Utilities
Helper components provide utility functions to help manage data and perform simple tasks in your flow.
Calculator
The Calculator component performs basic arithmetic operations on mathematical expressions. It supports addition, subtraction, multiplication, division, and exponentiation operations.
For an example of using this component in a flow, see the Python Interpreter component.
Calculator parameters
| Name | Type | Description |
|---|---|---|
| expression | String | Input parameter. The arithmetic expression to evaluate, such as 4*4*(33/22)+12-20. |
| result | Data | Output parameter. The calculation result as a Data object containing the evaluated expression. |
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 a Robility flow pipeline.
Current Date parameters
| Name | Type | Description |
|---|---|---|
| timezone | String | Input parameter. The timezone for the current date and time. |
| current_date | String | Output parameter. The resulting current date and time in the selected timezone. |
Legacy Helper components
The following components are legacy components. You can use these components in your flows, but they are no longer maintained and may be removed in a future release. It is recommended that you replace legacy components with the recommended alternatives as soon as possible.
a. Chat History: Replaced by the Message History component
b. Message Store: Replaced by the Message History component
Create List
This component dynamically creates a record with a specified number of fields. It accepts the following parameters:
| Name | Type | Description |
|---|---|---|
| n_fields | Integer | Input parameter. The number of fields to be added to the record. |
| text_key | String | Input parameter. The key used as text. |
| list | List | Output parameter. The dynamically created list with the specified number of fields. |
ID Generator
This component generates a unique ID. It accepts the following parameters:
| Name | Type | Description |
|---|---|---|
| unique_id | String | Input parameter. The generated unique ID. |
| id | String | Output parameter. The generated unique ID. |
Output Parser
Replace the legacy Output Parser component with the Structured Output component and Parser component. The components you need depend on the data types and complexity of the parsing task.
The Output Parser component transforms the output of a language model into comma-separated values (CSV) format, such as [“item1”, “item2”, “item3”], using CommaSeparatedListOutputParser. The Structured Output component is a good alternative for this component because it also formats LLM responses with support for custom schemas and more complex parsing.
Parsing components only provide formatting instructions and parsing functionality. They don’t include prompts. You must connect parsers to Prompt Template components to create prompts that LLMs can use.
1. Open a flow that has a Chat Input, Language Model, and Chat Output components.
2. Add Output Parser and Prompt Template components to your flow.
3. Define your LLM’s prompt in the Prompt Template component’s Template, including all instructions and pre-loaded context. Make sure to include a {format_instructions} variable where you will inject the formatting instructions from the Output Parser component. For example:
You are a helpful assistant that provides lists of information.
Variables in the template dynamically add fields to the Prompt Template component so that your flow can receive definitions for those values from other components, Robility flow global variables, or fixed input.
4. Connect the Output Parser component’s output to the Prompt Template Component’s format instructions input.
The Output Parser component accepts the following parameters:
| Name | Type | Description |
|---|---|---|
| parser_type | String | Input parameter. Sets the parser type as "CSV". |
| format_instructions | String | Output parameter. Pass to a prompt template to include formatting instructions for LLM responses. |
| output_parser | Parser | Output parameter. The constructed output parser that can be used to parse LLM responses. |
