unstract-client 1.3.0

Python client for the Unstract LLM-powered structured data extraction platform

unstract-python-client

Python client for the Unstract LLM-powered structured data extraction platform

Installation

You can install the Unstract Python Client using pip:

pip install unstract-client

Usage

First, import the APIDeploymentsClient from the client module:

from unstract.api_deployments.client import APIDeploymentsClient

Then, create an instance of the APIDeploymentsClient:

client = APIDeploymentsClient(api_url="url", api_key="your_api_key")

Note: Pass the raw API key without the "Bearer " prefix — the client adds it automatically.

Now, you can use the client to interact with the Unstract API deployments API:

try:
    adc = APIDeploymentsClient(
        api_url=os.getenv("UNSTRACT_API_URL"),
        api_key=os.getenv("UNSTRACT_API_DEPLOYMENT_KEY"),
        api_timeout=10,
        logging_level="DEBUG",
        include_metadata=False # optional
    )
    # Replace files with pdfs
    response = adc.structure_file(
        ["<files>"]
    )
    print(response)
    if response["pending"]:
        while True:
            p_response = adc.check_execution_status(
                response["status_check_api_endpoint"]
            )
            print(p_response)
            if not p_response["pending"]:
                break
            print("Sleeping and checking again in 5 seconds..")
            time.sleep(5)
except APIDeploymentsClientException as e:
    print(e)

Parameter Details

api_url: The URL of the Unstract API deployment. api_key: Your raw API key. Do not include the "Bearer " prefix — the client adds it automatically. api_timeout: Set a timeout for API requests, e.g., api_timeout=10. logging_level: Set logging verbosity (e.g., "DEBUG"). include_metadata: If set to True, the response will include additional metadata (cost, tokens consumed and context) for each call made by the Prompt Studio exported tool.

Retry Configuration

The client includes built-in exponential backoff retry with the following behavior:

• Async mode (api_timeout=0): POST requests are retried on transient failures (5xx, 429) and connection errors, since the server returns immediately after queuing.
• Sync mode (api_timeout > 0, the default): POST requests are not retried, because the server blocks during processing — a failure may mean the request was processed but the response was lost.
• Status polling (check_execution_status): GET requests are always retried, as they are idempotent.

Retries are enabled by default and can be customized:

client = APIDeploymentsClient(
    api_url="url",
    api_key="your_api_key",
    max_retries=4,       # Max retry attempts (default: 4, set to 0 to disable)
    initial_delay=2.0,   # Initial delay in seconds (default: 2.0)
    max_delay=60.0,      # Maximum delay cap in seconds (default: 60.0)
    backoff_factor=2.0,  # Multiplier per retry (default: 2.0)
)

Parameter	Default	Description
max_retries	4	Maximum number of retry attempts. Set to 0 to disable retries.
initial_delay	2.0	Initial delay in seconds before the first retry.
max_delay	60.0	Maximum delay cap in seconds between retries.
backoff_factor	2.0	Multiplier applied to the delay for each subsequent retry.

The retry logic uses exponential backoff with full jitter and respects the Retry-After header on 429 responses.

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