mirror of
https://github.com/farion1231/cc-switch.git
synced 2026-07-30 02:14:43 +08:00
YoVinchen
a35d112cd4
This major refactoring introduces a modular provider adapter architecture to support format transformation between different AI API formats. New features: - Add ProviderAdapter trait for unified provider abstraction - Implement Claude, Codex, and Gemini adapters with specific logic - Add Anthropic ↔ OpenAI format transformation for OpenRouter compatibility - Support model mapping from provider configuration (ANTHROPIC_MODEL, etc.) - Add OpenRouter preset to Claude provider presets Refactoring: - Extract authentication logic into auth.rs with AuthInfo and AuthStrategy - Move URL building and request transformation to individual adapters - Simplify ProviderRouter to only use proxy target providers - Refactor RequestForwarder to use adapter-based request/response handling - Use whitelist mode for header forwarding (only pass necessary headers) Architecture: - providers/adapter.rs: ProviderAdapter trait definition - providers/auth.rs: AuthInfo, AuthStrategy types - providers/claude.rs: Claude adapter with OpenRouter detection - providers/codex.rs: Codex (OpenAI) adapter - providers/gemini.rs: Gemini (Google) adapter - providers/models/: Anthropic and OpenAI API data models - providers/transform.rs: Bidirectional format transformation
114 lines
3.0 KiB
Rust
114 lines
3.0 KiB
Rust
//! OpenAI API 数据模型
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//!
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//! 用于 OpenAI Chat Completions API 的请求/响应格式转换
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use serde::{Deserialize, Serialize};
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use serde_json::Value;
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/// OpenAI 请求
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct OpenAIRequest {
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pub model: String,
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pub messages: Vec<OpenAIMessage>,
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#[serde(skip_serializing_if = "Option::is_none")]
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pub max_tokens: Option<u32>,
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#[serde(skip_serializing_if = "Option::is_none")]
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pub temperature: Option<f32>,
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#[serde(skip_serializing_if = "Option::is_none")]
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pub stream: Option<bool>,
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#[serde(skip_serializing_if = "Option::is_none")]
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pub tools: Option<Vec<OpenAITool>>,
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#[serde(skip_serializing_if = "Option::is_none")]
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pub tool_choice: Option<Value>,
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}
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/// OpenAI 消息
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct OpenAIMessage {
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pub role: String,
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#[serde(skip_serializing_if = "Option::is_none")]
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pub content: Option<Value>, // String 或 Vec<ContentPart>
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#[serde(skip_serializing_if = "Option::is_none")]
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pub tool_calls: Option<Vec<OpenAIToolCall>>,
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#[serde(skip_serializing_if = "Option::is_none")]
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pub tool_call_id: Option<String>,
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}
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/// OpenAI 内容部分
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#[derive(Debug, Clone, Serialize, Deserialize)]
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#[serde(tag = "type")]
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pub enum OpenAIContentPart {
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#[serde(rename = "text")]
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Text { text: String },
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#[serde(rename = "image_url")]
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ImageUrl { image_url: ImageUrl },
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}
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/// 图片 URL
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct ImageUrl {
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pub url: String,
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}
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/// OpenAI 工具调用
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct OpenAIToolCall {
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pub id: String,
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#[serde(rename = "type")]
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pub call_type: String,
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pub function: OpenAIFunction,
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}
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/// OpenAI 函数
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct OpenAIFunction {
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pub name: String,
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pub arguments: String, // JSON 字符串
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}
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/// OpenAI 工具定义
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct OpenAITool {
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#[serde(rename = "type")]
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pub tool_type: String,
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pub function: OpenAIFunctionDef,
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}
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/// OpenAI 函数定义
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct OpenAIFunctionDef {
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pub name: String,
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#[serde(skip_serializing_if = "Option::is_none")]
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pub description: Option<String>,
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pub parameters: Value,
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}
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/// OpenAI 响应
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct OpenAIResponse {
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pub id: String,
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pub object: String,
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pub created: u64,
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pub model: String,
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pub choices: Vec<OpenAIChoice>,
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#[serde(skip_serializing_if = "Option::is_none")]
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pub usage: Option<OpenAIUsage>,
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}
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/// OpenAI 选择
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct OpenAIChoice {
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pub index: u32,
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pub message: OpenAIMessage,
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#[serde(skip_serializing_if = "Option::is_none")]
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pub finish_reason: Option<String>,
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}
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/// OpenAI 使用量
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#[derive(Debug, Clone, Serialize, Deserialize)]
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pub struct OpenAIUsage {
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pub prompt_tokens: u32,
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pub completion_tokens: u32,
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pub total_tokens: u32,
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}
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