mirror of
https://github.com/aaronpo97/the-biergarten-app.git
synced 2026-06-01 01:54:00 +00:00
refactor(pipeline): restructure config, add PromptDirectory, consolidate SQLite layer (#217)
* Refactor ApplicationOptions to separate config concerns * add prompt dir app option * readability updates: remove magic numbers, update comments * codebase formatting * Update docs * Extract argument parsing, timer out of
This commit is contained in:
@@ -9,6 +9,7 @@
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#include <boost/di.hpp>
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#include <boost/program_options.hpp>
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#include <chrono>
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#include <cstdint>
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#include <exception>
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#include <memory>
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#include <optional>
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@@ -23,127 +24,14 @@
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#include "llama_backend_state.h"
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#include "services/enrichment_service.h"
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#include "services/export_service.h"
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#include "services/prompt_directory.h"
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#include "services/sqlite_export_service.h"
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#include "services/timer.h"
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#include "services/wikipedia_service.h"
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#include "web_client/curl_web_client.h"
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namespace prog_opts = boost::program_options;
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namespace di = boost::di;
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/**
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* @brief Parse command-line arguments into ApplicationOptions.
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*
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* @param argc Command-line argument count.
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* @param argv Command-line arguments.
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* @return Parsed ApplicationOptions if parsing succeeded, std::nullopt
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* otherwise.
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*/
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std::optional<ApplicationOptions> ParseArguments(const int argc, char** argv) {
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prog_opts::options_description desc("Pipeline Options");
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auto opt = desc.add_options();
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opt("help,h", "Produce help message");
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opt("mocked", prog_opts::bool_switch(),
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"Use mocked generator for brewery/user data");
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opt("model,m", prog_opts::value<std::string>()->default_value(""),
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"Path to LLM model (gguf)");
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opt("temperature", prog_opts::value<float>()->default_value(1.0F),
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"Sampling temperature (higher = more random)");
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opt("top-p", prog_opts::value<float>()->default_value(0.95F),
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"Nucleus sampling top-p in (0,1] (higher = more random)");
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opt("top-k", prog_opts::value<uint32_t>()->default_value(64),
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"Top-k sampling parameter (higher = more candidate tokens)");
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opt("n-ctx", prog_opts::value<uint32_t>()->default_value(8192),
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"Context window size in tokens (1-32768)");
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opt("seed", prog_opts::value<int>()->default_value(-1),
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"Sampler seed: -1 for random, otherwise non-negative integer");
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// Handle the "no arguments" or "help" case
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if (argc == 1) {
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spdlog::info("Biergarten Pipeline");
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std::stringstream usage_stream;
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usage_stream << "\nUsage: biergarten-pipeline [options]\n\n" << desc;
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spdlog::info(usage_stream.str());
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return std::nullopt;
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}
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try {
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prog_opts::variables_map variables_map;
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prog_opts::store(prog_opts::parse_command_line(argc, argv, desc),
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variables_map);
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prog_opts::notify(variables_map);
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if (variables_map.contains("help")) {
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std::stringstream help_stream;
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help_stream << "\n" << desc;
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spdlog::info(help_stream.str());
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return std::nullopt;
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}
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const auto use_mocked = variables_map["mocked"].as<bool>();
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const auto model_path = variables_map["model"].as<std::string>();
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if (use_mocked && !model_path.empty()) {
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spdlog::error(
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"Invalid arguments: --mocked and --model are mutually exclusive");
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return std::nullopt;
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}
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if (!use_mocked && model_path.empty()) {
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spdlog::error(
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"Invalid arguments: Either --mocked or --model must be specified");
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return std::nullopt;
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}
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const bool has_llm_params = !variables_map["temperature"].defaulted() ||
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!variables_map["top-p"].defaulted() ||
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!variables_map["top-k"].defaulted() ||
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!variables_map["seed"].defaulted();
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if (use_mocked && has_llm_params) {
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spdlog::warn(
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"Sampling parameters (--temperature, --top-p, --top-k, --seed) are"
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" ignored when using --mocked");
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}
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ApplicationOptions options;
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options.use_mocked = use_mocked;
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options.model_path = model_path;
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options.temperature = variables_map["temperature"].as<float>();
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options.top_p = variables_map["top-p"].as<float>();
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options.top_k = variables_map["top-k"].as<uint32_t>();
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options.n_ctx = variables_map["n-ctx"].as<uint32_t>();
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options.seed = variables_map["seed"].as<int>();
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return options;
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} catch (const std::exception& exception) {
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spdlog::error("Failed to parse command-line arguments: {}",
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exception.what());
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return std::nullopt;
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} catch (...) {
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spdlog::error("Failed to parse command-line arguments: unknown error");
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return std::nullopt;
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}
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}
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struct Timer {
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std::chrono::steady_clock::time_point start_time =
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std::chrono::steady_clock::now();
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[[nodiscard]] int64_t Elapsed() const {
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return std::chrono::duration_cast<std::chrono::milliseconds>(
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std::chrono::steady_clock::now() - start_time)
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.count();
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}
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};
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int main(const int argc, char** argv) {
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try {
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Timer timer;
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@@ -157,6 +45,20 @@ int main(const int argc, char** argv) {
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}
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const auto options = *parsed_options;
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const std::string model_path = options.generator.model_path.string();
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const auto sampling =
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options.generator.sampling.value_or(SamplingOptions{});
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std::unique_ptr<IPromptDirectory> prompt_directory;
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if (!options.generator.use_mocked) {
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try {
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prompt_directory =
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std::make_unique<PromptDirectory>(options.pipeline.prompt_dir);
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} catch (const std::exception& dir_error) {
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spdlog::error("[Startup] Invalid --prompt-dir: {}", dir_error.what());
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return 1;
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}
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}
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const auto injector = di::make_injector(
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di::bind<WebClient>().to<CURLWebClient>(),
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@@ -164,10 +66,11 @@ int main(const int argc, char** argv) {
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di::bind<IEnrichmentService>().to<WikipediaService>(),
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di::bind<IExportService>().to<SqliteExportService>(),
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di::bind<IPromptFormatter>().to<Gemma4JinjaPromptFormatter>(),
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di::bind<std::string>().to(options.model_path),
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di::bind<std::string>().to(model_path),
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di::bind<DataGenerator>().to(
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[options](const auto& inj) -> std::unique_ptr<DataGenerator> {
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if (options.use_mocked) {
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[options, model_path, sampling, &prompt_directory](
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const auto& inj) -> std::unique_ptr<DataGenerator> {
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if (options.generator.use_mocked) {
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spdlog::info(
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"[Generator] Using MockGenerator (no model path provided)");
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return std::make_unique<MockGenerator>();
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@@ -176,9 +79,12 @@ int main(const int argc, char** argv) {
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spdlog::info(
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"[Generator] Using LlamaGenerator: {} (temperature={}, "
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"top-p={}, top-k={}, n_ctx={}, seed={})",
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options.model_path, options.temperature, options.top_p,
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options.top_k, options.n_ctx, options.seed);
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return inj.template create<std::unique_ptr<LlamaGenerator>>();
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model_path, sampling.temperature, sampling.top_p,
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sampling.top_k, sampling.n_ctx, sampling.seed);
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return std::make_unique<LlamaGenerator>(
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options, model_path,
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inj.template create<std::unique_ptr<IPromptFormatter>>(),
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std::move(prompt_directory));
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}));
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auto generator =
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