Refactor BiergartenDataGenerator to use dependency injection container

pipeline/src/data_generation/llama/constructor.cpp

@@ -0,0 +1,53 @@
+/**
+ * @file data_generation/llama/constructor.cpp
+ * @brief LlamaGenerator constructor implementation.
+ */
+
+#include <llama.h>
+
+#include <stdexcept>
+#include <string>
+
+#include "biergarten_data_generator.h"
+#include "data_generation/llama_generator.h"
+
+LlamaGenerator::LlamaGenerator(const ApplicationOptions& options,
+                               const std::string& model_path) {
+   if (model_path.empty()) {
+      throw std::runtime_error("LlamaGenerator: model path must not be empty");
+   }
+
+   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.seed < -1) {
+      throw std::runtime_error(
+          "LlamaGenerator: seed must be >= 0, or -1 for random");
+   }
+
+   if (options.n_ctx == 0 || options.n_ctx > 32768) {
+      throw std::runtime_error(
+          "LlamaGenerator: context size must be in range [1, 32768]");
+   }
+
+   sampling_temperature_ = options.temperature;
+   sampling_top_p_ = options.top_p;
+   sampling_seed_ = (options.seed < 0)
+                        ? static_cast<uint32_t>(LLAMA_DEFAULT_SEED)
+                        : static_cast<uint32_t>(options.seed);
+   n_ctx_ = options.n_ctx;
+
+   try {
+      Load(model_path);
+   } catch (...) {
+      llama_backend_free();
+      throw;
+   }
+}

pipeline/src/data_generation/llama/load.cpp

@@ -1,7 +1,7 @@
 /**
  * @file data_generation/llama/load.cpp
  * @brief Initializes llama backend, loads model weights, creates inference
- * context, and resets prior resources during model reload.
+ * context, and resets prior resources during model initialization.
  */
 
 #include <spdlog/spdlog.h>
@@ -13,12 +13,6 @@
 #include "llama.h"
 
 void LlamaGenerator::Load(const std::string& model_path) {
-   /**
-    * Validate input and clean up any previously loaded model/context
-    */
-   if (model_path.empty())
-      throw std::runtime_error("LlamaGenerator: model path must not be empty");
-
    if (context_ != nullptr) {
       llama_free(context_);
       context_ = nullptr;

pipeline/src/data_generation/llama/set_sampling_options.cpp

@@ -1,64 +0,0 @@
-/**
- * @file data_generation/llama/set_sampling_options.cpp
- * @brief Validates and stores sampling temperature, top-p, seed, and context
- * size configuration used by subsequent LlamaGenerator inference calls.
- */
-
-#include <stdexcept>
-
-#include "data_generation/llama_generator.h"
-#include "llama.h"
-
-void LlamaGenerator::SetSamplingOptions(float temperature, float top_p,
-                                        int seed) {
-   /**
-    * Validate temperature: controls randomness in output distribution
-    * 0.0 = deterministic (always pick highest probability token)
-    * Higher values = more random/diverse output
-    */
-   if (temperature < 0.0f) {
-      throw std::runtime_error(
-          "LlamaGenerator: sampling temperature must be >= 0");
-   }
-
-   /**
-    * Validate top-p (nucleus sampling): only sample from top cumulative
-    * probability e.g., top-p=0.9 means sample from tokens that make up 90% of
-    * probability mass
-    */
-   if (!(top_p > 0.0f && top_p <= 1.0f)) {
-      throw std::runtime_error(
-          "LlamaGenerator: sampling top-p must be in (0, 1]");
-   }
-
-   /**
-    * Validate seed: for reproducible results (-1 uses random seed)
-    */
-   if (seed < -1) {
-      throw std::runtime_error(
-          "LlamaGenerator: seed must be >= 0, or -1 for random");
-   }
-
-   /**
-    * Store sampling parameters for use during token generation
-    */
-   sampling_temperature_ = temperature;
-   sampling_top_p_ = top_p;
-   sampling_seed_ = (seed < 0) ? static_cast<uint32_t>(LLAMA_DEFAULT_SEED)
-                               : static_cast<uint32_t>(seed);
-}
-
-void LlamaGenerator::SetContextSize(uint32_t n_ctx) {
-   /**
-    * Validate context size: must be positive and reasonable for the model
-    */
-   if (n_ctx == 0 || n_ctx > 32768) {
-      throw std::runtime_error(
-          "LlamaGenerator: context size must be in range [1, 32768]");
-   }
-
-   /**
-    * Store context size for use during model loading
-    */
-   n_ctx_ = n_ctx;
-}