AI API gateway for Claude Code, Codex, Gemini, and OpenAI.
English | 简体中文
Smart routing | Automatic failover | Model-aware cooldown | Multi-URL scheduling | Protocol transforms | Live monitoring | Cost control
ccLoad removes the operational mess of running multiple AI API upstreams. It keeps Claude Code, Codex, Gemini, and OpenAI-compatible clients on one stable gateway, then handles upstream selection, failover, cooldown, protocol conversion, request visibility, and cost limits in the service instead of in every client script.
During OpenAI Build Week, Codex powered by GPT-5.6 was the primary engineering agent used to:
- Trace request routing, failover, cooldown, protocol conversion, and dashboard flows across the Go backend and embedded web UI.
- Implement and review model-scoped cooldown handling for upstream
5xx, key-level429, and model-unavailable404failures without unnecessarily cooling an entire channel. - Refine the model-status and call-statistics UI, update the English and Chinese documentation, and verify the result with focused Go tests, builds, and browser walkthroughs.
- Prepare the reproducible demo and Devpost submission while keeping architecture, security, and final-review decisions under human control.
GPT-5.6 is also integrated into the product itself: ccLoad exposes GPT-5.6 through OpenAI-compatible and Codex Responses endpoints, includes Sol, Terra, and Luna model presets, calculates their standard, priority, flex, cached-token, and long-context costs, and applies routing and model-scoped cooldown decisions to them like any other configured upstream model.
The repository's AGENTS.md and CLAUDE.md provide persistent engineering constraints so Codex works against the same KISS-first review and testing rules in every session.
Common failure modes when you run several AI API channels:
- Manual channel switching: Different keys, validity windows, quotas, and upstream URLs quickly become hard to manage.
- Rate limits and upstream failures:
429,502,504, expired keys, and overloaded providers should not stop the client workflow. - Opaque request status: Without live request visibility, long streaming requests become guesswork.
- HTTP 200 with error content: Some upstreams return a successful HTTP status while the response body is an actual error.
- Cost drift: Shared gateways need per-channel and per-token limits, not spreadsheet accounting after the bill arrives.
ccLoad handles those cases with:
- Smart routing: High-priority channels are selected first; channels at the same priority use smooth weighted round-robin.
- Automatic failover: Failed keys, models, channels, and URLs are skipped according to the classified error scope.
- Model-aware cooldown: Structured
model_cooldownresponses, upstream HTTP 5xx failures, key-level 429 rate limits, and model-unavailable 404 errors all cool only the actual upstream model first; other models on the same channel remain available. The channel is promoted to cooldown only after every configured model or every enabled key is cooling. - Multi-URL scheduling: A single channel can use multiple upstream URLs, weighted by observed latency and health.
- Protocol transforms: Anthropic, OpenAI, Gemini, and Codex request/response families can be converted at the gateway.
- Live monitoring: Active requests, logs, token usage, TTFB, cost, and upstream details are visible in the web dashboard.
- Soft-error detection: HTTP 200 responses that are actually errors trigger the same failover path as regular upstream failures. Common cases include:
- JSON responses containing
{"error": {...}}structure - Responses with
typefield set to"error" - Explicit rate limits in SSE
errorevents (rate_limit_exceeded/too_many_requests) are handled as429 - Plain text messages like
"当前模型负载过高"/"Current model load too high"(load warnings)
- JSON responses containing
- 🚀 High-Performance Architecture - Gin framework, 1000+ concurrent connections, high-performance caching
- 🧮 Local Token Counting - API-compliant local token estimation, <5ms response, 93%+ accuracy, supports large-scale tool scenarios
- 🎯 Smart Error Classification - Distinguishes Key/Model/Channel/Client errors, soft error detection (200 masquerading as error), SSE rate-limit errors as 429, 1308 quota handling
- 🔀 Smart Routing - Priority + smooth weighted round-robin channel selection, pre-filters cooled channels, multi-key load balancing, health-based dynamic sorting (confidence factor prevents small sample over-penalization)
- 🛡️ Failover - Key/channel failures use exponential backoff; model cooldowns (structured responses, 5xx, 429, model-unavailable 404) honor the upstream reset deadline and switch channels without cooling the whole channel
- 🔒 Race-Safe - Key selector race condition protection, startup config validation, automatic resource cleanup
- 📊 Real-time Monitoring - Built-in trend analysis, logging, and stats dashboard, Token usage stats with time range selection and per-token classification
- 🎯 Transparent Proxy - Supports Claude Code, Codex, Gemini, and OpenAI compatible APIs with smart auth detection
- 📦 Single Binary Deployment - No external dependencies, embedded SQLite included
- 🔒 Secure Authentication - Token-based admin interface and API access control
- 🏷️ Build Tags - GOTAGS support, high-performance JSON library enabled by default
- 🐳 Docker Support - Multi-arch images (amd64/arm64), automated CI/CD
- ☁️ Cloud Native - Container deployment support, GitHub Actions auto-build
- 🤗 Hugging Face - One-click deployment to Hugging Face Spaces, free hosting
- 💰 Cost Limits - Per-channel daily cost limits, per-token cost limits
- 🚦 Channel RPM Limits - Per-channel rolling 60-second request caps, 0=unlimited
- 🚧 Channel Concurrency Limits - Per-channel in-flight request caps, 0=unlimited
- 🔐 Token Restrictions - Per-token cost limits, model restrictions, channel allowlist/denylist, and concurrency caps for fine-grained access control
- ⏱️ TTFB Monitoring - Streaming request first byte time tracking for upstream latency diagnosis
- 🌐 Multi-URL Load Balancing - Multiple URLs per channel with latency-weighted random selection
- 💵 service_tier Pricing - OpenAI priority/flex/default tier multipliers for accurate cost accounting
- 🖼️ Image Tool Billing - Responses image_generation/gpt-image-2 cost accounting
- 📉 Tiered Pricing - GPT-5.4/Qwen-Plus/Gemini long-context step pricing, auto-applies lower rate at token thresholds
- 🔄 Protocol Transform - All 12 directed Anthropic/OpenAI/Gemini/Codex conversion paths for requests plus streaming and non-streaming responses, including tool, reasoning/signature, usage, and SSE normalization
- 💬 Conversational Model Testing - Channel/model/chat testing modes with image upload, reasoning level, built-in search, and chat export
- 🔍 Debug Logs - Upstream request/response raw data capture with sensitive header masking, essential for troubleshooting
- 🕐 Scheduled Checks - Background periodic channel availability probing, auto-detect failed channels
- 🔄 Auto Updates - Checks for new releases every 12 hours by default, configurable from the admin settings page
- 🧩 Custom Request Rules - Per-channel HTTP header & JSON body rewriting (remove/override/append), with auth header protection, CRLF guard, and capacity caps
- 🎛️ Log Column Customization - Show/hide table columns per preference, settings persist in browser localStorage
graph TB
subgraph "Client"
A[Claude Code / Codex / Gemini / OpenAI Client]
end
subgraph "ccLoad Service"
B[HTTP Proxy]
C[Authentication + Route Dispatch]
D[Channel Selector<br/>Priority + Smooth Weighted RR]
E[Protocol Registry<br/>Native Bypass / Local Transform]
F[URL Selector<br/>Explore + 1/EWMA Weighting]
G[(Storage Factory<br/>SQLite / MySQL / PostgreSQL)]
H[Logs + Metrics + Cost Control]
A --> B --> C --> D --> E --> F
D <--> G
H <--> G
B --> H
end
subgraph "Upstream Services"
U1[Anthropic]
U2[OpenAI-compatible]
U3[Gemini]
U4[Codex Responses]
end
F --> U1
F --> U2
F --> U3
F --> U4
U1 -. JSON / SSE .-> E
U2 -. JSON / SSE .-> E
U3 -. JSON / SSE .-> E
U4 -. JSON / SSE .-> E
E -. Client Protocol .-> B
style B fill:#4F46E5,stroke:#000,color:#fff
style D fill:#059669,stroke:#000,color:#fff
style E fill:#0EA5E9,stroke:#000,color:#fff
Choose the deployment method that suits you best:
| Method | Difficulty | Cost | Use Case | HTTPS | Persistence |
|---|---|---|---|---|---|
| 🐳 Docker | ⭐⭐ | VPS required | Production, high performance | Config required | ✅ |
| 🤗 Hugging Face | ⭐ | Free | Personal use, quick trial | ✅ Auto | ✅ |
| 🔧 Source Build | ⭐⭐⭐ | Server required | Development, customization | Config required | ✅ |
| 📦 Binary | ⭐⭐ | Server required | Lightweight, simple setup | Config required | ✅ |
Using pre-built images (Recommended):
# Option 1: Using docker-compose (Simplest)
curl -o docker-compose.yml https://raw.githubusercontent.com/caidaoli/ccLoad/master/docker-compose.yml
curl -o .env https://raw.githubusercontent.com/caidaoli/ccLoad/master/.env.example
# Edit .env file to set password
docker-compose up -d
# Option 2: Run image directly
docker pull ghcr.io/caidaoli/ccload:latest
docker run -d --name ccload \
-p 8080:8080 \
-e CCLOAD_PASS=your_secure_password \
-v ccload_data:/app/data \
ghcr.io/caidaoli/ccload:latestBuilding from source:
# Clone project
git clone https://github.com/caidaoli/ccLoad.git
cd ccLoad
# Build and run with docker-compose
docker-compose -f docker-compose.build.yml up -d
# Or build manually
docker build -t ccload:local .
docker run -d --name ccload \
-p 8080:8080 \
-e CCLOAD_PASS=your_secure_password \
-v ccload_data:/app/data \
ccload:local# Clone project
git clone https://github.com/caidaoli/ccLoad.git
cd ccLoad
# Build project (uses high-performance JSON library by default)
go build -tags sonic -o ccload .
# Or use Makefile
make build
# Run in development mode
go run -tags sonic .
# Or
make dev# Download binary for your platform from GitHub Releases
wget https://github.com/caidaoli/ccLoad/releases/latest/download/ccload-linux-amd64
chmod +x ccload-linux-amd64
./ccload-linux-amd64Hugging Face Spaces provides free container hosting with Docker support, ideal for personal and small team use.
-
Login to Hugging Face
Visit huggingface.co and log into your account
-
Create New Space
- Click "New" → "Space" in the top right
- Space name:
ccload(or custom name) - License:
MIT - Select the SDK:
Docker - Visibility:
PublicorPrivate(private requires paid subscription) - Click "Create Space"
-
Create Dockerfile
Create a
Dockerfilein the Space repository:FROM ghcr.io/caidaoli/ccload:latest ENV TZ=Asia/Shanghai ENV PORT=7860 ENV SQLITE_PATH=/tmp/ccload.db EXPOSE 7860
Create via:
Method A - Web Interface (Recommended):
- Click "Files" tab on Space page
- Click "Add file" → "Create a new file"
- Enter
Dockerfileas filename - Paste the content above
- Click "Commit new file to main"
Method B - Git Command Line:
# Clone your Space repository git clone https://huggingface.co/spaces/YOUR_USERNAME/ccload cd ccload # Create Dockerfile cat > Dockerfile << 'EOF' FROM ghcr.io/caidaoli/ccload:latest ENV TZ=Asia/Shanghai ENV PORT=7860 ENV SQLITE_PATH=/tmp/ccload.db EXPOSE 7860 EOF # Commit and push git add Dockerfile git commit -m "Add Dockerfile for ccLoad deployment" git push
-
Configure Environment Variables (Secrets)
In Space settings (Settings → Variables and secrets → New secret):
Variable Value Required Description CCLOAD_PASSyour_admin_password✅ Required Admin interface password CCLOAD_API_TOKENStoken1|production,token2|developmentOptional Pre-seed API access tokens on startup Note: API access tokens can be pre-seeded with
CCLOAD_API_TOKENSor managed in the Web admin interface/web/tokens.html. -
Wait for Build and Startup
After pushing Dockerfile, Hugging Face will automatically:
- Pull pre-built image (~30 seconds)
- Start application container (~10 seconds)
- Total time ~1-2 minutes (3-5x faster than source build)
-
Access Application
After build completes, access via:
- App URL:
https://YOUR_USERNAME-ccload.hf.space - Admin Interface:
https://YOUR_USERNAME-ccload.hf.space/web/ - API Endpoint:
https://YOUR_USERNAME-ccload.hf.space/v1/messages
First Access Note:
- If Space is sleeping, first access takes 20-30 seconds to wake
- Subsequent accesses respond immediately
- App URL:
Advantages:
- ✅ Completely Free: Public Spaces are permanently free with CPU and storage
- ✅ Fast Deployment: Pre-built image, 1-2 minutes (3-5x faster than source build)
- ✅ Auto HTTPS: No SSL certificate configuration needed
- ✅ Auto Restart: Automatic restart after crashes
- ✅ Version Control: Git-based, easy rollback and collaboration
- ✅ Simple Maintenance: Only 5-line Dockerfile, no source code management
Limitations:
⚠️ Resource Limits: Free tier provides 2 CPU + 16GB RAM⚠️ Sleep Policy: 48 hours without access triggers sleep, first access takes ~20-30s to wake⚠️ Fixed Port: Must use port 7860⚠️ Public Access: Spaces are public by default, must configure API tokens via Web admin to access /v1/* APIs (otherwise 401)
Important: Hugging Face Spaces Storage Policy
Due to Hugging Face Spaces limitations (/tmp directory clears on restart), we strongly recommend using an external MySQL or PostgreSQL database for complete data persistence:
Option 1: Hybrid Storage Mode (Recommended, Best Performance)
- ✅ Ultra-fast queries: Reads go through local SQLite, avoiding remote database latency
- ✅ Restart-safe: Durable data is stored in MySQL/PostgreSQL and restored on startup
- ✅ Stats caching: Smart TTL cache reduces repetitive aggregate queries
- Configuration: Add one primary DSN (
CCLOAD_MYSQLorCCLOAD_POSTGRES) plusCCLOAD_ENABLE_SQLITE_REPLICA=1in Secrets
Dockerfile Example (Hybrid Mode):
FROM ghcr.io/caidaoli/ccload:latest
ENV TZ=Asia/Shanghai
ENV PORT=7860
# Configure in Secrets: CCLOAD_MYSQL or CCLOAD_POSTGRES, plus CCLOAD_ENABLE_SQLITE_REPLICA=1
EXPOSE 7860Option 2: Pure External Database Mode
- ✅ Complete Persistence: Channel configs, logs, and stats all preserved
- ✅ Restart-Safe: Data stored externally, unaffected by Space restarts
⚠️ Database Latency: Stats page latency depends on the remote database and region- Configuration: Add exactly one of
CCLOAD_MYSQLorCCLOAD_POSTGRESin Secrets
Recommended Free MySQL Services:
- TiDB Cloud Serverless - Free 5GB storage, MySQL compatible, no connection limits, recommended first choice
- Aiven for MySQL - Free 1GB storage, multi-region support
MySQL Configuration Example (TiDB Cloud):
- Register for TiDB Cloud account
- Create Serverless Cluster (free)
- Get connection info, format:
user:password@tcp(host:4000)/database?tls=true - Add
CCLOAD_MYSQLvariable in Hugging Face Space Secrets - (Optional) Enable Hybrid Mode: Add
CCLOAD_ENABLE_SQLITE_REPLICA=1for best performance - Restart Space, all data will auto-persist to MySQL
PostgreSQL Configuration Example:
CCLOAD_POSTGRES=postgres://user:password@host:5432/ccload?sslmode=requireURL and libpq keyword DSNs are supported. Do not set CCLOAD_MYSQL and CCLOAD_POSTGRES at the same time.
Dockerfile Example (Pure External Database):
FROM ghcr.io/caidaoli/ccload:latest
ENV TZ=Asia/Shanghai
ENV PORT=7860
# Configure CCLOAD_MYSQL or CCLOAD_POSTGRES in Secrets; SQLITE_PATH is not required
EXPOSE 7860Option 3: Local Storage Only (Not Recommended)
⚠️ Data Loss:/tmpclears on Space restart, channel config lost⚠️ Manual Recovery: Must re-import via Web interface or CSV- Use case: Temporary testing only
With pre-built images, updates are simple:
Image Refresh:
- When new version image (
ghcr.io/caidaoli/ccload:latest) is released - Click "Factory rebuild" in Space settings to pull latest image
- Or wait for Hugging Face auto-restart (typically after 48 hours)
Manual Trigger Update:
# Add empty commit to trigger rebuild
git commit --allow-empty -m "Trigger rebuild to pull latest image"
git pushVersion Pinning (Optional): To lock specific version, modify Dockerfile:
FROM ghcr.io/caidaoli/ccload:v2.44.1 # Specify version
ENV TZ=Asia/Shanghai
ENV PORT=7860
ENV SQLITE_PATH=/tmp/ccload.db
EXPOSE 7860Choose SQLite, MySQL, or PostgreSQL based on the deployment shape. MySQL and PostgreSQL are mutually exclusive.
SQLite Mode (Default):
# Set environment variables
export CCLOAD_PASS=your_admin_password
export PORT=8080
export SQLITE_PATH=./data/ccload.db
# Or use .env file
echo "CCLOAD_PASS=your_admin_password" > .env
echo "PORT=8080" >> .env
echo "SQLITE_PATH=./data/ccload.db" >> .env
# Start service
./ccloadMySQL Mode:
# 1. Create MySQL database
mysql -u root -p -e "CREATE DATABASE ccload CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;"
# 2. Set environment variables
export CCLOAD_PASS=your_admin_password
export CCLOAD_MYSQL="user:password@tcp(localhost:3306)/ccload?charset=utf8mb4"
export PORT=8080
# Or use .env file
echo "CCLOAD_PASS=your_admin_password" > .env
echo "CCLOAD_MYSQL=user:password@tcp(localhost:3306)/ccload?charset=utf8mb4" >> .env
echo "PORT=8080" >> .env
# 3. Start service (auto-creates tables)
./ccloadPostgreSQL Mode:
# 1. Create the database and user in PostgreSQL
# 2. Set environment variables
export CCLOAD_PASS=your_admin_password
export CCLOAD_POSTGRES="postgres://user:password@localhost:5432/ccload?sslmode=disable"
export PORT=8080
# 3. Start service (auto-creates and migrates tables)
./ccloadDocker + MySQL:
# Option 1: docker-compose (Recommended)
cat > docker-compose.mysql.yml << 'EOF'
version: '3.8'
services:
mysql:
image: mysql:8.0
environment:
MYSQL_ROOT_PASSWORD: rootpass
MYSQL_DATABASE: ccload
MYSQL_USER: ccload
MYSQL_PASSWORD: ccloadpass
volumes:
- mysql_data:/var/lib/mysql
ports:
- "3306:3306"
healthcheck:
test: ["CMD", "mysqladmin", "ping", "-h", "localhost"]
interval: 10s
timeout: 5s
retries: 5
ccload:
image: ghcr.io/caidaoli/ccload:latest
environment:
CCLOAD_PASS: your_admin_password
CCLOAD_MYSQL: "ccload:ccloadpass@tcp(mysql:3306)/ccload?charset=utf8mb4"
PORT: 8080
ports:
- "8080:8080"
depends_on:
mysql:
condition: service_healthy
volumes:
mysql_data:
EOF
docker-compose -f docker-compose.mysql.yml up -d
# Option 2: Direct run (requires existing MySQL service)
docker run -d --name ccload \
-p 8080:8080 \
-e CCLOAD_PASS=your_admin_password \
-e CCLOAD_MYSQL="user:pass@tcp(mysql_host:3306)/ccload?charset=utf8mb4" \
ghcr.io/caidaoli/ccload:latestDocker + PostgreSQL (requires an existing PostgreSQL service):
docker run -d --name ccload \
-p 8080:8080 \
-e CCLOAD_PASS=your_admin_password \
-e CCLOAD_POSTGRES="postgres://user:pass@postgres_host:5432/ccload?sslmode=require" \
ghcr.io/caidaoli/ccload:latestAfter service starts, access:
- Admin Interface:
http://localhost:8080/web/ - API Proxy:
POST http://localhost:8080/v1/messages - API Token Management:
http://localhost:8080/web/tokens.html- Configure API access tokens via Web interface
Claude API Proxy (Requires Auth):
First, configure API access token in Web admin interface http://localhost:8080/web/tokens.html, then use that token to access API:
curl -X POST http://localhost:8080/v1/messages \
-H "Content-Type: application/json" \
-H "Authorization: Bearer your-api-token" \
-H "x-api-key: your-claude-api-key" \
-H "anthropic-version: 2023-06-01" \
-d '{
"model": "claude-sonnet-4-6",
"max_tokens": 1024,
"messages": [
{
"role": "user",
"content": "Hello, Claude!"
}
]
}'OpenAI Compatible API Proxy (Chat Completions):
curl -X POST http://localhost:8080/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer your-api-token" \
-d '{
"model": "gpt-4o",
"messages": [
{
"role": "user",
"content": "Hello!"
}
]
}'Codex Alpha Search (Native Passthrough Only):
POST /v1/alpha/search accepts the native Codex search payload. The model field is optional. This endpoint is forwarded only to channels whose resolved upstream protocol is Codex; it is not handled by local cross-protocol transforms.
curl -X POST http://localhost:8080/v1/alpha/search \
-H "Content-Type: application/json" \
-H "Authorization: Bearer your-api-token" \
-d '{
"query": "golang channels"
}'For a regular channel base URL, ccLoad appends /v1/alpha/search. If the channel uses the trailing # exact-URL marker, the configured URL must already point to this endpoint, for example https://upstream.example.com/v1/alpha/search#. Responses-only fields prompt_cache_key and prompt_cache_retention are removed before forwarding.
Quickly estimate request token consumption (no upstream API call needed):
curl -X POST http://localhost:8080/v1/messages/count_tokens \
-H "Content-Type: application/json" \
-d '{
"model": "claude-sonnet-4-6",
"messages": [
{"role": "user", "content": "Hello, how are you?"}
],
"system": "You are a helpful assistant."
}'
# Response example
# {
# "input_tokens": 28
# }Features:
- ✅ Compliant with Anthropic official API spec
- ✅ Local computation, <5ms response, no API quota consumption
- ✅ 93%+ accuracy (compared to official API)
- ✅ Supports system prompts, tool definitions, large-scale tool scenarios
- ✅ Requires auth token (configure at
/web/tokens.html)
Manage channels via Web interface /web/channels.html or API:
# Add channel (supports multiple URLs, comma-separated)
curl -X POST http://localhost:8080/admin/channels \
-H "Content-Type: application/json" \
-d '{
"name": "Claude-API",
"api_key": "sk-ant-api03-xxx",
"url": "https://api.anthropic.com,https://api2.anthropic.com",
"priority": 10,
"rpm_limit": 0,
"max_concurrency": 0,
"models": ["claude-sonnet-4-6", "claude-opus-4-6"],
"enabled": true
}'Multi-URL Note: The
urlfield supports comma-separated multiple URLs. The system uses latency-weighted random selection for optimal URL choice, with automatic cooldown for failed URLs, enabling URL-level load balancing and failover within a single channel.
RPM Limit Note:
rpm_limitis a per-channel request cap over a rolling 60-second window;0means unlimited. Proxy forwarding, manual tests, single-URL tests, and scheduled checks all count toward the cap. Multi-URL failover counts each actual upstream HTTP request. The counter is in-memory: restart clears it, and multiple instances count independently.
Concurrency Limit Note:
max_concurrencyis a per-channel cap on simultaneous in-flight upstream requests;0means unlimited. A slot is acquired before the upstream request starts and released when the response body is closed, so streaming requests hold the slot until the stream ends. Over-limit channels are skipped without cooldown. The counter is in-memory and per instance.
The "Advanced" button in the channel editor opens a secondary modal that lets you rewrite the HTTP headers and JSON request body forwarded upstream at channel granularity. Typical use cases include User-Agent override, forcing API version headers, or tweaking fields like thinking / max_tokens. Rules apply in configured order and take effect for all subsequent requests on that channel as soon as they are saved.
Action matrix:
| Target | remove |
override |
append |
|---|---|---|---|
| HTTP Header | Delete the named header (supports token-level removal on multi-value headers such as Anthropic-Beta) |
Header.Set replaces all values |
Header.Add appends a value (multi-value semantics) |
| JSON Body | Delete a field/array element by dotted path | Set the value at a path, creating intermediate nodes as needed | Not supported (ambiguous in JSON) |
JSON path syntax:
- Dotted path + numeric array index:
thinking.budget_tokens,messages.0.role,generation_config.temperature - Values accept any JSON literal: number
0.7, booleantrue, string"claude-opus-4-6", object{"type":"adaptive"}, array["a","b"]
Safety constraints (hard-enforced server-side even if the frontend is bypassed):
- Auth header blacklist: any rule targeting
Authorization,x-api-key, orx-goog-api-key(case-insensitive) is silently ignored and logged viaslog.Warn - CRLF injection guard: header names/values must not contain
\r\n - Non-JSON body passthrough: requests without
application/jsoncontent type, empty bodies, or bodies that fail to deserialize are forwarded untouched without blocking - Capacity caps: ≤ 32 header rules and ≤ 32 body rules per channel, each value ≤ 8 KB; violations return HTTP 400
Typical example:
Interaction with built-in logic: Custom rules run after the anyrouter
anthropic-betainjection and anyrouter adaptive-thinking fallback, so they can override or remove those fields. Generated Anthropic requests usethinking.type=adaptiveplusoutput_config.effortfor thinking depth; anyrouter/v1/messagesadditionally fills missing thinking and normalizes legacythinking.type=enabled. Authentication headers remain unmodifiable at all times.
Supports CSV format for channel config import/export:
Export Config:
# Web interface: Visit /web/channels.html, click "Export CSV" button
# API call:
curl -H "Authorization: Bearer your_token" \
http://localhost:8080/admin/channels/export > channels.csvImport Config:
# Web interface: Visit /web/channels.html, click "Import CSV" button
# API call:
curl -X POST -H "Authorization: Bearer your_token" \
-F "file=@channels.csv" \
http://localhost:8080/admin/channels/importCSV Format Example:
name,api_key,url,priority,models,enabled
Claude-API-1,sk-ant-xxx,https://api.anthropic.com,10,"[\"claude-sonnet-4-6\"]",true
Claude-API-2,sk-ant-yyy,https://api.anthropic.com,5,"[\"claude-opus-4-6\"]",trueFeatures:
- Auto column name mapping (Chinese/English)
- Smart data validation with error messages
- Incremental import and overwrite update
- UTF-8 encoding, Excel compatible
Check out the awesome admin dashboard 👇
Real-time Monitoring Dashboard: Claude Code, Codex, OpenAI, and Gemini platform metrics at a glance
Core Features:
-
📈 24-hour Trend Charts - Request volumes clearly visualized with peaks and valleys
-
🔴 Real-time Error Logs - Instantly detect which channel has issues
-
📊 Channel Call Statistics - See which channels are performing well with data-backed insights
-
💬 Model Testing Workbench - Test by channel, by model, or in a chat-style model testing workflow:
- Upload or paste images in chat mode to verify multimodal requests directly
- Toggle reasoning level, built-in search, and streaming to inspect transformed upstream behavior
- Export conversations as Markdown or HTML for review, incident notes, or regression records
-
⚡ Performance Metrics - Latency, success rates, and bottleneck detection
-
💰 Token Usage Stats - Know exactly where your budget goes:
- Custom time range selector for flexible analysis
- Per API token ID classification for multi-tenant billing
- Supports Gemini/OpenAI cache token visualization
-
🎛️ Log Column Customization - Click the gear icon to show/hide columns, settings auto-saved to browser
UI Highlights:
- 🎨 Modern gradient purple theme for comfortable viewing
- 📱 Responsive design works great on mobile and desktop
- ⚡ Real-time data refresh without manual page reload
- 📊 Multi-dimensional stat cards show key metrics on one screen
- Cached query optimization
- Gemini/OpenAI Cache Token (Cache Read) display
| Component | Version | Purpose | Performance Advantage |
|---|---|---|---|
| Go | 1.26.0+ | Runtime | Native concurrency, modern toolchain |
| Gin | v1.12.0 | Web Framework | High-performance HTTP routing |
| modernc/sqlite | v1.54.0 | Embedded Database | Pure Go, zero CGO dependency, single file (default) |
| MySQL | v1.10.0 | RDBMS | Optional, for high-concurrency production |
| PostgreSQL (pgx) | v5.10.0 | RDBMS | Optional, supports URL and libpq DSNs |
| Sonic | v1.15.2 | JSON Library | 2-3x faster than stdlib |
| gjson / sjson | v1.19.0 / v1.2.5 | Protocol JSON transforms | Targeted reads and writes without generic map conversion |
| godotenv | v1.5.1 | Env Config | Simplified config management |
Modular Architecture:
- Proxy Module Split (SRP):
proxy_handler.go: HTTP entry, concurrency control, route selectionproxy_forward.go: Core forwarding logic, request building, response handlingproxy_error.go: Error handling, cooldown decisions, retry logicproxy_util.go: Constants, type definitions, utility functionsproxy_stream.go: Streaming responses, first byte detectionproxy_gemini.go: Gemini API special handlingproxy_sse_parser.go: SSE parser (defensive handling, Gemini/OpenAI cache token parsing)proxy_debug.go: Upstream request/response debug capture (with sensitive header masking)
- Admin Module Split (SRP):
admin_channels.go: Channel CRUDadmin_stats.go: Stats analysis APIadmin_cooldown.go: Cooldown management APIadmin_csv.go: CSV import/exportadmin_types.go: Admin API type definitionsadmin_auth_tokens.go: API access token CRUD (with token stats, cost limits, model/channel restrictions, concurrency limits)admin_settings.go: System settings managementadmin_models.go: Model list managementadmin_testing.go: Channel testing (with protocol transform testing)admin_debug_log.go: Debug log API (sensitive header masking + base64 binary encoding)channel_check_scheduler.go: Scheduled channel check schedulerdetection_log.go: Detection result to LogEntry builder
- Protocol Transform System (2026-07 core refresh):
protocol/types.go: Four protocol definitions (Anthropic/OpenAI/Gemini/Codex)protocol/registry.go: Contract boundary for request, streaming response, and non-stream response transforms; same-protocol traffic bypasses conversionprotocol/builtin/register.go: Registers all 12 directed cross-protocol pairsprotocol/builtin/cliproxy_adapter.go: ccLoad-owned request validation, JSON/SSE normalization, and stream framingprotocol/cliproxy/: In-tree snapshot of the pure CLIProxyAPI conversion core; provenance and synchronization rules live inUPSTREAM.md- Upstream refresh workflow: invoke
$sync-cliproxy-corein Codex or/sync-cliproxy-corein Claude Code; both resolve to the same repository Skill under.agents/skills/ - Requests that cannot be represented in the selected upstream protocol return
400 Bad Request; they do not trigger channel failover or cooldown - Two modes:
upstream(default, handled natively by upstream) /local(local translation) - Channel config:
ProtocolTransformMode+ProtocolTransforms - Codex
/v1/alpha/searchis native passthrough only and never enters local protocol translation
- Cooldown Manager (DRY):
cooldown/manager.go: Unified cooldown decision engine- Eliminates duplicate code, unified cooldown logic
- Distinguishes network vs HTTP error classification
- Uses separate Key/Model/Channel actions;
ActionRetryModeldoes not retry another Key or URL in the same channel - Persists structured
model_cooldownresponses, upstream HTTP 5xx failures, key-level 429 rate limits, and model-unavailable 404 errors by(channel_id, actual upstream model); other models on that channel stay eligible - Automatically promotes to channel cooldown only when all configured models or all enabled keys are cooling
- Multi-URL Selector (URLSelector):
url_selector.go: Smart URL selection within a single channel- Explore-first: Unvisited URLs get priority to collect latency data
- Weighted random: Weight = 1/EWMA latency, lower latency = higher selection probability
- Independent cooldown: Failed URLs cool down independently without affecting other URLs
- BaseURL tracking: Active requests, logs, and UI carry upstream URL throughout
- Storage Layer Refactor (2025-12 optimization, eliminated 467 lines of duplicate code):
storage/schema/: Unified schema definition (supports SQLite/MySQL/PostgreSQL differences)storage/sql/: Common SQL implementation layer shared by SQLite, MySQL, and PostgreSQLstorage/factory.go: Factory pattern auto-selects database- Composite index optimization, stats query performance improved
- OpenAI service_tier Pricing (2026-03 new):
util.OpenAIServiceTierMultiplier(): Returns multiplier for priority/flex/default tiersLogEntry.ServiceTier: Persisted to database, log cost column shows tier annotation- Supports GPT-5.4, GPT-5.4-pro, and other latest model pricing
- Responses image_generation Tool Billing (2026-05 new):
- Parses Responses API
tool_usage.image_genand theimage_generationtool model - Bills
gpt-image-2by text input, image input, and image output tokens - Streaming/non-streaming proxy paths and channel tests share the same usage parser to keep cost accounting consistent
- Parses Responses API
- Tiered Pricing:
- GPT-5.4: Input price auto-steps down after token threshold
- Qwen-Plus: Lower price tier kicks in after threshold
- Gemini long-context: Price doubles above threshold
- Cache discounts: Claude/Opus independent multipliers, OpenAI cache hit 50% discount
Multi-level Cache System:
- Channel config cache (60s TTL)
- Round-robin pointer cache (in-memory)
- Channel/Key cooldown state inline (
channels/api_keys); model cooldown state inchannel_model_cooldowns - Error classification cache (1000 capacity)
Async Processing Architecture:
- Log system (1000 buffer + single worker, guarantees FIFO order)
- Token/log cleanup (background goroutine, periodic maintenance)
Unified Response System:
StandardResponse[T]generic struct (DRY)ResponseHelperutility class with 9 shortcut methods- Auto-extracts app-level error codes, unified JSON format
Connection Pool Optimization:
- SQLite: 10 connections for memory mode / 5 for file mode, 5-minute lifetime
- HTTP client: 100 max connections, 30s timeout, keepalive optimization
- TLS: Session cache (1024 capacity), reduces handshake latency
| Variable | Default | Description |
|---|---|---|
CCLOAD_PASS |
None | Admin password (Required, exits if not set) |
CCLOAD_API_TOKENS |
None | Pre-seed API access tokens on startup. Format: token1,token2 or token1|production,token2|development; existing tokens are not overwritten |
API_TOKENS |
None | Compatibility alias for CCLOAD_API_TOKENS; startup fails if both variables are set with different values |
CCLOAD_MYSQL |
None | MySQL DSN (optional, format: user:pass@tcp(host:port)/db?charset=utf8mb4)Mutually exclusive with CCLOAD_POSTGRES |
CCLOAD_POSTGRES |
None | PostgreSQL DSN (optional, URL or libpq keywords, e.g. postgres://user:pass@host:5432/db?sslmode=disable)Mutually exclusive with CCLOAD_MYSQL |
CCLOAD_ENABLE_SQLITE_REPLICA |
0 |
Hybrid storage mode switch (1=enable, needs MySQL or Postgres primary DSN) |
CCLOAD_SQLITE_LOG_DAYS |
7 |
Days of logs to restore from primary DB on startup in hybrid mode (-1=all, 0=no logs) |
CCLOAD_ALLOW_INSECURE_TLS |
0 |
Disable upstream TLS cert validation (1=enable; |
PORT |
8080 |
Service port |
GIN_MODE |
release |
Run mode (debug/release) |
GIN_LOG |
true |
Gin access log switch (false/0/no/off to disable) |
TRUSTED_PROXIES |
Private ranges + Loopback + 100.64.0.0/10 |
Trusted proxy CIDRs (comma-separated); none = trust no proxies |
SQLITE_PATH |
data/ccload.db |
SQLite database file path (SQLite mode only) |
SQLITE_JOURNAL_MODE |
WAL |
SQLite Journal mode (WAL/TRUNCATE/DELETE, recommend TRUNCATE for containers) |
CCLOAD_MAX_CONCURRENCY |
1000 |
Max concurrent requests (limits simultaneous proxy requests) |
CCLOAD_MAX_BODY_BYTES |
10485760 |
Max request body bytes (10MB, Images API auto-expands to 20MB) |
CCLOAD_COOLDOWN_AUTH_SEC |
300 |
Auth error (401/402/403) initial cooldown (seconds) |
CCLOAD_COOLDOWN_SERVER_SEC |
120 |
Server error (5xx) initial cooldown (seconds) |
CCLOAD_COOLDOWN_TIMEOUT_SEC |
60 |
Timeout error (597/598) initial cooldown (seconds) |
CCLOAD_COOLDOWN_RATE_LIMIT_SEC |
60 |
Rate limit error (429) initial cooldown (seconds) |
CCLOAD_COOLDOWN_MAX_SEC |
1800 |
Exponential backoff cooldown max (seconds, 30 minutes) |
CCLOAD_COOLDOWN_MIN_SEC |
10 |
Exponential backoff cooldown min (seconds) |
CCLOAD_HOST_OVERRIDES |
None | DNS override: pin upstream domains to fixed IPs, bypassing DNS resolution. Format: host1=ip1,host2=ip2, e.g. anyrouter.top=47.246.23.200. TLS SNI/cert/Host header unaffected |
If the service sits behind a reverse proxy or load balancer, set
TRUSTED_PROXIESexplicitly so spoofedX-Forwarded-Forvalues cannot affect client IP detection or login rate limiting.
HuggingFace Spaces and similar environments lose local data on restart, but remote MySQL/Postgres can have high query latency. Hybrid mode offers the best of both worlds:
- Primary Storage (MySQL or PostgreSQL): Write operations go to the primary first, ensuring data persistence
- SQLite Local Cache: Read operations go through local SQLite, latency <1ms
- Startup Recovery: Restore data from primary to SQLite, supports restoring logs by days
- Log Special Handling: Write to SQLite first (fast), then async sync to primary (backup)
# Enable hybrid mode (MySQL primary)
export CCLOAD_MYSQL="user:pass@tcp(host:3306)/db?charset=utf8mb4"
export CCLOAD_ENABLE_SQLITE_REPLICA=1
export CCLOAD_SQLITE_LOG_DAYS=7 # Restore last 7 days of logs (optional)
# Or PostgreSQL primary
export CCLOAD_POSTGRES="postgres://user:pass@host:5432/db?sslmode=disable"
export CCLOAD_ENABLE_SQLITE_REPLICA=1Storage Modes:
| Mode | Configuration | Use Case |
|---|---|---|
| Pure SQLite | Don't set primary DSN | Local dev, single instance |
| Pure MySQL | Set CCLOAD_MYSQL |
Standard production |
| Pure PostgreSQL | Set CCLOAD_POSTGRES |
Standard production (PG) |
| Hybrid Mode | Primary DSN + CCLOAD_ENABLE_SQLITE_REPLICA=1 |
HuggingFace Spaces / high-latency primary |
These settings have been migrated to database, managed via Web interface /web/settings.html, changes take effect immediately without restart:
| Setting | Default | Description |
|---|---|---|
log_retention_days |
7 |
Log retention days (-1 for permanent, 1-365 days) |
max_key_retries |
3 |
Max key retries within single channel |
upstream_first_byte_timeout |
0 |
Upstream first valid stream content timeout (seconds, 0=disabled, stream only) |
non_stream_timeout |
120 |
Non-stream request timeout (seconds, 0=disabled) |
anthropic_first_byte_timeout |
0 |
Anthropic first valid stream content timeout (seconds, 0=use global upstream_first_byte_timeout) |
anthropic_non_stream_timeout |
0 |
Anthropic non-stream request timeout (seconds, 0=use global non_stream_timeout) |
codex_first_byte_timeout |
0 |
Codex first valid stream content timeout (seconds, 0=use global upstream_first_byte_timeout) |
codex_non_stream_timeout |
0 |
Codex non-stream request timeout (seconds, 0=use global non_stream_timeout) |
openai_first_byte_timeout |
0 |
OpenAI first valid stream content timeout (seconds, 0=use global upstream_first_byte_timeout) |
openai_non_stream_timeout |
0 |
OpenAI non-stream request timeout (seconds, 0=use global non_stream_timeout) |
gemini_first_byte_timeout |
0 |
Gemini first valid stream content timeout (seconds, 0=use global upstream_first_byte_timeout) |
gemini_non_stream_timeout |
0 |
Gemini non-stream request timeout (seconds, 0=use global non_stream_timeout) |
enable_health_score |
false |
Enable health-based dynamic channel sorting |
success_rate_penalty_weight |
100 |
Success rate penalty weight (see below) |
health_score_window_minutes |
30 |
Success rate stats time window (minutes) |
health_score_update_interval |
30 |
Success rate cache update interval (seconds) |
health_min_confident_sample |
20 |
Confidence sample threshold (full penalty at this sample size) |
enable_ttfb_score |
false |
Enable relative first-byte latency penalty; requires enable_health_score |
ttfb_penalty_weight |
20 |
TTFB penalty when average first-byte latency is 2× the candidate median at full confidence |
ttfb_max_slow_ratio |
2 |
Upper bound for relative TTFB slowness (avg_ttfb / median_ttfb - 1) |
ttfb_min_confident_sample |
10 |
TTFB confidence sample threshold |
channel_check_interval_hours |
5 |
Scheduled channel check interval (hours, supports decimals, 0=disabled) |
model_catalog_sync_interval_hours |
6 |
Syncs the models.dev catalog every 6 hours; 0 disables network sync. At startup, the last-good cache is used, with the embedded catalog as fallback; channel cost_multiplier still applies. |
auto_update_interval_hours |
12 |
Auto-update check interval (hours, 0=disabled, minimum enabled value is 1) |
Per-protocol timeouts apply to the runtime upstream protocol: if a transformed request is forwarded to OpenAI, ccLoad reads openai_*_timeout; when that value is 0, it falls back to the global timeout.
ccLoad supports in-process auto updates. It checks releases every 12 hours by default, trying ghproxy.net first and GitHub directly if that source fails. A source is accepted only when release detection, binary download, checksum download, and SHA256 verification all succeed. The interval can be changed from the Web admin settings page via auto_update_interval_hours; set it to 0 to disable automatic update checks.
To use only a private mirror, set CCLOAD_RELEASE_BASE_URL to a complete latest-download base such as https://mirror.example/caidaoli/ccLoad/releases/latest/download. An explicit value disables the built-in fallback sources. This setting affects release downloads only; it does not configure HTTP_PROXY or HTTPS_PROXY for upstream API traffic.
When enable_health_score is enabled, ccLoad calculates an effective priority from recent channel health. The success-rate penalty is always active; the relative first-byte latency penalty is added only when enable_ttfb_score=true:
failure_confidence = min(1.0, sample_count / health_min_confident_sample)
failure_penalty = failure_rate × success_rate_penalty_weight × failure_confidence
relative_slowness = clamp(avg_ttfb / candidate_median_ttfb - 1, 0, ttfb_max_slow_ratio)
ttfb_confidence = min(1.0, ttfb_sample_count / ttfb_min_confident_sample)
ttfb_penalty = relative_slowness × ttfb_penalty_weight × ttfb_confidence
effective_priority = base_priority - failure_penalty - ttfb_penalty
Confidence factors prevent new or low-traffic channels from receiving a full penalty from a few samples. TTFB scoring compares successful first-byte samples against the median of the current candidate channels. Channels at or faster than the median receive no TTFB penalty, and scoring is skipped when fewer than two candidates have valid TTFB data.
Success-rate-only example (enable_ttfb_score=false, success_rate_penalty_weight = 100, health_min_confident_sample = 20):
| Channel | Base Priority | Success Rate | Samples | Confidence | Penalty | Effective Priority |
|---|---|---|---|---|---|---|
| A | 100 | 95% | 100 | 1.0 | 5 | 95 |
| B | 90 | 70% | 80 | 1.0 | 30 | 60 |
| C | 80 | 60% | 4 | 0.2 | 8 | 72 |
| D | 70 | 100% | 50 | 1.0 | 0 | 70 |
Base priority order: A > B > C > D Effective priority order: A (95) > C (72) > D (70) > B (60)
Important: API access tokens are normally managed in the Web admin interface; Docker and CI deployments can pre-seed them with an environment variable.
- Visit
http://localhost:8080/web/tokens.htmlfor token management - Set
CCLOAD_API_TOKENS=token1|production,token2|developmentto create missing tokens on startup - Provisioning is idempotent: existing tokens keep their description, limits, model/channel restrictions, and statistics
- Only missing tokens are created; existing tokens are never modified
- Supports add, delete, view tokens
- All tokens stored in database with persistence
- Without any tokens configured, all
/v1/*and/v1beta/*APIs return401 Unauthorized
- In production, prefer Docker Secrets, Kubernetes Secrets, or platform encrypted Secrets over plain environment variables
- In CI/CD, do not print full environment variables to logs
- After provisioning, remove
CCLOAD_API_TOKENSfrom deployment config if automatic recovery is no longer needed - Restrict access to container inspect output, orchestration dashboards, and deployment configuration
Advanced Token Features:
- Cost Limits: Set cost limits per token (USD), requests rejected with 429 when exceeded
- Model Restrictions: Restrict which models a token can access for fine-grained access control
- Channel Restrictions: Combine
allowed_channel_idswithchannel_restriction_mode—allowtreats the list as an allowlist,denyas a denylist; an empty list is unrestricted in either mode - Concurrency Limit:
max_concurrencycaps a token's simultaneous in-flight requests (0= unlimited) - First Byte Time: Records streaming request TTFB (milliseconds) for upstream latency diagnosis
CCLOAD_PASSnot set: Program fails to start and exits (secure default)- No API access tokens configured: All
/v1/*and/v1beta/*APIs return401 Unauthorized. Configure tokens via Web interface/web/tokens.html - Public endpoints:
GET /health(health check) andGET /public/summary(stats summary) require no auth, all others require auth token
Project supports multi-arch Docker images:
- Supported Architectures:
linux/amd64,linux/arm64 - Image Registry:
ghcr.io/caidaoli/ccload - Available Tags:
latest- Latest stable versionv2.44.1- Specific release tag, matching the GitHub Release tag
The official GHCR runtime image is Alpine-based. On container startup, it downloads and verifies the latest Linux release binary, trying ghproxy.net first and GitHub directly on failure. After ccLoad starts, its in-process updater uses the same source order. Set CCLOAD_RELEASE_BASE_URL to a complete .../releases/latest/download URL to use only a custom mirror. The default in-process check interval is 12 hours and can be changed with auto_update_interval_hours in the Web admin settings.
# Pull latest version
docker pull ghcr.io/caidaoli/ccload:latest
# Pull specific version
docker pull ghcr.io/caidaoli/ccload:v2.44.1
# Specify architecture (Docker usually auto-selects)
docker pull --platform linux/amd64 ghcr.io/caidaoli/ccload:latest
docker pull --platform linux/arm64 ghcr.io/caidaoli/ccload:latestStorage Architecture (Factory Pattern):
storage/
├── store.go # Store interface (unified contract)
├── factory.go # NewStore() auto-selects database
├── schema/ # Unified schema definition layer (2025-12 new)
│ ├── tables.go # Table definitions (DefineXxxTable functions)
│ └── builder.go # Schema builder (supports SQLite/MySQL/PostgreSQL differences)
├── sql/ # Common SQL implementation layer (2025-12 refactor, eliminated 467 lines)
│ ├── store_impl.go # SQLStore core implementation
│ ├── config.go # Channel config CRUD
│ ├── apikey.go # API key CRUD
│ ├── cooldown.go # Cooldown management
│ ├── log.go # Log storage
│ ├── metrics.go # Metrics stats
│ ├── metrics_filter.go # Filter intersection support
│ ├── metrics_aggregate_rows.go # Aggregate row processing
│ ├── metrics_finalize.go # Finalization processing
│ ├── auth_tokens.go # API access tokens
│ ├── auth_token_stats.go # Token statistics
│ ├── web_sessions.go # Role-aware Web sessions
│ ├── system_settings.go # System settings
│ └── helpers.go # Helper functions
└── sqlite/ # SQLite specific (test files only)
Database Selection Logic:
CCLOAD_MYSQLset → MySQL primary (fatal if also set withCCLOAD_POSTGRES)CCLOAD_POSTGRESset → PostgreSQL primary- Neither set → SQLite (default)
- Primary DSN +
CCLOAD_ENABLE_SQLITE_REPLICA=1→ Hybrid (primary write + SQLite read cache)
Core Table Structure (SQLite / MySQL / PostgreSQL shared):
channels- Channel config (channel-level cooldown inline, UNIQUE constraint on name, with protocol transform config, scheduled check config, RPM/concurrency limit config)api_keys- API keys (key-level cooldown inline, multi-key strategies)channel_model_cooldowns- Model-level runtime cooldown keyed by channel and actual upstream modellogs- Request logs (with base_url upstream URL tracking)debug_logs- Debug logs (upstream request/response raw data, independent cleanup policy)key_rr- Round-robin pointers (channel_id → idx)auth_tokens- Auth tokens (with cost limits, model/channel restrictions, concurrency limits, first byte time tracking)web_sessions- Role-aware Web sessions bound to an optional API tokensystem_settings- System config (hot reload support)
Architecture Features (✅ 2025-12 through 2026-04 continuous improvements):
- ✅ Unified SQL Layer (refactor): SQLite, MySQL, and PostgreSQL share
storage/sql/implementation - ✅ Unified Schema Definition (new):
storage/schema/defines table structures, supports database differences - ✅ Factory pattern unified interface (OCP, easy to extend new storage)
- ✅ Channel/Key cooldown data inline; model-scoped cooldown stored separately so one unavailable model does not disable the whole channel
- ✅ Performance index optimization (channel selection latency ↓30-50%, key lookup latency ↓40-60%)
- ✅ Composite index optimization (stats query performance improved)
- ✅ Foreign key constraints (cascade delete, ensures data consistency)
- ✅ Multi-key support (sequential/round_robin strategies)
- ✅ Auto migration (auto creates/updates table structure on startup)
- ✅ Token stats enhancement (time range selection, per-token ID classification, cache optimization)
- ✅ service_tier cost tracking: Logs persist service_tier field, cost column shows tier label
- ✅ Responses image tool cost tracking:
image_generationtool costs are included in logs, stats, and cost limit accounting - ✅ Tiered pricing engine: GPT-5.4/Qwen-Plus/Gemini long-context step billing
- ✅ Log UX improvements: Cost column formats to 3 decimal places (empty for zero), IP column shows full address on hover
- ✅ Protocol transform system: Anthropic/OpenAI/Gemini/Codex four-protocol cross-conversion, upstream/local modes
- ✅ Debug logs: Upstream request/response raw data capture, sensitive header masking, independent cleanup policy
- ✅ Scheduled channel checks: Background periodic channel availability probing, configurable check model per channel
- ✅ Channel RPM limits: Per-channel rolling 60-second request caps,
0means unlimited, over-limit channels are skipped - ✅ Channel concurrency limits: Per-channel in-flight request caps,
0means unlimited, over-limit channels are skipped
Backward Compatible Migration:
- Auto-detects and fixes duplicate channel names
- Intelligently adds UNIQUE constraints, ensures data integrity
- Runs automatically on startup, no manual intervention needed
- Log database merged into main database (single data source)
- Production must set strong password
CCLOAD_PASS - Configure API access tokens via Web admin
/web/tokens.htmlto protect API endpoint access - API keys used only in memory, not logged
- Only random Web-session tokens are stored in client localStorage, with a 24-hour expiry
- Recommend using HTTPS reverse proxy
- Docker images run as non-root user for enhanced security
ccLoad uses token-based authentication for simple and efficient secure access control.
Auth Methods:
- Web Interface: Login with an admin password or API token and receive a 24-hour Web-session token
- API Endpoints: Support
Authorization: Bearer <token>header auth
Core Features:
- ✅ Scoped Web Sessions: API-token sessions are read-only and server-bound to their own usage data
- ✅ Immediate Revocation: Disabling, deleting, or expiring an API token invalidates its Web session
- ✅ Credential Isolation: Plaintext API tokens are never stored in browser storage
- ✅ Server-side Authorization: Channel management, token management, settings, and debug data remain admin-only
Usage Example:
# 1. Login to get token
curl -X POST http://localhost:8080/login \
-H "Content-Type: application/json" \
-d '{"mode":"admin","password":"your_admin_password"}' | jq
# Response example:
# {
# "status": "success",
# "token": "abc123...", # 64-char hex token
# "expiresIn": 86400 # 24 hours (seconds)
# }
# 2. Use token to access admin API
curl http://localhost:8080/admin/channels \
-H "Authorization: Bearer <your_token>"
# 3. Logout (optional, token auto-expires after 24 hours)
curl -X POST http://localhost:8080/logout \
-H "Authorization: Bearer <your_token>"Project uses GitHub Actions for automated CI/CD:
- Trigger Conditions: Push version tags (
v*) or manual trigger - Build Output: Multi-arch Docker images pushed to GitHub Container Registry
- Version Management: Auto-generates semantic version tags
- Cache Optimization: Uses GitHub Actions cache to accelerate builds
Issues and Pull Requests welcome!
Use sonic for Go commands. Before sending a change, run the checks that match the touched area:
bash .agents/skills/sync-cliproxy-core/scripts/verify.sh --tests # snapshot audit + focused protocol tests
go test -tags sonic ./internal/...
make race-fast # high-value race subset
make race # full race suite
make verify-web # frontend node:test checks
golangci-lint run ./...When protocol translation changes, run the snapshot audit before the full internal test suite. make race-fast keeps the common race-sensitive packages fast enough for local iteration; use make race before larger or concurrency-sensitive changes. Override RACE_P or RACE_PARALLEL only when the machine needs a different parallelism cap.
Port In Use:
# Find and kill process using port 8080
lsof -i :8080 && kill -9 <PID>Container Issues:
# View container logs
docker logs ccload -f
# Check container health status
docker inspect ccload --format='{{.State.Health.Status}}'Config Validation:
# Test service health (lightweight health check, <5ms)
curl -s http://localhost:8080/health
# Or view stats summary (returns business data, 50-200ms)
curl -s http://localhost:8080/public/summary
# Check environment variable config
env | grep CCLOADMIT License. The synchronized translator snapshot under internal/protocol/cliproxy retains its upstream MIT notice and provenance record.

{ "custom_request_rules": { "headers": [ { "action": "override", "name": "User-Agent", "value": "claude-cli/1.0 (custom)" }, { "action": "remove", "name": "Anthropic-Beta", "value": "context-1m-2025-08-07" }, { "action": "append", "name": "Accept", "value": "application/json" } ], "body": [ { "action": "override", "path": "thinking", "value": {"type":"adaptive"} }, { "action": "override", "path": "max_tokens", "value": 4096 }, { "action": "remove", "path": "stop_sequences" } ] } }