#include "config.h" #include "logger.h" #include "toml.hpp" #include #include namespace humanus { // Initialize static members Config* Config::_instance = nullptr; std::mutex Config::_mutex; void Config::_load_initial_llm_config() { try { auto config_path = _get_llm_config_path(); std::cout << "Loading LLM config file from: " << config_path.string() << std::endl; const auto& data = toml::parse_file(config_path.string()); // Load LLM configuration for (const auto& [key, value] : data) { const auto& llm_table = *value.as_table(); LLMConfig llm_config; if (llm_table.contains("model") && llm_table["model"].is_string()) { llm_config.model = llm_table["model"].as_string()->get(); } if (llm_table.contains("api_key") && llm_table["api_key"].is_string()) { llm_config.api_key = llm_table["api_key"].as_string()->get(); } if (llm_table.contains("base_url") && llm_table["base_url"].is_string()) { llm_config.base_url = llm_table["base_url"].as_string()->get(); } if (llm_table.contains("endpoint") && llm_table["endpoint"].is_string()) { llm_config.endpoint = llm_table["endpoint"].as_string()->get(); } if (llm_table.contains("vision_details") && llm_table["vision_details"].is_string()) { llm_config.vision_details = llm_table["vision_details"].as_string()->get(); } if (llm_table.contains("max_tokens") && llm_table["max_tokens"].is_integer()) { llm_config.max_tokens = llm_table["max_tokens"].as_integer()->get(); } if (llm_table.contains("timeout") && llm_table["timeout"].is_integer()) { llm_config.timeout = llm_table["timeout"].as_integer()->get(); } if (llm_table.contains("temperature") && llm_table["temperature"].is_floating_point()) { llm_config.temperature = llm_table["temperature"].as_floating_point()->get(); } if (llm_table.contains("enable_vision") && llm_table["enable_vision"].is_boolean()) { llm_config.enable_vision = llm_table["enable_vision"].as_boolean()->get(); } if (llm_table.contains("oai_tool_support") && llm_table["oai_tool_support"].is_boolean()) { llm_config.oai_tool_support = llm_table["oai_tool_support"].as_boolean()->get(); } _config.llm[std::string(key.str())] = llm_config; if (!llm_config.oai_tool_support) { // Load tool helper configuration ToolParser tool_parser; if (llm_table.contains("tool_parser") && llm_table["tool_parser"].is_table()) { const auto& tool_parser_table = *llm_table["tool_parser"].as_table(); if (tool_parser_table.contains("tool_start")) { tool_parser.tool_start = tool_parser_table["tool_start"].as_string()->get(); } if (tool_parser_table.contains("tool_end")) { tool_parser.tool_end = tool_parser_table["tool_end"].as_string()->get(); } if (tool_parser_table.contains("tool_hint_template")) { tool_parser.tool_hint_template = tool_parser_table["tool_hint_template"].as_string()->get(); } } _config.tool_parser[std::string(key.str())] = tool_parser; } } if (_config.llm.empty()) { throw std::runtime_error("No LLM configuration found"); } else if (_config.llm.find("default") == _config.llm.end()) { _config.llm["default"] = _config.llm.begin()->second; } if (_config.tool_parser.find("default") == _config.tool_parser.end()) { _config.tool_parser["default"] = ToolParser(); } } catch (const std::exception& e) { std::cerr << "Loading config file failed: " << e.what() << std::endl; // Set default configuration _config.llm["default"] = LLMConfig(); _config.tool_parser["default"] = ToolParser(); } } void Config::_load_initial_embedding_model_config() { try { auto config_path = _get_embedding_model_config_path(); std::cout << "Loading embedding model config file from: " << config_path.string() << std::endl; const auto& data = toml::parse_file(config_path.string()); // Load embedding model configuration for (const auto& [key, value] : data) { const auto& embd_table = *value.as_table(); EmbeddingModelConfig embd_config; if (embd_table.contains("provider") && embd_table["provider"].is_string()) { embd_config.provider = embd_table["provider"].as_string()->get(); } if (embd_table.contains("base_url") && embd_table["base_url"].is_string()) { embd_config.base_url = embd_table["base_url"].as_string()->get(); } if (embd_table.contains("endpoint") && embd_table["endpoint"].is_string()) { embd_config.endpoint = embd_table["endpoint"].as_string()->get(); } if (embd_table.contains("model") && embd_table["model"].is_string()) { embd_config.model = embd_table["model"].as_string()->get(); } if (embd_table.contains("api_key") && embd_table["api_key"].is_string()) { embd_config.api_key = embd_table["api_key"].as_string()->get(); } if (embd_table.contains("embedding_dims") && embd_table["embedding_dims"].is_integer()) { embd_config.embedding_dims = embd_table["embedding_dims"].as_integer()->get(); } if (embd_table.contains("max_retries") && embd_table["max_retries"].is_integer()) { embd_config.max_retries = embd_table["max_retries"].as_integer()->get(); } _config.embedding_model[std::string(key.str())] = embd_config; } if (_config.embedding_model.empty()) { throw std::runtime_error("No embedding model configuration found"); } else if (_config.embedding_model.find("default") == _config.embedding_model.end()) { _config.embedding_model["default"] = _config.embedding_model.begin()->second; } } catch (const std::exception& e) { std::cerr << "Loading embedding model config file failed: " << e.what() << std::endl; // Set default configuration _config.embedding_model["default"] = EmbeddingModelConfig(); } } void Config::_load_initial_vector_store_config() { try { auto config_path = _get_vector_store_config_path(); std::cout << "Loading vector store config file from: " << config_path.string() << std::endl; const auto& data = toml::parse_file(config_path.string()); // Load vector store configuration for (const auto& [key, value] : data) { const auto& vs_table = *value.as_table(); VectorStoreConfig vs_config; if (vs_table.contains("provider") && vs_table["provider"].is_string()) { vs_config.provider = vs_table["provider"].as_string()->get(); } if (vs_table.contains("dim") && vs_table["dim"].is_integer()) { vs_config.dim = vs_table["dim"].as_integer()->get(); } if (vs_table.contains("max_elements") && vs_table["max_elements"].is_integer()) { vs_config.max_elements = vs_table["max_elements"].as_integer()->get(); } if (vs_table.contains("M") && vs_table["M"].is_integer()) { vs_config.M = vs_table["M"].as_integer()->get(); } if (vs_table.contains("ef_construction") && vs_table["ef_construction"].is_integer()) { vs_config.ef_construction = vs_table["ef_construction"].as_integer()->get(); } if (vs_table.contains("metric") && vs_table["metric"].is_string()) { const auto& metric_str = vs_table["metric"].as_string()->get(); if (metric_str == "L2") { vs_config.metric = VectorStoreConfig::Metric::L2; } else if (metric_str == "IP") { vs_config.metric = VectorStoreConfig::Metric::IP; } else { throw std::runtime_error("Invalid metric: " + metric_str); } } _config.vector_store[std::string(key.str())] = vs_config; } if (_config.vector_store.empty()) { throw std::runtime_error("No vector store configuration found"); } else if (_config.vector_store.find("default") == _config.vector_store.end()) { _config.vector_store["default"] = _config.vector_store.begin()->second; } } catch (const std::exception& e) { std::cerr << "Loading vector store config file failed: " << e.what() << std::endl; // Set default configuration _config.vector_store["default"] = VectorStoreConfig(); } } } // namespace humanus