Beta

BetaAgent Data

Get Agent Data

$ llamacloud-prod beta:agent-data get

GET/api/v1/beta/agent-data/{item_id}

Update Agent Data

$ llamacloud-prod beta:agent-data update

PUT/api/v1/beta/agent-data/{item_id}

Delete Agent Data

$ llamacloud-prod beta:agent-data delete

DELETE/api/v1/beta/agent-data/{item_id}

Create Agent Data

$ llamacloud-prod beta:agent-data create

POST/api/v1/beta/agent-data

Search Agent Data

$ llamacloud-prod beta:agent-data search

POST/api/v1/beta/agent-data/:search

Aggregate Agent Data

$ llamacloud-prod beta:agent-data aggregate

POST/api/v1/beta/agent-data/:aggregate

Delete Agent Data By Query

$ llamacloud-prod beta:agent-data delete-by-query

POST/api/v1/beta/agent-data/:delete

ModelsExpand Collapse

agent_data: object { data, deployment_name, id, 4 more }

API Result for a single agent data item

data: map[unknown]

deployment_name: string

id: optional string

collection: optional string

created_at: optional string

project_id: optional string

updated_at: optional string

BetaSheets

Create Spreadsheet Job

$ llamacloud-prod beta:sheets create

POST/api/v1/beta/sheets/jobs

List Spreadsheet Jobs

$ llamacloud-prod beta:sheets list

GET/api/v1/beta/sheets/jobs

Get Spreadsheet Job

$ llamacloud-prod beta:sheets get

GET/api/v1/beta/sheets/jobs/{spreadsheet_job_id}

Get Result Region

$ llamacloud-prod beta:sheets get-result-table

GET/api/v1/beta/sheets/jobs/{spreadsheet_job_id}/regions/{region_id}/result/{region_type}

Delete Spreadsheet Job

$ llamacloud-prod beta:sheets delete-job

DELETE/api/v1/beta/sheets/jobs/{spreadsheet_job_id}

ModelsExpand Collapse

sheets_job: object { id, config, created_at, 10 more }

A spreadsheet parsing job

id: string

The ID of the job

config: object { extraction_range, flatten_hierarchical_tables, generate_additional_metadata, 5 more }

Configuration for the parsing job

extraction_range: optional string

A1 notation of the range to extract a single region from. If None, the entire sheet is used.

flatten_hierarchical_tables: optional boolean

Return a flattened dataframe when a detected table is recognized as hierarchical.

generate_additional_metadata: optional boolean

Whether to generate additional metadata (title, description) for each extracted region.

include_hidden_cells: optional boolean

Whether to include hidden cells when extracting regions from the spreadsheet.

sheet_names: optional array of string

The names of the sheets to extract regions from. If empty, all sheets will be processed.

specialization: optional string

Optional specialization mode for domain-specific extraction. Supported values: 'financial-standard', 'financial-enhanced', 'financial-precise'. Default None uses the general-purpose pipeline.

table_merge_sensitivity: optional "strong" or "weak"

Influences how likely similar-looking regions are merged into a single table. Useful for spreadsheets that either have sparse tables (strong merging) or many distinct tables close together (weak merging).

"strong"

"weak"

use_experimental_processing: optional boolean

Enables experimental processing. Accuracy may be impacted.

created_at: string

When the job was created

file_id: string

The ID of the input file

project_id: string

The ID of the project

status: "PENDING" or "SUCCESS" or "ERROR" or 2 more

The status of the parsing job

"PENDING"

"SUCCESS"

"ERROR"

"PARTIAL_SUCCESS"

"CANCELLED"

updated_at: string

When the job was last updated

user_id: string

The ID of the user

errors: optional array of string

Any errors encountered

Deprecatedfile: optional object { id, name, project_id, 11 more }

Schema for a file.

id: string

Unique identifier

name: string

project_id: string

The ID of the project that the file belongs to

created_at: optional string

Creation datetime

data_source_id: optional string

The ID of the data source that the file belongs to

expires_at: optional string

The expiration date for the file. Files past this date can be deleted.

external_file_id: optional string

The ID of the file in the external system

file_size: optional number

Size of the file in bytes

file_type: optional string

File type (e.g. pdf, docx, etc.)

last_modified_at: optional string

The last modified time of the file

permission_info: optional map[map[unknown] or array of unknown or string or 2 more]

Permission information for the file

union_member_0: map[unknown]

union_member_1: array of unknown

union_member_2: string

union_member_3: number

union_member_4: boolean

purpose: optional string

The intended purpose of the file (e.g., 'user_data', 'parse', 'extract', 'split', 'classify')

resource_info: optional map[map[unknown] or array of unknown or string or 2 more]

Resource information for the file

union_member_0: map[unknown]

union_member_1: array of unknown

union_member_2: string

union_member_3: number

union_member_4: boolean

updated_at: optional string

Update datetime

regions: optional array of object { location, region_type, sheet_name, 3 more }

All extracted regions (populated when job is complete)

location: string

Location of the region in the spreadsheet

region_type: string

Type of the extracted region

sheet_name: string

Worksheet name where region was found

description: optional string

Generated description for the region

region_id: optional string

Unique identifier for this region within the file

title: optional string

Generated title for the region

success: optional boolean

Whether the job completed successfully

worksheet_metadata: optional array of object { sheet_name, description, title }

Metadata for each processed worksheet (populated when job is complete)

sheet_name: string

Name of the worksheet

description: optional string

Generated description of the worksheet

title: optional string

Generated title for the worksheet

sheets_parsing_config: object { extraction_range, flatten_hierarchical_tables, generate_additional_metadata, 5 more }

Configuration for spreadsheet parsing and region extraction

extraction_range: optional string

A1 notation of the range to extract a single region from. If None, the entire sheet is used.

flatten_hierarchical_tables: optional boolean

Return a flattened dataframe when a detected table is recognized as hierarchical.

generate_additional_metadata: optional boolean

Whether to generate additional metadata (title, description) for each extracted region.

include_hidden_cells: optional boolean

Whether to include hidden cells when extracting regions from the spreadsheet.

sheet_names: optional array of string

The names of the sheets to extract regions from. If empty, all sheets will be processed.

specialization: optional string

Optional specialization mode for domain-specific extraction. Supported values: 'financial-standard', 'financial-enhanced', 'financial-precise'. Default None uses the general-purpose pipeline.

table_merge_sensitivity: optional "strong" or "weak"

"strong"

"weak"

use_experimental_processing: optional boolean

Enables experimental processing. Accuracy may be impacted.

BetaBatchJob Items

List Batch Job Items

$ llamacloud-prod beta:batch:job-items list

GET/api/v1/beta/batch-processing/{job_id}/items

Get Item Processing Results

$ llamacloud-prod beta:batch:job-items get-processing-results

GET/api/v1/beta/batch-processing/items/{item_id}/processing-results

ModelsExpand Collapse

split_category: object { name, description }

Category definition for document splitting.

name: string

Name of the category.

description: optional string

Optional description of what content belongs in this category.

split_document_input: object { type, value }

Document input specification for beta API.

type: string

Type of document input. Valid values are: file_id

value: string

Document identifier.

split_result_response: object { segments }

Result of a completed split job.

segments: array of SplitSegmentResponse { category, confidence_category, pages }

List of document segments.

category: string

Category name this split belongs to.

confidence_category: string

Categorical confidence level. Valid values are: high, medium, low.

pages: array of number

1-indexed page numbers in this split.

split_segment_response: object { category, confidence_category, pages }

A segment of the split document.

category: string

Category name this split belongs to.

confidence_category: string

Categorical confidence level. Valid values are: high, medium, low.

pages: array of number

1-indexed page numbers in this split.

Beta

BetaAgent Data

ModelsExpand Collapse

BetaSheets

ModelsExpand Collapse

BetaDirectories

BetaDirectoriesFiles

BetaBatch

BetaBatchJob Items

BetaSplit

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