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// Copyright (C) 2024 Sutou Kouhei <kou@clear-code.com>
//
// This library is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 2.1 of the License, or (at your option) any later version.
//
// This library is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
// Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License along with this library; if not, write to the Free Software
// Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
#ifdef GRN_EMBEDDED
# define GRN_PLUGIN_FUNCTION_TAG functions_language_model
#endif
#include <groonga/plugin.h>
static grn_obj *
func_language_model_vectorize(grn_ctx *ctx,
int n_args,
grn_obj **args,
grn_user_data *user_data)
{
const char *tag = "language_model_vectorize():";
if (!(n_args == 2 || n_args == 3)) {
GRN_PLUGIN_ERROR(ctx,
GRN_INVALID_ARGUMENT,
"%s wrong number of arguments (%d for 2..3)",
tag,
n_args);
return NULL;
}
grn_obj *vector = NULL;
grn_language_model_loader *loader = grn_language_model_loader_open(ctx);
grn_language_model *model = NULL;
grn_language_model_inferencer *inferencer = NULL;
grn_obj *model_name = args[0];
if (!grn_obj_is_text_family_bulk(ctx, model_name)) {
grn_obj inspected;
GRN_TEXT_INIT(&inspected, 0);
grn_inspect(ctx, &inspected, model_name);
GRN_PLUGIN_ERROR(ctx,
GRN_INVALID_ARGUMENT,
"%s the 1st argument must be model name: %.*s",
tag,
(int)(GRN_TEXT_LEN(&inspected)),
GRN_TEXT_VALUE(&inspected));
GRN_OBJ_FIN(ctx, &inspected);
goto exit;
}
grn_language_model_loader_set_model(ctx,
loader,
GRN_TEXT_VALUE(model_name),
GRN_TEXT_LEN(model_name));
grn_obj *text = args[1];
if (!grn_obj_is_text_family_bulk(ctx, text)) {
grn_obj inspected;
GRN_TEXT_INIT(&inspected, 0);
grn_inspect(ctx, &inspected, text);
GRN_PLUGIN_ERROR(ctx,
GRN_INVALID_ARGUMENT,
"%s the 2nd argument must be text to vectorize: %.*s",
tag,
(int)(GRN_TEXT_LEN(&inspected)),
GRN_TEXT_VALUE(&inspected));
GRN_OBJ_FIN(ctx, &inspected);
goto exit;
}
grn_obj *options = NULL;
if (n_args == 3) {
options = args[2];
}
model = grn_language_model_loader_load(ctx, loader);
if (!model) {
GRN_PLUGIN_ERROR(ctx,
ctx->rc,
"%s failed to load model: %s",
tag,
ctx->errbuf);
goto exit;
}
inferencer = grn_language_model_open_inferencer(ctx, model);
if (!inferencer) {
GRN_PLUGIN_ERROR(ctx,
ctx->rc,
"%s failed to open model inferencer: %s",
tag,
ctx->errbuf);
goto exit;
}
vector =
grn_plugin_proc_alloc(ctx, user_data, GRN_DB_FLOAT32, GRN_OBJ_VECTOR);
if (!vector) {
return NULL;
}
grn_rc rc = grn_language_model_inferencer_vectorize(ctx,
inferencer,
GRN_TEXT_VALUE(text),
GRN_TEXT_LEN(text),
vector);
if (rc != GRN_SUCCESS) {
GRN_PLUGIN_ERROR(ctx,
ctx->rc,
"%s failed to vectorize: %s",
tag,
ctx->errbuf);
grn_obj_close(ctx, vector);
vector = NULL;
goto exit;
}
exit:
grn_language_model_inferencer_close(ctx, inferencer);
grn_language_model_close(ctx, model);
grn_language_model_loader_close(ctx, loader);
return vector;
}
static grn_rc
applier_language_model_vectorize(grn_ctx *ctx, grn_applier_data *data)
{
const char *tag = "language_model_vectorize():";
size_t n_args;
grn_obj **args = grn_applier_data_get_args(ctx, data, &n_args);
if (!(n_args == 2 || n_args == 3)) {
GRN_PLUGIN_ERROR(ctx,
GRN_INVALID_ARGUMENT,
"%s wrong number of arguments (%d for 2..3)",
tag,
(uint32_t)n_args);
return ctx->rc;
}
grn_language_model_loader *loader = grn_language_model_loader_open(ctx);
grn_language_model *model = NULL;
grn_language_model_inferencer *inferencer = NULL;
grn_obj *model_name = args[0];
if (!grn_obj_is_text_family_bulk(ctx, model_name)) {
grn_obj inspected;
GRN_TEXT_INIT(&inspected, 0);
grn_inspect(ctx, &inspected, model_name);
GRN_PLUGIN_ERROR(ctx,
GRN_INVALID_ARGUMENT,
"%s the 1st argument must be model name: %.*s",
tag,
(int)(GRN_TEXT_LEN(&inspected)),
GRN_TEXT_VALUE(&inspected));
GRN_OBJ_FIN(ctx, &inspected);
goto exit;
}
grn_language_model_loader_set_model(ctx,
loader,
GRN_TEXT_VALUE(model_name),
GRN_TEXT_LEN(model_name));
grn_obj *input_column = args[1];
if (!(grn_obj_is_text_family_scalar_column(ctx, input_column) ||
grn_obj_is_text_family_scalar_accessor(ctx, input_column))) {
grn_obj inspected;
GRN_TEXT_INIT(&inspected, 0);
grn_inspect(ctx, &inspected, input_column);
GRN_PLUGIN_ERROR(ctx,
GRN_INVALID_ARGUMENT,
"%s the 2nd argument must be a text family column "
"or accessor to vectorize: %.*s",
tag,
(int)(GRN_TEXT_LEN(&inspected)),
GRN_TEXT_VALUE(&inspected));
GRN_OBJ_FIN(ctx, &inspected);
goto exit;
}
grn_obj *options = NULL;
if (n_args == 3) {
options = args[2];
}
model = grn_language_model_loader_load(ctx, loader);
if (!model) {
GRN_PLUGIN_ERROR(ctx,
ctx->rc,
"%s failed to load model: %s",
tag,
ctx->errbuf);
goto exit;
}
inferencer = grn_language_model_open_inferencer(ctx, model);
if (!inferencer) {
GRN_PLUGIN_ERROR(ctx,
ctx->rc,
"%s failed to open model inferencer: %s",
tag,
ctx->errbuf);
goto exit;
}
grn_rc rc = grn_language_model_inferencer_vectorize_applier(ctx,
inferencer,
input_column,
data);
if (rc != GRN_SUCCESS) {
GRN_PLUGIN_ERROR(ctx,
ctx->rc,
"%s failed to vectorize: %s",
tag,
ctx->errbuf);
goto exit;
}
exit:
grn_language_model_inferencer_close(ctx, inferencer);
grn_language_model_close(ctx, model);
grn_language_model_loader_close(ctx, loader);
return ctx->rc;
}
grn_rc
GRN_PLUGIN_INIT(grn_ctx *ctx)
{
return ctx->rc;
}
grn_rc
GRN_PLUGIN_REGISTER(grn_ctx *ctx)
{
grn_rc rc = GRN_SUCCESS;
{
grn_obj *proc = grn_proc_create(ctx,
"language_model_vectorize",
-1,
GRN_PROC_FUNCTION,
func_language_model_vectorize,
NULL,
NULL,
0,
NULL);
grn_proc_set_applier(ctx, proc, applier_language_model_vectorize);
}
return rc;
}
grn_rc
GRN_PLUGIN_FIN(grn_ctx *ctx)
{
return GRN_SUCCESS;
}
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