### start

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

General start method used across various components like HostedAppFileRead, BatchPrediction, Deployment, LlmCodeBlock. Specific usage depends on the class context.

```APIDOC
## start()

### Description
Initiates a process or operation within a specific AbacusAI component. The exact functionality depends on the class it is called on (e.g., HostedAppFileRead, BatchPrediction, Deployment, LlmCodeBlock).

### Method
(Implicitly a method call in Python SDK)

### Endpoint
(Not applicable for SDK method)

### Parameters
(Parameters are not detailed in the source and are context-dependent)

### Request Example
(Not applicable for SDK method)

### Response
(Response details are not detailed in the source)
```

--------------------------------

### Start Autonomous Agent API

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/prediction_client/index.rst.txt

Starts a deployed Autonomous agent.

```APIDOC
## POST /api/agents/autonomous/start

### Description
Starts a deployed Autonomous agent associated with the given deployment_conversation_id using the arguments and keyword arguments as inputs for execute function of trigger node.

### Method
POST

### Endpoint
/api/agents/autonomous/start

### Parameters
#### Request Body
- **deployment_token** (str) - Required - The deployment token used to authenticate access to created deployments.
- **deployment_id** (str) - Required - A unique string identifier for the deployment created under the project.
- **arguments** (list) - Optional - Positional arguments to the agent execute function.
- **keyword_arguments** (dict) - Optional - A dictionary where each 'key' represents the parameter name and its corresponding 'value' represents the value of that parameter for the agent execute function.
- **save_conversations** (bool) - Optional - If true then a new conversation will be created for every run of the workflow associated with the agent. Defaults to true.

### Request Example
{
  "deployment_token": "your_deployment_token",
  "deployment_id": "your_deployment_id",
  "arguments": ["start_command"],
  "save_conversations": true
}

### Response
#### Success Response (200)
- **message** (str) - Confirmation message that the agent has started.

#### Response Example
{
  "message": "Autonomous agent started successfully."
}
```

--------------------------------

### start

Source: https://github.com/abacusai/api-python/blob/main/docs/autoapi/abacusai/deployment/index.html

Restarts a specified deployment that was previously suspended.

```APIDOC
## start_deployment

### Description
Restarts the specified deployment that was previously suspended.

### Method
POST

### Endpoint
/deployments/{deployment_id}/start

### Parameters
#### Path Parameters
- **deployment_id** (string) - Required - A unique string identifier associated with the deployment.
```

--------------------------------

### test_start

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Indicates the start of the test set for ForecastingTrainingConfig and TimeseriesAnomalyTrainingConfig.

```APIDOC
## test_start

### Description
Defines the starting point for the test data set in forecasting and time series anomaly detection.

### Parameters
This attribute does not have explicitly documented parameters in the provided source.
```

--------------------------------

### Get Conversation Response

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/prediction_client/index.rst.txt

Retrieves a conversation response based on the user's message, continuing an existing conversation or starting a new one.

```APIDOC
## POST /api/conversations/response

### Description
Return a conversation response which continues the conversation based on the input message and deployment conversation id (if exists).

### Method
POST

### Endpoint
/api/conversations/response

### Parameters
#### Path Parameters
- **deployment_id** (str) - Required - The unique identifier to a deployment created under the project.
- **message** (str) - Required - A message from the user

#### Query Parameters
- **deployment_token** (str) - Required - A token used to authenticate access to deployments created in this project. This token is only authorized to predict on deployments in this project, so it is safe to embed this model inside of an application or website.
- **deployment_conversation_id** (str) - Optional - The unique identifier of a deployment conversation to continue. If not specified, a new one will be created.
- **external_session_id** (str) - Optional - The user supplied unique identifier of a deployment conversation to continue. If specified, we will use this instead of a internal deployment conversation id.
- **llm_name** (str) - Optional - Name of the specific LLM backend to use to power the chat experience
- **num_completion_tokens** (int) - Optional - Default for maximum number of tokens for chat answers
- **system_message** (str) - Optional - The system message to use for the chat.
- **temperature** (float) - Optional - The generative LLM temperature
- **filter_key_values** (dict) - Optional - A dictionary mapping column names to a list of values to restrict the retrieved search results.
- **search_score_cutoff** (float) - Optional - Cutoff for the document retriever score. Matching search results below this score will be ignored.
- **chat_config** (dict) - Optional - A dictionary specifying the query chat config override.
- **doc_infos** (list) - Optional - An optional list of documents use for the conversation. A keyword 'doc_id' is expected to be present in each document for retrieving contents from docstore.
- **user_info** (dict) - Optional - User information for the conversation.
- **execute_usercode_tool** (bool) - Optional - If True, will return the tool output in the response.

### Request Example
{
  "deployment_id": "your_deployment_id",
  "message": "Hello, how are you?",
  "deployment_token": "your_deployment_token",
  "deployment_conversation_id": "optional_conversation_id",
  "external_session_id": "optional_external_session_id",
  "llm_name": "optional_llm_name",
  "num_completion_tokens": 100,
  "system_message": "You are a helpful assistant.",
  "temperature": 0.7,
  "filter_key_values": {
    "category": ["news", "sports"]
  },
  "search_score_cutoff": 0.8,
  "chat_config": {
    "model": "gpt-4"
  },
  "doc_infos": [
    {"doc_id": "doc1", "content": "Document 1 content..."}
  ],
  "user_info": {
    "name": "John Doe"
  },
  "execute_usercode_tool": false
}

### Response
#### Success Response (200)
- **response** (str) - The conversation response from the model.
- **conversation_id** (str) - The ID of the conversation.
- **tool_output** (str) - The output of the executed tool, if applicable.

#### Response Example
{
  "response": "I am doing well, thank you for asking!",
  "conversation_id": "conv_abc123",
  "tool_output": null
}
```

--------------------------------

### Get Archive ID

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/api_client_utils/index.rst.txt

Static method to retrieve the archive ID from a document ID. No specific setup is required beyond having the document ID.

```python
get_archive_id(doc_id)
```

--------------------------------

### start_deployment

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Initiates a deployment process. This method is available via the ApiClient and its submodule.

```APIDOC
## start_deployment()

### Description
Starts a deployment. This is used to initiate the deployment of models or services.

### Method
(Implicitly a method call in Python SDK)

### Endpoint
(Not applicable for SDK method)

### Parameters
(Parameters are not detailed in the source, but would typically include deployment configuration)

### Request Example
(Not applicable for SDK method)

### Response
(Response details are not detailed in the source)
```

--------------------------------

### Enum Iteration and Length Example

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/api_class/enums/index.rst.txt

Demonstrates how to iterate over all members of an enumeration and get the total count of members. This is useful for processing all available enum options.

```python
>>> len(Color)
3

>>> list(Color)
[<Color.RED: 1>, <Color.BLUE: 2>, <Color.GREEN: 3>]
```

--------------------------------

### Initialize PredictionClient and Define Prompt Variables

Source: https://github.com/abacusai/api-python/blob/main/examples/language/helpers/prompting_iteration.ipynb

Initializes the PredictionClient and sets up variables for deployment tokens and behavior instructions. Ensure you fill in your specific behavior, data prompt, and response instructions.

```python
from abacusai import PredictionClient, ApiClient
client = PredictionClient()

deployment_token = ""
deployment_id = ""

behavior = """ FILL IN YOUR BEHAVIOR INSTRUCTIONS

"

data_prompt = """
FILL IN YOUR DATA PROMPT INSTRUCTIONS
"""

response_instructions = """
FILL IN YOUR RESPONSE INSTRUCTIONS
"""

```

--------------------------------

### abacusai.api_class.model.ThemeAnalysisTrainingConfig.__post_init__

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Initializes the configuration for Theme Analysis training.

```APIDOC
## abacusai.api_class.model.ThemeAnalysisTrainingConfig.__post_init__

### Description
Initializes the configuration object for Theme Analysis training. This method is part of the object's initialization process.

### Method
__post_init__ (internal method)

### Parameters
This method does not accept explicit user-provided parameters in its signature, but it processes initialization arguments passed during object creation.
```

--------------------------------

### Enum Attribute Access Example

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/api_class/enums/index.rst.txt

Demonstrates accessing an enum member using attribute access. This is a common way to get a specific enum value.

```python
>>> class Color(Enum):
...     RED = 1
...     BLUE = 2
...     GREEN = 3
...
>>> Color.RED
<Color.RED: 1>
```

--------------------------------

### GET /dataset_version/get_metrics

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/dataset_version/index.rst.txt

Get metrics for a specific dataset version.

```APIDOC
## GET /dataset_version/get_metrics

### Description
Get metrics for a specific dataset version.

### Method
GET

### Endpoint
/dataset_version/get_metrics

### Parameters
#### Query Parameters
- **dataset_version** (str) - Required - The unique identifier of the dataset version.
- **selected_columns** (List) - Optional - A list of columns to order first.
- **include_charts** (bool) - Optional - A flag indicating whether charts should be included in the response. Default is false.
- **include_statistics** (bool) - Optional - A flag indicating whether statistics should be included in the response. Default is true.

### Response
#### Success Response (200)
- **DataMetrics** (DataMetrics) - The metrics for the specified Dataset version.

#### Response Example
```json
{
  "metrics": {
    "column1": {"mean": 10.5, "stddev": 2.1},
    "column2": {"unique_count": 50}
  },
  "charts": []
}
```
```

--------------------------------

### ChatLLmComputer Class Initialization

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/chatllm_computer/index.rst.txt

Information on how to initialize the ChatLLmComputer class with various parameters.

```APIDOC
## ChatLLmComputer Class

### Description
Represents a ChatLLM Computer, allowing interaction with the service.

### Parameters
#### Initialization Parameters
- **client** (ApiClient) - Required - An authenticated API Client instance.
- **computerId** (int) - Optional - The computer id.
- **token** (str) - Optional - The token.
- **vncEndpoint** (str) - Optional - The VNC endpoint.

### Attributes
- **computer_id**: Stores the computer ID.
- **token**: Stores the authentication token.
- **vnc_endpoint**: Stores the VNC endpoint.
- **deprecated_keys**: List of deprecated keys.

### Methods
#### `__repr__()`
Returns a string representation of the object.

#### `to_dict()`
Get a dict representation of the parameters in this class.

- **Returns**: The dict value representation of the class parameters.
- **Return Type**: dict
```

--------------------------------

### abacusai.api_class.OptimizationTrainingConfig.__post_init__

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Initializes the configuration for Optimization training.

```APIDOC
## abacusai.api_class.OptimizationTrainingConfig.__post_init__

### Description
Initializes the configuration object for Optimization training. This method is part of the object's initialization process.

### Method
__post_init__ (internal method)

### Parameters
This method does not accept explicit user-provided parameters in its signature, but it processes initialization arguments passed during object creation.
```

--------------------------------

### Get Dictionary Representation

Source: https://github.com/abacusai/api-python/blob/main/docs/autoapi/abacusai/index.html

Gets a dictionary representation of the parameters in the GraphDashboard class.

```APIDOC
## to_dict Graph Dashboard

### Description
Gets a dict representation of the parameters in this class.

### Method
(Method not explicitly defined, likely internal to object)

### Endpoint
(Not applicable, operates on an object instance)

### Response
#### Success Response
- **The dict value representation of the class parameters** (dict)

### Response Example
{
  "example": "{\"name\": \"Example Dashboard\", \"graphDashboardId\": \"dsh_12345\", \"createdAt\": \"2023-10-27T10:00:00Z\", \"projectId\": \"proj_abcde\", \"pythonFunctionIds\": [\"func_1\", \"func_2\"], \"plotReferenceIds\": [\"plot_a\", \"plot_b\"], \"pythonFunctionNames\": [\"Function 1\", \"Function 2\"], \"projectName\": \"My Project\", \"description\": \"A sample dashboard\"}"
}
```

--------------------------------

### abacusai.api_class.NSamplingConfig.__post_init__

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Initializes the configuration for N-sampling.

```APIDOC
## abacusai.api_class.NSamplingConfig.__post_init__

### Description
Initializes the configuration object for N-sampling, a method for selecting data points. This method is part of the object's initialization process.

### Method
__post_init__ (internal method)

### Parameters
This method does not accept explicit user-provided parameters in its signature, but it processes initialization arguments passed during object creation.
```

--------------------------------

### Get Collinearity for Feature

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/client/index.rst.txt

Gets the collinearity for a specific feature from the Exploratory Data Analysis.

```APIDOC
## get_collinearity_for_feature

### Description
Gets the Collinearity for the given feature from the Exploratory Data Analysis.

### Method
Not specified (assumed to be a client library method call)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
* **eda_version** (str) - Required - Unique string identifier associated with the EDA instance.
* **feature_name** (str) - Optional - The name of the feature to get collinearity for.

### Returns
* Not specified in the source.
```

--------------------------------

### __post_init__

Source: https://github.com/abacusai/api-python/blob/main/docs/autoapi/abacusai/api_class/index.html

Post-initialization method for KafkaDatasetConfig, likely used for internal setup or validation.

```APIDOC
## __post_init__

### Description
Performs post-initialization tasks for KafkaDatasetConfig.
```

--------------------------------

### Get Document Retriever Deployment Status

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/document_retriever/index.rst.txt

Gets the deployment status of the document retriever.

```APIDOC
## GET /document_retrievers/{document_retriever_id}/deployment_status

### Description
Gets the deployment status of the document retriever.

### Method
GET

### Endpoint
/document_retrievers/{document_retriever_id}/deployment_status

### Parameters
#### Path Parameters
- **document_retriever_id** (str) - Required - A unique string identifier associated with the document retriever.

### Response
#### Success Response (200)
- **deployment_status** (str) - A string describing the deployment status of document retriever (pending, deploying, active, etc.).

#### Response Example
```json
{
  "deployment_status": "active"
}
```
```

--------------------------------

### Get EDA Collinearity

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/client/index.rst.txt

Gets the collinearity between all features for a given Exploratory Data Analysis version.

```APIDOC
## get_eda_collinearity

### Description
Gets the Collinearity between all features for the Exploratory Data Analysis.

### Method
Not specified (assumed to be a client library method call)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
* **eda_version** (str) - Required - Unique string identifier associated with the EDA instance.

### Returns
* **EdaCollinearity** - An object with a record of correlations between each feature for the EDA.
```

--------------------------------

### abacusai.api_class.PersonalizationTrainingConfig.__post_init__

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Initializes the configuration for Personalization training.

```APIDOC
## abacusai.api_class.PersonalizationTrainingConfig.__post_init__

### Description
Initializes the configuration object for Personalization training. This method is part of the object's initialization process.

### Method
__post_init__ (internal method)

### Parameters
This method does not accept explicit user-provided parameters in its signature, but it processes initialization arguments passed during object creation.
```

--------------------------------

### Install Abacus.AI Python Client

Source: https://github.com/abacusai/api-python/blob/main/README.md

Use pip to install the Abacus.AI Python API Client Library.

```console
$ pip install abacusai
```

--------------------------------

### Create and Configure Streaming Dataset for Event Logging

Source: https://github.com/abacusai/api-python/blob/main/featurestore.md

Set up a streaming dataset for logging events, configuring it with an update timestamp key and lookup keys. This is suitable for scenarios where data is appended as a log.

```python
streaming_dataset_user_activity = client.create_streaming_dataset(table_name='streaming_user_activity')
streaming_feature_group_user_activity = client.describe_feature_group_by_table_name(table_name='streaming_user_activity')
streaming_feature_group_user_activity.set_indexing_config(update_timestamp_key='event_timestamp', lookup_keys=['user_id'])
```

--------------------------------

### Get EDA Data Consistency

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/client/index.rst.txt

Gets the data consistency for an Exploratory Data Analysis version, optionally for a specific transformation feature.

```APIDOC
## get_eda_data_consistency

### Description
Gets the data consistency for the Exploratory Data Analysis.

### Method
Not specified (assumed to be a client library method call)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
* **eda_version** (str) - Required - Unique string identifier associated with the EDA instance.
* **transformation_feature** (str) - Optional - The transformation feature to get consistency for.

### Returns
* **EdaDataConsistency** - Object with duplication, deletion, and transformation data for data consistency analysis for an EDA.
```

--------------------------------

### abacusai.api_class.PercentSamplingConfig.__post_init__

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Initializes the configuration for Percent-sampling.

```APIDOC
## abacusai.api_class.PercentSamplingConfig.__post_init__

### Description
Initializes the configuration object for Percent-sampling, a method for selecting a percentage of data points. This method is part of the object's initialization process.

### Method
__post_init__ (internal method)

### Parameters
This method does not accept explicit user-provided parameters in its signature, but it processes initialization arguments passed during object creation.
```

--------------------------------

### HostedApp Methods

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/index.rst.txt

Documentation for the HostedApp class, including its initialization parameters.

```APIDOC
## HostedApp Class

### Initialization

- **Parameters**
  - `client` (ApiClient) - An authenticated API Client instance.
  - `hostedAppId` (id) - The ID of the hosted app.
  - `deploymentConversationId` (id) - The ID of the deployment conversation.
  - `name` (str) - The name of the hosted app.
  - `createdAt` (str) - The creation timestamp.
```

--------------------------------

### Get Model Monitor Summary from Organization

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/client/index.rst.txt

Gets a consolidated summary of model monitors for an organization, covering accuracy, bias, drift, and integrity.

```APIDOC
## get_model_monitor_summary_from_organization

### Description
Gets a consolidated summary of model monitors for an organization.

### Method
Not specified (assumed to be a client library method call)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Returns
* **list[ModelMonitorOrgSummary]** - A list of `ModelMonitorSummaryForOrganization` objects describing accuracy, bias, drift, and integrity for all model monitors in an organization.
```

--------------------------------

### Defining an Example Enumeration

Source: https://github.com/abacusai/api-python/blob/main/docs/autoapi/abacusai/api_class/enums/index.html

Shows how to define a basic enumeration with members and their associated values. This serves as a foundational example for creating custom enumerations.

```python
>>> class Color(Enum):
...     RED = 1
...     BLUE = 2
...     GREEN = 3
```

--------------------------------

### start

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/deployment/index.rst.txt

Restarts a specified deployment that was previously suspended. This action brings a stopped deployment back online.

```APIDOC
## start()

### Description
Restarts the specified deployment that was previously suspended.

### Method
(Not specified, likely a Python method call)

### Parameters
#### Path Parameters
(None specified)

#### Query Parameters
(None specified)

#### Request Body
(None specified)

### Parameters
- **deployment_id** (str) - Required - A unique string identifier associated with the deployment.
```

--------------------------------

### FileConnectorInstructions

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Provides instructions for configuring file connectors.

```APIDOC
## Class: FileConnectorInstructions

### Description
This class is related to instructions for file connectors within the AbacusAI system.

### Usage
Instantiate or use methods from this class to manage file connector configurations.
```

--------------------------------

### Get Document Retriever Status

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/document_retriever/index.rst.txt

Gets the status of the document retriever. It represents indexing status until indexing isn't complete, and deployment status after indexing is complete.

```APIDOC
## GET /document_retrievers/{document_retriever_id}/status

### Description
Gets the status of the document retriever. It represents indexing status until indexing isn't complete, and deployment status after indexing is complete.

### Method
GET

### Endpoint
/document_retrievers/{document_retriever_id}/status

### Parameters
#### Path Parameters
- **document_retriever_id** (str) - Required - A unique string identifier associated with the document retriever.

### Response
#### Success Response (200)
- **status** (str) - A string describing the status of a document retriever (pending, indexing, complete, active, etc.).

#### Response Example
```json
{
  "status": "active"
}
```
```

--------------------------------

### abacusai.api_class.NaturalLanguageSearchTrainingConfig.__post_init__

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Initializes the configuration for Natural Language Search training.

```APIDOC
## abacusai.api_class.NaturalLanguageSearchTrainingConfig.__post_init__

### Description
Initializes the configuration object for Natural Language Search training. This method is part of the object's initialization process.

### Method
__post_init__ (internal method)

### Parameters
This method does not accept explicit user-provided parameters in its signature, but it processes initialization arguments passed during object creation.
```

--------------------------------

### Dataset Configuration Methods

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Configuration classes for various data sources. Each class has a `__post_init__` method for initialization.

```APIDOC
## Dataset Configuration Classes

This section details the configuration classes for various data sources. Each class is used to configure how data from a specific source is ingested and processed.

### FreshserviceDatasetConfig

- **Description**: Configuration for Freshservice datasets.
- **Method**: `__post_init__`

### GoogleAnalyticsDatasetConfig

- **Description**: Configuration for Google Analytics datasets.
- **Method**: `__post_init__`

### GoogleDriveDatasetConfig

- **Description**: Configuration for Google Drive datasets.
- **Method**: `__post_init__`

### HubspotDatasetConfig

- **Description**: Configuration for Hubspot datasets.
- **Method**: `__post_init__`

### JiraDatasetConfig

- **Description**: Configuration for Jira datasets.
- **Method**: `__post_init__`

### OneDriveDatasetConfig

- **Description**: Configuration for OneDrive datasets.
- **Method**: `__post_init__`

### OutlookDatasetConfig

- **Description**: Configuration for Outlook datasets.
- **Method**: `__post_init__`

### QuickbooksDatasetConfig

- **Description**: Configuration for Quickbooks datasets.
- **Method**: `__post_init__`

### SftpDatasetConfig

- **Description**: Configuration for SFTP datasets.
- **Method**: `__post_init__`

### SharepointDatasetConfig

- **Description**: Configuration for Sharepoint datasets.
- **Method**: `__post_init__`

### TeamsScraperDatasetConfig

- **Description**: Configuration for Teams Scraper datasets.
- **Method**: `__post_init__`

### ZendeskDatasetConfig

- **Description**: Configuration for Zendesk datasets.
- **Method**: `__post_init__`
```

--------------------------------

### Get JSON Response from LLM

Source: https://github.com/abacusai/api-python/blob/main/examples/language/0.calling_large_language_models.ipynb

Specify `response_type='json'` and provide a `json_response_schema` to get structured JSON output from the LLM. The `json` library is used to parse the response content.

```python
import json

r = client.evaluate_prompt(prompt = "In this course, you will learn about car batteries, car doors, and car suspension system",
                           # system_message = "OPTIONAL, but good to have", 
                           llm_name = 'OPENAI_GPT4O',
                           response_type='json',
                           json_response_schema = {"learning_objectives": {"type": "list", "description": "A list of learning objectives", "is_required": True}})
learning_objectives = json.loads(r.content)
learning_objectives
```

--------------------------------

### Module Class Initialization

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/module/index.rst.txt

Information on how to initialize the Module class, including its parameters and their types.

```APIDOC
## Module Class

### Description
Represents a customer-created Python module within the AbacusAI platform.

### Parameters
#### Initialization Parameters
- **client** (ApiClient) - Required - An authenticated API Client instance.
- **name** (str) - Optional - The name to identify the algorithm. Only uppercase letters, numbers, and underscores are allowed.
- **createdAt** (str) - Optional - The date and time when the Python function was created, in ISO-8601 format.
- **notebookId** (str) - Optional - The unique string identifier of the notebook used to create or edit the module.
- **hideModuleCode** (bool) - Optional - Whether the module code is hidden from external users.
- **codeSource** (CodeSource) - Optional - Information about the source code of the Python function.

### Attributes
- **name** (any) - Value is None.
- **created_at** (any) - Value is None.
- **notebook_id** (any) - Value is None.
- **hide_module_code** (any) - Value is None.
- **code_source** (any)

### Methods
- **__repr__()**: Returns a string representation of the object.
- **to_dict()**: Get a dict representation of the parameters in this class.
  - **Returns**: The dict value representation of the class parameters.
  - **Return Type**: dict
```

--------------------------------

### describe_holdout_analysis

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/client/index.rst.txt

Get a holdout analysis.

```APIDOC
## describe_holdout_analysis

### Description
Get a holdout analysis.

### Method
Not specified (assumed to be a client library method call)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
* **holdout_analysis_id** (str) - Required - ID of the holdout analysis to get

### Returns
The holdout analysis
Type: HoldoutAnalysis
```

--------------------------------

### ModelVersion.get_training_logs

Source: https://github.com/abacusai/api-python/blob/main/docs/autoapi/abacusai/model_version/index.html

Returns training logs for the model. Parameters: stdout (bool): Set True to get info logs. stderr (bool): Set True to get error logs. Returns: A function logs object (FunctionLogs).

```APIDOC
## ModelVersion.get_training_logs

### Description
Returns training logs for the model.

### Parameters
#### Query Parameters
- **stdout** (bool) - Optional - Set True to get info logs.
- **stderr** (bool) - Optional - Set True to get error logs.

### Returns
- A function logs object (FunctionLogs)

```

--------------------------------

### FileConnectorInstructions Class

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/index.rst.txt

Provides instructions for authenticating with a cloud storage bucket. It includes verification status, write permissions, and a list of authentication options.

```APIDOC
## Class: FileConnectorInstructions

### Description
An object with a full description of the cloud storage bucket authentication options and bucket policy. Returns an error message if the parameters are invalid.

### Parameters
* **client**: An authenticated API Client instance.
* **verified** (bool): `True` if the bucket has passed verification.
* **writePermission** (bool): `True` if Abacus.AI has permission to write to this bucket.
* **authOptions** (list[dict]): A list of options for giving Abacus.AI access to this bucket.

### Attributes
* **verified** (bool): `True` if the bucket has passed verification.
* **write_permission** (bool): `True` if Abacus.AI has permission to write to this bucket.
* **auth_options** (list[dict]): A list of options for giving Abacus.AI access to this bucket.
* **deprecated_keys**: Deprecated keys associated with the file connector instructions.

### Methods
* **__repr__()**: Returns a string representation of the object.
* **to_dict()**: Get a dict representation of the parameters in this class.
  * Returns: The dict value representation of the class parameters (dict).
```

--------------------------------

### abacusai.FileConnectorInstructions

Source: https://github.com/abacusai/api-python/blob/main/docs/autoapi/abacusai/index.html

Provides instructions for authenticating and configuring cloud storage buckets, including verification status and permissions.

```APIDOC
## Class: abacusai.FileConnectorInstructions

### Description
An object with a full description of the cloud storage bucket authentication options and bucket policy. Returns an error message if the parameters are invalid.

### Parameters
*   **client** (_ApiClient_) – An authenticated API Client instance.
*   **verified** (_bool_, optional) – True if the bucket has passed verification. Defaults to None.
*   **writePermission** (_bool_, optional) – True if Abacus.AI has permission to write to this bucket. Defaults to None.
*   **authOptions** (_object_, optional) – Authentication options for the file connector. Defaults to None.

### Methods
*   **__repr__()**: Returns a string representation of the object.
*   **to_dict()**: Get a dict representation of the parameters in this class.
    *   Returns: The dict value representation of the class parameters.
    *   Return type: dict
```

--------------------------------

### DatasetVersion.get_status

Source: https://github.com/abacusai/api-python/blob/main/docs/autoapi/abacusai/index.html

Gets the status of the dataset version.

```APIDOC
## get_status

### Description
Gets the status of the dataset version.

### Returns
A string describing the status of a dataset version (importing, inspecting, complete, etc.).

### Return Type
[str](https://docs.python.org/3/library/stdtypes.html#str "in Python v3.14")
```

--------------------------------

### describe_holdout_analysis_version

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/client/index.rst.txt

Get a holdout analysis version.

```APIDOC
## describe_holdout_analysis_version

### Description
Get a holdout analysis version.

### Method
Not specified (assumed to be a client library method call)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
* **holdout_analysis_version** (str) - Required - ID of the holdout analysis version to get
* **get_metrics** (bool) - Optional - Whether to get the metrics for the holdout analysis version

### Returns
The holdout analysis version
Type: HoldoutAnalysisVersion
```

--------------------------------

### PercentSamplingConfig Initialization

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/index.rst.txt

Initializes a sampling configuration based on a percentage of rows.

```python
sample_percent: float
key_columns: List[str] = []
```

--------------------------------

### Model Training and Configuration Parameters

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/index.rst.txt

This section details the various parameters that can be configured when setting up a model for training within the AbacusAI framework. These parameters cover data preparation, model objectives, hyperparameter tuning, and advanced training options.

```APIDOC
## Model Training and Configuration Parameters

This section details the various parameters that can be configured when setting up a model for training within the AbacusAI framework. These parameters cover data preparation, model objectives, hyperparameter tuning, and advanced training options.

### Parameters

- **data_split_feature_group_table_name** (str) - Specify the table name of the feature group to export training data with the fold column.
- **custom_loss_functions** (List[str]) - Registered custom losses available for selection.
- **custom_metrics** (List[str]) - Registered custom metrics available for selection.
- **partial_dependence_analysis** (PartialDependenceAnalysis) - Specify whether to run partial dependence plots for all features or only some features.
- **do_masked_language_model_pretraining** (bool) - Specify whether to run a masked language model unsupervised pretraining step before supervized training in certain supported algorithms which use BERT-like backbones.
- **max_tokens_in_sentence** (int) - Specify the max tokens to be kept in a sentence based on the truncation strategy.
- **truncation_strategy** (str) - What strategy to use to deal with text rows with more than a given number of tokens (if num of tokens is more than "max_tokens_in_sentence").
- **objective** (abacusai.api_class.enums.RegressionObjective) - The objective for the regression model.
- **sort_objective** (abacusai.api_class.enums.RegressionObjective) - The objective to sort by.
- **tree_hpo_mode** (abacusai.api_class.enums.RegressionTreeHPOMode) - The mode for hyperparameter optimization of trees.
- **type_of_split** (abacusai.api_class.enums.RegressionTypeOfSplit) - The type of data split to use.
- **test_split** (int) - The percentage of data to use for testing.
- **disable_test_val_fold** (bool) - Whether to disable the test/validation fold.
- **k_fold_cross_validation** (bool) - Whether to enable k-fold cross-validation.
- **num_cv_folds** (int) - The number of folds for cross-validation.
- **timestamp_based_splitting_column** (str) - The column to use for timestamp-based splitting.
- **timestamp_based_splitting_method** (abacusai.api_class.enums.RegressionTimeSplitMethod) - The method for timestamp-based splitting.
- **test_splitting_timestamp** (str) - The timestamp to use for splitting test data.
- **sampling_unit_keys** (List[str]) - Keys to use for sampling units.
- **test_row_indicator** (str) - The column name that indicates test rows.
- **full_data_retraining** (bool) - Whether to retrain on the full dataset.
- **rebalance_classes** (bool) - Whether to rebalance classes.
- **rare_class_augmentation_threshold** (float) - The threshold for augmenting rare classes.
- **augmentation_strategy** (abacusai.api_class.enums.RegressionAugmentationStrategy) - The strategy for data augmentation.
- **training_rows_downsample_ratio** (float) - The ratio for downsampling training rows.
- **active_labels_column** (str) - The column containing active labels.
- **min_categorical_count** (int) - The minimum count for a categorical feature.
- **sample_weight** (str) - The column to use for sample weights.
- **numeric_clipping_percentile** (float) - The percentile for clipping numeric features.
- **target_transform** (abacusai.api_class.enums.RegressionTargetTransform) - The transformation to apply to the target variable.
- **ignore_datetime_features** (bool) - Whether to ignore datetime features.
- **max_text_words** (int) - The maximum number of words to consider in text features.
- **perform_feature_selection** (bool) - Whether to perform feature selection.
- **feature_selection_intensity** (int) - The intensity of feature selection.
- **batch_size** (abacusai.api_class.enums.BatchSize) - The batch size for training.
- **dropout_rate** (int) - The dropout rate for regularization.
- **pretrained_model_name** (str) - The name of a pre-trained model to use.
- **pretrained_llm_name** (str) - The name of a pre-trained large language model to use.
- **is_multilingual** (bool) - Whether the model should support multiple languages.
- **loss_function** (abacusai.api_class.enums.RegressionLossFunction) - The loss function to use for training.
- **loss_parameters** (str) - Parameters for the loss function.
- **target_encode_categoricals** (bool) - Whether to one-hot encode categorical target variables.
- **drop_original_categoricals** (bool) - Whether to drop original categorical columns after encoding.
```

--------------------------------

### PipelineVersion.get_status

Source: https://github.com/abacusai/api-python/blob/main/docs/autoapi/abacusai/pipeline_version/index.html

Gets the status of the pipeline version.

```APIDOC
## PipelineVersion.get_status

### Description
Gets the status of the pipeline version.

### Returns
A string describing the status of a pipeline version (pending, running, complete, etc.).

### Return Type
[str](https://docs.python.org/3/library/stdtypes.html#str "(in Python v3.14)")
```

--------------------------------

### summary_instructions

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Attribute representing summary instructions, found in VectorStoreConfig.

```APIDOC
## summary_instructions

### Description
Attribute that provides instructions for generating summaries, specifically within VectorStoreConfig.

### Method
Attribute access within the Python SDK.

### Endpoint
N/A (Python SDK attribute)

### Parameters
N/A
```

--------------------------------

### get_status()

Source: https://github.com/abacusai/api-python/blob/main/docs/autoapi/abacusai/agent/index.html

Gets the status of the agent publishing.

```APIDOC
## get_status()

### Description
Gets the status of the agent publishing.

### Returns
- A string describing the status of a agent publishing (pending, complete, etc.).

### Return Type
- str
```

--------------------------------

### abacusai.api_class.OptimizationPredictionArguments.__post_init__

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Initializes arguments for Optimization predictions.

```APIDOC
## abacusai.api_class.OptimizationPredictionArguments.__post_init__

### Description
Initializes the argument object for predictions related to optimization tasks. This method is part of the object's initialization process.

### Method
__post_init__ (internal method)

### Parameters
This method does not accept explicit user-provided parameters in its signature, but it processes initialization arguments passed during object creation.
```

--------------------------------

### list_refresh_policies

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/dataset/index.rst.txt

Gets the refresh policies in a list.

```APIDOC
## list_refresh_policies

### Description
Gets the refresh policies in a list.

### Method
GET

### Endpoint
/datasets/{dataset_id}/refresh_policies

### Response
#### Success Response (200)
- **refresh_policies** (List[RefreshPolicy]) - A list of refresh policy objects.

#### Response Example
{
  "refresh_policies": [
    {
      "cron": "0 0 * * *",
      "last_run": null
    }
  ]
}
```

--------------------------------

### execute_async_feature_group_operation

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/client/index.rst.txt

Starts the execution of fg operation.

```APIDOC
## execute_async_feature_group_operation

### Description
Starts the execution of fg operation.

### Method
Not specified (assumed to be a client library method call)

### Parameters
#### Query Parameters
* **query** (str) - Optional - The SQL to be executed.
* **fix_query_on_error** (bool) - Optional - If enabled, SQL query is auto fixed if parsing fails.
* **use_latest_version** (bool) - Optional - If enabled, executes the query on the latest version of the feature group, and if version doesn't exist, FailedDependencyError is sent. If disabled, query is executed considering the latest feature group state irrespective of the latest version of the feature group.

### Returns
A dict that contains the execution status.
```

--------------------------------

### DefaultLlm Class Initialization

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/default_llm/index.rst.txt

Information on how to initialize the DefaultLlm class.

```APIDOC
## DefaultLlm Class

### Description
A default LLM class that allows interaction with default Large Language Models.

### Method
Initialization

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
- **client** (ApiClient) - Required - An authenticated API Client instance.
- **name** (str) - Optional - The name of the LLM.
- **enum** (str) - Optional - The enum of the LLM.

### Request Example
```python
from abacusai import ApiClient
from abacusai.default_llm import DefaultLlm

client = ApiClient(api_key="YOUR_API_KEY")
llm = DefaultLlm(client=client, name="some-llm-name", enum="some-enum")
```

### Response
#### Success Response (200)
Initialization of the DefaultLlm object.

#### Response Example
```json
{
  "message": "DefaultLlm object initialized successfully"
}
```
```

--------------------------------

### start_deployment

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/client/index.rst.txt

Restarts the specified deployment that was previously suspended.

```APIDOC
## start_deployment

### Description
Restarts the specified deployment that was previously suspended.

### Method
Not specified (assumed to be a client method call)

### Parameters
#### Path Parameters
* **deployment_id** (str) - Required - A unique string identifier associated with the deployment.
```

--------------------------------

### DatasetVersion.get_metrics

Source: https://github.com/abacusai/api-python/blob/main/docs/autoapi/abacusai/index.html

Get metrics for a specific dataset version.

```APIDOC
## get_metrics

### Description
Get metrics for a specific dataset version.

### Parameters
#### Query Parameters
- **selected_columns** (List) - Optional - A list of columns to order first.
- **include_charts** (bool) - Optional - A flag indicating whether charts should be included in the response. Default is false.
- **include_statistics** (bool) - Optional - A flag indicating whether statistics should be included in the response. Default is true.

### Returns
The metrics for the specified Dataset version.

### Return Type
[DataMetrics](#abacusai.DataMetrics "abacusai.DataMetrics")
```

--------------------------------

### Pipeline Execution

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/pipeline/index.rst.txt

This section details how to run a pipeline with specified arguments.

```APIDOC
## POST /pipelines/{pipeline_id}/run

### Description
Runs a specified pipeline with the arguments provided.

### Method
POST

### Endpoint
/pipelines/{pipeline_id}/run

### Parameters
#### Path Parameters
- **pipeline_id** (str) - Required - The ID of the pipeline to run.

#### Request Body
- **pipeline_variable_mappings** (dict) - Optional - A dictionary of variable mappings for the pipeline run.

### Response
#### Success Response (200)
- **RunResponse** (object) - An object containing details about the pipeline run.

#### Response Example
```json
{
  "run_id": "example_run_id",
  "pipeline_id": "example_pipeline_id",
  "status": "RUNNING",
  "start_time": "2023-01-10T12:00:00Z"
}
```
```

--------------------------------

### abacusai.ApiClient.get_ranked_items

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Gets ranked items using the ApiClient.

```APIDOC
## abacusai.ApiClient.get_ranked_items

### Description
Retrieves ranked items.

### Method
Not specified (likely a Python method call).

### Endpoint
Not applicable (Python method).

### Parameters
*   **user_id** (string) - Required - The ID of the user.
*   **items** (list) - Required - A list of items to rank.
*   **num_recommendations** (int) - Optional - The number of recommendations to return.

### Request Example
```python
# Example usage (actual parameters may vary)
api_client.get_ranked_items(user_id='user_xyz', items=['item1', 'item2', 'item3'], num_recommendations=5)
```

### Response
*   **ranked_items** (list) - A list of ranked items.
```

--------------------------------

### PipelineStepVersion.get_step_version_logs

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/index.rst.txt

Gets the logs for a given step version.

```APIDOC
## PipelineStepVersion.get_step_version_logs

### Description
Retrieves the logs (stdout and stderr) for a specified pipeline step version.

### Method
N/A (Instance Method)

### Endpoint
N/A

### Parameters
#### Path Parameters
- **pipeline_step_version** (str) - Required - The ID of the pipeline step version for which to retrieve logs.

### Response
#### Success Response
- **PipelineStepVersionLogs**: An object containing the logs for the specified pipeline step version.
```

--------------------------------

### ThemeAnalysisTrainingConfig

Source: https://github.com/abacusai/api-python/blob/main/docs/genindex.html

Configuration for training a theme analysis model. The __post_init__ method is used for initialization.

```APIDOC
## abacusai.api_class.ThemeAnalysisTrainingConfig.__post_init__

### Description
Initializes the ThemeAnalysisTrainingConfig object.

### Method
__post_init__
```

--------------------------------

### HumeVoice Class Initialization

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/hume_voice/index.rst.txt

Information on how to initialize the HumeVoice class.

```APIDOC
## HumeVoice Class

### Description
Represents a Hume Voice, allowing interaction with voice-related API functionalities.

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Initialization
```python
HumeVoice(client, name=None, gender=None)
```

### Parameters
- **client** (ApiClient) - Required - An authenticated API Client instance.
- **name** (str) - Optional - The name of the voice.
- **gender** (str) - Optional - The gender of the voice.

### Methods
- **__repr__()**: Returns a string representation of the object.
- **to_dict()**: Get a dict representation of the parameters in this class.

### Attributes
- **name** (str): The name of the voice.
- **gender** (str): The gender of the voice.
- **deprecated_keys**: (list) A list of deprecated keys.

### Request Example
```json
{
  "client": "<authenticated_api_client_instance>",
  "name": "example_voice_name",
  "gender": "female"
}
```

### Response
#### Success Response (200)
This class does not have a direct success response as it's a client-side representation.

#### Response Example
```json
{
  "name": "example_voice_name",
  "gender": "female"
}
```
```

--------------------------------

### describe_async_feature_group_operation

Source: https://github.com/abacusai/api-python/blob/main/docs/_sources/autoapi/abacusai/client/index.rst.txt

Gets the status of the execution of fg operation.

```APIDOC
## describe_async_feature_group_operation

### Description
Gets the status of the execution of fg operation.

### Method
Not specified (assumed to be a client library method call)

### Parameters
#### Path Parameters
* **feature_group_operation_run_id** (str) - Required - The unique ID associated with the execution.

### Returns
A dict that contains the execution status.
```

--------------------------------

### RefreshPolicy.to_dict()

Source: https://github.com/abacusai/api-python/blob/main/docs/autoapi/abacusai/refresh_policy/index.html

Get a dict representation of the parameters in this class.

```APIDOC
## RefreshPolicy.to_dict()

### Description
Get a dict representation of the parameters in this class.

### Returns
The dict value representation of the class parameters.

### Return Type
dict
```

--------------------------------

### MonitorAlert.to_dict

Source: https://github.com/abacusai/api-python/blob/main/docs/autoapi/abacusai/monitor_alert/index.html

Gets a dictionary representation of the parameters in this class.

```APIDOC
## MonitorAlert.to_dict

### Description
Gets a dictionary representation of the parameters in this class.

### Method
To Dictionary

### Parameters
None

### Response
#### Success Response (200)
* **The dict value representation of the class parameters**

### Response Example
{
  "example": "dict representation"
}
```

--------------------------------

### start

Source: https://github.com/abacusai/api-python/blob/main/docs/autoapi/abacusai/index.html

Initiates a new batch prediction version job for a specified batch prediction.

```APIDOC
## start

### Description

Creates a new batch prediction version job for a given batch prediction job description.

### Method

POST (implied, as it creates a new resource/job)

### Endpoint

`/batch_predictions/{batch_prediction_id}/versions` (inferred path based on common REST practices and method description)

### Parameters

#### Path Parameters

- **batch_prediction_id** (string) - Required - The unique identifier of the batch prediction to create a new version of.

### Returns

#### Success Response

- **BatchPredictionVersion** - The batch prediction version started by this method call.

### Example

```python
# Assuming 'batch_prediction' is an instance of BatchPrediction
new_version = batch_prediction.start()
```
```