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Update the test with more detailed example

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This commit is contained in:
ozanarmagan 2023-07-03 13:19:21 +03:00
parent 992ff2d9ad
commit 1ffa3c4ed2
1 changed files with 40 additions and 34 deletions
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74
test/collection_vector_search_test.cpp
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@ -679,34 +679,37 @@ TEST_F(CollectionVectorTest, VectorWithNullValue) {
}
TEST_F(CollectionVectorTest, HybridSearchWithExplicitVector) {
nlohmann::json schema = R"({
"name": "coll1",
"fields": [
{"name": "name", "type": "string"},
{"name": "vec", "type": "float[]", "embed":{"from": ["name"], "model_config": {"model_name": "ts/e5-small"}}}
]
})"_json;
nlohmann::json schema = R"({
"name": "objects",
"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");
Collection* coll1 = collectionManager.create_collection(schema).get();
auto op = collectionManager.create_collection(schema);
ASSERT_TRUE(op.ok());
Collection* coll = op.get();
nlohmann::json object;
object["name"] = "butter";
auto add_op = coll->add(object.dump());
ASSERT_TRUE(add_op.ok());
nlohmann::json doc;
object["name"] = "butterball";
add_op = coll->add(object.dump());
ASSERT_TRUE(add_op.ok());
doc["name"] = "micheal scott";
ASSERT_TRUE(coll1->add(doc.dump()).ok());
doc["name"] = "jim halpert";
ASSERT_TRUE(coll1->add(doc.dump()).ok());
doc["name"] = "pam beesly";
ASSERT_TRUE(coll1->add(doc.dump()).ok());
object["name"] = "butterfly";
add_op = coll->add(object.dump());
ASSERT_TRUE(add_op.ok());
nlohmann::json model_config = R"({
"model_name": "ts/e5-small"
})"_json;
auto query_embedding = TextEmbedderManager::get_instance().get_text_embedder(model_config).get()->Embed("dwight schrute");
auto query_embedding = TextEmbedderManager::get_instance().get_text_embedder(model_config).get()->Embed("butter");
std::string vec_string = "[";
for(size_t i = 0; i < query_embedding.embedding.size(); i++) {
@ -716,30 +719,33 @@ TEST_F(CollectionVectorTest, HybridSearchWithExplicitVector) {
}
}
vec_string += "]";
auto results_op = coll1->search("john", {"name"}, "", {}, {}, {0}, 20, 1, FREQUENCY, {true}, Index::DROP_TOKENS_THRESHOLD,
auto search_res_op = coll->search("butter", {"name"}, "", {}, {}, {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:(" + vec_string + ")");
ASSERT_EQ(true, results_op.ok());
false, true, "embedding:(" + vec_string + ")");
ASSERT_TRUE(search_res_op.ok());
auto search_res = search_res_op.get();
ASSERT_EQ(3, search_res["found"].get<size_t>());
ASSERT_EQ(3, search_res["hits"].size());
// Hybrid search with rank fusion order:
// 1. butter (1/1 * 0.7) + (1/1 * 0.3) = 1
// 2. butterfly (1/2 * 0.7) + (1/3 * 0.3) = 0.45
// 3. butterball (1/3 * 0.7) + (1/2 * 0.3) = 0.383
ASSERT_EQ("butter", search_res["hits"][0]["document"]["name"].get<std::string>());
ASSERT_EQ("butterfly", search_res["hits"][1]["document"]["name"].get<std::string>());
ASSERT_EQ("butterball", search_res["hits"][2]["document"]["name"].get<std::string>());
ASSERT_EQ(3, results_op.get()["found"].get<size_t>());
ASSERT_EQ(3, results_op.get()["hits"].size());
// order:
// 1. jim halpert
// 2. michael scott
// 3. pam beesly
ASSERT_EQ("jim halpert", results_op.get()["hits"][0]["document"]["name"].get<std::string>());
ASSERT_EQ("micheal scott", results_op.get()["hits"][1]["document"]["name"].get<std::string>());
ASSERT_EQ("pam beesly", results_op.get()["hits"][2]["document"]["name"].get<std::string>());
ASSERT_FLOAT_EQ((1.0/1.0 * 0.7) + (1.0/1.0 * 0.3), search_res["hits"][0]["hybrid_search_info"]["rank_fusion_score"].get<float>());
ASSERT_FLOAT_EQ((1.0/2.0 * 0.7) + (1.0/3.0 * 0.3), search_res["hits"][1]["hybrid_search_info"]["rank_fusion_score"].get<float>());
ASSERT_FLOAT_EQ((1.0/3.0 * 0.7) + (1.0/2.0 * 0.3), search_res["hits"][2]["hybrid_search_info"]["rank_fusion_score"].get<float>());
}
TEST_F(CollectionVectorTest, HybridSearchOnlyVectorMatches) {
nlohmann::json schema = R"({
"name": "coll1",