摘要][群日批处理] 完成: group={chatroom_id}, date={digest_date}, "
+ f"candidates={len(candidate_wxids)}, pending={len(pending_wxids)}, built={len(digests)}"
+ )
+ return digests
+
def _build_daily_digest(self, chatroom_id: str, wxid: str, display_name: str,
digest_date: str, messages: List[Dict]) -> Optional[Dict]:
prompt = MemberContextPromptBuilder.build_daily_digest_prompt(
@@ -256,6 +345,39 @@ class MemberDigestService:
self.LOG.warning(f"[成员交互摘要][AI] 摘要请求失败: group={chatroom_id}, wxid={wxid}, tag={tag}, error={e}")
return None
+ def _request_group_daily_json(self, chatroom_id: str, digest_date: str,
+ member_labels: List[str], compressed_chat: str) -> List[Dict]:
+ if not self.ai_enabled or not self.ai_base_url or not self.ai_api_key:
+ return []
+ prompt = MemberContextPromptBuilder.build_group_daily_digest_prompt(
+ chatroom_id, digest_date, member_labels, compressed_chat
+ )
+ headers = {
+ "Authorization": f"Bearer {self.ai_api_key}",
+ "Content-Type": "application/json",
+ }
+ payload = {
+ "inputs": {"query": prompt},
+ "response_mode": "blocking",
+ "user": f"member-digest:{chatroom_id}:group-daily:{digest_date}",
+ }
+ url = f"{self.ai_base_url}/{self.ai_endpoint}"
+ try:
+ self.LOG.info(
+ f"[成员交互摘要][AI] 发起群日批量摘要请求: group={chatroom_id}, "
+ f"date={digest_date}, members={len(member_labels)}"
+ )
+ response = requests.post(url, headers=headers, json=payload, timeout=self.ai_timeout)
+ response.raise_for_status()
+ data = response.json()
+ parsed = self._parse_group_daily_answer(data.get("answer", ""))
+ return parsed
+ except Exception as e:
+ self.LOG.warning(
+ f"[成员交互摘要][AI] 群日批量摘要失败: group={chatroom_id}, date={digest_date}, error={e}"
+ )
+ return []
+
def _parse_ai_answer(self, answer: str) -> Optional[Dict]:
if not answer:
return None
@@ -277,6 +399,29 @@ class MemberDigestService:
normalized[key] = str(value).strip()
return normalized
+ def _parse_group_daily_answer(self, answer: str) -> List[Dict]:
+ if not answer:
+ return []
+ text = answer.strip()
+ match = re.search(r"\{.*\}", text, re.S)
+ if match:
+ text = match.group(0)
+ try:
+ parsed = json.loads(text)
+ except Exception:
+ return []
+ members = parsed.get("members", [])
+ if not isinstance(members, list):
+ return []
+ normalized = []
+ for item in members:
+ if not isinstance(item, dict):
+ continue
+ normalized_item = self._normalize_profile_item(item)
+ if normalized_item.get("wxid"):
+ normalized.append(normalized_item)
+ return normalized
+
def _build_daily_digest_fallback(self, messages: List[Dict]) -> Optional[Dict]:
if not messages:
return None
@@ -288,11 +433,18 @@ class MemberDigestService:
message_pattern = "短句居多" if avg_len <= 16 else "表达较完整" if avg_len >= 35 else "表达中等长度"
return {
"topics": [],
+ "identity_clues": [],
+ "skill_signals": [],
+ "family_signals": [],
+ "life_stage_signals": [],
+ "value_preferences": [],
"interaction_style": "自然跟随式互动",
"message_pattern": message_pattern,
"response_style_hint": "保持简洁自然，先回应核心点",
"habit_signals": [],
"engagement_traits": [],
+ "decision_style": "",
+ "social_role": "",
"reply_taboos": [],
"temperament_signal": "当天样本有限，暂以中性沟通观察为主",
"summary_text": f"当日消息约{len(messages)}条，{message_pattern}。",
@@ -332,9 +484,16 @@ class MemberDigestService:
if digest_type == "weekly":
return {
"stable_topics": top_topics,
+ "identity_traits": [],
+ "skill_profile": [],
+ "family_profile": [],
+ "life_stage_profile": [],
+ "value_profile": [],
"stable_traits": top_traits,
"habit_patterns": top_habits,
"reply_preferences": top_reply,
+ "group_role": "",
+ "decision_profile": "",
"recent_state": top_topics[:3],
"temperament_tendency": temperament,
"summary_text": "本周沟通特征已按重复信号汇总。",
@@ -343,15 +502,53 @@ class MemberDigestService:
return {
"long_term_topics": top_topics,
+ "identity_traits": [],
+ "skill_profile": [],
+ "family_profile": [],
+ "life_stage_profile": [],
+ "value_profile": [],
"stable_traits": top_traits,
"habit_patterns": top_habits,
"long_term_reply_preferences": top_reply,
+ "group_role": "",
+ "decision_profile": "",
"phase_state": top_topics[:3],
"temperament_tendency": temperament,
"summary_text": "本月沟通特征已按周摘要汇总。",
"confidence": 0.5,
}
+ def _format_group_messages_optimized(self, messages: List[Dict], member_name_map: Dict[str, str]) -> str:
+ if not messages:
+ return ""
+ time_groups = defaultdict(lambda: defaultdict(list))
+ for msg in messages:
+ timestamp = msg.get("timestamp")
+ sender = msg.get("sender", "")
+ content = str(msg.get("content", "")).strip()
+ if not sender or not content:
+ continue
+ try:
+ dt = datetime.strptime(str(timestamp), "%Y-%m-%d %H:%M:%S")
+ except Exception:
+ dt = None
+ if not dt:
+ continue
+ time_key = dt.strftime("%H:%M")
+ sender_name = member_name_map.get(sender, sender)
+ time_groups[time_key][sender_name].append(content)
+
+ lines = []
+ for time_key in sorted(time_groups.keys()):
+ lines.append(f"【{time_key}】")
+ for sender_name, contents in time_groups[time_key].items():
+ for idx, content in enumerate(contents):
+ if idx == 0:
+ lines.append(f"{sender_name}：{content}")
+ else:
+ lines.append(f" {content}")
+ return "\n".join(lines)
+
@staticmethod
def _week_period_bounds(date_value: str) -> Tuple[str, str, str]:
target_date = datetime.strptime(str(date_value)[:10], "%Y-%m-%d")
diff --git a/plugins/member_context/prompt_builder.py b/plugins/member_context/prompt_builder.py
index 1b17d90..e5693a9 100644
--- a/plugins/member_context/prompt_builder.py
+++ b/plugins/member_context/prompt_builder.py
@@ -6,6 +6,58 @@ from typing import Dict, List
class MemberContextPromptBuilder:
"""成员分层画像提示词构建器"""
+ @staticmethod
+ def build_group_daily_digest_prompt(chatroom_id: str, digest_date: str,
+ member_labels: List[str], compressed_chat: str) -> str:
+ return (
+ "你是微信群后台的成员日观察批量提取器。\n"
+ "请基于给定的一天群聊记录，识别当天有参与发言的成员，并分别提取中性、克制的成员日观察摘要。\n"
+ "不要做心理诊断、隐私猜测、负面评价，不要输出未在候选名单中的成员。\n"
+ "你的输出将被后续系统按周、按月持续累积，因此优先提取可复用、可累计、可验证的行为信号，而不是一次性的情绪和玩笑。\n"
+ "输出严格 JSON，不要 markdown。\n"
+ "{"
+ "\"members\":["
+ "{"
+ "\"wxid\":\"成员wxid\","
+ "\"display_name\":\"成员显示名\","
+ "\"topics\":[\"主题1\"],"
+ "\"identity_clues\":[\"身份线索1\"],"
+ "\"skill_signals\":[\"技能信号1\"],"
+ "\"family_signals\":[\"家庭线索1\"],"
+ "\"life_stage_signals\":[\"阶段线索1\"],"
+ "\"value_preferences\":[\"价值偏好1\"],"
+ "\"interaction_style\":\"一句中文\","
+ "\"message_pattern\":\"一句中文\","
+ "\"response_style_hint\":\"一句中文\","
+ "\"habit_signals\":[\"信号1\"],"
+ "\"engagement_traits\":[\"特征1\"],"
+ "\"decision_style\":\"一句中文\","
+ "\"social_role\":\"一句中文，描述当天在群中的角色表现\","
+ "\"reply_taboos\":[\"避坑1\"],"
+ "\"temperament_signal\":\"一句中文，描述当天沟通倾向，必须克制\","
+ "\"summary_text\":\"一段不超过100字的日摘要\","
+ "\"representative_messages\":[\"原话1\",\"原话2\"],"
+ "\"confidence\":0.0"
+ "}"
+ "]"
+ "}\n"
+ "要求：\n"
+ "1. 只输出当天真正参与发言且能看出明确行为信号的成员；发言极少的人可以不输出。\n"
+ "2. 每个成员的 topics、identity_clues、skill_signals、family_signals、life_stage_signals、value_preferences、habit_signals、engagement_traits 最多4个，reply_taboos 最多3个。\n"
+ "3. representative_messages 只保留最能代表当天表达方式的短句，最多3条。\n"
+ "4. 必须严格使用候选成员列表中的 wxid 和显示名。\n"
+ "5. identity_clues、family_signals、life_stage_signals 只能写公开聊天中出现的线索，不可把弱线索写成确定事实。\n"
+ "6. skill_signals 重点提炼成员解决问题、提供信息、组织表达、专业能力等信号。\n"
+ "7. social_role 只描述当天在群里的角色表现，例如：问题提出者、信息补充者、气氛调节者、组织推进者。\n"
+ "8. topics 更偏向持续关注的话题方向；habit_signals 更偏向重复表达或互动习惯；engagement_traits 更偏向参与方式。\n"
+ "9. value_preferences 只记录公开表达出的偏好，如效率优先、成本敏感、谨慎验证、乐于助人，不要写抽象大词。\n"
+ "10. summary_text 应是后台观察摘要，不要写成对用户说的话。\n"
+ f"群ID: {chatroom_id}\n"
+ f"日期: {digest_date}\n"
+ "候选成员:\n" + "\n".join(member_labels[:80]) + "\n"
+ "压缩后的群聊记录:\n" + compressed_chat
+ )
+
@staticmethod
def build_daily_digest_prompt(chatroom_id: str, wxid: str, display_name: str,
digest_date: str, messages: List[Dict]) -> str:
@@ -20,14 +72,22 @@ class MemberContextPromptBuilder:
"你是微信群后台的成员日观察摘要生成器。\n"
"请仅基于给定的当日公开聊天记录，提取对后续互动有帮助的中性行为观察。\n"
"不要做人格诊断、隐私猜测、负面评价，不要脑补群外信息。\n"
+ "这些日观察会被后续系统按周、按月持续累积，所以应优先输出长期可验证的行为线索，而不是一次性情绪。\n"
"输出严格 JSON，不要 markdown。\n"
"{"
"\"topics\":[\"主题1\"],"
+ "\"identity_clues\":[\"身份线索1\"],"
+ "\"skill_signals\":[\"技能信号1\"],"
+ "\"family_signals\":[\"家庭线索1\"],"
+ "\"life_stage_signals\":[\"阶段线索1\"],"
+ "\"value_preferences\":[\"价值偏好1\"],"
"\"interaction_style\":\"一句中文\","
"\"message_pattern\":\"一句中文\","
"\"response_style_hint\":\"一句中文\","
"\"habit_signals\":[\"信号1\"],"
"\"engagement_traits\":[\"特征1\"],"
+ "\"decision_style\":\"一句中文\","
+ "\"social_role\":\"一句中文\","
"\"reply_taboos\":[\"避坑1\"],"
"\"temperament_signal\":\"一句中文，描述当天显露的沟通倾向，必须克制\","
"\"summary_text\":\"一段不超过100字的日摘要\","
@@ -35,9 +95,14 @@ class MemberContextPromptBuilder:
"\"confidence\":0.0"
"}\n"
"要求：\n"
- "1. topics 最多4个，habit_signals 最多4个，engagement_traits 最多4个，reply_taboos 最多3个。\n"
+ "1. topics、identity_clues、skill_signals、family_signals、life_stage_signals、value_preferences、habit_signals、engagement_traits 最多4个，reply_taboos 最多3个。\n"
"2. temperament_signal 只能写当日可观察到的沟通倾向，不可上升为长期性格判断。\n"
"3. representative_messages 保留最能代表当天风格的短句，最多3条。\n"
+ "4. identity_clues、family_signals、life_stage_signals 只能写线索，不可写成确定事实。\n"
+ "5. skill_signals 重点描述专业能力、工具熟练度、信息组织能力、问题解决能力等当天显露出的信号。\n"
+ "6. topics 尽量写持续关注方向，避免写一次性插话；habit_signals 只写当天已明显出现的表达或互动习惯。\n"
+ "7. value_preferences 只保留公开表达出的判断偏好，如效率优先、先验证再决策、重成本、重稳定。\n"
+ "8. summary_text 要像后台备注，不要像对话回复。\n"
f"成员: {display_name} ({wxid})\n"
f"群ID: {chatroom_id}\n"
f"日期: {digest_date}\n"
@@ -54,9 +119,16 @@ class MemberContextPromptBuilder:
"period_key": item.get("period_key"),
"summary_text": item.get("summary_text", ""),
"topics": structured.get("topics") or structured.get("stable_topics") or structured.get("long_term_topics") or [],
+ "identity_clues": structured.get("identity_clues") or structured.get("identity_traits") or [],
+ "skill_signals": structured.get("skill_signals") or structured.get("skill_profile") or [],
+ "family_signals": structured.get("family_signals") or structured.get("family_profile") or [],
+ "life_stage_signals": structured.get("life_stage_signals") or structured.get("life_stage_profile") or [],
+ "value_preferences": structured.get("value_preferences") or structured.get("value_profile") or [],
"habit_signals": structured.get("habit_signals") or structured.get("habit_patterns") or [],
"engagement_traits": structured.get("engagement_traits") or structured.get("stable_traits") or [],
"reply_preferences": structured.get("reply_preferences") or structured.get("long_term_reply_preferences") or [],
+ "social_role": structured.get("social_role") or structured.get("group_role") or "",
+ "decision_style": structured.get("decision_style") or structured.get("decision_profile") or "",
"temperament_signal": structured.get("temperament_signal") or structured.get("temperament_tendency") or "",
"recent_state": structured.get("recent_state") or [],
}
@@ -66,9 +138,16 @@ class MemberContextPromptBuilder:
schema = (
"{"
"\"stable_topics\":[\"主题1\"],"
+ "\"identity_traits\":[\"身份特征1\"],"
+ "\"skill_profile\":[\"技能画像1\"],"
+ "\"family_profile\":[\"家庭线索1\"],"
+ "\"life_stage_profile\":[\"阶段线索1\"],"
+ "\"value_profile\":[\"价值偏好1\"],"
"\"stable_traits\":[\"特征1\"],"
"\"habit_patterns\":[\"习惯1\"],"
"\"reply_preferences\":[\"偏好1\"],"
+ "\"group_role\":\"一句中文\","
+ "\"decision_profile\":\"一句中文\","
"\"recent_state\":[\"状态1\"],"
"\"temperament_tendency\":\"一句中文\","
"\"summary_text\":\"一段不超过120字的周摘要\","
@@ -80,9 +159,16 @@ class MemberContextPromptBuilder:
schema = (
"{"
"\"long_term_topics\":[\"主题1\"],"
+ "\"identity_traits\":[\"身份特征1\"],"
+ "\"skill_profile\":[\"技能画像1\"],"
+ "\"family_profile\":[\"家庭线索1\"],"
+ "\"life_stage_profile\":[\"阶段线索1\"],"
+ "\"value_profile\":[\"价值偏好1\"],"
"\"stable_traits\":[\"特征1\"],"
"\"habit_patterns\":[\"习惯1\"],"
"\"long_term_reply_preferences\":[\"偏好1\"],"
+ "\"group_role\":\"一句中文\","
+ "\"decision_profile\":\"一句中文\","
"\"phase_state\":[\"状态1\"],"
"\"temperament_tendency\":\"一句中文\","
"\"summary_text\":\"一段不超过140字的月摘要\","
@@ -100,6 +186,10 @@ class MemberContextPromptBuilder:
"1. 所有列表字段最多5项，必须中性克制。\n"
"2. 只有多个下级摘要反复出现的特征，才允许写进 stable_traits / habit_patterns / long_term_reply_preferences。\n"
"3. recent_state / phase_state 只描述当前阶段状态，不要冒充长期人格。\n"
+ "4. identity_traits、family_profile、life_stage_profile 只能保留反复出现的公开线索，不可编造事实。\n"
+ "5. skill_profile 要优先提炼稳定出现的能力、专业方向、擅长处理的问题类型。\n"
+ "6. group_role 描述其在群中的长期角色位置，decision_profile 描述其决策与判断风格。\n"
+ "7. value_profile 需要优先保留真正反复出现的判断偏好，如效率优先、成本敏感、风险谨慎、愿意分享。\n"
f"成员: {display_name} ({wxid})\n"
f"群ID: {chatroom_id}\n"
f"周期: {period_key}\n"
@@ -125,9 +215,16 @@ class MemberContextPromptBuilder:
"\"response_style_hint\":\"一句中文\","
"\"topics_of_interest\":[\"主题1\"],"
"\"recent_focus\":[\"近期主题1\"],"
+ "\"identity_traits\":[\"身份线索1\"],"
+ "\"skill_profile\":[\"技能画像1\"],"
+ "\"family_profile\":[\"家庭线索1\"],"
+ "\"life_stage_profile\":[\"阶段线索1\"],"
+ "\"value_profile\":[\"价值偏好1\"],"
"\"stable_traits\":[\"长期特征1\"],"
"\"habit_patterns\":[\"习惯1\"],"
"\"long_term_reply_preferences\":[\"偏好1\"],"
+ "\"group_role\":\"一句中文\","
+ "\"decision_profile\":\"一句中文\","
"\"recent_state\":[\"近期状态1\"],"
"\"temperament_tendency\":\"一句中文\","
"\"summary_text\":\"一段不超过150字的后台摘要\","
@@ -139,6 +236,10 @@ class MemberContextPromptBuilder:
"1. stable_traits、habit_patterns、long_term_reply_preferences 只从月级和多次重复证据中提取。\n"
"2. recent_focus、recent_state 更依赖最近周级和日级。\n"
"3. summary_text 要像后台备注，不要明显暴露在给用户做画像。\n"
+ "4. identity_traits、family_profile、life_stage_profile 必须写成公开线索或长期观察，不得伪造事实。\n"
+ "5. skill_profile 要尽量覆盖专业能力、问题解决能力、表达组织能力、资源协调能力等维度。\n"
+ "6. group_role 要描述其在群中的角色定位，decision_profile 要描述其决策/判断方式。\n"
+ "7. 如果月级与周级证据不足，宁可少写，也不要把短期状态写成长期人格。\n"
f"成员: {display_name} ({wxid})\n"
f"群ID: {chatroom_id}\n"
"月级摘要:\n" + ("\n".join(monthly_lines) or "暂无")
diff --git a/plugins/member_context/service.py b/plugins/member_context/service.py
index 580ec1c..a4b7775 100644
--- a/plugins/member_context/service.py
+++ b/plugins/member_context/service.py
@@ -67,7 +67,8 @@ class MemberContextService:
self.min_group_messages = int(schedule_config.get("min_group_messages", 20))
def build_member_context(self, chatroom_id: str, wxid: str, days: Optional[int] = None,
- limit: Optional[int] = None, force_digest_rebuild: bool = False) -> Dict:
+ limit: Optional[int] = None, force_digest_rebuild: bool = False,
+ ensure_group_daily: bool = True) -> Dict:
days = days or self.sample_days
limit = limit or self.refresh_limit_per_member
@@ -75,6 +76,11 @@ class MemberContextService:
member = self.contacts_db.get_chatroom_member_info(chatroom_id, wxid) or {}
display_name = member.get("display_name") or member.get("nick_name") or wxid
+ group_digest_stats = {"built_daily": 0, "touched_members": []}
+ if ensure_group_daily:
+ group_digest_stats = self.digest_service.ensure_recent_group_daily_digests(
+ chatroom_id, force=force_digest_rebuild
+ )
digest_snapshot = self.digest_service.ensure_member_digest_pipeline(
chatroom_id, wxid, force=force_digest_rebuild
)
@@ -82,7 +88,13 @@ class MemberContextService:
weekly_digests = digest_snapshot.get("weekly_digests", [])
monthly_digests = digest_snapshot.get("monthly_digests", [])
- recent_messages = self.message_db.get_member_recent_messages(chatroom_id, wxid, days=min(days, 7), limit=120)
+ recent_messages = self.message_db.get_member_recent_messages(
+ chatroom_id,
+ wxid,
+ days=min(days, 7),
+ limit=120,
+ include_today=False,
+ )
monthly_structured = [item.get("structured", {}) or {} for item in monthly_digests]
weekly_structured = [item.get("structured", {}) or {} for item in weekly_digests]
daily_structured = [item.get("structured", {}) or {} for item in daily_digests]
@@ -113,6 +125,26 @@ class MemberContextService:
"source_days": days,
"last_profiled_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
"meta": {
+ "identity_traits": self._extract_scored_items(
+ monthly_structured + weekly_structured + daily_structured,
+ ["identity_traits", "identity_clues"], limit=5
+ ),
+ "skill_profile": self._extract_scored_items(
+ monthly_structured + weekly_structured + daily_structured,
+ ["skill_profile", "skill_signals"], limit=6
+ ),
+ "family_profile": self._extract_scored_items(
+ monthly_structured + weekly_structured + daily_structured,
+ ["family_profile", "family_signals"], limit=4
+ ),
+ "life_stage_profile": self._extract_scored_items(
+ monthly_structured + weekly_structured + daily_structured,
+ ["life_stage_profile", "life_stage_signals"], limit=4
+ ),
+ "value_profile": self._extract_scored_items(
+ monthly_structured + weekly_structured + daily_structured,
+ ["value_profile", "value_preferences"], limit=5
+ ),
"stable_traits": self._extract_scored_items(
monthly_structured + weekly_structured, ["stable_traits", "engagement_traits"], limit=self.stable_max_items
),
@@ -130,6 +162,14 @@ class MemberContextService:
monthly_structured + weekly_structured + daily_structured,
["temperament_tendency", "temperament_signal"], default=""
),
+ "group_role": self._best_text(
+ monthly_structured + weekly_structured + daily_structured,
+ ["group_role", "social_role"], default=""
+ ),
+ "decision_profile": self._best_text(
+ monthly_structured + weekly_structured + daily_structured,
+ ["decision_profile", "decision_style"], default=""
+ ),
"engagement_traits": self._extract_scored_items(
daily_structured + weekly_structured, ["engagement_traits", "stable_traits"], limit=4
),
@@ -144,7 +184,7 @@ class MemberContextService:
"last_daily_digest_at": daily_digests[0].get("last_generated_at") if daily_digests else "",
"last_weekly_digest_at": weekly_digests[0].get("last_generated_at") if weekly_digests else "",
"last_monthly_digest_at": monthly_digests[0].get("last_generated_at") if monthly_digests else "",
- "refresh_mode": self._build_refresh_mode(existing_context, digest_snapshot),
+ "refresh_mode": self._build_refresh_mode(existing_context, digest_snapshot, group_digest_stats),
},
}
@@ -214,6 +254,13 @@ class MemberContextService:
f"days={days}, limit_per_member={limit_per_member}"
)
+ group_digest_stats = self.digest_service.ensure_recent_group_daily_digests(chatroom_id)
+ self.LOG.info(
+ f"[成员交互摘要] 群日摘要批处理完成: group={chatroom_id}, "
+ f"built_daily={group_digest_stats.get('built_daily', 0)}, "
+ f"touched_members={len(group_digest_stats.get('touched_members', []))}"
+ )
+
for index, active_member in enumerate(active_members, start=1):
wxid = active_member.get("wxid")
if wxid not in enabled_members:
@@ -231,7 +278,9 @@ class MemberContextService:
f"last_profiled_at={(existing_context or {}).get('last_profiled_at')}"
)
continue
- context = self.build_member_context(chatroom_id, wxid, days=days, limit=limit_per_member)
+ context = self.build_member_context(
+ chatroom_id, wxid, days=days, limit=limit_per_member, ensure_group_daily=False
+ )
if context["source_message_count"] <= 0 and context.get("meta", {}).get("digest_daily_count", 0) <= 0:
skipped += 1
self.LOG.debug(
@@ -329,7 +378,8 @@ class MemberContextService:
WHERE group_id = %s
AND sender IS NOT NULL
AND sender <> ''
- AND timestamp >= DATE_SUB(NOW(), INTERVAL %s HOUR)
+ AND timestamp >= DATE_SUB(CURDATE(), INTERVAL %s HOUR)
+ AND timestamp < CURDATE()
AND message_type IN (1, 49)
GROUP BY sender
HAVING COUNT(*) >= %s
@@ -384,7 +434,8 @@ class MemberContextService:
SELECT group_id, COUNT(*) AS msg_count
FROM messages
WHERE group_id LIKE %s
- AND timestamp >= DATE_SUB(NOW(), INTERVAL %s HOUR)
+ AND timestamp >= DATE_SUB(CURDATE(), INTERVAL %s HOUR)
+ AND timestamp < CURDATE()
GROUP BY group_id
HAVING COUNT(*) >= %s
"""
@@ -473,9 +524,16 @@ class MemberContextService:
"summary_text": str(data.get("summary_text", "")).strip(),
"confidence": max(0.0, min(1.0, confidence)),
"meta": {
+ "identity_traits": norm_list(data.get("identity_traits"), 5),
+ "skill_profile": norm_list(data.get("skill_profile"), 6),
+ "family_profile": norm_list(data.get("family_profile"), 4),
+ "life_stage_profile": norm_list(data.get("life_stage_profile"), 4),
+ "value_profile": norm_list(data.get("value_profile"), 5),
"stable_traits": norm_list(data.get("stable_traits"), self.stable_max_items),
"habit_patterns": norm_list(data.get("habit_patterns"), self.stable_max_items),
"long_term_reply_preferences": norm_list(data.get("long_term_reply_preferences"), 4),
+ "group_role": str(data.get("group_role", "")).strip(),
+ "decision_profile": str(data.get("decision_profile", "")).strip(),
"recent_state": norm_list(data.get("recent_state"), 4),
"temperament_tendency": str(data.get("temperament_tendency", "")).strip(),
"engagement_traits": norm_list(data.get("engagement_traits"), 4),
@@ -510,6 +568,31 @@ class MemberContextService:
meta.get("habit_patterns", []),
current_context.get("confidence", 0),
)
+ merged_identity_scores = self._merge_scored_items(
+ existing_meta.get("identity_trait_scores", {}),
+ meta.get("identity_traits", []),
+ current_context.get("confidence", 0) * 0.75,
+ )
+ merged_skill_scores = self._merge_scored_items(
+ existing_meta.get("skill_profile_scores", {}),
+ meta.get("skill_profile", []),
+ current_context.get("confidence", 0) * 0.85,
+ )
+ merged_family_scores = self._merge_scored_items(
+ existing_meta.get("family_profile_scores", {}),
+ meta.get("family_profile", []),
+ current_context.get("confidence", 0) * 0.55,
+ )
+ merged_life_stage_scores = self._merge_scored_items(
+ existing_meta.get("life_stage_profile_scores", {}),
+ meta.get("life_stage_profile", []),
+ current_context.get("confidence", 0) * 0.65,
+ )
+ merged_value_scores = self._merge_scored_items(
+ existing_meta.get("value_profile_scores", {}),
+ meta.get("value_profile", []),
+ current_context.get("confidence", 0) * 0.75,
+ )
merged_reply_pref_scores = self._merge_scored_items(
existing_meta.get("long_term_reply_preference_scores", {}),
meta.get("long_term_reply_preferences", []),
@@ -524,13 +607,35 @@ class MemberContextService:
meta["topic_scores"] = merged_topic_scores
meta["stable_trait_scores"] = merged_trait_scores
meta["habit_pattern_scores"] = merged_habit_scores
+ meta["identity_trait_scores"] = merged_identity_scores
+ meta["skill_profile_scores"] = merged_skill_scores
+ meta["family_profile_scores"] = merged_family_scores
+ meta["life_stage_profile_scores"] = merged_life_stage_scores
+ meta["value_profile_scores"] = merged_value_scores
meta["long_term_reply_preference_scores"] = merged_reply_pref_scores
meta["temperament_tendency_scores"] = merged_temperament_scores
+ meta["identity_traits"] = self._top_scored_items(merged_identity_scores, limit=5)
+ meta["skill_profile"] = self._top_scored_items(merged_skill_scores, limit=6)
+ meta["family_profile"] = self._top_scored_items(merged_family_scores, limit=4)
+ meta["life_stage_profile"] = self._top_scored_items(merged_life_stage_scores, limit=4)
+ meta["value_profile"] = self._top_scored_items(merged_value_scores, limit=5)
meta["stable_traits"] = self._top_scored_items(merged_trait_scores, limit=self.stable_max_items)
meta["habit_patterns"] = self._top_scored_items(merged_habit_scores, limit=self.stable_max_items)
meta["long_term_reply_preferences"] = self._top_scored_items(merged_reply_pref_scores, limit=4)
temperament = self._top_scored_items(merged_temperament_scores, limit=1)
meta["temperament_tendency"] = temperament[0] if temperament else meta.get("temperament_tendency", "")
+ if not meta["identity_traits"]:
+ meta["identity_traits"] = (existing_meta.get("identity_traits") or [])[:5]
+ if not meta["skill_profile"]:
+ meta["skill_profile"] = (existing_meta.get("skill_profile") or [])[:6]
+ if not meta["family_profile"]:
+ meta["family_profile"] = (existing_meta.get("family_profile") or [])[:4]
+ if not meta["life_stage_profile"]:
+ meta["life_stage_profile"] = (existing_meta.get("life_stage_profile") or [])[:4]
+ if not meta["value_profile"]:
+ meta["value_profile"] = (existing_meta.get("value_profile") or [])[:5]
+ meta["group_role"] = meta.get("group_role") or existing_meta.get("group_role") or ""
+ meta["decision_profile"] = meta.get("decision_profile") or existing_meta.get("decision_profile") or ""
meta["engagement_traits"] = (meta.get("engagement_traits") or existing_meta.get("engagement_traits") or [])[:4]
meta["reply_taboos"] = (meta.get("reply_taboos") or existing_meta.get("reply_taboos") or [])[:3]
meta["recent_state"] = (meta.get("recent_state") or existing_meta.get("recent_state") or [])[:4]
@@ -611,9 +716,12 @@ class MemberContextService:
def _sum_digest_source_count(daily_digests: List[Dict]) -> int:
return sum(int(item.get("source_count", 0)) for item in daily_digests)
- def _build_refresh_mode(self, existing_context: Optional[Dict], digest_snapshot: Dict) -> str:
+ def _build_refresh_mode(self, existing_context: Optional[Dict], digest_snapshot: Dict,
+ group_digest_stats: Optional[Dict] = None) -> str:
if not existing_context:
return "bootstrap"
+ if (group_digest_stats or {}).get("built_daily", 0) > 0:
+ return "daily_rollup"
if (digest_snapshot.get("stats", {}) or {}).get("built_monthly", 0) > 0:
return "recalibration"
return "incremental"
@@ -626,6 +734,12 @@ class MemberContextService:
parts.append(f"{label}：{meta.get('temperament_tendency')}")
if meta.get("stable_traits"):
parts.append(f"长期特征：{'、'.join(meta.get('stable_traits')[:3])}")
+ if meta.get("identity_traits"):
+ parts.append(f"身份线索：{'、'.join(meta.get('identity_traits')[:2])}")
+ if meta.get("skill_profile"):
+ parts.append(f"技能画像：{'、'.join(meta.get('skill_profile')[:3])}")
+ if meta.get("value_profile"):
+ parts.append(f"判断偏好：{'、'.join(meta.get('value_profile')[:2])}")
if meta.get("habit_patterns"):
parts.append(f"习惯模式：{'、'.join(meta.get('habit_patterns')[:3])}")
if meta.get("recent_state"):