ModelsExpand Collapse SplitCategory = object { name , description }
Category definition for document splitting.
description : optional string
Optional description of what content belongs in this category.
Document input specification for beta API.
Type of document input. Valid values are: file_id
SplitResultResponse = object { segments }
Result of a completed split job.
List of document segments.
Category name this split belongs to.
confidence_category : string
Categorical confidence level. Valid values are: high, medium, low.
1-indexed page numbers in this split.
SplitSegmentResponse = object { category , confidence_category , pages }
A segment of the split document.
Category name this split belongs to.
confidence_category : string
Categorical confidence level. Valid values are: high, medium, low.
1-indexed page numbers in this split.
SplitCreateResponse = object { id , categories , document_input , 8 more }
Beta response — uses nested document_input object.
Unique identifier for the split job.
Categories used for splitting.
description : optional string
Optional description of what content belongs in this category.
Type of document input. Valid values are: file_id
Project ID this job belongs to.
Current status of the job. Valid values are: pending, processing, completed, failed, cancelled.
User ID who created this job.
configuration_id : optional string
Split configuration ID used for this job.
created_at : optional string
error_message : optional string
Error message if the job failed.
Result of a completed split job.
List of document segments.
Category name this split belongs to.
confidence_category : string
Categorical confidence level. Valid values are: high, medium, low.
1-indexed page numbers in this split.
updated_at : optional string
SplitListResponse = object { id , categories , document_input , 8 more }
Beta response — uses nested document_input object.
Unique identifier for the split job.
Categories used for splitting.
description : optional string
Optional description of what content belongs in this category.
Type of document input. Valid values are: file_id
Project ID this job belongs to.
Current status of the job. Valid values are: pending, processing, completed, failed, cancelled.
User ID who created this job.
configuration_id : optional string
Split configuration ID used for this job.
created_at : optional string
error_message : optional string
Error message if the job failed.
Result of a completed split job.
List of document segments.
Category name this split belongs to.
confidence_category : string
Categorical confidence level. Valid values are: high, medium, low.
1-indexed page numbers in this split.
updated_at : optional string
SplitGetResponse = object { id , categories , document_input , 8 more }
Beta response — uses nested document_input object.
Unique identifier for the split job.
Categories used for splitting.
description : optional string
Optional description of what content belongs in this category.
Type of document input. Valid values are: file_id
Project ID this job belongs to.
Current status of the job. Valid values are: pending, processing, completed, failed, cancelled.
User ID who created this job.
configuration_id : optional string
Split configuration ID used for this job.
created_at : optional string
error_message : optional string
Error message if the job failed.
Result of a completed split job.
List of document segments.
Category name this split belongs to.
confidence_category : string
Categorical confidence level. Valid values are: high, medium, low.
1-indexed page numbers in this split.
updated_at : optional string
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/