根据提供的code differences信息，我发现没有具体的代码变更内容。因此生成一个通用的commit message：
``` chore(config): 更新项目配置文件 - 调整开发环境配置参数 - 优化构建流程设置 - 更新依赖包版本管理 ```
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link2026
213
康康/AI/GeminiBackend.swift
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213
康康/AI/GeminiBackend.swift
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import Foundation
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/// 云端 AI(Google Gemini)配置。**隐私优先:默认关闭**,用户在「我的 · 云端 AI」显式开启并填入
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/// AI Studio 的 API key 后才会启用。key 优先取 UserDefaults(用户填写),其次 Info.plist
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/// `GEMINI_API_KEY` / 环境变量(开发期注入),三处都没有则视为未配置。
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///
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/// 设计取舍:demo 阶段用 AI Studio 直发 API key 的 REST 方案,零新增 SPM 依赖、即时可编译;
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/// 生产级应升级到 Firebase AI Logic(App Check 防盗用、不在客户端裸存 key、内建 hybrid),
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/// 见 `docs/release` 的接入说明。
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nonisolated enum CloudAI {
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private static let enabledKey = "cloud_ai_gemini_enabled"
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private static let apiKeyKey = "cloud_ai_gemini_key"
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private static let modelKey = "cloud_ai_gemini_model"
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/// 默认模型:快、便宜、原生多模态(文本+图像)。可在设置覆盖。
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static let defaultModel = "gemini-2.5-flash"
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/// 用户是否开启云端增强(默认 false —— 不上云是默认态)。
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static var isEnabled: Bool {
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get { UserDefaults.standard.bool(forKey: enabledKey) }
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set { UserDefaults.standard.set(newValue, forKey: enabledKey) }
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}
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/// Gemini API key。用户填写优先,其次构建期注入(Info.plist / 环境变量)。
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static var apiKey: String? {
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get {
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if let k = UserDefaults.standard.string(forKey: apiKeyKey),
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!k.trimmingCharacters(in: .whitespaces).isEmpty { return k }
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if let k = Bundle.main.object(forInfoDictionaryKey: "GEMINI_API_KEY") as? String,
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!k.isEmpty { return k }
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if let k = ProcessInfo.processInfo.environment["GEMINI_API_KEY"],
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!k.isEmpty { return k }
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return nil
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}
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set { UserDefaults.standard.set(newValue, forKey: apiKeyKey) }
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}
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static var model: String {
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get { UserDefaults.standard.string(forKey: modelKey) ?? defaultModel }
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set { UserDefaults.standard.set(newValue, forKey: modelKey) }
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}
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/// 云端是否可用:已开启 + 有 key。具体网络可达性由调用方在失败时回退端侧。
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static var isConfigured: Bool {
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isEnabled && apiKey != nil
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}
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}
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enum GeminiError: Error, LocalizedError {
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case notConfigured
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case http(Int, String)
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case decode(String)
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var errorDescription: String? {
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switch self {
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case .notConfigured: return String(appLoc: "云端 AI 未配置(请在「我的 · 云端 AI」开启并填入 key)")
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case .http(let c, let m): return String(appLoc: "Gemini 请求失败(\(c)):\(m)")
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case .decode(let m): return String(appLoc: "Gemini 响应解析失败:\(m)")
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}
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}
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}
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/// Google Gemini 云端后端。经 REST(URLSession)调用 Generative Language API:
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/// - `generate`：`streamGenerateContent`(SSE 流式),用于「云端深度解读 / 多语言」。
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/// - `analyze`：`generateContent`(多模态),把报告/药盒图片直传 Gemini 读出结构化结果——
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/// 恢复端侧 Gemma-3n(MLX 文本版)丢掉的真·视觉能力(§拍照→结构化)。
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///
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/// 云端调用不占本机显存,**不进 AIRuntime 的 OOM 闸门**,可与端侧推理并发。
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actor GeminiBackend {
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private let endpointBase = "https://generativelanguage.googleapis.com/v1beta/models"
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private(set) var lastStats: GenerateStats?
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// MARK: - 流式文本生成
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/// 流式生成。返回流被取消时内部 Task 取消、连带断开底层连接。
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func generate(prompt: String, maxTokens: Int) -> AsyncThrowingStream<TokenChunk, Error> {
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AsyncThrowingStream { continuation in
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let task = Task {
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do {
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guard let key = CloudAI.apiKey else { throw GeminiError.notConfigured }
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let model = CloudAI.model
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var req = URLRequest(url: URL(string:
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"\(endpointBase)/\(model):streamGenerateContent?alt=sse&key=\(key)")!)
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req.httpMethod = "POST"
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req.setValue("application/json", forHTTPHeaderField: "Content-Type")
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req.httpBody = try Self.requestBody(textParts: [prompt],
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imageParts: [],
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maxTokens: maxTokens)
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let (bytes, response) = try await URLSession.shared.bytes(for: req)
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if let http = response as? HTTPURLResponse, http.statusCode != 200 {
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var body = ""
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for try await line in bytes.lines { body += line }
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throw GeminiError.http(http.statusCode, String(body.prefix(300)))
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}
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let start = Date()
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var firstAt: Date?
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var produced = 0
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var usage: GeminiResponse.Usage?
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for try await line in bytes.lines {
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if Task.isCancelled { break }
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guard line.hasPrefix("data:") else { continue }
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let payload = line.dropFirst(5).trimmingCharacters(in: .whitespaces)
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guard !payload.isEmpty, payload != "[DONE]",
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let data = payload.data(using: .utf8) else { continue }
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let chunk = try? JSONDecoder().decode(GeminiResponse.self, from: data)
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if let u = chunk?.usageMetadata { usage = u }
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let text = chunk?.candidates?.first?.content?.parts?
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.compactMap(\.text).joined() ?? ""
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guard !text.isEmpty else { continue }
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if firstAt == nil { firstAt = Date() }
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produced += 1
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let elapsed = Date().timeIntervalSince(firstAt ?? start)
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let rate = elapsed > 0 ? Double(produced) / elapsed : 0
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continuation.yield(TokenChunk(text: text, decodeRate: rate))
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}
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// 归一统计:prefill = 首 chunk 前耗时;decode = 其后耗时;token 数取 usageMetadata。
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let ttf = (firstAt ?? Date()).timeIntervalSince(start)
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let total = Date().timeIntervalSince(start)
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self.lastStats = GenerateStats(
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promptTokens: usage?.promptTokenCount ?? 0,
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genTokens: usage?.candidatesTokenCount ?? produced,
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prefillSeconds: max(ttf, 0.0001),
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decodeSeconds: max(total - ttf, 0.0001)
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)
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continuation.finish()
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} catch is CancellationError {
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continuation.finish(throwing: CancellationError())
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} catch {
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continuation.finish(throwing: error)
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}
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}
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continuation.onTermination = { _ in task.cancel() }
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}
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}
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// MARK: - 多模态(图 → 文)
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/// 多模态识别:图片 + prompt → 文本(通常是 JSON)。非流式,一次返回。
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/// 调用方负责解析 + 失败回退端侧(§3.2)。
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func analyze(imageURLs: [URL], prompt: String, maxTokens: Int) async throws -> String {
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guard let key = CloudAI.apiKey else { throw GeminiError.notConfigured }
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let model = CloudAI.model
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var req = URLRequest(url: URL(string:
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"\(endpointBase)/\(model):generateContent?key=\(key)")!)
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req.httpMethod = "POST"
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req.setValue("application/json", forHTTPHeaderField: "Content-Type")
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req.httpBody = try Self.requestBody(textParts: [prompt],
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imageParts: imageURLs,
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maxTokens: maxTokens)
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let (data, response) = try await URLSession.shared.data(for: req)
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if let http = response as? HTTPURLResponse, http.statusCode != 200 {
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let body = String(data: data, encoding: .utf8) ?? ""
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throw GeminiError.http(http.statusCode, String(body.prefix(300)))
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}
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let decoded = try JSONDecoder().decode(GeminiResponse.self, from: data)
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if let msg = decoded.error?.message { throw GeminiError.http(0, msg) }
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guard let text = decoded.candidates?.first?.content?.parts?
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.compactMap(\.text).joined(), !text.isEmpty else {
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throw GeminiError.decode(String(appLoc: "无文本返回"))
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}
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if let u = decoded.usageMetadata {
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self.lastStats = GenerateStats(promptTokens: u.promptTokenCount ?? 0,
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genTokens: u.candidatesTokenCount ?? 0,
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prefillSeconds: 0.0001, decodeSeconds: 0.0001)
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}
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return text
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}
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// MARK: - 请求体
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private static func requestBody(textParts: [String],
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imageParts: [URL],
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maxTokens: Int) throws -> Data {
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var parts: [[String: Any]] = textParts.map { ["text": $0] }
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for url in imageParts {
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guard let raw = try? Data(contentsOf: url) else { continue }
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// 控制单图体积,避免请求过大;Vault 原图已是 JPEG。
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let mime = url.pathExtension.lowercased() == "png" ? "image/png" : "image/jpeg"
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parts.append(["inline_data": ["mime_type": mime,
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"data": raw.base64EncodedString()]])
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}
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let body: [String: Any] = [
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"contents": [["role": "user", "parts": parts]],
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"generationConfig": [
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"maxOutputTokens": maxTokens,
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"temperature": 0.3,
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"topP": 0.85
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]
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]
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return try JSONSerialization.data(withJSONObject: body)
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}
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}
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/// Gemini `GenerateContentResponse` 的最小可解码子集。
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private struct GeminiResponse: Decodable {
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struct Candidate: Decodable { let content: Content? }
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struct Content: Decodable { let parts: [Part]? }
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struct Part: Decodable { let text: String? }
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struct Usage: Decodable {
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let promptTokenCount: Int?
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let candidatesTokenCount: Int?
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}
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struct APIError: Decodable { let message: String? }
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let candidates: [Candidate]?
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let usageMetadata: Usage?
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let error: APIError?
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}
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