Dontopedia

VectorStorage

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)

VectorStorage has 70 facts recorded in Dontopedia across 15 references, with 12 live disagreements.

70 facts·29 predicates·15 sources·12 in dispute

Mostly:rdf:type(11), has attribute(10), has instance variable(5)

Maturity scale raw canonical shape-checked rule-derived certified

Rdf:typein disputerdf:type

Has Attributein disputehasAttribute

  • Queue Name[13]sourceall time · Ad9dc53d Fc07 4458 813b Af9cc4b42f09
  • Output Filepath[13]sourceall time · Ad9dc53d Fc07 4458 813b Af9cc4b42f09
  • Connection[13]sourceall time · Ad9dc53d Fc07 4458 813b Af9cc4b42f09
  • Channel[13]sourceall time · Ad9dc53d Fc07 4458 813b Af9cc4b42f09
  • Processed Vectors[13]sourceall time · Ad9dc53d Fc07 4458 813b Af9cc4b42f09
  • processed_queue_name[14]all time · 17dbe1f0 1751 4859 98fa C095b8ce3eb9
  • output_filepath[14]all time · 17dbe1f0 1751 4859 98fa C095b8ce3eb9
  • self.processed_queue_name[14]all time · 17dbe1f0 1751 4859 98fa C095b8ce3eb9
  • self.output_filepath[14]all time · 17dbe1f0 1751 4859 98fa C095b8ce3eb9
  • self.processed_vectors[14]all time · 17dbe1f0 1751 4859 98fa C095b8ce3eb9

Inbound mentions (35)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

usedForUsed for(5)

memberOfMember of(3)

belongsToBelongs to(2)

coordinatesWithCoordinates With(2)

subClassOfSub Class of(2)

appliesToApplies to(1)

causesRemovalFromCauses Removal From(1)

connectedToConnected to(1)

constrainsConstrains(1)

containsContains(1)

dataFlowData Flow(1)

designedForDesigned for(1)

ex:designedForEx:designed for(1)

ex:suitableForEx:suitable for(1)

ex:usedForEx:used for(1)

hasComponentHas Component(1)

intendedStorageIntended Storage(1)

is-used-forIs Used for(1)

orchestratesOrchestrates(1)

passesThroughPasses Through(1)

precedesPrecedes(1)

proposesMechanismProposes Mechanism(1)

providesProvides(1)

sourceForSource for(1)

storageLocationStorage Location(1)

usedByUsed by(1)

Other facts (42)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

42 facts
PredicateValueRef
Has Instance VariableQueue Name Instance[13]
Has Instance VariableOutput Filepath Instance[13]
Has Instance VariableConnection Instance[13]
Has Instance VariableChannel Instance[13]
Has Instance VariableProcessed Vectors Instance[13]
Has MethodCallback Method[13]
Has MethodStart Storing Method[13]
Has MethodStart Storing[14]
Has MethodSave Vectors[14]
Depends onPika Library[13]
Depends onJson Library[13]
Depends onNumpy Library[13]
InitializesProcessed Vectors List[13]
InitializesStorage Instance[14]
Initialized WithQueue Name[13]
Initialized WithOutput Filepath[13]
Uses ModuleNumpy[14]
Uses ModulePika[14]
Init Parameterself.processed_queue_name[14]
Init Parameterself.output_filepath[14]
Defines MethodStart Storing[14]
Defines MethodSave Vectors[14]
ImportsPika[14]
ImportsNumpy[14]
StoresJudgement[3]
Followed byVector Decryption[4]
Used byRag System[6]
Purpose ofImproved Implementation[11]
Record Count200000[12]
Requires100 Percent Encryption[12]
Scale200000[12]
Encryption Target200 K Records[12]
Defined inVector Storage Service[13]
Consumes FromQueue Name[13]
Publishes toProcessed Queue[13]
Has Init MethodInit[14]
Part ofProcessing Pipeline[14]
Creates ObjectPika Object[14]
ConsumesVector Queue Processed[14]
ProducesProcessed Vectors.npy[14]
Described AsStores processed vectors[14]
Receives FromVector Queue Processed[14]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

typebeam/adbf517e-1335-405d-8a65-aca63a92c7f3
ex:DataStructure
typebeam/65ffbfaa-762e-4210-bda5-5e222ad85a43
ex:Service
storesblah/models/15
ex:judgement
followedBybeam/cbcc52f9-bbf7-48d0-9673-c18b30cc4544
ex:vector-decryption
typebeam/5cbfc373-2797-488e-9dab-6ae88803e66c
ex:DataStorageOperation
labelbeam/5cbfc373-2797-488e-9dab-6ae88803e66c
Vector Storage
typebeam/92f9d4b6-659a-439c-ae2a-0330d3d8ab30
ex:StoragePurpose
usedBybeam/92f9d4b6-659a-439c-ae2a-0330d3d8ab30
ex:rag-system
typebeam/4e052521-c073-47ac-8fbe-f614c6acf9f2
ex:SoftwareComponent
typebeam/0e98f2e1-cdc0-4a33-868b-98a143f5105d
ex:DataStorageConcept
typebeam/8a3414c7-4f1f-4769-bd10-d0358b46e718
ex:StorageMechanism
labelbeam/8a3414c7-4f1f-4769-bd10-d0358b46e718
Vector Storage
typebeam/e84015fa-c493-4afc-989d-244a981b70fe
ex:Concept
labelbeam/e84015fa-c493-4afc-989d-244a981b70fe
Vector Storage
typebeam/306c29bb-24f7-454f-9101-afe06f337d8e
ex:Function
labelbeam/306c29bb-24f7-454f-9101-afe06f337d8e
Vector Storage
purposeOfbeam/306c29bb-24f7-454f-9101-afe06f337d8e
ex:improved-implementation
recordCountbeam/b36ea991-056a-4a10-9e2f-c64a84237aa8
200000
requiresbeam/b36ea991-056a-4a10-9e2f-c64a84237aa8
ex:100-percent-encryption
scalebeam/b36ea991-056a-4a10-9e2f-c64a84237aa8
200000
encryptionTargetbeam/b36ea991-056a-4a10-9e2f-c64a84237aa8
ex:200K-records
typebeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:Class
labelbeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
VectorStorage
definedInbeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:vector-storage-service
hasInstanceVariablebeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:queue-name-instance
hasInstanceVariablebeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:output-filepath-instance
hasInstanceVariablebeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:connection-instance
hasInstanceVariablebeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:channel-instance
hasInstanceVariablebeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:processed-vectors-instance
hasMethodbeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:callback-method
hasMethodbeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:start-storing-method
initializesbeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:processed-vectors-list
consumesFrombeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:queue-name
publishesTobeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:processed-queue
hasAttributebeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:queue-name
hasAttributebeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:output-filepath
hasAttributebeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:connection
hasAttributebeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:channel
hasAttributebeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:processed-vectors
dependsOnbeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:pika-library
dependsOnbeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:json-library
dependsOnbeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:numpy-library
initializedWithbeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:queue-name
initializedWithbeam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
ex:output-filepath
typebeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:Service
labelbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
Vector Storage Service
hasAttributebeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
processed_queue_name
hasAttributebeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
output_filepath
hasMethodbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:start-storing
hasMethodbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:save-vectors
usesModulebeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:numpy
usesModulebeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:pika
initializesbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:storage-instance
hasInitMethodbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:__init__
initParameterbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
self.processed_queue_name
initParameterbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
self.output_filepath
definesMethodbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:start_storing
definesMethodbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:save_vectors
partOfbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:processing-pipeline
hasAttributebeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
self.processed_queue_name
hasAttributebeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
self.output_filepath
hasAttributebeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
self.processed_vectors
createsObjectbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:pika-object
importsbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:pika
importsbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:numpy
consumesbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:vector_queue_processed
producesbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:processed_vectors.npy
describedAsbeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
Stores processed vectors
receivesFrombeam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
ex:vector_queue_processed
labelbeam/3ec8c303-e081-4923-9f67-5956a4f6bef5
Vector Storage

References (15)

15 references
  1. ctx:claims/beam/adbf517e-1335-405d-8a65-aca63a92c7f3
    • full textbeam-chunk
      text/plain1 KBdoc:beam/adbf517e-1335-405d-8a65-aca63a92c7f3
      Show excerpt
      # Perform search results = search(COLLECTION_NAME, query_vector, TOP_K) print(results) ``` ### Explanation 1. **Collection Creation**: - `create_collection`: Creates a collection with specified parameters, including dimensi
  2. ctx:claims/beam/65ffbfaa-762e-4210-bda5-5e222ad85a43
  3. [3]151 fact
    ctx:discord/blah/models/15
  4. ctx:claims/beam/cbcc52f9-bbf7-48d0-9673-c18b30cc4544
    • full textbeam-chunk
      text/plain1 KBdoc:beam/cbcc52f9-bbf7-48d0-9673-c18b30cc4544
      Show excerpt
      - `decrypt_vector`: Decrypts the vector, decodes it from base64, and deserializes it back to a list. 2. **Weaviate Client**: - Initialize the Weaviate client without specifying encryption directly. - Encrypt the vectors before sto
  5. ctx:claims/beam/5cbfc373-2797-488e-9dab-6ae88803e66c
    • full textbeam-chunk
      text/plain1 KBdoc:beam/5cbfc373-2797-488e-9dab-6ae88803e66c
      Show excerpt
      decrypted_vector = decrypt_vector(result["vector"]) print(f"Name: {result['name']}, Vector: {decrypted_vector}") ``` ### Explanation 1. **Encryption Functions**: - `encrypt_vector`: Serializes the vector to bytes, encodes it in
  6. ctx:claims/beam/92f9d4b6-659a-439c-ae2a-0330d3d8ab30
    • full textbeam-chunk
      text/plain1 KBdoc:beam/92f9d4b6-659a-439c-ae2a-0330d3d8ab30
      Show excerpt
      'vector': [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6], [0.7, 0.8, 0.9]] } # Create a DataFrame to store the data df = pd.DataFrame(data) # Connect to MongoDB client = MongoClient('mongodb://localhost:27017/') db = client['rag_db'] collection =
  7. ctx:claims/beam/4e052521-c073-47ac-8fbe-f614c6acf9f2
  8. ctx:claims/beam/0e98f2e1-cdc0-4a33-868b-98a143f5105d
    • full textbeam-chunk
      text/plain1 KBdoc:beam/0e98f2e1-cdc0-4a33-868b-98a143f5105d
      Show excerpt
      - A NumPy array `vectors` is created with the specified initial capacity and vector size. 2. **Adding Vectors**: - The `add_vector` method checks if the current number of vectors has reached the capacity. If so, it resizes the array
  9. ctx:claims/beam/8a3414c7-4f1f-4769-bd10-d0358b46e718
    • full textbeam-chunk
      text/plain1 KBdoc:beam/8a3414c7-4f1f-4769-bd10-d0358b46e718
      Show excerpt
      [7. 8. 9. 0. 0. 0. 0. 0. 0. 0.]] ``` ### Additional Considerations - **Handling Incomplete Data Points**: If your data points are not always of the same length, you can pad them with zeros or another default value to ensure they match th
  10. ctx:claims/beam/e84015fa-c493-4afc-989d-244a981b70fe
    • full textbeam-chunk
      text/plain1 KBdoc:beam/e84015fa-c493-4afc-989d-244a981b70fe
      Show excerpt
      - The `add_vector` method checks if the current number of vectors has reached the capacity. If so, it resizes the array to accommodate more vectors. - The new vector is added to the array, and the count of vectors is incremented. 3.
  11. ctx:claims/beam/306c29bb-24f7-454f-9101-afe06f337d8e
  12. ctx:claims/beam/b36ea991-056a-4a10-9e2f-c64a84237aa8
    • full textbeam-chunk
      text/plain1 KBdoc:beam/b36ea991-056a-4a10-9e2f-c64a84237aa8
      Show excerpt
      - **Monitoring and Logging**: Tracks system health and performance. - **Backup and Recovery**: Ensures data integrity and availability. By following this architecture, you should be able to achieve the desired performance and uptime for yo
  13. ctx:claims/beam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
    • full textbeam-chunk
      text/plain1 KBdoc:beam/ad9dc53d-fc07-4458-813b-af9cc4b42f09
      Show excerpt
      ch.basic_publish(exchange='', routing_key=self.queue_name + '_processed', body=json.dumps(reduced_vector.tolist())) ch.basic_ack(delivery_tag=method.delivery_tag) def start_processing(self): self.channel.basic_c
  14. ctx:claims/beam/17dbe1f0-1751-4859-98fa-c095b8ce3eb9
  15. ctx:claims/beam/3ec8c303-e081-4923-9f67-5956a4f6bef5

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