feat: add OpenAI provider support
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@@ -5,7 +5,7 @@
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## ✨ 特性
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- 🚀 **基于 Cloudflare Workers**：无服务器架构，全球边缘部署
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- 🔐 **多渠道支持**：目前支持 Azure OpenAI，后续会继续增加其他 AI 服务提供商
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- 🔐 **多渠道支持**：支持 Azure OpenAI 和 OpenAI，后续会继续增加其他 AI 服务提供商
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- 🎫 **Token 管理**：完整的 API Token 生成、管理和配额控制
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- 📊 **使用量统计**：实时统计 API 使用量和费用
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- 💰 **定价管理**：灵活的模型定价配置
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@@ -26,6 +26,7 @@ awsl-one-api/
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│ │ └── index.ts # 管理接口路由
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│ ├── providers/ # AI 服务提供商
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│ │ ├── azure-openai-proxy.ts # Azure OpenAI 代理
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│ │ ├── openai-proxy.ts # OpenAI 代理
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│ │ └── index.ts # 提供商路由
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│ ├── db/ # 数据库相关
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│ ├── model/ # 数据模型
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@@ -44,9 +45,9 @@ awsl-one-api/
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```text
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┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
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│ Client Apps │───▶│ AWSL One API │───▶│ AI Providers │
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│ │ │ (CF Workers) │ │ (Azure OpenAI) │
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└─────────────────┘ └─────────────────┘ └─────────────────┘
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│
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│ │ │ (CF Workers) │ │(Azure OpenAI & │
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└─────────────────┘ └─────────────────┘ │ OpenAI) │
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│ └─────────────────┘
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▼
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┌─────────────────┐
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│ Cloudflare D1 │
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@@ -127,8 +128,13 @@ pnpm run deploy
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1. 在 Web 界面切换到 **🔗 频道管理** 标签
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2. 点击 **➕ 添加频道** 按钮
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3. 填写频道标识和配置信息
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4. 点击 **💾 保存频道** 按钮
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3. 选择频道类型（Azure OpenAI 或 OpenAI）
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4. 填写频道标识和配置信息：
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- 对于 OpenAI：填写基本信息（名称、端点、API密钥）和模型映射配置
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- 对于 Azure OpenAI：还需要配置 API 版本和模型部署映射
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5. 点击 **💾 保存频道** 按钮
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**提示**：系统会根据选择的频道类型自动显示相应的配置字段。
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### Token 创建和使用
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@@ -185,7 +191,7 @@ curl https://your-domain.com/v1/chat/completions \
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访问 `https://your-domain.com` 即可使用 Web 管理界面，功能包括：
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- **📊 数据库管理**：一键初始化数据库表结构
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- **🔗 频道配置管理**：添加、编辑、删除 AI 服务提供商频道
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- **🔗 频道配置管理**：添加、编辑、删除 AI 服务提供商频道（支持 Azure OpenAI 和 OpenAI）
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- **🔑 API Token 管理**：生成、管理和监控 API Token 使用情况
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- **💰 定价配置**：灵活配置不同模型的定价策略
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- **🧪 API 测试工具**：内置 API 测试界面，支持实时调试和错误排查
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@@ -194,21 +200,23 @@ curl https://your-domain.com/v1/chat/completions \
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- **现代化 UI**：响应式设计，支持桌面和移动设备
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- **实时反馈**：操作结果即时显示，支持悬浮提示
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- **智能表单**：自动生成 Token、JSON 格式验证、一键复制功能
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- **智能表单**：自动生成 Token、JSON 格式验证、一键复制功能，根据频道类型智能显示配置字段
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- **安全认证**：管理员 Token 认证，数据安全保护
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## 🔧 配置说明
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### 渠道配置
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目前支持 Azure OpenAI 服务提供商的配置：
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目前支持以下 AI 服务提供商：
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#### Azure OpenAI 配置
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```json
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{
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"name": "Azure OpenAI",
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"name": "My Azure OpenAI",
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"type": "azure-openai",
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"endpoint": "https://your-resource.openai.azure.com/",
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"api_key": "your-api-key",
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"api_key": "your-azure-api-key",
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"api_version": "2024-02-15-preview",
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"deployment_mapper": {
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"gpt-4": "gpt-4-deployment-name",
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@@ -217,14 +225,29 @@ curl https://your-domain.com/v1/chat/completions \
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}
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```
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#### OpenAI 配置
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```json
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{
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"name": "My OpenAI Channel",
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"type": "openai",
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"endpoint": "https://api.openai.com/v1/",
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"api_key": "sk-your-openai-api-key",
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"deployment_mapper": {
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"gpt-4": "gpt-4",
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"gpt-3.5-turbo": "gpt-3.5-turbo"
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}
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}
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```
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**配置说明**：
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- `name`: 频道显示名称
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- `type`: 服务提供商类型（如 `azure-openai`）
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- `type`: 服务提供商类型（`azure-openai` 或 `openai`）
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- `endpoint`: API 端点地址
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- `api_key`: API 密钥
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- `api_version`: API 版本
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- `deployment_mapper`: 模型名称映射关系
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- `api_version`: API 版本（仅 Azure OpenAI 需要）
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- `deployment_mapper`: 模型名称映射关系（用于自定义模型名称映射）
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### Token 配置
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+6
-4
@@ -842,12 +842,14 @@
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<div id="channelFormMode">
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<div class="form-group">
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<label for="channelName">频道名称</label>
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<input type="text" id="channelName" class="form-control" placeholder="例如: Azure OpenAI">
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<input type="text" id="channelName" class="form-control"
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placeholder="例如: My OpenAI Channel">
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</div>
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<div class="form-group">
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<label for="channelType">频道类型</label>
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<select id="channelType" class="form-control" onchange="toggleApiVersionField()">
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<option value="azure-openai">Azure OpenAI</option>
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<option value="openai">OpenAI</option>
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</select>
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</div>
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<div class="form-group">
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@@ -869,7 +871,7 @@
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<label for="deploymentMapper">模型部署映射 (JSON)</label>
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<textarea id="deploymentMapper" class="form-control" rows="4"
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placeholder='{"gpt-35-turbo": "gpt-35-turbo", "gpt-4": "gpt-4"}'></textarea>
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<small style="color: #666; font-size: 12px;">配置模型名称到部署名称的映射关系</small>
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<small style="color: #666; font-size: 12px;">配置模型名称映射关系（主要用于Azure OpenAI）</small>
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</div>
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<div class="form-group">
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<label for="additionalConfig">其他配置 (JSON，可选)</label>
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@@ -1695,8 +1697,8 @@
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// 重置表单状态
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FormUtils.setReadonly('channelKey', false);
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DOMUtils.setValue('channelType', 'azure-openai');
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DOMUtils.getElement('channelKey').placeholder = '例如: azure-openai-1';
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DOMUtils.setValue('channelType', 'openai');
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DOMUtils.getElement('channelKey').placeholder = '例如: openai-1';
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// 重置编辑模式
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channelModeManager.resetToFormMode();
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@@ -2,9 +2,9 @@ import { Context, Hono } from "hono"
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import { contentJson, fromHono, OpenAPIRoute } from 'chanfana';
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import azureOpenaiProxy from "./azure-openai-proxy"
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import openaiProxy from "./openai-proxy"
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import utils from "../utils"
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import { TokenUtils } from "../admin/token_utils"
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import { ChannelConfigRow } from "../db/db_model"
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import { CONSTANTS } from "../constants"
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import { z } from "zod";
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@@ -19,6 +19,7 @@ const providerMap: Record<
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) => Promise<Response>
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> = {
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"azure-openai": azureOpenaiProxy.fetch,
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"openai": openaiProxy.fetch,
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};
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class ProxyEndpoint extends OpenAPIRoute {
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@@ -0,0 +1,134 @@
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import { Context } from "hono"
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import { streamText } from 'hono/streaming'
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// 辅助函数
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const buildProxyRequest = (
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request: Request,
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reqJson: any,
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config: ChannelConfig
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): Request => {
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const url = new URL(request.url)
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const targetUrl = new URL(config.endpoint)
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targetUrl.pathname = url.pathname
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const targetHeaders = new Headers(request.headers)
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targetHeaders.set("Authorization", `Bearer ${config.api_key}`)
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return new Request(targetUrl, {
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method: request.method,
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headers: targetHeaders,
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body: JSON.stringify(reqJson),
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})
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}
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const checkoutUsageData = async (
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saveUsage: (usage: Usage) => Promise<void>,
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response: Response | OpenAIResponse
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): Promise<void> => {
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try {
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const res = response instanceof Response
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? await response.clone().json<OpenAIResponse>()
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: response
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if (!res.usage) return;
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await saveUsage(res.usage)
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} catch (error) {
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console.error("Error logging usage data:", error)
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}
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}
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const processStreamData = (
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lines: string[],
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saveUsage: (usage: Usage) => Promise<void>
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): void => {
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lines
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.map(line => line.trim())
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.filter(line => line.length > 0 && line.startsWith('data:'))
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.map(line => line.replace('data: ', '').trim())
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.filter(line => line !== '[DONE]')
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.forEach(jsonContent => {
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try {
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const res = JSON.parse(jsonContent) as OpenAIResponse
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checkoutUsageData(saveUsage, res)
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} catch (e) {
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console.error("Error parsing stream data:", e)
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}
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})
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}
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const handleStreamResponse = async (
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c: Context<HonoCustomType>,
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response: Response,
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saveUsage: (usage: Usage) => Promise<void>
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): Promise<Response> => {
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return streamText(c, async (stream) => {
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const reader = response.body?.getReader()
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if (!reader) {
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throw new Error("No reader found in response body")
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}
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const decoder = new TextDecoder('utf-8')
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let buffer = ""
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while (true) {
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const { done, value } = await reader.read()
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if (done) break
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const chunk = decoder.decode(value, { stream: true })
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await stream.write(chunk)
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buffer += chunk
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if (!chunk.includes('\n')) continue
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const lines = buffer.split('\n')
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buffer = lines.pop() || ""
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processStreamData(lines, saveUsage)
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}
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// 处理最后剩余的数据
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if (buffer.trim()) {
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processStreamData([buffer], saveUsage)
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}
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})
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}
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export default {
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async fetch(
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c: Context<HonoCustomType>,
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config: ChannelConfig,
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saveUsage: (usage: Usage) => Promise<void>,
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): Promise<Response> {
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// 准备请求数据
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const reqJson = await c.req.json()
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// 强制包含使用数据
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const { model: modelName, stream } = reqJson;
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if (stream) {
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reqJson.stream_options = { "include_usage": true }
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}
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// 检查模型是否受支持
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const deploymentName = config.deployment_mapper[modelName]
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if (!deploymentName) {
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throw new Error(`Model ${modelName} not supported`)
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}
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// 构建目标请求
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const proxyRequest = buildProxyRequest(c.req.raw, reqJson, config)
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// 发送请求并获取响应
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const response = await fetch(proxyRequest)
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// 处理流式响应
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if (stream) {
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return handleStreamResponse(c, response, saveUsage)
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}
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// 处理常规响应
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if (response.ok) {
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await checkoutUsageData(saveUsage, response)
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}
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return response
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}
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}
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