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Merge pull request #1346 from ozanarmagan/v0.25-join

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Fix updating auto embedding field indexes
This commit is contained in:
Kishore Nallan 2023-10-30 17:16:00 +05:30 committed by GitHub
commit 813352ec48
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2 changed files with 96 additions and 6 deletions
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9
src/index.cpp
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@ -6741,13 +6741,10 @@ void Index::batch_embed_fields(std::vector<index_record*>& records,
texts_to_embed[i].first->index_failure(embedding_res.status_code, "");
continue;
}
nlohmann::json* document;
if(texts_to_embed[i].first->is_update) {
document = &texts_to_embed[i].first->new_doc;
} else {
document = &texts_to_embed[i].first->doc;
}
(*document)[field.name] = embedding_res.embedding;
texts_to_embed[i].first->new_doc[field.name] = embedding_res.embedding;
}
texts_to_embed[i].first->doc[field.name] = embedding_res.embedding;
}
}
}

93
test/collection_vector_search_test.cpp
View File

@ -2729,4 +2729,97 @@ TEST_F(CollectionVectorTest, TestSearchNonIndexedVectorField) {
ASSERT_FALSE(search_result.ok());
ASSERT_EQ("Field `vec` is marked as a non-indexed field in the schema.", search_result.error());
}
TEST_F(CollectionVectorTest, TestSemanticSearchAfterUpdate) {
nlohmann::json schema = R"({
"name": "test",
"fields": [
{
"name": "name",
"type": "string"
},
{
"name": "embedding",
"type": "float[]",
"embed": {
"from": [
"name"
],
"model_config": {
"model_name": "ts/e5-small"
}
}
}
]
})"_json;
TextEmbedderManager::set_model_dir("/tmp/typesense_test/models");
auto collection_create_op = collectionManager.create_collection(schema);
ASSERT_TRUE(collection_create_op.ok());
auto coll = collection_create_op.get();
auto add_op = coll->add(R"({
"name": "soccer",
"id": "0"
})"_json.dump());
ASSERT_TRUE(add_op.ok());
add_op = coll->add(R"({
"name": "basketball",
"id": "1"
})"_json.dump());
ASSERT_TRUE(add_op.ok());
add_op = coll->add(R"({
"name": "typesense",
"id": "2"
})"_json.dump());
ASSERT_TRUE(add_op.ok());
add_op = coll->add(R"({
"name": "potato",
"id": "3"
})"_json.dump());
ASSERT_TRUE(add_op.ok());
auto result = coll->search("*", {}, "", {}, {}, {0}, 20, 1, FREQUENCY, {true}, Index::DROP_TOKENS_THRESHOLD,
spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 5,
"", 10, {}, {}, {}, 0,
"<mark>", "</mark>", {}, 1000, true, false, true, "", false, 6000 * 1000, 4, 7,
fallback,
4, {off}, 32767, 32767, 2,
false, true, "embedding:([], id:0, k:1)");
ASSERT_TRUE(result.ok());
ASSERT_EQ(1, result.get()["hits"].size());
ASSERT_EQ("basketball", result.get()["hits"][0]["document"]["name"]);
auto update_op = coll->add(R"({
"name": "onion",
"id": "0"
})"_json.dump(), index_operation_t::UPDATE, "0");
ASSERT_TRUE(update_op.ok());
result = coll->search("*", {}, "", {}, {}, {0}, 20, 1, FREQUENCY, {true}, Index::DROP_TOKENS_THRESHOLD,
spp::sparse_hash_set<std::string>(),
spp::sparse_hash_set<std::string>(), 10, "", 30, 5,
"", 10, {}, {}, {}, 0,
"<mark>", "</mark>", {}, 1000, true, false, true, "", false, 6000 * 1000, 4, 7,
fallback,
4, {off}, 32767, 32767, 2,
false, true, "embedding:([], id:0, k:1)");
ASSERT_TRUE(result.ok());
ASSERT_EQ(1, result.get()["hits"].size());
ASSERT_EQ("potato", result.get()["hits"][0]["document"]["name"]);
}