[ENH] Upgrade tests and release to Python 3.12 #1715
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Needed to fix the failing property tests in #1715 ## Description of changes *Summarize the changes made by this PR.* - Improvements & Bug fixes - Moved the model update after conditional checks for new_name and metadata. - New functionality - ... ## Test plan *How are these changes tested?* - [ ] Tests pass locally with `pytest` for python, `yarn test` for js ## Documentation Changes Failure logs + Error analysis: ``` > assert c.metadata == self.model[coll.name] E AssertionError: assert {'g': 1.1, 'n...': 31734, ...} == {'3': 'd71IL'...235e-208, ...} E E Left contains 5 more items: E {'g': 1.1, E 'n1dUTalF-MY': -1000000.0, E 'ugXZ_hK': 5494, E 'xVW09xUpDZA': 31734, E 'y': 'G3EtXTZ'} E Right contains 9 more items: E {'3': 'd71IL', E '45227B': '65', E '7DjCkbusc-K': 'vc94', E '8-tD9nJd': 4.8728578364902235e-208, E 'Bpyj': -675165.8688164671, E 'Uy6KZu6abCD9Z': -72, E 'giC': -6.103515625e-05, E 'pO4': -0.0, E 'r3': -41479} E E Full diff: E { E + 'g': 1.1, E + 'n1dUTalF-MY': -1000000.0, E + 'ugXZ_hK': 5494, E + 'xVW09xUpDZA': 31734, E + 'y': 'G3EtXTZ', E - '3': 'd71IL', E - '45227B': '65', E - '7DjCkbusc-K': 'vc94', E - '8-tD9nJd': 4.8728578364902235e-208, E - 'Bpyj': -675165.8688164671, E - 'Uy6KZu6abCD9Z': -72, E - 'giC': -6.103515625e-05, E - 'pO4': -0.0, E - 'r3': -41479, E } E Falsifying example: E state = CollectionStateMachine() E state.initialize() E state.list_collections_with_limit_offset(limit=5, offset=0) E state.list_collections_with_limit_offset(limit=4, offset=5) E (v1,) = state.get_or_create_coll(coll=Collection(name='E60V1ekr9eDcL\n', id=UUID('4435abf2-9fc6-4d5a-bb7b-33177a956d44'), metadata={'_m5jalwo': -228}, dimension=1356, dtype=<class 'numpy.float64'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=False, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181bb0590>), new_metadata={'k5o6Q': 'Op', E 'LP': -5.960464477539063e-08, E 'pzHdzczVCn': '81', E '7': False, E 'e4Lz': 999999.0, E '206': False}) E (v2,) = state.get_or_create_coll(coll=v1, new_metadata=None) E (v3,) = state.get_or_create_coll(coll=v1, new_metadata={'4OQN': -2097032423, E 'cW': -0.99999, E 'o6wq3': -147, E 'M8j3KBU': -2.2250738585072014e-308, E 'D8nZrA0': 252, E 'up4P_': 34761, E 'L_win': -6.103515625e-05, E '5kt': '_q', E 'UybO2dJF4': -0.3333333333333333, E 'NfQ83VsmI': 'Qpy', E 'fk': -1.192092896e-07, E 'J1ck': 'ozL'}) E (v4,) = state.get_or_create_coll(coll=Collection(name='nOeHg-OXVl', id=UUID('9c28b027-9f22-409c-b3fd-c5de03b60018'), metadata=None, dimension=1009, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=True, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181bdfe50>), new_metadata={'p4isW': 'k8l', E 'k2tFn3v1E': True, E 'R': 'ji-2d5lDGV', E 'K5vdi': False, E 'TZs': False, E 'OgJ_DZ2j': False, E 'ovZjD3': -64297, E '9p': True, E '32f3nw8h2d54LPCzsV': 1733994327, E '4P': 2.896381722565434e-121}) E state.list_collections_with_limit_offset(limit=2, offset=0) E state.list_collections_with_limit_offset(limit=3, offset=0) E state.list_collections_with_limit_offset(limit=5, offset=5) E (v5,) = state.modify_coll(coll=v4, new_metadata=None, new_name=None) E (v6,) = state.get_or_create_coll(coll=Collection(name='A1w5m1l5I\n', id=UUID('606d59a6-6f66-456d-81ca-a8ea029c318c'), metadata={'3': '6Y'}, dimension=1544, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=False, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d6d110>), new_metadata=None) E (v7,) = state.get_or_create_coll(coll=v4, new_metadata={'01316': -0.0, '14UwVu': 81, 'C9eMDDdnB0oy': False, 'n964': '0a'}) E state.modify_coll(coll=v7, new_metadata={}, new_name='B-5Z2m2j52121') E state.get_or_create_coll(coll=Collection(name='E31\n', id=UUID('e67426e8-8595-4916-92a6-b2777b52f157'), metadata={'0Kr5Wp': -769, '9xT': 143980.04500299558, '8': True}, dimension=1800, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=True, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d6d6d0>), new_metadata={}) E state.list_collections_with_limit_offset(limit=2, offset=1) E state.list_collections_with_limit_offset(limit=2, offset=0) E state.list_collections_with_limit_offset(limit=1, offset=0) E state.list_collections_with_limit_offset(limit=1, offset=1) E (v8,) = state.get_or_create_coll(coll=Collection(name='A00\n', id=UUID('01522a4f-3383-4a58-8b18-0418e38e3ec6'), metadata=None, dimension=1032, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=False, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d94bd0>), new_metadata=None) E (v9,) = state.get_or_create_coll(coll=v6, new_metadata=None) E state.list_collections_with_limit_offset(limit=3, offset=2) E (v10,) = state.modify_coll(coll=v3, new_metadata=None, new_name=None) E (v11,) = state.modify_coll(coll=v10, new_metadata=None, new_name=None) E state.modify_coll(coll=v9, new_metadata={}, new_name=None) E (v12,) = state.get_or_create_coll(coll=Collection(name='A10\n', id=UUID('01efb806-fffa-4ce6-b285-b9aae55f50af'), metadata={}, dimension=258, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=False, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd183bbe5d0>), new_metadata=None) E state.modify_coll(coll=v11, new_metadata={}, new_name='A01011110\n') E state.list_collections_with_limit_offset(limit=3, offset=1) ------ Problem start here ------ E (v13,) = state.get_or_create_coll(coll=Collection(name='C1030', id=UUID('7858d028-1295-4769-96c1-e58bf242b7bd'), metadata={}, dimension=2, dtype=<class 'numpy.float32'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=False, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181bbff10>), new_metadata=None) E (v14,) = state.get_or_create_coll(coll=Collection(name='A01200671\n', id=UUID('f77d01a4-e43f-4b17-9579-daadccad2f71'), metadata={'0': 'L', '01': -4}, dimension=1282, dtype=<class 'numpy.float32'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=True, has_embeddings=False, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d5a9d0>), new_metadata=None) E state.list_collections_with_limit_offset(limit=2, offset=1) E (v15,) = state.modify_coll(coll=v13, new_metadata={'0': '10', '40': '0', 'p1nviWeL7fO': 'qN', '7b': 'YS', 'VYWq4LEMWjCo': True}, new_name='OF5F0MzbQg\n') E (v16,) = state.get_or_create_coll(coll=Collection(name='VS0QGh', id=UUID('c6b85c1d-c3e9-4d37-b9ca-c4b4266193e9'), metadata={'h': 5.681951615025145e-227, 'A1': 61126, 'uhUhLEEMfeC_kN': 2147483647, 'weF': 'pSP', 'B3DSaP': False, '6H533K': 1.192092896e-07}, dimension=1915, dtype=<class 'numpy.float32'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=False, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d202d0>), new_metadata={'xVW09xUpDZA': 31734, E 'g': 1.1, E 'n1dUTalF-MY': -1000000.0, E 'y': 'G3EtXTZ', E 'ugXZ_hK': 5494}) E state.list_collections_with_limit_offset(limit=4, offset=5) E state.modify_coll(coll=v16, new_metadata={'giC': -6.103515625e-05, E '45227B': '65', E 'Uy6KZu6abCD9Z': -72, E 'r3': -41479, E 'pO4': -0.0, E 'Bpyj': -675165.8688164671, E '8-tD9nJd': 4.8728578364902235e-208, E '7DjCkbusc-K': 'vc94', E '3': 'd71IL'}, new_name='OF5F0MzbQg\n') E state.list_collections_with_limit_offset(limit=4, offset=4) E (v17,) = state.modify_coll(coll=v15, new_metadata={'L35J2S': 'K0l026'}, new_name='Ai1\n') E (v18,) = state.get_or_create_coll(coll=v13, new_metadata=None) E state.list_collections_with_limit_offset(limit=3, offset=1) E (v19,) = state.modify_coll(coll=v14, new_metadata=None, new_name='F0K570\n') E (v20,) = state.get_or_create_coll(coll=Collection(name='Ad5m003\n', id=UUID('5e23b560-7f62-4f14-bf80-93f5ff4e906a'), metadata={'3M': 'q_'}, dimension=57, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=True, has_embeddings=False, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d5aad0>), new_metadata={'_000': 852410}) E (v21,) = state.get_or_create_coll(coll=v14, new_metadata=None) E state.list_collections_with_limit_offset(limit=4, offset=1) E (v22,) = state.modify_coll(coll=v21, new_metadata=None, new_name=None) E (v23,) = state.modify_coll(coll=v22, new_metadata=None, new_name=None) E state.list_collections_with_limit_offset(limit=1, offset=1) E state.get_or_create_coll(coll=Collection(name='VS0QGh', id=UUID('ca92837d-3425-436c-bf11-dba969f0f8c7'), metadata=None, dimension=326, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=True, has_embeddings=False, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d6f4d0>), new_metadata=None) E state.teardown() ``` The problem starts in v13 where we create a new collection named `C1030` In v15 we modify the collection `C1030` and rename it to `OF5F0MzbQg\n` In v16 we create a new collection named `VS0QGh` We try to modify the collection `VS0QGh` and rename it to `OF5F0MzbQg\n` which is the same name as the collection `C1030` which is fails in the and we return empty from the rule. However we have already updated the model: ```python if new_metadata is not None: if len(new_metadata) == 0: with pytest.raises(Exception): c = self.api.get_or_create_collection( name=coll.name, metadata=new_metadata, embedding_function=coll.embedding_function, ) return multiple() coll.metadata = new_metadata self.set_model(coll.name, coll.metadata) # <--- here we update the metadata if new_name is not None: if new_name in self.model and new_name != coll.name: with pytest.raises(Exception): # <--- fail here to rename the collection to `OF5F0MzbQg\n` c.modify(metadata=new_metadata, name=new_name) return multiple() prev_metadata = self.model[coll.name] self.delete_from_model(coll.name) self.set_model(new_name, prev_metadata) coll.name = new_name ``` then in `E state.get_or_create_coll(coll=Collection(name='VS0QGh', id=UUID('ca92837d-3425-436c-bf11-dba969f0f8c7'), metadata=None, dimension=326, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=True, has_embeddings=False, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d6f4d0>), new_metadata=None)` We try to create or get collection `VS0QGh` which exists in API and in state. Metadata and new metadata are None so we fall into case 0. Existing collection with old metadata and but we take the metadata from model which has been updated after the failure above. So we have API version of the metadata and partly updated model metadata, which causes the failure.
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Needed to fix the failing property tests in chroma-core#1715 ## Description of changes *Summarize the changes made by this PR.* - Improvements & Bug fixes - Moved the model update after conditional checks for new_name and metadata. - New functionality - ... ## Test plan *How are these changes tested?* - [ ] Tests pass locally with `pytest` for python, `yarn test` for js ## Documentation Changes Failure logs + Error analysis: ``` > assert c.metadata == self.model[coll.name] E AssertionError: assert {'g': 1.1, 'n...': 31734, ...} == {'3': 'd71IL'...235e-208, ...} E E Left contains 5 more items: E {'g': 1.1, E 'n1dUTalF-MY': -1000000.0, E 'ugXZ_hK': 5494, E 'xVW09xUpDZA': 31734, E 'y': 'G3EtXTZ'} E Right contains 9 more items: E {'3': 'd71IL', E '45227B': '65', E '7DjCkbusc-K': 'vc94', E '8-tD9nJd': 4.8728578364902235e-208, E 'Bpyj': -675165.8688164671, E 'Uy6KZu6abCD9Z': -72, E 'giC': -6.103515625e-05, E 'pO4': -0.0, E 'r3': -41479} E E Full diff: E { E + 'g': 1.1, E + 'n1dUTalF-MY': -1000000.0, E + 'ugXZ_hK': 5494, E + 'xVW09xUpDZA': 31734, E + 'y': 'G3EtXTZ', E - '3': 'd71IL', E - '45227B': '65', E - '7DjCkbusc-K': 'vc94', E - '8-tD9nJd': 4.8728578364902235e-208, E - 'Bpyj': -675165.8688164671, E - 'Uy6KZu6abCD9Z': -72, E - 'giC': -6.103515625e-05, E - 'pO4': -0.0, E - 'r3': -41479, E } E Falsifying example: E state = CollectionStateMachine() E state.initialize() E state.list_collections_with_limit_offset(limit=5, offset=0) E state.list_collections_with_limit_offset(limit=4, offset=5) E (v1,) = state.get_or_create_coll(coll=Collection(name='E60V1ekr9eDcL\n', id=UUID('4435abf2-9fc6-4d5a-bb7b-33177a956d44'), metadata={'_m5jalwo': -228}, dimension=1356, dtype=<class 'numpy.float64'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=False, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181bb0590>), new_metadata={'k5o6Q': 'Op', E 'LP': -5.960464477539063e-08, E 'pzHdzczVCn': '81', E '7': False, E 'e4Lz': 999999.0, E '206': False}) E (v2,) = state.get_or_create_coll(coll=v1, new_metadata=None) E (v3,) = state.get_or_create_coll(coll=v1, new_metadata={'4OQN': -2097032423, E 'cW': -0.99999, E 'o6wq3': -147, E 'M8j3KBU': -2.2250738585072014e-308, E 'D8nZrA0': 252, E 'up4P_': 34761, E 'L_win': -6.103515625e-05, E '5kt': '_q', E 'UybO2dJF4': -0.3333333333333333, E 'NfQ83VsmI': 'Qpy', E 'fk': -1.192092896e-07, E 'J1ck': 'ozL'}) E (v4,) = state.get_or_create_coll(coll=Collection(name='nOeHg-OXVl', id=UUID('9c28b027-9f22-409c-b3fd-c5de03b60018'), metadata=None, dimension=1009, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=True, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181bdfe50>), new_metadata={'p4isW': 'k8l', E 'k2tFn3v1E': True, E 'R': 'ji-2d5lDGV', E 'K5vdi': False, E 'TZs': False, E 'OgJ_DZ2j': False, E 'ovZjD3': -64297, E '9p': True, E '32f3nw8h2d54LPCzsV': 1733994327, E '4P': 2.896381722565434e-121}) E state.list_collections_with_limit_offset(limit=2, offset=0) E state.list_collections_with_limit_offset(limit=3, offset=0) E state.list_collections_with_limit_offset(limit=5, offset=5) E (v5,) = state.modify_coll(coll=v4, new_metadata=None, new_name=None) E (v6,) = state.get_or_create_coll(coll=Collection(name='A1w5m1l5I\n', id=UUID('606d59a6-6f66-456d-81ca-a8ea029c318c'), metadata={'3': '6Y'}, dimension=1544, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=False, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d6d110>), new_metadata=None) E (v7,) = state.get_or_create_coll(coll=v4, new_metadata={'01316': -0.0, '14UwVu': 81, 'C9eMDDdnB0oy': False, 'n964': '0a'}) E state.modify_coll(coll=v7, new_metadata={}, new_name='B-5Z2m2j52121') E state.get_or_create_coll(coll=Collection(name='E31\n', id=UUID('e67426e8-8595-4916-92a6-b2777b52f157'), metadata={'0Kr5Wp': -769, '9xT': 143980.04500299558, '8': True}, dimension=1800, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=True, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d6d6d0>), new_metadata={}) E state.list_collections_with_limit_offset(limit=2, offset=1) E state.list_collections_with_limit_offset(limit=2, offset=0) E state.list_collections_with_limit_offset(limit=1, offset=0) E state.list_collections_with_limit_offset(limit=1, offset=1) E (v8,) = state.get_or_create_coll(coll=Collection(name='A00\n', id=UUID('01522a4f-3383-4a58-8b18-0418e38e3ec6'), metadata=None, dimension=1032, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=False, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d94bd0>), new_metadata=None) E (v9,) = state.get_or_create_coll(coll=v6, new_metadata=None) E state.list_collections_with_limit_offset(limit=3, offset=2) E (v10,) = state.modify_coll(coll=v3, new_metadata=None, new_name=None) E (v11,) = state.modify_coll(coll=v10, new_metadata=None, new_name=None) E state.modify_coll(coll=v9, new_metadata={}, new_name=None) E (v12,) = state.get_or_create_coll(coll=Collection(name='A10\n', id=UUID('01efb806-fffa-4ce6-b285-b9aae55f50af'), metadata={}, dimension=258, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=False, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd183bbe5d0>), new_metadata=None) E state.modify_coll(coll=v11, new_metadata={}, new_name='A01011110\n') E state.list_collections_with_limit_offset(limit=3, offset=1) ------ Problem start here ------ E (v13,) = state.get_or_create_coll(coll=Collection(name='C1030', id=UUID('7858d028-1295-4769-96c1-e58bf242b7bd'), metadata={}, dimension=2, dtype=<class 'numpy.float32'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=False, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181bbff10>), new_metadata=None) E (v14,) = state.get_or_create_coll(coll=Collection(name='A01200671\n', id=UUID('f77d01a4-e43f-4b17-9579-daadccad2f71'), metadata={'0': 'L', '01': -4}, dimension=1282, dtype=<class 'numpy.float32'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=True, has_embeddings=False, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d5a9d0>), new_metadata=None) E state.list_collections_with_limit_offset(limit=2, offset=1) E (v15,) = state.modify_coll(coll=v13, new_metadata={'0': '10', '40': '0', 'p1nviWeL7fO': 'qN', '7b': 'YS', 'VYWq4LEMWjCo': True}, new_name='OF5F0MzbQg\n') E (v16,) = state.get_or_create_coll(coll=Collection(name='VS0QGh', id=UUID('c6b85c1d-c3e9-4d37-b9ca-c4b4266193e9'), metadata={'h': 5.681951615025145e-227, 'A1': 61126, 'uhUhLEEMfeC_kN': 2147483647, 'weF': 'pSP', 'B3DSaP': False, '6H533K': 1.192092896e-07}, dimension=1915, dtype=<class 'numpy.float32'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=False, has_embeddings=True, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d202d0>), new_metadata={'xVW09xUpDZA': 31734, E 'g': 1.1, E 'n1dUTalF-MY': -1000000.0, E 'y': 'G3EtXTZ', E 'ugXZ_hK': 5494}) E state.list_collections_with_limit_offset(limit=4, offset=5) E state.modify_coll(coll=v16, new_metadata={'giC': -6.103515625e-05, E '45227B': '65', E 'Uy6KZu6abCD9Z': -72, E 'r3': -41479, E 'pO4': -0.0, E 'Bpyj': -675165.8688164671, E '8-tD9nJd': 4.8728578364902235e-208, E '7DjCkbusc-K': 'vc94', E '3': 'd71IL'}, new_name='OF5F0MzbQg\n') E state.list_collections_with_limit_offset(limit=4, offset=4) E (v17,) = state.modify_coll(coll=v15, new_metadata={'L35J2S': 'K0l026'}, new_name='Ai1\n') E (v18,) = state.get_or_create_coll(coll=v13, new_metadata=None) E state.list_collections_with_limit_offset(limit=3, offset=1) E (v19,) = state.modify_coll(coll=v14, new_metadata=None, new_name='F0K570\n') E (v20,) = state.get_or_create_coll(coll=Collection(name='Ad5m003\n', id=UUID('5e23b560-7f62-4f14-bf80-93f5ff4e906a'), metadata={'3M': 'q_'}, dimension=57, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=True, has_embeddings=False, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d5aad0>), new_metadata={'_000': 852410}) E (v21,) = state.get_or_create_coll(coll=v14, new_metadata=None) E state.list_collections_with_limit_offset(limit=4, offset=1) E (v22,) = state.modify_coll(coll=v21, new_metadata=None, new_name=None) E (v23,) = state.modify_coll(coll=v22, new_metadata=None, new_name=None) E state.list_collections_with_limit_offset(limit=1, offset=1) E state.get_or_create_coll(coll=Collection(name='VS0QGh', id=UUID('ca92837d-3425-436c-bf11-dba969f0f8c7'), metadata=None, dimension=326, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=True, has_embeddings=False, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d6f4d0>), new_metadata=None) E state.teardown() ``` The problem starts in v13 where we create a new collection named `C1030` In v15 we modify the collection `C1030` and rename it to `OF5F0MzbQg\n` In v16 we create a new collection named `VS0QGh` We try to modify the collection `VS0QGh` and rename it to `OF5F0MzbQg\n` which is the same name as the collection `C1030` which is fails in the and we return empty from the rule. However we have already updated the model: ```python if new_metadata is not None: if len(new_metadata) == 0: with pytest.raises(Exception): c = self.api.get_or_create_collection( name=coll.name, metadata=new_metadata, embedding_function=coll.embedding_function, ) return multiple() coll.metadata = new_metadata self.set_model(coll.name, coll.metadata) # <--- here we update the metadata if new_name is not None: if new_name in self.model and new_name != coll.name: with pytest.raises(Exception): # <--- fail here to rename the collection to `OF5F0MzbQg\n` c.modify(metadata=new_metadata, name=new_name) return multiple() prev_metadata = self.model[coll.name] self.delete_from_model(coll.name) self.set_model(new_name, prev_metadata) coll.name = new_name ``` then in `E state.get_or_create_coll(coll=Collection(name='VS0QGh', id=UUID('ca92837d-3425-436c-bf11-dba969f0f8c7'), metadata=None, dimension=326, dtype=<class 'numpy.float16'>, topic='topic', known_metadata_keys={}, known_document_keywords=[], has_documents=True, has_embeddings=False, embedding_function=<chromadb.test.property.strategies.hashing_embedding_function object at 0x7fd181d6f4d0>), new_metadata=None)` We try to create or get collection `VS0QGh` which exists in API and in state. Metadata and new metadata are None so we fall into case 0. Existing collection with old metadata and but we take the metadata from model which has been updated after the failure above. So we have API version of the metadata and partly updated model metadata, which causes the failure.
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## Description of changes Chroma did not support Python 3.12 because of our dependency on the ONNX runtime for our default embedding function. As of version 1.17.0, ONNX supports python 3.12: microsoft/onnxruntime#17842 (comment) This already automatically fixes the issue for Chroma users when they install the new version of ONNX / reinstall Chroma. This PR is just to update our test and release actions to also use python 3.12. ## Test plan These are changes to test workers. ## Documentation Changes N/A
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Description of changes
Chroma did not support Python 3.12 because of our dependency on the ONNX runtime for our default embedding function. As of version 1.17.0, ONNX supports python 3.12: microsoft/onnxruntime#17842 (comment)
This already automatically fixes the issue for Chroma users when they install the new version of ONNX / reinstall Chroma. This PR is just to update our test and release actions to also use python 3.12.
Test plan
These are changes to test workers.
Documentation Changes
N/A