imbajin commented on code in PR #315: URL: https://github.com/apache/hugegraph-ai/pull/315#discussion_r3266757278
########## hugegraph-llm/src/tests/integration/test_flows_integration.py: ########## @@ -0,0 +1,329 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. + +import pytest + +from hugegraph_llm.config.prompt_config import PromptConfig +from hugegraph_llm.demo.rag_demo.rag_block import update_ui_configs +from hugegraph_llm.demo.rag_demo.text2gremlin_block import build_example_vector_index +from hugegraph_llm.demo.rag_demo.vector_graph_block import load_query_examples +from hugegraph_llm.flows import FlowName +from hugegraph_llm.flows.scheduler import SchedulerSingleton +from hugegraph_llm.utils.log import log + + +class TestFlowsIntegration: + """Flow集成测试 - 验证各个Flow能正常执行不抛异常""" + + @pytest.fixture(autouse=True) + def setup(self): + self.index_text = """ + 梁漱溟年轻时，一日，他与父亲梁济讨论当时一战欧洲的时局，梁济突然问道：“这个世界会好吗？”梁漱溟答：“我相信世界是一天一天往好里去的。”梁济叹道：“能好就好啊！”然后离家，三日后，梁济投湖自尽。晚年梁漱溟回忆自己的一生和跌宕起伏的近代社会，总结了一本书，书名就叫《这个世界会好吗？》。梁漱溟的回答与年轻时一致。但很多人特别是遗老遗少们总在回忆往日的时光，仿佛那是人类的黄金时代。如同鲁迅笔下的九斤老太，整日里念叨着“一代不如一代”。或者极端如梁济，对世界未来充满悲观，一死了之。在今天的时代，很多人认为“世界正变得越来越糟”，这其中不乏知名的知识分子。平克将这种情况称之为「进步恐惧症」，并总结为「认知偏差」。因为每天的新闻报道里总是充斥着战争、恐怖主义、犯� �污染等坏消息，不是因为这些事情是主流，而是因为它们是热点，导致给人们的印象是世界越来越糟。所谓“好事不出门，坏事传千里”，而在互联网时代，发达的信息传播让坏事传播的更快更广。要纠正这种「可得性偏差」的方法是用数据说话。数字是最能反应趋势，看战争的比例、犯罪死亡人数在总人数的占比，就能看出犯罪是增加了，还是减少了。实际上，从各种数字显示，人类暴力事件在历史呈明显的下降趋势，这在平克之前发表的另一大部头著作《人性中的善良天使：暴力为什么会减少》中详细阐述过。世界变得更好了，说到底就是进步。 + """ + self.scheduler = SchedulerSingleton.get_instance() + + def test_build_knowledge_graph(self): + try: + res = self.scheduler.schedule_flow(FlowName.BUILD_VECTOR_INDEX, [self.index_text]) + assert "chunks" in res, "The result of BUILD_VECTOR_INDEX flow should contain 'chunks' field" + log.info("✓ BUILD_VECTOR_INDEX flow executed successfully") + + schema = """ + { + "vertexlabels": [ + { + "id": 1, + "name": "Person", + "id_strategy": "PRIMARY_KEY", + "primary_keys": [ + "name" + ], + "properties": [ + "name", + "age", + "occupation" + ] + }, + { + "id": 2, + "name": "Book", + "id_strategy": "PRIMARY_KEY", + "primary_keys": [ + "title" + ], + "properties": [ + "title", + "author", + "year" + ] + }, + { + "id": 3, + "name": "Concept", + "id_strategy": "PRIMARY_KEY", + "primary_keys": [ + "name" + ], + "properties": [ + "name", + "description" + ] + } + ], + "edgelabels": [ + { + "id": 1, + "name": "Wrote", + "source_label": "Person", + "target_label": "Book", + "properties": [] + }, + { + "id": 2, + "name": "Discussed", + "source_label": "Person", + "target_label": "Concept", + "properties": [] + }, + { + "id": 3, + "name": "Believes", + "source_label": "Person", + "target_label": "Concept", + "properties": [] + } + ] + } + """ + + data = self.scheduler.schedule_flow( + FlowName.GRAPH_EXTRACT, + schema, + [self.index_text], + PromptConfig.extract_graph_prompt_EN, + "property_graph", + ) + assert "vertices" in data, "The result of GRAPH_EXTRACT flow should contain 'vertices' field" + assert "edges" in data, "The result of GRAPH_EXTRACT flow should contain 'edges' field" + log.info("✓ GRAPH_EXTRACT flow executed successfully") + + res = self.scheduler.schedule_flow(FlowName.IMPORT_GRAPH_DATA, data, schema) + assert res is not None, "The result of IMPORT_GRAPH_DATA flow should not be None" + log.info("✓ IMPORT_GRAPH_DATA flow executed successfully") + + self.scheduler.schedule_flow(FlowName.UPDATE_VID_EMBEDDINGS) + log.info("✓ UPDATE_VID_EMBEDDING flow executed successfully") + except Exception as e: + pytest.fail(f"BUILD_VECTOR_INDEX flow failed: {e}") + + def test_schema_generator(self): + try: + query_examples = load_query_examples() + + few_shot = """ + { + "vertexlabels": [ + { + "id": 1, + "name": "person", + "id_strategy": "PRIMARY_KEY", + "primary_keys": [ + "name" + ], + "properties": [ + "name", + "age", + "occupation" + ] + }, + { + "id": 2, + "name": "webpage", + "id_strategy": "PRIMARY_KEY", + "primary_keys": [ + "name" + ], + "properties": [ + "name", + "url" + ] + } + ], + "edgelabels": [ + { + "id": 1, + "name": "roommate", + "source_label": "person", + "target_label": "person", + "properties": [ + "date" + ] + }, + { + "id": 2, + "name": "link", + "source_label": "webpage", + "target_label": "person", + "properties": [] + } + ] + } + """ + + self.scheduler.schedule_flow(FlowName.BUILD_SCHEMA, [self.index_text], query_examples, few_shot) + except Exception as e: + pytest.fail(f"BUILD_VECTOR_INDEX flow failed: {e}") + + def test_graph_extract_prompt(self): + try: + scenario = "social relationships" + example_name = "Official Person-Relationship Extraction" + + res = self.scheduler.schedule_flow(FlowName.PROMPT_GENERATE, self.index_text, scenario, example_name) + assert res is not None, "The result of PROMPT_GENERATE flow should not be None" + except Exception as e: + pytest.fail(f"BUILD_VECTOR_INDEX flow failed: {e}") + + def test_rag(self): + query = "梁漱溟和梁济的关系是什么？" + + raw_answer = True + vector_only_answer = False + graph_only_answer = False + graph_vector_answer = False + graph_ratio = 0.6 + rerank_method = "bleu" + near_neighbor_first = False + custom_related_information = "" + + graph_search, gremlin_prompt, vector_search = update_ui_configs( Review Comment: ‼️ **Critical**：`test_rag` 实际只测了 raw 模式 + 测试会写回 `config_prompt.yaml` **问题 1（死代码 → 名义 4 模式实际只测 1 种）** `update_ui_configs(...)`（line 213-222）只调用一次，传入的 `vector_only_answer / graph_only_answer / graph_vector_answer` 都是 `False`，因此返回 `vector_search=False, graph_search=False`。 后续四段 `schedule_flow` 始终复用这同一组标记（见 line 227-228 / 251-252 / 275-276 / 299-300），而对局部 bool 的反复赋值（line 244-247 / 268-271 / 292-295）根本没传给 flow，是死代码。 => 四次调用实际全部以"无检索"模式运行；`RAG_VECTOR_ONLY / RAG_GRAPH_ONLY / RAG_GRAPH_VECTOR` 这三条核心路径**没被实际验证**。CONTRIBUTING.md 中的 "All RAG modes" 描述不成立。 **问题 2（副作用：测试会改 contributor 的 yaml）** `update_ui_configs` 在 prompt 内容变化时会触发 `prompt.update_yaml_file()`（见 `rag_block.py:141-147`）。Contributor 跑完该测试后，工作区里的 `config_prompt.yaml` 会被悄悄改写为测试中的 EN prompt 与 `default_question="梁漱溟和梁济的关系是什么？"`，下次 `git status` 会冒出无关 diff，极易误提交。 **修法**：参数化覆盖 4 种模式 + 直接构造 `vector_search / graph_search`，绕开 demo helper 副作用： ```python @pytest.mark.parametrize( ("flow_name", "raw", "vec_only", "graph_only", "graph_vec"), [ (FlowName.RAG_RAW, True, False, False, False), (FlowName.RAG_VECTOR_ONLY, False, True, False, False), (FlowName.RAG_GRAPH_ONLY, False, False, True, False), (FlowName.RAG_GRAPH_VECTOR, False, False, False, True), ], ) def test_rag(self, flow_name, raw, vec_only, graph_only, graph_vec): query = "梁漱溟和梁济的关系是什么？" graph_search = graph_only or graph_vec vector_search = vec_only or graph_vec res = self.scheduler.schedule_flow( flow_name, query=query, vector_search=vector_search, graph_search=graph_search, raw_answer=raw, vector_only_answer=vec_only, graph_only_answer=graph_only, graph_vector_answer=graph_vec, graph_ratio=0.6, rerank_method="bleu", near_neighbor_first=False, custom_related_information="", answer_prompt=PromptConfig.answer_prompt_EN, keywords_extract_prompt=PromptConfig.keywords_extract_prompt_EN, gremlin_tmpl_num=-1, gremlin_prompt=PromptConfig.gremlin_generate_prompt_EN, ) assert isinstance(res, dict) and res.get("answer"), f"{flow_name} returned empty answer" ``` ########## hugegraph-llm/src/tests/integration/test_flows_integration.py: ########## @@ -0,0 +1,329 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. + +import pytest + +from hugegraph_llm.config.prompt_config import PromptConfig +from hugegraph_llm.demo.rag_demo.rag_block import update_ui_configs +from hugegraph_llm.demo.rag_demo.text2gremlin_block import build_example_vector_index +from hugegraph_llm.demo.rag_demo.vector_graph_block import load_query_examples +from hugegraph_llm.flows import FlowName +from hugegraph_llm.flows.scheduler import SchedulerSingleton +from hugegraph_llm.utils.log import log + + +class TestFlowsIntegration: + """Flow集成测试 - 验证各个Flow能正常执行不抛异常""" + + @pytest.fixture(autouse=True) + def setup(self): + self.index_text = """ + 梁漱溟年轻时，一日，他与父亲梁济讨论当时一战欧洲的时局，梁济突然问道：“这个世界会好吗？”梁漱溟答：“我相信世界是一天一天往好里去的。”梁济叹道：“能好就好啊！”然后离家，三日后，梁济投湖自尽。晚年梁漱溟回忆自己的一生和跌宕起伏的近代社会，总结了一本书，书名就叫《这个世界会好吗？》。梁漱溟的回答与年轻时一致。但很多人特别是遗老遗少们总在回忆往日的时光，仿佛那是人类的黄金时代。如同鲁迅笔下的九斤老太，整日里念叨着“一代不如一代”。或者极端如梁济，对世界未来充满悲观，一死了之。在今天的时代，很多人认为“世界正变得越来越糟”，这其中不乏知名的知识分子。平克将这种情况称之为「进步恐惧症」，并总结为「认知偏差」。因为每天的新闻报道里总是充斥着战争、恐怖主义、犯� �污染等坏消息，不是因为这些事情是主流，而是因为它们是热点，导致给人们的印象是世界越来越糟。所谓“好事不出门，坏事传千里”，而在互联网时代，发达的信息传播让坏事传播的更快更广。要纠正这种「可得性偏差」的方法是用数据说话。数字是最能反应趋势，看战争的比例、犯罪死亡人数在总人数的占比，就能看出犯罪是增加了，还是减少了。实际上，从各种数字显示，人类暴力事件在历史呈明显的下降趋势，这在平克之前发表的另一大部头著作《人性中的善良天使：暴力为什么会减少》中详细阐述过。世界变得更好了，说到底就是进步。 + """ + self.scheduler = SchedulerSingleton.get_instance() + + def test_build_knowledge_graph(self): + try: + res = self.scheduler.schedule_flow(FlowName.BUILD_VECTOR_INDEX, [self.index_text]) + assert "chunks" in res, "The result of BUILD_VECTOR_INDEX flow should contain 'chunks' field" + log.info("✓ BUILD_VECTOR_INDEX flow executed successfully") + + schema = """ + { + "vertexlabels": [ + { + "id": 1, + "name": "Person", + "id_strategy": "PRIMARY_KEY", + "primary_keys": [ + "name" + ], + "properties": [ + "name", + "age", + "occupation" + ] + }, + { + "id": 2, + "name": "Book", + "id_strategy": "PRIMARY_KEY", + "primary_keys": [ + "title" + ], + "properties": [ + "title", + "author", + "year" + ] + }, + { + "id": 3, + "name": "Concept", + "id_strategy": "PRIMARY_KEY", + "primary_keys": [ + "name" + ], + "properties": [ + "name", + "description" + ] + } + ], + "edgelabels": [ + { + "id": 1, + "name": "Wrote", + "source_label": "Person", + "target_label": "Book", + "properties": [] + }, + { + "id": 2, + "name": "Discussed", + "source_label": "Person", + "target_label": "Concept", + "properties": [] + }, + { + "id": 3, + "name": "Believes", + "source_label": "Person", + "target_label": "Concept", + "properties": [] + } + ] + } + """ + + data = self.scheduler.schedule_flow( + FlowName.GRAPH_EXTRACT, + schema, + [self.index_text], + PromptConfig.extract_graph_prompt_EN, + "property_graph", + ) + assert "vertices" in data, "The result of GRAPH_EXTRACT flow should contain 'vertices' field" + assert "edges" in data, "The result of GRAPH_EXTRACT flow should contain 'edges' field" + log.info("✓ GRAPH_EXTRACT flow executed successfully") + + res = self.scheduler.schedule_flow(FlowName.IMPORT_GRAPH_DATA, data, schema) + assert res is not None, "The result of IMPORT_GRAPH_DATA flow should not be None" + log.info("✓ IMPORT_GRAPH_DATA flow executed successfully") + + self.scheduler.schedule_flow(FlowName.UPDATE_VID_EMBEDDINGS) + log.info("✓ UPDATE_VID_EMBEDDING flow executed successfully") + except Exception as e: + pytest.fail(f"BUILD_VECTOR_INDEX flow failed: {e}") Review Comment: ‼️ **Critical**：复制粘贴错误信息 + `try/except + pytest.fail` 反模式 本行（line 131）以及 line 189、line 199 三处 `pytest.fail(...)` **全部**写成 `"BUILD_VECTOR_INDEX flow failed: {e}"`，但实际抛出的可能是 `BUILD_SCHEMA / PROMPT_GENERATE / IMPORT_GRAPH_DATA` 等任意一个 flow。对于一个面向 contributor 本地自查的 smoke test，错误信息**直接误导新人去排查错误的 flow**。 更深层的问题是 `try/except + pytest.fail(str(e))` 本身就是反模式： 1. pytest 默认遇到异常就会 fail 并展示完整 traceback；这层包装**反而吞掉**异常类型与 cause chain； 2. 多余的 try 块降低了可读性。 **最简修法**：直接删除 `try/except` 让异常自然冒泡。例如本测试（`test_build_knowledge_graph`）： ```python def test_build_knowledge_graph(self): res = self.scheduler.schedule_flow(FlowName.BUILD_VECTOR_INDEX, [self.index_text]) assert "chunks" in res log.info("BUILD_VECTOR_INDEX flow executed successfully") # ...后续步骤同样直接调用，不要包 try/except ``` 如果非要保留上下文，至少把 flow 名称变量化：`pytest.fail(f"{current_flow} failed: {e}")`。 ########## hugegraph-llm/src/tests/integration/test_flows_integration.py: ########## @@ -0,0 +1,329 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. + +import pytest + +from hugegraph_llm.config.prompt_config import PromptConfig +from hugegraph_llm.demo.rag_demo.rag_block import update_ui_configs +from hugegraph_llm.demo.rag_demo.text2gremlin_block import build_example_vector_index +from hugegraph_llm.demo.rag_demo.vector_graph_block import load_query_examples +from hugegraph_llm.flows import FlowName +from hugegraph_llm.flows.scheduler import SchedulerSingleton +from hugegraph_llm.utils.log import log + + +class TestFlowsIntegration: + """Flow集成测试 - 验证各个Flow能正常执行不抛异常""" + + @pytest.fixture(autouse=True) + def setup(self): + self.index_text = """ + 梁漱溟年轻时，一日，他与父亲梁济讨论当时一战欧洲的时局，梁济突然问道：“这个世界会好吗？”梁漱溟答：“我相信世界是一天一天往好里去的。”梁济叹道：“能好就好啊！”然后离家，三日后，梁济投湖自尽。晚年梁漱溟回忆自己的一生和跌宕起伏的近代社会，总结了一本书，书名就叫《这个世界会好吗？》。梁漱溟的回答与年轻时一致。但很多人特别是遗老遗少们总在回忆往日的时光，仿佛那是人类的黄金时代。如同鲁迅笔下的九斤老太，整日里念叨着“一代不如一代”。或者极端如梁济，对世界未来充满悲观，一死了之。在今天的时代，很多人认为“世界正变得越来越糟”，这其中不乏知名的知识分子。平克将这种情况称之为「进步恐惧症」，并总结为「认知偏差」。因为每天的新闻报道里总是充斥着战争、恐怖主义、犯� �污染等坏消息，不是因为这些事情是主流，而是因为它们是热点，导致给人们的印象是世界越来越糟。所谓“好事不出门，坏事传千里”，而在互联网时代，发达的信息传播让坏事传播的更快更广。要纠正这种「可得性偏差」的方法是用数据说话。数字是最能反应趋势，看战争的比例、犯罪死亡人数在总人数的占比，就能看出犯罪是增加了，还是减少了。实际上，从各种数字显示，人类暴力事件在历史呈明显的下降趋势，这在平克之前发表的另一大部头著作《人性中的善良天使：暴力为什么会减少》中详细阐述过。世界变得更好了，说到底就是进步。 + """ + self.scheduler = SchedulerSingleton.get_instance() + + def test_build_knowledge_graph(self): Review Comment: ⚠️ **Important**：单个测试串行 4 个 flow，配合错误信息 bug 让定位极困难 `test_build_knowledge_graph` 串行执行 `BUILD_VECTOR_INDEX → GRAPH_EXTRACT → IMPORT_GRAPH_DATA → UPDATE_VID_EMBEDDINGS` 四个 flow（line 41-129）。若 `IMPORT_GRAPH_DATA` 挂掉，配合上面那条复制粘贴 bug，contributor 看到的错误是 `"BUILD_VECTOR_INDEX flow failed"`，会被严重误导。 另外 CONTRIBUTING.md 表格把它标为 1 项测试，与实际行为不符。 **修法**：拆成 4 个独立测试，用 fixture 共享上一步的产物；或至少改用 `pytest-subtests`： ```python def test_build_kg__vector_index(self): res = self.scheduler.schedule_flow(FlowName.BUILD_VECTOR_INDEX, [self.index_text]) assert "chunks" in res and len(res["chunks"]) > 0 def test_build_kg__graph_extract(self): data = self.scheduler.schedule_flow(FlowName.GRAPH_EXTRACT, ...) assert data["vertices"] and data["edges"] # 以此类推 ``` 好处：失败定位精确到 flow；CONTRIBUTING.md 表格与代码对齐；contributor 跑挂时不需要从头再来。 ########## hugegraph-llm/src/tests/integration/test_flows_integration.py: ########## @@ -0,0 +1,329 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. + +import pytest + +from hugegraph_llm.config.prompt_config import PromptConfig +from hugegraph_llm.demo.rag_demo.rag_block import update_ui_configs +from hugegraph_llm.demo.rag_demo.text2gremlin_block import build_example_vector_index +from hugegraph_llm.demo.rag_demo.vector_graph_block import load_query_examples +from hugegraph_llm.flows import FlowName +from hugegraph_llm.flows.scheduler import SchedulerSingleton +from hugegraph_llm.utils.log import log + + +class TestFlowsIntegration: + """Flow集成测试 - 验证各个Flow能正常执行不抛异常""" + + @pytest.fixture(autouse=True) + def setup(self): Review Comment: ‼️ **Critical**：缺 `should_skip_external()` 守卫，本地默认命令必爆 `hugegraph-llm/src/tests/conftest.py:45` 强制设置 `SKIP_EXTERNAL_SERVICES=true`，所有现存 integration test（如 `test_kg_construction.py:126`、`test_rag_pipeline.py:113`）都会调用 `should_skip_external()` 在此前提下自动 skip。 新文件**没有这个守卫** → contributor 跑 `pytest src/tests/` 或 `pytest src/tests/integration/` 时，其它 integration test 全部跳过，**只有这套新 test 不跳过且必爆**（因为它会真实调 LLM/HugeGraph 但默认 SKIP=true 时基础设施不一定齐全），对 contributor 来说是最糟糕的体验。 @coderzc 已在 P2 提出过一次，作者回复"故意不进 CI"——但**进不进 CI 与本地默认 pytest 行为是两回事**。至少二选一： **方案 A**：在 setup 中加守卫，与现有 integration test 一致： ```python from src.tests.test_utils import should_skip_external @pytest.fixture(autouse=True) def setup(self): if should_skip_external(): pytest.skip("Skipping tests that require external services") self.index_text = "..." self.scheduler = SchedulerSingleton.get_instance() ``` **方案 B**：用自定义 mark + CONTRIBUTING.md 引导： ```python # pytest.ini 或 pyproject.toml [tool.pytest.ini_options] markers = ["local_e2e: tests requiring HugeGraph + LLM API key (skipped by default)"] # 测试文件 @pytest.mark.local_e2e class TestFlowsIntegration: ... ``` 并在 CONTRIBUTING.md 写明 `pytest -m local_e2e` 才会跑这套测试。 ########## hugegraph-llm/src/tests/integration/test_flows_integration.py: ########## @@ -0,0 +1,329 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. + +import pytest + +from hugegraph_llm.config.prompt_config import PromptConfig +from hugegraph_llm.demo.rag_demo.rag_block import update_ui_configs +from hugegraph_llm.demo.rag_demo.text2gremlin_block import build_example_vector_index +from hugegraph_llm.demo.rag_demo.vector_graph_block import load_query_examples +from hugegraph_llm.flows import FlowName +from hugegraph_llm.flows.scheduler import SchedulerSingleton +from hugegraph_llm.utils.log import log + + +class TestFlowsIntegration: + """Flow集成测试 - 验证各个Flow能正常执行不抛异常""" + + @pytest.fixture(autouse=True) + def setup(self): + self.index_text = """ + 梁漱溟年轻时，一日，他与父亲梁济讨论当时一战欧洲的时局，梁济突然问道：“这个世界会好吗？”梁漱溟答：“我相信世界是一天一天往好里去的。”梁济叹道：“能好就好啊！”然后离家，三日后，梁济投湖自尽。晚年梁漱溟回忆自己的一生和跌宕起伏的近代社会，总结了一本书，书名就叫《这个世界会好吗？》。梁漱溟的回答与年轻时一致。但很多人特别是遗老遗少们总在回忆往日的时光，仿佛那是人类的黄金时代。如同鲁迅笔下的九斤老太，整日里念叨着“一代不如一代”。或者极端如梁济，对世界未来充满悲观，一死了之。在今天的时代，很多人认为“世界正变得越来越糟”，这其中不乏知名的知识分子。平克将这种情况称之为「进步恐惧症」，并总结为「认知偏差」。因为每天的新闻报道里总是充斥着战争、恐怖主义、犯� �污染等坏消息，不是因为这些事情是主流，而是因为它们是热点，导致给人们的印象是世界越来越糟。所谓“好事不出门，坏事传千里”，而在互联网时代，发达的信息传播让坏事传播的更快更广。要纠正这种「可得性偏差」的方法是用数据说话。数字是最能反应趋势，看战争的比例、犯罪死亡人数在总人数的占比，就能看出犯罪是增加了，还是减少了。实际上，从各种数字显示，人类暴力事件在历史呈明显的下降趋势，这在平克之前发表的另一大部头著作《人性中的善良天使：暴力为什么会减少》中详细阐述过。世界变得更好了，说到底就是进步。 + """ + self.scheduler = SchedulerSingleton.get_instance() Review Comment: ⚠️ **Important**：`SchedulerSingleton` 是进程级单例，跨测试共享 pipeline_pool `SchedulerSingleton.get_instance()`（见 `flows/scheduler.py:181-191`）是进程级单例，其 `pipeline_pool` 内每个 `GPipelineManager` 都会缓存 pipeline。这意味着： 1. **顺序耦合**：`test_build_knowledge_graph` 写入的图数据 / 向量索引会被后续 `test_rag` 看到。如果用户用 `pytest -k test_rag` 单独跑，`test_rag` 是否通过取决于此前是否跑过 `test_build_knowledge_graph`，行为不可复现。 2. **脏 pipeline**：某测试中途异常未走到 `manager.release/add` 时，下一个测试可能拿到错误状态的 pipeline。 对 contributor 在反复修复-重试的场景下尤其糟糕：上一次失败留下的脏状态会让下一次的失败原因看起来与代码无关。 **修法**：teardown 中重置；或为每个测试用唯一的 `graph_name`（避免共享数据）。例如： ```python @pytest.fixture(autouse=True) def setup(self): if should_skip_external(): pytest.skip("...") self.index_text = "..." huge_settings.graph_name = f"test_{uuid.uuid4().hex[:8]}" self.scheduler = SchedulerSingleton.get_instance() yield # teardown：清空该 graph，或释放 pipeline ``` 至少在文件 docstring 写明"测试间存在隐式数据依赖"，让维护者心里有数。 ########## hugegraph-llm/src/tests/integration/test_flows_integration.py: ########## @@ -0,0 +1,329 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. + +import pytest + +from hugegraph_llm.config.prompt_config import PromptConfig +from hugegraph_llm.demo.rag_demo.rag_block import update_ui_configs +from hugegraph_llm.demo.rag_demo.text2gremlin_block import build_example_vector_index +from hugegraph_llm.demo.rag_demo.vector_graph_block import load_query_examples +from hugegraph_llm.flows import FlowName +from hugegraph_llm.flows.scheduler import SchedulerSingleton +from hugegraph_llm.utils.log import log + + +class TestFlowsIntegration: + """Flow集成测试 - 验证各个Flow能正常执行不抛异常""" + + @pytest.fixture(autouse=True) + def setup(self): + self.index_text = """ + 梁漱溟年轻时，一日，他与父亲梁济讨论当时一战欧洲的时局，梁济突然问道：“这个世界会好吗？”梁漱溟答：“我相信世界是一天一天往好里去的。”梁济叹道：“能好就好啊！”然后离家，三日后，梁济投湖自尽。晚年梁漱溟回忆自己的一生和跌宕起伏的近代社会，总结了一本书，书名就叫《这个世界会好吗？》。梁漱溟的回答与年轻时一致。但很多人特别是遗老遗少们总在回忆往日的时光，仿佛那是人类的黄金时代。如同鲁迅笔下的九斤老太，整日里念叨着“一代不如一代”。或者极端如梁济，对世界未来充满悲观，一死了之。在今天的时代，很多人认为“世界正变得越来越糟”，这其中不乏知名的知识分子。平克将这种情况称之为「进步恐惧症」，并总结为「认知偏差」。因为每天的新闻报道里总是充斥着战争、恐怖主义、犯� �污染等坏消息，不是因为这些事情是主流，而是因为它们是热点，导致给人们的印象是世界越来越糟。所谓“好事不出门，坏事传千里”，而在互联网时代，发达的信息传播让坏事传播的更快更广。要纠正这种「可得性偏差」的方法是用数据说话。数字是最能反应趋势，看战争的比例、犯罪死亡人数在总人数的占比，就能看出犯罪是增加了，还是减少了。实际上，从各种数字显示，人类暴力事件在历史呈明显的下降趋势，这在平克之前发表的另一大部头著作《人性中的善良天使：暴力为什么会减少》中详细阐述过。世界变得更好了，说到底就是进步。 + """ + self.scheduler = SchedulerSingleton.get_instance() + + def test_build_knowledge_graph(self): + try: + res = self.scheduler.schedule_flow(FlowName.BUILD_VECTOR_INDEX, [self.index_text]) + assert "chunks" in res, "The result of BUILD_VECTOR_INDEX flow should contain 'chunks' field" + log.info("✓ BUILD_VECTOR_INDEX flow executed successfully") + + schema = """ + { + "vertexlabels": [ + { + "id": 1, + "name": "Person", + "id_strategy": "PRIMARY_KEY", + "primary_keys": [ + "name" + ], + "properties": [ + "name", + "age", + "occupation" + ] + }, + { + "id": 2, + "name": "Book", + "id_strategy": "PRIMARY_KEY", + "primary_keys": [ + "title" + ], + "properties": [ + "title", + "author", + "year" + ] + }, + { + "id": 3, + "name": "Concept", + "id_strategy": "PRIMARY_KEY", + "primary_keys": [ + "name" + ], + "properties": [ + "name", + "description" + ] + } + ], + "edgelabels": [ + { + "id": 1, + "name": "Wrote", + "source_label": "Person", + "target_label": "Book", + "properties": [] + }, + { + "id": 2, + "name": "Discussed", + "source_label": "Person", + "target_label": "Concept", + "properties": [] + }, + { + "id": 3, + "name": "Believes", + "source_label": "Person", + "target_label": "Concept", + "properties": [] + } + ] + } + """ + + data = self.scheduler.schedule_flow( + FlowName.GRAPH_EXTRACT, + schema, + [self.index_text], + PromptConfig.extract_graph_prompt_EN, + "property_graph", + ) + assert "vertices" in data, "The result of GRAPH_EXTRACT flow should contain 'vertices' field" + assert "edges" in data, "The result of GRAPH_EXTRACT flow should contain 'edges' field" + log.info("✓ GRAPH_EXTRACT flow executed successfully") + + res = self.scheduler.schedule_flow(FlowName.IMPORT_GRAPH_DATA, data, schema) + assert res is not None, "The result of IMPORT_GRAPH_DATA flow should not be None" + log.info("✓ IMPORT_GRAPH_DATA flow executed successfully") + + self.scheduler.schedule_flow(FlowName.UPDATE_VID_EMBEDDINGS) + log.info("✓ UPDATE_VID_EMBEDDING flow executed successfully") + except Exception as e: + pytest.fail(f"BUILD_VECTOR_INDEX flow failed: {e}") + + def test_schema_generator(self): + try: + query_examples = load_query_examples() + + few_shot = """ + { + "vertexlabels": [ + { + "id": 1, + "name": "person", + "id_strategy": "PRIMARY_KEY", + "primary_keys": [ + "name" + ], + "properties": [ + "name", + "age", + "occupation" + ] + }, + { + "id": 2, + "name": "webpage", + "id_strategy": "PRIMARY_KEY", + "primary_keys": [ + "name" + ], + "properties": [ + "name", + "url" + ] + } + ], + "edgelabels": [ + { + "id": 1, + "name": "roommate", + "source_label": "person", + "target_label": "person", + "properties": [ + "date" + ] + }, + { + "id": 2, + "name": "link", + "source_label": "webpage", + "target_label": "person", + "properties": [] + } + ] + } + """ + + self.scheduler.schedule_flow(FlowName.BUILD_SCHEMA, [self.index_text], query_examples, few_shot) Review Comment: ⚠️ **Important**：断言过弱 / `test_schema_generator` 无任何断言 本行 `self.scheduler.schedule_flow(FlowName.BUILD_SCHEMA, ...)` 没有任何断言，等价于"只要不抛异常就算通过"。schema 生成器返回空 list、错误结构、或 LLM 回了一句 `"抱歉，我无法生成"` 都会被判通过。 同样的弱断言遍布全文件： - line 197 / 242 / 266 / 290 / 314 / 329：仅 `assert res is not None` - line 125：`assert res is not None`（IMPORT_GRAPH_DATA） 对于面向 contributor 的本地自查，"通过"应该真正校验返回结构。 **最低限度**修法： ```python res = self.scheduler.schedule_flow(FlowName.BUILD_SCHEMA, ...) assert isinstance(res, dict) assert res.get("schema", {}).get("vertexlabels"), "BUILD_SCHEMA returned empty vertexlabels" assert res["schema"].get("edgelabels"), "BUILD_SCHEMA returned empty edgelabels" ``` 理想做法：把期望产物存到 `src/tests/data/flows/expected_schema.json`（仓库已有 `src/tests/data/` 目录），用结构 diff 校验。 ########## CONTRIBUTING.md: ########## @@ -0,0 +1,41 @@ +# Contributing to HugeGraph-AI + +Thank you for your interest in contributing! Before submitting a pull request, please run the end-to-end integration tests locally to make sure nothing is broken. + +## Prerequisites + +1. **HugeGraph Server** running on `localhost:8080` (see [README.md](./README.md) for setup) +2. **Python 3.10+** with dependencies installed via `uv sync --extra llm` +3. **Proxy users**: If you have `http_proxy`/`https_proxy` set, make sure to exclude localhost: + ```bash + export no_proxy=localhost,127.0.0.1 + export NO_PROXY=localhost,127.0.0.1 + ``` + +## Running Integration Tests + +```bash +# Activate the virtual environment +source .venv/bin/activate + +# Run the end-to-end integration tests +cd hugegraph-llm +python -m pytest src/tests/integration/test_flows_integration.py -v Review Comment: ⚠️ **Important**：项目用 `uv` 管理依赖，CONTRIBUTING.md 主命令应统一为 `uv run pytest` `hugegraph-llm/AGENTS.md` 与 `.github/workflows/hugegraph-llm.yml:82` 都使用 `uv run pytest`。本文件 line 23 的 `python -m pytest` 在 contributor 没正确激活 `.venv`、或 `.venv` 缺 `--extra llm` 时会跑到系统 Python，得到莫名其妙的 import error。 CONTRIBUTING.md 是 contributor 的入口，命令必须与 CI 保持一致。 ```python # Run the end-to-end integration tests cd hugegraph-llm uv run pytest src/tests/integration/test_flows_integration.py -v ``` 另外，由于 conftest.py 默认 `SKIP_EXTERNAL_SERVICES=true`，contributor 直接跑命令时这套 test 可能被全部 skip。需要在文档里告知： ```bash # 显式开启外部服务测试 SKIP_EXTERNAL_SERVICES=false uv run pytest src/tests/integration/test_flows_integration.py -v ``` ########## CONTRIBUTING.md: ########## @@ -0,0 +1,41 @@ +# Contributing to HugeGraph-AI + +Thank you for your interest in contributing! Before submitting a pull request, please run the end-to-end integration tests locally to make sure nothing is broken. + +## Prerequisites + +1. **HugeGraph Server** running on `localhost:8080` (see [README.md](./README.md) for setup) +2. **Python 3.10+** with dependencies installed via `uv sync --extra llm` +3. **Proxy users**: If you have `http_proxy`/`https_proxy` set, make sure to exclude localhost: + ```bash + export no_proxy=localhost,127.0.0.1 + export NO_PROXY=localhost,127.0.0.1 + ``` + +## Running Integration Tests + +```bash +# Activate the virtual environment +source .venv/bin/activate + +# Run the end-to-end integration tests +cd hugegraph-llm +python -m pytest src/tests/integration/test_flows_integration.py -v +``` + +All 6 tests must pass before you submit your code: Review Comment: 🧹 **Minor**：CONTRIBUTING.md 选址 / 范围 / 强制性 1. **选址错位**：标题 "Contributing to HugeGraph-AI" 但内容只覆盖 `hugegraph-llm` 子模块。HugeGraph-AI 是 monorepo（含 `hugegraph-ml`、`hugegraph-python-client`、`vermeer-python-client`）。建议： - **方案 A**：把当前内容移动到 `hugegraph-llm/TESTING.md`（与 `hugegraph-llm/AGENTS.md` 同级），把根 CONTRIBUTING.md 作为通用入口； - **方案 B**：保留根级 CONTRIBUTING.md，但把当前内容降级为 "### Module: hugegraph-llm" 章节，并补充 ASF 通用部分（DCO/sign-off、commit message 规范、ICLA 链接、Issue/PR 模板）。 2. **强制性过度**：line 26 "All 6 tests must pass before you submit your code" 强制要求 contributor 本地启动 HugeGraph + 配置 LLM API key 才能贡献。对纯文档 / UI / 非 flow PR 是过度要求。建议改为： > 如果你的修改涉及 flow / 索引 / RAG 相关代码，请在本地通过下列 6 个测试。 3. **额外缺失**：当前文档没列出 LLM API key 与 embedding provider 等前置条件，但作者表态"测试需要 api-key"——这条信息应当出现在 Prerequisites。 4. **数字硬编码**："All 6 tests must pass" / "`6 passed`"（line 39）会随测试增删而过时，建议改成"全部通过"。 -- This is an automated message from the Apache Git Service. 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