260331-OpenWebUI统计所有Chat的对话字符个数

1 OWUI启动脚本

bash 复制代码
# Open-WebUI Settings
export DATA_DIR='data0331'
export ENABLE_SIGNUP=True
export DEFAULT_USER_ROLE='admin'
export DEFAULT_GROUP_ID='xai'
export OFFLINE_MODE=false
export HF_HUB_OFFLINE=1

# OpenAI API 配置
export ENABLE_OLLAMA_API=false
export ENABLE_OPENAI_API=true
export OPENAI_API_BASE_URLS='https://api.siliconflow.cn/v1;'
export OPENAI_API_KEYS='sk-xxx;'

# Activate conda environment
source ~/miniconda3/etc/profile.d/conda.sh
conda activate owui-0.6.43

# Start Open-WebUI
open-webui serve --port 9999

# pkill -f "open-webui --port 9999" && sleep 1 && ps aux | grep open-webui | grep -v grep || echo "已停止"

2 Chat提取脚本1

python 复制代码
#!/usr/bin/env python3
"""
从webui.db提取chat表数据,计算每个chat中所有content的字符长度,保存到新sqlite文件
"""

import sqlite3
import json
import os

# 配置
SOURCE_DB = "data0331/webui.db"
TARGET_DB = "chat_content_stats.db"


def extract_content_length(chat_json: str) -> int:
    """
    从chat JSON中提取所有message的content字符长度总和
    """
    if not chat_json:
        return 0

    try:
        data = json.loads(chat_json)
    except json.JSONDecodeError:
        return 0

    total_length = 0

    # Open-WebUI的chat JSON结构: {"history": {"messages": {...}}}
    messages = data.get("history", {}).get("messages", {})

    for msg_id, msg in messages.items():
        if isinstance(msg, dict):
            content = msg.get("content", "")
            if content:
                total_length += len(str(content))

    return total_length


def main():
    # 检查源数据库是否存在
    if not os.path.exists(SOURCE_DB):
        print(f"错误: 源数据库不存在: {SOURCE_DB}")
        return

    # 连接源数据库
    source_conn = sqlite3.connect(SOURCE_DB)
    source_cursor = source_conn.cursor()

    # 获取所有chat记录
    source_cursor.execute("""
        SELECT user_id, created_at, chat
        FROM chat
        ORDER BY created_at
    """)
    rows = source_cursor.fetchall()
    print(f"从 {SOURCE_DB} 读取到 {len(rows)} 条chat记录")

    # 创建目标数据库
    if os.path.exists(TARGET_DB):
        os.remove(TARGET_DB)

    target_conn = sqlite3.connect(TARGET_DB)
    target_cursor = target_conn.cursor()

    # 创建目标表
    target_cursor.execute("""
        CREATE TABLE chat_content_stats (
            user_id TEXT NOT NULL,
            created_at TEXT NOT NULL,
            content_length INTEGER NOT NULL
        )
    """)

    # 插入数据
    processed = 0
    for user_id, created_at, chat_json in rows:
        content_length = extract_content_length(chat_json)
        target_cursor.execute("""
            INSERT INTO chat_content_stats (user_id, created_at, content_length)
            VALUES (?, ?, ?)
        """, (user_id, created_at, content_length))
        processed += 1

    target_conn.commit()

    # 显示统计信息
    target_cursor.execute("SELECT COUNT(*), SUM(content_length), AVG(content_length) FROM chat_content_stats")
    count, total, avg = target_cursor.fetchone()

    print(f"\n处理完成!")
    print(f"输出文件: {TARGET_DB}")
    print(f"总记录数: {count}")
    print(f"总字符数: {total:,}")
    print(f"平均每条chat字符数: {avg:.2f}")

    # 显示前5条示例
    print("\n前5条数据示例:")
    target_cursor.execute("SELECT user_id, created_at, content_length FROM chat_content_stats LIMIT 5")
    for row in target_cursor.fetchall():
        print(f"  user_id={row[0][:8]}..., created_at={row[1]}, content_length={row[2]:,}")

    # 关闭连接
    source_conn.close()
    target_conn.close()


if __name__ == "__main__":
    main()

3 Chat提取脚本2

python 复制代码
#!/usr/bin/env python3
"""
从webui.db提取chat表数据,计算每个chat中所有content的字符长度,保存到新sqlite文件
"""

import sqlite3
import json
import os

import re


# 配置
SOURCE_DB = "data0331/webui.db"
TARGET_DB = "chat_content_stats.db"


def extract_content_stats(chat_json: str) -> dict:
    """
    从chat JSON中提取内容统计:中文字、英文字母、数字、标点符号、空格、emoji、其他
    """
    if not chat_json:
        return {
            "chinese": 0, "english": 0, "digit": 0,
            "punctuation": 0, "space": 0, "emoji": 0, "other": 0
        }

    try:
        data = json.loads(chat_json)
    except json.JSONDecodeError:
        return {
            "chinese": 0, "english": 0, "digit": 0,
            "punctuation": 0, "space": 0, "emoji": 0, "other": 0
        }

    chinese_count = 0
    english_count = 0
    digit_count = 0
    punctuation_count = 0
    space_count = 0
    emoji_count = 0
    other_count = 0

    # 标点符号定义
    punctuation_chars = set(".,;:!?-'\"()[]{}<>`~@#$%^&*+=_|\\/·,。;:!?、""''()【】《》「」『』〔〕~@#¥%......&*------+|\\")

    # Emoji范围检测
    def is_emoji(char):
        code = ord(char)
        return (
            0x1F600 <= code <= 0x1F64F or  # 表情符号
            0x1F300 <= code <= 0x1F5FF or  # 符号和象形文字
            0x1F680 <= code <= 0x1F6FF or  # 交通和地图符号
            0x1F700 <= code <= 0x1F77F or  # 其他符号
            0x1F780 <= code <= 0x1F7FF or  # 几何图形
            0x1F900 <= code <= 0x1F9FF or  # 补充符号
            0x1FA00 <= code <= 0x1FA6F or  # 扩展符号
            0x2600 <= code <= 0x26FF or    # 杂项符号
            0x2700 <= code <= 0x27BF or    # 装饰符号
            0x2B50 <= code <= 0x2B55 or    # 更多符号
            0x1F1E0 <= code <= 0x1F1FF    # 国旗
        )

    # Open-WebUI的chat JSON结构: {"history": {"messages": {...}}}
    messages = data.get("history", {}).get("messages", {})

    for msg_id, msg in messages.items():
        if isinstance(msg, dict):
            content = str(msg.get("content", ""))
            for char in content:
                if '\u4e00' <= char <= '\u9fff':  # 中文字符范围
                    chinese_count += 1
                elif char.isalpha():  # 英文字母
                    english_count += 1
                elif char.isdigit():  # 数字
                    digit_count += 1
                elif char.isspace():  # 空格、换行等空白字符
                    space_count += 1
                elif is_emoji(char):  # Emoji
                    emoji_count += 1
                elif char in punctuation_chars:  # 标点符号
                    punctuation_count += 1
                else:
                    other_count += 1

    return {
        "chinese": chinese_count,
        "english": english_count,
        "digit": digit_count,
        "punctuation": punctuation_count,
        "space": space_count,
        "emoji": emoji_count,
        "other": other_count
    }


def main():
    # 检查源数据库是否存在
    if not os.path.exists(SOURCE_DB):
        print(f"错误: 源数据库不存在: {SOURCE_DB}")
        return

    # 连接源数据库
    source_conn = sqlite3.connect(SOURCE_DB)
    source_cursor = source_conn.cursor()

    # 获取所有chat记录,包含user_id
    source_cursor.execute("""
        SELECT user_id, created_at, chat
        FROM chat
        ORDER BY created_at
    """)
    rows = source_cursor.fetchall()
    print(f"从 {SOURCE_DB} 读取到 {len(rows)} 条chat记录")

    # 获取所有用户的email映射 {user_id: email}
    source_cursor.execute("SELECT id, email FROM user")
    user_emails = dict(source_cursor.fetchall())
    print(f"从 user 表读取到 {len(user_emails)} 个用户")

    # 创建目标数据库
    if os.path.exists(TARGET_DB):
        os.remove(TARGET_DB)

    target_conn = sqlite3.connect(TARGET_DB)
    target_cursor = target_conn.cursor()

    # 创建目标表
    target_cursor.execute("""
        CREATE TABLE chat_content_stats (
            user_id TEXT NOT NULL,
            email TEXT,
            created_at TEXT NOT NULL,
            chinese INTEGER NOT NULL DEFAULT 0,
            english INTEGER NOT NULL DEFAULT 0,
            digit INTEGER NOT NULL DEFAULT 0,
            punctuation INTEGER NOT NULL DEFAULT 0,
            space INTEGER NOT NULL DEFAULT 0,
            emoji INTEGER NOT NULL DEFAULT 0,
            other INTEGER NOT NULL DEFAULT 0
        )
    """)

    # 插入数据
    processed = 0
    for user_id, created_at, chat_json in rows:
        stats = extract_content_stats(chat_json)
        email = user_emails.get(user_id, "unknown")
        target_cursor.execute("""
            INSERT INTO chat_content_stats
            (user_id, email, created_at, chinese, english, digit, punctuation, space, emoji, other)
            VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
        """, (user_id, email, created_at, stats["chinese"], stats["english"], stats["digit"],
              stats["punctuation"], stats["space"], stats["emoji"], stats["other"]))
        processed += 1

    target_conn.commit()

    # 显示统计信息
    target_cursor.execute("""
        SELECT
            COUNT(*),
            SUM(chinese),
            SUM(english),
            SUM(digit),
            SUM(punctuation),
            SUM(space),
            SUM(emoji),
            SUM(other),
            AVG(chinese + english + digit + punctuation + space + emoji + other)
        FROM chat_content_stats
    """)
    result = target_cursor.fetchone()
    count = result[0]
    total_chinese, total_english, total_digit, total_punct = result[1:5]
    total_space, total_emoji, total_other = result[5:8]
    avg = result[8]

    # 计算总计
    grand_total = sum([total_chinese, total_english, total_digit,
                       total_punct, total_space, total_emoji, total_other])

    print(f"\n处理完成!")
    print(f"输出文件: {TARGET_DB}")
    print(f"总记录数: {count}")
    print(f"\n【字符类型统计】")
    print(f"  中文字符: {total_chinese:,}")
    print(f"  英文字母: {total_english:,}")
    print(f"  数字:     {total_digit:,}")
    print(f"  标点符号: {total_punct:,}")
    print(f"  空格换行: {total_space:,}")
    print(f"  Emoji:    {total_emoji:,}")
    print(f"  其他字符: {total_other:,}")
    print(f"  ─────────")
    print(f"  总计:     {grand_total:,}")
    print(f"\n平均每条chat字符数: {avg:.2f}")

    # 显示前5条示例
    print("\n【前3条数据示例】:")
    target_cursor.execute("""
        SELECT user_id, email, created_at, chinese, english, digit,
               punctuation, space, emoji, other
        FROM chat_content_stats
        LIMIT 3
    """)
    for i, row in enumerate(target_cursor.fetchall()):
        total = sum(row[3:])
        print(f"\n  记录 {i+1}:")
        print(f"    user_id={row[0][:8]}..., email={row[1]}")
        print(f"    created_at={row[2]}")
        print(f"    中文={row[3]:,}, 英文={row[4]:,}, 数字={row[5]:,}")
        print(f"    标点={row[6]:,}, 空格={row[7]:,}, emoji={row[8]:,}, 其他={row[9]:,}")
        print(f"    总计={total:,}")

    # 关闭连接
    source_conn.close()
    target_conn.close()


if __name__ == "__main__":
    main()
相关推荐
阿坨3 分钟前
firestart:一行命令启动你的日常应用和网页
python·pypi·cli·click
老歌老听老掉牙13 分钟前
麻花钻切屑形态演变的力学机制与临界条件分析
python·算法·钻头
happylifetree1 小时前
Python18(补充):练习
python
weixin_416667961 小时前
银河麒麟V10看门狗试验-1
网络·chrome·python
古城小栈2 小时前
Pydantic 从入门到实践全讲解
python
happylifetree2 小时前
Python18:核心语法-数据存储与运算-运算符-算术运算符
python
打工仔折腾 AI2 小时前
从Attention到BERT:双向预训练语言模型到底解决了什么问题
人工智能·后端·python·深度学习·语言模型·bert
迅猛龙办公室2 小时前
实现第一个python程序(HelloWorld)
开发语言·python
拉格朗日(Lagrange)2 小时前
【第2 章】WorkBuddy 从入门到高手
开发语言·python
老歌老听老掉牙4 小时前
斜抛运动问题分析:给定最大高度与墙面位置的轨迹与时间求解
python·斜抛运动