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Delete Agent Data By Query

beta.agent_data.delete_by_query(AgentDataDeleteByQueryParams**kwargs) -> AgentDataDeleteByQueryResponse
POST/api/v1/beta/agent-data/:delete

Bulk delete agent data by query (deployment_name, collection, optional filters).

ParametersExpand Collapse
deployment_name: str

The agent deployment’s name to delete data for

organization_id: Optional[str]
project_id: Optional[str]
collection: Optional[str]

The logical agent data collection to delete from

filter: Optional[Dict[str, Filter]]

Optional filters to select which items to delete

eq: Optional[Union[float, str, Union[str, datetime], null]]
One of the following:
float
str
Union[str, datetime]
excludes: Optional[SequenceNotStr[Union[float, str, Union[str, datetime], null]]]
One of the following:
float
str
Union[str, datetime]
gt: Optional[Union[float, str, Union[str, datetime], null]]
One of the following:
float
str
Union[str, datetime]
gte: Optional[Union[float, str, Union[str, datetime], null]]
One of the following:
float
str
Union[str, datetime]
includes: Optional[SequenceNotStr[Union[float, str, Union[str, datetime], null]]]
One of the following:
float
str
Union[str, datetime]
lt: Optional[Union[float, str, Union[str, datetime], null]]
One of the following:
float
str
Union[str, datetime]
lte: Optional[Union[float, str, Union[str, datetime], null]]
One of the following:
float
str
Union[str, datetime]
ne: Optional[Union[float, str, Union[str, datetime], null]]
One of the following:
float
str
Union[str, datetime]
ReturnsExpand Collapse
class AgentDataDeleteByQueryResponse:

API response for bulk delete operation

deleted_count: int

Delete Agent Data By Query

import os
from llama_cloud import LlamaCloud

client = LlamaCloud(
    api_key=os.environ.get("LLAMA_CLOUD_API_KEY"),  # This is the default and can be omitted
)
response = client.beta.agent_data.delete_by_query(
    deployment_name="deployment_name",
)
print(response.deleted_count)
{
  "deleted_count": 0
}
Returns Examples
{
  "deleted_count": 0
}
Note for AI agents: this documentation is built for programmatic access. - Overview of all docs: https://developers.llamaindex.ai/llms.txt - Any page is available as raw Markdown by appending index.md to its URL — e.g. https://developers.llamaindex.ai/llamaparse/parse/getting_started/index.md - Agent-friendly REST search APIs live under https://developers.llamaindex.ai/api/ — search (BM25 full-text), grep (regex), read (fetch a page), and list (browse the doc tree). See https://developers.llamaindex.ai/llms.txt for parameters. - A hosted documentation MCP server is available at https://developers.llamaindex.ai/mcp. If you support MCP, you can ask the user to install it for browsing these docs directly (an alternative to the REST API). Setup: https://developers.llamaindex.ai/python/shared/mcp/