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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'
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'
class CloudAzStorageBlobDataSource: …
account_url: str
The Azure Storage Blob account URL to use for authentication.
container_name: str
The name of the Azure Storage Blob container to read from.
account_key: Optional[str]
The Azure Storage Blob account key to use for authentication.
account_name: Optional[str]
The Azure Storage Blob account name to use for authentication.
blob: Optional[str]
The blob name to read from.
client_id: Optional[str]
The Azure AD client ID to use for authentication.
client_secret: Optional[str]
The Azure AD client secret to use for authentication.
prefix: Optional[str]
The prefix of the Azure Storage Blob objects to read from.
tenant_id: Optional[str]
The Azure AD tenant ID to use for authentication.
class CloudAzureAISearchVectorStore: …
Cloud Azure AI Search Vector Store.
class CloudBoxDataSource: …
authentication_mechanism: Literal["developer_token", "ccg"]
The type of authentication to use (Developer Token or CCG)
client_id: Optional[str]
Box API key used for identifying the application the user is authenticating with
client_secret: Optional[str]
Box API secret used for making auth requests.
developer_token: Optional[str]
Developer token for authentication if authentication_mechanism is 'developer_token'.
enterprise_id: Optional[str]
Box Enterprise ID, if provided authenticates as service.
folder_id: Optional[str]
The ID of the Box folder to read from.
user_id: Optional[str]
Box User ID, if provided authenticates as user.
class CloudConfluenceDataSource: …
authentication_mechanism: str
Type of Authentication for connecting to Confluence APIs.
server_url: str
The server URL of the Confluence instance.
api_token: Optional[str]
The API token to use for authentication.
cql: Optional[str]
The CQL query to use for fetching pages.
failure_handling: Optional[FailureHandlingConfig]
Configuration for handling failures during processing. Key-value object controlling failure handling behaviors.
Example: { "skip_list_failures": true }
Currently supports:
- skip_list_failures: Skip failed batches/lists and continue processing
skip_list_failures: Optional[bool]
Whether to skip failed batches/lists and continue processing
index_restricted_pages: Optional[bool]
Whether to index restricted pages.
keep_markdown_format: Optional[bool]
Whether to keep the markdown format.
label: Optional[str]
The label to use for fetching pages.
page_ids: Optional[str]
The page IDs of the Confluence to read from.
space_key: Optional[str]
The space key to read from.
user_name: Optional[str]
The username to use for authentication.
class CloudGoogleDriveDataSource: …
folder_id: str
The ID of the Google Drive folder to read from.
service_account_key: Optional[Dict[str, str]]
A dictionary containing secret values
class CloudJiraDataSource: …
Cloud Jira Data Source integrating JiraReader.
authentication_mechanism: str
Type of Authentication for connecting to Jira APIs.
query: str
JQL (Jira Query Language) query to search.
api_token: Optional[str]
The API/ Access Token used for Basic, PAT and OAuth2 authentication.
cloud_id: Optional[str]
The cloud ID, used in case of OAuth2.
email: Optional[str]
The email address to use for authentication.
server_url: Optional[str]
The server url for Jira Cloud.
class CloudJiraDataSourceV2: …
Cloud Jira Data Source integrating JiraReaderV2.
authentication_mechanism: str
Type of Authentication for connecting to Jira APIs.
query: str
JQL (Jira Query Language) query to search.
server_url: str
The server url for Jira Cloud.
api_token: Optional[str]
The API Access Token used for Basic, PAT and OAuth2 authentication.
api_version: Optional[Literal["2", "3"]]
Jira REST API version to use (2 or 3). 3 supports Atlassian Document Format (ADF).
cloud_id: Optional[str]
The cloud ID, used in case of OAuth2.
email: Optional[str]
The email address to use for authentication.
expand: Optional[str]
Fields to expand in the response.
fields: Optional[List[str]]
List of fields to retrieve from Jira. If None, retrieves all fields.
get_permissions: Optional[bool]
Whether to fetch project role permissions and issue-level security
requests_per_minute: Optional[int]
Rate limit for Jira API requests per minute.
class CloudMilvusVectorStore: …
Cloud Milvus Vector Store.
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
class CloudNotionPageDataSource: …
integration_token: str
The integration token to use for authentication.
database_ids: Optional[str]
The Notion Database Id to read content from.
page_ids: Optional[str]
The Page ID's of the Notion to read from.
class CloudOneDriveDataSource: …
client_id: str
The client ID to use for authentication.
client_secret: str
The client secret to use for authentication.
tenant_id: str
The tenant ID to use for authentication.
user_principal_name: str
The user principal name to use for authentication.
folder_id: Optional[str]
The ID of the OneDrive folder to read from.
folder_path: Optional[str]
The path of the OneDrive folder to read from.
required_exts: Optional[List[str]]
The list of required file extensions.
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
api_key: str
The API key for authenticating with Pinecone
class CloudPostgresVectorStore: …
hnsw_settings: Optional[PgVectorHnswSettings]
HNSW settings for PGVector.
distance_method: Optional[Literal["l2", "ip", "cosine", 3 more]]
The distance method to use.
ef_construction: Optional[int]
The number of edges to use during the construction phase.
ef_search: Optional[int]
The number of edges to use during the search phase.
m: Optional[int]
The number of bi-directional links created for each new element.
vector_type: Optional[Literal["vector", "half_vec", "bit", "sparse_vec"]]
The type of vector to use.
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
class CloudS3DataSource: …
bucket: str
The name of the S3 bucket to read from.
aws_access_id: Optional[str]
The AWS access ID to use for authentication.
aws_access_secret: Optional[str]
The AWS access secret to use for authentication.
prefix: Optional[str]
The prefix of the S3 objects to read from.
regex_pattern: Optional[str]
The regex pattern to filter S3 objects. Must be a valid regex pattern.
s3_endpoint_url: Optional[str]
The S3 endpoint URL to use for authentication.
class CloudSharepointDataSource: …
client_id: str
The client ID to use for authentication.
client_secret: str
The client secret to use for authentication.
tenant_id: str
The tenant ID to use for authentication.
drive_name: Optional[str]
The name of the Sharepoint drive to read from.
exclude_path_patterns: Optional[List[str]]
List of regex patterns for file paths to exclude. Files whose paths (including filename) match any pattern will be excluded. Example: ['/temp/', '/backup/', '.git/', '.tmp$', '^~']
folder_id: Optional[str]
The ID of the Sharepoint folder to read from.
folder_path: Optional[str]
The path of the Sharepoint folder to read from.
get_permissions: Optional[bool]
Whether to get permissions for the sharepoint site.
include_path_patterns: Optional[List[str]]
List of regex patterns for file paths to include. Full paths (including filename) must match at least one pattern to be included. Example: ['/reports/', '/docs/..pdf$', '^Report..pdf$']
required_exts: Optional[List[str]]
The list of required file extensions.
site_id: Optional[str]
The ID of the SharePoint site to download from.
site_name: Optional[str]
The name of the SharePoint site to download from.
class CloudSlackDataSource: …
slack_token: str
Slack Bot Token.
channel_ids: Optional[str]
Slack Channel.
channel_patterns: Optional[str]
Slack Channel name pattern.
earliest_date: Optional[str]
Earliest date.
earliest_date_timestamp: Optional[float]
Earliest date timestamp.
latest_date: Optional[str]
Latest date.
latest_date_timestamp: Optional[float]
Latest date timestamp.
class FailureHandlingConfig: …
Configuration for handling different types of failures during data source processing.
skip_list_failures: Optional[bool]
Whether to skip failed batches/lists and continue processing
class PgVectorHnswSettings: …
HNSW settings for PGVector.
distance_method: Optional[Literal["l2", "ip", "cosine", 3 more]]
The distance method to use.
ef_construction: Optional[int]
The number of edges to use during the construction phase.
ef_search: Optional[int]
The number of edges to use during the search phase.
m: Optional[int]
The number of bi-directional links created for each new element.
vector_type: Optional[Literal["vector", "half_vec", "bit", "sparse_vec"]]
The type of vector to use.