# # Copyright 2025 The InfiniFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # from concurrent.futures import ThreadPoolExecutor, as_completed from operator import attrgetter import pytest from configs import DATASET_NAME_LIMIT, DEFAULT_PARSER_CONFIG, HOST_ADDRESS, INVALID_API_TOKEN from hypothesis import example, given, settings from ragflow_sdk import DataSet, RAGFlow from utils import encode_avatar from utils.file_utils import create_image_file from utils.hypothesis_utils import valid_names @pytest.mark.usefixtures("clear_datasets") class TestAuthorization: @pytest.mark.p2 @pytest.mark.parametrize( "invalid_auth, expected_message", [ (None, ""), (INVALID_API_TOKEN, ""), ], ids=["empty_auth", "invalid_api_token"], ) def test_auth_invalid(self, invalid_auth, expected_message): client = RAGFlow(invalid_auth, HOST_ADDRESS) with pytest.raises(Exception) as exception_info: client.create_dataset(**{"name": "auth_test"}) assert str(exception_info.value) == expected_message @pytest.mark.usefixtures("clear_datasets") class TestCapability: @pytest.mark.p3 def test_create_dataset_1k(self, client): count = 1_000 for i in range(count): payload = {"name": f"dataset_{i}"} client.create_dataset(**payload) assert len(client.list_datasets(page_size=2000)) == count @pytest.mark.p3 def test_create_dataset_concurrent(self, client): count = 100 with ThreadPoolExecutor(max_workers=5) as executor: futures = [executor.submit(client.create_dataset, **{"name": f"dataset_{i}"}) for i in range(100)] responses = list(as_completed(futures)) assert len(responses) == count, responses @pytest.mark.usefixtures("clear_datasets") class TestDatasetCreate: @pytest.mark.p1 @given(name=valid_names()) @example("a" * 128) @settings(max_examples=20) def test_name(self, client, name): dataset = client.create_dataset(**{"name": name}) assert dataset.name == name, str(dataset) @pytest.mark.p2 @pytest.mark.parametrize( "name, expected_message", [ ("", "String should have at least 1 character"), (" ", "String should have at least 1 character"), ("a" * (DATASET_NAME_LIMIT + 1), "String should have at most 128 characters"), (0, "not instance of"), (None, "not instance of"), ], ids=["empty_name", "space_name", "too_long_name", "invalid_name", "None_name"], ) def test_name_invalid(self, client, name, expected_message): with pytest.raises(Exception) as exception_info: client.create_dataset(**{"name": name}) assert expected_message in str(exception_info.value), str(exception_info.value) @pytest.mark.p3 def test_name_duplicated(self, client): name = "duplicated_name" payload = {"name": name} client.create_dataset(**payload) dataset = client.create_dataset(**payload) assert dataset.name == name + "(1)", str(dataset) @pytest.mark.p3 def test_name_case_insensitive(self, client): name = "CaseInsensitive" payload = {"name": name.upper()} client.create_dataset(**payload) payload = {"name": name.lower()} dataset = client.create_dataset(**payload) assert dataset.name == name.lower() + "(1)", str(dataset) @pytest.mark.p2 def test_avatar(self, client, tmp_path): fn = create_image_file(tmp_path / "ragflow_test.png") payload = { "name": "avatar", "avatar": f"data:image/png;base64,{encode_avatar(fn)}", } client.create_dataset(**payload) @pytest.mark.p3 def test_avatar_exceeds_limit_length(self, client): payload = {"name": "avatar_exceeds_limit_length", "avatar": "a" * 65536} with pytest.raises(Exception) as exception_info: client.create_dataset(**payload) assert "String should have at most 65535 characters" in str(exception_info.value), str(exception_info.value) @pytest.mark.p3 @pytest.mark.parametrize( "name, prefix, expected_message", [ ("empty_prefix", "", "Missing MIME prefix. Expected format: data:;base64,"), ("missing_comma", "data:image/png;base64", "Missing MIME prefix. Expected format: data:;base64,"), ("unsupported_mine_type", "invalid_mine_prefix:image/png;base64,", "Invalid MIME prefix format. Must start with 'data:'"), ("invalid_mine_type", "data:unsupported_mine_type;base64,", "Unsupported MIME type. Allowed: ['image/jpeg', 'image/png']"), ], ids=["empty_prefix", "missing_comma", "unsupported_mine_type", "invalid_mine_type"], ) def test_avatar_invalid_prefix(self, client, tmp_path, name, prefix, expected_message): fn = create_image_file(tmp_path / "ragflow_test.png") payload = { "name": name, "avatar": f"{prefix}{encode_avatar(fn)}", } with pytest.raises(Exception) as exception_info: client.create_dataset(**payload) assert expected_message in str(exception_info.value), str(exception_info.value) @pytest.mark.p3 def test_avatar_unset(self, client): payload = {"name": "avatar_unset"} dataset = client.create_dataset(**payload) assert dataset.avatar is None, str(dataset) @pytest.mark.p2 def test_description(self, client): payload = {"name": "description", "description": "description"} dataset = client.create_dataset(**payload) assert dataset.description == "description", str(dataset) @pytest.mark.p3 def test_description_exceeds_limit_length(self, client): payload = {"name": "description_exceeds_limit_length", "description": "a" * 65536} with pytest.raises(Exception) as exception_info: client.create_dataset(**payload) assert "String should have at most 65535 characters" in str(exception_info.value), str(exception_info.value) @pytest.mark.p3 def test_description_unset(self, client): payload = {"name": "description_unset"} dataset = client.create_dataset(**payload) assert dataset.description is None, str(dataset) @pytest.mark.p3 def test_description_none(self, client): payload = {"name": "description_none", "description": None} dataset = client.create_dataset(**payload) assert dataset.description is None, str(dataset) @pytest.mark.p1 @pytest.mark.parametrize( "name, embedding_model", [ ("BAAI/bge-small-en-v1.5@Builtin", "BAAI/bge-small-en-v1.5@Builtin"), ("embedding-3@ZHIPU-AI", "embedding-3@ZHIPU-AI"), ], ids=["builtin_baai", "tenant_zhipu"], ) def test_embedding_model(self, client, name, embedding_model): payload = {"name": name, "embedding_model": embedding_model} dataset = client.create_dataset(**payload) assert dataset.embedding_model == embedding_model, str(dataset) @pytest.mark.p2 @pytest.mark.parametrize( "name, embedding_model", [ ("unknown_llm_name", "unknown@ZHIPU-AI"), ("unknown_llm_factory", "embedding-3@unknown"), ("tenant_no_auth_default_tenant_llm", "text-embedding-v3@Tongyi-Qianwen"), ("tenant_no_auth", "text-embedding-3-small@OpenAI"), ], ids=["unknown_llm_name", "unknown_llm_factory", "tenant_no_auth_default_tenant_llm", "tenant_no_auth"], ) def test_embedding_model_invalid(self, client, name, embedding_model): payload = {"name": name, "embedding_model": embedding_model} with pytest.raises(Exception) as exception_info: client.create_dataset(**payload) if "tenant_no_auth" in name: assert str(exception_info.value) == f"Unauthorized model: <{embedding_model}>", str(exception_info.value) else: assert str(exception_info.value) == f"Unsupported model: <{embedding_model}>", str(exception_info.value) @pytest.mark.p2 @pytest.mark.parametrize( "name, embedding_model", [ ("empty", ""), ("space", " "), ("missing_at", "BAAI/bge-small-en-v1.5Builtin"), ("missing_model_name", "@Builtin"), ("missing_provider", "BAAI/bge-small-en-v1.5@"), ("whitespace_only_model_name", " @Builtin"), ("whitespace_only_provider", "BAAI/bge-small-en-v1.5@ "), ], ids=["empty", "space", "missing_at", "empty_model_name", "empty_provider", "whitespace_only_model_name", "whitespace_only_provider"], ) def test_embedding_model_format(self, client, name, embedding_model): payload = {"name": name, "embedding_model": embedding_model} with pytest.raises(Exception) as exception_info: client.create_dataset(**payload) if name in ["empty", "space", "missing_at"]: assert "Embedding model identifier must follow @ format" in str(exception_info.value), str(exception_info.value) else: assert "Both model_name and provider must be non-empty strings" in str(exception_info.value), str(exception_info.value) @pytest.mark.p2 def test_embedding_model_unset(self, client): payload = {"name": "embedding_model_unset"} dataset = client.create_dataset(**payload) assert dataset.embedding_model == "BAAI/bge-small-en-v1.5@Builtin", str(dataset) @pytest.mark.p2 def test_embedding_model_none(self, client): payload = {"name": "embedding_model_none", "embedding_model": None} dataset = client.create_dataset(**payload) assert dataset.embedding_model == "BAAI/bge-small-en-v1.5@Builtin", str(dataset) @pytest.mark.p2 @pytest.mark.parametrize( "name, permission", [ ("me", "me"), ("team", "team"), ], ids=["me", "team"], ) def test_permission(self, client, name, permission): payload = {"name": name, "permission": permission} dataset = client.create_dataset(**payload) assert dataset.permission == permission.lower().strip(), str(dataset) @pytest.mark.p2 @pytest.mark.parametrize( "name, permission", [ ("empty", ""), ("unknown", "unknown"), ("me_upercase", "ME"), ("team_upercase", "TEAM"), ("whitespace", " ME "), ], ids=["empty", "unknown", "me_upercase", "team_upercase", "whitespace"], ) def test_permission_invalid(self, client, name, permission): payload = {"name": name, "permission": permission} with pytest.raises(Exception) as exception_info: client.create_dataset(**payload) assert "Input should be 'me' or 'team'" in str(exception_info.value) @pytest.mark.p2 def test_permission_unset(self, client): payload = {"name": "permission_unset"} dataset = client.create_dataset(**payload) assert dataset.permission == "me", str(dataset) @pytest.mark.p3 def test_permission_none(self, client): payload = {"name": "permission_none", "permission": None} with pytest.raises(Exception) as exception_info: client.create_dataset(**payload) assert "not instance of" in str(exception_info.value), str(exception_info.value) @pytest.mark.p1 @pytest.mark.parametrize( "name, chunk_method", [ ("naive", "naive"), ("book", "book"), ("email", "email"), ("laws", "laws"), ("manual", "manual"), ("one", "one"), ("paper", "paper"), ("picture", "picture"), ("presentation", "presentation"), ("qa", "qa"), ("table", "table"), ("tag", "tag"), ("resume", "resume") ], ids=["naive", "book", "email", "laws", "manual", "one", "paper", "picture", "presentation", "qa", "table", "tag", "resume"], ) def test_chunk_method(self, client, name, chunk_method): payload = {"name": name, "chunk_method": chunk_method} dataset = client.create_dataset(**payload) assert dataset.chunk_method == chunk_method, str(dataset) @pytest.mark.p2 @pytest.mark.parametrize( "name, chunk_method", [ ("empty", ""), ("unknown", "unknown"), ], ids=["empty", "unknown"], ) def test_chunk_method_invalid(self, client, name, chunk_method): payload = {"name": name, "chunk_method": chunk_method} with pytest.raises(Exception) as exception_info: client.create_dataset(**payload) assert "Input should be 'naive', 'book', 'email', 'laws', 'manual', 'one', 'paper', 'picture', 'presentation', 'qa', 'table', 'tag' or 'resume'" in str(exception_info.value), str(exception_info.value) @pytest.mark.p2 def test_chunk_method_unset(self, client): payload = {"name": "chunk_method_unset"} dataset = client.create_dataset(**payload) assert dataset.chunk_method == "naive", str(dataset) @pytest.mark.p3 def test_chunk_method_none(self, client): payload = {"name": "chunk_method_none", "chunk_method": None} with pytest.raises(Exception) as exception_info: client.create_dataset(**payload) assert "not instance of" in str(exception_info.value), str(exception_info.value) @pytest.mark.p1 @pytest.mark.parametrize( "name, parser_config", [ ("auto_keywords_min", {"auto_keywords": 0}), ("auto_keywords_mid", {"auto_keywords": 16}), ("auto_keywords_max", {"auto_keywords": 32}), ("auto_questions_min", {"auto_questions": 0}), ("auto_questions_mid", {"auto_questions": 5}), ("auto_questions_max", {"auto_questions": 10}), ("chunk_token_num_min", {"chunk_token_num": 1}), ("chunk_token_num_mid", {"chunk_token_num": 1024}), ("chunk_token_num_max", {"chunk_token_num": 2048}), ("delimiter", {"delimiter": "\n"}), ("delimiter_space", {"delimiter": " "}), ("html4excel_true", {"html4excel": True}), ("html4excel_false", {"html4excel": False}), ("layout_recognize_DeepDOC", {"layout_recognize": "DeepDOC"}), ("layout_recognize_navie", {"layout_recognize": "Plain Text"}), ("tag_kb_ids", {"tag_kb_ids": ["1", "2"]}), ("topn_tags_min", {"topn_tags": 1}), ("topn_tags_mid", {"topn_tags": 5}), ("topn_tags_max", {"topn_tags": 10}), ("filename_embd_weight_min", {"filename_embd_weight": 0.1}), ("filename_embd_weight_mid", {"filename_embd_weight": 0.5}), ("filename_embd_weight_max", {"filename_embd_weight": 1.0}), ("task_page_size_min", {"task_page_size": 1}), ("task_page_size_None", {"task_page_size": None}), ("pages", {"pages": [[1, 100]]}), ("pages_none", {"pages": None}), ("graphrag_true", {"graphrag": {"use_graphrag": True}}), ("graphrag_false", {"graphrag": {"use_graphrag": False}}), ("graphrag_entity_types", {"graphrag": {"entity_types": ["age", "sex", "height", "weight"]}}), ("graphrag_method_general", {"graphrag": {"method": "general"}}), ("graphrag_method_light", {"graphrag": {"method": "light"}}), ("graphrag_community_true", {"graphrag": {"community": True}}), ("graphrag_community_false", {"graphrag": {"community": False}}), ("graphrag_resolution_true", {"graphrag": {"resolution": True}}), ("graphrag_resolution_false", {"graphrag": {"resolution": False}}), ("raptor_true", {"raptor": {"use_raptor": True}}), ("raptor_false", {"raptor": {"use_raptor": False}}), ("raptor_prompt", {"raptor": {"prompt": "Who are you?"}}), ("raptor_max_token_min", {"raptor": {"max_token": 1}}), ("raptor_max_token_mid", {"raptor": {"max_token": 1024}}), ("raptor_max_token_max", {"raptor": {"max_token": 2048}}), ("raptor_threshold_min", {"raptor": {"threshold": 0.0}}), ("raptor_threshold_mid", {"raptor": {"threshold": 0.5}}), ("raptor_threshold_max", {"raptor": {"threshold": 1.0}}), ("raptor_max_cluster_min", {"raptor": {"max_cluster": 1}}), ("raptor_max_cluster_mid", {"raptor": {"max_cluster": 512}}), ("raptor_max_cluster_max", {"raptor": {"max_cluster": 1024}}), ("raptor_random_seed_min", {"raptor": {"random_seed": 0}}), ], ids=[ "auto_keywords_min", "auto_keywords_mid", "auto_keywords_max", "auto_questions_min", "auto_questions_mid", "auto_questions_max", "chunk_token_num_min", "chunk_token_num_mid", "chunk_token_num_max", "delimiter", "delimiter_space", "html4excel_true", "html4excel_false", "layout_recognize_DeepDOC", "layout_recognize_navie", "tag_kb_ids", "topn_tags_min", "topn_tags_mid", "topn_tags_max", "filename_embd_weight_min", "filename_embd_weight_mid", "filename_embd_weight_max", "task_page_size_min", "task_page_size_None", "pages", "pages_none", "graphrag_true", "graphrag_false", "graphrag_entity_types", "graphrag_method_general", "graphrag_method_light", "graphrag_community_true", "graphrag_community_false", "graphrag_resolution_true", "graphrag_resolution_false", "raptor_true", "raptor_false", "raptor_prompt", "raptor_max_token_min", "raptor_max_token_mid", "raptor_max_token_max", "raptor_threshold_min", "raptor_threshold_mid", "raptor_threshold_max", "raptor_max_cluster_min", "raptor_max_cluster_mid", "raptor_max_cluster_max", "raptor_random_seed_min", ], ) def test_parser_config(self, client, name, parser_config): parser_config_o = DataSet.ParserConfig(client, parser_config) payload = {"name": name, "parser_config": parser_config_o} dataset = client.create_dataset(**payload) for k, v in parser_config.items(): if isinstance(v, dict): for kk, vv in v.items(): assert attrgetter(f"{k}.{kk}")(dataset.parser_config) == vv, str(dataset) else: assert attrgetter(k)(dataset.parser_config) == v, str(dataset) @pytest.mark.p2 @pytest.mark.parametrize( "name, parser_config, expected_message", [ ("auto_keywords_min_limit", {"auto_keywords": -1}, "Input should be greater than or equal to 0"), ("auto_keywords_max_limit", {"auto_keywords": 33}, "Input should be less than or equal to 32"), ("auto_keywords_float_not_allowed", {"auto_keywords": 3.14}, "Input should be a valid integer"), ("auto_keywords_type_invalid", {"auto_keywords": "string"}, "Input should be a valid integer"), ("auto_questions_min_limit", {"auto_questions": -1}, "Input should be greater than or equal to 0"), ("auto_questions_max_limit", {"auto_questions": 11}, "Input should be less than or equal to 10"), ("auto_questions_float_not_allowed", {"auto_questions": 3.14}, "Input should be a valid integer"), ("auto_questions_type_invalid", {"auto_questions": "string"}, "Input should be a valid integer"), ("chunk_token_num_min_limit", {"chunk_token_num": 0}, "Input should be greater than or equal to 1"), ("chunk_token_num_max_limit", {"chunk_token_num": 2049}, "Input should be less than or equal to 2048"), ("chunk_token_num_float_not_allowed", {"chunk_token_num": 3.14}, "Input should be a valid integer"), ("chunk_token_num_type_invalid", {"chunk_token_num": "string"}, "Input should be a valid integer"), ("delimiter_empty", {"delimiter": ""}, "String should have at least 1 character"), ("html4excel_type_invalid", {"html4excel": "string"}, "Input should be a valid boolean"), ("tag_kb_ids_not_list", {"tag_kb_ids": "1,2"}, "Input should be a valid list"), ("tag_kb_ids_int_in_list", {"tag_kb_ids": [1, 2]}, "Input should be a valid string"), ("topn_tags_min_limit", {"topn_tags": 0}, "Input should be greater than or equal to 1"), ("topn_tags_max_limit", {"topn_tags": 11}, "Input should be less than or equal to 10"), ("topn_tags_float_not_allowed", {"topn_tags": 3.14}, "Input should be a valid integer"), ("topn_tags_type_invalid", {"topn_tags": "string"}, "Input should be a valid integer"), ("filename_embd_weight_min_limit", {"filename_embd_weight": -1}, "Input should be greater than or equal to 0"), ("filename_embd_weight_max_limit", {"filename_embd_weight": 1.1}, "Input should be less than or equal to 1"), ("filename_embd_weight_type_invalid", {"filename_embd_weight": "string"}, "Input should be a valid number"), ("task_page_size_min_limit", {"task_page_size": 0}, "Input should be greater than or equal to 1"), ("task_page_size_float_not_allowed", {"task_page_size": 3.14}, "Input should be a valid integer"), ("task_page_size_type_invalid", {"task_page_size": "string"}, "Input should be a valid integer"), ("pages_not_list", {"pages": "1,2"}, "Input should be a valid list"), ("pages_not_list_in_list", {"pages": ["1,2"]}, "Input should be a valid list"), ("pages_not_int_list", {"pages": [["string1", "string2"]]}, "Input should be a valid integer"), ("graphrag_type_invalid", {"graphrag": {"use_graphrag": "string"}}, "Input should be a valid boolean"), ("graphrag_entity_types_not_list", {"graphrag": {"entity_types": "1,2"}}, "Input should be a valid list"), ("graphrag_entity_types_not_str_in_list", {"graphrag": {"entity_types": [1, 2]}}, "nput should be a valid string"), ("graphrag_method_unknown", {"graphrag": {"method": "unknown"}}, "Input should be 'light', 'general' or 'ner'"), ("graphrag_method_none", {"graphrag": {"method": None}}, "Input should be 'light', 'general' or 'ner'"), ("graphrag_community_type_invalid", {"graphrag": {"community": "string"}}, "Input should be a valid boolean"), ("graphrag_resolution_type_invalid", {"graphrag": {"resolution": "string"}}, "Input should be a valid boolean"), ("raptor_type_invalid", {"raptor": {"use_raptor": "string"}}, "Input should be a valid boolean"), ("raptor_prompt_empty", {"raptor": {"prompt": ""}}, "String should have at least 1 character"), ("raptor_prompt_space", {"raptor": {"prompt": " "}}, "String should have at least 1 character"), ("raptor_max_token_min_limit", {"raptor": {"max_token": 0}}, "Input should be greater than or equal to 1"), ("raptor_max_token_max_limit", {"raptor": {"max_token": 2049}}, "Input should be less than or equal to 2048"), ("raptor_max_token_float_not_allowed", {"raptor": {"max_token": 3.14}}, "Input should be a valid integer"), ("raptor_max_token_type_invalid", {"raptor": {"max_token": "string"}}, "Input should be a valid integer"), ("raptor_threshold_min_limit", {"raptor": {"threshold": -0.1}}, "Input should be greater than or equal to 0"), ("raptor_threshold_max_limit", {"raptor": {"threshold": 1.1}}, "Input should be less than or equal to 1"), ("raptor_threshold_type_invalid", {"raptor": {"threshold": "string"}}, "Input should be a valid number"), ("raptor_max_cluster_min_limit", {"raptor": {"max_cluster": 0}}, "Input should be greater than or equal to 1"), ("raptor_max_cluster_max_limit", {"raptor": {"max_cluster": 1025}}, "Input should be less than or equal to 1024"), ("raptor_max_cluster_float_not_allowed", {"raptor": {"max_cluster": 3.14}}, "Input should be a valid integer"), ("raptor_max_cluster_type_invalid", {"raptor": {"max_cluster": "string"}}, "Input should be a valid integer"), ("raptor_random_seed_min_limit", {"raptor": {"random_seed": -1}}, "Input should be greater than or equal to 0"), ("raptor_random_seed_float_not_allowed", {"raptor": {"random_seed": 3.14}}, "Input should be a valid integer"), ("raptor_random_seed_type_invalid", {"raptor": {"random_seed": "string"}}, "Input should be a valid integer"), ("parser_config_type_invalid", {"delimiter": "a" * 65536}, "Parser config exceeds size limit (max 65,535 characters)"), ], ids=[ "auto_keywords_min_limit", "auto_keywords_max_limit", "auto_keywords_float_not_allowed", "auto_keywords_type_invalid", "auto_questions_min_limit", "auto_questions_max_limit", "auto_questions_float_not_allowed", "auto_questions_type_invalid", "chunk_token_num_min_limit", "chunk_token_num_max_limit", "chunk_token_num_float_not_allowed", "chunk_token_num_type_invalid", "delimiter_empty", "html4excel_type_invalid", "tag_kb_ids_not_list", "tag_kb_ids_int_in_list", "topn_tags_min_limit", "topn_tags_max_limit", "topn_tags_float_not_allowed", "topn_tags_type_invalid", "filename_embd_weight_min_limit", "filename_embd_weight_max_limit", "filename_embd_weight_type_invalid", "task_page_size_min_limit", "task_page_size_float_not_allowed", "task_page_size_type_invalid", "pages_not_list", "pages_not_list_in_list", "pages_not_int_list", "graphrag_type_invalid", "graphrag_entity_types_not_list", "graphrag_entity_types_not_str_in_list", "graphrag_method_unknown", "graphrag_method_none", "graphrag_community_type_invalid", "graphrag_resolution_type_invalid", "raptor_type_invalid", "raptor_prompt_empty", "raptor_prompt_space", "raptor_max_token_min_limit", "raptor_max_token_max_limit", "raptor_max_token_float_not_allowed", "raptor_max_token_type_invalid", "raptor_threshold_min_limit", "raptor_threshold_max_limit", "raptor_threshold_type_invalid", "raptor_max_cluster_min_limit", "raptor_max_cluster_max_limit", "raptor_max_cluster_float_not_allowed", "raptor_max_cluster_type_invalid", "raptor_random_seed_min_limit", "raptor_random_seed_float_not_allowed", "raptor_random_seed_type_invalid", "parser_config_type_invalid", ], ) def test_parser_config_invalid(self, client, name, parser_config, expected_message): parser_config_o = DataSet.ParserConfig(client, parser_config) payload = {"name": name, "parser_config": parser_config_o} with pytest.raises(Exception) as exception_info: client.create_dataset(**payload) assert expected_message in str(exception_info.value), str(exception_info.value) @pytest.mark.p2 def test_parser_config_empty(self, client): excepted_value = DataSet.ParserConfig( client, DEFAULT_PARSER_CONFIG, ) parser_config_o = DataSet.ParserConfig(client, {}) payload = {"name": "parser_config_empty", "parser_config": parser_config_o} dataset = client.create_dataset(**payload) assert str(dataset.parser_config) == str(excepted_value), str(dataset) @pytest.mark.p2 def test_parser_config_unset(self, client): excepted_value = DataSet.ParserConfig( client, DEFAULT_PARSER_CONFIG, ) payload = {"name": "parser_config_unset"} dataset = client.create_dataset(**payload) assert str(dataset.parser_config) == str(excepted_value), str(dataset) @pytest.mark.p3 def test_parser_config_none(self, client): excepted_value = DataSet.ParserConfig( client, DEFAULT_PARSER_CONFIG, ) payload = {"name": "parser_config_empty", "parser_config": None} dataset = client.create_dataset(**payload) assert str(dataset.parser_config) == str(excepted_value), str(dataset) @pytest.mark.p2 @pytest.mark.parametrize( "payload", [ {"name": "id", "id": "id"}, {"name": "tenant_id", "tenant_id": "e57c1966f99211efb41e9e45646e0111"}, {"name": "created_by", "created_by": "created_by"}, {"name": "create_date", "create_date": "Tue, 11 Mar 2025 13:37:23 GMT"}, {"name": "create_time", "create_time": 1741671443322}, {"name": "update_date", "update_date": "Tue, 11 Mar 2025 13:37:23 GMT"}, {"name": "update_time", "update_time": 1741671443339}, {"name": "document_count", "document_count": 1}, {"name": "chunk_count", "chunk_count": 1}, {"name": "token_num", "token_num": 1}, {"name": "status", "status": "1"}, {"name": "pagerank", "pagerank": 50}, {"name": "unknown_field", "unknown_field": "unknown_field"}, ], ) def test_unsupported_field(self, client, payload): with pytest.raises(Exception) as exception_info: client.create_dataset(**payload) assert "got an unexpected keyword argument" in str(exception_info.value), str(exception_info.value) @pytest.mark.usefixtures("clear_datasets") class TestParserConfigBugFix: @pytest.mark.p1 def test_parser_config_missing_raptor_and_graphrag(self, client): parser_config = DataSet.ParserConfig(client, {"chunk_token_num": 1024}) payload = {"name": "test_parser_config_missing_fields_sdk", "parser_config": parser_config} dataset = client.create_dataset(**payload) config = dataset.parser_config assert hasattr(config, "raptor"), "raptor field should be present" assert hasattr(config, "graphrag"), "graphrag field should be present" assert config.raptor.use_raptor is False, "raptor.use_raptor should default to False" assert config.graphrag.use_graphrag is False, "graphrag.use_graphrag should default to False" assert config.chunk_token_num == 1024, "User-provided chunk_token_num should be preserved" @pytest.mark.p1 def test_parser_config_with_only_raptor(self, client): parser_config = DataSet.ParserConfig(client, {"chunk_token_num": 1024, "raptor": {"use_raptor": True}}) payload = {"name": "test_parser_config_only_raptor_sdk", "parser_config": parser_config} dataset = client.create_dataset(**payload) config = dataset.parser_config assert config.raptor.use_raptor is True, "User-provided raptor.use_raptor should be preserved" assert hasattr(config, "graphrag"), "graphrag field should be present" assert config.graphrag.use_graphrag is False, "graphrag.use_graphrag should default to False" @pytest.mark.p1 def test_parser_config_with_only_graphrag(self, client): parser_config = DataSet.ParserConfig(client, {"chunk_token_num": 1024, "graphrag": {"use_graphrag": True}}) payload = {"name": "test_parser_config_only_graphrag_sdk", "parser_config": parser_config} dataset = client.create_dataset(**payload) config = dataset.parser_config assert hasattr(config, "raptor"), "raptor field should be present" assert config.raptor.use_raptor is False, "raptor.use_raptor should default to False" assert config.graphrag.use_graphrag is True, "User-provided graphrag.use_graphrag should be preserved" @pytest.mark.p1 def test_parser_config_with_both_fields(self, client): parser_config = DataSet.ParserConfig(client, {"chunk_token_num": 1024, "raptor": {"use_raptor": True}, "graphrag": {"use_graphrag": True}}) payload = {"name": "test_parser_config_both_fields_sdk", "parser_config": parser_config} dataset = client.create_dataset(**payload) config = dataset.parser_config assert config.raptor.use_raptor is True, "User-provided raptor.use_raptor should be preserved" assert config.graphrag.use_graphrag is True, "User-provided graphrag.use_graphrag should be preserved" @pytest.mark.p2 @pytest.mark.parametrize("chunk_method", ["qa", "manual", "paper", "book", "laws", "presentation"]) def test_parser_config_different_chunk_methods(self, client, chunk_method): parser_config = DataSet.ParserConfig(client, {"chunk_token_num": 512}) payload = {"name": f"test_parser_config_{chunk_method}_sdk", "chunk_method": chunk_method, "parser_config": parser_config} dataset = client.create_dataset(**payload) config = dataset.parser_config assert hasattr(config, "raptor"), f"raptor field should be present for {chunk_method}" assert hasattr(config, "graphrag"), f"graphrag field should be present for {chunk_method}" assert config.raptor.use_raptor is False, f"raptor.use_raptor should default to False for {chunk_method}" assert config.graphrag.use_graphrag is False, f"graphrag.use_graphrag should default to False for {chunk_method}"