Helper components in NebulaAIFlow

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

Use a helper component in a flow

Chat memory in NebulaAIFlow is stored either in local NebulaAIFlow tables with LCBufferMemory, or connected to an external database.

The Store Message helper component stores chat memories as Data 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 component with Store Message and Chat Memory components.

Batch Run Component

The Batch Run component runs a language model over each row of a DataFrame text column and returns a new DataFrame with the original text and the model's response.

Inputs

Name	Display Name	Type	Info	Required
model	Language Model	HandleInput	Connect the 'Language Model' output from your LLM component here.	Yes
system_message	System Message	MultilineInput	Multi-line system instruction for all rows in the DataFrame.	No
df	DataFrame	DataFrameInput	The DataFrame whose column (specified by 'column_name') will be treated as text messages.	Yes
column_name	Column Name	StrInput	The name of the DataFrame column to treat as text messages. Default='text'.	Yes

Outputs

Name	Display Name	Method	Info
batch_results	Batch Results	run_batch	A DataFrame with two columns: 'text_input' and 'model_response'.

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 NebulaAIFlow pipeline.

Inputs

Name	Display Name	Info
timezone	Timezone	Select the timezone for the current date and time.

Outputs

Name	Display Name	Info
current_date	Current Date	The resulting current date and time in the selected timezone.

ID Generator

This component generates a unique ID.

Inputs

Name	Display Name	Info
unique_id	Value	The generated unique ID.

Outputs

Name	Display Name	Info
id	ID	The generated unique ID.

Message history

This component retrieves and manages chat messages from NebulaAIFlow tables or an external memory.

Inputs

Name	Display Name	Info
memory	External Memory	Retrieve messages from an external memory. If empty, it will use the NebulaAIFlow tables.
sender	Sender Type	Filter by sender type.
sender_name	Sender Name	Filter by sender name.
n_messages	Number of Messages	Number of messages to retrieve.
session_id	Session ID	The session ID of the chat. If empty, the current session ID parameter will be used.
order	Order	Order of the messages.
template	Template	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	Display Name	Info
messages	Messages (Data)	Retrieved messages as Data objects.
messages_text	Messages (Text)	Retrieved messages formatted as text.
lc_memory	Memory	A constructed Langchain ConversationBufferMemory object

Message store

This component stores chat messages or text into NebulaAIFlow tables or an external memory.

It provides flexibility in managing message storage and retrieval within a chat system.

Inputs

Name	Display Name	Info
message	Message	The chat message to be stored. (Required)
memory	External Memory	The external memory to store the message. If empty, it will use the NebulaAIFlow tables.
sender	Sender	The sender of the message. Can be Machine or User. If empty, the current sender parameter will be used.
sender_name	Sender Name	The name of the sender. Can be AI or User. If empty, the current sender parameter will be used.
session_id	Session ID	The session ID of the chat. If empty, the current session ID parameter will be used.

Outputs

Name	Display Name	Info
stored_messages	Stored Messages	The list of stored messages after the current message has been added.

Structured output

This component transforms LLM responses into structured data formats.

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

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 Parse DataFrame 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.

Inputs

Name	Display Name	Info
llm	Language Model	The language model to use to generate the structured output.
input_value	Input Message	The input message to the language model.
system_prompt	Format Instructions	Instructions to the language model for formatting the output.
schema_name	Schema Name	The name for the output data schema.
output_schema	Output Schema	Defines the structure and data types for the model's output.
multiple	Generate Multiple	[Deprecated] Always set to True.

Outputs

Name	Display Name	Info
structured_output	Structured Output	The structured output is a Data object based on the defined schema.
structured_output_dataframe	DataFrame	The structured output converted to a DataFrame format.