> ## Documentation Index
> Fetch the complete documentation index at: https://docs.llmcontrols.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Helper components in LLM Controls

Helper components provide utility functions to help manage data, tasks, and other components in your flow.

## **Use a helper component in a flow**[**​**](https://docs.langflow.org/components-helpers#use-a-helper-component-in-a-flow)

Chat memory in LLM Controls is stored either in local LLM Controls tables with `LCBufferMemory` or connected to an external database.

The **Store Message** helper component stores chat memories as [Data](/Concepts/LLMCobjects) objects, and the **Message History** helper component retrieves chat messages as data objects or strings.

This example flow stores and retrieves chat history from an [AstraDBChatMemory](https://docs.llmcontrols.ai/Components/Memories#astradbchatmemory-component%E2%80%8B) component with **Store Message** and **Chat Memory** components.

<img src="https://mintcdn.com/devrel/9PuWEwunOBJ8KxNm/images/helper_components.png?fit=max&auto=format&n=9PuWEwunOBJ8KxNm&q=85&s=d73a26fb749aab3338d4232bdee9ff6a" alt="Helper Components Pn" width="1091" height="644" data-path="images/helper_components.png" />

## **Batch Run**[**​**](https://docs.langflow.org/components-helpers#batch-run)

The **Batch Run** component runs a language model over **each row** of a [DataFrame](/Concepts/LLMCobjects) text column and returns a new DataFrame with the original text and an LLM response.

The response contains the following columns:

* `text_input`: The original text from the input DataFrame.
* `model_response`: The model's response for each input.
* `batch_index`: The processing order, with a `0`-based index.
* `metadata` (optional): Additional information about the processing.

These columns, when connected to a **Parser** component, can be used as variables within curly braces.

To use the Batch Run component with a **Parser** component, do the following:

1. Connect a **Model** component to the **Batch Run** component's **Language model** port.
2. Connect a component that outputs a DataFrame, like the **File** component, to the **Batch Run** component's **DataFrame** input.
3. Connect the **Batch Run** component's **Batch Results** output to a **Parser** component's **DataFrame** input. The flow looks like this:

<img src="https://mintcdn.com/devrel/3c4Ck_HlevcLlxoS/images/helper_component_2.png?fit=max&auto=format&n=3c4Ck_HlevcLlxoS&q=85&s=b0be236af9d4ddf00f41d734d69be423" alt="Helper Component 2 Pn" width="998" height="721" data-path="images/helper_component_2.png" />

4. In the **Column Name** field of the **Batch Run** component, enter a column name based on the data you're loading from the **File** loader. For example, to process a column of `names`, enter `name`.
5. Optionally, in the **System Message** field of the **Batch Run** component, enter a **System Message** to instruct the connected LLM on how to process your file. For example, `create a business card for each name.`
6. In the **Template** field of the **Parser** component, enter a template for using the **Batch Run** component's new DataFrame columns. To use all three columns from the **Batch Run** component, include them like this:
7. To run the flow, in the **Parser** component, click **Run component**.
8. To view your created DataFrame, in the **Parser** component, click.
9. Optionally, connect a **Chat Output** component, and open the **Playground** to see the output.

<Accordion title="Parameters">
  **Inputs**

  | **Name**             | **Type**         | **Description**                                                                                          |
  | :------------------- | :--------------- | :------------------------------------------------------------------------------------------------------- |
  | model                | HandleInput      | Connect the 'Language Model' output from your LLM component here. Required.                              |
  | system\_message      | MultilineInput   | A multi-line system instruction for all rows in the DataFrame.                                           |
  | df                   | DataFrameInput   | The DataFrame whose column is treated as text messages, as specified by 'column\_name'. Required.        |
  | column\_name         | MessageTextInput | The name of the DataFrame column to treat as text messages. If empty, all columns are formatted in TOML. |
  | output\_column\_name | MessageTextInput | Name of the column where the model's response is stored. Default=`model_response`.                       |
  | enable\_metadata     | BoolInput        | If True, add metadata to the output DataFrame.                                                           |

  **Outputs**

  | **Name**       | **Type**  | **Description**                                                         |
  | :------------- | :-------- | :---------------------------------------------------------------------- |
  | batch\_results | DataFrame | A DataFrame with all original columns plus the model's response column. |
</Accordion>

## **Current date**

The Current Date component returns the current date and time in a selected timezone. This component provides a flexible way to obtain timezone-specific date and time information within an LLM Controls pipeline.

<Accordion title="Parameters">
  **Inputs**

  | **Name** | **Type** | **Description**                             |
  | :------- | :------- | :------------------------------------------ |
  | timezone | String   | The timezone for the current date and time. |

  **Outputs**

  | **Name**      | **Type** | **Description**                                               |
  | :------------ | :------- | :------------------------------------------------------------ |
  | current\_date | String   | The resulting current date and time in the selected timezone. |
</Accordion>

## **ID Generator**

This component generates a unique ID.

<Accordion title="Parameters">
  **Inputs**

  | **Name**   | **Type** | **Description**          |
  | :--------- | :------- | :----------------------- |
  | unique\_id | String   | The generated unique ID. |

  **Outputs**

  | **Name** | **Type** | **Description**          |
  | :------- | :------- | :----------------------- |
  | id       | String   | The generated unique ID. |
</Accordion>

## **Message history**

<Note>
  **info**

  Before LLM Controls 1.1, this component was known as the Chat Memory component.
</Note>

This component retrieves chat messages from LLM Controls tables or external memory.

In this example, the **Message Store** component stores the complete chat history in a local LLM Controls table, which the **Message History** component retrieves as context for the LLM to answer each question.

<img src="https://mintcdn.com/devrel/3c4Ck_HlevcLlxoS/images/helper_component_3.png?fit=max&auto=format&n=3c4Ck_HlevcLlxoS&q=85&s=8545af9a6b5b2c8d9b5a53ddf00729f0" alt="Helper Component 3 Pn" width="753" height="655" data-path="images/helper_component_3.png" />

For more information on configuring memory in LLM Controls.

<Accordion title="Parameters">
  **Inputs**

  | **Name**     | **Type** | **Description**                                                                                                                 |
  | :----------- | :------- | :------------------------------------------------------------------------------------------------------------------------------ |
  | memory       | Memory   | Retrieve messages from an external memory. If empty, the LLM Controls tables are used.                                          |
  | sender       | String   | Filter by sender type.                                                                                                          |
  | sender\_name | String   | Filter by sender name.                                                                                                          |
  | n\_messages  | Integer  | The number of messages to retrieve.                                                                                             |
  | session\_id  | String   | The session ID of the chat. If empty, the current session ID parameter is used.                                                 |
  | order        | String   | The order of the messages.                                                                                                      |
  | template     | String   | The template to use for formatting the data. It can contain the keys `{text}`, `{sender}` or any other key in the message data. |

  **Outputs**

  | **Name**       | **Type**  | **Description**                           |
  | :------------- | :-------- | :---------------------------------------- |
  | messages       | Data      | The retrieved messages as Data objects.   |
  | messages\_text | Message   | The retrieved messages formatted as text. |
  | dataframe      | DataFrame | A DataFrame containing the message data.  |
</Accordion>

## **Message store**

This component stores chat messages or text in LLM Controls tables or external memory.

In this example, the **Message Store** component stores the complete chat history in a local LLM Controls table, which the **Message History** component retrieves as context for the LLM to answer each question.

<img src="https://mintcdn.com/devrel/3c4Ck_HlevcLlxoS/images/helper_component_4.png?fit=max&auto=format&n=3c4Ck_HlevcLlxoS&q=85&s=cd553663db346f73ab90887d25ff1088" alt="Helper Component 4 Pn" width="692" height="594" data-path="images/helper_component_4.png" />

For more information on configuring memory in LLM Controls.

<Accordion title="Parameters">
  **Inputs**

  | **Name**     | **Type** | **Description**                                                                                    |
  | :----------- | :------- | :------------------------------------------------------------------------------------------------- |
  | message      | String   | The chat message to be stored. (Required)                                                          |
  | memory       | Memory   | The external memory to store the message. If empty, the LLM Controls tables are used.              |
  | sender       | String   | The sender of the message. Can be Machine or User. If empty, the current sender parameter is used. |
  | sender\_name | String   | The name of the sender. Can be AI or User. If empty, the current sender parameter is used.         |
  | session\_id  | String   | The session ID of the chat. If empty, the current session ID parameter is used.                    |

  **Outputs**

  | **Name**         | **Type**    | **Description**                                                       |
  | :--------------- | :---------- | :-------------------------------------------------------------------- |
  | stored\_messages | List\[Data] | The list of stored messages after the current message has been added. |
</Accordion>

## **Structured output**

This component transforms LLM responses into structured data formats.

In this example from the **Financial Report Parser** template, the **Structured Output** component transforms unstructured financial reports into structured data.

<img src="https://mintcdn.com/devrel/3c4Ck_HlevcLlxoS/images/helper_component_5.png?fit=max&auto=format&n=3c4Ck_HlevcLlxoS&q=85&s=9e9cd45855e32756c70247c8020798be" alt="Helper Component 5 Pn" width="1062" height="715" data-path="images/helper_component_5.png" />

The connected LLM model is prompted by the **Structured Output** component's `Format Instructions` parameter to extract structured output from the unstructured text. `Format Instructions` is utilized as the system prompt for the **Structured Output** component.

In the **Structured Output** component, click the **Open table** button to view the `Output Schema` table. The `Output Schema` parameter defines the structure and data types for the model's output using a table with the following fields:

* **Name**: The name of the output field.
* **Description**: The purpose of the output field.
* **Type**: The data type of the output field. The available types are `str`, `int`, `float`, `bool`, `list`, or `dict`. The default is `text`.
* **Multiple**: This feature is deprecated. Currently, it is set to `True` by default if you expect multiple values for a single field. For example, a `list` of `features` is set to `True` to contain multiple values, such as `["waterproof", "durable", "lightweight"]`. Default: `True`.

The **Parser** component parses the structured output into a template for orderly presentation in chat output. The template receives the values from the `output_schema` table with curly braces.

For example, the template `EBITDA: {EBITDA}, Net Income: {NET_INCOME}, GROSS_PROFIT: {GROSS_PROFIT}` presents the extracted values in the **Playground** as `EBITDA: 900 million, Net Income: 500 million, GROSS_PROFIT: 1.2 billion`.

<Accordion title="Parameters">
  **Inputs**

  | **Name**       | **Type**      | **Description**                                                   |
  | :------------- | :------------ | :---------------------------------------------------------------- |
  | llm            | LanguageModel | The language model to use to generate the structured output.      |
  | input\_value   | String        | The input message to the language model.                          |
  | system\_prompt | String        | The instructions to the language model for formatting the output. |
  | schema\_name   | String        | The name for the output data schema.                              |
  | output\_schema | Table         | The structure and data types for the model's output.              |
  | multiple       | Boolean       | \[Deprecated] Always set to `True`.                               |

  **Outputs**

  | **Name**           | **Type** | **Description**                                                     |
  | :----------------- | :------- | :------------------------------------------------------------------ |
  | structured\_output | Data     | The structured output is a Data object based on the defined schema. |
</Accordion>