postgres/typesense
1
0
Fork 0
mirror of https://github.com/typesense/typesense.git synced 2025-05-20 21:52:23 +08:00
Code Issues Actions 3 Packages Projects Releases Wiki Activity

Add test for wildcard vector query + eval.

Browse Source
This commit is contained in:
Kishore Nallan 2024-04-04 22:49:44 +05:30
parent 3d4ad20bba
commit 5f3b3684b2
1 changed files with 53 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

53
test/collection_vector_search_test.cpp
View File

@ -1472,6 +1472,59 @@ TEST_F(CollectionVectorTest, HybridSearchWithEvalSort) {
ASSERT_EQ("1", results_op.get()["hits"][2]["document"]["id"].get<std::string>());
}
TEST_F(CollectionVectorTest, VectorSearchWithEvalSort) {
nlohmann::json schema = R"({
"name": "coll1",
"fields": [
{"name": "name", "type": "string", "facet": true},
{"name": "category", "type": "string", "facet": true},
{"name": "vec", "type": "float[]", "num_dim": 4}
]
})"_json;
EmbedderManager::set_model_dir("/tmp/typesense_test/models");
Collection* coll1 = collectionManager.create_collection(schema).get();
nlohmann::json doc;
doc["id"] = "0";
doc["name"] = "Apple Fruit";
doc["category"] = "Fresh";
doc["vec"] = {0.1, 0.2, 0.3, 0.4};
ASSERT_TRUE(coll1->add(doc.dump()).ok());
doc["id"] = "1";
doc["name"] = "Apple";
doc["category"] = "Phone";
doc["vec"] = {0.2, 0.3, 0.1, 0.1};
ASSERT_TRUE(coll1->add(doc.dump()).ok());
doc["id"] = "2";
doc["name"] = "Apple Pie";
doc["category"] = "Notebook";
doc["vec"] = {0.1, 0.3, 0.2, 0.4};
ASSERT_TRUE(coll1->add(doc.dump()).ok());
std::vector<sort_by> sort_fields;
CollectionManager::parse_sort_by_str("_eval([(category:Fresh):3,(category:Notebook):2,(category:Phone):1]):desc", sort_fields);
auto results_op = coll1->search("*", {"vec"}, "", {"name"}, sort_fields, {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, "vec:([0.1, 0.4, 0.2, 0.3])");
ASSERT_EQ(true, results_op.ok());
ASSERT_EQ(3, results_op.get()["found"].get<size_t>());
ASSERT_EQ(3, results_op.get()["hits"].size());
ASSERT_EQ("0", results_op.get()["hits"][0]["document"]["id"].get<std::string>());
ASSERT_EQ("2", results_op.get()["hits"][1]["document"]["id"].get<std::string>());
ASSERT_EQ("1", results_op.get()["hits"][2]["document"]["id"].get<std::string>());
}
TEST_F(CollectionVectorTest, EmbedFromOptionalNullField) {
nlohmann::json schema = R"({
"name": "objects",