Chat Logs and Statistics
See how active MaiBot is and what it has been chatting about!
Chat Statistics
📊 Data Overview
Open the "Chat Statistics" page to view:
- Total Messages - How many messages the bot received
- Replies - How many messages the bot replied to
- Uptime - How long the bot has been running
- Average Response - How fast the bot replies
💰 Cost Statistics
You can also view spending details:
- Total Cost - Total amount spent
- Hourly Cost - Average cost per hour
- Token Usage - How much text the AI processed
- Cost by Model - How much was spent on each AI model
📈 Trend Charts
Intuitive charts display:
- 24 Hours - Activity over the last day
- 7 Days - Trends over the last week
- Peak Hours - When the bot is most active
Chat Logs
View Logs
View detailed chat history:
- Who said what
- How the bot replied
- When the conversation took place
- In which group chat
Search Logs
Looking for specific content?
- Filter by user
- Search by time range
- Filter by group chat
Log Management
- Clean Logs - Delete old records
- Backup Important Chats - Save interesting conversations
User Management
User List
Displays all users who have chatted:
- User nickname and avatar
- How long they have been known
- Chat frequency
- Platform where they were met
User Profiles
Click on a user to view:
- Personality traits
- Interests and hobbies
- Chatting habits
- Interaction history
User Statistics
- Total Users - How many users are known
- Active Users - How many chat frequently
- Platform Distribution - Counts for QQ, WeChat, etc.
Expression Styles
Speaking Style
MaiBot learns different expression styles:
- Formal/Casual
- Lively/Serene
- Humorous/Serious
- Various internet slang
Slang Management
Internet slang learned by the bot:
- New and trending words
- Memes and jokes
- Niche community terms
- Can be manually approved or rejected
Stickers
Collected stickers:
- Usage frequency statistics
- Popular stickers
- Ability to upload new ones
- Ability to disable inappropriate ones
Stickers in the WebUI are uniformly displayed in four states:
- Known: Has a description, but is not registered or banned
- Unknown: No description yet, and not registered or banned
- Claimed: Already registered and available for MaiBot to use
- Discarded: Already banned and no longer used
Stickers manually uploaded via the WebUI are directly marked as "Claimed". The tag list filled in during upload is merged into the sticker description; if the image already exists in the database, the original record is reused, the description is updated, the ban is lifted, and it is marked as registered. Deleting unregistered stickers synchronously deletes the database record and local file; deleting registered stickers first unloads them from the available sticker library, then deletes the database record and file.
Usage Recommendations
Daily Checks
- Check statistics daily to understand activity levels
- Monitor cost changes to avoid overspending
- Review user feedback to improve the bot
Data Analysis
- Analyze peak hours to schedule maintenance appropriately
- Observe user preferences to adjust the bot's personality
- Track popular topics to add relevant content
Optimization Tips
- Response too slow? Check configuration
- Costs too high? Switch to a cheaper model
- Too few users? Increase promotion
Frequently Asked Questions
Q: How often are statistics updated? A: Real-time updates; you can see the latest data anytime
Q: How long are logs saved? A: Saved indefinitely by default; automatic cleanup can be configured
Q: Can data be exported? A: Export functionality is not currently supported but will be added in future versions
Q: How to reduce usage costs? A: Choose cheaper models, reduce unnecessary calls, and optimize prompts
Practical Tips
Monitor Bot Health
- Response time suddenly increased? There may be an issue
- Costs increased abnormally? Check for potential attacks
- Active users declined? Check if something inappropriate was said
Improve User Experience
- Analyze user profiles for personalized replies
- Track popular topics to prepare relevant content
- Record user feedback for continuous improvement
Save Costs
- Choose cost-effective models
- Set reasonable call frequencies
- Avoid repeated calls that waste tokens