API Reference

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Data Sinks

List Data Sinks

IReadOnlyList<DataSink> DataSinks.List(DataSinkListParams?parameters, CancellationTokencancellationToken = default)

GET/api/v1/data-sinks

Create Data Sink

DataSink DataSinks.Create(DataSinkCreateParamsparameters, CancellationTokencancellationToken = default)

POST/api/v1/data-sinks

Get Data Sink

DataSink DataSinks.Get(DataSinkGetParamsparameters, CancellationTokencancellationToken = default)

GET/api/v1/data-sinks/{data_sink_id}

Update Data Sink

DataSink DataSinks.Update(DataSinkUpdateParamsparameters, CancellationTokencancellationToken = default)

PUT/api/v1/data-sinks/{data_sink_id}

Delete Data Sink

DataSinks.Delete(DataSinkDeleteParamsparameters, CancellationTokencancellationToken = default)

DELETE/api/v1/data-sinks/{data_sink_id}

ModelsExpand Collapse

class DataSink:

Schema for a data sink.

required string ID

Unique identifier

formatuuid

required Component Component

Component that implements the data sink

One of the following:

IReadOnlyDictionary<string, JsonElement>

class CloudPineconeVectorStore:

Cloud Pinecone Vector Store.

This class is used to store the configuration for a Pinecone vector store, so that it can be created and used in LlamaCloud.

Args: api_key (str): API key for authenticating with Pinecone index_name (str): name of the Pinecone index namespace (optional[str]): namespace to use in the Pinecone index insert_kwargs (optional[dict]): additional kwargs to pass during insertion

required string ApiKey

The API key for authenticating with Pinecone

formatpassword

required string IndexName

string ClassName

IReadOnlyDictionary<string, JsonElement>? InsertKwargs

string? Namespace

SupportsNestedMetadataFilters SupportsNestedMetadataFilters

class CloudPostgresVectorStore:

required string Database

required Long EmbedDim

required string Host

required string Password

required Long Port

required string SchemaName

required string TableName

required string User

string ClassName

PgVectorHnswSettings? HnswSettings

HNSW settings for PGVector.

DistanceMethod DistanceMethod

The distance method to use.

One of the following:

"cosine"Cosine

"hamming"Hamming

"ip"IP

"jaccard"Jaccard

"l1"L1

"l2"L2

Long EfConstruction

The number of edges to use during the construction phase.

minimum1

Long EfSearch

The number of edges to use during the search phase.

minimum1

Long M

The number of bi-directional links created for each new element.

minimum1

VectorType VectorType

The type of vector to use.

One of the following:

"bit"Bit

"half_vec"HalfVec

"sparse_vec"SparseVec

"vector"Vector

Boolean? HybridSearch

Boolean PerformSetup

Boolean SupportsNestedMetadataFilters

class CloudQdrantVectorStore:

Cloud Qdrant Vector Store.

This class is used to store the configuration for a Qdrant vector store, so that it can be created and used in LlamaCloud.

Args: collection_name (str): name of the Qdrant collection url (str): url of the Qdrant instance api_key (str): API key for authenticating with Qdrant max_retries (int): maximum number of retries in case of a failure. Defaults to 3 client_kwargs (dict): additional kwargs to pass to the Qdrant client

required string ApiKey

required string CollectionName

required string Url

string ClassName

IReadOnlyDictionary<string, JsonElement> ClientKwargs

Long MaxRetries

SupportsNestedMetadataFilters SupportsNestedMetadataFilters

class CloudAzureAISearchVectorStore:

Cloud Azure AI Search Vector Store.

required string SearchServiceApiKey

required string SearchServiceEndpoint

string ClassName

string? ClientID

string? ClientSecret

Long? EmbeddingDimension

IReadOnlyDictionary<string, JsonElement>? FilterableMetadataFieldKeys

string? IndexName

string? SearchServiceApiVersion

SupportsNestedMetadataFilters SupportsNestedMetadataFilters

string? TenantID

class CloudMongoDBAtlasVectorSearch:

Cloud MongoDB Atlas Vector Store.

This class is used to store the configuration for a MongoDB Atlas vector store, so that it can be created and used in LlamaCloud.

Args: mongodb_uri (str): URI for connecting to MongoDB Atlas db_name (str): name of the MongoDB database collection_name (str): name of the MongoDB collection vector_index_name (str): name of the MongoDB Atlas vector index fulltext_index_name (str): name of the MongoDB Atlas full-text index

required string CollectionName

required string DBName

required string MongoDBUri

string ClassName

Long? EmbeddingDimension

string? FulltextIndexName

Boolean SupportsNestedMetadataFilters

string? VectorIndexName

class CloudMilvusVectorStore:

Cloud Milvus Vector Store.

required string Uri

string? Token

string ClassName

string? CollectionName

Long? EmbeddingDimension

Boolean SupportsNestedMetadataFilters

class CloudAstraDBVectorStore:

Cloud AstraDB Vector Store.

This class is used to store the configuration for an AstraDB vector store, so that it can be created and used in LlamaCloud.

Args: token (str): The Astra DB Application Token to use. api_endpoint (str): The Astra DB JSON API endpoint for your database. collection_name (str): Collection name to use. If not existing, it will be created. embedding_dimension (int): Length of the embedding vectors in use. keyspace (optional[str]): The keyspace to use. If not provided, ‘default_keyspace’

required string Token

The Astra DB Application Token to use

formatpassword

required string ApiEndpoint

The Astra DB JSON API endpoint for your database

required string CollectionName

Collection name to use. If not existing, it will be created

required Long EmbeddingDimension

Length of the embedding vectors in use

string ClassName

string? Keyspace

The keyspace to use. If not provided, ‘default_keyspace’

SupportsNestedMetadataFilters SupportsNestedMetadataFilters

required string Name

The name of the data sink.

required string ProjectID

required SinkType SinkType

One of the following:

"ASTRA_DB"AstraDB

"AZUREAI_SEARCH"AzureaiSearch

"MILVUS"Milvus

"MONGODB_ATLAS"MongoDBAtlas

"PINECONE"Pinecone

"POSTGRES"Postgres

"QDRANT"Qdrant

DateTimeOffset? CreatedAt

Creation datetime

formatdate-time

DateTimeOffset? UpdatedAt

Update datetime

formatdate-time