First upload version 0.0.1

node_modules/node-llama-cpp/llama/addon/AddonContext.cpp

@@ -0,0 +1,985 @@
+#include <thread>
+#include <algorithm>
+#include <cmath>
+#include "common/common.h"
+#include "llama-vocab.h"
+#include "llama.h"
+
+#include "addonGlobals.h"
+#include "AddonModel.h"
+#include "AddonModelLora.h"
+#include "AddonGrammarEvaluationState.h"
+#include "AddonContext.h"
+
+static uint64_t calculateBatchMemorySize(int32_t n_tokens_alloc, int32_t embd, int32_t n_seq_max) {
+    uint64_t totalSize = 0;
+
+    if (embd) {
+        totalSize += sizeof(float) * n_tokens_alloc * embd;
+    } else {
+        totalSize += sizeof(llama_token) * n_tokens_alloc;
+    }
+
+    totalSize += sizeof(llama_pos) * n_tokens_alloc;
+    totalSize += sizeof(int32_t) * n_tokens_alloc;
+    totalSize += sizeof(llama_seq_id *) * (n_tokens_alloc + 1);
+
+    totalSize += sizeof(llama_seq_id) * n_seq_max * n_tokens_alloc;
+
+    totalSize += sizeof(int8_t) * n_tokens_alloc;
+
+    return totalSize;
+}
+
+class AddonContextDecodeBatchWorker : public Napi::AsyncWorker {
+    public:
+        AddonContext* ctx;
+
+        AddonContextDecodeBatchWorker(const Napi::Env& env, AddonContext* ctx)
+            : Napi::AsyncWorker(env, "AddonContextDecodeBatchWorker"),
+              ctx(ctx),
+              deferred(Napi::Promise::Deferred::New(env)) {
+            ctx->Ref();
+        }
+        ~AddonContextDecodeBatchWorker() {
+            ctx->Unref();
+        }
+
+        Napi::Promise GetPromise() {
+            return deferred.Promise();
+        }
+
+    protected:
+        Napi::Promise::Deferred deferred;
+
+        void Execute() {
+            try {
+                // Perform the evaluation using llama_decode.
+                int r = llama_decode(ctx->ctx, ctx->batch);
+
+                if (r != 0) {
+                    if (r == 1) {
+                        SetError("could not find a KV slot for the batch (try reducing the size of the batch or increase the context)");
+                    } else {
+                        SetError("Eval has failed");
+                    }
+
+                    return;
+                }
+
+                llama_synchronize(ctx->ctx);
+            } catch (const std::exception& e) {
+                SetError(e.what());
+            } catch(...) {
+                SetError("Unknown error when calling \"llama_decode\"");
+            }
+        }
+        void OnOK() {
+            deferred.Resolve(Env().Undefined());
+        }
+        void OnError(const Napi::Error& err) {
+            deferred.Reject(err.Value());
+        }
+};
+
+class AddonContextLoadContextWorker : public Napi::AsyncWorker {
+    public:
+        AddonContext* context;
+
+        AddonContextLoadContextWorker(const Napi::Env& env, AddonContext* context)
+            : Napi::AsyncWorker(env, "AddonContextLoadContextWorker"),
+              context(context),
+              deferred(Napi::Promise::Deferred::New(env)) {
+            context->Ref();
+        }
+        ~AddonContextLoadContextWorker() {
+            context->Unref();
+        }
+
+        Napi::Promise GetPromise() {
+            return deferred.Promise();
+        }
+
+    protected:
+        Napi::Promise::Deferred deferred;
+
+        void Execute() {
+            try {
+                context->ctx = llama_init_from_model(context->model->model, context->context_params);
+
+                context->contextLoaded = context->ctx != nullptr && context->ctx != NULL;
+            } catch (const std::exception& e) {
+                SetError(e.what());
+            } catch(...) {
+                SetError("Unknown error when calling \"llama_init_from_model\"");
+            }
+        }
+        void OnOK() {
+            if (context->contextLoaded) {
+                uint64_t contextMemorySize = llama_state_get_size(context->ctx);
+                adjustNapiExternalMemoryAdd(Env(), contextMemorySize);
+                context->loadedContextMemorySize = contextMemorySize;
+            }
+
+            deferred.Resolve(Napi::Boolean::New(Env(), context->contextLoaded));
+        }
+        void OnError(const Napi::Error& err) {
+            deferred.Reject(err.Value());
+        }
+};
+class AddonContextUnloadContextWorker : public Napi::AsyncWorker {
+    public:
+        AddonContext* context;
+
+        AddonContextUnloadContextWorker(const Napi::Env& env, AddonContext* context)
+            : Napi::AsyncWorker(env, "AddonContextUnloadContextWorker"),
+              context(context),
+              deferred(Napi::Promise::Deferred::New(env)) {
+            context->Ref();
+        }
+        ~AddonContextUnloadContextWorker() {
+            context->Unref();
+        }
+
+        Napi::Promise GetPromise() {
+            return deferred.Promise();
+        }
+
+    protected:
+        Napi::Promise::Deferred deferred;
+
+        void Execute() {
+            try {
+                llama_free(context->ctx);
+                context->contextLoaded = false;
+
+                try {
+                    if (context->has_batch) {
+                        llama_batch_free(context->batch);
+                        context->has_batch = false;
+                        context->batch_n_tokens = 0;
+                    }
+
+                    context->dispose();
+                } catch (const std::exception& e) {
+                    SetError(e.what());
+                } catch(...) {
+                    SetError("Unknown error when calling \"llama_batch_free\"");
+                }
+            } catch (const std::exception& e) {
+                SetError(e.what());
+            } catch(...) {
+                SetError("Unknown error when calling \"llama_free\"");
+            }
+        }
+        void OnOK() {
+            adjustNapiExternalMemorySubtract(Env(), context->loadedContextMemorySize);
+            context->loadedContextMemorySize = 0;
+
+            adjustNapiExternalMemorySubtract(Env(), context->batchMemorySize);
+            context->batchMemorySize = 0;
+
+            deferred.Resolve(Env().Undefined());
+        }
+        void OnError(const Napi::Error& err) {
+            deferred.Reject(err.Value());
+        }
+};
+
+
+class AddonContextSampleTokenWorker : public Napi::AsyncWorker {
+    public:
+        AddonContext* ctx;
+        AddonSampler* sampler;
+        bool arrayResult = false;
+        bool returnProbabilities = false;
+        bool returnConfidence = false;
+        float tokenConfidence = -1;
+        bool has_probabilities = false;
+        size_t probabilities_size;
+        llama_token * probabilities_tokens;
+        float * probabilities_probs;
+        int32_t batchLogitIndex;
+        llama_token result;
+        bool no_output = false;
+
+        AddonContextSampleTokenWorker(const Napi::CallbackInfo& info, AddonContext* ctx)
+            : Napi::AsyncWorker(info.Env(), "AddonContextSampleTokenWorker"),
+              ctx(ctx),
+              deferred(Napi::Promise::Deferred::New(info.Env())) {
+            ctx->Ref();
+
+            batchLogitIndex = info[0].As<Napi::Number>().Int32Value();
+            sampler = Napi::ObjectWrap<AddonSampler>::Unwrap(info[1].As<Napi::Object>());
+            arrayResult = info.Length() > 2 && info[2].IsBoolean();
+            returnProbabilities = arrayResult ? info[2].As<Napi::Boolean>().Value() : false;
+            returnConfidence = arrayResult && info.Length() > 3 && info[3].IsBoolean() ? info[3].As<Napi::Boolean>().Value() : false;
+            sampler->Ref();
+        }
+        ~AddonContextSampleTokenWorker() {
+            ctx->Unref();
+            sampler->Unref();
+
+            if (has_probabilities) {
+                delete[] probabilities_tokens;
+                delete[] probabilities_probs;
+            }
+        }
+
+        Napi::Promise GetPromise() {
+            return deferred.Promise();
+        }
+
+    protected:
+        Napi::Promise::Deferred deferred;
+
+        void Execute() {
+            try {
+                SampleToken();
+            } catch (const std::exception& e) {
+                SetError(e.what());
+            } catch(...) {
+                SetError("Unknown error when calling \"SampleToken\"");
+            }
+        }
+
+        void SampleToken() {
+            if (llama_get_logits(ctx->ctx) == nullptr) {
+                SetError("This model does not support token generation");
+                return;
+            }
+
+            sampler->rebuildChainIfNeeded();
+
+            const auto * logits = llama_get_logits_ith(ctx->ctx, batchLogitIndex);
+            const int n_vocab = llama_vocab_n_tokens(ctx->model->vocab);
+
+            auto & candidates = sampler->tokenCandidates;
+            for (llama_token token_id = 0; token_id < n_vocab; token_id++) {
+                candidates[token_id] = llama_token_data{token_id, logits[token_id], 0.0f};
+            }
+
+            llama_token_data_array cur_p = {
+                /* .data       = */ candidates.data(),
+                /* .size       = */ candidates.size(),
+                /* .selected   = */ -1,
+                /* .sorted     = */ false,
+            };
+
+            llama_sampler_apply(sampler->chain, &cur_p);
+
+            if (!(cur_p.selected >= 0 && cur_p.selected < (int32_t)cur_p.size)) {
+                no_output = true;
+                return;
+            }
+
+            auto new_token_id = cur_p.data[cur_p.selected].id;
+
+            if (returnProbabilities || returnConfidence) {
+                if (!cur_p.sorted) {
+                    std::sort(cur_p.data, cur_p.data + cur_p.size, [](const llama_token_data & a, const llama_token_data & b) {
+                        return a.logit > b.logit;
+                    });
+                    cur_p.sorted = true;
+
+                    for (size_t i = 0; i < cur_p.size; i++) {
+                        if (cur_p.data[i].id == new_token_id) {
+                            cur_p.selected = i;
+                            break;
+                        }
+                    }
+                }
+            }
+
+            if (returnProbabilities) {
+                probabilities_size = cur_p.size;
+                probabilities_tokens = new llama_token[probabilities_size];
+                probabilities_probs = new float[probabilities_size];
+                float maxLogit = cur_p.size > 0 ? cur_p.data[0].logit : -INFINITY;
+
+                for (size_t i = 0; i < cur_p.size; i++) {
+                    auto logit = cur_p.data[i].logit;
+
+                    probabilities_tokens[i] = cur_p.data[i].id;
+                    probabilities_probs[i] = logit;
+
+                    if (logit > maxLogit) {
+                        maxLogit = logit;
+                    }
+                }
+
+                if (probabilities_size > 0 && maxLogit != -INFINITY) {
+                    float sum = 0.0f;
+                    for (size_t i = 0; i < probabilities_size; i++) {
+                        float prob = expf(probabilities_probs[i] - maxLogit);
+                        probabilities_probs[i] = prob;
+                        sum += prob;
+                    }
+
+                    for (size_t i = 0; i < probabilities_size; i++) {
+                        probabilities_probs[i] /= sum;
+                    }
+                }
+
+                has_probabilities = true;
+            }
+
+            if (returnConfidence) {
+                if (has_probabilities && cur_p.selected < probabilities_size) {
+                    tokenConfidence = probabilities_probs[cur_p.selected];
+                } else {
+                    float maxLogit = cur_p.data[0].logit;
+                    float sum = 0.0f;
+                    for (size_t i = 0; i < cur_p.size; i++) {
+                        auto logit = cur_p.data[i].logit;
+
+                        if (logit > maxLogit) {
+                            maxLogit = logit;
+                        }
+                    }
+
+                    for (size_t i = 0; i < cur_p.size; i++) {
+                        sum += expf(cur_p.data[i].logit - maxLogit);
+                    }
+
+                    tokenConfidence = expf(cur_p.data[cur_p.selected].logit - maxLogit) / sum;
+                }
+            }
+
+            try {
+                sampler->acceptToken(new_token_id);
+                result = new_token_id;
+            } catch (const std::exception& e) {
+                SetError(std::string("Failed to accept token in sampler: ") + e.what());
+            } catch(...) {
+                SetError("Unknown error when calling \"acceptToken\"");
+            }
+        }
+        void OnOK() {
+            Napi::Number resultToken;
+            if (no_output) {
+                resultToken = Napi::Number::New(Env(), -1);
+            } else {
+                resultToken = Napi::Number::New(Env(), static_cast<uint32_t>(result));
+            }
+
+            if (!arrayResult) {
+                deferred.Resolve(resultToken);
+                return;
+            }
+
+            Napi::Array resultArray = Napi::Array::New(Env(), 2);
+            resultArray.Set(Napi::Number::New(Env(), 0), resultToken);
+
+            if (has_probabilities) {
+                Napi::Array probabilities = Napi::Array::New(Env(), probabilities_size * 2);
+                for (size_t i = 0; i < probabilities_size; i++) {
+                    probabilities.Set(i * 2, Napi::Number::New(Env(), probabilities_tokens[i]));
+                    probabilities.Set(i * 2 + 1, Napi::Number::New(Env(), probabilities_probs[i]));
+                }
+                resultArray.Set(1, probabilities);
+            }
+
+            if (returnConfidence && tokenConfidence != -1) {
+                resultArray.Set(2, Napi::Number::New(Env(), tokenConfidence));
+            }
+
+            deferred.Resolve(resultArray);
+        }
+        void OnError(const Napi::Error& err) {
+            deferred.Reject(err.Value());
+        }
+};
+
+AddonContext::AddonContext(const Napi::CallbackInfo& info) : Napi::ObjectWrap<AddonContext>(info) {
+    model = Napi::ObjectWrap<AddonModel>::Unwrap(info[0].As<Napi::Object>());
+    model->Ref();
+
+    context_params = llama_context_default_params();
+    context_params.n_ctx = 4096;
+    context_params.n_threads = std::max(cpu_get_num_math(), 1);
+    context_params.n_threads_batch = context_params.n_threads;
+    context_params.no_perf = true;
+    context_params.swa_full = false;
+
+    if (info.Length() > 1 && info[1].IsObject()) {
+        Napi::Object options = info[1].As<Napi::Object>();
+
+        if (options.Has("contextSize")) {
+            context_params.n_ctx = options.Get("contextSize").As<Napi::Number>().Uint32Value();
+        }
+
+        if (options.Has("batchSize")) {
+            context_params.n_batch = options.Get("batchSize").As<Napi::Number>().Uint32Value();
+            context_params.n_ubatch = context_params.n_batch; // the batch queue is managed in the JS side, so there's no need for managing it on the C++ side
+        }
+
+        if (options.Has("sequences")) {
+            context_params.n_seq_max = options.Get("sequences").As<Napi::Number>().Uint32Value();
+        }
+
+        if (options.Has("embeddings")) {
+            context_params.embeddings = options.Get("embeddings").As<Napi::Boolean>().Value();
+        }
+
+        if (options.Has("ranking") && options.Get("ranking").As<Napi::Boolean>().Value()) {
+            context_params.pooling_type = LLAMA_POOLING_TYPE_RANK;
+        }
+
+        if (options.Has("flashAttention")) {
+            bool flashAttention = options.Get("flashAttention").As<Napi::Boolean>().Value();
+            context_params.flash_attn_type = flashAttention ? LLAMA_FLASH_ATTN_TYPE_ENABLED : LLAMA_FLASH_ATTN_TYPE_DISABLED;
+        }
+
+        if (options.Has("threads")) {
+            const auto n_threads = options.Get("threads").As<Napi::Number>().Int32Value();
+            const auto resolved_n_threads = n_threads == 0 ? std::max((int32_t)std::thread::hardware_concurrency(), context_params.n_threads) : n_threads;
+
+            context_params.n_threads = resolved_n_threads;
+            context_params.n_threads_batch = resolved_n_threads;
+        }
+
+        if (options.Has("performanceTracking")) {
+            context_params.no_perf = !(options.Get("performanceTracking").As<Napi::Boolean>().Value());
+        }
+
+        if (options.Has("swaFullCache")) {
+            context_params.swa_full = options.Get("swaFullCache").As<Napi::Boolean>().Value();
+        }
+    }
+}
+AddonContext::~AddonContext() {
+    dispose();
+}
+
+void AddonContext::dispose() {
+    if (disposed) {
+        return;
+    }
+
+    disposed = true;
+    if (contextLoaded) {
+        contextLoaded = false;
+        llama_free(ctx);
+
+        adjustNapiExternalMemorySubtract(Env(), loadedContextMemorySize);
+        loadedContextMemorySize = 0;
+    }
+
+    model->Unref();
+
+    disposeBatch();
+}
+void AddonContext::disposeBatch() {
+    if (!has_batch) {
+        return;
+    }
+
+    llama_batch_free(batch);
+    has_batch = false;
+    batch_n_tokens = 0;
+
+    adjustNapiExternalMemorySubtract(Env(), batchMemorySize);
+    batchMemorySize = 0;
+}
+
+Napi::Value AddonContext::Init(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    AddonContextLoadContextWorker* worker = new AddonContextLoadContextWorker(this->Env(), this);
+    worker->Queue();
+    return worker->GetPromise();
+}
+Napi::Value AddonContext::Dispose(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        return info.Env().Undefined();
+    }
+
+    if (contextLoaded) {
+        contextLoaded = false;
+
+        AddonContextUnloadContextWorker* worker = new AddonContextUnloadContextWorker(this->Env(), this);
+        worker->Queue();
+        return worker->GetPromise();
+    } else {
+        dispose();
+
+        Napi::Promise::Deferred deferred = Napi::Promise::Deferred::New(info.Env());
+        deferred.Resolve(info.Env().Undefined());
+        return deferred.Promise();
+    }
+}
+
+Napi::Value AddonContext::GetContextSize(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    return Napi::Number::From(info.Env(), llama_n_ctx(ctx));
+}
+Napi::Value AddonContext::InitBatch(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    if (has_batch) {
+        llama_batch_free(batch);
+    }
+
+    int32_t n_tokens = info[0].As<Napi::Number>().Int32Value();
+
+    batch = llama_batch_init(n_tokens, 0, 1);
+    has_batch = true;
+    batch_n_tokens = n_tokens;
+
+    uint64_t newBatchMemorySize = calculateBatchMemorySize(n_tokens, llama_model_n_embd(model->model), context_params.n_batch);
+    if (newBatchMemorySize > batchMemorySize) {
+        adjustNapiExternalMemoryAdd(Env(), newBatchMemorySize - batchMemorySize);
+        batchMemorySize = newBatchMemorySize;
+    } else if (newBatchMemorySize < batchMemorySize) {
+        adjustNapiExternalMemorySubtract(Env(), batchMemorySize - newBatchMemorySize);
+        batchMemorySize = newBatchMemorySize;
+    }
+
+    return info.Env().Undefined();
+}
+Napi::Value AddonContext::DisposeBatch(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    disposeBatch();
+
+    return info.Env().Undefined();
+}
+Napi::Value AddonContext::AddToBatch(const Napi::CallbackInfo& info) {
+    if (!has_batch) {
+        Napi::Error::New(info.Env(), "No batch is initialized").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    int32_t sequenceId = info[0].As<Napi::Number>().Int32Value();
+    int32_t firstTokenContextIndex = info[1].As<Napi::Number>().Int32Value();
+    Napi::Uint32Array tokens = info[2].As<Napi::Uint32Array>();
+    Napi::Uint32Array tokenLogitIndexes = info[3].As<Napi::Uint32Array>();
+
+    auto tokensLength = tokens.ElementLength();
+    auto tokenLogitIndexesLength = tokenLogitIndexes.ElementLength();
+    GGML_ASSERT(batch.n_tokens + tokensLength <= batch_n_tokens);
+
+    Napi::Uint32Array resLogitIndexes = Napi::Uint32Array::New(info.Env(), tokenLogitIndexesLength);
+
+    for (size_t i = 0, l = 0; i < tokensLength; i++) {
+        if (l < tokenLogitIndexesLength && l < tokenLogitIndexesLength && tokenLogitIndexes[l] == i) {
+            common_batch_add(batch, static_cast<llama_token>(tokens[i]), firstTokenContextIndex + i, { sequenceId }, true);
+            resLogitIndexes[l] = batch.n_tokens - 1;
+            l++;
+        } else {
+            common_batch_add(batch, static_cast<llama_token>(tokens[i]), firstTokenContextIndex + i, { sequenceId }, false);
+        }
+    }
+
+    return resLogitIndexes;
+}
+Napi::Value AddonContext::DisposeSequence(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    int32_t sequenceId = info[0].As<Napi::Number>().Int32Value();
+
+    bool result = llama_memory_seq_rm(llama_get_memory(ctx), sequenceId, -1, -1);
+
+    if (!result) {
+        Napi::Error::New(info.Env(), "Failed to dispose sequence").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    return info.Env().Undefined();
+}
+Napi::Value AddonContext::RemoveTokenCellsFromSequence(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    int32_t sequenceId = info[0].As<Napi::Number>().Int32Value();
+    int32_t startPos = info[1].As<Napi::Number>().Int32Value();
+    int32_t endPos = info[2].As<Napi::Number>().Int32Value();
+
+    bool result = llama_memory_seq_rm(llama_get_memory(ctx), sequenceId, startPos, endPos);
+
+    return Napi::Boolean::New(info.Env(), result);
+}
+Napi::Value AddonContext::ShiftSequenceTokenCells(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    int32_t sequenceId = info[0].As<Napi::Number>().Int32Value();
+    int32_t startPos = info[1].As<Napi::Number>().Int32Value();
+    int32_t endPos = info[2].As<Napi::Number>().Int32Value();
+    int32_t shiftDelta = info[3].As<Napi::Number>().Int32Value();
+
+    llama_memory_seq_add(llama_get_memory(ctx), sequenceId, startPos, endPos, shiftDelta);
+
+    return info.Env().Undefined();
+}
+Napi::Value AddonContext::GetSequenceKvCacheMinPosition(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    int32_t sequenceId = info[0].As<Napi::Number>().Int32Value();
+
+
+    const auto minPosition = llama_memory_seq_pos_min(llama_get_memory(ctx), sequenceId);
+
+    return Napi::Number::New(info.Env(), minPosition);
+}
+Napi::Value AddonContext::GetSequenceKvCacheMaxPosition(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    int32_t sequenceId = info[0].As<Napi::Number>().Int32Value();
+
+
+    const auto maxPosition = llama_memory_seq_pos_max(llama_get_memory(ctx), sequenceId);
+
+    return Napi::Number::New(info.Env(), maxPosition);
+}
+Napi::Value AddonContext::DecodeBatch(const Napi::CallbackInfo& info) {
+    AddonContextDecodeBatchWorker* worker = new AddonContextDecodeBatchWorker(info.Env(), this);
+    worker->Queue();
+    return worker->GetPromise();
+}
+Napi::Value AddonContext::SampleToken(const Napi::CallbackInfo& info) {
+    AddonContextSampleTokenWorker* worker = new AddonContextSampleTokenWorker(info, this);
+    worker->Queue();
+    return worker->GetPromise();
+}
+
+Napi::Value AddonContext::GetEmbedding(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    int32_t inputTokensLength = info[0].As<Napi::Number>().Int32Value();
+    int32_t maxVectorSize = (info.Length() > 1 && info[1].IsNumber()) ? info[1].As<Napi::Number>().Int32Value() : 0;
+
+    if (inputTokensLength <= 0) {
+        Napi::Error::New(info.Env(), "Invalid input tokens length").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    const int n_embd = llama_model_n_embd(model->model);
+    const enum llama_pooling_type pooling_type = llama_pooling_type(ctx);
+    const auto* embeddings = pooling_type == LLAMA_POOLING_TYPE_NONE ? NULL : llama_get_embeddings_seq(ctx, 0);
+    if (embeddings == NULL) {
+        embeddings = llama_get_embeddings_ith(ctx, inputTokensLength - 1);
+    }
+
+    if (embeddings == NULL) {
+        Napi::Error::New(info.Env(), std::string("Failed to get embeddings for token ") + std::to_string(inputTokensLength - 1)).ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    size_t resultSize = maxVectorSize == 0 ? n_embd : std::min(n_embd, maxVectorSize);
+    Napi::Float64Array result = Napi::Float64Array::New(info.Env(), resultSize);
+    for (size_t i = 0; i < resultSize; i++) {
+        result[i] = embeddings[i];
+    }
+
+    return result;
+}
+
+Napi::Value AddonContext::GetStateSize(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    return Napi::Number::From(info.Env(), llama_state_get_size(ctx));
+}
+
+Napi::Value AddonContext::GetThreads(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    return Napi::Number::From(info.Env(), llama_n_threads(ctx));
+}
+
+Napi::Value AddonContext::SetThreads(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    const auto threads = info[0].As<Napi::Number>().Int32Value();
+    const auto resolvedThreads = threads == 0
+        ? std::max((int32_t)std::thread::hardware_concurrency(), std::max(cpu_get_num_math(), 1))
+        : threads;
+
+    if (llama_n_threads(ctx) != resolvedThreads) {
+        llama_set_n_threads(ctx, resolvedThreads, resolvedThreads);
+    }
+
+    return info.Env().Undefined();
+}
+
+class AddonContextSaveSequenceStateToFileWorker : public Napi::AsyncWorker {
+    public:
+        AddonContext* context;
+        std::string filepath;
+        llama_seq_id sequenceId;
+        std::vector<llama_token> tokens;
+        size_t savedFileSize = 0;
+
+        AddonContextSaveSequenceStateToFileWorker(const Napi::CallbackInfo& info, AddonContext* context)
+            : Napi::AsyncWorker(info.Env(), "AddonContextSaveSequenceStateToFileWorker"),
+              context(context),
+              deferred(Napi::Promise::Deferred::New(info.Env())) {
+            context->Ref();
+
+            filepath = info[0].As<Napi::String>().Utf8Value();
+            sequenceId = info[1].As<Napi::Number>().Int32Value();
+            Napi::Uint32Array inputTokens = info[2].As<Napi::Uint32Array>();
+
+            tokens.resize(inputTokens.ElementLength());
+            for (size_t i = 0; i < tokens.size(); i++) {
+                tokens[i] = inputTokens[i];
+            }
+        }
+        ~AddonContextSaveSequenceStateToFileWorker() {
+            context->Unref();
+        }
+
+        Napi::Promise GetPromise() {
+            return deferred.Promise();
+        }
+
+    protected:
+        Napi::Promise::Deferred deferred;
+
+        void Execute() {
+            try {
+                savedFileSize = llama_state_seq_save_file(context->ctx, filepath.c_str(), sequenceId, tokens.data(), tokens.size());
+                if (savedFileSize == 0) {
+                    SetError("Failed to save state to file");
+                    return;
+                }
+            } catch (const std::exception& e) {
+                SetError(e.what());
+            } catch(...) {
+                SetError("Unknown error when calling \"llama_state_seq_save_file\"");
+            }
+        }
+        void OnOK() {
+            deferred.Resolve(Napi::Number::New(Env(), savedFileSize));
+        }
+        void OnError(const Napi::Error& err) {
+            deferred.Reject(err.Value());
+        }
+};
+Napi::Value AddonContext::SaveSequenceStateToFile(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    AddonContextSaveSequenceStateToFileWorker* worker = new AddonContextSaveSequenceStateToFileWorker(info, this);
+    worker->Queue();
+    return worker->GetPromise();
+}
+
+class AddonContextLoadSequenceStateFromFileWorker : public Napi::AsyncWorker {
+    public:
+        AddonContext* context;
+        std::string filepath;
+        llama_seq_id sequenceId;
+        size_t maxContextSize;
+        std::vector<llama_token> tokens;
+
+        AddonContextLoadSequenceStateFromFileWorker(const Napi::CallbackInfo& info, AddonContext* context)
+            : Napi::AsyncWorker(info.Env(), "AddonContextLoadSequenceStateFromFileWorker"),
+              context(context),
+              deferred(Napi::Promise::Deferred::New(info.Env())) {
+            context->Ref();
+
+            filepath = info[0].As<Napi::String>().Utf8Value();
+            sequenceId = info[1].As<Napi::Number>().Int32Value();
+            maxContextSize = info[2].As<Napi::Number>().Uint32Value();
+
+            tokens.resize(maxContextSize);
+        }
+        ~AddonContextLoadSequenceStateFromFileWorker() {
+            context->Unref();
+        }
+
+        Napi::Promise GetPromise() {
+            return deferred.Promise();
+        }
+
+    protected:
+        Napi::Promise::Deferred deferred;
+
+        void Execute() {
+            try {
+                size_t tokenCount = 0;
+                const size_t fileSize = llama_state_seq_load_file(context->ctx, filepath.c_str(), sequenceId, tokens.data(), tokens.size(), &tokenCount);
+                if (fileSize == 0) {
+                    SetError("Failed to load state from file. Current context sequence size may be smaller that the state of the file");
+                    return;
+                }
+
+                tokens.resize(tokenCount);
+            } catch (const std::exception& e) {
+                SetError(e.what());
+            } catch(...) {
+                SetError("Unknown error when calling \"llama_state_seq_load_file\"");
+            }
+        }
+        void OnOK() {
+            size_t tokenCount = tokens.size();
+            Napi::Uint32Array result = Napi::Uint32Array::New(Env(), tokenCount);
+
+            for (size_t i = 0; i < tokenCount; i++) {
+                result[i] = tokens[i];
+            }
+
+            deferred.Resolve(result);
+        }
+        void OnError(const Napi::Error& err) {
+            deferred.Reject(err.Value());
+        }
+};
+Napi::Value AddonContext::LoadSequenceStateFromFile(const Napi::CallbackInfo& info) {
+    if (disposed) {
+        Napi::Error::New(info.Env(), "Context is disposed").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    AddonContextLoadSequenceStateFromFileWorker* worker = new AddonContextLoadSequenceStateFromFileWorker(info, this);
+    worker->Queue();
+    return worker->GetPromise();
+}
+
+Napi::Value AddonContext::PrintTimings(const Napi::CallbackInfo& info) {
+    llama_perf_context_print(ctx);
+    llama_perf_context_reset(ctx);
+    return info.Env().Undefined();
+}
+
+Napi::Value AddonContext::EnsureDraftContextIsCompatibleForSpeculative(const Napi::CallbackInfo& info) {
+    constexpr auto vocabSizeMaxDifference = 128; // SPEC_VOCAB_MAX_SIZE_DIFFERENCE
+    constexpr auto vocabCheckStartTokenId = 5; // SPEC_VOCAB_CHECK_START_TOKEN_ID
+
+    const AddonContext * draftContext = Napi::ObjectWrap<AddonContext>::Unwrap(info[0].As<Napi::Object>());
+    const auto currentCtx = ctx;
+    const auto draftCtx = draftContext->ctx;
+    const auto currentModel = model->model;
+    const auto draftModel = draftContext->model->model;
+    const auto currentVocab = model->vocab;
+    const auto draftVocab = draftContext->model->vocab;
+
+    if (llama_vocab_type(currentVocab) != llama_vocab_type(draftVocab)) {
+        Napi::Error::New(info.Env(), "Speculative draft model vocabulary type must match the target model vocabulary type").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    if (llama_vocab_get_add_bos(currentVocab) != llama_vocab_get_add_bos(draftVocab) ||
+        llama_vocab_get_add_eos(currentVocab) != llama_vocab_get_add_eos(draftVocab) ||
+        llama_vocab_bos(currentVocab) != llama_vocab_bos(draftVocab) ||
+        llama_vocab_eos(currentVocab) != llama_vocab_eos(draftVocab)
+    ) {
+        Napi::Error::New(info.Env(), "Speculative draft model special tokens must match the target model special tokens").ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    const int currentModelVocabSize = llama_vocab_n_tokens(currentVocab);
+    const int draftModelVocabSize = llama_vocab_n_tokens(draftVocab);
+
+    const int vocabDiff = std::abs(currentModelVocabSize - draftModelVocabSize);
+
+    if (vocabDiff > vocabSizeMaxDifference) {
+        Napi::Error::New(
+            info.Env(),
+            std::string("Speculative draft model vocabulary must closely match the target model vocabulary size (vocabulary size difference: ") +
+            std::to_string(vocabDiff) + std::string(", max allowed: ") + std::to_string(vocabSizeMaxDifference) + std::string(")")
+        ).ThrowAsJavaScriptException();
+        return info.Env().Undefined();
+    }
+
+    const int minVocabSize = std::min(currentModelVocabSize, draftModelVocabSize);
+    for (int i = vocabCheckStartTokenId; i < minVocabSize; ++i) {
+        const char * currentTokenText = llama_vocab_get_text(currentVocab, i);
+        const char * draftTokenText = llama_vocab_get_text(draftVocab, i);
+        if (std::strcmp(currentTokenText, draftTokenText) != 0) {
+            Napi::Error::New(
+                info.Env(),
+                std::string("Speculative draft model vocabulary must match the target model vocabulary, but token ") +
+                std::to_string(i) + std::string(" content differs. Target: \"") + std::string(currentTokenText) +
+                std::string("\", Draft: \"") + std::string(draftTokenText) + std::string("")
+            ).ThrowAsJavaScriptException();
+            return info.Env().Undefined();
+        }
+    }
+
+    return info.Env().Undefined();
+}
+
+Napi::Value AddonContext::SetLora(const Napi::CallbackInfo& info) {
+    AddonModelLora* lora = Napi::ObjectWrap<AddonModelLora>::Unwrap(info[0].As<Napi::Object>());
+    float scale = info[1].As<Napi::Number>().FloatValue();
+
+    llama_set_adapter_lora(ctx, lora->lora_adapter, scale);
+
+    return info.Env().Undefined();
+}
+
+void AddonContext::init(Napi::Object exports) {
+    exports.Set(
+        "AddonContext",
+        DefineClass(
+            exports.Env(),
+            "AddonContext",
+            {
+                InstanceMethod("init", &AddonContext::Init),
+                InstanceMethod("getContextSize", &AddonContext::GetContextSize),
+                InstanceMethod("initBatch", &AddonContext::InitBatch),
+                InstanceMethod("addToBatch", &AddonContext::AddToBatch),
+                InstanceMethod("disposeSequence", &AddonContext::DisposeSequence),
+                InstanceMethod("removeTokenCellsFromSequence", &AddonContext::RemoveTokenCellsFromSequence),
+                InstanceMethod("shiftSequenceTokenCells", &AddonContext::ShiftSequenceTokenCells),
+                InstanceMethod("getSequenceKvCacheMinPosition", &AddonContext::GetSequenceKvCacheMinPosition),
+                InstanceMethod("getSequenceKvCacheMaxPosition", &AddonContext::GetSequenceKvCacheMaxPosition),
+                InstanceMethod("decodeBatch", &AddonContext::DecodeBatch),
+                InstanceMethod("sampleToken", &AddonContext::SampleToken),
+                InstanceMethod("getEmbedding", &AddonContext::GetEmbedding),
+                InstanceMethod("getStateSize", &AddonContext::GetStateSize),
+                InstanceMethod("getThreads", &AddonContext::GetThreads),
+                InstanceMethod("setThreads", &AddonContext::SetThreads),
+                InstanceMethod("printTimings", &AddonContext::PrintTimings),
+                InstanceMethod("ensureDraftContextIsCompatibleForSpeculative", &AddonContext::EnsureDraftContextIsCompatibleForSpeculative),
+                InstanceMethod("saveSequenceStateToFile", &AddonContext::SaveSequenceStateToFile),
+                InstanceMethod("loadSequenceStateFromFile", &AddonContext::LoadSequenceStateFromFile),
+                InstanceMethod("setLora", &AddonContext::SetLora),
+                InstanceMethod("dispose", &AddonContext::Dispose),
+            }
+        )
+    );
+}