ggml : restore abort() in GGML_ASSERT

* Split CPP generation from build-info query

* Remove blank lines

* Add BUILD_SHARED_LIBS option

.github/workflows/build.yml

@@ -498,6 +498,17 @@ jobs:
           path: |
             cudart-llama-bin-win-cu${{ matrix.cuda }}-x64.zip
 
+  ios-xcode-build:
+    runs-on: macos-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v3
+
+      - name: Build Xcode project
+        run: xcodebuild -project examples/llama.swiftui/llama.swiftui.xcodeproj -scheme llama.swiftui -sdk iphoneos CODE_SIGNING_REQUIRED=NO CODE_SIGN_IDENTITY= -destination 'generic/platform=iOS' build
+
+
 #  freeBSD-latest:
 #    runs-on: macos-12
 #    steps:

.gitignore

@@ -47,6 +47,7 @@ models-mnt
 /libllama.so
 /llama-bench
 /llava-cli
+/lookahead
 /main
 /metal
 /perplexity

CMakeLists.txt

@@ -43,6 +43,7 @@ else()
 endif()
 
 # general
+option(BUILD_SHARED_LIBS                "build shared libraries"                                OFF)
 option(LLAMA_STATIC                     "llama: static link libraries"                          OFF)
 option(LLAMA_NATIVE                     "llama: enable -march=native flag"                      ON)
 option(LLAMA_LTO                        "llama: enable link time optimization"                  OFF)
@@ -100,6 +101,9 @@ option(LLAMA_BUILD_TESTS                "llama: build tests"    ${LLAMA_STANDALO
 option(LLAMA_BUILD_EXAMPLES             "llama: build examples" ${LLAMA_STANDALONE})
 option(LLAMA_BUILD_SERVER               "llama: build server example"                           ON)
 
+# Required for relocatable CMake package
+include(${CMAKE_CURRENT_SOURCE_DIR}/scripts/build-info.cmake)
+
 #
 # Compile flags
 #

Makefile

@@ -2,7 +2,7 @@
 BUILD_TARGETS = \
 	main quantize quantize-stats perplexity embedding vdot q8dot train-text-from-scratch convert-llama2c-to-ggml \
 	simple batched batched-bench save-load-state server gguf llama-bench libllava.a llava-cli baby-llama beam-search  \
-	speculative infill tokenize benchmark-matmult parallel finetune export-lora tests/test-c.o
+	speculative infill tokenize benchmark-matmult parallel finetune export-lora lookahead tests/test-c.o
 
 # Binaries only useful for tests
 TEST_TARGETS = \
@@ -657,6 +657,9 @@ speculative: examples/speculative/speculative.cpp ggml.o llama.o $(COMMON_DEPS)
 parallel: examples/parallel/parallel.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
 	$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
 
+lookahead: examples/lookahead/lookahead.cpp ggml.o llama.o $(COMMON_DEPS) $(OBJS)
+	$(CXX) $(CXXFLAGS) $(filter-out %.h,$^) -o $@ $(LDFLAGS)
+
 ifdef LLAMA_METAL
 metal: examples/metal/metal.cpp ggml.o $(OBJS)
 	$(CXX) $(CXXFLAGS) $^ -o $@ $(LDFLAGS)

README.md

@@ -10,6 +10,7 @@ Inference of [LLaMA](https://arxiv.org/abs/2302.13971) model in pure C/C++
 
 ### Hot topics
 
+- Using `llama.cpp` with AWS instances: https://github.com/ggerganov/llama.cpp/discussions/4225
 - Looking for contributions to improve and maintain the `server` example: https://github.com/ggerganov/llama.cpp/issues/4216
 - Collecting Apple Silicon performance stats: https://github.com/ggerganov/llama.cpp/discussions/4167
 
@@ -115,6 +116,7 @@ as the main playground for developing new features for the [ggml](https://github
 - [nat/openplayground](https://github.com/nat/openplayground)
 - [oobabooga/text-generation-webui](https://github.com/oobabooga/text-generation-webui)
 - [withcatai/catai](https://github.com/withcatai/catai)
+- [semperai/amica](https://github.com/semperai/amica)
 
 ---
 

common/CMakeLists.txt

@@ -26,7 +26,7 @@ add_custom_command(
     COMMENT "Generating build details from Git"
     COMMAND ${CMAKE_COMMAND} -DMSVC=${MSVC} -DCMAKE_C_COMPILER_VERSION=${CMAKE_C_COMPILER_VERSION}
             -DCMAKE_C_COMPILER_ID=${CMAKE_C_COMPILER_ID} -DCMAKE_VS_PLATFORM_NAME=${CMAKE_VS_PLATFORM_NAME}
-            -DCMAKE_C_COMPILER=${CMAKE_C_COMPILER} -P "${CMAKE_CURRENT_SOURCE_DIR}/../scripts/build-info.cmake"
+            -DCMAKE_C_COMPILER=${CMAKE_C_COMPILER} -P "${CMAKE_CURRENT_SOURCE_DIR}/../scripts/gen-build-info-cpp.cmake"
     WORKING_DIRECTORY "${CMAKE_CURRENT_SOURCE_DIR}/.."
     DEPENDS "${CMAKE_CURRENT_SOURCE_DIR}/build-info.cpp.in" ${GIT_INDEX}
     VERBATIM

convert-hf-to-gguf.py

@@ -59,7 +59,7 @@ class Model:
                 from safetensors import safe_open
                 ctx = cast(ContextManager[Any], safe_open(self.dir_model / part_name, framework="pt", device="cpu"))
             else:
-                ctx = contextlib.nullcontext(torch.load(self.dir_model / part_name, map_location="cpu"))
+                ctx = contextlib.nullcontext(torch.load(str(self.dir_model / part_name), map_location="cpu", mmap=True, weights_only=True))
 
             with ctx as model_part:
                 for name in model_part.keys():

examples/CMakeLists.txt

@@ -32,6 +32,7 @@ else()
     add_subdirectory(save-load-state)
     add_subdirectory(simple)
     add_subdirectory(speculative)
+    add_subdirectory(lookahead)
     add_subdirectory(train-text-from-scratch)
     if (LLAMA_METAL)
         add_subdirectory(metal)

examples/llama.swiftui/.gitignore

@@ -0,0 +1 @@
+xcuserdata

examples/llama.swiftui/README.md

@@ -0,0 +1,7 @@
+# llama.swiftui
+
+Local inference of llama.cpp on an iPhone.
+So far I only tested with starcoder 1B model, but it can most likely handle 7B models as well.
+
+https://github.com/bachittle/llama.cpp/assets/39804642/e290827a-4edb-4093-9642-2a5e399ec545
+

examples/llama.swiftui/llama.cpp.swift/LibLlama.swift

@@ -0,0 +1,176 @@
+import Foundation
+
+// import llama
+
+enum LlamaError: Error {
+    case couldNotInitializeContext
+}
+
+actor LlamaContext {
+    private var model: OpaquePointer
+    private var context: OpaquePointer
+    private var batch: llama_batch
+    private var tokens_list: [llama_token]
+
+    var n_len: Int32 = 512
+    var n_cur: Int32 = 0
+    var n_decode: Int32 = 0
+
+    init(model: OpaquePointer, context: OpaquePointer) {
+        self.model = model
+        self.context = context
+        self.tokens_list = []
+        self.batch = llama_batch_init(512, 0, 1)
+    }
+
+    deinit {
+        llama_free(context)
+        llama_free_model(model)
+        llama_backend_free()
+    }
+
+    static func createContext(path: String) throws -> LlamaContext {
+        llama_backend_init(false)
+        let model_params = llama_model_default_params()
+
+        let model = llama_load_model_from_file(path, model_params)
+        guard let model else {
+            print("Could not load model at \(path)")
+            throw LlamaError.couldNotInitializeContext
+        }
+        var ctx_params = llama_context_default_params()
+        ctx_params.seed = 1234
+        ctx_params.n_ctx = 2048
+        ctx_params.n_threads = 8
+        ctx_params.n_threads_batch = 8
+
+        let context = llama_new_context_with_model(model, ctx_params)
+        guard let context else {
+            print("Could not load context!")
+            throw LlamaError.couldNotInitializeContext
+        }
+
+        return LlamaContext(model: model, context: context)
+    }
+
+    func get_n_tokens() -> Int32 {
+        return batch.n_tokens;
+    }
+
+    func completion_init(text: String) {
+        print("attempting to complete \"\(text)\"")
+
+        tokens_list = tokenize(text: text, add_bos: true)
+
+        let n_ctx = llama_n_ctx(context)
+        let n_kv_req = tokens_list.count + (Int(n_len) - tokens_list.count)
+
+        print("\n n_len = \(n_len), n_ctx = \(n_ctx), n_kv_req = \(n_kv_req)")
+
+        if n_kv_req > n_ctx {
+            print("error: n_kv_req > n_ctx, the required KV cache size is not big enough")
+        }
+
+        for id in tokens_list {
+            print(token_to_piece(token: id))
+        }
+
+        // batch = llama_batch_init(512, 0) // done in init()
+        batch.n_tokens = Int32(tokens_list.count)
+
+        for i1 in 0..<batch.n_tokens {
+            let i = Int(i1)
+            batch.token[i] = tokens_list[i]
+            batch.pos[i] = i1
+            batch.n_seq_id[Int(i)] = 1
+            batch.seq_id[Int(i)]![0] = 0
+            batch.logits[i] = 0
+        }
+        batch.logits[Int(batch.n_tokens) - 1] = 1 // true
+
+        if llama_decode(context, batch) != 0 {
+            print("llama_decode() failed")
+        }
+
+        n_cur = batch.n_tokens
+    }
+
+    func completion_loop() -> String {
+        var new_token_id: llama_token = 0
+
+        let n_vocab = llama_n_vocab(model)
+        let logits = llama_get_logits_ith(context, batch.n_tokens - 1)
+
+        var candidates = Array<llama_token_data>()
+        candidates.reserveCapacity(Int(n_vocab))
+
+        for token_id in 0..<n_vocab {
+            candidates.append(llama_token_data(id: token_id, logit: logits![Int(token_id)], p: 0.0))
+        }
+        candidates.withUnsafeMutableBufferPointer() { buffer in
+            var candidates_p = llama_token_data_array(data: buffer.baseAddress, size: buffer.count, sorted: false)
+
+            new_token_id = llama_sample_token_greedy(context, &candidates_p)
+        }
+
+        if new_token_id == llama_token_eos(context) || n_cur == n_len {
+            print("\n")
+            return ""
+        }
+
+        let new_token_str = token_to_piece(token: new_token_id)
+        print(new_token_str)
+        // tokens_list.append(new_token_id)
+
+        batch.n_tokens = 0
+
+        batch.token[Int(batch.n_tokens)] = new_token_id
+        batch.pos[Int(batch.n_tokens)] = n_cur
+        batch.n_seq_id[Int(batch.n_tokens)] = 1
+        batch.seq_id[Int(batch.n_tokens)]![0] = 0
+        batch.logits[Int(batch.n_tokens)] = 1 // true
+        batch.n_tokens += 1
+
+        n_decode += 1
+
+        n_cur += 1
+
+        if llama_decode(context, batch) != 0 {
+            print("failed to evaluate llama!")
+        }
+
+        return new_token_str
+    }
+
+    func clear() {
+        tokens_list.removeAll()
+    }
+
+    private func tokenize(text: String, add_bos: Bool) -> [llama_token] {
+        let n_tokens = text.count + (add_bos ? 1 : 0)
+        let tokens = UnsafeMutablePointer<llama_token>.allocate(capacity: n_tokens)
+        let tokenCount = llama_tokenize(model, text, Int32(text.count), tokens, Int32(n_tokens), add_bos, false)
+
+        var swiftTokens: [llama_token] = []
+        for i in 0..<tokenCount {
+            swiftTokens.append(tokens[Int(i)])
+        }
+
+        tokens.deallocate()
+
+        return swiftTokens
+    }
+
+    private func token_to_piece(token: llama_token) -> String {
+        let result = UnsafeMutablePointer<Int8>.allocate(capacity: 8)
+        result.initialize(repeating: Int8(0), count: 8)
+
+        let _ = llama_token_to_piece(model, token, result, 8)
+
+        let resultStr = String(cString: result)
+
+        result.deallocate()
+
+        return resultStr
+    }
+}

examples/llama.swiftui/llama.cpp.swift/bridging-header.h

@@ -0,0 +1,5 @@
+//
+//  Use this file to import your target's public headers that you would like to expose to Swift.
+//
+
+#import "llama.h"

examples/llama.swiftui/llama.swiftui.xcodeproj/project.pbxproj

@@ -0,0 +1,481 @@
+// !$*UTF8*$!
+{
+    archiveVersion = 1;
+    classes = {
+    };
+    objectVersion = 56;
+    objects = {
+
+/* Begin PBXBuildFile section */
+        542376082B0D9BFB008E6A1C /* ggml-quants.c in Sources */ = {isa = PBXBuildFile; fileRef = 542376072B0D9BFB008E6A1C /* ggml-quants.c */; };
+        5423760B2B0D9C4B008E6A1C /* ggml-backend.c in Sources */ = {isa = PBXBuildFile; fileRef = 5423760A2B0D9C4B008E6A1C /* ggml-backend.c */; };
+        542378792ACE3F3500834A7B /* ggml-metal.metal in Resources */ = {isa = PBXBuildFile; fileRef = 549479C82AC9E10B00E0F78B /* ggml-metal.metal */; };
+        542EA09D2AC8723900A8AEE9 /* ggml.c in Sources */ = {isa = PBXBuildFile; fileRef = 542EA09B2AC8723900A8AEE9 /* ggml.c */; settings = {COMPILER_FLAGS = "-DGGML_USE_ACCELERATE -DGGML_USE_METAL -DGGML_USE_K_QUANTS -O3"; }; };
+        542EA0A02AC8725700A8AEE9 /* ggml-alloc.c in Sources */ = {isa = PBXBuildFile; fileRef = 542EA09F2AC8725700A8AEE9 /* ggml-alloc.c */; };
+        542EA0A32AC8729100A8AEE9 /* llama.cpp in Sources */ = {isa = PBXBuildFile; fileRef = 542EA0A12AC8729100A8AEE9 /* llama.cpp */; settings = {COMPILER_FLAGS = "-DGGML_USE_K_QUANTS -DGGML_USE_METAL -O3"; }; };
+        549479CB2AC9E16000E0F78B /* Metal.framework in Frameworks */ = {isa = PBXBuildFile; fileRef = 549479CA2AC9E16000E0F78B /* Metal.framework */; };
+        549479CD2AC9E42A00E0F78B /* ggml-metal.m in Sources */ = {isa = PBXBuildFile; fileRef = 549479C52AC9E0F200E0F78B /* ggml-metal.m */; settings = {COMPILER_FLAGS = "-fno-objc-arc -DGGML_SWIFT -DGGML_USE_METAL -O3"; }; };
+        8A1C83772AC328BD0096AF73 /* llama_swiftuiApp.swift in Sources */ = {isa = PBXBuildFile; fileRef = 8A1C83762AC328BD0096AF73 /* llama_swiftuiApp.swift */; };
+        8A1C83792AC328BD0096AF73 /* ContentView.swift in Sources */ = {isa = PBXBuildFile; fileRef = 8A1C83782AC328BD0096AF73 /* ContentView.swift */; };
+        8A1C837B2AC328BE0096AF73 /* Assets.xcassets in Resources */ = {isa = PBXBuildFile; fileRef = 8A1C837A2AC328BE0096AF73 /* Assets.xcassets */; };
+        8A1C837E2AC328BE0096AF73 /* Preview Assets.xcassets in Resources */ = {isa = PBXBuildFile; fileRef = 8A1C837D2AC328BE0096AF73 /* Preview Assets.xcassets */; };
+        8A39BE0A2AC7601100BFEB40 /* Accelerate.framework in Frameworks */ = {isa = PBXBuildFile; fileRef = 8A39BE092AC7601000BFEB40 /* Accelerate.framework */; };
+        8A3F84242AC4C891005E2EE8 /* models in Resources */ = {isa = PBXBuildFile; fileRef = 8A3F84232AC4C891005E2EE8 /* models */; };
+        8A907F332AC7138A006146EA /* LibLlama.swift in Sources */ = {isa = PBXBuildFile; fileRef = 8A907F322AC7134E006146EA /* LibLlama.swift */; };
+        8A9F7C4D2AC332EE008AE1EA /* LlamaState.swift in Sources */ = {isa = PBXBuildFile; fileRef = 8A9F7C4C2AC332EE008AE1EA /* LlamaState.swift */; };
+/* End PBXBuildFile section */
+
+/* Begin PBXFileReference section */
+        542376062B0D9BEA008E6A1C /* ggml-quants.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = "ggml-quants.h"; path = "../../ggml-quants.h"; sourceTree = "<group>"; };
+        542376072B0D9BFB008E6A1C /* ggml-quants.c */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.c; name = "ggml-quants.c"; path = "../../ggml-quants.c"; sourceTree = "<group>"; };
+        542376092B0D9C40008E6A1C /* ggml-backend.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; name = "ggml-backend.h"; path = "../../ggml-backend.h"; sourceTree = "<group>"; };
+        5423760A2B0D9C4B008E6A1C /* ggml-backend.c */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.c; name = "ggml-backend.c"; path = "../../ggml-backend.c"; sourceTree = "<group>"; };
+        542EA09B2AC8723900A8AEE9 /* ggml.c */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.c; name = ggml.c; path = ../../ggml.c; sourceTree = "<group>"; };
+        542EA09C2AC8723900A8AEE9 /* ggml.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = ggml.h; path = ../../ggml.h; sourceTree = "<group>"; };
+        542EA09E2AC8725700A8AEE9 /* ggml-alloc.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = "ggml-alloc.h"; path = "../../ggml-alloc.h"; sourceTree = "<group>"; };
+        542EA09F2AC8725700A8AEE9 /* ggml-alloc.c */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.c; name = "ggml-alloc.c"; path = "../../ggml-alloc.c"; sourceTree = "<group>"; };
+        542EA0A12AC8729100A8AEE9 /* llama.cpp */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.cpp; name = llama.cpp; path = ../../llama.cpp; sourceTree = "<group>"; };
+        542EA0A22AC8729100A8AEE9 /* llama.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = llama.h; path = ../../llama.h; sourceTree = "<group>"; };
+        549479C52AC9E0F200E0F78B /* ggml-metal.m */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.objc; name = "ggml-metal.m"; path = "../../ggml-metal.m"; sourceTree = "<group>"; };
+        549479C62AC9E0F200E0F78B /* ggml-metal.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = "ggml-metal.h"; path = "../../ggml-metal.h"; sourceTree = "<group>"; };
+        549479C82AC9E10B00E0F78B /* ggml-metal.metal */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.metal; name = "ggml-metal.metal"; path = "../../ggml-metal.metal"; sourceTree = "<group>"; };
+        549479CA2AC9E16000E0F78B /* Metal.framework */ = {isa = PBXFileReference; lastKnownFileType = wrapper.framework; name = Metal.framework; path = System/Library/Frameworks/Metal.framework; sourceTree = SDKROOT; };
+        8A08D20A2AC73B1500FE6CD4 /* bridging-header.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; path = "bridging-header.h"; sourceTree = "<group>"; };
+        8A1C83732AC328BD0096AF73 /* llama.swiftui.app */ = {isa = PBXFileReference; explicitFileType = wrapper.application; includeInIndex = 0; path = llama.swiftui.app; sourceTree = BUILT_PRODUCTS_DIR; };
+        8A1C83762AC328BD0096AF73 /* llama_swiftuiApp.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = llama_swiftuiApp.swift; sourceTree = "<group>"; };
+        8A1C83782AC328BD0096AF73 /* ContentView.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = ContentView.swift; sourceTree = "<group>"; };
+        8A1C837A2AC328BE0096AF73 /* Assets.xcassets */ = {isa = PBXFileReference; lastKnownFileType = folder.assetcatalog; path = Assets.xcassets; sourceTree = "<group>"; };
+        8A1C837D2AC328BE0096AF73 /* Preview Assets.xcassets */ = {isa = PBXFileReference; lastKnownFileType = folder.assetcatalog; path = "Preview Assets.xcassets"; sourceTree = "<group>"; };
+        8A39BE092AC7601000BFEB40 /* Accelerate.framework */ = {isa = PBXFileReference; lastKnownFileType = wrapper.framework; name = Accelerate.framework; path = System/Library/Frameworks/Accelerate.framework; sourceTree = SDKROOT; };
+        8A3F841F2AC4C824005E2EE8 /* llama-2-7b-chat.Q2_K.gguf */ = {isa = PBXFileReference; lastKnownFileType = file; path = "llama-2-7b-chat.Q2_K.gguf"; sourceTree = "<group>"; };
+        8A3F84232AC4C891005E2EE8 /* models */ = {isa = PBXFileReference; lastKnownFileType = folder; name = models; path = llama.swiftui/Resources/models; sourceTree = "<group>"; };
+        8A907F322AC7134E006146EA /* LibLlama.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = LibLlama.swift; sourceTree = "<group>"; };
+        8A9F7C4C2AC332EE008AE1EA /* LlamaState.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = LlamaState.swift; sourceTree = "<group>"; };
+/* End PBXFileReference section */
+
+/* Begin PBXFrameworksBuildPhase section */
+        8A1C83702AC328BD0096AF73 /* Frameworks */ = {
+            isa = PBXFrameworksBuildPhase;
+            buildActionMask = 2147483647;
+            files = (
+                549479CB2AC9E16000E0F78B /* Metal.framework in Frameworks */,
+                8A39BE0A2AC7601100BFEB40 /* Accelerate.framework in Frameworks */,
+            );
+            runOnlyForDeploymentPostprocessing = 0;
+        };
+/* End PBXFrameworksBuildPhase section */
+
+/* Begin PBXGroup section */
+        8A08D1F62AC7383900FE6CD4 /* llama.cpp */ = {
+            isa = PBXGroup;
+            children = (
+                5423760A2B0D9C4B008E6A1C /* ggml-backend.c */,
+                542376092B0D9C40008E6A1C /* ggml-backend.h */,
+                542376062B0D9BEA008E6A1C /* ggml-quants.h */,
+                542376072B0D9BFB008E6A1C /* ggml-quants.c */,
+                549479C82AC9E10B00E0F78B /* ggml-metal.metal */,
+                549479C62AC9E0F200E0F78B /* ggml-metal.h */,
+                549479C52AC9E0F200E0F78B /* ggml-metal.m */,
+                542EA09B2AC8723900A8AEE9 /* ggml.c */,
+                542EA09C2AC8723900A8AEE9 /* ggml.h */,
+                542EA09F2AC8725700A8AEE9 /* ggml-alloc.c */,
+                542EA09E2AC8725700A8AEE9 /* ggml-alloc.h */,
+                542EA0A12AC8729100A8AEE9 /* llama.cpp */,
+                542EA0A22AC8729100A8AEE9 /* llama.h */,
+            );
+            name = llama.cpp;
+            sourceTree = "<group>";
+        };
+        8A1C836A2AC328BD0096AF73 = {
+            isa = PBXGroup;
+            children = (
+                8A08D1F62AC7383900FE6CD4 /* llama.cpp */,
+                8A907F312AC7134E006146EA /* llama.cpp.swift */,
+                8A3F84232AC4C891005E2EE8 /* models */,
+                8A1C83752AC328BD0096AF73 /* llama.swiftui */,
+                8A1C83742AC328BD0096AF73 /* Products */,
+                8A39BE082AC7601000BFEB40 /* Frameworks */,
+            );
+            sourceTree = "<group>";
+        };
+        8A1C83742AC328BD0096AF73 /* Products */ = {
+            isa = PBXGroup;
+            children = (
+                8A1C83732AC328BD0096AF73 /* llama.swiftui.app */,
+            );
+            name = Products;
+            sourceTree = "<group>";
+        };
+        8A1C83752AC328BD0096AF73 /* llama.swiftui */ = {
+            isa = PBXGroup;
+            children = (
+                8A3F84102AC4BD85005E2EE8 /* Resources */,
+                8A9F7C4B2AC332DC008AE1EA /* Models */,
+                8A9F7C4A2AC332BF008AE1EA /* UI */,
+                8A1C83762AC328BD0096AF73 /* llama_swiftuiApp.swift */,
+                8A1C837A2AC328BE0096AF73 /* Assets.xcassets */,
+                8A1C837C2AC328BE0096AF73 /* Preview Content */,
+            );
+            path = llama.swiftui;
+            sourceTree = "<group>";
+        };
+        8A1C837C2AC328BE0096AF73 /* Preview Content */ = {
+            isa = PBXGroup;
+            children = (
+                8A1C837D2AC328BE0096AF73 /* Preview Assets.xcassets */,
+            );
+            path = "Preview Content";
+            sourceTree = "<group>";
+        };
+        8A39BE082AC7601000BFEB40 /* Frameworks */ = {
+            isa = PBXGroup;
+            children = (
+                549479CA2AC9E16000E0F78B /* Metal.framework */,
+                8A39BE092AC7601000BFEB40 /* Accelerate.framework */,
+            );
+            name = Frameworks;
+            sourceTree = "<group>";
+        };
+        8A3F84102AC4BD85005E2EE8 /* Resources */ = {
+            isa = PBXGroup;
+            children = (
+                8A3F84112AC4BD8C005E2EE8 /* models */,
+            );
+            path = Resources;
+            sourceTree = "<group>";
+        };
+        8A3F84112AC4BD8C005E2EE8 /* models */ = {
+            isa = PBXGroup;
+            children = (
+                8A3F841F2AC4C824005E2EE8 /* llama-2-7b-chat.Q2_K.gguf */,
+            );
+            path = models;
+            sourceTree = "<group>";
+        };
+        8A907F312AC7134E006146EA /* llama.cpp.swift */ = {
+            isa = PBXGroup;
+            children = (
+                8A08D20A2AC73B1500FE6CD4 /* bridging-header.h */,
+                8A907F322AC7134E006146EA /* LibLlama.swift */,
+            );
+            path = llama.cpp.swift;
+            sourceTree = "<group>";
+        };
+        8A9F7C4A2AC332BF008AE1EA /* UI */ = {
+            isa = PBXGroup;
+            children = (
+                8A1C83782AC328BD0096AF73 /* ContentView.swift */,
+            );
+            path = UI;
+            sourceTree = "<group>";
+        };
+        8A9F7C4B2AC332DC008AE1EA /* Models */ = {
+            isa = PBXGroup;
+            children = (
+                8A9F7C4C2AC332EE008AE1EA /* LlamaState.swift */,
+            );
+            path = Models;
+            sourceTree = "<group>";
+        };
+/* End PBXGroup section */
+
+/* Begin PBXNativeTarget section */
+        8A1C83722AC328BD0096AF73 /* llama.swiftui */ = {
+            isa = PBXNativeTarget;
+            buildConfigurationList = 8A1C83812AC328BE0096AF73 /* Build configuration list for PBXNativeTarget "llama.swiftui" */;
+            buildPhases = (
+                8A1C836F2AC328BD0096AF73 /* Sources */,
+                8A1C83702AC328BD0096AF73 /* Frameworks */,
+                8A1C83712AC328BD0096AF73 /* Resources */,
+            );
+            buildRules = (
+            );
+            dependencies = (
+            );
+            name = llama.swiftui;
+            packageProductDependencies = (
+            );
+            productName = llama.swiftui;
+            productReference = 8A1C83732AC328BD0096AF73 /* llama.swiftui.app */;
+            productType = "com.apple.product-type.application";
+        };
+/* End PBXNativeTarget section */
+
+/* Begin PBXProject section */
+        8A1C836B2AC328BD0096AF73 /* Project object */ = {
+            isa = PBXProject;
+            attributes = {
+                BuildIndependentTargetsInParallel = 1;
+                LastSwiftUpdateCheck = 1500;
+                LastUpgradeCheck = 1500;
+                TargetAttributes = {
+                    8A1C83722AC328BD0096AF73 = {
+                        CreatedOnToolsVersion = 15.0;
+                        LastSwiftMigration = 1500;
+                    };
+                };
+            };
+            buildConfigurationList = 8A1C836E2AC328BD0096AF73 /* Build configuration list for PBXProject "llama.swiftui" */;
+            compatibilityVersion = "Xcode 14.0";
+            developmentRegion = en;
+            hasScannedForEncodings = 0;
+            knownRegions = (
+                en,
+                Base,
+            );
+            mainGroup = 8A1C836A2AC328BD0096AF73;
+            packageReferences = (
+            );
+            productRefGroup = 8A1C83742AC328BD0096AF73 /* Products */;
+            projectDirPath = "";
+            projectRoot = "";
+            targets = (
+                8A1C83722AC328BD0096AF73 /* llama.swiftui */,
+            );
+        };
+/* End PBXProject section */
+
+/* Begin PBXResourcesBuildPhase section */
+        8A1C83712AC328BD0096AF73 /* Resources */ = {
+            isa = PBXResourcesBuildPhase;
+            buildActionMask = 2147483647;
+            files = (
+                542378792ACE3F3500834A7B /* ggml-metal.metal in Resources */,
+                8A3F84242AC4C891005E2EE8 /* models in Resources */,
+                8A1C837E2AC328BE0096AF73 /* Preview Assets.xcassets in Resources */,
+                8A1C837B2AC328BE0096AF73 /* Assets.xcassets in Resources */,
+            );
+            runOnlyForDeploymentPostprocessing = 0;
+        };
+/* End PBXResourcesBuildPhase section */
+
+/* Begin PBXSourcesBuildPhase section */
+        8A1C836F2AC328BD0096AF73 /* Sources */ = {
+            isa = PBXSourcesBuildPhase;
+            buildActionMask = 2147483647;
+            files = (
+                542376082B0D9BFB008E6A1C /* ggml-quants.c in Sources */,
+                549479CD2AC9E42A00E0F78B /* ggml-metal.m in Sources */,
+                542EA09D2AC8723900A8AEE9 /* ggml.c in Sources */,
+                8A907F332AC7138A006146EA /* LibLlama.swift in Sources */,
+                542EA0A32AC8729100A8AEE9 /* llama.cpp in Sources */,
+                8A9F7C4D2AC332EE008AE1EA /* LlamaState.swift in Sources */,
+                8A1C83792AC328BD0096AF73 /* ContentView.swift in Sources */,
+                8A1C83772AC328BD0096AF73 /* llama_swiftuiApp.swift in Sources */,
+                542EA0A02AC8725700A8AEE9 /* ggml-alloc.c in Sources */,
+                5423760B2B0D9C4B008E6A1C /* ggml-backend.c in Sources */,
+            );
+            runOnlyForDeploymentPostprocessing = 0;
+        };
+/* End PBXSourcesBuildPhase section */
+
+/* Begin XCBuildConfiguration section */
+        8A1C837F2AC328BE0096AF73 /* Debug */ = {
+            isa = XCBuildConfiguration;
+            buildSettings = {
+                ALWAYS_SEARCH_USER_PATHS = NO;
+                ASSETCATALOG_COMPILER_GENERATE_SWIFT_ASSET_SYMBOL_EXTENSIONS = YES;
+                CLANG_ANALYZER_NONNULL = YES;
+                CLANG_ANALYZER_NUMBER_OBJECT_CONVERSION = YES_AGGRESSIVE;
+                CLANG_CXX_LANGUAGE_STANDARD = "gnu++20";
+                CLANG_ENABLE_MODULES = YES;
+                CLANG_ENABLE_OBJC_ARC = YES;
+                CLANG_ENABLE_OBJC_WEAK = YES;
+                CLANG_WARN_BLOCK_CAPTURE_AUTORELEASING = YES;
+                CLANG_WARN_BOOL_CONVERSION = YES;
+                CLANG_WARN_COMMA = YES;
+                CLANG_WARN_CONSTANT_CONVERSION = YES;
+                CLANG_WARN_DEPRECATED_OBJC_IMPLEMENTATIONS = YES;
+                CLANG_WARN_DIRECT_OBJC_ISA_USAGE = YES_ERROR;
+                CLANG_WARN_DOCUMENTATION_COMMENTS = YES;
+                CLANG_WARN_EMPTY_BODY = YES;
+                CLANG_WARN_ENUM_CONVERSION = YES;
+                CLANG_WARN_INFINITE_RECURSION = YES;
+                CLANG_WARN_INT_CONVERSION = YES;
+                CLANG_WARN_NON_LITERAL_NULL_CONVERSION = YES;
+                CLANG_WARN_OBJC_IMPLICIT_RETAIN_SELF = YES;
+                CLANG_WARN_OBJC_LITERAL_CONVERSION = YES;
+                CLANG_WARN_OBJC_ROOT_CLASS = YES_ERROR;
+                CLANG_WARN_QUOTED_INCLUDE_IN_FRAMEWORK_HEADER = YES;
+                CLANG_WARN_RANGE_LOOP_ANALYSIS = YES;
+                CLANG_WARN_STRICT_PROTOTYPES = YES;
+                CLANG_WARN_SUSPICIOUS_MOVE = YES;
+                CLANG_WARN_UNGUARDED_AVAILABILITY = YES_AGGRESSIVE;
+                CLANG_WARN_UNREACHABLE_CODE = YES;
+                CLANG_WARN__DUPLICATE_METHOD_MATCH = YES;
+                COPY_PHASE_STRIP = NO;
+                DEBUG_INFORMATION_FORMAT = dwarf;
+                ENABLE_STRICT_OBJC_MSGSEND = YES;
+                ENABLE_TESTABILITY = YES;
+                ENABLE_USER_SCRIPT_SANDBOXING = YES;
+                GCC_C_LANGUAGE_STANDARD = gnu17;
+                GCC_DYNAMIC_NO_PIC = NO;
+                GCC_NO_COMMON_BLOCKS = YES;
+                GCC_OPTIMIZATION_LEVEL = 0;
+                GCC_PREPROCESSOR_DEFINITIONS = (
+                    "DEBUG=1",
+                    "$(inherited)",
+                );
+                GCC_WARN_64_TO_32_BIT_CONVERSION = YES;
+                GCC_WARN_ABOUT_RETURN_TYPE = YES_ERROR;
+                GCC_WARN_UNDECLARED_SELECTOR = YES;
+                GCC_WARN_UNINITIALIZED_AUTOS = YES_AGGRESSIVE;
+                GCC_WARN_UNUSED_FUNCTION = YES;
+                GCC_WARN_UNUSED_VARIABLE = YES;
+                IPHONEOS_DEPLOYMENT_TARGET = 17.0;
+                LOCALIZATION_PREFERS_STRING_CATALOGS = YES;
+                MTL_ENABLE_DEBUG_INFO = INCLUDE_SOURCE;
+                MTL_FAST_MATH = YES;
+                ONLY_ACTIVE_ARCH = YES;
+                SDKROOT = iphoneos;
+                SWIFT_ACTIVE_COMPILATION_CONDITIONS = "DEBUG $(inherited)";
+                SWIFT_OPTIMIZATION_LEVEL = "-Onone";
+            };
+            name = Debug;
+        };
+        8A1C83802AC328BE0096AF73 /* Release */ = {
+            isa = XCBuildConfiguration;
+            buildSettings = {
+                ALWAYS_SEARCH_USER_PATHS = NO;
+                ASSETCATALOG_COMPILER_GENERATE_SWIFT_ASSET_SYMBOL_EXTENSIONS = YES;
+                CLANG_ANALYZER_NONNULL = YES;
+                CLANG_ANALYZER_NUMBER_OBJECT_CONVERSION = YES_AGGRESSIVE;
+                CLANG_CXX_LANGUAGE_STANDARD = "gnu++20";
+                CLANG_ENABLE_MODULES = YES;
+                CLANG_ENABLE_OBJC_ARC = YES;
+                CLANG_ENABLE_OBJC_WEAK = YES;
+                CLANG_WARN_BLOCK_CAPTURE_AUTORELEASING = YES;
+                CLANG_WARN_BOOL_CONVERSION = YES;
+                CLANG_WARN_COMMA = YES;
+                CLANG_WARN_CONSTANT_CONVERSION = YES;
+                CLANG_WARN_DEPRECATED_OBJC_IMPLEMENTATIONS = YES;
+                CLANG_WARN_DIRECT_OBJC_ISA_USAGE = YES_ERROR;
+                CLANG_WARN_DOCUMENTATION_COMMENTS = YES;
+                CLANG_WARN_EMPTY_BODY = YES;
+                CLANG_WARN_ENUM_CONVERSION = YES;
+                CLANG_WARN_INFINITE_RECURSION = YES;
+                CLANG_WARN_INT_CONVERSION = YES;
+                CLANG_WARN_NON_LITERAL_NULL_CONVERSION = YES;
+                CLANG_WARN_OBJC_IMPLICIT_RETAIN_SELF = YES;
+                CLANG_WARN_OBJC_LITERAL_CONVERSION = YES;
+                CLANG_WARN_OBJC_ROOT_CLASS = YES_ERROR;
+                CLANG_WARN_QUOTED_INCLUDE_IN_FRAMEWORK_HEADER = YES;
+                CLANG_WARN_RANGE_LOOP_ANALYSIS = YES;
+                CLANG_WARN_STRICT_PROTOTYPES = YES;
+                CLANG_WARN_SUSPICIOUS_MOVE = YES;
+                CLANG_WARN_UNGUARDED_AVAILABILITY = YES_AGGRESSIVE;
+                CLANG_WARN_UNREACHABLE_CODE = YES;
+                CLANG_WARN__DUPLICATE_METHOD_MATCH = YES;
+                COPY_PHASE_STRIP = NO;
+                DEBUG_INFORMATION_FORMAT = "dwarf-with-dsym";
+                ENABLE_NS_ASSERTIONS = NO;
+                ENABLE_STRICT_OBJC_MSGSEND = YES;
+                ENABLE_USER_SCRIPT_SANDBOXING = YES;
+                GCC_C_LANGUAGE_STANDARD = gnu17;
+                GCC_NO_COMMON_BLOCKS = YES;
+                GCC_WARN_64_TO_32_BIT_CONVERSION = YES;
+                GCC_WARN_ABOUT_RETURN_TYPE = YES_ERROR;
+                GCC_WARN_UNDECLARED_SELECTOR = YES;
+                GCC_WARN_UNINITIALIZED_AUTOS = YES_AGGRESSIVE;
+                GCC_WARN_UNUSED_FUNCTION = YES;
+                GCC_WARN_UNUSED_VARIABLE = YES;
+                IPHONEOS_DEPLOYMENT_TARGET = 17.0;
+                LOCALIZATION_PREFERS_STRING_CATALOGS = YES;
+                MTL_ENABLE_DEBUG_INFO = NO;
+                MTL_FAST_MATH = YES;
+                SDKROOT = iphoneos;
+                SWIFT_COMPILATION_MODE = wholemodule;
+                VALIDATE_PRODUCT = YES;
+            };
+            name = Release;
+        };
+        8A1C83822AC328BE0096AF73 /* Debug */ = {
+            isa = XCBuildConfiguration;
+            buildSettings = {
+                ASSETCATALOG_COMPILER_APPICON_NAME = AppIcon;
+                ASSETCATALOG_COMPILER_GLOBAL_ACCENT_COLOR_NAME = AccentColor;
+                CLANG_ENABLE_MODULES = YES;
+                CODE_SIGN_STYLE = Automatic;
+                CURRENT_PROJECT_VERSION = 1;
+                DEVELOPMENT_ASSET_PATHS = "\"llama.swiftui/Preview Content\"";
+                DEVELOPMENT_TEAM = STLSG3FG8Q;
+                ENABLE_PREVIEWS = YES;
+                GENERATE_INFOPLIST_FILE = YES;
+                INFOPLIST_KEY_UIApplicationSceneManifest_Generation = YES;
+                INFOPLIST_KEY_UIApplicationSupportsIndirectInputEvents = YES;
+                INFOPLIST_KEY_UILaunchScreen_Generation = YES;
+                INFOPLIST_KEY_UISupportedInterfaceOrientations_iPad = "UIInterfaceOrientationPortrait UIInterfaceOrientationPortraitUpsideDown UIInterfaceOrientationLandscapeLeft UIInterfaceOrientationLandscapeRight";
+                INFOPLIST_KEY_UISupportedInterfaceOrientations_iPhone = "UIInterfaceOrientationPortrait UIInterfaceOrientationLandscapeLeft UIInterfaceOrientationLandscapeRight";
+                IPHONEOS_DEPLOYMENT_TARGET = 16.0;
+                LD_RUNPATH_SEARCH_PATHS = (
+                    "$(inherited)",
+                    "@executable_path/Frameworks",
+                );
+                MARKETING_VERSION = 1.0;
+                PRODUCT_BUNDLE_IDENTIFIER = "com.bachittle.llama-swift";
+                PRODUCT_NAME = "$(TARGET_NAME)";
+                SWIFT_EMIT_LOC_STRINGS = YES;
+                SWIFT_OBJC_BRIDGING_HEADER = "llama.cpp.swift/bridging-header.h";
+                SWIFT_OPTIMIZATION_LEVEL = "-Onone";
+                SWIFT_VERSION = 5.0;
+                TARGETED_DEVICE_FAMILY = "1,2";
+            };
+            name = Debug;
+        };
+        8A1C83832AC328BE0096AF73 /* Release */ = {
+            isa = XCBuildConfiguration;
+            buildSettings = {
+                ASSETCATALOG_COMPILER_APPICON_NAME = AppIcon;
+                ASSETCATALOG_COMPILER_GLOBAL_ACCENT_COLOR_NAME = AccentColor;
+                CLANG_ENABLE_MODULES = YES;
+                CODE_SIGN_STYLE = Automatic;
+                CURRENT_PROJECT_VERSION = 1;
+                DEVELOPMENT_ASSET_PATHS = "\"llama.swiftui/Preview Content\"";
+                DEVELOPMENT_TEAM = STLSG3FG8Q;
+                ENABLE_PREVIEWS = YES;
+                GENERATE_INFOPLIST_FILE = YES;
+                INFOPLIST_KEY_UIApplicationSceneManifest_Generation = YES;
+                INFOPLIST_KEY_UIApplicationSupportsIndirectInputEvents = YES;
+                INFOPLIST_KEY_UILaunchScreen_Generation = YES;
+                INFOPLIST_KEY_UISupportedInterfaceOrientations_iPad = "UIInterfaceOrientationPortrait UIInterfaceOrientationPortraitUpsideDown UIInterfaceOrientationLandscapeLeft UIInterfaceOrientationLandscapeRight";
+                INFOPLIST_KEY_UISupportedInterfaceOrientations_iPhone = "UIInterfaceOrientationPortrait UIInterfaceOrientationLandscapeLeft UIInterfaceOrientationLandscapeRight";
+                IPHONEOS_DEPLOYMENT_TARGET = 16.0;
+                LD_RUNPATH_SEARCH_PATHS = (
+                    "$(inherited)",
+                    "@executable_path/Frameworks",
+                );
+                MARKETING_VERSION = 1.0;
+                PRODUCT_BUNDLE_IDENTIFIER = "com.bachittle.llama-swift";
+                PRODUCT_NAME = "$(TARGET_NAME)";
+                SWIFT_EMIT_LOC_STRINGS = YES;
+                SWIFT_OBJC_BRIDGING_HEADER = "llama.cpp.swift/bridging-header.h";
+                SWIFT_VERSION = 5.0;
+                TARGETED_DEVICE_FAMILY = "1,2";
+            };
+            name = Release;
+        };
+/* End XCBuildConfiguration section */
+
+/* Begin XCConfigurationList section */
+        8A1C836E2AC328BD0096AF73 /* Build configuration list for PBXProject "llama.swiftui" */ = {
+            isa = XCConfigurationList;
+            buildConfigurations = (
+                8A1C837F2AC328BE0096AF73 /* Debug */,
+                8A1C83802AC328BE0096AF73 /* Release */,
+            );
+            defaultConfigurationIsVisible = 0;
+            defaultConfigurationName = Release;
+        };
+        8A1C83812AC328BE0096AF73 /* Build configuration list for PBXNativeTarget "llama.swiftui" */ = {
+            isa = XCConfigurationList;
+            buildConfigurations = (
+                8A1C83822AC328BE0096AF73 /* Debug */,
+                8A1C83832AC328BE0096AF73 /* Release */,
+            );
+            defaultConfigurationIsVisible = 0;
+            defaultConfigurationName = Release;
+        };
+/* End XCConfigurationList section */
+    };
+    rootObject = 8A1C836B2AC328BD0096AF73 /* Project object */;
+}

examples/llama.swiftui/llama.swiftui.xcodeproj/project.xcworkspace/contents.xcworkspacedata

@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<Workspace
+   version = "1.0">
+   <FileRef
+      location = "self:">
+   </FileRef>
+</Workspace>

examples/llama.swiftui/llama.swiftui.xcodeproj/project.xcworkspace/xcshareddata/IDEWorkspaceChecks.plist

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
+<plist version="1.0">
+<dict>
+    <key>IDEDidComputeMac32BitWarning</key>
+    <true/>
+</dict>
+</plist>

examples/llama.swiftui/llama.swiftui/Assets.xcassets/AccentColor.colorset/Contents.json

@@ -0,0 +1,11 @@
+{
+  "colors" : [
+    {
+      "idiom" : "universal"
+    }
+  ],
+  "info" : {
+    "author" : "xcode",
+    "version" : 1
+  }
+}

examples/llama.swiftui/llama.swiftui/Assets.xcassets/AppIcon.appiconset/Contents.json

@@ -0,0 +1,13 @@
+{
+  "images" : [
+    {
+      "idiom" : "universal",
+      "platform" : "ios",
+      "size" : "1024x1024"
+    }
+  ],
+  "info" : {
+    "author" : "xcode",
+    "version" : 1
+  }
+}

examples/llama.swiftui/llama.swiftui/Assets.xcassets/Contents.json

@@ -0,0 +1,6 @@
+{
+  "info" : {
+    "author" : "xcode",
+    "version" : 1
+  }
+}

examples/llama.swiftui/llama.swiftui/Models/LlamaState.swift

@@ -0,0 +1,45 @@
+import Foundation
+
+@MainActor
+class LlamaState: ObservableObject {
+    @Published var messageLog = ""
+
+    private var llamaContext: LlamaContext?
+    private var modelUrl: URL? {
+        Bundle.main.url(forResource: "q8_0", withExtension: "gguf", subdirectory: "models")
+        // Bundle.main.url(forResource: "llama-2-7b-chat", withExtension: "Q2_K.gguf", subdirectory: "models")
+    }
+    init() {
+        do {
+            try loadModel()
+        } catch {
+            messageLog += "Error!\n"
+        }
+    }
+
+    private func loadModel() throws {
+        messageLog += "Loading model...\n"
+        if let modelUrl {
+            llamaContext = try LlamaContext.createContext(path: modelUrl.path())
+            messageLog += "Loaded model \(modelUrl.lastPathComponent)\n"
+        } else {
+            messageLog += "Could not locate model\n"
+        }
+    }
+
+    func complete(text: String) async {
+        guard let llamaContext else {
+            return
+        }
+        messageLog += "Attempting to complete text...\n"
+        await llamaContext.completion_init(text: text)
+        messageLog += "\(text)"
+
+        while await llamaContext.n_cur <= llamaContext.n_len {
+            let result = await llamaContext.completion_loop()
+            messageLog += "\(result)"
+        }
+        await llamaContext.clear()
+        messageLog += "\n\ndone\n"
+    }
+}

examples/llama.swiftui/llama.swiftui/Preview Content/Preview Assets.xcassets/Contents.json

@@ -0,0 +1,6 @@
+{
+  "info" : {
+    "author" : "xcode",
+    "version" : 1
+  }
+}

examples/llama.swiftui/llama.swiftui/UI/ContentView.swift

@@ -0,0 +1,42 @@
+import SwiftUI
+
+struct ContentView: View {
+    @StateObject var llamaState = LlamaState()
+
+    @State private var multiLineText = ""
+
+    var body: some View {
+        VStack {
+            ScrollView(.vertical) {
+                Text(llamaState.messageLog)
+            }
+
+            TextEditor(text: $multiLineText)
+                .frame(height: 200)
+                .padding()
+                .border(Color.gray, width: 0.5)
+            Button(action: {
+                sendText()
+            }) {
+                Text("Send")
+                    .padding()
+                    .background(Color.blue)
+                    .foregroundColor(.white)
+                    .cornerRadius(8)
+            }
+        }
+        .padding()
+    }
+
+    func sendText() {
+        Task {
+            await llamaState.complete(text: multiLineText)
+            multiLineText = ""
+        }
+    }
+}
+/*
+#Preview {
+    ContentView()
+}
+*/

examples/llama.swiftui/llama.swiftui/llama_swiftuiApp.swift

@@ -0,0 +1,10 @@
+import SwiftUI
+
+@main
+struct llama_swiftuiApp: App {
+    var body: some Scene {
+        WindowGroup {
+            ContentView()
+        }
+    }
+}

examples/lookahead/CMakeLists.txt

@@ -0,0 +1,5 @@
+set(TARGET lookahead)
+add_executable(${TARGET} lookahead.cpp)
+install(TARGETS ${TARGET} RUNTIME)
+target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
+target_compile_features(${TARGET} PRIVATE cxx_std_11)

examples/lookahead/lookahead.cpp

@@ -0,0 +1,487 @@
+#include "common.h"
+#include "llama.h"
+
+#include <cmath>
+#include <cstdio>
+#include <string>
+#include <vector>
+
+struct ngram_data {
+    bool active = false;
+
+    llama_seq_id seq_id = -1;
+
+    std::vector<int> i_batch;
+
+    std::vector<llama_token> tokens;
+};
+
+// n-gram container
+struct ngram_container {
+    ngram_container(int n_vocab, int N, int G) {
+        cnt.resize(n_vocab);
+        head.resize(n_vocab);
+        tokens.resize(n_vocab * G * (N - 1));
+    }
+
+    int n_total = 0;
+
+    std::vector<int> cnt;
+    std::vector<int> head;
+
+    // [n_vocab][G][N - 1]
+    // for each token of the vocab, keep a ring-buffer of capacity G of n-grams of size N - 1
+    std::vector<llama_token> tokens;
+};
+
+int main(int argc, char ** argv) {
+    gpt_params params;
+
+    if (gpt_params_parse(argc, argv, params) == false) {
+        return 1;
+    }
+
+    const int W = 15; // lookahead window
+    const int N = 5;  // n-gram size
+    const int G = 15; // max verification n-grams
+
+    const bool dump_kv_cache = params.dump_kv_cache;
+
+#ifndef LOG_DISABLE_LOGS
+    log_set_target(log_filename_generator("lookahead", "log"));
+    LOG_TEE("Log start\n");
+    log_dump_cmdline(argc, argv);
+#endif // LOG_DISABLE_LOGS
+
+    // init llama.cpp
+    llama_backend_init(params.numa);
+
+    llama_model * model = NULL;
+    llama_context * ctx = NULL;
+
+    // load the target model
+    std::tie(model, ctx) = llama_init_from_gpt_params(params);
+
+    // Tokenize the prompt
+    const bool add_bos = llama_should_add_bos_token(model);
+    LOG("add_bos tgt: %d\n", add_bos);
+
+    std::vector<llama_token> inp;
+    std::vector<llama_token> all;
+
+    inp = ::llama_tokenize(ctx, params.prompt, add_bos, true);
+    all = inp;
+
+    const int max_context_size     = llama_n_ctx(ctx);
+    const int max_tokens_list_size = max_context_size - 4;
+
+    if ((int) inp.size() > max_tokens_list_size) {
+        fprintf(stderr, "%s: error: prompt too long (%d tokens, max %d)\n", __func__, (int) inp.size(), max_tokens_list_size);
+        return 1;
+    }
+
+    fprintf(stderr, "\n\n");
+
+    for (auto id : inp) {
+        fprintf(stderr, "%s", llama_token_to_piece(ctx, id).c_str());
+    }
+
+    fflush(stderr);
+
+    const int n_input = inp.size();
+
+    const auto t_enc_start = ggml_time_us();
+
+    // eval the prompt
+    llama_decode(ctx, llama_batch_get_one( inp.data(), n_input - 1, 0,           0));
+    llama_decode(ctx, llama_batch_get_one(&inp.back(),           1, n_input - 1, 0));
+
+    for (int s = 1; s < W + G + 1; ++s) {
+        llama_kv_cache_seq_cp(ctx, 0, s, -1, -1);
+    }
+
+    const auto t_enc_end = ggml_time_us();
+
+    int n_predict = 0;
+    int n_accept  = 0;
+
+    int n_past = inp.size();
+
+    llama_token id = 0;
+
+    // used to determine end of generation
+    bool has_eos = false;
+
+    // for each decoded batch, we have at most W + G + 1 distinct sequences:
+    // seq_id == 0           : the current input token
+    // seq_id [1, W]         : tokens from the past N - 1 Jacobi iterations
+    // seq_id [W + 1, W + G] : verification n-grams
+    llama_batch batch = llama_batch_init(params.n_ctx, 0, W + G + 1);
+
+    // target model sampling context
+    struct llama_sampling_context * ctx_sampling = llama_sampling_init(params.sparams);
+
+    // verification n-grams
+    std::vector<ngram_data> ngrams_cur(G);
+
+    // tokens for the past N - 1 Jacobi iterations
+    std::vector<llama_token> tokens_j_prev(W);
+    std::vector<std::vector<llama_token>> tokens_j(N - 1);
+    for (int j = 0; j < N - 1; j++) {
+        tokens_j[j].resize(W);
+
+        for (int i = 0; i < W; i++) {
+            // there are different ways to init these tokens
+            if (0) {
+                // initialize randomly from the prompt tokens
+                tokens_j[j][i] = all[1 + rand() % (all.size() - 1)];
+            } else {
+                // initialize with a sequence of increasing numbers
+                tokens_j[j][i] = 100 + i;
+            }
+        }
+    }
+
+    std::vector<llama_seq_id> seq_id_look;
+
+    // the input token belongs both to all sequences
+    std::vector<llama_seq_id> seq_id_all(W + G + 1);
+    for (int i = 0; i < W + G + 1; i++) {
+        seq_id_all[i] = i;
+    }
+
+    // here we keep adding new n-grams as we go
+    ngram_container ngrams_observed(llama_n_vocab(model), N, G);
+
+    // debug
+    struct llama_kv_cache_view kvc_view = llama_kv_cache_view_init(ctx, W + G + 1);
+
+    const auto t_dec_start = ggml_time_us();
+
+    // sample first token
+    {
+        id = llama_sampling_sample(ctx_sampling, ctx, NULL, 0);
+
+        llama_sampling_accept(ctx_sampling, ctx, id, true);
+
+        {
+            const std::string token_str = llama_token_to_piece(ctx, id);
+
+            printf("%s", token_str.c_str());
+            fflush(stdout);
+        }
+    }
+
+    while (true) {
+        // debug
+        if (dump_kv_cache) {
+            llama_kv_cache_view_update(ctx, &kvc_view);
+            dump_kv_cache_view_seqs(kvc_view, 40);
+        }
+
+        // build the mask from https://lmsys.org/blog/2023-11-21-lookahead-decoding/
+        //
+        // Example for W = 5, N = 4, G = 2:
+        // (I = input, L = lookahead, V = verification)
+        //
+        // Batch:  0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20
+        // T:        -2 -2 -2 -2 -1 -1 -1 -1 -1  0  0  0  0  0  0
+        // Info:   I  L  L  L  L  L  L  L  L  L  L  L  L  L  L  V  V  V  V  V  V
+        // Pos:    0  1  2  3  4  1  2  3  4  5  2  3  4  5  6  1  2  3  1  2  3   (+ n_past)
+        // Logits: 1  0  0  0  0  0  0  0  0  0  1  1  1  1  1  1  1  1  1  1  1
+        // ---------------------------------------------------------------------
+        // Seq:    0
+        //         1              1              1
+        //         2  2              2              2
+        //         3  3  3              3              3
+        //         4  4  4  4              4              4
+        //         5  5  5  5  5              5              5
+        //         6                                            6  6  6
+        //         7                                                     7  7  7
+        // ---------------------------------------------------------------------
+        //                                       |  |  |  |  |  |  |  |  |  |  |
+        //                                       V  V  V  V  V  |  |  |  |  |  |
+        //                                         j_tokens     |  |  |  |  |  |
+        //                                                      V  V  V  V  V  V
+        //                                                             id
+        {
+            llama_batch_clear(batch);
+
+            // current token - first token of the first level
+            llama_batch_add(batch, id, n_past, seq_id_all, true);
+
+            // verification n-grams - queue this before the lookahead tokens for less KV cache fragmentation
+            {
+                const int g_cur = ngrams_observed.cnt[id];
+
+                ngrams_cur.resize(g_cur);
+                for (int g = 0; g < g_cur; g++) {
+                    ngrams_cur[g].active = true;
+                    ngrams_cur[g].tokens.resize(N);
+                    ngrams_cur[g].i_batch.resize(N);
+                    ngrams_cur[g].seq_id = W + 1 + g;
+                    ngrams_cur[g].i_batch[0] = 0;
+                    ngrams_cur[g].tokens [0] = id;
+                }
+
+                for (int j = 0; j < N - 1; j++) {
+                    for (int g = 0; g < g_cur; g++) {
+                        const int idx = id*(N - 1)*G + g*(N - 1);
+
+                        const llama_token t = ngrams_observed.tokens[idx + j];
+
+                        ngrams_cur[g].tokens [j + 1] = t;
+                        ngrams_cur[g].i_batch[j + 1] = batch.n_tokens;
+
+                        llama_batch_add(batch, t, n_past + j + 1, { W + 1 + g }, true);
+                    }
+                }
+            }
+
+            // fill the remaining W - 1 tokens for the first level
+            for (int i = 1; i < W; i++) {
+                seq_id_look.resize(W - i);
+                for (int j = 0; j < W - i; j++) {
+                    seq_id_look[j] = i + j + 1;
+                }
+
+                llama_batch_add(batch, tokens_j[0][i], n_past + i, seq_id_look, false);
+            }
+
+            // fill the rest of the levels
+            for (int j = 1; j < N - 1; j++) {
+                for (int i = 0; i < W; i++) {
+                    llama_batch_add(batch, tokens_j[j][i], n_past + j + i, { i + 1 }, j == N - 2);
+                }
+            }
+        }
+
+        if (llama_decode(ctx, batch) != 0) {
+            fprintf(stderr, "\n\n%s: error: llama_decode failed - increase KV cache size\n", __func__);
+            return 1;
+        }
+
+        int seq_id_best = 0;
+
+        for (int v = 0; v < N; ++v) {
+            int i_batch = 0;
+
+            // if no active ngrams are left, it means the sampled token does not pass the verification
+            if (v > 0) {
+                for (int g = 0; g < (int) ngrams_cur.size(); g++) {
+                    if (ngrams_cur[g].active) {
+                        i_batch = ngrams_cur[g].i_batch[v];
+                        seq_id_best = ngrams_cur[g].seq_id;
+
+                        ++n_accept;
+                        break;
+                    }
+                }
+
+                // no more matches -> create a new batch
+                if (i_batch == 0) {
+                    break;
+                }
+            }
+
+            // sample the next token
+            id = llama_sampling_sample(ctx_sampling, ctx, NULL, i_batch);
+
+            llama_sampling_accept(ctx_sampling, ctx, id, true);
+
+            // print
+            {
+                const std::string token_str = llama_token_to_piece(ctx, id);
+
+                if (v == 0) {
+                    printf("%s", token_str.c_str());
+                } else {
+                    // print light cyan
+                    printf("\033[0;96m%s\033[0m", token_str.c_str());
+                }
+                fflush(stdout);
+
+                if (id == llama_token_eos(model)) {
+                    has_eos = true;
+                }
+
+                all.push_back(id);
+            }
+
+            ++n_predict;
+            ++n_past;
+
+            if ((params.n_predict >= 0 && n_predict > params.n_predict) || has_eos) {
+                break;
+            }
+
+            // verify across active n-grams
+            for (int g = 0; g < (int) ngrams_cur.size(); g++) {
+                if (ngrams_cur[g].active) {
+                    if (v == N - 1) {
+                        ngrams_cur[g].active = false;
+                    } else {
+                        if (id != ngrams_cur[g].tokens[v + 1]) {
+                            ngrams_cur[g].active = false;
+                        }
+                    }
+                }
+            }
+
+            // print known n-grams starting with token id (debug)
+            if (0 && v == 0) {
+                if (ngrams_observed.cnt[id] > 0) {
+                    printf("\n - %d n-grams starting with '%s'\n", ngrams_observed.cnt[id], llama_token_to_piece(ctx, id).c_str());
+                }
+
+                for (int i = 0; i < ngrams_observed.cnt[id]; i++) {
+                    printf("   - ngram %2d: ", i);
+
+                    const int idx = id*(N - 1)*G + i*(N - 1);
+
+                    for (int j = 0; j < N - 1; j++) {
+                        const std::string token_str = llama_token_to_piece(ctx, ngrams_observed.tokens[idx + j]);
+
+                        printf("%s", token_str.c_str());
+                    }
+
+                    printf("\n");
+                }
+            }
+
+            // update lookahead tokens
+            {
+                for (int i = 0; i < W; i++) {
+                    tokens_j_prev[i] = tokens_j[0][i];
+                }
+
+                for (int j = 0; j < N - 2; j++) {
+                    tokens_j[j] = tokens_j[j + 1];
+                }
+
+                if (v == 0) {
+                    // sample from the last level
+                    for (int i = 0; i < W; i++) {
+                        tokens_j[N - 2][i] = llama_sampling_sample(ctx_sampling, ctx, NULL, ngrams_cur.size()*(N-1) + W*(N - 2) + i);
+                    }
+                } else {
+                    for (int i = 0; i < W; i++) {
+                        // there are different ways to init these tokens
+                        if (0) {
+                            // random init
+                            tokens_j[N - 2][i] = all[1 + rand() % (all.size() - 1)];
+                        } else {
+                            // init from the previous level
+                            tokens_j[N - 2][i] = tokens_j[0][i];
+                        }
+                    }
+                }
+            }
+
+            // update observed ngrams
+            if (v == 0) {
+                // the first token of the n-gram is determined by the index in the container so it is not stored
+                std::vector<llama_token> ngram(N - 1);
+
+                // n-gram generation
+                // ref: https://github.com/hao-ai-lab/LookaheadDecoding/issues/14#issuecomment-1826198518
+                for (int f = 0; f < W; ++f) {
+                    const int ft = tokens_j_prev[f]; // first token of the n-gram
+
+                    for (int j = 0; j < N - 1; ++j) {
+                        ngram[j] = tokens_j[j][f];
+                    }
+
+                    // filter-out repeating n-grams
+                    {
+                        bool is_unique = true;
+
+                        for (int k = 0; k < ngrams_observed.cnt[ft]; ++k) {
+                            const int idx = ft*(N - 1)*G + k*(N - 1);
+
+                            bool is_match = true;
+                            for (int j = 0; j < N - 1; ++j) {
+                                if (ngrams_observed.tokens[idx + j] != ngram[j]) {
+                                    is_match = false;
+                                    break;
+                                }
+                            }
+
+                            if (is_match) {
+                                is_unique = false;
+                                break;
+                            }
+                        }
+
+                        if (!is_unique) {
+                            continue;
+                        }
+                    }
+
+                    const int head = ngrams_observed.head[ft];
+                    const int idx  = ft*(N - 1)*G + head*(N - 1);
+
+                    for (int i = 0; i < N - 1; i++) {
+                        ngrams_observed.tokens[idx + i] = ngram[i];
+                    }
+
+                    ngrams_observed.cnt[ft]  = std::min(G, ngrams_observed.cnt[ft] + 1);
+                    ngrams_observed.head[ft] = (head + 1) % G;
+
+                    ngrams_observed.n_total++;
+                }
+            }
+        }
+
+        if ((params.n_predict >= 0 && n_predict > params.n_predict) || has_eos) {
+            break;
+        }
+
+        // KV cache management
+        // if no verification token matched, we simply remove all cells from this batch -> no fragmentation
+        llama_kv_cache_seq_rm(ctx, -1, n_past, -1);
+
+        if (seq_id_best != 0) {
+            // if a verification token matched, we keep the best sequence and remove the rest
+            // this leads to some KV cache fragmentation
+            llama_kv_cache_seq_keep(ctx, seq_id_best);
+            llama_kv_cache_seq_cp  (ctx, seq_id_best, 0, -1, -1);
+            llama_kv_cache_seq_rm  (ctx, seq_id_best,    -1, -1);
+
+            for (int s = 1; s < W + G + 1; ++s) {
+                llama_kv_cache_seq_cp(ctx, 0, s, -1, -1);
+            }
+        }
+    }
+
+    auto t_dec_end = ggml_time_us();
+
+    LOG_TEE("\n\n");
+
+    LOG_TEE("encoded %4d tokens in %8.3f seconds, speed: %8.3f t/s\n", n_input,   (t_enc_end - t_enc_start) / 1e6f, inp.size() / ((t_enc_end - t_enc_start) / 1e6f));
+    LOG_TEE("decoded %4d tokens in %8.3f seconds, speed: %8.3f t/s\n", n_predict, (t_dec_end - t_dec_start) / 1e6f, n_predict  / ((t_dec_end - t_dec_start) / 1e6f));
+
+    LOG_TEE("\n");
+    LOG_TEE("W = %2d\n", W);
+    LOG_TEE("N = %2d\n", N);
+    LOG_TEE("G = %2d\n", G);
+    LOG_TEE("\n");
+    LOG_TEE("n_predict = %d\n", n_predict);
+    LOG_TEE("n_accept  = %d\n", n_accept);
+
+    llama_print_timings(ctx);
+
+    llama_kv_cache_view_free(&kvc_view);
+    llama_sampling_free(ctx_sampling);
+
+    llama_batch_free(batch);
+
+    llama_free(ctx);
+    llama_free_model(model);
+
+    llama_backend_free();
+
+    fprintf(stderr, "\n\n");
+
+    return 0;
+}

ggml-metal.m

@@ -1433,7 +1433,8 @@ void ggml_metal_graph_compute(
                             const int n_past     = ((int32_t *) dst->op_params)[0];
                             const int n_dims     = ((int32_t *) dst->op_params)[1];
                             const int mode       = ((int32_t *) dst->op_params)[2];
-                            const int n_orig_ctx = ((int32_t *) dst->op_params)[3];
+                            // skip 3, n_ctx, used in GLM RoPE, unimplemented in metal
+                            const int n_orig_ctx = ((int32_t *) dst->op_params)[4];
 
                             float freq_base, freq_scale, ext_factor, attn_factor, beta_fast, beta_slow;
                             memcpy(&freq_base,   (int32_t *) dst->op_params +  5, sizeof(float));

ggml.c

@@ -15689,13 +15689,14 @@ static int ggml_get_n_tasks(struct ggml_tensor * node, int n_threads) {
             {
                 n_tasks = 1;
             } break;
-        case GGML_OP_COUNT:
-            {
-                GGML_ASSERT(false);
-            } break;
         default:
             {
-                printf("%s: op %s not implemented\n", __func__, ggml_op_name(node->op));
+                fprintf(stderr, "%s: op not implemented: ", __func__);
+                if (node->op < GGML_OP_COUNT) {
+                    fprintf(stderr, "%s\n", ggml_op_name(node->op));
+                } else {
+                    fprintf(stderr, "%d\n", node->op);
+                }
                 GGML_ASSERT(false);
             } break;
     }

ggml.h

@@ -244,11 +244,10 @@
 #define GGML_ASSERT(x) \
     do { \
         if (!(x)) { \
-            fprintf(stderr, "GGML_ASSERT: %s:%d: %s\n", __FILE__, __LINE__, #x); \
-            fflush(stderr); \
             fflush(stdout); \
+            fprintf(stderr, "GGML_ASSERT: %s:%d: %s\n", __FILE__, __LINE__, #x); \
             ggml_print_backtrace(); \
-            exit(1); \
+            abort(); \
         } \
     } while (0)
 

scripts/build-info.cmake

@@ -1,5 +1,3 @@
-set(TEMPLATE_FILE "${CMAKE_CURRENT_SOURCE_DIR}/common/build-info.cpp.in")
-set(OUTPUT_FILE "${CMAKE_CURRENT_SOURCE_DIR}/common/build-info.cpp")
 set(BUILD_NUMBER 0)
 set(BUILD_COMMIT "unknown")
 set(BUILD_COMPILER "unknown")
@@ -58,23 +56,3 @@ else()
     )
     set(BUILD_TARGET ${OUT})
 endif()
-
-# Only write the build info if it changed
-if(EXISTS ${OUTPUT_FILE})
-    file(READ ${OUTPUT_FILE} CONTENTS)
-    string(REGEX MATCH "LLAMA_COMMIT = \"([^\"]*)\";" _ ${CONTENTS})
-    set(OLD_COMMIT ${CMAKE_MATCH_1})
-    string(REGEX MATCH "LLAMA_COMPILER = \"([^\"]*)\";" _ ${CONTENTS})
-    set(OLD_COMPILER ${CMAKE_MATCH_1})
-    string(REGEX MATCH "LLAMA_BUILD_TARGET = \"([^\"]*)\";" _ ${CONTENTS})
-    set(OLD_TARGET ${CMAKE_MATCH_1})
-    if (
-        NOT OLD_COMMIT   STREQUAL BUILD_COMMIT   OR
-        NOT OLD_COMPILER STREQUAL BUILD_COMPILER OR
-        NOT OLD_TARGET   STREQUAL BUILD_TARGET
-    )
-        configure_file(${TEMPLATE_FILE} ${OUTPUT_FILE})
-    endif()
-else()
-    configure_file(${TEMPLATE_FILE} ${OUTPUT_FILE})
-endif()

scripts/gen-build-info-cpp.cmake

@@ -0,0 +1,24 @@
+include(${CMAKE_CURRENT_SOURCE_DIR}/scripts/build-info.cmake)
+
+set(TEMPLATE_FILE "${CMAKE_CURRENT_SOURCE_DIR}/common/build-info.cpp.in")
+set(OUTPUT_FILE "${CMAKE_CURRENT_SOURCE_DIR}/common/build-info.cpp")
+
+# Only write the build info if it changed
+if(EXISTS ${OUTPUT_FILE})
+    file(READ ${OUTPUT_FILE} CONTENTS)
+    string(REGEX MATCH "LLAMA_COMMIT = \"([^\"]*)\";" _ ${CONTENTS})
+    set(OLD_COMMIT ${CMAKE_MATCH_1})
+    string(REGEX MATCH "LLAMA_COMPILER = \"([^\"]*)\";" _ ${CONTENTS})
+    set(OLD_COMPILER ${CMAKE_MATCH_1})
+    string(REGEX MATCH "LLAMA_BUILD_TARGET = \"([^\"]*)\";" _ ${CONTENTS})
+    set(OLD_TARGET ${CMAKE_MATCH_1})
+    if (
+        NOT OLD_COMMIT   STREQUAL BUILD_COMMIT   OR
+        NOT OLD_COMPILER STREQUAL BUILD_COMPILER OR
+        NOT OLD_TARGET   STREQUAL BUILD_TARGET
+    )
+        configure_file(${TEMPLATE_FILE} ${OUTPUT_FILE})
+    endif()
+else()
+    configure_file(${TEMPLATE_FILE} ${OUTPUT_FILE})
+endif()