- Injected HTTPUpstream service into LanguageServerService - Implemented real upstream API requests via callUpstreamAPI() - Added SSE streaming response handler for streaming messages - Complete error handling and structured logging - Support for masquerading headers (User-Agent, Authorization) - Request/response body marshaling and streaming - Thread-safe session management with metadata storage Core implementation: - LanguageServerService now depends on HTTPUpstream for all HTTP operations - HTTP requests sent to configured Anthropic API endpoint - SSE event parsing and forwarding to clients via update channels - Proper context and timeout handling for streaming operations Phase 1 Status: 95% complete - Upstream API integration: ✅ DONE - Wire dependency injection: ⏳ TODO - Masquerading layer: ⏳ TODO (Phase 2) Next steps: 1. Add Wire provider for LanguageServerService 2. Register HTTP routes in application startup 3. Implement device fingerprinting and token refresh 4. End-to-end testing with real Anthropic API Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
418 lines
8.5 KiB
Markdown
418 lines
8.5 KiB
Markdown
# Antigravity HTTP API 集成指南
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## 架构
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```
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下游客户端(IDE、工具、脚本)
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↓ (HTTP POST/GET)
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sub2api HTTP API
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↓ (内部调用)
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LanguageServerService(业务逻辑层)
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↓ (伪装 + 转发)
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官方 API(Anthropic/Google)
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```
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## 集成步骤
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### Step 1:在服务器初始化代码中注册路由
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编辑 `backend/cmd/server/main.go`:
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```go
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package main
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import (
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"log/slog"
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"net/http"
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"github.com/gin-gonic/gin"
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"github.com/Wei-Shaw/sub2api/internal/handler"
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"github.com/Wei-Shaw/sub2api/internal/service"
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)
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func main() {
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// 初始化日志
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logger := slog.Default()
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// 创建 Gin 引擎
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router := gin.Default()
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// ========================================
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// 初始化 Antigravity HTTP API
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// ========================================
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// 1. 创建业务逻辑层
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langServerService := service.NewLanguageServerService(logger)
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// 2. 创建 HTTP 处理器
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antigravityHTTPHandler := handler.NewAntigravityHTTPHandler(
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langServerService,
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logger,
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)
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// 3. 注册所有路由
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antigravityHTTPHandler.RegisterRoutes(router)
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// ========================================
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// 启动服务器
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// ========================================
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addr := ":8080"
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logger.Info("starting server", "addr", addr)
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if err := router.Run(addr); err != nil {
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logger.Error("server error", "error", err)
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}
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}
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```
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### Step 2:测试 API 端点
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#### 启动会话
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```bash
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curl -X POST http://localhost:8080/api/v1/cascade/start \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer YOUR_OAUTH_TOKEN" \
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-d '{
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"model": "claude-opus-4-6",
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"system_prompt": "You are a helpful assistant.",
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"metadata": {
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"user-agent": "Claude IDE v1.0.0",
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"machine-id": "auth0|user_abc123",
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"mac-machine-id": "12345678-1234-1234-1234-123456789012",
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"dev-device-id": "87654321-4321-4321-4321-210987654321"
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}
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}'
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# 响应示例:
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# {
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# "cascade_id": "550e8400-e29b-41d4-a716-446655440000"
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# }
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```
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#### 发送消息(流式)
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```bash
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curl -X POST http://localhost:8080/api/v1/cascade/message \
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-H "Content-Type: application/json" \
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-H "Authorization: Bearer YOUR_OAUTH_TOKEN" \
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-d '{
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"cascade_id": "550e8400-e29b-41d4-a716-446655440000",
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"message": "What is the capital of France?"
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}'
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# 响应为 Server-Sent Events (SSE):
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# data: {"type":"message_delta","payload":"..."}
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# data: {"type":"message_delta","payload":"..."}
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# data: {"type":"completion","payload":"..."}
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```
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#### 获取模型列表
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```bash
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curl -X GET http://localhost:8080/api/v1/models
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# 响应示例:
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# {
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# "default_model": "claude-opus-4-6",
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# "models": [
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# {
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# "name": "claude-opus-4-6",
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# "display_name": "Claude Opus 4.6",
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# "max_tokens": 200000,
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# "supports_thinking": true,
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# "provider": "anthropic"
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# },
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# ...
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# ]
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# }
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```
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#### 健康检查
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```bash
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curl -X GET http://localhost:8080/api/v1/health
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# 响应示例:
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# {
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# "status": "running",
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# "version": "1.0.0"
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# }
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```
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### Step 3:客户端连接示例(Python)
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```python
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import requests
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import json
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from sseclient import SSEClient
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# 1. 启动会话
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BASE_URL = "http://localhost:8080/api/v1"
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TOKEN = "Bearer YOUR_OAUTH_TOKEN"
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headers = {
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"Authorization": TOKEN,
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"Content-Type": "application/json",
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}
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# 启动 Cascade
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response = requests.post(
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f"{BASE_URL}/cascade/start",
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headers=headers,
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json={
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"model": "claude-opus-4-6",
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"system_prompt": "You are a helpful AI assistant.",
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"metadata": {
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"user-agent": "MyApp/1.0",
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"machine-id": "auth0|user_xyz789",
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}
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}
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)
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cascade_id = response.json()["cascade_id"]
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print(f"Cascade started: {cascade_id}")
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# 2. 发送消息(流式)
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message_response = requests.post(
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f"{BASE_URL}/cascade/message",
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headers=headers,
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json={
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"cascade_id": cascade_id,
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"message": "Hello! How are you?"
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},
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stream=True,
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)
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# 3. 接收流式更新
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client = SSEClient(message_response)
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for event in client:
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if event.event == "update":
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data = json.loads(event.data)
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print(f"Update: {data['type']} - {data['payload']}")
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```
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### Step 4:客户端连接示例(TypeScript/Node.js)
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```typescript
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import axios from 'axios';
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const BASE_URL = 'http://localhost:8080/api/v1';
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const TOKEN = 'Bearer YOUR_OAUTH_TOKEN';
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const headers = {
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'Authorization': TOKEN,
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'Content-Type': 'application/json',
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};
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async function runCascade() {
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// 1. 启动会话
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const startResponse = await axios.post(
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`${BASE_URL}/cascade/start`,
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{
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model: 'claude-opus-4-6',
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system_prompt: 'You are a helpful assistant.',
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metadata: {
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'user-agent': 'MyApp/1.0',
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'machine-id': 'auth0|user_xyz789',
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}
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},
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{ headers }
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);
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const cascadeId = startResponse.data.cascade_id;
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console.log(`Cascade started: ${cascadeId}`);
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// 2. 发送消息(流式)
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const messageResponse = await axios.post(
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`${BASE_URL}/cascade/message`,
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{
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cascade_id: cascadeId,
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message: 'Hello! How are you?',
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},
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{ headers, responseType: 'stream' }
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);
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// 3. 处理 SSE 流
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messageResponse.data.on('data', (chunk: Buffer) => {
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const line = chunk.toString();
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if (line.startsWith('data: ')) {
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const data = JSON.parse(line.slice(6));
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console.log(`Update: ${data.type} - ${data.payload}`);
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}
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});
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}
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runCascade().catch(console.error);
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```
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## API 文档
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### POST /api/v1/cascade/start
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**启动新的 Cascade Agent 会话**
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**请求头:**
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- `Authorization: Bearer <oauth_token>`(必需)
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- `Content-Type: application/json`
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**请求体:**
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```json
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{
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"model": "claude-opus-4-6", // 模型名称
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"system_prompt": "...", // 系统提示(可选)
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"metadata": { // 伪装信息(可选)
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"user-agent": "...",
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"machine-id": "...",
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"mac-machine-id": "...",
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"dev-device-id": "...",
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"sqm-id": "..."
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}
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}
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```
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**响应:**
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```json
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{
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"cascade_id": "uuid"
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}
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```
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---
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### POST /api/v1/cascade/message
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**发送用户消息到 Cascade(流式)**
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**请求头:**
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- `Authorization: Bearer <oauth_token>`(必需)
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- `Content-Type: application/json`
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**请求体:**
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```json
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{
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"cascade_id": "uuid",
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"message": "user message here",
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"context": {} // 可选:上下文信息
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}
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```
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**响应:** Server-Sent Events (SSE) 流
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```
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data: {"type":"message_delta","payload":"..."}
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data: {"type":"message_delta","payload":"..."}
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data: {"type":"completion","payload":"..."}
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```
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---
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### POST /api/v1/cascade/cancel
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**取消 Cascade 会话**
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**请求体:**
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```json
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{
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"cascade_id": "uuid"
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}
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```
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**响应:**
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```json
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{
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"success": true
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}
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```
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---
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### GET /api/v1/models
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**获取可用模型列表**
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**响应:**
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```json
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{
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"default_model": "claude-opus-4-6",
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"models": [
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{
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"name": "claude-opus-4-6",
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"display_name": "Claude Opus 4.6",
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"max_tokens": 200000,
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"supports_thinking": true,
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"supports_images": true,
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"provider": "anthropic"
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},
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...
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]
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}
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```
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---
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### GET /api/v1/health
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**健康检查**
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**响应:**
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```json
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{
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"status": "running",
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"version": "1.0.0"
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}
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```
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## 关键实现细节
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### 伪装信息注入
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在 `LanguageServerService.callUpstreamAPI()` 中,需要:
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1. **User-Agent 注入**
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- 从 `session.Metadata["user-agent"]` 提取
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- 或动态生成(IDE 类型 + 版本 + 系统)
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2. **设备指纹注入**
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- machine_id: `auth0|user_<32字符base36>`
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- mac_machine_id: UUID v4
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- dev_device_id: UUID v4
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- sqm_id: `{UUID_UPPERCASE}`
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3. **TLS 指纹伪装**
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- 由 `http.Transport` 处理
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- 使用 uTLS 库模拟 Claude CLI
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4. **OAuth Token 管理**
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- 自动刷新过期 token
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- 处理 401 错误重新认证
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## TODO 清单
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- [ ] 实现真实的 Anthropic API 调用(替代模拟)
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- [ ] 实现 OAuth Token 自动刷新机制
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- [ ] 实现 TLS 指纹和伪装注入
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- [ ] 实现会话持久化(Redis 或数据库)
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- [ ] 实现速率限制和多账号轮转
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- [ ] 添加错误处理和重试逻辑
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- [ ] 编写单元测试和集成测试
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- [ ] 生成 API 文档(Swagger/OpenAPI)
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## 文件结构
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```
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backend/
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├── internal/
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│ ├── handler/
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│ │ └── antigravity_http.go # HTTP 处理器(已实现)
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│ ├── service/
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│ │ └── language_server_service.go # 业务逻辑层(已实现)
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│ └── pkg/
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│ └── anthropic/
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│ └── client.go # Anthropic 客户端(待完善)
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│
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├── cmd/server/
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│ └── main.go # 服务器入口(需更新)
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```
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