OpenAI

curl --request POST \
  --url "${UNSTRUCTURED_API_URL}/api/v1/jobs/" \
  --header "unstructured-api-key: ${UNSTRUCTURED_API_KEY}" \
  --form "request_data={\"template_id\":\"f0a1b2c3-4d5e-6f7a-8b9c-0d1e2f3a4b5c\"}" \
  --form "input_files=@/path/to/document.pdf"

import os
from unstructured_client import UnstructuredClient
from unstructured_client.models.operations import CreateJobRequest

client = UnstructuredClient(
    api_key_auth=os.getenv("UNSTRUCTURED_API_KEY"),
    server_url=os.getenv("UNSTRUCTURED_API_URL"),
)

response = client.jobs.create_job(
    request=CreateJobRequest(
        request_data="{\"template_id\":\"f0a1b2c3-4d5e-6f7a-8b9c-0d1e2f3a4b5c\"}"
    )
)
print(response)

import asyncio
import os
from unstructured_client import UnstructuredClient
from unstructured_client.models.operations import CreateJobRequest

async def create_job():
    client = UnstructuredClient(
        api_key_auth=os.getenv("UNSTRUCTURED_API_KEY"),
        server_url=os.getenv("UNSTRUCTURED_API_URL"),
    )
    response = await client.jobs.create_job_async(
        request=CreateJobRequest(
            request_data="{\"template_id\":\"f0a1b2c3-4d5e-6f7a-8b9c-0d1e2f3a4b5c\"}"
        )
    )
    print(response)

asyncio.run(create_job())

{
  "id": "b2c3d4e5-6f7a-8b9c-0d1e-2f3a4b5c6d7e",
  "workflow_id": "f0a1b2c3-4d5e-6f7a-8b9c-0d1e2f3a4b5c",
  "workflow_name": "My ETL Workflow",
  "status": "SCHEDULED",
  "stop_requested": false,
  "created_at": "2026-01-01T00:00:00Z",
  "input_file_ids": ["a6a27cf4-684f-45ed-992e-d2b1be77f2c6"],
  "job_type": "ephemeral"
}

POST

api

jobs

curl --request POST \
  --url "${UNSTRUCTURED_API_URL}/api/v1/jobs/" \
  --header "unstructured-api-key: ${UNSTRUCTURED_API_KEY}" \
  --form "request_data={\"template_id\":\"f0a1b2c3-4d5e-6f7a-8b9c-0d1e2f3a4b5c\"}" \
  --form "input_files=@/path/to/document.pdf"

import os
from unstructured_client import UnstructuredClient
from unstructured_client.models.operations import CreateJobRequest

client = UnstructuredClient(
    api_key_auth=os.getenv("UNSTRUCTURED_API_KEY"),
    server_url=os.getenv("UNSTRUCTURED_API_URL"),
)

response = client.jobs.create_job(
    request=CreateJobRequest(
        request_data="{\"template_id\":\"f0a1b2c3-4d5e-6f7a-8b9c-0d1e2f3a4b5c\"}"
    )
)
print(response)

import asyncio
import os
from unstructured_client import UnstructuredClient
from unstructured_client.models.operations import CreateJobRequest

async def create_job():
    client = UnstructuredClient(
        api_key_auth=os.getenv("UNSTRUCTURED_API_KEY"),
        server_url=os.getenv("UNSTRUCTURED_API_URL"),
    )
    response = await client.jobs.create_job_async(
        request=CreateJobRequest(
            request_data="{\"template_id\":\"f0a1b2c3-4d5e-6f7a-8b9c-0d1e2f3a4b5c\"}"
        )
    )
    print(response)

asyncio.run(create_job())

{
  "id": "b2c3d4e5-6f7a-8b9c-0d1e-2f3a4b5c6d7e",
  "workflow_id": "f0a1b2c3-4d5e-6f7a-8b9c-0d1e2f3a4b5c",
  "workflow_name": "My ETL Workflow",
  "status": "SCHEDULED",
  "stop_requested": false,
  "created_at": "2026-01-01T00:00:00Z",
  "input_file_ids": ["a6a27cf4-684f-45ed-992e-d2b1be77f2c6"],
  "job_type": "ephemeral"
}

An local-file processing job is a job that takes one or more local files only as input, and whose temporary workflow exists only for the duration of the job’s run.

To run a workflow that was already created at some point in the past and still exists, see run workflow endpoint instead. To run a workflow that takes files and data from remote locations as input (instead of local files), do the following instead:

Create a source connector to the remote source locations.
Create a destination connector to the remote destination location.
Create a long-lived workflow that uses this specific source connector and destination connector.
Run this long-lived workflow manually, if you have not already created the workflow to run on a schedule.

Body

string

required

Job configuration data.

To use a workflow template for a job, include a template_id field that specifies the unique ID of the workflow template. For more information, see list templates.
To use a custom workflow definition for a job, include a job_nodes field that specifies the settings for the job’s workflow nodes. For instructions, see Workflow Nodes.

array

Input files to process. Upload as multipart/form-data, in the following format:

--form "input_files=@</full/path/to/local/filename.extension>;filename=<filename.extension>;type=<local-file-media-type>" \
--form "input_files=@</full/path/to/local/filename.extension>;filename=<filename.extension>;type=<local-file-media-type>" # For each additional file to be uploaded.

For more information, see Unstructured API Quickstart - local-file processing jobs.

array

IDs of files already uploaded to the playground. Send one multipart field per ID. The API combines these with IDs in request_data and removes duplicates. Provide files, file IDs, or both.

Response

string

required

Unique identifier for the job.

string

required

Unique identifier of the workflow that created this job.

string

required

Name of the workflow that created this job.

string

required

Job lifecycle state. One of: SCHEDULED, IN_PROGRESS, COMPLETED, STOPPED, FAILED, REJECTED. COMPLETED means job execution finished. Check processing_status for the document outcome.

string

required

ISO 8601 timestamp when the job was created.

string

ISO 8601 duration of the job run.

array

IDs of input files for this job.

array

Output file metadata objects. Each object includes node_id, file_id, node_type, and node_subtype.

string

Job type. Default: ephemeral.

boolean

true means someone requested a stop for the job. false means no one has requested a stop.

string

Identifier of the user who created the job, when available.

string

Sanitized failure reason for a failed job, when available.

string

Document processing outcome. This field is absent when a newly created job has not processed documents.

integer

Number of documents recorded as failed so far. A zero on an unfinished job is not a final result.

string

Reason a completed job delivered no documents, if detected: NO_DOCUMENTS_DISCOVERED or NO_DOCUMENTS_SUCCEEDED.

curl --request POST \
  --url "${UNSTRUCTURED_API_URL}/api/v1/jobs/" \
  --header "unstructured-api-key: ${UNSTRUCTURED_API_KEY}" \
  --form "request_data={\"template_id\":\"f0a1b2c3-4d5e-6f7a-8b9c-0d1e2f3a4b5c\"}" \
  --form "input_files=@/path/to/document.pdf"

import os
from unstructured_client import UnstructuredClient
from unstructured_client.models.operations import CreateJobRequest

client = UnstructuredClient(
    api_key_auth=os.getenv("UNSTRUCTURED_API_KEY"),
    server_url=os.getenv("UNSTRUCTURED_API_URL"),
)

response = client.jobs.create_job(
    request=CreateJobRequest(
        request_data="{\"template_id\":\"f0a1b2c3-4d5e-6f7a-8b9c-0d1e2f3a4b5c\"}"
    )
)
print(response)

import asyncio
import os
from unstructured_client import UnstructuredClient
from unstructured_client.models.operations import CreateJobRequest

async def create_job():
    client = UnstructuredClient(
        api_key_auth=os.getenv("UNSTRUCTURED_API_KEY"),
        server_url=os.getenv("UNSTRUCTURED_API_URL"),
    )
    response = await client.jobs.create_job_async(
        request=CreateJobRequest(
            request_data="{\"template_id\":\"f0a1b2c3-4d5e-6f7a-8b9c-0d1e2f3a4b5c\"}"
        )
    )
    print(response)

asyncio.run(create_job())

{
  "id": "b2c3d4e5-6f7a-8b9c-0d1e-2f3a4b5c6d7e",
  "workflow_id": "f0a1b2c3-4d5e-6f7a-8b9c-0d1e2f3a4b5c",
  "workflow_name": "My ETL Workflow",
  "status": "SCHEDULED",
  "stop_requested": false,
  "created_at": "2026-01-01T00:00:00Z",
  "input_file_ids": ["a6a27cf4-684f-45ed-992e-d2b1be77f2c6"],
  "job_type": "ephemeral"
}

Developer guide

API reference

Troubleshooting

Create job

Body

Response

​Body

​Response

Body

Response