# Collection Reference turned into UUID, and couldn't be link **URL:** \ **Category:** Support\ **Created:** [September 22, 2024, 3:25am UTC](https://forum.weaviate.io/t/collection-reference-turned-into-uuid-and-couldnt-be-link/4247 "2024-09-22T03:25:54Z")\ **Posts on this page:** 2\ **Page:** 1
**Author:** ![EpiphanyFall](https://yyz1.discourse-cdn.com/flex027/user_avatar/forum.weaviate.io/epiphanyfall/32/2382_2.png) [@EpiphanyFall](https://forum.weaviate.io/u/EpiphanyFall)\ **Post date:** [September 22, 2024, 3:25am UTC](https://forum.weaviate.io/t/collection-reference-turned-into-uuid-and-couldnt-be-link/4247/1 "2024-09-22T03:25:55Z")
### Description I have a schema.json: ```json { "classes": [ { "class": "Pack", "properties": [ { "name": "pack_name", "dataType": [ "string" ] }, { "name": "version", "dataType": [ "string" ] }, { "name": "author", "dataType": [ "string" ] }, { "name": "website", "dataType": [ "string" ] }, { "name": "state", "dataType": [ "string" ] }, { "name": "date", "dataType": [ "date" ] } ] }, { "class": "TextFile", "properties": [ { "name": "path_in_pack", "dataType": [ "string" ] }, { "name": "simhash", "dataType": [ "vector" ] }, { "name": "sequences", "dataType": [ "string[]" ] }, { "name": "belongs_to_pack", "dataType": [ "Pack" ] }, { "name": "md5", "dataType": [ "string" ] } ], "vectorIndexConfig": { "distance": "hamming" } }, { "class": "ImageFile", "properties": [ { "name": "md5", "dataType": [ "string" ] }, { "name": "path_in_pack", "dataType": [ "string" ] }, { "name": "histogram", "dataType": [ "vector" ] }, { "name": "phash", "dataType": [ "vector" ] }, { "name": "lbp_features", "dataType": [ "vector" ] }, { "name": "belongs_to_pack", "dataType": [ "Pack" ] } ] }, { "class": "AudioFile", "properties": [ { "name": "path_in_pack", "dataType": [ "string" ] }, { "name": "belongs_to_pack", "dataType": [ "Pack" ] }, { "name": "md5", "dataType": [ "string" ] } ] } ] } ``` and I load the schema with ```python self.client = weaviate.Client(WEAVIATE_URL) try: self.load_schema('database/schema.gql') except Exception as e: print(e) ``` If GET the schemas ```python schema = self.client.schema.get() ``` ```json { "classes": [ { "class": "TextFile", "invertedIndexConfig": { "bm25": { "b": 0.75, "k1": 1.2 }, "cleanupIntervalSeconds": 60, "stopwords": { "additions": null, "preset": "en", "removals": null } }, "multiTenancyConfig": { "autoTenantActivation": false, "autoTenantCreation": false, "enabled": false }, "properties": [ { "dataType": [ "text" ], "indexFilterable": true, "indexSearchable": true, "name": "path_in_pack", "tokenization": "whitespace" }, { "dataType": [ "text[]" ], "indexFilterable": true, "indexSearchable": true, "name": "sequences", "tokenization": "whitespace" }, { "dataType": [ "text" ], "indexFilterable": true, "indexSearchable": true, "name": "md5", "tokenization": "whitespace" }, { "dataType": [ "uuid" ], "description": "This property was generated by Weaviate's auto-schema feature on Fri Sep 20 12:16:53 2024", "indexFilterable": true, "indexSearchable": false, "name": "belongs_to_pack" }, { "dataType": [ "text" ], "description": "This property was generated by Weaviate's auto-schema feature on Fri Sep 20 12:16:53 2024", "indexFilterable": true, "indexSearchable": true, "name": "file_path", "tokenization": "word" }, { "dataType": [ "number[]" ], "description": "This property was generated by Weaviate's auto-schema feature on Fri Sep 20 12:16:53 2024", "indexFilterable": true, "indexSearchable": false, "name": "simhash" } ], "replicationConfig": { "factor": 1 }, "shardingConfig": { "actualCount": 1, "actualVirtualCount": 128, "desiredCount": 1, "desiredVirtualCount": 128, "function": "murmur3", "key": "_id", "strategy": "hash", "virtualPerPhysical": 128 }, "vectorIndexConfig": { "bq": { "enabled": false }, "cleanupIntervalSeconds": 300, "distance": "hamming", "dynamicEfFactor": 8, "dynamicEfMax": 500, "dynamicEfMin": 100, "ef": -1, "efConstruction": 128, "flatSearchCutoff": 40000, "maxConnections": 64, "pq": { "bitCompression": false, "centroids": 256, "enabled": false, "encoder": { "distribution": "log-normal", "type": "kmeans" }, "segments": 0, "trainingLimit": 100000 }, "skip": false, "vectorCacheMaxObjects": 1000000000000 }, "vectorIndexType": "hnsw", "vectorizer": "none" }, { "class": "AudioFile", "invertedIndexConfig": { "bm25": { "b": 0.75, "k1": 1.2 }, "cleanupIntervalSeconds": 60, "stopwords": { "additions": null, "preset": "en", "removals": null } }, "multiTenancyConfig": { "autoTenantActivation": false, "autoTenantCreation": false, "enabled": false }, "properties": [ { "dataType": [ "text" ], "indexFilterable": true, "indexSearchable": true, "name": "path_in_pack", "tokenization": "whitespace" }, { "dataType": [ "text" ], "indexFilterable": true, "indexSearchable": true, "name": "md5", "tokenization": "whitespace" } ], "replicationConfig": { "factor": 1 }, "shardingConfig": { "actualCount": 1, "actualVirtualCount": 128, "desiredCount": 1, "desiredVirtualCount": 128, "function": "murmur3", "key": "_id", "strategy": "hash", "virtualPerPhysical": 128 }, "vectorIndexConfig": { "bq": { "enabled": false }, "cleanupIntervalSeconds": 300, "distance": "cosine", "dynamicEfFactor": 8, "dynamicEfMax": 500, "dynamicEfMin": 100, "ef": -1, "efConstruction": 128, "flatSearchCutoff": 40000, "maxConnections": 64, "pq": { "bitCompression": false, "centroids": 256, "enabled": false, "encoder": { "distribution": "log-normal", "type": "kmeans" }, "segments": 0, "trainingLimit": 100000 }, "skip": false, "vectorCacheMaxObjects": 1000000000000 }, "vectorIndexType": "hnsw", "vectorizer": "none" }, { "class": "ImageFile", "invertedIndexConfig": { "bm25": { "b": 0.75, "k1": 1.2 }, "cleanupIntervalSeconds": 60, "stopwords": { "additions": null, "preset": "en", "removals": null } }, "multiTenancyConfig": { "autoTenantActivation": false, "autoTenantCreation": false, "enabled": false }, "properties": [ { "dataType": [ "text" ], "indexFilterable": true, "indexSearchable": true, "name": "md5", "tokenization": "whitespace" }, { "dataType": [ "text" ], "indexFilterable": true, "indexSearchable": true, "name": "path_in_pack", "tokenization": "whitespace" }, { "dataType": [ "text" ], "description": "This property was generated by Weaviate's auto-schema feature on Fri Sep 20 12:16:53 2024", "indexFilterable": true, "indexSearchable": true, "name": "file_path", "tokenization": "word" }, { "dataType": [ "number[]" ], "description": "This property was generated by Weaviate's auto-schema feature on Fri Sep 20 12:16:53 2024", "indexFilterable": true, "indexSearchable": false, "name": "phash" }, { "dataType": [ "number[]" ], "description": "This property was generated by Weaviate's auto-schema feature on Fri Sep 20 12:16:53 2024", "indexFilterable": true, "indexSearchable": false, "name": "lbp_features" }, { "dataType": [ "uuid" ], "description": "This property was generated by Weaviate's auto-schema feature on Fri Sep 20 12:16:53 2024", "indexFilterabl53 2024", "indexFilterable": true, "indexSearchable": false, "name": "belongs_to_pack" } ], "replicationConfig": { "factor": 1 }, "shardingConfig": { "actualCount": 1, "actualVirtualCount": 128, "desiredCount": 1, "desiredVirtualCount": 128, "function": "murmur3", "key": "_id", "strategy": "hash", "virtualPerPhysical": 128 }, "vectorIndexConfig": { "bq": { "enabled": false }, "cleanupIntervalSeconds": 300, "distance": "cosine", "dynamicEfFactor": 8, "dynamicEfMax": 500, "dynamicEfMin": 100, "ef": -1, "efConstruction": 128, "flatSearchCutoff": 40000, "maxConnections": 64, "pq": { "bitCompression": false, "centroids": 256, "enabled": false, "encoder": { "distribution": "log-normal", "type": "kmeans" }, "segments": 0, "trainingLimit": 100000 }, "skip": false, "vectorCacheMaxObjects": 1000000000000 }, "vectorIndexType": "hnsw", "vectorizer": "none" }, { "class": "Pack", "invertedIndexConfig": { "bm25": { "b": 0.75, "k1": 1.2 }, "cleanupIntervalSeconds": 60, "stopwords": { "additions": null, "preset": "en", "removals": null } }, "multiTenancyConfig": { "autoTenantActivation": false, "autoTenantCreation": false, "enabled": false }, "properties": [ { "dataType": [ "text" ], "indexFilterable": true, "indexSearchable": true, "name": "pack_name", "tokenization": "whitespace" }, { "dataType": [ "text" ], "indexFilterable": true, "indexSearchable": true, "name": "version", "tokenization": "whitespace" }, { "dataType": [ "text" ], "indexFilterable": true, "indexSearchable": true, "name": "author", "tokenization": "whitespace" }, { "dataType": [ "text" ], "indexFilterable": true, "indexSearchable": true, "name": "website", "tokenization": "whitespace" }, { "dataType": [ "text" ], "indexFilterable": true, "indexSearchable": true, "name": "state", "tokenization": "whitespace" }, { "dataType": [ "date" ], "indexFilterable": true, "indexSearchable": false, "name": "date" } ], "replicationConfig": { "factor": 1 }, "shardingConfig": { "actualCount": 1, "actualVirtualCount": 128, "desiredCount": 1, "desiredVirtualCount": 128, "function": "murmur3", "key": "_id", "strategy": "hash", "virtualPerPhysical": 128 }, "vectorIndexConfig": { "bq": { "enabled": false }, "cleanupIntervalSeconds": 300, "distance": "cosine", "dynamicEfFactor": 8, "dynamicEfMax": 500, "dynamicEfMin": 100, "ef": -1, "efConstruction": 128, "flatSearchCutoff": 40000, "maxConnections": 64, "pq": { "bitCompression": false, "centroids": 256, "enabled": false, "encoder": { "distribution": "log-normal", "type": "kmeans" }, "segments": 0, "trainingLimit": 100000 }, "skip": false, "vectorCacheMaxObjects": 1000000000000 }, "vectorIndexType": "hnsw", "vectorizer": "none" } ] } ``` You can tall that the class references turned into UUID ```json { "dataType": [ "uuid" ], "description": "This property was generated by Weaviate's auto-schema feature on Fri Sep 20 12:16:53 2024", "indexFilterabl53 2024", "indexFilterable": true, "indexSearchable": false, "name": "belongs_to_pack" } ``` But when I query the references, wether use python sdk(v3) or use native gql: ```auto self.client.query.get("TextFile", ["path_in_pack", # LinkTo( # link_on="belongs_to_pack", # 要查询的字段 # linked_class="Pack", # 引用的类 # properties=["pack_name"] # 查询该引用类中的字段 # ) """ belongs_to_pack { name }""" ]).with_near_vector(query).do() ``` It errors: ```bash {'errors': [{'locations': [{'column': 17, 'line': 2}], 'message': 'Field "belongs_to_pack" of type "String" must not have a sub selection.', 'path': None}]} ``` How to solve this, pls. ### Server Setup Information - Weaviate Server Version: `{"action":"startup","build_git_commit":"447949c","build_go_version":"go1.22.7","build_image_tag":"1.25.17","build_wv_version":"1.25.17","default_vectorizer_module":"none","level":"info","msg":"the default vectorizer modules is set to \"none\", as a result all new schema classes without an explicit vectorizer setting, will use this vectorizer","time":"2024-09-17T17:20:52Z"}` - Deployment Method: **docker** - Number of Running Nodes: **1** - Client Language and Version: **python** weaviate==0.1.0 weaviate-client==4.8.1 - Multitenancy?: ### Any additional Information ---
**Author:** ![DudaNogueira](https://yyz1.discourse-cdn.com/flex027/user_avatar/forum.weaviate.io/dudanogueira/32/7846_2.png) [@DudaNogueira](https://forum.weaviate.io/u/DudaNogueira)\ **Post date:** [September 23, 2024, 8:34am UTC](https://forum.weaviate.io/t/collection-reference-turned-into-uuid-and-couldnt-be-link/4247/2 "2024-09-23T08:34:54Z")
Hi! I was not able to create the collections using this schema. I got this error, due to the data type “vector” that is not valid: ```auto { "name": "simhash", "dataType": [ "vector" ] }, ``` this was the error: > UnexpectedStatusCodeError: Collection may not have been created properly.! Unexpected status code: 422, with response body: {‘error’: [{‘message’: “property ‘simhash’: invalid dataType: unknown primitive data type ‘vector’”}]}. I was able to comment that property, and create the class, however it was working properly. I have used python v4 syntax (you are using python v3). Here is what I have done: ```python import weaviate client = weaviate.connect_to_local() print(weaviate. __version__ , client.get_meta().get("version")) schema = { "classes": [ { "class": "Pack", "properties": [ { "name": "pack_name", "dataType": [ "string" ] }, { "name": "version", "dataType": [ "string" ] }, { "name": "author", "dataType": [ "string" ] }, { "name": "website", "dataType": [ "string" ] }, { "name": "state", "dataType": [ "string" ] }, { "name": "date", "dataType": [ "date" ] } ] }, { "class": "TextFile", "properties": [ { "name": "path_in_pack", "dataType": [ "string" ] }, # { # "name": "simhash", # "dataType": [ # "vector" # ] # }, { "name": "sequences", "dataType": [ "string[]" ] }, { "name": "belongs_to_pack", "dataType": [ "Pack" ] }, { "name": "md5", "dataType": [ "string" ] } ], "vectorIndexConfig": { "distance": "hamming" } }, { "class": "ImageFile", "properties": [ { "name": "md5", "dataType": [ "string" ] }, { "name": "path_in_pack", "dataType": [ "string" ] }, { "name": "histogram", "dataType": [ "vector" ] }, { "name": "phash", "dataType": [ "vector" ] }, { "name": "lbp_features", "dataType": [ "vector" ] }, { "name": "belongs_to_pack", "dataType": [ "Pack" ] } ] }, { "class": "AudioFile", "properties": [ { "name": "path_in_pack", "dataType": [ "string" ] }, { "name": "belongs_to_pack", "dataType": [ "Pack" ] }, { "name": "md5", "dataType": [ "string" ] } ] } ] } c = client.collections.create_from_dict(schema["classes"][0]) c = client.collections.create_from_dict(schema["classes"][1]) ``` we have now created the first and second classes. And the property that is a cross reference is correctly created: ```python collection = client.collections.get("TextFile") for p in collection.config.get().references: print("----") print(p) ``` here is the output: `_ReferenceProperty(name='belongs_to_pack', description=None, target_collections=['Pack'])` Let me know if this hels! Thanks!