# Extraction Configuration
Configuration parameters specific to Extraction models.
There are also [Basic Model Configuration](/integrations/client-libraries-sdk/basic-model-configuration.md) which can be used with all models.
## Optional Features Configuration
Enable or disable [Optional Features](/extraction-models/optional-features.md).
{% hint style="warning" icon="money-check-dollar-pen" %}
Enabling a feature not in your plan will result in a Payment Required error (HTTP 402).
Check the [Plans](/account-management/plans.md#feature-comparison) section for more information.
{% endhint %}
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.
{% tabs %}
{% tab title="Python" %}
Only the `model_id` is required.
```python
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 ...
)
```
{% endtab %}
{% tab title="Node.js" %}
Only the `modelId` is required.
```typescript
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 ...
};
```
{% endtab %}
{% tab title="PHP" %}
Only the `modelId` is required.
```php
$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 ...
);
```
{% endtab %}
{% tab title="Ruby" %}
Only the `model_id` is required.
```ruby
inference_params = {
# ID of the model, required.
model_id: '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 ...
}
```
{% endtab %}
{% tab title="Java" %}
Only the `modelId` is required.
```java
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();
```
{% endtab %}
{% tab title=".NET" %}
Only the `modelId` is required.
```csharp
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 ...
);
```
{% endtab %}
{% endtabs %}
## Dynamic Model Options
These options allow changing how the model performs an inference on a per-call basis.
These features can **only** be used via API.
{% hint style="info" %}
These advanced features are not generally meant for improving model accuracy.
Instead, make sure the Data Schema has been [properly optimized](/extraction-models/data-schema.md#performance-optimization).
{% endhint %}
### 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
Allows changing the Data Schema on a per-call basis: directly modify the Data Schema: add, remove, or change fields.
The typical use case is when the data needing to be extracted change based on internal business logic.
To download the JSON string appropriate for your model:
1. Go to your model's page
2. On the left-hand menu, click on "General Settings"
3. Scroll down to the "Actions" section
4. 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.
{% tabs %}
{% tab title="Python" %}
Only the `model_id` is required.
```python
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 ...
)
```
{% endtab %}
{% tab title="Node.js" %}
Only the `modelId` is required.
```typescript
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 ...
};
```
{% endtab %}
{% tab title="PHP" %}
Only the `modelId` is required.
```php
$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 ...
);
```
{% endtab %}
{% tab title="Ruby" %}
Only the `model_id` is required.
```ruby
inference_params = {
# 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 ...
}
```
{% endtab %}
{% tab title="Java" %}
Only the `modelId` is required.
```java
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();
```
{% endtab %}
{% tab title=".NET" %}
Only the `modelId` is required.
```csharp
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 ...
);
```
{% endtab %}
{% endtabs %}
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