Configure the Client

Reference documentation on preparing and configuring the Mindee client.

This is reference documentation.

Code samples shown are only examples, and will not work as-is. You'll need to copy-paste and modify according to your requirements.

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Take a look at the Quick Start page.
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Requirements

Before proceeding you'll need to have one of the official Mindee client libraries installed.

You'll also need to use one of your Integration Overview and one or several Models configured.

Overview

Before sending any files to the Mindee servers for processing, you'll need to initialize your client and set inference options.

These settings will determine how your files are sent, including any extra options, and how you want to process the result.

Initialize the Mindee Client

This should be the first step in your code. It will determine which organization is used to make the calls.

You should reuse the same client instance for all calls of the same organization.

The client instance is thread-safe where applicable.

First import the needed classes:

from mindee import (
    ClientV2,
    InferenceParameters,
    InferenceResponse,
    PathInput,  # for loading files from disk
)

For the API key, you can pass it directly to the client. This is useful for quick testing.

api_key = "MY_API_KEY"

mindee_client = ClientV2(api_key)

Instead of passing the key directly, you can also set the following environment variable:

MINDEE_V2_API_KEY

This is recommended for production use. In this way there is no need to pass the api_key when initializing the client.

mindee_client = ClientV2()

First import the needed classes. We recommend using ES Modules.

import * as mindee from "mindee";
// If you're on CommonJS:
// const mindee = require("mindee");

For the API key, you can pass it directly to the client. This is useful for quick testing.

const apiKey = "MY_API_KEY";

const mindeeClient = new mindee.Client({ apiKey: apiKey });

Instead of passing the key directly, you can also set the following environment variable:

MINDEE_V2_API_KEY

This is recommended for production use. In this way there is no need to pass the apiKey argument when initializing the client.

const mindeeClient = new mindee.Client();

Advanced Usage

internally, undici is used for making HTTP calls, and when the client is initialized getGlobalDispatcher is called.

This is perfectly fine for the vast majority of cases: If you set a custom Agent as the global dispatcher, Mindee will use it.

In the rare case where you need a specific dispatcher for Mindee, you can set it as follows:

import { Agent, interceptors } from "undici";

// Init the custom Dispatcher
// REPLACE THE LINE BELOW WITH YOUR CODE - this example will NOT work!
const myDispatcher = new Agent().compose( ... );

const mindeeClient = new mindee.Client({
  // Don't set if using an environment variable
  apiKey: apiKey,

  // Activates verbose logging - disable in production!
  debug: true,

  // Pass the custom dispatcher to the Mindee client
  dispatcher: myDispatcher,
});

First import the needed classes:

use Mindee\ClientV2;
use Mindee\Input\InferenceParameters;
use Mindee\Error\MindeeException;

For the API key, you can pass it directly to the client. This is useful for quick testing.

$apiKey = "MY_API_KEY";

$mindeeClient = new ClientV2($apiKey);

Instead of passing the key directly, you can also set the following environment variable:

MINDEE_V2_API_KEY

This is recommended for production use. In this way there is no need to pass the $apiKey when initializing the client.

$mindeeClient = new ClientV2($apiKey);

First import the Mindee package:

require 'mindee'

For the API key, you can pass it directly to the client. This is useful for quick testing.

api_key = 'MY_API_KEY'
mindee_client = Mindee::ClientV2.new(api_key: api_key)

Instead of passing the key directly, you can also set the following environment variable:

MINDEE_V2_API_KEY

This is recommended for production use. In this way there is no need to pass the api_key when initializing the client.

mindee_client = Mindee::ClientV2.new()

First import the needed classes:

import com.mindee.MindeeClientV2;
import com.mindee.InferenceParameters;

For the API key, you can pass it directly to the client. This is useful for quick testing.

String apiKey = "MY_API_KEY";

MindeeClientV2 mindeeClient = new MindeeClientV2(apiKey);

Instead of passing the key directly, you can also set the following environment variable:

MINDEE_V2_API_KEY

This is recommended for production use. In this way there is no need to pass the apiKey argument when initializing the client.

MindeeClientV2 mindeeClient = new MindeeClientV2();

First add the required namespaces.

using Mindee;
using Mindee.Input;

For the API key, you can pass it directly to the client. This is useful for quick testing.

string apiKey = "MY_API_KEY";

MindeeClientV2 mindeeClient = new MindeeClientV2(apiKey);

Instead of passing the key directly, you can also set the following environment variable:

MindeeV2__ApiKey

This is recommended for production use. In this way there is no need to pass the apiKey argument when initializing the client.

MindeeClientV2 mindeeClient = new MindeeClientV2();

Set Product Parameters

Product parameters control:

which model to use
server-side processing options
how the results will be returned to you

Use an Alias

You can set an alias for linking the sent file to your own system.

For example, you could use an internal PO number, or your database ID.

Aliases are not unique in our database, you can use the same alias multiple times.

Only the model_id is required.

inference_params = InferenceParameters(
    # ID of the model, required.
    model_id="MY_MODEL_ID",
    
    # Use an alias to link the file to your own DB.
    # If empty, no alias will be used.
    alias="MY_ALIAS",
    
    # ... any other options ...
)

Only the modelId is required.

const productParams = {
  // ID of the model, required.
  modelId: "MY_MODEL_ID",
  
  // Use an alias to link the file to your own DB.
  // If empty, no alias will be used.
  alias: "MY_ALIAS",
  
  // ... any other options ...
};

Only the modelId is required.

$inferenceParams = new InferenceParameters(
    // ID of the model, required.
    "MY_MODEL_ID",

    // Use an alias to link the file to your own DB.
    // If empty, no alias will be used.
    alias: "MY_ALIAS",
    
    // ... any other options ...
);

Only the model_id is required.

inference_params = Mindee::Input::InferenceParameters.new(
    # ID of the model, required.
    'MY_MODEL_ID',
    
    # Use an alias to link the file to your own DB.
    # If empty, no alias will be used.
    file_alias: 'MY_ALIAS',
    
    # ... any other options ...
)

Only the modelId is required.

InferenceParameters params = InferenceParameters
    // ID of the model, required.
    .builder("MY_MODEL_ID")
    
    // Use an alias to link the file to your own DB.
    // If empty, no alias will be used.
    .alias("MY_ALIAS")
    
    // ... any other options ...

    // complete the builder
    .build();

Only the modelId is required.

var inferenceParams = new InferenceParameters(
    // ID of the model, required.
    modelId: "MY_MODEL_ID"

    // Use an alias to link the file to your own DB.
    // If empty, no alias will be used.
    , alias: "MY_ALIAS"
    
    // ... any other options ...
);

Optional Features Configuration

Enable or disable Optional Features.

Enabling a feature not in your plan will result in a Payment Required error (HTTP 402).

Check the Feature Comparison section for more information.

The default activation states for Optional Features are set on the platform. Any values set here will override the defaults.

Leave empty or null to use the default platform values.

For example: if the Polygon feature is enabled on the platform, and polygon is explicitly set to false in the parameters ⇒ the Polygon feature will not be enabled for the API call.

Only the model_id is required.

inference_params = InferenceParameters(
    # ID of the model, required.
    model_id="MY_MODEL_ID",

    # Optional Features: set to `True` or `False` to override defaults

    # Enhance extraction accuracy with Retrieval-Augmented Generation.
    rag=None,
    # Extract the full text content from the document as strings.
    raw_text=None,
    # Calculate bounding box polygons for all fields.
    polygon=None,
    # Boost the precision and accuracy of all extractions.
    # Calculate confidence scores for all fields.
    confidence=None,
    
    # ... any other options ...
)

Only the modelId is required.

const productParams = {
  // ID of the model, required.
  modelId: "MY_MODEL_ID",

  // Optional Features: set to `true` or `false` to override defaults

  // Enhance extraction accuracy with Retrieval-Augmented Generation.
  rag: undefined,
  // Extract the full text content from the document as strings.
  rawText: undefined,
  // Calculate bounding box polygons for all fields.
  polygon: undefined,
  // Boost the precision and accuracy of all extractions.
  // Calculate confidence scores for all fields.
  confidence: undefined,
  
  // ... any other options ...
};

Only the modelId is required.

$inferenceParams = new InferenceParameters(
    // ID of the model, required.
    "MY_MODEL_ID",

    // Optional Features: set to `true` or `false` to override defaults

    // Enhance extraction accuracy with Retrieval-Augmented Generation.
    rag: null,
    // Extract the full text content from the document as strings.
    rawText: null,
    // Calculate bounding box polygons for all fields.
    polygon: null,
    // Boost the precision and accuracy of all extractions.
    // Calculate confidence scores for all fields.
    confidence: null,
    
    // ... any other options ...
);

Only the model_id is required.

inference_params = Mindee::Input::InferenceParameters.new(
    # ID of the model, required.
    'MY_MODEL_ID',

    # Options: set to `true` or `false` to override defaults

    # Enhance extraction accuracy with Retrieval-Augmented Generation.
    rag: nil,
    # Extract the full text content from the document as strings.
    raw_text: nil,
    # Calculate bounding box polygons for all fields.
    polygon: nil,
    # Boost the precision and accuracy of all extractions.
    # Calculate confidence scores for all fields.
    confidence: nil,
    
    # ... any other options ...
)

Only the modelId is required.

InferenceParameters params = InferenceParameters
    // ID of the model, required.
    .builder("MY_MODEL_ID")

    // Optional Features: set to `true` or `false` to override defaults

    // Enhance extraction accuracy with Retrieval-Augmented Generation.
    .rag(null)
    // Extract the full text content from the document as strings.
    .rawText(null)
    // Calculate bounding box polygons for all fields.
    .polygon(null)
    // Boost the precision and accuracy of all extractions.
    // Calculate confidence scores for all fields.
    .confidence(null)
    
    // ... any other options ...

    // complete the builder
    .build();

Only the modelId is required.

var inferenceParams = new InferenceParameters(
    // ID of the model, required.
    modelId: "MY_MODEL_ID"

    // Optional Features: set to `true` or `false` to override defaults

    // Enhance extraction accuracy with Retrieval-Augmented Generation.
    , rag: null
    // Extract the full text content from the document as strings.
    , rawText: null
    // Calculate bounding box polygons for all fields.
    , polygon: null
    // Boost the precision and accuracy of all extractions.
    // Calculate confidence scores for all fields.
    , confidence: null
    
    // ... any other options ...
);

Dynamic Model Options

These options allow changing how the model performs an inference on a per-call basis.

As such they can only be used via API.

Text Context

Give additional guidelines to the model to help it better process a specific document.

This is a free-form text format.

Data Schema

In the rare cases when Text Context and/or RAG is not enough.

Directly modify the Data Schema: add, remove, or change fields.

To download the JSON string appropriate for your model:

Go to your model's page
On the left-hand menu, click on "General Settings"
Scroll down to the "Actions" section
Click on the "Download Data Schema" button:

Code Sample

The Data Schema can be passed as a JSON string or by instantiating the appropriate classes.

If passed as a JSON string, it will be validated in the client before being sent to the server.

Only the model_id is required.

inference_params = InferenceParameters(
    # ID of the model, required.
    model_id="MY_MODEL_ID",
    
    # Text Context
    text_context="this is an invoice.",
    
    # Data Schema
    data_schema="{ ... JSON DATA ... }",
    
    # ... any other options ...
)

Only the modelId is required.

const productParams = {
  // ID of the model, required.
  modelId: "MY_MODEL_ID",
  
  // Text Context
  textContext: "this is an invoice.",
    
  // Data Schema
  dataSchema: "{ ... JSON DATA ... }",
  
  // ... any other options ...
};

Only the modelId is required.

$inferenceParams = new InferenceParameters(
    // ID of the model, required.
    "MY_MODEL_ID",

    // Text Context
    textContext: "this is an invoice.",

    // Data Schema
    dataSchema: "{ ... JSON DATA ... }",

    // ... any other options ...
);

Only the model_id is required.

inference_params = Mindee::Input::InferenceParameters.new(
    # ID of the model, required.
    'MY_MODEL_ID',
    
    # Text Context
    text_context: "this is an invoice.",
    
    # Data Schema
    data_schema: "{ ... JSON DATA ... }",
    
    # ... any other options ...
)

Only the modelId is required.

InferenceParameters params = InferenceParameters
    // ID of the model, required.
    .builder("MY_MODEL_ID")
    
    // Text Context
    .textContext("this is an invoice.")
    
    // Data Schema
    .dataSchema("{ ... JSON DATA ... }")
    
    // ... any other options ...

    // complete the builder
    .build();

Only the modelId is required.

var inferenceParams = new InferenceParameters(
    // ID of the model, required.
    modelId: "MY_MODEL_ID"
    
    // Text Context
    , textContext: "this is an invoice."
    
    // Data Schema
    , dataSchema: "{ ... JSON DATA ... }"
    
    // ... any other options ...
);

Next Steps

Now that everything is ready to, it's time to send your files to the Mindee servers.

If you're sending a local file, head on over to the Load and Adjust a File section for details on the next step.

If you're sending an URL, head on over to the Send a File or URL section.

PreviousQuick Start NextLoad and Adjust a File

Last updated 4 days ago

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hashtagRequirements

hashtagOverview

hashtagInitialize the Mindee Client

hashtagAdvanced Usage

hashtagSet Product Parameters

hashtagUse an Alias

hashtagOptional Features Configuration

hashtagDynamic Model Options

hashtagText Context

hashtagData Schema

hashtagCode Sample

hashtagNext Steps

Requirements

Overview

Initialize the Mindee Client

Advanced Usage

Set Product Parameters

Use an Alias

Optional Features Configuration

Dynamic Model Options

Text Context

Data Schema

Code Sample

Next Steps