feat(AI/MNN): 集成 MNN.xcframework + ObjC++ 桥(LLM+SME2,Phase 1-2)
挑战赛考核点要求 Qwen + MNN + SME2 + CPU 端侧推理,MLX(GPU)不满足。
本提交打通原生 MNN 集成的工程层:
- scripts/build-mnn-xcframework.sh:从 alibaba/MNN 源码构建 device+sim arm64
双切片 xcframework,MNN_BUILD_LLM=ON 导出 llm/llm.hpp,MNN_SME2=ON
(KleidiAI 运行时自动路由:A19/iPhone17 走 SME2,A17 回退 NEON)
- MNNLLMBridge.{h,mm}:ObjC++ 封装 MNN Llm 的加载/流式生成,streambuf 按
UTF-8 边界聚合回调,getContext() 取 prefill/decode 算 tok/s;模拟器编为桩
(走 MLX 兜底),SME2 经 sysctl hw.optional.arm.FEAT_SME2 探测
- pbxproj:链接 MNN.xcframework + bridging header
- 二进制 gitignore,由脚本本地生成防历史膨胀
模拟器 BUILD SUCCEEDED(0 error),xcframework 处理 + 桥编译 + 链接通过。
下一步 Phase 3:MNNBackend + AIRuntime 双后端路由。
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
link2026
55
康康/AI/MNN/MNNLLMBridge.h
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55
康康/AI/MNN/MNNLLMBridge.h
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//
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// MNNLLMBridge.h
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// 康康
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//
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// Objective-C 接口,封装 MNN-LLM(Qwen)的加载与流式推理。
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// 真实实现在 .mm 中以 ObjC++ 调用 <MNN/llm/llm.hpp>;模拟器下编为可用性返回 NO 的桩
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// (MNN.framework 仅 device arm64 切片有真实 CPU/SME2 内核,模拟器走 MLX 兜底)。
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//
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#import <Foundation/Foundation.h>
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NS_ASSUME_NONNULL_BEGIN
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/// 末次生成的性能统计(取自 MNN LlmContext)。
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@interface MNNGenerateStats : NSObject
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@property (nonatomic, readonly) int promptTokens;
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@property (nonatomic, readonly) int genTokens;
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@property (nonatomic, readonly) double prefillMs;
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@property (nonatomic, readonly) double decodeMs;
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/// 解码速率 tok/s = genTokens / (decodeMs/1000)。demo 卖点 #6 / Live Activity 用。
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@property (nonatomic, readonly) double decodeTokensPerSecond;
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@end
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@interface MNNLLMBridge : NSObject
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/// 本构建是否含真实 MNN 运行时(device=YES,simulator 桩=NO)。
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+ (BOOL)isAvailable;
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/// CPU 是否支持 SME2(运行时探测);A19/iPhone17 YES,A17/iPhone15Pro NO。仅用于 UI 展示加速状态。
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+ (BOOL)cpuSupportsSME2;
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/// 用 MNN llm 的 config.json 路径加载模型(目录含 llm.mnn / 权重 / tokenizer)。失败返回 nil。
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- (nullable instancetype)initWithConfigPath:(NSString *)configPath;
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@property (nonatomic, readonly) BOOL isLoaded;
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/// 纯文本流式生成。onToken 每解码出一段文本回调一次(在调用线程,同步阻塞直到生成结束)。
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/// 返回末次统计。
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- (MNNGenerateStats *)generateText:(NSString *)prompt
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maxTokens:(int)maxTokens
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onToken:(void (^)(NSString *piece))onToken;
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/// 图→文(VL,需 MNN_BUILD_LLM_OMNI 构建)。imagePaths 为本地文件路径。
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/// 当前文本构建未含 OMNI 时返回 nil 并置 error。
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- (nullable MNNGenerateStats *)analyzeImages:(NSArray<NSString *> *)imagePaths
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prompt:(NSString *)prompt
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maxTokens:(int)maxTokens
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onToken:(void (^)(NSString *piece))onToken
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error:(NSError *_Nullable *_Nullable)error;
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/// 请求取消当前生成(best-effort:置标志,后续 token 不再回调)。
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- (void)cancel;
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@end
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NS_ASSUME_NONNULL_END
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178
康康/AI/MNN/MNNLLMBridge.mm
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康康/AI/MNN/MNNLLMBridge.mm
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//
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// MNNLLMBridge.mm
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// 康康
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//
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// ObjC++ 实现。device 真机用 <MNN/llm/llm.hpp>;模拟器编为桩(返回不可用,上层回退 MLX)。
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//
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#import "MNNLLMBridge.h"
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#include <sys/sysctl.h>
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// MARK: - 性能统计(私有 readwrite 重声明)
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@interface MNNGenerateStats ()
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@property (nonatomic, readwrite) int promptTokens;
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@property (nonatomic, readwrite) int genTokens;
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@property (nonatomic, readwrite) double prefillMs;
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@property (nonatomic, readwrite) double decodeMs;
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@end
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@implementation MNNGenerateStats
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- (double)decodeTokensPerSecond {
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return self.decodeMs > 0 ? (self.genTokens / (self.decodeMs / 1000.0)) : 0;
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}
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@end
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// MARK: - SME2 / 可用性探测(device + simulator 都可编)
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static BOOL kk_sysctlFlag(const char *name) {
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int64_t v = 0; size_t sz = sizeof(v);
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if (sysctlbyname(name, &v, &sz, NULL, 0) != 0) return NO;
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return v != 0;
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}
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#if TARGET_OS_SIMULATOR
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// ============ 模拟器桩:无真实 MNN ============
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@implementation MNNLLMBridge
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+ (BOOL)isAvailable { return NO; }
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+ (BOOL)cpuSupportsSME2 { return NO; }
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- (nullable instancetype)initWithConfigPath:(NSString *)configPath { return nil; }
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- (BOOL)isLoaded { return NO; }
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- (MNNGenerateStats *)generateText:(NSString *)prompt maxTokens:(int)maxTokens
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onToken:(void (^)(NSString *))onToken { return [MNNGenerateStats new]; }
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- (nullable MNNGenerateStats *)analyzeImages:(NSArray<NSString *> *)imagePaths prompt:(NSString *)prompt
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maxTokens:(int)maxTokens onToken:(void (^)(NSString *))onToken
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error:(NSError **)error {
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if (error) *error = [NSError errorWithDomain:@"MNN" code:-1
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userInfo:@{NSLocalizedDescriptionKey: @"MNN 在模拟器不可用"}];
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return nil;
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}
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- (void)cancel {}
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@end
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#else
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// ============ 真机:真实 MNN-LLM ============
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#include <MNN/llm/llm.hpp>
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#include <string>
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#include <ostream>
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#include <streambuf>
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#include <atomic>
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using MNN::Transformer::Llm;
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namespace {
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/// 把 MNN 写入 ostream 的解码文本转成 NSString 回调;按 UTF-8 完整边界聚合,避免截断多字节。
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class TokenStreamBuf : public std::streambuf {
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public:
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TokenStreamBuf(void (^onToken)(NSString *), std::atomic<bool> *cancel)
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: _onToken(onToken), _cancel(cancel) {}
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void flush() {
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if (_pending.empty()) return;
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emitPending(); // 末尾尽力 emit(即便非完整 UTF-8 也交出去)
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_pending.clear();
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}
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protected:
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std::streamsize xsputn(const char *s, std::streamsize n) override {
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append(s, (size_t)n);
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return n;
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}
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int overflow(int c) override {
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if (c != EOF) { char ch = (char)c; append(&ch, 1); }
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return c;
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}
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private:
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void append(const char *s, size_t n) {
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if (_cancel && _cancel->load()) return; // 已取消,吞掉不回调
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_pending.append(s, n);
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// 仅当整个 pending 是合法 UTF-8 才 emit(token 通常是完整字/词,边界自然对齐)
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NSString *str = [[NSString alloc] initWithBytes:_pending.data()
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length:_pending.size()
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encoding:NSUTF8StringEncoding];
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if (str) { if (_onToken) _onToken(str); _pending.clear(); }
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}
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void emitPending() {
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NSString *str = [[NSString alloc] initWithBytes:_pending.data()
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length:_pending.size()
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encoding:NSUTF8StringEncoding];
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if (str && _onToken) _onToken(str);
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}
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void (^_onToken)(NSString *);
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std::atomic<bool> *_cancel;
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std::string _pending;
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};
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} // namespace
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@implementation MNNLLMBridge {
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Llm *_llm;
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std::atomic<bool> _cancel;
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BOOL _loaded;
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}
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+ (BOOL)isAvailable { return YES; }
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+ (BOOL)cpuSupportsSME2 {
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// Apple 通过 sysctl 暴露 ARM 特性位:FEAT_SME2(A19/iPhone17+)。
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return kk_sysctlFlag("hw.optional.arm.FEAT_SME2");
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}
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- (nullable instancetype)initWithConfigPath:(NSString *)configPath {
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self = [super init];
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if (!self) return nil;
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_cancel = false;
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_llm = Llm::createLLM(std::string(configPath.UTF8String));
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if (_llm == nullptr) return nil;
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_loaded = _llm->load();
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if (!_loaded) { Llm::destroy(_llm); _llm = nullptr; return nil; }
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return self;
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}
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- (void)dealloc {
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if (_llm) { Llm::destroy(_llm); _llm = nullptr; }
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}
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- (BOOL)isLoaded { return _loaded; }
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- (void)cancel { _cancel = true; }
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- (MNNGenerateStats *)generateText:(NSString *)prompt
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maxTokens:(int)maxTokens
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onToken:(void (^)(NSString *))onToken {
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_cancel = false;
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TokenStreamBuf buf(onToken, &_cancel);
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std::ostream os(&buf);
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if (_llm) {
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_llm->response(std::string(prompt.UTF8String), &os, nullptr, maxTokens);
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}
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buf.flush();
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return [self statsFromContext];
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}
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- (nullable MNNGenerateStats *)analyzeImages:(NSArray<NSString *> *)imagePaths
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prompt:(NSString *)prompt
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maxTokens:(int)maxTokens
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onToken:(void (^)(NSString *))onToken
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error:(NSError **)error {
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// VL 需 MNN_BUILD_LLM_OMNI 构建(OpenCV 解码图像)。当前文本构建不含,显式报错。
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if (error) *error = [NSError errorWithDomain:@"MNN" code:-2
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userInfo:@{NSLocalizedDescriptionKey: @"当前 MNN 构建未含 VL(OMNI),请用 OMNI 框架"}];
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return nil;
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}
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- (MNNGenerateStats *)statsFromContext {
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MNNGenerateStats *s = [MNNGenerateStats new];
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if (_llm) {
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const MNN::Transformer::LlmContext *ctx = _llm->getContext();
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if (ctx) {
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s.promptTokens = ctx->prompt_len;
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s.genTokens = ctx->gen_seq_len;
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s.prefillMs = ctx->prefill_us / 1000.0;
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s.decodeMs = ctx->decode_us / 1000.0;
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}
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}
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return s;
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}
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@end
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#endif
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6
康康/康康-Bridging-Header.h
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6
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//
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// 康康-Bridging-Header.h
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// 把 Objective-C 接口暴露给 Swift。
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//
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#import "AI/MNN/MNNLLMBridge.h"
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