mirror of https://github.com/Mai-with-u/MaiBot.git
remove：人格的兴趣配置项移动到planner prompt中
SengokuCola
parent
910c73be73
commit
a0ba073cfb
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@ -0,0 +1,304 @@
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"""
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统计和展示 replyer 动作选择记录
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用法:
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python scripts/replyer_action_stats.py
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"""
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import json
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import os
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import sys
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from collections import Counter, defaultdict
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from datetime import datetime
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from typing import Dict, List, Any
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from pathlib import Path
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# Add project root to Python path
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project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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sys.path.insert(0, project_root)
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try:
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from src.common.database.database_model import ChatStreams
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from src.chat.message_receive.chat_stream import get_chat_manager
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except ImportError:
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ChatStreams = None
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get_chat_manager = None
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def get_chat_name(chat_id: str) -> str:
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"""根据 chat_id 获取聊天名称"""
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try:
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if ChatStreams:
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chat_stream = ChatStreams.get_or_none(ChatStreams.stream_id == chat_id)
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if chat_stream:
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if chat_stream.group_name:
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return f"{chat_stream.group_name}"
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elif chat_stream.user_nickname:
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return f"{chat_stream.user_nickname}的私聊"
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if get_chat_manager:
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chat_manager = get_chat_manager()
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stream_name = chat_manager.get_stream_name(chat_id)
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if stream_name:
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return stream_name
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return f"未知聊天 ({chat_id[:8]}...)"
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except Exception:
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return f"查询失败 ({chat_id[:8]}...)"
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def load_records(temp_dir: str = "data/temp") -> List[Dict[str, Any]]:
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"""加载所有 replyer 动作记录"""
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records = []
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temp_path = Path(temp_dir)
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if not temp_path.exists():
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print(f"目录不存在: {temp_dir}")
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return records
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# 查找所有 replyer_action_*.json 文件
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pattern = "replyer_action_*.json"
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for file_path in temp_path.glob(pattern):
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try:
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with open(file_path, "r", encoding="utf-8") as f:
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data = json.load(f)
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records.append(data)
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except Exception as e:
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print(f"读取文件失败 {file_path}: {e}")
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# 按时间戳排序
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records.sort(key=lambda x: x.get("timestamp", ""))
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return records
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def format_timestamp(ts: str) -> str:
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"""格式化时间戳"""
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try:
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dt = datetime.fromisoformat(ts)
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return dt.strftime("%Y-%m-%d %H:%M:%S")
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except Exception:
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return ts
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def calculate_time_distribution(records: List[Dict[str, Any]]) -> Dict[str, int]:
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"""计算时间分布"""
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now = datetime.now()
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distribution = {
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"今天": 0,
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"昨天": 0,
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"3天内": 0,
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"7天内": 0,
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"30天内": 0,
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"更早": 0,
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}
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for record in records:
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try:
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ts = record.get("timestamp", "")
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if not ts:
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continue
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dt = datetime.fromisoformat(ts)
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diff = (now - dt).days
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if diff == 0:
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distribution["今天"] += 1
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elif diff == 1:
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distribution["昨天"] += 1
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elif diff < 3:
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distribution["3天内"] += 1
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elif diff < 7:
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distribution["7天内"] += 1
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elif diff < 30:
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distribution["30天内"] += 1
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else:
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distribution["更早"] += 1
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except Exception:
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pass
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return distribution
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def print_statistics(records: List[Dict[str, Any]]):
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"""打印统计信息"""
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if not records:
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print("没有找到任何记录")
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return
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print("=" * 80)
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print("Replyer 动作选择记录统计")
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print("=" * 80)
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print()
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# 总记录数
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total_count = len(records)
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print(f"📊 总记录数: {total_count}")
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print()
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# 时间范围
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timestamps = [r.get("timestamp", "") for r in records if r.get("timestamp")]
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if timestamps:
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first_time = format_timestamp(min(timestamps))
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last_time = format_timestamp(max(timestamps))
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print(f"📅 时间范围: {first_time} ~ {last_time}")
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print()
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# 按 think_level 统计
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think_levels = [r.get("think_level", 0) for r in records]
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think_level_counter = Counter(think_levels)
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print("🧠 思考深度分布:")
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for level in sorted(think_level_counter.keys()):
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count = think_level_counter[level]
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percentage = (count / total_count) * 100
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level_name = {0: "不需要思考", 1: "简单思考", 2: "深度思考"}.get(level, f"未知({level})")
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print(f" Level {level} ({level_name}): {count} 次 ({percentage:.1f}%)")
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print()
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# 按 chat_id 统计（总体）
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chat_counter = Counter([r.get("chat_id", "未知") for r in records])
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print(f"💬 聊天分布 (共 {len(chat_counter)} 个聊天):")
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# 只显示前10个
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for chat_id, count in chat_counter.most_common(10):
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chat_name = get_chat_name(chat_id)
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percentage = (count / total_count) * 100
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print(f" {chat_name}: {count} 次 ({percentage:.1f}%)")
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if len(chat_counter) > 10:
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print(f" ... 还有 {len(chat_counter) - 10} 个聊天")
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print()
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# 每个 chat_id 的详细统计
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print("=" * 80)
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print("每个聊天的详细统计")
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print("=" * 80)
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print()
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# 按 chat_id 分组记录
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records_by_chat = defaultdict(list)
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for record in records:
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chat_id = record.get("chat_id", "未知")
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records_by_chat[chat_id].append(record)
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# 按记录数排序
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sorted_chats = sorted(records_by_chat.items(), key=lambda x: len(x[1]), reverse=True)
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for chat_id, chat_records in sorted_chats:
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chat_name = get_chat_name(chat_id)
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chat_count = len(chat_records)
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chat_percentage = (chat_count / total_count) * 100
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print(f"📱 {chat_name} ({chat_id[:8]}...)")
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print(f" 总记录数: {chat_count} ({chat_percentage:.1f}%)")
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# 该聊天的 think_level 分布
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chat_think_levels = [r.get("think_level", 0) for r in chat_records]
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chat_think_counter = Counter(chat_think_levels)
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print(" 思考深度分布:")
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for level in sorted(chat_think_counter.keys()):
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level_count = chat_think_counter[level]
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level_percentage = (level_count / chat_count) * 100
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level_name = {0: "不需要思考", 1: "简单思考", 2: "深度思考"}.get(level, f"未知({level})")
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print(f" Level {level} ({level_name}): {level_count} 次 ({level_percentage:.1f}%)")
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# 该聊天的时间范围
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chat_timestamps = [r.get("timestamp", "") for r in chat_records if r.get("timestamp")]
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if chat_timestamps:
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first_time = format_timestamp(min(chat_timestamps))
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last_time = format_timestamp(max(chat_timestamps))
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print(f" 时间范围: {first_time} ~ {last_time}")
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# 该聊天的时间分布
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chat_time_dist = calculate_time_distribution(chat_records)
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print(" 时间分布:")
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for period, count in chat_time_dist.items():
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if count > 0:
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period_percentage = (count / chat_count) * 100
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print(f" {period}: {count} 次 ({period_percentage:.1f}%)")
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# 显示该聊天最近的一条理由示例
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if chat_records:
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latest_record = chat_records[-1]
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reason = latest_record.get("reason", "无理由")
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if len(reason) > 120:
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reason = reason[:120] + "..."
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timestamp = format_timestamp(latest_record.get("timestamp", ""))
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think_level = latest_record.get("think_level", 0)
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print(f" 最新记录 [{timestamp}] (Level {think_level}): {reason}")
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print()
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# 时间分布
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time_dist = calculate_time_distribution(records)
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print("⏰ 时间分布:")
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for period, count in time_dist.items():
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if count > 0:
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percentage = (count / total_count) * 100
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print(f" {period}: {count} 次 ({percentage:.1f}%)")
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print()
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# 显示一些示例理由
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print("📝 示例理由 (最近5条):")
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recent_records = records[-5:]
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for i, record in enumerate(recent_records, 1):
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reason = record.get("reason", "无理由")
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think_level = record.get("think_level", 0)
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timestamp = format_timestamp(record.get("timestamp", ""))
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chat_id = record.get("chat_id", "未知")
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chat_name = get_chat_name(chat_id)
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# 截断过长的理由
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if len(reason) > 100:
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reason = reason[:100] + "..."
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print(f" {i}. [{timestamp}] {chat_name} (Level {think_level})")
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print(f" {reason}")
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print()
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# 按 think_level 分组显示理由示例
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print("=" * 80)
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print("按思考深度分类的示例理由")
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print("=" * 80)
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print()
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for level in [0, 1, 2]:
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level_records = [r for r in records if r.get("think_level") == level]
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if not level_records:
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continue
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level_name = {0: "不需要思考", 1: "简单思考", 2: "深度思考"}.get(level, f"未知({level})")
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print(f"Level {level} ({level_name}) - 共 {len(level_records)} 条:")
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# 显示3个示例（选择最近的）
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examples = level_records[-3:] if len(level_records) >= 3 else level_records
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for i, record in enumerate(examples, 1):
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reason = record.get("reason", "无理由")
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if len(reason) > 150:
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reason = reason[:150] + "..."
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timestamp = format_timestamp(record.get("timestamp", ""))
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chat_id = record.get("chat_id", "未知")
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chat_name = get_chat_name(chat_id)
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print(f" {i}. [{timestamp}] {chat_name}")
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print(f" {reason}")
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print()
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# 统计信息汇总
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print("=" * 80)
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print("统计汇总")
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print("=" * 80)
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print(f"总记录数: {total_count}")
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print(f"涉及聊天数: {len(chat_counter)}")
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if chat_counter:
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avg_count = total_count / len(chat_counter)
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print(f"平均每个聊天记录数: {avg_count:.1f}")
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else:
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print("平均每个聊天记录数: N/A")
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print()
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def main():
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"""主函数"""
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records = load_records()
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print_statistics(records)
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if __name__ == "__main__":
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main()
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@ -311,7 +311,6 @@ class BrainChatting:
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current_available_actions=available_actions,
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chat_content_block=chat_content_block,
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message_id_list=message_id_list,
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interest=global_config.personality.interest,
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prompt_key="brain_planner_prompt_react",
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)
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continue_flag, modified_message = await events_manager.handle_mai_events(
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@ -40,7 +40,6 @@ def init_prompt():
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"""
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{time_block}
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{name_block}
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你的兴趣是：{interest}
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{chat_context_description}，以下是具体的聊天内容
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**聊天内容**
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@ -305,7 +304,6 @@ class BrainPlanner:
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current_available_actions=filtered_actions,
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chat_content_block=chat_content_block,
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message_id_list=message_id_list,
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interest=global_config.personality.interest,
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prompt_key=prompt_key,
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)
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@ -375,7 +375,6 @@ class HeartFChatting:
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current_available_actions=available_actions,
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chat_content_block=chat_content_block,
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message_id_list=message_id_list,
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interest=global_config.personality.interest,
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)
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continue_flag, modified_message = await events_manager.handle_mai_events(
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EventType.ON_PLAN, None, prompt_info[0], None, self.chat_stream.stream_id
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@ -36,7 +36,6 @@ def init_prompt():
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"""
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{time_block}
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{name_block}
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你的兴趣是：{interest}
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{chat_context_description}，以下是具体的聊天内容
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**聊天内容**
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{chat_content_block}
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@ -48,8 +47,8 @@ reply
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2.你可以自然的顺着正在进行的聊天内容进行回复或自然的提出一个问题
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3.不要回复你自己发送的消息
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4.不要单独对表情包进行回复
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5.think_level表示思考深度，0表示该回复不需要思考，1表示该回复需要简单思考，2表示该回复需要深度思考
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{{"action":"reply", "think_level":数值等级(0-2), "target_message_id":"消息id(m+数字)"}}
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5.think_level表示思考深度，0表示该回复不需要思考和回忆，2表示该回复需要深度思考，进行深入的回忆和思考
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{{"action":"reply", "think_level":数值等级(0-2), "target_messamge_id":"消息id(m+数字)"}}
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no_reply
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动作描述：
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@ -361,7 +360,6 @@ class ActionPlanner:
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current_available_actions=filtered_actions,
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chat_content_block=chat_content_block,
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message_id_list=message_id_list,
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interest=global_config.personality.interest,
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is_mentioned=is_mentioned,
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)
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@ -45,9 +45,6 @@ class PersonalityConfig(ConfigBase):
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reply_style: str = ""
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"""表达风格"""
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interest: str = ""
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"""兴趣"""
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plan_style: str = ""
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"""说话规则，行为风格"""
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@ -79,12 +76,6 @@ class ChatConfig(ConfigBase):
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max_context_size: int = 18
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"""上下文长度"""
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interest_rate_mode: Literal["fast", "accurate"] = "fast"
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"""兴趣值计算模式，fast为快速计算，accurate为精确计算"""
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planner_size: float = 1.5
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"""副规划器大小，越小，麦麦的动作执行能力越精细，但是消耗更多token，调大可以缓解429类错误"""
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mentioned_bot_reply: bool = True
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"""是否启用提及必回复"""
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@ -27,16 +27,14 @@ personality = "是一个女大学生，现在在读大二，会刷贴吧。"
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# 描述麦麦说话的表达风格，表达习惯，如要修改，可以酌情新增内容
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reply_style = "请回复的平淡一些，简短一些，说中文，不要刻意突出自身学科背景。可以参考贴吧，知乎和微博的回复风格。"
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# 麦麦的兴趣，会影响麦麦对什么话题进行回复
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interest = "对技术相关话题，游戏和动漫相关话题感兴趣，也对日常话题感兴趣，不喜欢太过沉重严肃的话题"
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# 麦麦的说话规则，行为风格:
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plan_style = """
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1.思考**所有**的可用的action中的**每个动作**是否符合当下条件，如果动作使用条件符合聊天内容就使用
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2.如果相同的内容已经被执行，请不要重复执行
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3.请控制你的发言频率，不要太过频繁的发言
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4.如果有人对你感到厌烦，请减少回复
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5.如果有人对你进行攻击，或者情绪激动，请你以合适的方法应对"""
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3.你对技术相关话题，游戏和动漫相关话题感兴趣，也对日常话题感兴趣，不喜欢太过沉重严肃的话题
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4.请控制你的发言频率，不要太过频繁的发言
|
||||
5.如果有人对你感到厌烦，请减少回复
|
||||
6.如果有人对你进行攻击，或者情绪激动，请你以合适的方法应对"""
|
||||
|
||||
# 麦麦识图规则，不建议修改
|
||||
visual_style = "请用中文描述这张图片的内容。如果有文字，请把文字描述概括出来，请留意其主题，直观感受，输出为一段平文本，最多30字，请注意不要分点，就输出一段文本"
|
||||
|
|
@ -107,7 +105,7 @@ talk_value_rules = [
|
|||
]
|
||||
|
||||
[memory]
|
||||
max_agent_iterations = 2 # 记忆思考深度（最低为1）
|
||||
max_agent_iterations = 3 # 记忆思考深度（最低为1）
|
||||
agent_timeout_seconds = 45.0 # 最长回忆时间（秒）
|
||||
enable_jargon_detection = true # 记忆检索过程中是否启用黑话识别
|
||||
global_memory = false # 是否允许记忆检索进行全局查询
|
||||
|
|
|
|||
Loading…
Reference in New Issue