From 5bcfbdb88d10403b2457eccfaa620610af91e913 Mon Sep 17 00:00:00 2001
From: freedakgmail <freedak.gemini@gmail.com>
Date: Mon, 3 Aug 2026 07:57:31 +0800
Subject: [PATCH] =?UTF-8?q?docs:=20=E6=B7=BB=E5=8A=A0=E4=BD=BF=E7=94=A8?=
 =?UTF-8?q?=E7=A4=BA=E8=8C=83=E5=92=8C=E5=90=AF=E5=8A=A8=E6=8C=87=E5=8D=97?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

- 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）
---
 examples/demo_usage.go | 141 +++++++++++++++++++++++++++++++
 examples/demo_usage.py | 184 +++++++++++++++++++++++++++++++++++++++++
 run.md                 | 154 ++++++++++++++++++++++++++++++++++
 3 files changed, 479 insertions(+)
 create mode 100644 examples/demo_usage.go
 create mode 100644 examples/demo_usage.py
 create mode 100644 run.md

diff --git a/examples/demo_usage.go b/examples/demo_usage.go
new file mode 100644
index 0000000..3e8b7e4
--- /dev/null
+++ b/examples/demo_usage.go
@@ -0,0 +1,141 @@
+// Edge AI Gateway 使用示范 (Go 版本)
+//
+// 演示 Go 应用如何调用 Edge AI Gateway 的 OpenAI 兼容 API。
+//
+// 运行：go run examples/demo_usage.go
+package main
+
+import (
+	"bufio"
+	"encoding/json"
+	"fmt"
+	"io"
+	"net/http"
+	"strings"
+)
+
+const (
+	BaseURL = "http://localhost:8080"
+	APIKey  = "test-key"
+)
+
+func main() {
+	// === 1. 非流式对话 ===
+	fmt.Println("=== 非流式对话 ===")
+	resp := doPost(BaseURL+"/v1/chat/completions", map[string]any{
+		"model":    "general-chat",
+		"messages": []map[string]string{{"role": "user", "content": "你好，介绍一下你自己"}},
+		"stream":   false,
+	})
+	fmt.Printf("回复: %s\n", resp["choices"].([]any)[0].(map[string]any)["message"].(map[string]any)["content"])
+	fmt.Printf("模型: %s\n", resp["actual_model"])
+	fmt.Println()
+
+	// === 2. 流式对话 (SSE) ===
+	fmt.Println("=== 流式对话 ===")
+	doStream(BaseURL+"/v1/chat/completions", map[string]any{
+		"model":    "fast-chat",
+		"messages": []map[string]string{{"role": "user", "content": "写一个Go hello world"}},
+		"stream":   true,
+	})
+	fmt.Println()
+
+	// === 3. 查看模型列表 ===
+	fmt.Println("=== 可用模型 ===")
+	resp2 := doGet(BaseURL + "/v1/models")
+	for _, m := range resp2["data"].([]any) {
+		fmt.Printf("  - %s\n", m.(map[string]any)["id"])
+	}
+	fmt.Println()
+
+	// === 4. 会话管理 ===
+	fmt.Println("=== 会话管理 ===")
+	sess := doPost(BaseURL+"/v1/sessions", map[string]any{
+		"application_id": "demo-app",
+		"user_id":        "user1",
+	})
+	sessionID := sess["session_id"].(string)
+	fmt.Printf("创建会话: %s\n\n", sessionID)
+
+	// === 5. 错误处理 ===
+	fmt.Println("=== 错误处理 ===")
+	// 无认证
+	resp3, _ := http.Get(BaseURL + "/v1/models")
+	fmt.Printf("无认证: HTTP %d\n", resp3.StatusCode)
+	resp3.Body.Close()
+	// 缺少 model
+	resp4 := doPost(BaseURL+"/v1/chat/completions", map[string]any{
+		"messages": []map[string]string{{"role": "user", "content": "hi"}},
+	})
+	if err, ok := resp4["error"]; ok {
+		fmt.Printf("缺少model: %s\n", err.(map[string]any)["code"])
+	}
+
+	fmt.Println("\n✅ 示范完成！")
+}
+
+func doPost(url string, body map[string]any) map[string]any {
+	b, _ := json.Marshal(body)
+	req, _ := http.NewRequest("POST", url, strings.NewReader(string(b)))
+	req.Header.Set("Content-Type", "application/json")
+	req.Header.Set("Authorization", "Bearer "+APIKey)
+	resp, err := http.DefaultClient.Do(req)
+	if err != nil {
+		fmt.Printf("请求失败: %v\n", err)
+		return nil
+	}
+	defer resp.Body.Close()
+	data, _ := io.ReadAll(resp.Body)
+	var result map[string]any
+	json.Unmarshal(data, &result)
+	return result
+}
+
+func doGet(url string) map[string]any {
+	req, _ := http.NewRequest("GET", url, nil)
+	req.Header.Set("Authorization", "Bearer "+APIKey)
+	resp, err := http.DefaultClient.Do(req)
+	if err != nil {
+		fmt.Printf("请求失败: %v\n", err)
+		return nil
+	}
+	defer resp.Body.Close()
+	data, _ := io.ReadAll(resp.Body)
+	var result map[string]any
+	json.Unmarshal(data, &result)
+	return result
+}
+
+func doStream(url string, body map[string]any) {
+	b, _ := json.Marshal(body)
+	req, _ := http.NewRequest("POST", url, strings.NewReader(string(b)))
+	req.Header.Set("Content-Type", "application/json")
+	req.Header.Set("Authorization", "Bearer "+APIKey)
+	resp, err := http.DefaultClient.Do(req)
+	if err != nil {
+		fmt.Printf("请求失败: %v\n", err)
+		return
+	}
+	defer resp.Body.Close()
+	scanner := bufio.NewScanner(resp.Body)
+	for scanner.Scan() {
+		line := scanner.Text()
+		if !strings.HasPrefix(line, "data: ") {
+			continue
+		}
+		data := strings.TrimPrefix(line, "data: ")
+		if data == "[DONE]" {
+			return
+		}
+		var chunk map[string]any
+		json.Unmarshal([]byte(data), &chunk)
+		choices := chunk["choices"].([]any)
+		delta := choices[0].(map[string]any)["delta"].(map[string]any)
+		if content, ok := delta["content"]; ok {
+			fmt.Print(content.(string))
+		}
+	}
+	if err := scanner.Err(); err != nil {
+		fmt.Printf("\nstream error: %v\n", err)
+	}
+}
diff --git a/examples/demo_usage.py b/examples/demo_usage.py
new file mode 100644
index 0000000..19d1329
--- /dev/null
+++ b/examples/demo_usage.py
@@ -0,0 +1,184 @@
+#!/usr/bin/env python3
+"""
+Edge AI Gateway 使用示范
+
+本文件演示其他应用如何通过 OpenAI 兼容 API 调用 Edge AI Gateway。
+支持两种方式：
+1. 使用 openai SDK（推荐）
+2. 使用 requests 库直接调用
+
+运行前请确保：
+- Edge AI Gateway 已启动 (默认 http://localhost:8080)
+- 已配置有效的 API Key
+"""
+
+# ============================================================
+# 方式一：使用 openai SDK（推荐）
+# ============================================================
+# pip install openai
+
+from openai import OpenAI
+
+client = OpenAI(
+    base_url="http://localhost:8080/v1",
+    api_key="test-key",  # 替换为你的 API Key
+)
+
+# --- 非流式对话 ---
+print("=== 非流式对话 ===")
+response = client.chat.completions.create(
+    model="general-chat",  # 逻辑模型名，网关自动路由到实际模型
+    messages=[
+        {"role": "system", "content": "你是一个简洁的助手"},
+        {"role": "user", "content": "你好，介绍一下你自己"},
+    ],
+    stream=False,
+)
+print(f"回复: {response.choices[0].message.content}")
+print(f"Token: 输入={response.usage.prompt_tokens}, 输出={response.usage.completion_tokens}")
+print()
+
+# --- 流式对话 (SSE) ---
+print("=== 流式对话 ===")
+stream = client.chat.completions.create(
+    model="fast-chat",
+    messages=[
+        {"role": "user", "content": "写一个 Python 的 hello world"},
+    ],
+    stream=True,
+)
+for chunk in stream:
+    delta = chunk.choices[0].delta.content
+    if delta:
+        print(delta, end="", flush=True)
+print("\n")
+
+# --- 带优先级的请求 (P0 最高) ---
+print("=== 高优先级请求 ===")
+response = client.chat.completions.create(
+    model="general-chat",
+    messages=[{"role": "user", "content": "1+1=?"}],
+    extra_headers={"X-Priority": "P0"},  # 通过 header 传递优先级
+)
+print(f"回复: {response.choices[0].message.content}")
+print()
+
+# --- 查看可用模型 ---
+print("=== 可用模型 ===")
+models = client.models.list()
+for m in models.data:
+    print(f"  - {m.id}")
+print()
+
+
+# ============================================================
+# 方式二：使用 requests 库直接调用
+# ============================================================
+# pip install requests
+
+import requests
+
+BASE_URL = "http://localhost:8080"
+API_KEY = "test-key"
+HEADERS = {
+    "Authorization": f"Bearer {API_KEY}",
+    "Content-Type": "application/json",
+}
+
+# --- 非流式 ---
+print("=== requests: 非流式 ===")
+resp = requests.post(
+    f"{BASE_URL}/v1/chat/completions",
+    headers=HEADERS,
+    json={
+        "model": "general-chat",
+        "messages": [{"role": "user", "content": "你好"}],
+        "stream": False,
+    },
+)
+data = resp.json()
+print(f"状态: {data.get('status')}")
+print(f"回复: {data['choices'][0]['message']['content']}")
+print(f"模型: {data.get('actual_model')}")
+print()
+
+# --- 流式 (SSE) ---
+print("=== requests: 流式 ===")
+resp = requests.post(
+    f"{BASE_URL}/v1/chat/completions",
+    headers=HEADERS,
+    json={
+        "model": "fast-chat",
+        "messages": [{"role": "user", "content": "讲个笑话"}],
+        "stream": True,
+    },
+    stream=True,
+)
+for line in resp.iter_lines():
+    if line:
+        line = line.decode("utf-8")
+        if line.startswith("data: ") and line != "data: [DONE]":
+            import json
+            chunk = json.loads(line[6:])
+            delta = chunk["choices"][0]["delta"].get("content", "")
+            if delta:
+                print(delta, end="", flush=True)
+print("\n")
+
+# --- 会话管理 ---
+print("=== 会话管理 ===")
+# 创建会话
+resp = requests.post(
+    f"{BASE_URL}/v1/sessions",
+    headers=HEADERS,
+    json={"application_id": "my-app", "user_id": "user123"},
+)
+session = resp.json()
+session_id = session["session_id"]
+print(f"创建会话: {session_id}")
+
+# 查询会话
+resp = requests.get(
+    f"{BASE_URL}/v1/sessions/{session_id}",
+    headers=HEADERS,
+)
+print(f"会话信息: {resp.json()}")
+
+# 删除会话
+resp = requests.delete(
+    f"{BASE_URL}/v1/sessions/{session_id}",
+    headers=HEADERS,
+)
+print(f"删除会话: HTTP {resp.status_code}")
+print()
+
+# --- 错误处理 ---
+print("=== 错误处理 ===")
+# 无认证
+resp = requests.get(f"{BASE_URL}/v1/models")
+print(f"无认证: {resp.status_code} - {resp.json()['error']['code']}")
+
+# 无效 key
+resp = requests.get(
+    f"{BASE_URL}/v1/models",
+    headers={"Authorization": "Bearer invalid-key"},
+)
+print(f"无效key: {resp.status_code} - {resp.json()['error']['code']}")
+
+# 缺少 model
+resp = requests.post(
+    f"{BASE_URL}/v1/chat/completions",
+    headers=HEADERS,
+    json={"messages": [{"role": "user", "content": "hi"}]},
+)
+print(f"缺少model: {resp.status_code} - {resp.json()['error']['code']}")
+
+# 未知 model
+resp = requests.post(
+    f"{BASE_URL}/v1/chat/completions",
+    headers=HEADERS,
+    json={"model": "nonexistent", "messages": [{"role": "user", "content": "hi"}]},
+)
+print(f"未知model: {resp.status_code} - {resp.json()['error']['code']}")
+
+print("\n✅ 示范完成！")
diff --git a/run.md b/run.md
new file mode 100644
index 0000000..ff0a1eb
--- /dev/null
+++ b/run.md
@@ -0,0 +1,154 @@
+# 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
+```