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chat: major UI redesign for v3.0.0 (#2396)

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Signed-off-by: Adam Treat <treat.adam@gmail.com>
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
Co-authored-by: Jared Van Bortel <jared@nomic.ai>
This commit is contained in:
AT
2024-06-24 18:49:23 -04:00
committed by GitHub
parent 1272b694ae
commit 9273b49b62
111 changed files with 8540 additions and 7879 deletions
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72
gpt4all-backend/llamamodel.cpp
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@@ -84,16 +84,19 @@ static const std::vector<const char *> EMBEDDING_ARCHES {
"bert", "nomic-bert",
};
static bool is_embedding_arch(const std::string &arch) {
static bool is_embedding_arch(const std::string &arch)
{
return std::find(EMBEDDING_ARCHES.begin(), EMBEDDING_ARCHES.end(), arch) < EMBEDDING_ARCHES.end();
}
static bool llama_verbose() {
static bool llama_verbose()
{
const char* var = getenv("GPT4ALL_VERBOSE_LLAMACPP");
return var && *var;
}
static void llama_log_callback(enum ggml_log_level level, const char *text, void *userdata) {
static void llama_log_callback(enum ggml_log_level level, const char *text, void *userdata)
{
(void)userdata;
if (llama_verbose() || level <= GGML_LOG_LEVEL_ERROR) {
fputs(text, stderr);
@@ -147,7 +150,8 @@ static int llama_sample_top_p_top_k(
return llama_sample_token(ctx, &candidates_p);
}
const char *get_arch_name(gguf_context *ctx_gguf) {
const char *get_arch_name(gguf_context *ctx_gguf)
{
const int kid = gguf_find_key(ctx_gguf, "general.architecture");
if (kid == -1)
throw std::runtime_error("key not found in model: general.architecture");
@@ -159,7 +163,8 @@ const char *get_arch_name(gguf_context *ctx_gguf) {
return gguf_get_val_str(ctx_gguf, kid);
}
static gguf_context *load_gguf(const char *fname) {
static gguf_context *load_gguf(const char *fname)
{
struct gguf_init_params params = {
/*.no_alloc = */ true,
/*.ctx = */ nullptr,
@@ -180,7 +185,8 @@ static gguf_context *load_gguf(const char *fname) {
return ctx;
}
static int32_t get_arch_key_u32(std::string const &modelPath, std::string const &archKey) {
static int32_t get_arch_key_u32(std::string const &modelPath, std::string const &archKey)
{
int32_t value = -1;
std::string arch;
@@ -237,7 +243,8 @@ struct llama_file_hparams {
enum llama_ftype ftype = LLAMA_FTYPE_MOSTLY_F16;
};
size_t LLamaModel::requiredMem(const std::string &modelPath, int n_ctx, int ngl) {
size_t LLamaModel::requiredMem(const std::string &modelPath, int n_ctx, int ngl)
{
// TODO(cebtenzzre): update to GGUF
(void)ngl; // FIXME(cetenzzre): use this value
auto fin = std::ifstream(modelPath, std::ios::binary);
@@ -261,7 +268,8 @@ size_t LLamaModel::requiredMem(const std::string &modelPath, int n_ctx, int ngl)
return filesize + est_kvcache_size;
}
bool LLamaModel::isModelBlacklisted(const std::string &modelPath) const {
bool LLamaModel::isModelBlacklisted(const std::string &modelPath) const
{
auto * ctx = load_gguf(modelPath.c_str());
if (!ctx) {
std::cerr << __func__ << ": failed to load " << modelPath << "\n";
@@ -297,7 +305,8 @@ bool LLamaModel::isModelBlacklisted(const std::string &modelPath) const {
return res;
}
bool LLamaModel::isEmbeddingModel(const std::string &modelPath) const {
bool LLamaModel::isEmbeddingModel(const std::string &modelPath) const
{
bool result = false;
std::string arch;
@@ -453,12 +462,14 @@ bool LLamaModel::loadModel(const std::string &modelPath, int n_ctx, int ngl)
return true;
}
void LLamaModel::setThreadCount(int32_t n_threads) {
void LLamaModel::setThreadCount(int32_t n_threads)
{
d_ptr->n_threads = n_threads;
llama_set_n_threads(d_ptr->ctx, n_threads, n_threads);
}
int32_t LLamaModel::threadCount() const {
int32_t LLamaModel::threadCount() const
{
return d_ptr->n_threads;
}
@@ -581,7 +592,8 @@ int32_t LLamaModel::layerCount(std::string const &modelPath) const
}
#ifdef GGML_USE_VULKAN
static const char *getVulkanVendorName(uint32_t vendorID) {
static const char *getVulkanVendorName(uint32_t vendorID)
{
switch (vendorID) {
case 0x10DE: return "nvidia";
case 0x1002: return "amd";
@@ -738,11 +750,13 @@ bool LLamaModel::usingGPUDevice() const
return hasDevice;
}
const char *LLamaModel::backendName() const {
const char *LLamaModel::backendName() const
{
return d_ptr->backend_name;
}
const char *LLamaModel::gpuDeviceName() const {
const char *LLamaModel::gpuDeviceName() const
{
if (usingGPUDevice()) {
#if defined(GGML_USE_KOMPUTE) || defined(GGML_USE_VULKAN) || defined(GGML_USE_CUDA)
return d_ptr->deviceName.c_str();
@@ -768,13 +782,15 @@ void llama_batch_add(
batch.n_tokens++;
}
static void batch_add_seq(llama_batch &batch, const std::vector<LLModel::Token> &tokens, int seq_id) {
static void batch_add_seq(llama_batch &batch, const std::vector<LLModel::Token> &tokens, int seq_id)
{
for (unsigned i = 0; i < tokens.size(); i++) {
llama_batch_add(batch, tokens[i], i, { seq_id }, i == tokens.size() - 1);
}
}
size_t LLamaModel::embeddingSize() const {
size_t LLamaModel::embeddingSize() const
{
return llama_n_embd(d_ptr->model);
}
@@ -894,12 +910,14 @@ void LLamaModel::embed(
// MD5 hash of "nomic empty"
static const char EMPTY_PLACEHOLDER[] = "24df574ea1c998de59d5be15e769658e";
auto product(double a) -> std::function<double(double)> {
auto product(double a) -> std::function<double(double)>
{
return [a](double b) { return a * b; };
}
template <typename T>
double getL2NormScale(T *start, T *end) {
double getL2NormScale(T *start, T *end)
{
double magnitude = std::sqrt(std::inner_product(start, end, start, 0.0));
return 1.0 / std::max(magnitude, 1e-12);
}
@@ -1107,19 +1125,23 @@ void LLamaModel::embedInternal(
#endif
extern "C" {
DLL_EXPORT bool is_g4a_backend_model_implementation() {
DLL_EXPORT bool is_g4a_backend_model_implementation()
{
return true;
}
DLL_EXPORT const char *get_model_type() {
DLL_EXPORT const char *get_model_type()
{
return modelType_;
}
DLL_EXPORT const char *get_build_variant() {
DLL_EXPORT const char *get_build_variant()
{
return GGML_BUILD_VARIANT;
}
DLL_EXPORT char *get_file_arch(const char *fname) {
DLL_EXPORT char *get_file_arch(const char *fname)
{
char *arch = nullptr;
std::string archStr;
@@ -1144,11 +1166,13 @@ cleanup:
return arch;
}
DLL_EXPORT bool is_arch_supported(const char *arch) {
DLL_EXPORT bool is_arch_supported(const char *arch)
{
return std::find(KNOWN_ARCHES.begin(), KNOWN_ARCHES.end(), std::string(arch)) < KNOWN_ARCHES.end();
}
DLL_EXPORT LLModel *construct() {
DLL_EXPORT LLModel *construct()
{
llama_log_set(llama_log_callback, nullptr);
return new LLamaModel;
}