Create Classify Job
$ llamacloud-prod classify create
POST/api/v2/classify
Create a classify job.
Classifies a document against a set of rules. Set file_input
to a file ID (dfl-...) or parse job ID (pjb-...), and provide
either inline configuration with rules or a configuration_id
referencing a saved preset.
Each rule has a type (the label to assign) and a description
(natural language criteria). The classifier returns the best
matching rule with a confidence score.
The job runs asynchronously. Poll GET /classify/{job_id} to
check status and retrieve results.
Create Classify Job
llamacloud-prod classify create \
--api-key 'My API Key'{
"id": "id",
"configuration": {
"rules": [
{
"description": "contains invoice number, line items, and total amount",
"type": "invoice"
}
],
"mode": "FAST",
"parsing_configuration": {
"lang": "en",
"max_pages": 10,
"target_pages": "1,3,5-7"
}
},
"document_input_type": "url",
"file_input": "file_input",
"project_id": "project_id",
"status": "PENDING",
"user_id": "user_id",
"configuration_id": "configuration_id",
"created_at": "2019-12-27T18:11:19.117Z",
"error_message": "error_message",
"parse_job_id": "parse_job_id",
"result": {
"confidence": 0,
"reasoning": "reasoning",
"type": "type"
},
"transaction_id": "transaction_id",
"updated_at": "2019-12-27T18:11:19.117Z"
}Returns Examples
{
"id": "id",
"configuration": {
"rules": [
{
"description": "contains invoice number, line items, and total amount",
"type": "invoice"
}
],
"mode": "FAST",
"parsing_configuration": {
"lang": "en",
"max_pages": 10,
"target_pages": "1,3,5-7"
}
},
"document_input_type": "url",
"file_input": "file_input",
"project_id": "project_id",
"status": "PENDING",
"user_id": "user_id",
"configuration_id": "configuration_id",
"created_at": "2019-12-27T18:11:19.117Z",
"error_message": "error_message",
"parse_job_id": "parse_job_id",
"result": {
"confidence": 0,
"reasoning": "reasoning",
"type": "type"
},
"transaction_id": "transaction_id",
"updated_at": "2019-12-27T18:11:19.117Z"
}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/