Create Classify Job

classify.create() -> ClassifyCreateResponse

POST/api/v2/classify

Create a classify job.

Classifies a document against a set of rules. Provide either file_id or parse_job_id as the document input, and 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.

ParametersExpand Collapse

organization_id: Optional[str]

project_id: Optional[str]

configuration: Optional[ClassifyConfigurationParam]

Configuration for a classify job.

rules: List[Rule]

Classify rules to evaluate against the document (at least one required)

description: str

Natural language criteria for matching this rule

maxLength500

minLength10

type: str

Document type to assign when rule matches

maxLength50

minLength1

mode: Optional[Literal["FAST"]]

Classify execution mode

parsing_configuration: Optional[ParsingConfiguration]

Parsing configuration for classify jobs.

lang: Optional[str]

ISO 639-1 language code for the document

max_pages: Optional[int]

Maximum number of pages to process. Omit for no limit.

minimum1

target_pages: Optional[str]

Comma-separated page numbers or ranges to process (1-based). Omit to process all pages.

configuration_id: Optional[str]

Product configuration ID for reusable presets

file_id: Optional[str]

File ID to classify

parse_job_id: Optional[str]

Parse job ID to classify

transaction_id: Optional[str]

Idempotency key scoped to the project

ReturnsExpand Collapse

class ClassifyCreateResponse: …

Response for a classify job.

id: str

Unique identifier

configuration: ClassifyConfiguration

Classify configuration used for this job

rules: List[Rule]

Classify rules to evaluate against the document (at least one required)

description: str

Natural language criteria for matching this rule

maxLength500

minLength10

type: str

Document type to assign when rule matches

maxLength50

minLength1

mode: Optional[Literal["FAST"]]

Classify execution mode

parsing_configuration: Optional[ParsingConfiguration]

Parsing configuration for classify jobs.

lang: Optional[str]

ISO 639-1 language code for the document

max_pages: Optional[int]

Maximum number of pages to process. Omit for no limit.

minimum1

target_pages: Optional[str]

Comma-separated page numbers or ranges to process (1-based). Omit to process all pages.

document_input_type: Literal["url", "file_id", "parse_job_id"]

Whether the input was a file or parse job (FILE or PARSE_JOB)

Accepts one of the following:

"url"

"file_id"

"parse_job_id"

document_input_value: str

ID of the input file or parse job

project_id: str

Project this job belongs to

status: Literal["PENDING", "RUNNING", "COMPLETED", "FAILED"]

Current job status: PENDING, RUNNING, COMPLETED, or FAILED

Accepts one of the following:

"PENDING"

"RUNNING"

"COMPLETED"

"FAILED"

user_id: str

User who created this job

configuration_id: Optional[str]

Product configuration ID

created_at: Optional[datetime]

Creation datetime

formatdate-time

error_message: Optional[str]

Error message if job failed

parse_job_id: Optional[str]

Associated parse job ID

result: Optional[ClassifyResult]

Result of classifying a document.

confidence: float

Confidence score between 0.0 and 1.0

maximum1

minimum0

reasoning: str

Why the document matched (or didn't match) the returned rule

type: Optional[str]

Matched rule type, or null if no rule matched

transaction_id: Optional[str]

Idempotency key

updated_at: Optional[datetime]

Update datetime

formatdate-time

Create Classify Job

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
)
classify = client.classify.create()
print(classify.id)

{
  "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",
  "document_input_value": "document_input_value",
  "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",
  "document_input_value": "document_input_value",
  "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"
}