t0ng7u 99fcc354e3 📊 feat: add comprehensive model monitoring dashboard
This commit introduces a complete model monitoring system that provides
real-time insights into model performance and usage statistics.

##  Features Added

### Core Components
- **ModelMonitoringStats**: Four key metric cards displaying total models,
  active models, total requests, and average success rate
- **ModelMonitoringTable**: Interactive table with search, filtering, and
  pagination for detailed model data
- **useModelMonitoring**: Custom hook for data fetching and state management

### Dashboard Integration
- Added new "模型观测" (Model Monitoring) tab to main dashboard
- Integrated monitoring components with existing dashboard layout
- Maintained consistent UI/UX with shadcn/ui design system

### Data Processing
- Smart data aggregation from existing `/api/data/` endpoints
- Automatic calculation of success rates and average metrics
- Support for both admin and user-specific data views

### Interactive Features
- Real-time search by model name
- Business group filtering
- Pagination with 10 items per page
- Color-coded success rate indicators (green >95%, yellow 90-95%, red <90%)
- Refresh capability for up-to-date data

## 🔧 Technical Implementation

### Type Safety
- Added comprehensive TypeScript interfaces in `@/types/api.ts`
- Defined `ModelInfo`, `ModelMonitoringStats`, and related types

### Utility Functions
- Enhanced color utilities with `modelToColor()` for consistent model identification
- Improved formatters for quota, tokens, and percentage display
- Maintained existing utility function architecture

### Architecture
- Follows established patterns from dashboard components
- Reuses existing HTTP client and authentication utilities
- Consistent error handling and loading states

### Code Quality
- All components pass linter checks
- Proper import organization and formatting
- Responsive design for mobile compatibility

## 🎯 User Experience

### Visual Design
- Color-coded model indicators for quick identification
- Success rate visualization with icons and colors
- Clean table layout with proper spacing and typography
- Skeleton loading states for smooth UX

### Functionality
- Search models by name with instant filtering
- Filter by business groups for organized viewing
- Navigate through paginated results efficiently
- Refresh data manually when needed

## 📋 Files Modified

- `web/src/types/api.ts`: Added model monitoring type definitions
- `web/src/features/dashboard/hooks/use-model-monitoring.ts`: Core data hook
- `web/src/features/dashboard/components/model-monitoring-stats.tsx`: Stats cards
- `web/src/features/dashboard/components/model-monitoring-table.tsx`: Data table
- `web/src/features/dashboard/index.tsx`: Dashboard integration
- Various formatting and import organization improvements

This implementation provides a comprehensive solution for model monitoring
that aligns with the existing codebase architecture while delivering
powerful insights into model performance and usage patterns.
2025-09-26 02:41:46 +08:00
CI
2025-09-19 14:20:35 +08:00
2025-08-19 01:44:44 +08:00
2025-09-20 13:38:44 +08:00
2025-09-19 14:20:15 +08:00
2025-09-19 14:20:15 +08:00
2025-09-19 14:20:15 +08:00
2025-06-09 14:57:01 +08:00
2023-06-22 11:37:44 +08:00
2025-08-21 12:49:56 +08:00
2023-06-02 14:20:40 +08:00

中文 | English

new-api

New API

🍥 Next-Generation Large Model Gateway and AI Asset Management System

Calcium-Ion%2Fnew-api | Trendshift

license release docker docker GoReportCard

📝 Project Description

Note

This is an open-source project developed based on One API

Important

🤝 Trusted Partners

 

No particular order

Cherry Studio Peking University UCloud Alibaba Cloud IO.NET

 

📚 Documentation

For detailed documentation, please visit our official Wiki: https://docs.newapi.pro/

You can also access the AI-generated DeepWiki: Ask DeepWiki

Key Features

New API offers a wide range of features, please refer to Features Introduction for details:

  1. 🎨 Brand new UI interface
  2. 🌍 Multi-language support
  3. 💰 Online recharge functionality (YiPay)
  4. 🔍 Support for querying usage quotas with keys (works with neko-api-key-tool)
  5. 🔄 Compatible with the original One API database
  6. 💵 Support for pay-per-use model pricing
  7. ⚖️ Support for weighted random channel selection
  8. 📈 Data dashboard (console)
  9. 🔒 Token grouping and model restrictions
  10. 🤖 Support for more authorization login methods (LinuxDO, Telegram, OIDC)
  11. 🔄 Support for Rerank models (Cohere and Jina), API Documentation
  12. Support for OpenAI Realtime API (including Azure channels), API Documentation
  13. Support for Claude Messages format, API Documentation
  14. Support for entering chat interface via /chat2link route
  15. 🧠 Support for setting reasoning effort through model name suffixes:
    1. OpenAI o-series models
      • Add -high suffix for high reasoning effort (e.g.: o3-mini-high)
      • Add -medium suffix for medium reasoning effort (e.g.: o3-mini-medium)
      • Add -low suffix for low reasoning effort (e.g.: o3-mini-low)
    2. Claude thinking models
      • Add -thinking suffix to enable thinking mode (e.g.: claude-3-7-sonnet-20250219-thinking)
  16. 🔄 Thinking-to-content functionality
  17. 🔄 Model rate limiting for users
  18. 💰 Cache billing support, which allows billing at a set ratio when cache is hit:
    1. Set the Prompt Cache Ratio option in System Settings-Operation Settings
    2. Set Prompt Cache Ratio in the channel, range 0-1, e.g., setting to 0.5 means billing at 50% when cache is hit
    3. Supported channels:
      • OpenAI
      • Azure
      • DeepSeek
      • Claude

Model Support

This version supports multiple models, please refer to API Documentation-Relay Interface for details:

  1. Third-party models gpts (gpt-4-gizmo-*)
  2. Third-party channel Midjourney-Proxy(Plus) interface, API Documentation
  3. Third-party channel Suno API interface, API Documentation
  4. Custom channels, supporting full call address input
  5. Rerank models (Cohere and Jina), API Documentation
  6. Claude Messages format, API Documentation
  7. Dify, currently only supports chatflow

Environment Variable Configuration

For detailed configuration instructions, please refer to Installation Guide-Environment Variables Configuration:

  • GENERATE_DEFAULT_TOKEN: Whether to generate initial tokens for newly registered users, default is false
  • STREAMING_TIMEOUT: Streaming response timeout, default is 300 seconds
  • DIFY_DEBUG: Whether to output workflow and node information for Dify channels, default is true
  • FORCE_STREAM_OPTION: Whether to override client stream_options parameter, default is true
  • GET_MEDIA_TOKEN: Whether to count image tokens, default is true
  • GET_MEDIA_TOKEN_NOT_STREAM: Whether to count image tokens in non-streaming cases, default is true
  • UPDATE_TASK: Whether to update asynchronous tasks (Midjourney, Suno), default is true
  • COHERE_SAFETY_SETTING: Cohere model safety settings, options are NONE, CONTEXTUAL, STRICT, default is NONE
  • GEMINI_VISION_MAX_IMAGE_NUM: Maximum number of images for Gemini models, default is 16
  • MAX_FILE_DOWNLOAD_MB: Maximum file download size in MB, default is 20
  • CRYPTO_SECRET: Encryption key used for encrypting database content
  • AZURE_DEFAULT_API_VERSION: Azure channel default API version, default is 2025-04-01-preview
  • NOTIFICATION_LIMIT_DURATION_MINUTE: Notification limit duration, default is 10 minutes
  • NOTIFY_LIMIT_COUNT: Maximum number of user notifications within the specified duration, default is 2
  • ERROR_LOG_ENABLED=true: Whether to record and display error logs, default is false

Deployment

For detailed deployment guides, please refer to Installation Guide-Deployment Methods:

Tip

Latest Docker image: calciumion/new-api:latest

Multi-machine Deployment Considerations

  • Environment variable SESSION_SECRET must be set, otherwise login status will be inconsistent across multiple machines
  • If sharing Redis, CRYPTO_SECRET must be set, otherwise Redis content cannot be accessed across multiple machines

Deployment Requirements

  • Local database (default): SQLite (Docker deployment must mount the /data directory)
  • Remote database: MySQL version >= 5.7.8, PgSQL version >= 9.6

Deployment Methods

Using BaoTa Panel Docker Feature

Install BaoTa Panel (version 9.2.0 or above), find New-API in the application store and install it. Tutorial with images

# Download the project
git clone https://github.com/Calcium-Ion/new-api.git
cd new-api
# Edit docker-compose.yml as needed
# Start
docker-compose up -d

Using Docker Image Directly

# Using SQLite
docker run --name new-api -d --restart always -p 3000:3000 -e TZ=Asia/Shanghai -v /home/ubuntu/data/new-api:/data calciumion/new-api:latest

# Using MySQL
docker run --name new-api -d --restart always -p 3000:3000 -e SQL_DSN="root:123456@tcp(localhost:3306)/oneapi" -e TZ=Asia/Shanghai -v /home/ubuntu/data/new-api:/data calciumion/new-api:latest

Channel Retry and Cache

Channel retry functionality has been implemented, you can set the number of retries in Settings->Operation Settings->General Settings. It is recommended to enable caching.

Cache Configuration Method

  1. REDIS_CONN_STRING: Set Redis as cache
  2. MEMORY_CACHE_ENABLED: Enable memory cache (no need to set manually if Redis is set)

API Documentation

For detailed API documentation, please refer to API Documentation:

Other projects based on New API:

  • new-api-horizon: High-performance optimized version of New API
  • VoAPI: Frontend beautified version based on New API

Help and Support

If you have any questions, please refer to Help and Support:

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