quantcdn.AIVectorDatabaseApi

All URIs are relative to https://dashboard.quantcdn.io

Method	HTTP request	Description
create_vector_collection	POST /api/v3/organizations/{organisation}/ai/vector-db/collections	Create Vector Database Collection
delete_vector_collection	DELETE /api/v3/organizations/{organisation}/ai/vector-db/collections/{collectionId}	Delete Collection
get_vector_collection	GET /api/v3/organizations/{organisation}/ai/vector-db/collections/{collectionId}	Get Collection Details
list_vector_collections	GET /api/v3/organizations/{organisation}/ai/vector-db/collections	List Vector Database Collections
query_vector_collection	POST /api/v3/organizations/{organisation}/ai/vector-db/collections/{collectionId}/query	Semantic Search Query
upload_vector_documents	POST /api/v3/organizations/{organisation}/ai/vector-db/collections/{collectionId}/documents	Upload Documents to Collection

create_vector_collection

CreateVectorCollection201Response create_vector_collection(organisation, create_vector_collection_request)

Create Vector Database Collection

Creates a new vector database collection (knowledge base category) for semantic search. Collections store documents with embeddings for RAG (Retrieval Augmented Generation). * * Use Cases: * - Product documentation ('docs') * - Company policies ('policies') * - Support knowledge base ('support') * - Technical specifications ('specs')

Example

Bearer (JWT) Authentication (BearerAuth):

import quantcdn
from quantcdn.models.create_vector_collection201_response import CreateVectorCollection201Response
from quantcdn.models.create_vector_collection_request import CreateVectorCollectionRequest
from quantcdn.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to https://dashboard.quantcdn.io
# See configuration.py for a list of all supported configuration parameters.
configuration = quantcdn.Configuration(
    host = "https://dashboard.quantcdn.io"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure Bearer authorization (JWT): BearerAuth
configuration = quantcdn.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# Enter a context with an instance of the API client
with quantcdn.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = quantcdn.AIVectorDatabaseApi(api_client)
    organisation = 'organisation_example' # str | The organisation ID
    create_vector_collection_request = quantcdn.CreateVectorCollectionRequest() # CreateVectorCollectionRequest | 

    try:
        # Create Vector Database Collection
        api_response = api_instance.create_vector_collection(organisation, create_vector_collection_request)
        print("The response of AIVectorDatabaseApi->create_vector_collection:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling AIVectorDatabaseApi->create_vector_collection: %s\n" % e)

Parameters

Name	Type	Description	Notes
organisation	str	The organisation ID
create_vector_collection_request	CreateVectorCollectionRequest

Return type

CreateVectorCollection201Response

Authorization

BearerAuth

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
201	Collection created successfully	-
400	Invalid request parameters	-
403	Access denied	-
409	Collection with this name already exists	-
500	Failed to create collection	-

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delete_vector_collection

DeleteVectorCollection200Response delete_vector_collection(organisation, collection_id)

Delete Collection

Deletes a vector database collection and all its documents. This action cannot be undone.

Example

Bearer (JWT) Authentication (BearerAuth):

import quantcdn
from quantcdn.models.delete_vector_collection200_response import DeleteVectorCollection200Response
from quantcdn.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to https://dashboard.quantcdn.io
# See configuration.py for a list of all supported configuration parameters.
configuration = quantcdn.Configuration(
    host = "https://dashboard.quantcdn.io"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure Bearer authorization (JWT): BearerAuth
configuration = quantcdn.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# Enter a context with an instance of the API client
with quantcdn.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = quantcdn.AIVectorDatabaseApi(api_client)
    organisation = 'organisation_example' # str | The organisation ID
    collection_id = 'collection_id_example' # str | The collection ID

    try:
        # Delete Collection
        api_response = api_instance.delete_vector_collection(organisation, collection_id)
        print("The response of AIVectorDatabaseApi->delete_vector_collection:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling AIVectorDatabaseApi->delete_vector_collection: %s\n" % e)

Parameters

Name	Type	Description	Notes
organisation	str	The organisation ID
collection_id	str	The collection ID

Return type

DeleteVectorCollection200Response

Authorization

BearerAuth

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Collection deleted successfully	-
403	Access denied	-
404	Collection not found	-
500	Failed to delete collection	-

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get_vector_collection

GetVectorCollection200Response get_vector_collection(organisation, collection_id)

Get Collection Details

Get detailed information about a specific vector database collection.

Example

Bearer (JWT) Authentication (BearerAuth):

import quantcdn
from quantcdn.models.get_vector_collection200_response import GetVectorCollection200Response
from quantcdn.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to https://dashboard.quantcdn.io
# See configuration.py for a list of all supported configuration parameters.
configuration = quantcdn.Configuration(
    host = "https://dashboard.quantcdn.io"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure Bearer authorization (JWT): BearerAuth
configuration = quantcdn.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# Enter a context with an instance of the API client
with quantcdn.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = quantcdn.AIVectorDatabaseApi(api_client)
    organisation = 'organisation_example' # str | The organisation ID
    collection_id = 'collection_id_example' # str | The collection ID

    try:
        # Get Collection Details
        api_response = api_instance.get_vector_collection(organisation, collection_id)
        print("The response of AIVectorDatabaseApi->get_vector_collection:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling AIVectorDatabaseApi->get_vector_collection: %s\n" % e)

Parameters

Name	Type	Description	Notes
organisation	str	The organisation ID
collection_id	str	The collection ID

Return type

GetVectorCollection200Response

Authorization

BearerAuth

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Collection details retrieved successfully	-
403	Access denied	-
404	Collection not found	-
500	Failed to retrieve collection	-

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list_vector_collections

ListVectorCollections200Response list_vector_collections(organisation)

List Vector Database Collections

Lists all vector database collections (knowledge bases) for an organization.

Example

Bearer (JWT) Authentication (BearerAuth):

import quantcdn
from quantcdn.models.list_vector_collections200_response import ListVectorCollections200Response
from quantcdn.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to https://dashboard.quantcdn.io
# See configuration.py for a list of all supported configuration parameters.
configuration = quantcdn.Configuration(
    host = "https://dashboard.quantcdn.io"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure Bearer authorization (JWT): BearerAuth
configuration = quantcdn.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# Enter a context with an instance of the API client
with quantcdn.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = quantcdn.AIVectorDatabaseApi(api_client)
    organisation = 'organisation_example' # str | The organisation ID

    try:
        # List Vector Database Collections
        api_response = api_instance.list_vector_collections(organisation)
        print("The response of AIVectorDatabaseApi->list_vector_collections:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling AIVectorDatabaseApi->list_vector_collections: %s\n" % e)

Parameters

Name	Type	Description	Notes
organisation	str	The organisation ID

Return type

ListVectorCollections200Response

Authorization

BearerAuth

HTTP request headers

Content-Type: Not defined
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Collections retrieved successfully	-
403	Access denied	-
500	Failed to retrieve collections	-

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query_vector_collection

QueryVectorCollection200Response query_vector_collection(organisation, collection_id, query_vector_collection_request)

Semantic Search Query

Performs semantic search on a collection using vector similarity. Returns the most relevant documents based on meaning, not keyword matching. * * Three Search Modes: * * 1. Text Query - Provide query string, server generates embedding * - Query text is embedded using the collection's embedding model * - Embeddings are cached for repeated queries * * 2. Vector Query - Provide pre-computed vector array * - Skip embedding generation (faster) * - Useful when you've already embedded the query elsewhere * - Vector dimension must match collection (e.g., 1024 for Titan v2) * * 3. Metadata List - Set listByMetadata: true with filter * - Skip semantic search entirely * - Return all documents matching the filter * - Supports cursor-based pagination for large datasets * - Results ordered by sortBy/sortOrder (default: created_at DESC) * * Filtering: * - filter.exact: Exact match on metadata fields (AND logic) * - filter.contains: Array contains filter for tags (ANY match) * - Filters can be combined with semantic search or used alone with listByMetadata * * Pagination (listByMetadata mode only): * - Use cursor from previous response's nextCursor to get next page * - Uses keyset pagination for efficient traversal of large datasets * - Control sort with sortBy and sortOrder * * Use Cases: * - Find relevant documentation for user questions * - Power RAG (Retrieval Augmented Generation) in AI assistants * - Semantic search across knowledge bases * - List all artifacts by building/worker/tag

Example

Bearer (JWT) Authentication (BearerAuth):

import quantcdn
from quantcdn.models.query_vector_collection200_response import QueryVectorCollection200Response
from quantcdn.models.query_vector_collection_request import QueryVectorCollectionRequest
from quantcdn.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to https://dashboard.quantcdn.io
# See configuration.py for a list of all supported configuration parameters.
configuration = quantcdn.Configuration(
    host = "https://dashboard.quantcdn.io"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure Bearer authorization (JWT): BearerAuth
configuration = quantcdn.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# Enter a context with an instance of the API client
with quantcdn.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = quantcdn.AIVectorDatabaseApi(api_client)
    organisation = 'organisation_example' # str | The organisation ID
    collection_id = 'collection_id_example' # str | The collection ID
    query_vector_collection_request = quantcdn.QueryVectorCollectionRequest() # QueryVectorCollectionRequest | 

    try:
        # Semantic Search Query
        api_response = api_instance.query_vector_collection(organisation, collection_id, query_vector_collection_request)
        print("The response of AIVectorDatabaseApi->query_vector_collection:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling AIVectorDatabaseApi->query_vector_collection: %s\n" % e)

Parameters

Name	Type	Description
organisation	str	The organisation ID
collection_id	str	The collection ID
query_vector_collection_request	QueryVectorCollectionRequest

Return type

QueryVectorCollection200Response

Authorization

BearerAuth

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Search completed successfully	-
400	Invalid request parameters	-
403	Access denied	-
404	Collection not found	-
500	Failed to perform search	-

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upload_vector_documents

UploadVectorDocuments200Response upload_vector_documents(organisation, collection_id, upload_vector_documents_request)

Upload Documents to Collection

Uploads documents to a vector database collection with automatic embedding generation. Documents are chunked (if needed), embedded using the collection's embedding model, and stored. * * Supported Content: * - Plain text content * - URLs to fetch content from * - Markdown documents * * Metadata: * Each document can include metadata (title, source_url, section, tags) that is returned with search results.

Example

Bearer (JWT) Authentication (BearerAuth):

import quantcdn
from quantcdn.models.upload_vector_documents200_response import UploadVectorDocuments200Response
from quantcdn.models.upload_vector_documents_request import UploadVectorDocumentsRequest
from quantcdn.rest import ApiException
from pprint import pprint

# Defining the host is optional and defaults to https://dashboard.quantcdn.io
# See configuration.py for a list of all supported configuration parameters.
configuration = quantcdn.Configuration(
    host = "https://dashboard.quantcdn.io"
)

# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.

# Configure Bearer authorization (JWT): BearerAuth
configuration = quantcdn.Configuration(
    access_token = os.environ["BEARER_TOKEN"]
)

# Enter a context with an instance of the API client
with quantcdn.ApiClient(configuration) as api_client:
    # Create an instance of the API class
    api_instance = quantcdn.AIVectorDatabaseApi(api_client)
    organisation = 'organisation_example' # str | The organisation ID
    collection_id = 'collection_id_example' # str | The collection ID
    upload_vector_documents_request = quantcdn.UploadVectorDocumentsRequest() # UploadVectorDocumentsRequest | 

    try:
        # Upload Documents to Collection
        api_response = api_instance.upload_vector_documents(organisation, collection_id, upload_vector_documents_request)
        print("The response of AIVectorDatabaseApi->upload_vector_documents:\n")
        pprint(api_response)
    except Exception as e:
        print("Exception when calling AIVectorDatabaseApi->upload_vector_documents: %s\n" % e)

Parameters

Name	Type	Description
organisation	str	The organisation ID
collection_id	str	The collection ID
upload_vector_documents_request	UploadVectorDocumentsRequest

Return type

UploadVectorDocuments200Response

Authorization

BearerAuth

HTTP request headers

Content-Type: application/json
Accept: application/json

HTTP response details

Status code	Description	Response headers
200	Documents uploaded successfully	-
400	Invalid request parameters	-
403	Access denied	-
404	Collection not found	-
500	Failed to upload documents	-

[Back to top] [Back to API list] [Back to Model list] [Back to README]

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quantcdn.AIVectorDatabaseApi

create_vector_collection

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

delete_vector_collection

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

get_vector_collection

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

list_vector_collections

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

query_vector_collection

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details

upload_vector_documents

Example

Parameters

Return type

Authorization

HTTP request headers

HTTP response details