common, tools : refactor model loading to support backend samplers

This commit refactors the model loading process in common/common.cpp
to enable backend sampler to be configure prior to the llama_context
creation.

The motivation for this change is that just being able to set/reset the
backend samplers after the llama_context has been created will cause a
resize to occur in llama_context::output_reserve which we want to avoid.

common/common.cpp

@@ -943,14 +943,26 @@ std::vector<common_file_info> fs_list_files(const std::string & path) {
 // Model utils
 //
 
-struct common_init_result common_init_from_params(common_params & params) {
-    common_init_result iparams;
+llama_model * common_load_model_from_params(common_params & params) {
     auto mparams = common_model_params_to_llama(params);
 
     llama_model * model = llama_model_load_from_file(params.model.path.c_str(), mparams);
     if (model == NULL) {
         LOG_ERR("%s: failed to load model '%s', try reducing --n-gpu-layers if you're running out of VRAM\n",
             __func__, params.model.path.c_str());
+        return nullptr;
+    }
+
+    return model;
+}
+
+struct common_init_result common_init_context_from_model(
+    llama_model * model,
+    common_params & params) {
+    common_init_result iparams;
+
+    if (model == NULL) {
+        LOG_ERR("%s: model is NULL\n", __func__);
         return iparams;
     }
 
@@ -1125,6 +1137,14 @@ struct common_init_result common_init_from_params(common_params & params) {
     return iparams;
 }
 
+struct common_init_result common_init_from_params(common_params & params) {
+    llama_model * model = common_load_model_from_params(params);
+    if (model == NULL) {
+        return common_init_result();
+    }
+    return common_init_context_from_model(model, params);
+}
+
 std::string get_model_endpoint() {
     const char * model_endpoint_env = getenv("MODEL_ENDPOINT");
     // We still respect the use of environment-variable "HF_ENDPOINT" for backward-compatibility.

common/common.h

@@ -640,6 +640,14 @@ struct common_init_result {
 
 struct common_init_result     common_init_from_params(common_params & params);
 
+// Load model only (allows creating backend samplers before context initialization)
+llama_model * common_load_model_from_params(common_params & params);
+
+// Initialize context from an already-loaded model (allows pre-configuring backend samplers)
+struct common_init_result common_init_context_from_model(
+    llama_model * model,
+    common_params & params);
+
 struct llama_model_params     common_model_params_to_llama  (      common_params & params);
 struct llama_context_params   common_context_params_to_llama(const common_params & params);
 struct ggml_threadpool_params ggml_threadpool_params_from_cpu_params(const cpu_params & params);

tools/main/main.cpp

@@ -137,18 +137,29 @@ int main(int argc, char ** argv) {
 
     // load the model and apply lora adapter, if any
     LOG_INF("%s: load the model and apply lora adapter, if any\n", __func__);
-    common_init_result llama_init = common_init_from_params(params);
-
-    model = llama_init.model.get();
-    ctx = llama_init.context.get();
 
+    model = common_load_model_from_params(params);
     if (model == NULL) {
         LOG_ERR("%s: error: unable to load model\n", __func__);
         return 1;
     }
 
-    // Configure backend sampler chain
-    llama_set_backend_sampler(ctx, 0, common_sampler_backend_init(model, sparams));
+    // Configure backend sampler if configured
+    llama_sampler * backend_sampler = common_sampler_backend_init(model, sparams);
+    if (backend_sampler) {
+        llama_sampler_seq_config sampler_config = { 0, backend_sampler };
+        params.backend_samplers = &sampler_config;
+        params.n_backend_samplers = 1;
+    }
+
+    common_init_result llama_init = common_init_context_from_model(model, params);
+    ctx = llama_init.context.get();
+    model = llama_init.model.get(); // Update pointer (now managed by llama_init)
+
+    if (ctx == NULL) {
+        LOG_ERR("%s: error: unable to create context\n", __func__);
+        return 1;
+    }
 
     auto * mem = llama_get_memory(ctx);