Create biergarten brewery pipeline project (#199)

This commit is contained in:
Aaron Po
2026-04-18 19:19:14 -04:00
committed by GitHub
parent fd3c172e35
commit 898cc8971b
59 changed files with 5638 additions and 0 deletions

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/**
* @file biergarten_data_generator/biergarten_data_generator.cc
* @brief BiergartenDataGenerator constructor implementation.
*/
#include "biergarten_data_generator.h"
#include <utility>
BiergartenDataGenerator::BiergartenDataGenerator(
std::unique_ptr<IEnrichmentService> context_service,
std::unique_ptr<DataGenerator> generator)
: context_service_(std::move(context_service)),
generator_(std::move(generator)) {}

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/**
* @file biergarten_data_generator/generate_breweries.cc
* @brief BiergartenDataGenerator::GenerateBreweries() implementation.
*/
#include <spdlog/spdlog.h>
#include "biergarten_data_generator.h"
void BiergartenDataGenerator::GenerateBreweries(
std::span<const EnrichedCity> cities) {
spdlog::info("\n=== SAMPLE BREWERY GENERATION ===");
generated_breweries_.clear();
size_t skipped_count = 0;
for (const auto& [location, region_context] : cities) {
try {
const BreweryResult brewery =
generator_->GenerateBrewery(location, region_context);
const GeneratedBrewery gen{.location = location, .brewery = brewery};
generated_breweries_.push_back(gen);
} catch (const std::exception& e) {
++skipped_count;
spdlog::warn(
"[Pipeline] Skipping city '{}' ({}): brewery generation failed: "
"{}",
location.city, location.country, e.what());
}
}
if (skipped_count > 0) {
spdlog::warn("[Pipeline] Skipped {} city/cities due to generation errors",
skipped_count);
}
}

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/**
* @file biergarten_data_generator/log_results.cc
* @brief BiergartenDataGenerator::LogResults() implementation.
*/
#include <spdlog/spdlog.h>
#include "biergarten_data_generator.h"
void BiergartenDataGenerator::LogResults() const {
spdlog::info("\n=== GENERATED DATA DUMP ===");
size_t index = 1;
for (const auto& [location, brewery] : generated_breweries_) {
spdlog::info(
"{}. city=\"{}\" country=\"{}\" state=\"{}\" "
"iso3166_2={} lat={} lon={}",
index, location.city, location.country, location.state_province,
location.iso3166_2, location.latitude, location.longitude);
spdlog::info(" brewery_name_en=\"{}\"", brewery.name_en);
spdlog::info(" brewery_description_en=\"{}\"",
brewery.description_en);
spdlog::info(" brewery_name_local=\"{}\"", brewery.name_local);
spdlog::info(" brewery_description_local=\"{}\"",
brewery.description_local);
++index;
}
}

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/**
* @file biergarten_data_generator/query_cities_with_countries.cc
* @brief BiergartenDataGenerator::QueryCitiesWithCountries() implementation.
*/
#include <spdlog/spdlog.h>
#include <algorithm>
#include <filesystem>
#include <iterator>
#include <random>
#include "biergarten_data_generator.h"
#include "json_handling/json_loader.h"
static constexpr size_t kBreweryAmount = 50;
std::vector<Location> BiergartenDataGenerator::QueryCitiesWithCountries() {
spdlog::info("\n=== GEOGRAPHIC DATA OVERVIEW ===");
const std::filesystem::path locations_path = "locations.json";
auto all_locations = JsonLoader::LoadLocations(locations_path);
spdlog::info(" Locations available: {}", all_locations.size());
const size_t sample_count = std::min(kBreweryAmount, all_locations.size());
const auto sample_count_signed =
static_cast<std::iter_difference_t<decltype(all_locations.cbegin())>>(
sample_count);
std::vector<Location> sampled_locations;
sampled_locations.reserve(sample_count);
std::random_device random_generator;
std::ranges::sample(all_locations, std::back_inserter(sampled_locations),
sample_count_signed, random_generator);
spdlog::info(" Sampled locations: {}", sampled_locations.size());
return sampled_locations;
}

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/**
* @file biergarten_data_generator/run.cc
* @brief BiergartenDataGenerator::Run() implementation.
*/
#include <utility>
#include <spdlog/spdlog.h>
#include "biergarten_data_generator.h"
bool BiergartenDataGenerator::Run() {
try {
std::vector<Location> cities = QueryCitiesWithCountries();
std::vector<EnrichedCity> enriched;
enriched.reserve(cities.size());
size_t skipped_count = 0;
for (auto& city : cities) {
try {
std::string region_context = context_service_->GetLocationContext(city);
spdlog::debug("[Pipeline] Context for '{}' ({}) gathered:\n{}",
city.city, city.country, region_context);
enriched.push_back(
EnrichedCity{.location = std::move(city),
.region_context = std::move(region_context)});
} catch (const std::exception& exception) {
++skipped_count;
spdlog::warn(
"[Pipeline] Skipping city '{}' ({}): context lookup failed: {}",
city.city, city.country, exception.what());
}
}
if (skipped_count > 0) {
spdlog::warn(
"[Pipeline] Skipped {} city/cities due to context lookup errors",
skipped_count);
}
this->GenerateBreweries(enriched);
this->LogResults();
return true;
} catch (const std::exception& e) {
spdlog::error("Pipeline execution failed with error: {}", e.what());
return false;
}
}

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/**
* @file data_generation/llama/generate_brewery.cc
* @brief Builds brewery prompts with regional context, performs retry-based
* inference, and validates structured JSON output for brewery records.
*/
#include <spdlog/spdlog.h>
#include <format>
#include <optional>
#include <stdexcept>
#include <string>
#include <string_view>
#include <vector>
#include "data_generation/llama_generator.h"
#include "data_generation/llama_generator_helpers.h"
static std::string FormatLocalLanguageCodes(
const std::vector<std::string>& codes) {
if (codes.empty()) {
return "Not provided";
}
std::string formatted;
for (const std::string& code : codes) {
if (!formatted.empty()) {
formatted += ", ";
}
formatted += code;
}
return formatted;
}
static constexpr std::string_view kBreweryJsonGrammar = R"json_brewery(
root ::= thought-block "{" ws "\"name_en\"" ws ":" ws string ws "," ws "\"description_en\"" ws ":" ws string ws "," ws "\"name_local\"" ws ":" ws string ws "," ws "\"description_local\"" ws ":" ws string ws "}" ws
thought-block ::= [^{]*
ws ::= [ \t\n\r]*
string ::= "\"" char+ "\""
char ::= [^"\\\x7F\x00-\x1F] | [\\] escape
escape ::= ["\\/bfnrt] | "u" hex hex hex hex
hex ::= [0-9a-fA-F]
)json_brewery";
static constexpr int kBreweryInitialMaxTokens = 2800;
BreweryResult LlamaGenerator::GenerateBrewery(
const Location& location, const std::string& region_context) {
/**
* Preprocess and truncate region context to manageable size
*/
const std::string safe_region_context = PrepareRegionContext(region_context);
const std::string local_language_codes =
FormatLocalLanguageCodes(location.local_languages);
const std::string country_suffix =
location.country.empty() ? std::string{}
: std::format(", {}", location.country);
/**
* Load brewery system prompt from file
* Falls back to minimal inline prompt if file not found
*/
const std::string system_prompt =
LoadBrewerySystemPrompt("prompts/system.md");
std::string user_prompt = std::format(
"## CITY:\n{}\n\n## COUNTRY:\n{}\n\n## LOCAL LANGUAGE CODES:\n{}\n\n## "
"CONTEXT:\n{}",
location.city, location.country, local_language_codes,
safe_region_context);
/**
* Store location context for retry prompts (without repeating full context)
*/
const std::string retry_location =
std::format("Location: {}{}\nLocal language codes: {}", location.city,
country_suffix, local_language_codes);
/**
* RETRY LOOP with validation and error correction
* Attempts to generate valid brewery data up to 3 times, with feedback-based
* refinement
*/
constexpr int max_attempts = 3;
std::string raw;
std::string last_error;
// Token budget: too small risks truncating valid JSON mid-string.
// Start conservatively but allow adaptive increases on truncation.
int max_tokens = kBreweryInitialMaxTokens;
// Limit output length to keep it concise and focused
for (int attempt = 0; attempt < max_attempts; ++attempt) {
// Generate brewery data from LLM
raw = this->Infer(system_prompt, user_prompt, max_tokens,
kBreweryJsonGrammar);
spdlog::debug("LlamaGenerator: raw output (attempt {}): {}", attempt + 1,
raw);
// Validate output: parse JSON and check required fields
BreweryResult brewery;
const std::optional<std::string> validation_error =
ValidateBreweryJson(raw, brewery);
if (!validation_error.has_value()) {
// Success: return parsed brewery data
spdlog::info(
"LlamaGenerator: successfully generated brewery data on attempt {}",
attempt + 1);
return brewery;
}
// Validation failed: log error and prepare corrective feedback
last_error = *validation_error;
spdlog::warn("LlamaGenerator: malformed brewery JSON (attempt {}): {}",
attempt + 1, *validation_error);
// Update prompt with error details to guide LLM toward correct output.
user_prompt = std::format(
"Your previous response was invalid. Error: {}\nReturn the thought "
"process before the JSON if needed, then return ONLY valid JSON with "
"exactly these keys, in this exact order: {{\"name_en\": \"<English "
"brewery name>\", \"description_en\": \"<English single-paragraph "
"description>\", \"name_local\": \"<local-language brewery name>\", "
"\"description_local\": \"<local-language single-paragraph "
"description>\"}}.\nDo not include markdown, comments, extra keys, or "
"literal placeholder values.\n\nKeep the JSON strings concise enough "
"to fit within the token budget.\n\n{}",
*validation_error, retry_location);
}
// All retry attempts exhausted: log failure and throw exception
spdlog::error(
"LlamaGenerator: malformed brewery response after {} attempts: "
"{}",
max_attempts, last_error.empty() ? raw : last_error);
throw std::runtime_error("LlamaGenerator: malformed brewery response");
}

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/**
* @file data_generation/llama/generate_user.cc
* @brief Generates locale-aware user profiles with strict two-line formatting,
* retry handling, and output sanitization for downstream parsing.
*/
#include <spdlog/spdlog.h>
#include <stdexcept>
#include <string>
#include "data_generation/llama_generator.h"
#include "data_generation/llama_generator_helpers.h"
UserResult LlamaGenerator::GenerateUser(const std::string& locale) {
return {.username = "test_user",
.bio = "This is a test user profile from " + locale + "."};
}

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/**
* @file data_generation/llama/helpers.cc
* @brief Provides prompt formatting, whitespace normalization, response
* parsing, token decoding, and JSON validation helpers for Llama modules.
*/
#include <algorithm>
#include <array>
#include <boost/json.hpp>
#include <cctype>
#include <optional>
#include <stdexcept>
#include <string>
#include <string_view>
#include <vector>
#include "data_generation/llama_generator_helpers.h"
#include "llama.h"
/**
* String trimming: removes leading and trailing whitespace
*/
static std::string Trim(std::string_view value) {
constexpr std::string_view whitespace = " \t\n\r\f\v";
const size_t first_index = value.find_first_not_of(whitespace);
if (first_index == std::string_view::npos) {
return {};
}
const size_t last_index = value.find_last_not_of(whitespace);
return std::string(value.substr(first_index, last_index - first_index + 1));
}
/**
* Normalize whitespace: collapses multiple spaces/tabs/newlines into single
* spaces
*/
static std::string CondenseWhitespace(std::string_view text) {
std::string out;
out.reserve(text.size());
bool pending_space = false;
for (const char chr : text) {
if (std::isspace(static_cast<unsigned char>(chr)) != 0) {
if (!out.empty()) {
pending_space = true;
}
continue;
}
if (pending_space) {
out.push_back(' ');
pending_space = false;
}
out.push_back(chr);
}
return out;
}
/**
* Truncate region context to fit within max length while preserving word
* boundaries
*/
std::string PrepareRegionContext(std::string_view region_context,
const size_t max_chars) {
std::string normalized = CondenseWhitespace(region_context);
if (normalized.size() <= max_chars) {
return normalized;
}
normalized.resize(max_chars);
const size_t last_space = normalized.find_last_of(' ');
if (last_space != std::string::npos && last_space > max_chars / 2) {
normalized.resize(last_space);
}
normalized += "...";
return normalized;
}
void AppendTokenPiece(const llama_vocab* vocab, llama_token token,
std::string& output) {
constexpr size_t initial_buffer_size = 256;
std::array<char, initial_buffer_size> buffer{};
// serialize the sampled token into UTF-8 bytes
auto buffer_too_small = [](int32_t result) -> bool { return result < 0; };
int32_t bytes =
llama_token_to_piece(vocab, token, buffer.data(), buffer.size(), 0, true);
if (!buffer_too_small(bytes)) {
// Append the decoded bytes from the stack buffer.
output.append(buffer.data(), static_cast<size_t>(bytes));
return;
}
const int32_t required_size = -bytes;
std::vector<char> dynamic_buffer(static_cast<size_t>(required_size));
// Retry token decoding against the larger heap buffer.
bytes = llama_token_to_piece(vocab, token, dynamic_buffer.data(),
static_cast<int32_t>(dynamic_buffer.size()), 0,
true);
if (!buffer_too_small(bytes)) {
output.append(dynamic_buffer.data(), static_cast<size_t>(bytes));
return;
}
throw std::runtime_error(
"LlamaGenerator: failed to decode sampled token piece");
}
static bool ReadRequiredTrimmedStringField(const boost::json::object& obj,
std::string_view key,
std::string& out,
std::string* error_out) {
const boost::json::value* field = obj.if_contains(key);
if (field == nullptr || !field->is_string()) {
if (error_out != nullptr) {
*error_out = "JSON field '" + std::string(key) +
"' is missing or not a string";
}
return false;
}
const auto& string_value = field->as_string();
out = Trim(std::string_view(string_value.data(), string_value.size()));
if (out.empty()) {
if (error_out != nullptr) {
*error_out = "JSON field '" + std::string(key) + "' must not be empty";
}
return false;
}
return true;
}
static bool HasSchemaPlaceholder(const std::array<std::string*, 4>& values) {
for (const std::string* value : values) {
std::string lowered = *value;
std::ranges::transform(lowered, lowered.begin(),
[](unsigned char character) {
return static_cast<char>(std::tolower(character));
});
if (lowered == "string") {
return true;
}
}
return false;
}
std::optional<std::string> ValidateBreweryJson(const std::string& raw,
BreweryResult& brewery_out) {
boost::system::error_code error_code;
const std::string_view raw_view(raw);
const size_t opening_brace = raw_view.find('{');
if (opening_brace == std::string_view::npos) {
return "JSON parse error: missing opening brace '{'";
}
const std::string_view json_payload = raw_view.substr(opening_brace);
boost::json::value json_value = boost::json::parse(json_payload, error_code);
if (error_code) {
return "JSON parse error: " + error_code.message();
}
if (!json_value.is_object()) {
return "JSON root must be an object";
}
const auto& obj = json_value.get_object();
if (obj.size() != 4) {
return "JSON object must contain exactly four keys";
}
std::string validation_error;
if (!ReadRequiredTrimmedStringField(obj, "name_en", brewery_out.name_en,
&validation_error)) {
return validation_error;
}
if (!ReadRequiredTrimmedStringField(obj, "description_en",
brewery_out.description_en,
&validation_error)) {
return validation_error;
}
if (!ReadRequiredTrimmedStringField(obj, "name_local",
brewery_out.name_local,
&validation_error)) {
return validation_error;
}
if (!ReadRequiredTrimmedStringField(obj, "description_local",
brewery_out.description_local,
&validation_error)) {
return validation_error;
}
const std::array<std::string*, 4> schema_placeholders = {
&brewery_out.name_en, &brewery_out.description_en,
&brewery_out.name_local, &brewery_out.description_local};
if (HasSchemaPlaceholder(schema_placeholders)) {
return "JSON appears to be a schema placeholder, not content";
}
return std::nullopt;
}

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/**
* Text Generation / Inference Module
* Core module that performs LLM inference: converts text prompts into tokens,
* runs the neural network forward pass, samples the next token, and converts
* output tokens back to text for system+user chat prompts.
*/
#include <spdlog/spdlog.h>
#include <algorithm>
#include <memory>
#include <stdexcept>
#include <string>
#include <string_view>
#include <vector>
#include "data_generation/llama_generator.h"
#include "data_generation/llama_generator_helpers.h"
#include "llama.h"
static constexpr size_t kPromptTokenSlack = 8;
namespace {
using SamplerHandle = std::unique_ptr<llama_sampler, decltype(&llama_sampler_free)>;
struct SamplerConfig {
float temperature;
uint32_t top_k;
float top_p;
uint32_t seed;
};
SamplerHandle MakeSamplerChain(const llama_vocab* vocab,
const SamplerConfig& config,
std::string_view grammar) {
const llama_sampler_chain_params sampler_params =
llama_sampler_chain_default_params();
SamplerHandle chain(llama_sampler_chain_init(sampler_params),
llama_sampler_free);
if (!chain) {
throw std::runtime_error("LlamaGenerator: failed to initialize sampler");
}
auto add_sampler = [&](llama_sampler* sampler, const char* error_message) {
if (sampler == nullptr) {
throw std::runtime_error(error_message);
}
llama_sampler_chain_add(chain.get(), sampler);
};
if (!grammar.empty()) {
const std::string grammar_text(grammar);
add_sampler(llama_sampler_init_grammar(vocab, grammar_text.c_str(), "root"),
"LlamaGenerator: failed to initialize grammar sampler");
}
add_sampler(llama_sampler_init_temp(config.temperature),
"LlamaGenerator: failed to initialize temperature sampler");
add_sampler(llama_sampler_init_top_k(static_cast<int32_t>(config.top_k)),
"LlamaGenerator: failed to initialize top-k sampler");
add_sampler(llama_sampler_init_top_p(config.top_p, 1),
"LlamaGenerator: failed to initialize top-p sampler");
add_sampler(llama_sampler_init_dist(config.seed),
"LlamaGenerator: failed to initialize distribution sampler");
return chain;
}
} // namespace
std::string LlamaGenerator::Infer(const std::string& system_prompt,
const std::string& prompt,
const int max_tokens,
std::string_view grammar) {
return InferFormatted(prompt_formatter_->Format(system_prompt, prompt),
max_tokens, grammar);
}
std::string LlamaGenerator::InferFormatted(const std::string& formatted_prompt,
const int max_tokens,
std::string_view grammar) {
/**
* Validate that model and context are loaded
*/
if (!model_ || !context_) {
throw std::runtime_error("LlamaGenerator: model not loaded");
}
/**
* Get vocabulary for tokenization and token-to-text conversion
*/
const llama_vocab* vocab = llama_model_get_vocab(model_.get());
if (vocab == nullptr) {
throw std::runtime_error("LlamaGenerator: vocab unavailable");
}
const SamplerConfig sampler_config{
.temperature = sampling_temperature_,
.top_k = sampling_top_k_,
.top_p = sampling_top_p_,
.seed = static_cast<uint32_t>(rng_()),
};
auto sampler = MakeSamplerChain(vocab, sampler_config, grammar);
/**
* Clear KV cache to ensure clean inference state (no residual context)
*/
llama_memory_clear(llama_get_memory(context_.get()), true);
/**
* TOKENIZATION PHASE
* Convert text prompt into token IDs (integers) that the model understands
*/
std::vector<llama_token> prompt_tokens(formatted_prompt.size() +
kPromptTokenSlack);
int32_t token_count = llama_tokenize(
vocab,
formatted_prompt.c_str(),
static_cast<int32_t>(formatted_prompt.size()),
prompt_tokens.data(),
static_cast<int32_t>(prompt_tokens.size()),
true,
true);
/**
* If buffer too small, negative return indicates required size
*/
if (token_count < 0) {
prompt_tokens.resize(static_cast<size_t>(-token_count));
token_count = llama_tokenize(
vocab, formatted_prompt.c_str(),
static_cast<int32_t>(formatted_prompt.size()), prompt_tokens.data(),
static_cast<int32_t>(prompt_tokens.size()), true, true);
}
if (token_count < 0) {
throw std::runtime_error("LlamaGenerator: prompt tokenization failed");
}
/**
* CONTEXT SIZE VALIDATION
* Validate and compute effective token budgets based on context window
* constraints
*/
const auto n_ctx = static_cast<int32_t>(llama_n_ctx(context_.get()));
const auto n_batch = static_cast<int32_t>(llama_n_batch(context_.get()));
if (n_ctx <= 1 || n_batch <= 0) {
throw std::runtime_error("LlamaGenerator: invalid context or batch size");
}
/**
* Clamp generation limit to available context window, reserve space for
* output
*/
const int32_t effective_max_tokens =
std::max(1, std::min(max_tokens, n_ctx - 1));
/**
* Prompt can use remaining context after reserving space for generation
*/
int32_t prompt_budget = std::min(n_batch, n_ctx - effective_max_tokens);
prompt_budget = std::max<int32_t>(1, prompt_budget);
/**
* Truncate prompt if necessary to fit within constraints
*/
prompt_tokens.resize(static_cast<size_t>(token_count));
if (token_count > prompt_budget) {
spdlog::warn(
"LlamaGenerator: prompt too long ({} tokens), truncating to {} "
"tokens to fit n_batch/n_ctx limits",
token_count, prompt_budget);
prompt_tokens.resize(static_cast<size_t>(prompt_budget));
token_count = prompt_budget;
}
/**
* PROMPT PROCESSING PHASE
* Create a batch containing all prompt tokens and feed through the model
* This computes internal representations and fills the KV cache
*/
const llama_batch prompt_batch = llama_batch_get_one(
prompt_tokens.data(), static_cast<int32_t>(prompt_tokens.size()));
if (llama_decode(context_.get(), prompt_batch) != 0) {
throw std::runtime_error("LlamaGenerator: prompt decode failed");
}
/**
* TOKEN GENERATION LOOP
* Iteratively generate tokens one at a time until max_tokens or
* end-of-sequence
*/
std::vector<llama_token> generated_tokens;
generated_tokens.reserve(static_cast<size_t>(effective_max_tokens));
for (int i = 0; i < effective_max_tokens; ++i) {
/**
* Sample next token using configured sampler chain and model logits
* Index -1 means use the last output position from previous batch
*/
const llama_token next =
llama_sampler_sample(sampler.get(), context_.get(), -1);
/**
* Stop if model predicts end-of-generation token (EOS/EOT)
*/
if (llama_vocab_is_eog(vocab, next)) {
break;
}
generated_tokens.push_back(next);
/**
* Feed the sampled token back into model for next iteration
* (autoregressive)
*/
llama_token decode_token = next;
const llama_batch one_token_batch = llama_batch_get_one(&decode_token, 1);
if (llama_decode(context_.get(), one_token_batch) != 0) {
throw std::runtime_error(
"LlamaGenerator: decode failed during generation");
}
}
/**
* DETOKENIZATION PHASE
* Convert generated token IDs back to text using vocabulary
*/
std::string output;
for (const llama_token token : generated_tokens) {
AppendTokenPiece(vocab, token, output);
}
return output;
}

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/**
* @file data_generation/llama/llama_generator.cc
* @brief LlamaGenerator constructor and destructor implementation.
*/
#include "data_generation/llama_generator.h"
#include <memory>
#include <random>
#include <stdexcept>
#include <string>
#include <filesystem>
#include "data_model/application_options.h"
#include "llama.h"
static constexpr uint32_t kMaxContextSize = 32768U;
void LlamaGenerator::ModelDeleter::operator()(
llama_model* model) const noexcept {
if (model != nullptr) {
llama_model_free(model);
}
}
void LlamaGenerator::ContextDeleter::operator()(
llama_context* context) const noexcept {
if (context != nullptr) {
llama_free(context);
}
}
LlamaGenerator::LlamaGenerator(const ApplicationOptions& options,
const std::string& model_path,
std::unique_ptr<IPromptFormatter> prompt_formatter)
: rng_(std::random_device{}()),
prompt_formatter_(std::move(prompt_formatter)) {
if (model_path.empty()) {
throw std::runtime_error("LlamaGenerator: model path must not be empty");
}
if (!prompt_formatter_) {
throw std::runtime_error(
"LlamaGenerator: prompt formatter dependency must not be null");
}
if (options.temperature < 0.0F) {
throw std::runtime_error(
"LlamaGenerator: sampling temperature must be >= 0");
}
if (options.top_p <= 0.0F || options.top_p > 1.0F) {
throw std::runtime_error(
"LlamaGenerator: sampling top-p must be in (0, 1]");
}
if (options.top_k == 0U) {
throw std::runtime_error("LlamaGenerator: sampling top-k must be > 0");
}
if (options.seed < -1) {
throw std::runtime_error(
"LlamaGenerator: seed must be >= 0, or -1 for random");
}
if (options.n_ctx == 0 || options.n_ctx > kMaxContextSize) {
throw std::runtime_error(
"LlamaGenerator: context size must be in range [1, 32768]");
}
sampling_temperature_ = options.temperature;
sampling_top_p_ = options.top_p;
sampling_top_k_ = options.top_k;
if (options.seed == -1) {
std::random_device random_device;
rng_.seed(random_device());
} else {
rng_.seed(static_cast<uint32_t>(options.seed));
}
n_ctx_ = options.n_ctx;
this->Load(model_path);
}
LlamaGenerator::~LlamaGenerator() = default;

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/**
* @file data_generation/llama/load.cc
* @brief Initializes llama backend, loads model weights, creates inference
* context, and resets prior resources during model initialization.
*/
#include <spdlog/spdlog.h>
#include <algorithm>
#include <stdexcept>
#include <string>
#include <utility>
#include "data_generation/llama_generator.h"
#include "llama.h"
void LlamaGenerator::Load(const std::string& model_path) {
context_.reset();
model_.reset();
const llama_model_params model_params = llama_model_default_params();
LlamaGenerator::ModelHandle loaded_model(
llama_model_load_from_file(model_path.c_str(), model_params));
if (!loaded_model) {
throw std::runtime_error(
"LlamaGenerator: failed to load model from path: " + model_path);
}
llama_context_params context_params = llama_context_default_params();
context_params.n_ctx = n_ctx_;
context_params.n_batch = std::min(n_ctx_, static_cast<uint32_t>(5000));
LlamaGenerator::ContextHandle loaded_context(
llama_init_from_model(loaded_model.get(), context_params));
if (!loaded_context) {
throw std::runtime_error("LlamaGenerator: failed to create context");
}
model_ = std::move(loaded_model);
context_ = std::move(loaded_context);
spdlog::info("[LlamaGenerator] Loaded model: {}", model_path);
}

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/**
* @file data_generation/llama/load_brewery_prompt.cc
* @brief Resolves brewery system prompt content from cache or a configured
* filesystem path and provides a robust inline fallback prompt when absent.
*/
#include <spdlog/spdlog.h>
#include <filesystem>
#include <fstream>
#include <stdexcept>
#include "data_generation/llama_generator.h"
/**
* @brief Loads brewery system prompt from disk or cache.
*
* @param prompt_file_path Preferred prompt file location.
* @return Prompt text loaded from disk.
*/
std::string LlamaGenerator::LoadBrewerySystemPrompt(
const std::filesystem::path& prompt_file_path) {
// Return cached version if already loaded
if (!brewery_system_prompt_.empty()) {
return brewery_system_prompt_;
}
std::ifstream prompt_file(prompt_file_path);
if (!prompt_file.is_open()) {
spdlog::error(
"LlamaGenerator: Failed to open brewery system prompt file '{}'",
prompt_file_path.string());
throw std::runtime_error(
"LlamaGenerator: missing brewery system prompt file: " +
prompt_file_path.string());
}
const std::string prompt((std::istreambuf_iterator(prompt_file)),
std::istreambuf_iterator<char>());
prompt_file.close();
if (prompt.empty()) {
spdlog::error("LlamaGenerator: Brewery system prompt file '{}' is empty",
prompt_file_path.string());
throw std::runtime_error(
"LlamaGenerator: empty brewery system prompt file: " +
prompt_file_path.string());
}
spdlog::info(
"LlamaGenerator: Loaded brewery system prompt from '{}' ({} chars)",
prompt_file_path.string(), prompt.length());
brewery_system_prompt_ = prompt;
return brewery_system_prompt_;
}

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/**
* @file data_generation/mock/deterministic_hash.cc
* @brief Implements a stable hash combiner used by MockGenerator to derive
* repeatable pseudo-random indices from location input.
*/
#include <boost/container_hash/hash.hpp>
#include "data_generation/mock_generator.h"
size_t MockGenerator::DeterministicHash(const Location& location) {
size_t seed = 0;
boost::hash_combine(seed, location.city);
boost::hash_combine(seed, location.country);
return seed;
}

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/**
* @file data_generation/mock/generate_brewery.cc
* @brief Builds deterministic brewery names and descriptions by hashing city
* and country into fixed mock phrase catalogs.
*/
#include <format>
#include <string>
#include <string_view>
#include "data_generation/mock_generator.h"
BreweryResult MockGenerator::GenerateBrewery(
const Location& location, const std::string& /*region_context*/) {
const size_t hash = DeterministicHash(location);
const std::string_view adjective =
kBreweryAdjectives.at(hash % kBreweryAdjectives.size());
const std::string_view noun =
kBreweryNouns.at(hash / 7 % kBreweryNouns.size());
const std::string_view base_description =
kBreweryDescriptions.at((hash / 13) % kBreweryDescriptions.size());
const std::string name =
std::format("{} {} {}", location.city, adjective, noun);
const std::string state_suffix =
location.state_province.empty()
? std::string{}
: std::format(", {}", location.state_province);
const std::string country_suffix =
location.country.empty() ? std::string{}
: std::format(", {}", location.country);
const std::string description =
std::format("{} Located in {}{}{}.", base_description, location.city,
state_suffix, country_suffix);
return {
.name_en = name,
.description_en = description,
.name_local = name,
.description_local = description,
};
}

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/**
* @file data_generation/mock/generate_user.cc
* @brief Generates deterministic mock user profiles by hashing locale values
* into predefined username and bio collections.
*/
#include <functional>
#include <string>
#include <string_view>
#include "data_generation/mock_generator.h"
UserResult MockGenerator::GenerateUser(const std::string& locale) {
const size_t hash = std::hash<std::string>{}(locale);
UserResult result;
const std::string_view username = kUsernames[hash % kUsernames.size()];
const std::string_view bio = kBios[hash / 11 % kBios.size()];
result.username = username;
result.bio = bio;
return result;
}

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#include "data_generation/prompt_formatting/gemma4_jinja_prompt_formatter.h"
#include <format>
#include <string>
#include <string_view>
static constexpr std::string_view kWhitespace = " \t\n\r\f\v";
// Strips leading and trailing whitespace to ensure clean prompt injection.
static std::string_view Trim(std::string_view value) {
const size_t first_index = value.find_first_not_of(kWhitespace);
const bool is_all_whitespace = (first_index == std::string_view::npos);
if (is_all_whitespace) {
return "";
}
const size_t last_index = value.find_last_not_of(kWhitespace);
return value.substr(first_index, last_index - first_index + 1);
}
std::string Gemma4JinjaPromptFormatter::Format(
std::string_view system_prompt, std::string_view user_prompt) const {
std::string_view trimmed_system = Trim(system_prompt);
std::string_view trimmed_user = Trim(user_prompt);
return std::format(
"<|turn|>system\n<|think|>\n{}\n<|turn|>\n"
"<|turn|>user\n{}\n<|turn|>\n"
"<|turn|>model\n<|channel>thought\n",
trimmed_system, trimmed_user);
}

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/**
* @file json_handling/json_loader.cc
* @brief Parses curated location JSON input into strongly typed Location
* records with strict field validation and descriptive error reporting.
*/
#include "json_handling/json_loader.h"
#include <fstream>
#include <sstream>
#include <stdexcept>
#include <string>
#include <string_view>
#include <boost/json.hpp>
#include <spdlog/spdlog.h>
static std::string ReadRequiredString(const boost::json::object& object,
const char* key) {
const boost::json::value* value = object.if_contains(key);
if (value == nullptr || !value->is_string()) {
throw std::runtime_error(std::string("Missing or invalid string field: ") +
key);
}
const std::string_view text = value->as_string();
return std::string(text);
}
static double ReadRequiredNumber(const boost::json::object& object,
const char* key) {
const boost::json::value* value = object.if_contains(key);
if (value == nullptr || !value->is_number()) {
throw std::runtime_error(std::string("Missing or invalid numeric field: ") +
key);
}
return value->to_number<double>();
}
static std::vector<std::string> ReadRequiredStringArray(
const boost::json::object& object, const char* key) {
const boost::json::value* value = object.if_contains(key);
if (value == nullptr || !value->is_array()) {
throw std::runtime_error(std::string("Missing or invalid string array field: ") +
key);
}
const auto& array = value->as_array();
std::vector<std::string> items;
items.reserve(array.size());
for (const auto& item : array) {
if (!item.is_string()) {
throw std::runtime_error(std::string("Missing or invalid string array field: ") +
key);
}
items.emplace_back(item.as_string());
}
return items;
}
std::vector<Location> JsonLoader::LoadLocations(
const std::filesystem::path& filepath) {
std::ifstream input(filepath);
if (!input.is_open()) {
throw std::runtime_error("Failed to open locations file: " +
filepath.string());
}
std::stringstream buffer;
buffer << input.rdbuf();
const std::string content = buffer.str();
boost::system::error_code error;
boost::json::value root = boost::json::parse(content, error);
if (error) {
throw std::runtime_error("Failed to parse locations JSON: " +
error.message());
}
if (!root.is_array()) {
throw std::runtime_error(
"Invalid locations JSON: root element must be an array");
}
std::vector<Location> locations;
const auto& items = root.as_array();
locations.reserve(items.size());
for (const auto& item : items) {
if (!item.is_object()) {
throw std::runtime_error(
"Invalid locations JSON: each entry must be an object");
}
const auto& object = item.as_object();
locations.push_back(Location{
.city = ReadRequiredString(object, "city"),
.state_province = ReadRequiredString(object, "state_province"),
.iso3166_2 = ReadRequiredString(object, "iso3166_2"),
.country = ReadRequiredString(object, "country"),
.iso3166_1 = ReadRequiredString(object, "iso3166_1"),
.local_languages =
ReadRequiredStringArray(object, "local_languages"),
.latitude = ReadRequiredNumber(object, "latitude"),
.longitude = ReadRequiredNumber(object, "longitude"),
});
}
spdlog::info("[JsonLoader] Loaded {} locations from {}", locations.size(),
filepath.string());
return locations;
}

194
pipeline/src/main.cc Normal file
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/**
* @file main.cc
* @brief Parses command-line options, validates runtime mode selection,
* initializes shared infrastructure, and executes the pipeline entry flow.
*/
#include <spdlog/spdlog.h>
#include <boost/di.hpp>
#include <boost/program_options.hpp>
#include <chrono>
#include <exception>
#include <memory>
#include <optional>
#include <sstream>
#include <string>
#include "biergarten_data_generator.h"
#include "data_generation/llama_generator.h"
#include "data_generation/mock_generator.h"
#include "data_generation/prompt_formatting/gemma4_jinja_prompt_formatter.h"
#include "data_model/application_options.h"
#include "llama_backend_state.h"
#include "services/enrichment_service.h"
#include "services/wikipedia_service.h"
#include "web_client/curl_web_client.h"
namespace prog_opts = boost::program_options;
namespace di = boost::di;
/**
* @brief Parse command-line arguments into ApplicationOptions.
*
* @param argc Command-line argument count.
* @param argv Command-line arguments.
* @return Parsed ApplicationOptions if parsing succeeded, std::nullopt
* otherwise.
*/
std::optional<ApplicationOptions> ParseArguments(const int argc, char** argv) {
prog_opts::options_description desc("Pipeline Options");
auto opt = desc.add_options();
opt("help,h", "Produce help message");
opt("mocked", prog_opts::bool_switch(),
"Use mocked generator for brewery/user data");
opt("model,m", prog_opts::value<std::string>()->default_value(""),
"Path to LLM model (gguf)");
opt("temperature", prog_opts::value<float>()->default_value(1.0F),
"Sampling temperature (higher = more random)");
opt("top-p", prog_opts::value<float>()->default_value(0.95F),
"Nucleus sampling top-p in (0,1] (higher = more random)");
opt("top-k", prog_opts::value<uint32_t>()->default_value(64),
"Top-k sampling parameter (higher = more candidate tokens)");
opt("n-ctx", prog_opts::value<uint32_t>()->default_value(8192),
"Context window size in tokens (1-32768)");
opt("seed", prog_opts::value<int>()->default_value(-1),
"Sampler seed: -1 for random, otherwise non-negative integer");
// Handle the "no arguments" or "help" case
if (argc == 1) {
spdlog::info("Biergarten Pipeline");
std::stringstream usage_stream;
usage_stream << "\nUsage: biergarten-pipeline [options]\n\n" << desc;
spdlog::info(usage_stream.str());
return std::nullopt;
}
try {
prog_opts::variables_map variables_map;
prog_opts::store(prog_opts::parse_command_line(argc, argv, desc),
variables_map);
prog_opts::notify(variables_map);
if (variables_map.contains("help")) {
std::stringstream help_stream;
help_stream << "\n" << desc;
spdlog::info(help_stream.str());
return std::nullopt;
}
const auto use_mocked = variables_map["mocked"].as<bool>();
const auto model_path = variables_map["model"].as<std::string>();
if (use_mocked && !model_path.empty()) {
spdlog::error(
"Invalid arguments: --mocked and --model are mutually exclusive");
return std::nullopt;
}
if (!use_mocked && model_path.empty()) {
spdlog::error(
"Invalid arguments: Either --mocked or --model must be specified");
return std::nullopt;
}
const bool has_llm_params = !variables_map["temperature"].defaulted() ||
!variables_map["top-p"].defaulted() ||
!variables_map["top-k"].defaulted() ||
!variables_map["seed"].defaulted();
if (use_mocked && has_llm_params) {
spdlog::warn(
"Sampling parameters (--temperature, --top-p, --top-k, --seed) are"
" ignored when using --mocked");
}
ApplicationOptions options;
options.use_mocked = use_mocked;
options.model_path = model_path;
options.temperature = variables_map["temperature"].as<float>();
options.top_p = variables_map["top-p"].as<float>();
options.top_k = variables_map["top-k"].as<uint32_t>();
options.n_ctx = variables_map["n-ctx"].as<uint32_t>();
options.seed = variables_map["seed"].as<int>();
return options;
} catch (const std::exception& exception) {
spdlog::error("Failed to parse command-line arguments: {}",
exception.what());
return std::nullopt;
} catch (...) {
spdlog::error("Failed to parse command-line arguments: unknown error");
return std::nullopt;
}
}
struct Timer {
std::chrono::steady_clock::time_point start_time =
std::chrono::steady_clock::now();
[[nodiscard]] int64_t Elapsed() const {
return std::chrono::duration_cast<std::chrono::milliseconds>(
std::chrono::steady_clock::now() - start_time)
.count();
}
};
int main(const int argc, char** argv) {
try {
Timer timer;
const CurlGlobalState curl_state;
const LlamaBackendState llama_backend_state;
spdlog::set_pattern("[%Y-%m-%d %H:%M:%S.%e] [%^%l%$] %v");
const auto parsed_options = ParseArguments(argc, argv);
if (!parsed_options.has_value()) {
return 0;
}
const auto options = *parsed_options;
const auto injector = di::make_injector(
di::bind<WebClient>().to<CURLWebClient>(),
di::bind<ApplicationOptions>().to(options),
di::bind<IEnrichmentService>().to<WikipediaService>(),
di::bind<IPromptFormatter>().to<Gemma4JinjaPromptFormatter>(),
di::bind<std::string>().to(options.model_path),
di::bind<DataGenerator>().to(
[options](const auto& inj) -> std::unique_ptr<DataGenerator> {
if (options.use_mocked) {
spdlog::info(
"[Generator] Using MockGenerator (no model path provided)");
return std::make_unique<MockGenerator>();
}
spdlog::info(
"[Generator] Using LlamaGenerator: {} (temperature={}, "
"top-p={}, top-k={}, n_ctx={}, seed={})",
options.model_path, options.temperature, options.top_p,
options.top_k, options.n_ctx, options.seed);
return inj.template create<std::unique_ptr<LlamaGenerator>>();
}));
auto generator = injector.create<BiergartenDataGenerator>();
if (!generator.Run()) {
spdlog::error("Pipeline execution failed");
return 1;
}
spdlog::info("Pipeline executed successfully in {} ms", timer.Elapsed());
return 0;
} catch (const std::exception& exception) {
spdlog::critical("Unhandled fatal error in main: {}", exception.what());
return 1;
}
}

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/**
* @file wikipedia/fetch_extract.cc
* @brief WikipediaService::FetchExtract() implementation.
*/
#include <spdlog/spdlog.h>
#include <boost/json.hpp>
#include <string>
#include <string_view>
#include "services/wikipedia_service.h"
std::string WikipediaService::FetchExtract(std::string_view query) {
const std::string cache_key(query);
const auto cache_it = this->extract_cache_.find(cache_key);
if (cache_it != this->extract_cache_.end()) {
return cache_it->second;
}
const std::string encoded = this->client_->UrlEncode(cache_key);
const std::string url =
"https://en.wikipedia.org/w/api.php?action=query&titles=" + encoded +
"&prop=extracts&explaintext=1&format=json";
const std::string body = this->client_->Get(url);
boost::system::error_code parse_error;
boost::json::value doc = boost::json::parse(body, parse_error);
if (!parse_error && doc.is_object()) {
try {
auto& pages = doc.at("query").at("pages").get_object();
if (!pages.empty()) {
auto& page = pages.begin()->value().get_object();
if (page.contains("extract") && page.at("extract").is_string()) {
const std::string_view extract_view = page.at("extract").as_string();
std::string extract(extract_view);
spdlog::debug("WikipediaService fetched {} chars for '{}'",
extract.size(), query);
this->extract_cache_.emplace(cache_key, extract);
return extract;
}
}
this->extract_cache_.emplace(cache_key, std::string{});
} catch (const std::exception& e) {
spdlog::warn(
"WikipediaService: failed to parse response structure for '{}': "
"{}",
query, e.what());
return {};
}
} else if (parse_error) {
spdlog::warn("WikipediaService: JSON parse error for '{}': {}", query,
parse_error.message());
}
return {};
}

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/**
* @file wikipedia/get_summary.cc
* @brief WikipediaService::GetLocationContext() implementation.
*/
#include <spdlog/spdlog.h>
#include <string>
#include "services/wikipedia_service.h"
std::string WikipediaService::GetLocationContext(const Location& loc) {
if (!client_) {
return {};
}
std::string result;
std::string region_query(loc.city);
if (!loc.country.empty()) {
region_query += ", ";
region_query += loc.country;
}
const std::string beer_query = "beer in " + loc.country;
const std::string city_beer_query = "beer in " + loc.city;
auto append_extract = [&result](const std::string& extract) -> void {
if (extract.empty()) {
return;
}
if (!result.empty()) {
result += "\n\n";
}
result += extract;
};
try {
append_extract(FetchExtract(region_query));
append_extract(FetchExtract(beer_query));
append_extract(FetchExtract(city_beer_query));
} catch (const std::runtime_error& e) {
spdlog::debug("WikipediaService lookup failed for '{}': {}", region_query,
e.what());
}
return result;
}

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/**
* @file services/wikipedia/wikipedia_service.cc
* @brief WikipediaService constructor implementation.
*/
#include "services/wikipedia_service.h"
#include <utility>
WikipediaService::WikipediaService(std::unique_ptr<WebClient> client)
: client_(std::move(client)) {}

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/**
* @file web_client/curl_global_state.cc
* @brief CurlGlobalState constructor and destructor implementation.
*/
#include <curl/curl.h>
#include <stdexcept>
#include "web_client/curl_web_client.h"
CurlGlobalState::CurlGlobalState() {
if (curl_global_init(CURL_GLOBAL_DEFAULT) != CURLE_OK) {
throw std::runtime_error(
"[CURLWebClient] Failed to initialize libcurl globally");
}
}
CurlGlobalState::~CurlGlobalState() { curl_global_cleanup(); }

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/**
* @file web_client/curl_web_client_get.cc
* @brief CURLWebClient::Get() implementation.
*/
#include "web_client/curl_web_client.h"
#include <cstdint>
#include <limits>
#include <memory>
#include <stdexcept>
#include <string>
#include <curl/curl.h>
using CurlHandle = std::unique_ptr<CURL, decltype(&curl_easy_cleanup)>;
static constexpr long kConnectionTimeout = 10;
static constexpr long kRequestTimeout = 30;
static constexpr int32_t kOkHttpStatus = 200;
static CurlHandle CreateHandle() {
CURL* handle = curl_easy_init();
if (handle == nullptr) {
throw std::runtime_error(
"[CURLWebClient] Failed to initialize libcurl handle");
}
return {handle, &curl_easy_cleanup};
}
static void SetCommonGetOptions(CURL* curl, const std::string& url) {
curl_easy_setopt(curl, CURLOPT_URL, url.c_str());
curl_easy_setopt(curl, CURLOPT_USERAGENT, "biergarten-pipeline/0.1.0");
curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L);
curl_easy_setopt(curl, CURLOPT_MAXREDIRS, 5L);
curl_easy_setopt(curl, CURLOPT_CONNECTTIMEOUT, kConnectionTimeout);
curl_easy_setopt(curl, CURLOPT_TIMEOUT, kRequestTimeout);
curl_easy_setopt(curl, CURLOPT_ACCEPT_ENCODING, "gzip");
}
// curl write callback that appends response data into a std::string
static size_t WriteCallbackString(void* contents, const size_t size,
const size_t nmemb, void* userp) {
const size_t real_size = size * nmemb;
auto* str = static_cast<std::string*>(userp);
str->append(static_cast<char*>(contents), real_size);
return real_size;
}
std::string CURLWebClient::Get(const std::string& url) {
const CurlHandle curl = CreateHandle();
std::string response_string;
SetCommonGetOptions(curl.get(), url);
curl_easy_setopt(curl.get(), CURLOPT_WRITEFUNCTION, WriteCallbackString);
curl_easy_setopt(curl.get(), CURLOPT_WRITEDATA, &response_string);
CURLcode curl_result = curl_easy_perform(curl.get());
if (curl_result != CURLE_OK) {
const auto error = std::string("[CURLWebClient] GET failed: ") +
curl_easy_strerror(curl_result);
throw std::runtime_error(error);
}
long curl_http_code = 0;
curl_easy_getinfo(curl.get(), CURLINFO_RESPONSE_CODE, &curl_http_code);
if (curl_http_code < std::numeric_limits<int32_t>::min() ||
curl_http_code > std::numeric_limits<int32_t>::max()) {
throw std::runtime_error("[CURLWebClient] Invalid HTTP status code: " +
std::to_string(curl_http_code));
}
const int32_t http_code = static_cast<int32_t>(curl_http_code);
if (http_code != kOkHttpStatus) {
const std::string error = "[CURLWebClient] HTTP error " +
std::to_string(http_code) + " for URL " + url;
throw std::runtime_error(error);
}
return response_string;
}

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/**
* @file web_client/curl_web_client_url_encode.cc
* @brief CURLWebClient::UrlEncode() implementation.
*/
#include <curl/curl.h>
#include <stdexcept>
#include <string>
#include "web_client/curl_web_client.h"
std::string CURLWebClient::UrlEncode(const std::string& value) {
// A NULL handle is fine for UTF-8 encoding according to libcurl docs.
char* output = curl_easy_escape(nullptr, value.c_str(), 0);
if (!output) {
throw std::runtime_error("[CURLWebClient] curl_easy_escape failed");
}
std::string result(output);
curl_free(output);
return result;
}