Create Extract Job
ExtractV2Job Extract.Create(ExtractCreateParamsparameters, CancellationTokencancellationToken = default)
POST/api/v2/extract
Create an extraction job.
Extracts structured data from a document using either a saved configuration or an inline JSON Schema.
Input
Provide exactly one of:
configuration_id— reference a saved extraction configconfiguration— inline configuration with adata_schema
Document input
Set file_input to a file ID (dfl-...) or a
completed parse job ID (pjb-...).
The job runs asynchronously. Poll GET /extract/{job_id} or
register a webhook to monitor completion.
Create Extract Job
ExtractCreateParams parameters = new()
{
FileInput = "dfl-aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee"
};
var extractV2Job = await client.Extract.Create(parameters);
Console.WriteLine(extractV2Job);{
"id": "ext-aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee",
"created_at": "2019-12-27T18:11:19.117Z",
"file_input": "dfl-aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee",
"project_id": "prj-aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee",
"status": "COMPLETED",
"updated_at": "2019-12-27T18:11:19.117Z",
"configuration": {
"data_schema": {
"foo": {
"foo": "bar"
}
},
"cite_sources": true,
"confidence_scores": true,
"extraction_target": "per_doc",
"max_pages": 10,
"parse_config_id": "cfg-11111111-2222-3333-4444-555555555555",
"parse_tier": "fast",
"system_prompt": "Extract all monetary values in USD. If a currency is not specified, assume USD.",
"target_pages": "1,3,5-7",
"tier": "cost_effective",
"version": "latest"
},
"configuration_id": "cfg-11111111-2222-3333-4444-555555555555",
"error_message": "error_message",
"extract_metadata": {
"field_metadata": {
"document_metadata": {
"items": [
{
"amount": {
"citation": [
{
"matching_text": "$10.00",
"page": 1
}
],
"confidence": 1
},
"description": {
"citation": [
{
"matching_text": "$10/month",
"page": 1
}
],
"confidence": 0.998
}
}
],
"total": {
"citation": "bar",
"confidence": "bar"
},
"vendor": {
"citation": "bar",
"confidence": "bar",
"extraction_confidence": "bar",
"parsing_confidence": "bar"
}
},
"page_metadata": [
{
"foo": {
"foo": "bar"
}
}
],
"row_metadata": [
{
"foo": {
"foo": "bar"
}
}
]
},
"parse_job_id": "parse_job_id",
"parse_tier": "parse_tier"
},
"extract_result": {
"foo": {
"foo": "bar"
}
},
"metadata": {
"usage": {
"num_pages_billed": 0,
"num_pages_extracted": 0
}
}
}Returns Examples
{
"id": "ext-aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee",
"created_at": "2019-12-27T18:11:19.117Z",
"file_input": "dfl-aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee",
"project_id": "prj-aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee",
"status": "COMPLETED",
"updated_at": "2019-12-27T18:11:19.117Z",
"configuration": {
"data_schema": {
"foo": {
"foo": "bar"
}
},
"cite_sources": true,
"confidence_scores": true,
"extraction_target": "per_doc",
"max_pages": 10,
"parse_config_id": "cfg-11111111-2222-3333-4444-555555555555",
"parse_tier": "fast",
"system_prompt": "Extract all monetary values in USD. If a currency is not specified, assume USD.",
"target_pages": "1,3,5-7",
"tier": "cost_effective",
"version": "latest"
},
"configuration_id": "cfg-11111111-2222-3333-4444-555555555555",
"error_message": "error_message",
"extract_metadata": {
"field_metadata": {
"document_metadata": {
"items": [
{
"amount": {
"citation": [
{
"matching_text": "$10.00",
"page": 1
}
],
"confidence": 1
},
"description": {
"citation": [
{
"matching_text": "$10/month",
"page": 1
}
],
"confidence": 0.998
}
}
],
"total": {
"citation": "bar",
"confidence": "bar"
},
"vendor": {
"citation": "bar",
"confidence": "bar",
"extraction_confidence": "bar",
"parsing_confidence": "bar"
}
},
"page_metadata": [
{
"foo": {
"foo": "bar"
}
}
],
"row_metadata": [
{
"foo": {
"foo": "bar"
}
}
]
},
"parse_job_id": "parse_job_id",
"parse_tier": "parse_tier"
},
"extract_result": {
"foo": {
"foo": "bar"
}
},
"metadata": {
"usage": {
"num_pages_billed": 0,
"num_pages_extracted": 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/for-agents/mcp/
- Other LlamaIndex tooling for agents — the LlamaParse Platform MCP server, agent skills and plugins, and the n8n node — is mapped at https://developers.llamaindex.ai/for-agents/