docs: 添加使用示范和启动指南
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- examples/demo_usage.py: Python 使用示范(openai SDK + requests)
- examples/demo_usage.go: Go 使用示范(net/http)
- run.md: 完整启动指南(前置条件、3种启动方式、API Key 配置、验证命令)
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# Edge AI Gateway 启动指南
## 前置条件
### 1. 安装 Go
```bash
# macOS
brew install go
# Linux
wget https://go.dev/dl/go1.23.0.linux-amd64.tar.gz
sudo tar -C /usr/local -xzf go1.23.0.linux-amd64.tar.gz
export PATH=$PATH:/usr/local/go/bin
```
### 2. 安装 Ollama(本地推理引擎)
```bash
# macOS
brew install ollama
# Linux
curl -fsSL https://ollama.com/install.sh | sh
# 拉取模型
ollama pull deepseek-r1:1.5b
```
### 3. 安装 SQLite
```bash
# macOS(自带)
# Linux
sudo apt install sqlite3
```
## 启动方式
### 方式一:直接运行
```bash
# 1. 创建数据目录
mkdir -p /tmp/edgeai-data
# 2. 启动 Ollama(另一个终端)
ollama serve
# 3. 启动 Edge AI Gateway
EDGEAI_DB_PATH=/tmp/edgeai-data go run ./cmd/gateway/ --config configs/config.yaml
```
服务器将在 `http://0.0.0.0:8080` 启动。
### 方式二:编译后运行
```bash
# 1. 编译
go build -o bin/gateway ./cmd/gateway/
# 2. 启动
EDGEAI_DB_PATH=/tmp/edgeai-data ./bin/gateway --config configs/config.yaml
```
### 方式三:Docker Compose
```bash
cd deploy
docker-compose up -d
```
服务端口:
- Gateway: http://localhost:8080
- Ollama: http://localhost:11434
- Prometheus: http://localhost:9090
- Grafana: http://localhost:3000
## 配置 API Key
首次启动后需要创建 API Key
```bash
# 1. 计算 key 的 SHA-256 哈希
HASH=$(echo -n "your-api-key" | shasum -a 256 | awk '{print $1}')
# 2. 插入数据库
sqlite3 /tmp/edgeai-data/auth.db "INSERT INTO api_keys (app_id, tenant_id, name, key_hash, allowed_models, allowed_priorities, is_admin, enabled) VALUES ('my-app', 'my-tenant', 'my-key', '$HASH', '[]', '[]', 1, 1);"
# 3. 重启服务器使 key 生效
```
## 环境变量
| 变量 | 默认值 | 说明 |
|------|--------|------|
| `EDGEAI_DB_PATH` | `/var/lib/edgeai` | 数据库目录 |
| `EDGEAI_SERVER_PORT` | `8080` | 服务端口 |
| `EDGEAI_LOG_LEVEL` | `info` | 日志级别 |
| `EDGEAI_CONFIG_PATH` | `configs/config.yaml` | 配置文件路径 |
## 验证
```bash
# 健康检查
curl http://localhost:8080/health
# 查看模型(需 API Key
curl -H "Authorization: Bearer your-api-key" http://localhost:8080/v1/models
# 非流式对话
curl -X POST http://localhost:8080/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer your-api-key" \
-d '{"model":"general-chat","messages":[{"role":"user","content":"你好"}]}'
# 流式对话
curl -N -X POST http://localhost:8080/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer your-api-key" \
-d '{"model":"fast-chat","messages":[{"role":"user","content":"你好"}],"stream":true}'
# Prometheus 指标
curl http://localhost:8080/metrics
```
## 可选:启动 vLLM
```bash
# 安装 vLLM
pip install vllm
# 启动 vLLM 服务(端口 8000
vllm serve --model deepseek-ai/deepseek-r1-1.5b --port 8000
# 然后在 Gateway 配置中使用 vllm-chat 模型
```
## 运行测试
```bash
# 单元测试
go test ./internal/... -count=1
# 集成测试
go test ./test/integration/ -count=1
# 全部测试
go test ./internal/... -count=1 && \
go test ./test/integration/ -count=1 && \
go test ./test/security/ -count=1 && \
go test ./test/compatibility/ -count=1 && \
go test ./test/performance/ -count=1 && \
go test ./test/chaos/ -count=1
```