mirror of
https://github.com/LostRuins/koboldcpp.git
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Merge branch 'upstream' into concedo_experimental
# Conflicts: # .github/workflows/build.yml # README.md # examples/CMakeLists.txt # examples/batched/batched.cpp # examples/gritlm/gritlm.cpp # examples/llama.android/llama/build.gradle.kts # examples/main/README.md # examples/retrieval/retrieval.cpp # examples/server/CMakeLists.txt # examples/server/README.md # ggml/CMakeLists.txt # ggml/src/ggml-cpu/CMakeLists.txt # ggml/src/ggml.c # scripts/compare-commits.sh # scripts/sync-ggml.last # tests/CMakeLists.txt # tests/test-backend-ops.cpp # tests/test-chat-template.cpp # tests/test-sampling.cpp
This commit is contained in:
Concedo
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@@ -39,7 +39,6 @@
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temperature: 0.8, // adapt all following parameters to optimized min-p requierements. If for non-english, set to 0.6 or lower
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repeat_last_n: 0, // 0 = disable penalty, -1 = context size
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repeat_penalty: 1.0, // 1.0 = disabled
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penalize_nl: false, // true only useful for infinite completion
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dry_multiplier: 0.0, // 0.0 = disabled, 0.8 works well
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dry_base: 1.75, // 0.0 = disabled
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dry_allowed_length: 2, // tokens extending repetitions beyond this receive penalty, 2 works well
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@@ -303,7 +303,6 @@
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temperature: 0.7,
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repeat_last_n: 256, // 0 = disable penalty, -1 = context size
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repeat_penalty: 1.18, // 1.0 = disabled
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penalize_nl: false,
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dry_multiplier: 0.0, // 0.0 = disabled, 0.8 works well
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dry_base: 1.75, // 0.0 = disabled
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dry_allowed_length: 2, // tokens extending repetitions beyond this receive penalty, 2 works well
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@@ -1006,7 +1005,6 @@
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${FloatField({ label: "Temperature", max: 2.0, min: 0.0, name: "temperature", step: 0.01, value: params.value.temperature })}
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${FloatField({ label: "Penalize repeat sequence", max: 2.0, min: 0.0, name: "repeat_penalty", step: 0.01, value: params.value.repeat_penalty })}
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${IntField({ label: "Consider N tokens for penalize", max: 2048, min: 0, name: "repeat_last_n", value: params.value.repeat_last_n })}
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${BoolField({ label: "Penalize repetition of newlines", name: "penalize_nl", value: params.value.penalize_nl })}
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${IntField({ label: "Top-K sampling", max: 100, min: -1, name: "top_k", value: params.value.top_k })}
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${FloatField({ label: "Top-P sampling", max: 1.0, min: 0.0, name: "top_p", step: 0.01, value: params.value.top_p })}
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${FloatField({ label: "Min-P sampling", max: 1.0, min: 0.0, name: "min_p", step: 0.01, value: params.value.min_p })}
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+135
-40
@@ -15,7 +15,7 @@
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#define MIMETYPE_JSON "application/json; charset=utf-8"
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// auto generated files (update with ./deps.sh)
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#include "index.html.hpp"
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#include "index.html.gz.hpp"
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#include "loading.html.hpp"
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#include <atomic>
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@@ -79,8 +79,9 @@ enum error_type {
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};
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struct slot_params {
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bool stream = true;
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bool cache_prompt = true; // remember the prompt to avoid reprocessing all prompt
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bool stream = true;
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bool cache_prompt = true; // remember the prompt to avoid reprocessing all prompt
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bool return_tokens = false;
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int32_t n_keep = 0; // number of tokens to keep from initial prompt
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int32_t n_discard = 0; // number of tokens after n_keep that may be discarded when shifting context, 0 defaults to half
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@@ -135,7 +136,6 @@ struct slot_params {
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{"mirostat", sampling.mirostat},
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{"mirostat_tau", sampling.mirostat_tau},
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{"mirostat_eta", sampling.mirostat_eta},
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{"penalize_nl", sampling.penalize_nl},
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{"stop", antiprompt},
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{"max_tokens", n_predict}, // User configured n_predict
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{"n_keep", n_keep},
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@@ -184,6 +184,7 @@ struct server_task {
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static slot_params params_from_json_cmpl(
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const llama_model * model,
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const llama_context * ctx,
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const common_params & params_base,
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const json & data) {
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slot_params params;
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@@ -199,6 +200,7 @@ struct server_task {
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params.stream = json_value(data, "stream", false);
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params.cache_prompt = json_value(data, "cache_prompt", true);
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params.return_tokens = json_value(data, "return_tokens", false);
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params.n_predict = json_value(data, "n_predict", json_value(data, "max_tokens", defaults.n_predict));
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params.n_indent = json_value(data, "n_indent", defaults.n_indent);
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params.n_keep = json_value(data, "n_keep", defaults.n_keep);
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@@ -226,7 +228,6 @@ struct server_task {
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params.sampling.mirostat = json_value(data, "mirostat", defaults.sampling.mirostat);
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params.sampling.mirostat_tau = json_value(data, "mirostat_tau", defaults.sampling.mirostat_tau);
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params.sampling.mirostat_eta = json_value(data, "mirostat_eta", defaults.sampling.mirostat_eta);
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params.sampling.penalize_nl = json_value(data, "penalize_nl", defaults.sampling.penalize_nl);
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params.sampling.seed = json_value(data, "seed", defaults.sampling.seed);
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params.sampling.n_probs = json_value(data, "n_probs", defaults.sampling.n_probs);
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params.sampling.min_keep = json_value(data, "min_keep", defaults.sampling.min_keep);
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@@ -239,8 +240,27 @@ struct server_task {
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params.speculative.n_min = std::max(params.speculative.n_min, 2);
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params.speculative.n_max = std::max(params.speculative.n_max, 0);
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// TODO: add more sanity checks for the input parameters
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if (params.sampling.penalty_last_n < -1) {
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throw std::runtime_error("Error: repeat_last_n must be >= -1");
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}
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if (params.sampling.dry_penalty_last_n < -1) {
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throw std::runtime_error("Error: dry_penalty_last_n must be >= -1");
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}
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if (params.sampling.penalty_last_n == -1) {
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// note: should be the slot's context and not the full context, but it's ok
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params.sampling.penalty_last_n = llama_n_ctx(ctx);
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}
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if (params.sampling.dry_penalty_last_n == -1) {
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params.sampling.dry_penalty_last_n = llama_n_ctx(ctx);
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}
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if (params.sampling.dry_base < 1.0f) {
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params.sampling.dry_base = defaults.sampling.dry_base;
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params.sampling.dry_base = defaults.sampling.dry_base;
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}
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// sequence breakers for DRY
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@@ -450,7 +470,10 @@ struct completion_token_output {
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struct server_task_result_cmpl_final : server_task_result {
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int index = 0;
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std::string content;
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std::string content;
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llama_tokens tokens;
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bool stream;
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result_timings timings;
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std::string prompt;
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@@ -492,6 +515,7 @@ struct server_task_result_cmpl_final : server_task_result {
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json res = json {
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{"index", index},
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{"content", stream ? "" : content}, // in stream mode, content is already in last partial chunk
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{"tokens", stream ? llama_tokens {} : tokens},
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{"id_slot", id_slot},
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{"stop", true},
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{"model", oaicompat_model},
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@@ -521,9 +545,9 @@ struct server_task_result_cmpl_final : server_task_result {
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json choices = json::array({json{
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{"finish_reason", finish_reason},
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{"index", 0},
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{"message", json{
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{"message", json {
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{"content", content},
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{"role", "assistant"}
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{"role", "assistant"}
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}
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}}});
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@@ -587,7 +611,9 @@ struct server_task_result_cmpl_final : server_task_result {
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struct server_task_result_cmpl_partial : server_task_result {
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int index = 0;
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std::string content;
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std::string content;
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llama_tokens tokens;
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int32_t n_decoded;
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int32_t n_prompt_tokens;
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@@ -619,6 +645,7 @@ struct server_task_result_cmpl_partial : server_task_result {
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json res = json {
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{"index", index},
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{"content", content},
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{"tokens", tokens},
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{"stop", false},
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{"id_slot", id_slot},
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{"tokens_predicted", n_decoded},
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@@ -660,7 +687,7 @@ struct server_task_result_cmpl_partial : server_task_result {
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json second_ret = json{
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{"choices", json::array({json{{"finish_reason", nullptr},
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{"index", 0},
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{"delta", json{
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{"delta", json {
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{"content", content}}}
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}})},
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{"created", t},
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@@ -675,7 +702,7 @@ struct server_task_result_cmpl_partial : server_task_result {
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{"finish_reason", nullptr},
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{"index", 0},
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{"delta",
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json{
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json {
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{"content", content},
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}},
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}});
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@@ -699,32 +726,52 @@ struct server_task_result_cmpl_partial : server_task_result {
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struct server_task_result_embd : server_task_result {
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int index = 0;
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std::vector<float> embedding;
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std::vector<std::vector<float>> embedding;
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int32_t n_tokens;
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// OAI-compat fields
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bool oaicompat = false;
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virtual int get_index() override {
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return index;
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}
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virtual json to_json() override {
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return oaicompat ? to_json_oaicompat() : to_json_non_oaicompat();
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}
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json to_json_non_oaicompat() {
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return json {
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{"index", index},
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{"embedding", embedding},
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};
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}
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json to_json_oaicompat() {
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return json {
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{"index", index},
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{"embedding", embedding[0]},
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{"tokens_evaluated", n_tokens},
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};
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}
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};
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struct server_task_result_rerank : server_task_result {
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int index = 0;
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float score = -1e6;
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int32_t n_tokens;
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virtual int get_index() override {
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return index;
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}
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virtual json to_json() override {
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return json {
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{"index", index},
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{"score", score},
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{"index", index},
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{"score", score},
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{"tokens_evaluated", n_tokens},
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};
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}
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};
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@@ -931,8 +978,11 @@ struct server_slot {
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size_t last_nl_pos = 0;
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std::string generated_text;
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std::string generated_text;
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llama_tokens generated_tokens;
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llama_tokens cache_tokens;
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std::vector<completion_token_output> generated_token_probs;
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bool has_next_token = true;
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@@ -976,6 +1026,7 @@ struct server_slot {
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n_sent_token_probs = 0;
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task_type = SERVER_TASK_TYPE_COMPLETION;
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generated_tokens.clear();
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generated_token_probs.clear();
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}
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@@ -1469,7 +1520,7 @@ struct server_context {
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n_ctx = llama_n_ctx(ctx);
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add_bos_token = llama_add_bos_token(model);
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has_eos_token = !llama_add_eos_token(model);
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has_eos_token = llama_token_eos(model) != LLAMA_TOKEN_NULL;
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if (!params_base.speculative.model.empty()) {
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SRV_INF("loading draft model '%s'\n", params_base.speculative.model.c_str());
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@@ -1716,8 +1767,10 @@ struct server_context {
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const std::string token_str = common_token_to_piece(ctx, result.tok, params_base.special);
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slot.sampled = result.tok;
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// search stop word and delete it
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slot.generated_text += token_str;
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if (slot.params.return_tokens) {
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slot.generated_tokens.push_back(result.tok);
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}
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slot.has_next_token = true;
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// check if there is incomplete UTF-8 character at the end
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@@ -1742,6 +1795,7 @@ struct server_context {
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break;
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}
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// search stop word and delete it
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if (!incomplete) {
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size_t pos = std::min(slot.n_sent_text, slot.generated_text.size());
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@@ -1894,6 +1948,7 @@ struct server_context {
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res->id = slot.id_task;
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res->index = slot.index;
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res->content = tkn.text_to_send;
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res->tokens = { tkn.tok };
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res->n_decoded = slot.n_decoded;
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res->n_prompt_tokens = slot.n_prompt_tokens;
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@@ -1934,6 +1989,7 @@ struct server_context {
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res->index = slot.index;
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res->content = slot.generated_text;
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res->tokens = slot.generated_tokens;
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res->timings = slot.get_timings();
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res->prompt = common_detokenize(ctx, slot.prompt_tokens, true);
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@@ -1975,8 +2031,10 @@ struct server_context {
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void send_embedding(const server_slot & slot, const llama_batch & batch) {
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auto res = std::make_unique<server_task_result_embd>();
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res->id = slot.id_task;
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res->index = slot.index;
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res->id = slot.id_task;
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res->index = slot.index;
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res->n_tokens = slot.n_prompt_tokens;
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res->oaicompat = slot.params.oaicompat;
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const int n_embd = llama_n_embd(model);
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@@ -1995,12 +2053,18 @@ struct server_context {
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if (embd == NULL) {
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SLT_ERR(slot, "failed to get embeddings, token = %d, seq_id = %d\n", batch.token[i], batch.seq_id[i][0]);
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res->embedding = std::vector<float>(n_embd, 0.0f);
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res->embedding.push_back(std::vector<float>(n_embd, 0.0f));
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continue;
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}
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common_embd_normalize(embd, embd_res.data(), n_embd);
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res->embedding = embd_res;
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// normalize only when there is pooling
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// TODO: configurable
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if (llama_pooling_type(slot.ctx) != LLAMA_POOLING_TYPE_NONE) {
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common_embd_normalize(embd, embd_res.data(), n_embd, 2);
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res->embedding.push_back(embd_res);
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} else {
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res->embedding.push_back({ embd, embd + n_embd });
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}
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}
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SLT_DBG(slot, "%s", "sending embeddings\n");
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@@ -2012,6 +2076,7 @@ struct server_context {
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auto res = std::make_unique<server_task_result_rerank>();
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res->id = slot.id_task;
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res->index = slot.index;
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res->n_tokens = slot.n_prompt_tokens;
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for (int i = 0; i < batch.n_tokens; ++i) {
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if (!batch.logits[i] || batch.seq_id[i][0] != slot.id) {
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@@ -2613,7 +2678,10 @@ struct server_context {
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// add prompt tokens for processing in the current batch
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while (slot.n_past < slot.n_prompt_tokens && batch.n_tokens < n_batch) {
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common_batch_add(batch, prompt_tokens[slot.n_past], slot.n_past, { slot.id }, false);
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// without pooling, we want to output the embeddings for all the tokens in the batch
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const bool need_embd = slot.task_type == SERVER_TASK_TYPE_EMBEDDING && llama_pooling_type(slot.ctx) == LLAMA_POOLING_TYPE_NONE;
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common_batch_add(batch, prompt_tokens[slot.n_past], slot.n_past, { slot.id }, need_embd);
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if (slot.params.cache_prompt) {
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slot.cache_tokens.push_back(prompt_tokens[slot.n_past]);
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@@ -3381,7 +3449,7 @@ int main(int argc, char ** argv) {
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task.index = i;
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task.prompt_tokens = std::move(tokenized_prompts[i]);
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task.params = server_task::params_from_json_cmpl(ctx_server.model, ctx_server.params_base, data);
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task.params = server_task::params_from_json_cmpl(ctx_server.model, ctx_server.ctx, ctx_server.params_base, data);
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task.id_selected_slot = json_value(data, "id_slot", -1);
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// OAI-compat
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@@ -3621,34 +3689,50 @@ int main(int argc, char ** argv) {
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res_ok(res, data);
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};
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const auto handle_embeddings = [&ctx_server, &res_error, &res_ok](const httplib::Request & req, httplib::Response & res) {
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const auto handle_embeddings_impl = [&ctx_server, &res_error, &res_ok](const httplib::Request & req, httplib::Response & res, bool oaicompat) {
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const json body = json::parse(req.body);
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bool oaicompat = false;
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// an input prompt can be a string or a list of tokens (integer)
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if (oaicompat && llama_pooling_type(ctx_server.ctx) == LLAMA_POOLING_TYPE_NONE) {
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res_error(res, format_error_response("Pooling type 'none' is not OAI compatible. Please use a different pooling type", ERROR_TYPE_INVALID_REQUEST));
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return;
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}
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// for the shape of input/content, see tokenize_input_prompts()
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json prompt;
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if (body.count("input") != 0) {
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oaicompat = true;
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prompt = body.at("input");
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} else if (body.count("content") != 0) {
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// with "content", we only support single prompt
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prompt = std::vector<std::string>{body.at("content")};
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} else if (body.contains("content")) {
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oaicompat = false;
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prompt = body.at("content");
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} else {
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res_error(res, format_error_response("\"input\" or \"content\" must be provided", ERROR_TYPE_INVALID_REQUEST));
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return;
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}
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||||
std::vector<llama_tokens> tokenized_prompts = tokenize_input_prompts(ctx_server.ctx, prompt, true, true);
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for (const auto & tokens : tokenized_prompts) {
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// this check is necessary for models that do not add BOS token to the input
|
||||
if (tokens.empty()) {
|
||||
res_error(res, format_error_response("Input content cannot be empty", ERROR_TYPE_INVALID_REQUEST));
|
||||
return;
|
||||
}
|
||||
}
|
||||
|
||||
// create and queue the task
|
||||
json responses = json::array();
|
||||
bool error = false;
|
||||
{
|
||||
std::vector<server_task> tasks;
|
||||
std::vector<llama_tokens> tokenized_prompts = tokenize_input_prompts(ctx_server.ctx, prompt, /* add_special */ false, true);
|
||||
for (size_t i = 0; i < tokenized_prompts.size(); i++) {
|
||||
server_task task = server_task(SERVER_TASK_TYPE_EMBEDDING);
|
||||
server_task task = server_task(SERVER_TASK_TYPE_EMBEDDING);
|
||||
|
||||
task.id = ctx_server.queue_tasks.get_new_id();
|
||||
task.index = i;
|
||||
task.prompt_tokens = std::move(tokenized_prompts[i]);
|
||||
|
||||
// OAI-compat
|
||||
task.params.oaicompat = oaicompat;
|
||||
|
||||
tasks.push_back(task);
|
||||
}
|
||||
|
||||
@@ -3676,12 +3760,18 @@ int main(int argc, char ** argv) {
|
||||
}
|
||||
|
||||
// write JSON response
|
||||
json root = oaicompat
|
||||
? format_embeddings_response_oaicompat(body, responses)
|
||||
: responses.size() == 1 ? responses[0] : json(responses);
|
||||
json root = oaicompat ? format_embeddings_response_oaicompat(body, responses) : json(responses);
|
||||
res_ok(res, root);
|
||||
};
|
||||
|
||||
const auto handle_embeddings = [&handle_embeddings_impl](const httplib::Request & req, httplib::Response & res) {
|
||||
handle_embeddings_impl(req, res, false);
|
||||
};
|
||||
|
||||
const auto handle_embeddings_oai = [&handle_embeddings_impl](const httplib::Request & req, httplib::Response & res) {
|
||||
handle_embeddings_impl(req, res, true);
|
||||
};
|
||||
|
||||
const auto handle_rerank = [&ctx_server, &res_error, &res_ok](const httplib::Request & req, httplib::Response & res) {
|
||||
if (!ctx_server.params_base.reranking || ctx_server.params_base.embedding) {
|
||||
res_error(res, format_error_response("This server does not support reranking. Start it with `--reranking` and without `--embedding`", ERROR_TYPE_NOT_SUPPORTED));
|
||||
@@ -3828,8 +3918,13 @@ int main(int argc, char ** argv) {
|
||||
}
|
||||
} else {
|
||||
// using embedded static index.html
|
||||
svr->Get("/", [](const httplib::Request &, httplib::Response & res) {
|
||||
res.set_content(reinterpret_cast<const char*>(index_html), index_html_len, "text/html; charset=utf-8");
|
||||
svr->Get("/", [](const httplib::Request & req, httplib::Response & res) {
|
||||
if (req.get_header_value("Accept-Encoding").find("gzip") == std::string::npos) {
|
||||
res.set_content("Error: gzip is not supported by this browser", "text/plain");
|
||||
} else {
|
||||
res.set_header("Content-Encoding", "gzip");
|
||||
res.set_content(reinterpret_cast<const char*>(index_html_gz), index_html_gz_len, "text/html; charset=utf-8");
|
||||
}
|
||||
return false;
|
||||
});
|
||||
}
|
||||
@@ -3850,7 +3945,7 @@ int main(int argc, char ** argv) {
|
||||
svr->Post("/infill", handle_infill);
|
||||
svr->Post("/embedding", handle_embeddings); // legacy
|
||||
svr->Post("/embeddings", handle_embeddings);
|
||||
svr->Post("/v1/embeddings", handle_embeddings);
|
||||
svr->Post("/v1/embeddings", handle_embeddings_oai);
|
||||
svr->Post("/rerank", handle_rerank);
|
||||
svr->Post("/reranking", handle_rerank);
|
||||
svr->Post("/v1/rerank", handle_rerank);
|
||||
|
||||
@@ -10,16 +10,17 @@ def create_server():
|
||||
global server
|
||||
server = ServerPreset.tinyllama2()
|
||||
|
||||
@pytest.mark.parametrize("prompt,n_predict,re_content,n_prompt,n_predicted,truncated", [
|
||||
("I believe the meaning of life is", 8, "(going|bed)+", 18, 8, False),
|
||||
("Write a joke about AI from a very long prompt which will not be truncated", 256, "(princesses|everyone|kids|Anna|forest)+", 46, 64, False),
|
||||
@pytest.mark.parametrize("prompt,n_predict,re_content,n_prompt,n_predicted,truncated,return_tokens", [
|
||||
("I believe the meaning of life is", 8, "(going|bed)+", 18, 8, False, False),
|
||||
("Write a joke about AI from a very long prompt which will not be truncated", 256, "(princesses|everyone|kids|Anna|forest)+", 46, 64, False, True),
|
||||
])
|
||||
def test_completion(prompt: str, n_predict: int, re_content: str, n_prompt: int, n_predicted: int, truncated: bool):
|
||||
def test_completion(prompt: str, n_predict: int, re_content: str, n_prompt: int, n_predicted: int, truncated: bool, return_tokens: bool):
|
||||
global server
|
||||
server.start()
|
||||
res = server.make_request("POST", "/completion", data={
|
||||
"n_predict": n_predict,
|
||||
"prompt": prompt,
|
||||
"return_tokens": return_tokens,
|
||||
})
|
||||
assert res.status_code == 200
|
||||
assert res.body["timings"]["prompt_n"] == n_prompt
|
||||
@@ -27,6 +28,11 @@ def test_completion(prompt: str, n_predict: int, re_content: str, n_prompt: int,
|
||||
assert res.body["truncated"] == truncated
|
||||
assert type(res.body["has_new_line"]) == bool
|
||||
assert match_regex(re_content, res.body["content"])
|
||||
if return_tokens:
|
||||
assert len(res.body["tokens"]) > 0
|
||||
assert all(type(tok) == int for tok in res.body["tokens"])
|
||||
else:
|
||||
assert res.body["tokens"] == []
|
||||
|
||||
|
||||
@pytest.mark.parametrize("prompt,n_predict,re_content,n_prompt,n_predicted,truncated", [
|
||||
@@ -56,6 +62,8 @@ def test_completion_stream(prompt: str, n_predict: int, re_content: str, n_promp
|
||||
assert data["generation_settings"]["seed"] == server.seed
|
||||
assert match_regex(re_content, content)
|
||||
else:
|
||||
assert len(data["tokens"]) > 0
|
||||
assert all(type(tok) == int for tok in data["tokens"])
|
||||
content += data["content"]
|
||||
|
||||
|
||||
|
||||
@@ -14,8 +14,9 @@ def create_server():
|
||||
|
||||
def test_embedding_single():
|
||||
global server
|
||||
server.pooling = 'last'
|
||||
server.start()
|
||||
res = server.make_request("POST", "/embeddings", data={
|
||||
res = server.make_request("POST", "/v1/embeddings", data={
|
||||
"input": "I believe the meaning of life is",
|
||||
})
|
||||
assert res.status_code == 200
|
||||
@@ -29,8 +30,9 @@ def test_embedding_single():
|
||||
|
||||
def test_embedding_multiple():
|
||||
global server
|
||||
server.pooling = 'last'
|
||||
server.start()
|
||||
res = server.make_request("POST", "/embeddings", data={
|
||||
res = server.make_request("POST", "/v1/embeddings", data={
|
||||
"input": [
|
||||
"I believe the meaning of life is",
|
||||
"Write a joke about AI from a very long prompt which will not be truncated",
|
||||
@@ -45,10 +47,69 @@ def test_embedding_multiple():
|
||||
assert len(d['embedding']) > 1
|
||||
|
||||
|
||||
def test_embedding_openai_library_single():
|
||||
@pytest.mark.parametrize(
|
||||
"input,is_multi_prompt",
|
||||
[
|
||||
# single prompt
|
||||
("string", False),
|
||||
([12, 34, 56], False),
|
||||
([12, 34, "string", 56, 78], False),
|
||||
# multiple prompts
|
||||
(["string1", "string2"], True),
|
||||
(["string1", [12, 34, 56]], True),
|
||||
([[12, 34, 56], [12, 34, 56]], True),
|
||||
([[12, 34, 56], [12, "string", 34, 56]], True),
|
||||
]
|
||||
)
|
||||
def test_embedding_mixed_input(input, is_multi_prompt: bool):
|
||||
global server
|
||||
server.start()
|
||||
client = OpenAI(api_key="dummy", base_url=f"http://{server.server_host}:{server.server_port}")
|
||||
res = server.make_request("POST", "/v1/embeddings", data={"input": input})
|
||||
assert res.status_code == 200
|
||||
data = res.body['data']
|
||||
if is_multi_prompt:
|
||||
assert len(data) == len(input)
|
||||
for d in data:
|
||||
assert 'embedding' in d
|
||||
assert len(d['embedding']) > 1
|
||||
else:
|
||||
assert 'embedding' in data[0]
|
||||
assert len(data[0]['embedding']) > 1
|
||||
|
||||
|
||||
def test_embedding_pooling_none():
|
||||
global server
|
||||
server.pooling = 'none'
|
||||
server.start()
|
||||
res = server.make_request("POST", "/embeddings", data={
|
||||
"input": "hello hello hello",
|
||||
})
|
||||
assert res.status_code == 200
|
||||
assert 'embedding' in res.body[0]
|
||||
assert len(res.body[0]['embedding']) == 5 # 3 text tokens + 2 special
|
||||
|
||||
# make sure embedding vector is not normalized
|
||||
for x in res.body[0]['embedding']:
|
||||
assert abs(sum([x ** 2 for x in x]) - 1) > EPSILON
|
||||
|
||||
|
||||
def test_embedding_pooling_none_oai():
|
||||
global server
|
||||
server.pooling = 'none'
|
||||
server.start()
|
||||
res = server.make_request("POST", "/v1/embeddings", data={
|
||||
"input": "hello hello hello",
|
||||
})
|
||||
|
||||
# /v1/embeddings does not support pooling type 'none'
|
||||
assert res.status_code == 400
|
||||
|
||||
|
||||
def test_embedding_openai_library_single():
|
||||
global server
|
||||
server.pooling = 'last'
|
||||
server.start()
|
||||
client = OpenAI(api_key="dummy", base_url=f"http://{server.server_host}:{server.server_port}/v1")
|
||||
res = client.embeddings.create(model="text-embedding-3-small", input="I believe the meaning of life is")
|
||||
assert len(res.data) == 1
|
||||
assert len(res.data[0].embedding) > 1
|
||||
@@ -56,8 +117,9 @@ def test_embedding_openai_library_single():
|
||||
|
||||
def test_embedding_openai_library_multiple():
|
||||
global server
|
||||
server.pooling = 'last'
|
||||
server.start()
|
||||
client = OpenAI(api_key="dummy", base_url=f"http://{server.server_host}:{server.server_port}")
|
||||
client = OpenAI(api_key="dummy", base_url=f"http://{server.server_host}:{server.server_port}/v1")
|
||||
res = client.embeddings.create(model="text-embedding-3-small", input=[
|
||||
"I believe the meaning of life is",
|
||||
"Write a joke about AI from a very long prompt which will not be truncated",
|
||||
@@ -71,8 +133,9 @@ def test_embedding_openai_library_multiple():
|
||||
|
||||
def test_embedding_error_prompt_too_long():
|
||||
global server
|
||||
server.pooling = 'last'
|
||||
server.start()
|
||||
res = server.make_request("POST", "/embeddings", data={
|
||||
res = server.make_request("POST", "/v1/embeddings", data={
|
||||
"input": "This is a test " * 512,
|
||||
})
|
||||
assert res.status_code != 200
|
||||
@@ -80,8 +143,9 @@ def test_embedding_error_prompt_too_long():
|
||||
|
||||
|
||||
def test_same_prompt_give_same_result():
|
||||
server.pooling = 'last'
|
||||
server.start()
|
||||
res = server.make_request("POST", "/embeddings", data={
|
||||
res = server.make_request("POST", "/v1/embeddings", data={
|
||||
"input": [
|
||||
"I believe the meaning of life is",
|
||||
"I believe the meaning of life is",
|
||||
@@ -97,3 +161,33 @@ def test_same_prompt_give_same_result():
|
||||
vi = res.body['data'][i]['embedding']
|
||||
for x, y in zip(v0, vi):
|
||||
assert abs(x - y) < EPSILON
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"content,n_tokens",
|
||||
[
|
||||
("I believe the meaning of life is", 9),
|
||||
("This is a test", 6),
|
||||
]
|
||||
)
|
||||
def test_embedding_usage_single(content, n_tokens):
|
||||
global server
|
||||
server.start()
|
||||
res = server.make_request("POST", "/v1/embeddings", data={"input": content})
|
||||
assert res.status_code == 200
|
||||
assert res.body['usage']['prompt_tokens'] == res.body['usage']['total_tokens']
|
||||
assert res.body['usage']['prompt_tokens'] == n_tokens
|
||||
|
||||
|
||||
def test_embedding_usage_multiple():
|
||||
global server
|
||||
server.start()
|
||||
res = server.make_request("POST", "/v1/embeddings", data={
|
||||
"input": [
|
||||
"I believe the meaning of life is",
|
||||
"I believe the meaning of life is",
|
||||
],
|
||||
})
|
||||
assert res.status_code == 200
|
||||
assert res.body['usage']['prompt_tokens'] == res.body['usage']['total_tokens']
|
||||
assert res.body['usage']['prompt_tokens'] == 2 * 9
|
||||
|
||||
@@ -53,3 +53,26 @@ def test_invalid_rerank_req(documents):
|
||||
})
|
||||
assert res.status_code == 400
|
||||
assert "error" in res.body
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"query,doc1,doc2,n_tokens",
|
||||
[
|
||||
("Machine learning is", "A machine", "Learning is", 19),
|
||||
("Which city?", "Machine learning is ", "Paris, capitale de la", 26),
|
||||
]
|
||||
)
|
||||
def test_rerank_usage(query, doc1, doc2, n_tokens):
|
||||
global server
|
||||
server.start()
|
||||
|
||||
res = server.make_request("POST", "/rerank", data={
|
||||
"query": query,
|
||||
"documents": [
|
||||
doc1,
|
||||
doc2,
|
||||
]
|
||||
})
|
||||
assert res.status_code == 200
|
||||
assert res.body['usage']['prompt_tokens'] == res.body['usage']['total_tokens']
|
||||
assert res.body['usage']['prompt_tokens'] == n_tokens
|
||||
|
||||
@@ -65,6 +65,7 @@ class ServerProcess:
|
||||
server_reranking: bool | None = False
|
||||
server_metrics: bool | None = False
|
||||
server_slots: bool | None = False
|
||||
pooling: str | None = None
|
||||
draft: int | None = None
|
||||
api_key: str | None = None
|
||||
response_format: str | None = None
|
||||
@@ -132,6 +133,8 @@ class ServerProcess:
|
||||
server_args.append("--metrics")
|
||||
if self.server_slots:
|
||||
server_args.append("--slots")
|
||||
if self.pooling:
|
||||
server_args.extend(["--pooling", self.pooling])
|
||||
if self.model_alias:
|
||||
server_args.extend(["--alias", self.model_alias])
|
||||
if self.n_ctx:
|
||||
|
||||
@@ -222,7 +222,6 @@
|
||||
temperature: 0.7,
|
||||
repeat_last_n: 256, // 0 = disable penalty, -1 = context size
|
||||
repeat_penalty: 1.18, // 1.0 = disabled
|
||||
penalize_nl: false,
|
||||
top_k: 40, // <= 0 to use vocab size
|
||||
top_p: 0.95, // 1.0 = disabled
|
||||
min_p: 0.05, // 0 = disabled
|
||||
@@ -779,7 +778,6 @@
|
||||
${FloatField({ label: "Temperature", max: 2.0, min: 0.0, name: "temperature", step: 0.01, value: params.value.temperature })}
|
||||
${FloatField({ label: "Penalize repeat sequence", max: 2.0, min: 0.0, name: "repeat_penalty", step: 0.01, value: params.value.repeat_penalty })}
|
||||
${IntField({ label: "Consider N tokens for penalize", max: 2048, min: 0, name: "repeat_last_n", value: params.value.repeat_last_n })}
|
||||
${BoolField({ label: "Penalize repetition of newlines", name: "penalize_nl", value: params.value.penalize_nl })}
|
||||
${IntField({ label: "Top-K sampling", max: 100, min: -1, name: "top_k", value: params.value.top_k })}
|
||||
${FloatField({ label: "Top-P sampling", max: 1.0, min: 0.0, name: "top_p", step: 0.01, value: params.value.top_p })}
|
||||
${FloatField({ label: "Min-P sampling", max: 1.0, min: 0.0, name: "min_p", step: 0.01, value: params.value.min_p })}
|
||||
|
||||
@@ -225,7 +225,6 @@
|
||||
temperature: 0.7,
|
||||
repeat_last_n: 256, // 0 = disable penalty, -1 = context size
|
||||
repeat_penalty: 1.18, // 1.0 = disabled
|
||||
penalize_nl: false,
|
||||
top_k: 40, // <= 0 to use vocab size
|
||||
top_p: 0.95, // 1.0 = disabled
|
||||
min_p: 0.05, // 0 = disabled
|
||||
@@ -782,7 +781,6 @@
|
||||
${FloatField({ label: "Temperature", max: 2.0, min: 0.0, name: "temperature", step: 0.01, value: params.value.temperature })}
|
||||
${FloatField({ label: "Penalize repeat sequence", max: 2.0, min: 0.0, name: "repeat_penalty", step: 0.01, value: params.value.repeat_penalty })}
|
||||
${IntField({ label: "Consider N tokens for penalize", max: 2048, min: 0, name: "repeat_last_n", value: params.value.repeat_last_n })}
|
||||
${BoolField({ label: "Penalize repetition of newlines", name: "penalize_nl", value: params.value.penalize_nl })}
|
||||
${IntField({ label: "Top-K sampling", max: 100, min: -1, name: "top_k", value: params.value.top_k })}
|
||||
${FloatField({ label: "Top-P sampling", max: 1.0, min: 0.0, name: "top_p", step: 0.01, value: params.value.top_p })}
|
||||
${FloatField({ label: "Min-P sampling", max: 1.0, min: 0.0, name: "min_p", step: 0.01, value: params.value.min_p })}
|
||||
|
||||
@@ -138,6 +138,7 @@ static llama_tokens tokenize_mixed(const llama_context * ctx, const json & json_
|
||||
* and multiple prompts (multi-tasks):
|
||||
* - "prompt": ["string1", "string2"]
|
||||
* - "prompt": ["string1", [12, 34, 56]]
|
||||
* - "prompt": [[12, 34, 56], [78, 90, 12]]
|
||||
* - "prompt": [[12, 34, "string", 56, 78], [12, 34, 56]]
|
||||
*/
|
||||
static std::vector<llama_tokens> tokenize_input_prompts(llama_context * ctx, const json & json_prompt, bool add_special, bool parse_special) {
|
||||
@@ -560,6 +561,7 @@ static json oaicompat_completion_params_parse(
|
||||
|
||||
static json format_embeddings_response_oaicompat(const json & request, const json & embeddings) {
|
||||
json data = json::array();
|
||||
int32_t n_tokens = 0;
|
||||
int i = 0;
|
||||
for (const auto & elem : embeddings) {
|
||||
data.push_back(json{
|
||||
@@ -567,14 +569,16 @@ static json format_embeddings_response_oaicompat(const json & request, const jso
|
||||
{"index", i++},
|
||||
{"object", "embedding"}
|
||||
});
|
||||
|
||||
n_tokens += json_value(elem, "tokens_evaluated", 0);
|
||||
}
|
||||
|
||||
json res = json {
|
||||
{"model", json_value(request, "model", std::string(DEFAULT_OAICOMPAT_MODEL))},
|
||||
{"object", "list"},
|
||||
{"usage", json { // TODO: fill
|
||||
{"prompt_tokens", 0},
|
||||
{"total_tokens", 0}
|
||||
{"usage", json {
|
||||
{"prompt_tokens", n_tokens},
|
||||
{"total_tokens", n_tokens}
|
||||
}},
|
||||
{"data", data}
|
||||
};
|
||||
@@ -584,20 +588,23 @@ static json format_embeddings_response_oaicompat(const json & request, const jso
|
||||
|
||||
static json format_response_rerank(const json & request, const json & ranks) {
|
||||
json data = json::array();
|
||||
int32_t n_tokens = 0;
|
||||
int i = 0;
|
||||
for (const auto & rank : ranks) {
|
||||
data.push_back(json{
|
||||
{"index", i++},
|
||||
{"relevance_score", json_value(rank, "score", 0.0)},
|
||||
});
|
||||
|
||||
n_tokens += json_value(rank, "tokens_evaluated", 0);
|
||||
}
|
||||
|
||||
json res = json {
|
||||
{"model", json_value(request, "model", std::string(DEFAULT_OAICOMPAT_MODEL))},
|
||||
{"object", "list"},
|
||||
{"usage", json { // TODO: fill
|
||||
{"prompt_tokens", 0},
|
||||
{"total_tokens", 0}
|
||||
{"usage", json {
|
||||
{"prompt_tokens", n_tokens},
|
||||
{"total_tokens", n_tokens}
|
||||
}},
|
||||
{"results", data}
|
||||
};
|
||||
|
||||
@@ -201,6 +201,10 @@
|
||||
<details class="collapse collapse-arrow bg-base-200 mb-2 overflow-visible">
|
||||
<summary class="collapse-title font-bold">Advanced config</summary>
|
||||
<div class="collapse-content">
|
||||
<div class="flex flex-row items-center mb-2" v-if="isDev">
|
||||
<!-- this button only shows in dev mode, used to import a demo conversation to test message rendering -->
|
||||
<button class="btn" @click="debugImportDemoConv()">(debug) Import demo conversation</button>
|
||||
</div>
|
||||
<div class="flex flex-row items-center mb-2">
|
||||
<input type="checkbox" class="checkbox" v-model="config.showTokensPerSecond" />
|
||||
<span class="ml-4">Show tokens per second</span>
|
||||
|
||||
Generated
+519
@@ -8,8 +8,12 @@
|
||||
"name": "webui",
|
||||
"version": "0.0.0",
|
||||
"dependencies": {
|
||||
"@sec-ant/readable-stream": "^0.6.0",
|
||||
"@vscode/markdown-it-katex": "^1.1.1",
|
||||
"autoprefixer": "^10.4.20",
|
||||
"daisyui": "^4.12.14",
|
||||
"highlight.js": "^11.10.0",
|
||||
"katex": "^0.16.15",
|
||||
"markdown-it": "^14.1.0",
|
||||
"postcss": "^8.4.49",
|
||||
"tailwindcss": "^3.4.15",
|
||||
@@ -18,6 +22,7 @@
|
||||
"vue": "^3.5.13"
|
||||
},
|
||||
"devDependencies": {
|
||||
"sass-embedded": "^1.83.0",
|
||||
"vite": "^5.4.10"
|
||||
}
|
||||
},
|
||||
@@ -33,6 +38,13 @@
|
||||
"url": "https://github.com/sponsors/sindresorhus"
|
||||
}
|
||||
},
|
||||
"node_modules/@bufbuild/protobuf": {
|
||||
"version": "2.2.3",
|
||||
"resolved": "https://registry.npmjs.org/@bufbuild/protobuf/-/protobuf-2.2.3.tgz",
|
||||
"integrity": "sha512-tFQoXHJdkEOSwj5tRIZSPNUuXK3RaR7T1nUrPgbYX1pUbvqqaaZAsfo+NXBPsz5rZMSKVFrgK1WL8Q/MSLvprg==",
|
||||
"devOptional": true,
|
||||
"license": "(Apache-2.0 AND BSD-3-Clause)"
|
||||
},
|
||||
"node_modules/@esbuild/aix-ppc64": {
|
||||
"version": "0.21.5",
|
||||
"resolved": "https://registry.npmjs.org/@esbuild/aix-ppc64/-/aix-ppc64-0.21.5.tgz",
|
||||
@@ -606,6 +618,21 @@
|
||||
"win32"
|
||||
]
|
||||
},
|
||||
"node_modules/@sec-ant/readable-stream": {
|
||||
"version": "0.6.0",
|
||||
"resolved": "https://registry.npmjs.org/@sec-ant/readable-stream/-/readable-stream-0.6.0.tgz",
|
||||
"integrity": "sha512-uiBh8DrB5FN35gP6/o8JEhEQ7/ci1jUsOZO/VMUjyvTpjtV54VstOXVj1TvTj/wsT23pfX6butxxh3qufsW3+g==",
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/@vscode/markdown-it-katex": {
|
||||
"version": "1.1.1",
|
||||
"resolved": "https://registry.npmjs.org/@vscode/markdown-it-katex/-/markdown-it-katex-1.1.1.tgz",
|
||||
"integrity": "sha512-3KTlbsRBPJQLE2YmLL7K6nunTlU+W9T5+FjfNdWuIUKgxSS6HWLQHaO3L4MkJi7z7MpIPpY+g4N+cWNBPE/MSA==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"katex": "^0.16.4"
|
||||
}
|
||||
},
|
||||
"node_modules/@vue/compiler-dom": {
|
||||
"version": "3.5.13",
|
||||
"resolved": "https://registry.npmjs.org/@vue/compiler-dom/-/compiler-dom-3.5.13.tgz",
|
||||
@@ -1004,6 +1031,13 @@
|
||||
"browserslist": ">= 4.21.0"
|
||||
}
|
||||
},
|
||||
"node_modules/buffer-builder": {
|
||||
"version": "0.2.0",
|
||||
"resolved": "https://registry.npmjs.org/buffer-builder/-/buffer-builder-0.2.0.tgz",
|
||||
"integrity": "sha512-7VPMEPuYznPSoR21NE1zvd2Xna6c/CloiZCfcMXR1Jny6PjX0N4Nsa38zcBFo/FMK+BlA+FLKbJCQ0i2yxp+Xg==",
|
||||
"devOptional": true,
|
||||
"license": "MIT/X11"
|
||||
},
|
||||
"node_modules/caniuse-lite": {
|
||||
"version": "1.0.30001684",
|
||||
"resolved": "https://registry.npmjs.org/caniuse-lite/-/caniuse-lite-1.0.30001684.tgz",
|
||||
@@ -1166,6 +1200,22 @@
|
||||
"node": ">=8.0"
|
||||
}
|
||||
},
|
||||
"node_modules/colorjs.io": {
|
||||
"version": "0.5.2",
|
||||
"resolved": "https://registry.npmjs.org/colorjs.io/-/colorjs.io-0.5.2.tgz",
|
||||
"integrity": "sha512-twmVoizEW7ylZSN32OgKdXRmo1qg+wT5/6C3xu5b9QsWzSFAhHLn2xd8ro0diCsKfCj1RdaTP/nrcW+vAoQPIw==",
|
||||
"devOptional": true,
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/commander": {
|
||||
"version": "8.3.0",
|
||||
"resolved": "https://registry.npmjs.org/commander/-/commander-8.3.0.tgz",
|
||||
"integrity": "sha512-OkTL9umf+He2DZkUq8f8J9of7yL6RJKI24dVITBmNfZBmri9zYZQrKkuXiKhyfPSu8tUhnVBB1iKXevvnlR4Ww==",
|
||||
"license": "MIT",
|
||||
"engines": {
|
||||
"node": ">= 12"
|
||||
}
|
||||
},
|
||||
"node_modules/css-selector-tokenizer": {
|
||||
"version": "0.8.0",
|
||||
"resolved": "https://registry.npmjs.org/css-selector-tokenizer/-/css-selector-tokenizer-0.8.0.tgz",
|
||||
@@ -1473,6 +1523,31 @@
|
||||
"node": ">=10.13.0"
|
||||
}
|
||||
},
|
||||
"node_modules/has-flag": {
|
||||
"version": "4.0.0",
|
||||
"resolved": "https://registry.npmjs.org/has-flag/-/has-flag-4.0.0.tgz",
|
||||
"integrity": "sha512-EykJT/Q1KjTWctppgIAgfSO0tKVuZUjhgMr17kqTumMl6Afv3EISleU7qZUzoXDFTAHTDC4NOoG/ZxU3EvlMPQ==",
|
||||
"devOptional": true,
|
||||
"license": "MIT",
|
||||
"engines": {
|
||||
"node": ">=8"
|
||||
}
|
||||
},
|
||||
"node_modules/highlight.js": {
|
||||
"version": "11.10.0",
|
||||
"resolved": "https://registry.npmjs.org/highlight.js/-/highlight.js-11.10.0.tgz",
|
||||
"integrity": "sha512-SYVnVFswQER+zu1laSya563s+F8VDGt7o35d4utbamowvUNLLMovFqwCLSocpZTz3MgaSRA1IbqRWZv97dtErQ==",
|
||||
"engines": {
|
||||
"node": ">=12.0.0"
|
||||
}
|
||||
},
|
||||
"node_modules/immutable": {
|
||||
"version": "5.0.3",
|
||||
"resolved": "https://registry.npmjs.org/immutable/-/immutable-5.0.3.tgz",
|
||||
"integrity": "sha512-P8IdPQHq3lA1xVeBRi5VPqUm5HDgKnx0Ru51wZz5mjxHr5n3RWhjIpOFU7ybkUxfB+5IToy+OLaHYDBIWsv+uw==",
|
||||
"devOptional": true,
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/is-glob": {
|
||||
"version": "4.0.3",
|
||||
"resolved": "https://registry.npmjs.org/is-glob/-/is-glob-4.0.3.tgz",
|
||||
@@ -1503,6 +1578,22 @@
|
||||
"jiti": "bin/jiti.js"
|
||||
}
|
||||
},
|
||||
"node_modules/katex": {
|
||||
"version": "0.16.15",
|
||||
"resolved": "https://registry.npmjs.org/katex/-/katex-0.16.15.tgz",
|
||||
"integrity": "sha512-yE9YJIEAk2aZ+FL/G8r+UGw0CTUzEA8ZFy6E+8tc3spHUKq3qBnzCkI1CQwGoI9atJhVyFPEypQsTY7mJ1Pi9w==",
|
||||
"funding": [
|
||||
"https://opencollective.com/katex",
|
||||
"https://github.com/sponsors/katex"
|
||||
],
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"commander": "^8.3.0"
|
||||
},
|
||||
"bin": {
|
||||
"katex": "cli.js"
|
||||
}
|
||||
},
|
||||
"node_modules/lilconfig": {
|
||||
"version": "2.1.0",
|
||||
"resolved": "https://registry.npmjs.org/lilconfig/-/lilconfig-2.1.0.tgz",
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||||
@@ -2022,6 +2113,381 @@
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||||
"integrity": "sha512-AYnb1nQyY49te+VRAVgmzfcgjYS91mY5P0TKUDCLEM+gNnA+3T6rWITXRLYCpahpqSQbN5cE+gHpnPyXjHWxcw==",
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/rxjs": {
|
||||
"version": "7.8.1",
|
||||
"resolved": "https://registry.npmjs.org/rxjs/-/rxjs-7.8.1.tgz",
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"integrity": "sha512-AA3TVj+0A2iuIoQkWEK/tqFjBq2j+6PO6Y0zJcvzLAFhEFIO3HL0vls9hWLncZbAAbK0mar7oZ4V079I/qPMxg==",
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"devOptional": true,
|
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"license": "Apache-2.0",
|
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"dependencies": {
|
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"tslib": "^2.1.0"
|
||||
}
|
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},
|
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"node_modules/sass-embedded": {
|
||||
"version": "1.83.0",
|
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"resolved": "https://registry.npmjs.org/sass-embedded/-/sass-embedded-1.83.0.tgz",
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"integrity": "sha512-/8cYZeL39evUqe0o//193na51Q1VWZ61qhxioQvLJwOtWIrX+PgNhCyD8RSuTtmzc4+6+waFZf899bfp/MCUwA==",
|
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"devOptional": true,
|
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"license": "MIT",
|
||||
"dependencies": {
|
||||
"@bufbuild/protobuf": "^2.0.0",
|
||||
"buffer-builder": "^0.2.0",
|
||||
"colorjs.io": "^0.5.0",
|
||||
"immutable": "^5.0.2",
|
||||
"rxjs": "^7.4.0",
|
||||
"supports-color": "^8.1.1",
|
||||
"sync-child-process": "^1.0.2",
|
||||
"varint": "^6.0.0"
|
||||
},
|
||||
"bin": {
|
||||
"sass": "dist/bin/sass.js"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=16.0.0"
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"sass-embedded-android-arm": "1.83.0",
|
||||
"sass-embedded-android-arm64": "1.83.0",
|
||||
"sass-embedded-android-ia32": "1.83.0",
|
||||
"sass-embedded-android-riscv64": "1.83.0",
|
||||
"sass-embedded-android-x64": "1.83.0",
|
||||
"sass-embedded-darwin-arm64": "1.83.0",
|
||||
"sass-embedded-darwin-x64": "1.83.0",
|
||||
"sass-embedded-linux-arm": "1.83.0",
|
||||
"sass-embedded-linux-arm64": "1.83.0",
|
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"sass-embedded-linux-ia32": "1.83.0",
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"sass-embedded-linux-musl-arm": "1.83.0",
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"sass-embedded-linux-musl-arm64": "1.83.0",
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"sass-embedded-linux-musl-ia32": "1.83.0",
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"sass-embedded-linux-musl-riscv64": "1.83.0",
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"sass-embedded-linux-musl-x64": "1.83.0",
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"sass-embedded-linux-riscv64": "1.83.0",
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"sass-embedded-linux-x64": "1.83.0",
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"sass-embedded-win32-arm64": "1.83.0",
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"sass-embedded-win32-ia32": "1.83.0",
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"sass-embedded-win32-x64": "1.83.0"
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}
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},
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"node_modules/sass-embedded-android-arm": {
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"version": "1.83.0",
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"resolved": "https://registry.npmjs.org/sass-embedded-android-arm/-/sass-embedded-android-arm-1.83.0.tgz",
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"integrity": "sha512-uwFSXzJlfbd4Px189xE5l+cxN8+TQpXdQgJec7TIrb4HEY7imabtpYufpVdqUVwT1/uiis5V4+qIEC4Vl5XObQ==",
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"cpu": [
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"arm"
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"license": "MIT",
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"optional": true,
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"os": [
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"android"
|
||||
],
|
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"engines": {
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"node": ">=14.0.0"
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"node_modules/sass-embedded-android-arm64": {
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"version": "1.83.0",
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"android"
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"engines": {
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"node": ">=14.0.0"
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"node_modules/sass-embedded-android-ia32": {
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"node_modules/sass-embedded-android-riscv64": {
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"cpu": [
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"riscv64"
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"license": "MIT",
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"optional": true,
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"os": [
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"node_modules/sass-embedded-android-x64": {
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"node_modules/sass-embedded-linux-musl-x64": {
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"node_modules/sass-embedded-linux-riscv64": {
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"version": "1.83.0",
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"resolved": "https://registry.npmjs.org/sass-embedded-win32-arm64/-/sass-embedded-win32-arm64-1.83.0.tgz",
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"cpu": [
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"arm64"
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"license": "MIT",
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"optional": true,
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"os": [
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"win32"
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],
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"engines": {
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"node": ">=14.0.0"
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}
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},
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"node_modules/sass-embedded-win32-ia32": {
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"version": "1.83.0",
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"resolved": "https://registry.npmjs.org/sass-embedded-win32-ia32/-/sass-embedded-win32-ia32-1.83.0.tgz",
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"integrity": "sha512-2PxNXJ8Pad4geVcTXY4rkyTr5AwbF8nfrCTDv0ulbTvPhzX2mMKEGcBZUXWn5BeHZTBc6whNMfS7d5fQXR9dDQ==",
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"cpu": [
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"ia32"
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],
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"license": "MIT",
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"optional": true,
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"os": [
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"win32"
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],
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"engines": {
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"node": ">=14.0.0"
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}
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},
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"node_modules/sass-embedded-win32-x64": {
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"version": "1.83.0",
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"resolved": "https://registry.npmjs.org/sass-embedded-win32-x64/-/sass-embedded-win32-x64-1.83.0.tgz",
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"integrity": "sha512-muBXkFngM6eLTNqOV0FQi7Dv9s+YRQ42Yem26mosdan/GmJQc81deto6uDTgrYn+bzFNmiXcOdfm+0MkTWK3OQ==",
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"cpu": [
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"x64"
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],
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"license": "MIT",
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"optional": true,
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"os": [
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"win32"
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],
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"engines": {
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"node": ">=14.0.0"
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}
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"node_modules/sucrase": {
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"version": "3.35.0",
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"resolved": "https://registry.npmjs.org/sucrase/-/sucrase-3.35.0.tgz",
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@@ -2641,6 +3107,45 @@
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"node": ">=8"
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}
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},
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"node_modules/supports-color": {
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"version": "8.1.1",
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"devOptional": true,
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"dependencies": {
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"has-flag": "^4.0.0"
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},
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"engines": {
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"node": ">=10"
|
||||
},
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||||
"funding": {
|
||||
"url": "https://github.com/chalk/supports-color?sponsor=1"
|
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}
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},
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"version": "1.0.2",
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"devOptional": true,
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"license": "MIT",
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"dependencies": {
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"sync-message-port": "^1.0.0"
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},
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"engines": {
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"node": ">=16.0.0"
|
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}
|
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},
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"node_modules/sync-message-port": {
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"version": "1.1.3",
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"resolved": "https://registry.npmjs.org/sync-message-port/-/sync-message-port-1.1.3.tgz",
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"integrity": "sha512-GTt8rSKje5FilG+wEdfCkOcLL7LWqpMlr2c3LRuKt/YXxcJ52aGSbGBAdI4L3aaqfrBt6y711El53ItyH1NWzg==",
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"devOptional": true,
|
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"license": "MIT",
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"engines": {
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"node": ">=16.0.0"
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}
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},
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"node_modules/tailwindcss": {
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"version": "3.4.15",
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"resolved": "https://registry.npmjs.org/tailwindcss/-/tailwindcss-3.4.15.tgz",
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@@ -2684,12 +3189,26 @@
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"integrity": "sha512-iBHbi7BQxrFmwZUQJsT0SjNzlLLsXhvW/kg7EyOMVMBIrlnj/qYofwo1LVLZi+3GbUEo96Iu2eqToI2+lZoAEQ==",
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"license": "MIT"
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"devOptional": true,
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"license": "0BSD"
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"node_modules/uc.micro": {
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"version": "2.1.0",
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"resolved": "https://registry.npmjs.org/uc.micro/-/uc.micro-2.1.0.tgz",
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"license": "MIT"
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},
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"node_modules/varint": {
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"version": "6.0.0",
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"resolved": "https://registry.npmjs.org/varint/-/varint-6.0.0.tgz",
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"integrity": "sha512-cXEIW6cfr15lFv563k4GuVuW/fiwjknytD37jIOLSdSWuOI6WnO/oKwmP2FQTU2l01LP8/M5TSAJpzUaGe3uWg==",
|
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"devOptional": true,
|
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"license": "MIT"
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},
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"node_modules/vite": {
|
||||
"version": "5.4.11",
|
||||
"resolved": "https://registry.npmjs.org/vite/-/vite-5.4.11.tgz",
|
||||
|
||||
@@ -6,14 +6,20 @@
|
||||
"scripts": {
|
||||
"dev": "vite",
|
||||
"build": "vite build",
|
||||
"preview": "vite preview"
|
||||
"preview": "vite preview",
|
||||
"analyze": "ANALYZE=1 npx vite-bundle-visualizer"
|
||||
},
|
||||
"devDependencies": {
|
||||
"sass-embedded": "^1.83.0",
|
||||
"vite": "^5.4.10"
|
||||
},
|
||||
"dependencies": {
|
||||
"@sec-ant/readable-stream": "^0.6.0",
|
||||
"@vscode/markdown-it-katex": "^1.1.1",
|
||||
"autoprefixer": "^10.4.20",
|
||||
"daisyui": "^4.12.14",
|
||||
"highlight.js": "^11.10.0",
|
||||
"katex": "^0.16.15",
|
||||
"markdown-it": "^14.1.0",
|
||||
"postcss": "^8.4.49",
|
||||
"tailwindcss": "^3.4.15",
|
||||
|
||||
@@ -0,0 +1,33 @@
|
||||
{
|
||||
"demo": true,
|
||||
"id": "conv-1734086746930",
|
||||
"lastModified": 1734087548943,
|
||||
"messages": [
|
||||
{
|
||||
"id": 1734086764521,
|
||||
"role": "user",
|
||||
"content": "this is a demo conversation, used in dev mode"
|
||||
},
|
||||
{
|
||||
"id": 1734087548327,
|
||||
"role": "assistant",
|
||||
"content": "This is the formula:\n\n$\\frac{e^{x_i}}{\\sum_{j=1}^{n}e^{x_j}}$\n\nGiven an input vector \\(\\mathbf{x} = [x_1, x_2, \\ldots, x_n]\\)\n\n\\[\ny_i = \\frac{e^{x_i}}{\\sum_{j=1}^n e^{x_j}}\n\\]\n\nCode block latex:\n```latex\n\\frac{e^{x_i}}{\\sum_{j=1}^{n}e^{x_j}}\n```\n\nTest dollar sign: $1234 $4567\n\nInvalid latex syntax: $E = mc^$ and $$E = mc^$$",
|
||||
"timings": {
|
||||
"prompt_n": 1,
|
||||
"prompt_ms": 28.923,
|
||||
"predicted_n": 25,
|
||||
"predicted_ms": 573.016
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 1734087548328,
|
||||
"role": "user",
|
||||
"content": "this is a demo conversation, used in dev mode"
|
||||
},
|
||||
{
|
||||
"id": 1734087548329,
|
||||
"role": "assistant",
|
||||
"content": "Code block:\n```js\nconsole.log('hello world')\n```\n```sh\nls -la /dev\n```"
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,60 @@
|
||||
import hljs from 'highlight.js/lib/core';
|
||||
|
||||
// only import commonly used languages to reduce bundle size
|
||||
|
||||
import python from 'highlight.js/lib/languages/python';
|
||||
import javascript from 'highlight.js/lib/languages/javascript';
|
||||
import json from 'highlight.js/lib/languages/json';
|
||||
import bash from 'highlight.js/lib/languages/bash';
|
||||
import yaml from 'highlight.js/lib/languages/yaml';
|
||||
import markdown from 'highlight.js/lib/languages/markdown';
|
||||
import scss from 'highlight.js/lib/languages/scss';
|
||||
import xml from 'highlight.js/lib/languages/xml';
|
||||
import ruby from 'highlight.js/lib/languages/ruby';
|
||||
import go from 'highlight.js/lib/languages/go';
|
||||
import java from 'highlight.js/lib/languages/java';
|
||||
import rust from 'highlight.js/lib/languages/rust';
|
||||
import scala from 'highlight.js/lib/languages/scala';
|
||||
import cpp from 'highlight.js/lib/languages/cpp';
|
||||
import csharp from 'highlight.js/lib/languages/csharp';
|
||||
import swift from 'highlight.js/lib/languages/swift';
|
||||
import dart from 'highlight.js/lib/languages/dart';
|
||||
import elixir from 'highlight.js/lib/languages/elixir';
|
||||
import kotlin from 'highlight.js/lib/languages/kotlin';
|
||||
import lua from 'highlight.js/lib/languages/lua';
|
||||
import php from 'highlight.js/lib/languages/php';
|
||||
import latex from 'highlight.js/lib/languages/latex';
|
||||
|
||||
hljs.registerLanguage('python', python);
|
||||
hljs.registerLanguage('javascript', javascript);
|
||||
hljs.registerLanguage('json', json);
|
||||
hljs.registerLanguage('yaml', yaml);
|
||||
hljs.registerLanguage('markdown', markdown);
|
||||
hljs.registerLanguage('xml', xml);
|
||||
hljs.registerLanguage('ruby', ruby);
|
||||
hljs.registerLanguage('go', go);
|
||||
hljs.registerLanguage('java', java);
|
||||
hljs.registerLanguage('rust', rust);
|
||||
hljs.registerLanguage('scala', scala);
|
||||
hljs.registerLanguage('csharp', csharp);
|
||||
hljs.registerLanguage('swift', swift);
|
||||
hljs.registerLanguage('dart', dart);
|
||||
hljs.registerLanguage('elixir', elixir);
|
||||
hljs.registerLanguage('kotlin', kotlin);
|
||||
hljs.registerLanguage('lua', lua);
|
||||
hljs.registerLanguage('php', php);
|
||||
hljs.registerLanguage('latex', latex);
|
||||
|
||||
// reuse some languages to further reduce bundle size
|
||||
|
||||
hljs.registerLanguage('shell', bash);
|
||||
hljs.registerLanguage('bash', bash);
|
||||
hljs.registerLanguage('sh', bash);
|
||||
|
||||
hljs.registerLanguage('css', scss);
|
||||
hljs.registerLanguage('scss', scss);
|
||||
|
||||
hljs.registerLanguage('c', cpp);
|
||||
hljs.registerLanguage('cpp', cpp);
|
||||
|
||||
export default hljs;
|
||||
@@ -0,0 +1,66 @@
|
||||
import katex from 'katex';
|
||||
|
||||
// Adapted from https://github.com/SchneeHertz/markdown-it-katex-gpt
|
||||
// MIT license
|
||||
|
||||
const defaultOptions = {
|
||||
delimiters: [
|
||||
{ left: '\\[', right: '\\]', display: true },
|
||||
{ left: '\\(', right: '\\)', display: false },
|
||||
],
|
||||
};
|
||||
|
||||
export function renderLatexHTML(content, display = false) {
|
||||
return katex.renderToString(content, {
|
||||
throwOnError: false,
|
||||
output: 'mathml',
|
||||
displayMode: display,
|
||||
});
|
||||
}
|
||||
|
||||
function escapedBracketRule(options) {
|
||||
return (state, silent) => {
|
||||
const max = state.posMax;
|
||||
const start = state.pos;
|
||||
|
||||
for (const { left, right, display } of options.delimiters) {
|
||||
|
||||
// Check if it starts with the left delimiter
|
||||
if (!state.src.slice(start).startsWith(left)) continue;
|
||||
|
||||
// Skip the length of the left delimiter
|
||||
let pos = start + left.length;
|
||||
|
||||
// Find the matching right delimiter
|
||||
while (pos < max) {
|
||||
if (state.src.slice(pos).startsWith(right)) {
|
||||
break;
|
||||
}
|
||||
pos++;
|
||||
}
|
||||
|
||||
// No matching right delimiter found, skip to the next match
|
||||
if (pos >= max) continue;
|
||||
|
||||
// If not in silent mode, convert LaTeX formula to MathML
|
||||
if (!silent) {
|
||||
const content = state.src.slice(start + left.length, pos);
|
||||
try {
|
||||
const renderedContent = renderLatexHTML(content, display);
|
||||
const token = state.push('html_inline', '', 0);
|
||||
token.content = renderedContent;
|
||||
} catch (e) {
|
||||
console.error(e);
|
||||
}
|
||||
}
|
||||
|
||||
// Update position, skip the length of the right delimiter
|
||||
state.pos = pos + right.length;
|
||||
return true;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export default function (md, options = defaultOptions) {
|
||||
md.inline.ruler.after('text', 'escaped_bracket', escapedBracketRule(options));
|
||||
}
|
||||
@@ -1,8 +1,20 @@
|
||||
import './styles.css';
|
||||
import './styles.scss';
|
||||
import { createApp, defineComponent, shallowRef, computed, h } from 'vue/dist/vue.esm-bundler.js';
|
||||
import MarkdownIt from 'markdown-it';
|
||||
import TextLineStream from 'textlinestream';
|
||||
|
||||
// math formula rendering
|
||||
import 'katex/dist/katex.min.css';
|
||||
import markdownItKatexGpt from './katex-gpt';
|
||||
import markdownItKatexNormal from '@vscode/markdown-it-katex';
|
||||
|
||||
// code highlighting
|
||||
import hljs from './highlight-config';
|
||||
import daisyuiThemes from 'daisyui/src/theming/themes';
|
||||
|
||||
// ponyfill for missing ReadableStream asyncIterator on Safari
|
||||
import { asyncIterator } from "@sec-ant/readable-stream/ponyfill/asyncIterator";
|
||||
|
||||
const isDev = import.meta.env.MODE === 'development';
|
||||
|
||||
// utility functions
|
||||
@@ -13,15 +25,18 @@ const escapeAttr = (str) => str.replace(/>/g, '>').replace(/"/g, '"');
|
||||
const copyStr = (str) => navigator.clipboard.writeText(str);
|
||||
|
||||
// constants
|
||||
const BASE_URL = localStorage.getItem('base') // for debugging
|
||||
|| (new URL('.', document.baseURI).href).toString().replace(/\/$/, ''); // for production
|
||||
const BASE_URL = isDev
|
||||
? (localStorage.getItem('base') || 'https://localhost:8080') // for debugging
|
||||
: (new URL('.', document.baseURI).href).toString().replace(/\/$/, ''); // for production
|
||||
console.log({ BASE_URL });
|
||||
|
||||
const CONFIG_DEFAULT = {
|
||||
// Note: in order not to introduce breaking changes, please keep the same data type (number, string, etc) if you want to change the default value. Do not use null or undefined for default value.
|
||||
apiKey: '',
|
||||
systemMessage: 'You are a helpful assistant.',
|
||||
showTokensPerSecond: false,
|
||||
// make sure these default values are in sync with `common.h`
|
||||
samplers: 'dkypmxt',
|
||||
samplers: 'edkypmxt',
|
||||
temperature: 0.8,
|
||||
dynatemp_range: 0.0,
|
||||
dynatemp_exponent: 1.0,
|
||||
@@ -69,12 +84,39 @@ const CONFIG_INFO = {
|
||||
// config keys having numeric value (i.e. temperature, top_k, top_p, etc)
|
||||
const CONFIG_NUMERIC_KEYS = Object.entries(CONFIG_DEFAULT).filter(e => isNumeric(e[1])).map(e => e[0]);
|
||||
// list of themes supported by daisyui
|
||||
const THEMES = ['light', 'dark', 'cupcake', 'bumblebee', 'emerald', 'corporate', 'synthwave', 'retro', 'cyberpunk', 'valentine', 'halloween', 'garden', 'forest', 'aqua', 'lofi', 'pastel', 'fantasy', 'wireframe', 'black', 'luxury', 'dracula', 'cmyk', 'autumn', 'business', 'acid', 'lemonade', 'night', 'coffee', 'winter', 'dim', 'nord', 'sunset'];
|
||||
const THEMES = ['light', 'dark']
|
||||
// make sure light & dark are always at the beginning
|
||||
.concat(Object.keys(daisyuiThemes).filter(t => t !== 'light' && t !== 'dark'));
|
||||
|
||||
// markdown support
|
||||
const VueMarkdown = defineComponent(
|
||||
(props) => {
|
||||
const md = shallowRef(new MarkdownIt({ breaks: true }));
|
||||
const md = shallowRef(new MarkdownIt({
|
||||
breaks: true,
|
||||
highlight: function (str, lang) { // Add highlight.js
|
||||
if (lang && hljs.getLanguage(lang)) {
|
||||
try {
|
||||
return '<pre><code class="hljs">' +
|
||||
hljs.highlight(str, { language: lang, ignoreIllegals: true }).value +
|
||||
'</code></pre>';
|
||||
} catch (__) {}
|
||||
}
|
||||
return '<pre><code class="hljs">' + md.value.utils.escapeHtml(str) + '</code></pre>';
|
||||
}
|
||||
}));
|
||||
// support latex with double dollar sign and square brackets
|
||||
md.value.use(markdownItKatexGpt, {
|
||||
delimiters: [
|
||||
{ left: '\\[', right: '\\]', display: true },
|
||||
{ left: '\\(', right: '\\)', display: false },
|
||||
{ left: '$$', right: '$$', display: false },
|
||||
// do not add single dollar sign here, other wise it will confused with dollar used for money symbol
|
||||
],
|
||||
throwOnError: false,
|
||||
});
|
||||
// support latex with single dollar sign
|
||||
md.value.use(markdownItKatexNormal, { throwOnError: false });
|
||||
// add copy button to code blocks
|
||||
const origFenchRenderer = md.value.renderer.rules.fence;
|
||||
md.value.renderer.rules.fence = (tokens, idx, ...args) => {
|
||||
const content = tokens[idx].content;
|
||||
@@ -244,7 +286,7 @@ async function* sendSSEPostRequest(url, fetchOptions) {
|
||||
const lines = res.body
|
||||
.pipeThrough(new TextDecoderStream())
|
||||
.pipeThrough(new TextLineStream());
|
||||
for await (const line of lines) {
|
||||
for await (const line of asyncIterator(lines)) {
|
||||
if (isDev) console.log({line});
|
||||
if (line.startsWith('data:') && !line.endsWith('[DONE]')) {
|
||||
const data = JSON.parse(line.slice(5));
|
||||
@@ -278,6 +320,7 @@ const mainApp = createApp({
|
||||
themes: THEMES,
|
||||
configDefault: {...CONFIG_DEFAULT},
|
||||
configInfo: {...CONFIG_INFO},
|
||||
isDev,
|
||||
}
|
||||
},
|
||||
computed: {},
|
||||
@@ -289,6 +332,7 @@ const mainApp = createApp({
|
||||
if (this.isGenerating) chatScrollToBottom(true);
|
||||
});
|
||||
resizeObserver.observe(pendingMsgElem);
|
||||
this.setSelectedTheme(this.selectedTheme);
|
||||
},
|
||||
watch: {
|
||||
viewingConvId: function(val, oldVal) {
|
||||
@@ -305,6 +349,8 @@ const mainApp = createApp({
|
||||
},
|
||||
setSelectedTheme(theme) {
|
||||
this.selectedTheme = theme;
|
||||
document.body.setAttribute('data-theme', theme);
|
||||
document.body.setAttribute('data-color-scheme', daisyuiThemes[theme]?.['color-scheme'] ?? 'auto');
|
||||
StorageUtils.setTheme(theme);
|
||||
},
|
||||
newConversation() {
|
||||
@@ -399,7 +445,7 @@ const mainApp = createApp({
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
'Authorization': this.config.apiKey ? `Bearer ${this.config.apiKey}` : undefined,
|
||||
...(this.config.apiKey ? {'Authorization': `Bearer ${this.config.apiKey}`} : {})
|
||||
},
|
||||
body: JSON.stringify(params),
|
||||
signal: abortController.signal,
|
||||
@@ -513,6 +559,17 @@ const mainApp = createApp({
|
||||
fetchMessages() {
|
||||
this.messages = StorageUtils.getOneConversation(this.viewingConvId)?.messages ?? [];
|
||||
},
|
||||
|
||||
// debug functions
|
||||
async debugImportDemoConv() {
|
||||
const res = await fetch('/demo-conversation.json');
|
||||
const demoConv = await res.json();
|
||||
StorageUtils.remove(demoConv.id);
|
||||
for (const msg of demoConv.messages) {
|
||||
StorageUtils.appendMsg(demoConv.id, msg);
|
||||
}
|
||||
this.fetchConversation();
|
||||
}
|
||||
},
|
||||
});
|
||||
mainApp.config.errorHandler = alert;
|
||||
|
||||
@@ -1,26 +0,0 @@
|
||||
@tailwind base;
|
||||
@tailwind components;
|
||||
@tailwind utilities;
|
||||
|
||||
.markdown {
|
||||
h1, h2, h3, h4, h5, h6, ul, ol, li { all: revert; }
|
||||
pre {
|
||||
@apply whitespace-pre-wrap rounded-lg p-2;
|
||||
border: 1px solid currentColor;
|
||||
}
|
||||
/* TODO: fix markdown table */
|
||||
}
|
||||
|
||||
.show-on-hover {
|
||||
@apply md:opacity-0 md:group-hover:opacity-100;
|
||||
}
|
||||
.btn-mini {
|
||||
@apply cursor-pointer hover:shadow-md;
|
||||
}
|
||||
.chat-screen { max-width: 900px; }
|
||||
|
||||
.chat-bubble-base-300 {
|
||||
--tw-bg-opacity: 1;
|
||||
--tw-text-opacity: 1;
|
||||
@apply bg-base-300 text-base-content;
|
||||
}
|
||||
@@ -0,0 +1,48 @@
|
||||
@use "sass:meta";
|
||||
|
||||
@tailwind base;
|
||||
@tailwind components;
|
||||
@tailwind utilities;
|
||||
|
||||
.markdown {
|
||||
h1, h2, h3, h4, h5, h6, ul, ol, li { all: revert; }
|
||||
pre {
|
||||
@apply whitespace-pre-wrap rounded-lg p-2;
|
||||
border: 1px solid currentColor;
|
||||
}
|
||||
/* TODO: fix markdown table */
|
||||
}
|
||||
|
||||
.show-on-hover {
|
||||
@apply md:opacity-0 md:group-hover:opacity-100;
|
||||
}
|
||||
.btn-mini {
|
||||
@apply cursor-pointer hover:shadow-md;
|
||||
}
|
||||
.chat-screen { max-width: 900px; }
|
||||
|
||||
.chat-bubble-base-300 {
|
||||
--tw-bg-opacity: 1;
|
||||
--tw-text-opacity: 1;
|
||||
@apply bg-base-300 text-base-content;
|
||||
}
|
||||
|
||||
/* Highlight.js */
|
||||
[data-color-scheme='light'] {
|
||||
@include meta.load-css('highlight.js/styles/stackoverflow-light');
|
||||
}
|
||||
[data-color-scheme='dark'] {
|
||||
@include meta.load-css('highlight.js/styles/stackoverflow-dark');
|
||||
}
|
||||
[data-color-scheme='auto'] {
|
||||
@media (prefers-color-scheme: light) {
|
||||
@include meta.load-css('highlight.js/styles/stackoverflow-light');
|
||||
}
|
||||
@media (prefers-color-scheme: dark) {
|
||||
@include meta.load-css('highlight.js/styles/stackoverflow-dark');
|
||||
}
|
||||
}
|
||||
.hljs {
|
||||
background: transparent !important;
|
||||
padding: 0.5em !important;
|
||||
}
|
||||
@@ -2,6 +2,9 @@
|
||||
import { viteSingleFile } from 'vite-plugin-singlefile';
|
||||
import path from 'path';
|
||||
import fs from 'fs';
|
||||
import zlib from 'zlib';
|
||||
|
||||
const MAX_BUNDLE_SIZE = 1.5 * 1024 * 1024; // only increase when absolutely necessary
|
||||
|
||||
const GUIDE_FOR_FRONTEND = `
|
||||
<!--
|
||||
@@ -12,25 +15,45 @@ const GUIDE_FOR_FRONTEND = `
|
||||
-->
|
||||
`.trim();
|
||||
|
||||
export default {
|
||||
plugins: [
|
||||
viteSingleFile(),
|
||||
(function llamaCppPlugin() {
|
||||
let config;
|
||||
return {
|
||||
name: 'llamacpp:build',
|
||||
apply: 'build',
|
||||
async configResolved(_config) {
|
||||
config = _config;
|
||||
},
|
||||
writeBundle() {
|
||||
const outputIndexHtml = path.join(config.build.outDir, 'index.html');
|
||||
const content = fs.readFileSync(outputIndexHtml, 'utf-8');
|
||||
const BUILD_PLUGINS = [
|
||||
viteSingleFile(),
|
||||
(function llamaCppPlugin() {
|
||||
let config;
|
||||
return {
|
||||
name: 'llamacpp:build',
|
||||
apply: 'build',
|
||||
async configResolved(_config) {
|
||||
config = _config;
|
||||
},
|
||||
writeBundle() {
|
||||
const outputIndexHtml = path.join(config.build.outDir, 'index.html');
|
||||
const content = GUIDE_FOR_FRONTEND + '\n' + fs.readFileSync(outputIndexHtml, 'utf-8');
|
||||
const compressed = zlib.gzipSync(Buffer.from(content, 'utf-8'), { level: 9 });
|
||||
|
||||
const targetOutputFile = path.join(config.build.outDir, '../../public/index.html');
|
||||
fs.writeFileSync(targetOutputFile, GUIDE_FOR_FRONTEND + '\n' + content);
|
||||
// because gzip header contains machine-specific info, we must remove these data from the header
|
||||
// timestamp
|
||||
compressed[0x4] = 0;
|
||||
compressed[0x5] = 0;
|
||||
compressed[0x6] = 0;
|
||||
compressed[0x7] = 0;
|
||||
// OS
|
||||
compressed[0x9] = 0;
|
||||
|
||||
if (compressed.byteLength > MAX_BUNDLE_SIZE) {
|
||||
throw new Error(
|
||||
`Bundle size is too large (${Math.ceil(compressed.byteLength / 1024)} KB).\n` +
|
||||
`Please reduce the size of the frontend or increase MAX_BUNDLE_SIZE in vite.config.js.\n`,
|
||||
);
|
||||
}
|
||||
|
||||
const targetOutputFile = path.join(config.build.outDir, '../../public/index.html.gz');
|
||||
fs.writeFileSync(targetOutputFile, compressed);
|
||||
}
|
||||
})(),
|
||||
],
|
||||
}
|
||||
})(),
|
||||
];
|
||||
|
||||
/** @type {import('vite').UserConfig} */
|
||||
export default {
|
||||
plugins: process.env.ANALYZE ? [] : BUILD_PLUGINS,
|
||||
};
|
||||
|
||||
Reference in New Issue
Block a user