Logic components in Langflow

Logic components provide functionalities for routing, conditional processing, and flow management.

Use a logic component in a flow

This flow creates a summarizing "for each" loop with the Loop component.

The component iterates over a list of Data objects until it's completed, and then the Done loop aggregates the results.

The File component loads text files from your local machine, and then the Parser component parses them into a list of structured Data objects. The Loop component passes each Data object to a Prompt to be summarized.

When the Loop component runs out of Data, the Done loop activates, which counts the number of pages and summarizes their tone with another Prompt. This is represented in Langflow by connecting the Parser component's Data List output to the Loop component's Data loop input.

The output is similar to this:

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Document Summary

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Total Pages Processed

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Total Pages: 2

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Overall Tone of Document

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Tone: Informative and Instructional

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The documentation outlines microservices architecture patterns and best practices.

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It emphasizes service isolation and inter-service communication protocols.

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The use of asynchronous messaging patterns is recommended for system scalability.

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It includes code examples of REST and gRPC implementations to demonstrate integration approaches.

Conditional router (If-Else component)

This component routes messages by comparing two strings. It evaluates a condition by comparing two text inputs using the specified operator and routes the message to true_result or false_result.

The operator looks for single strings based on your defined operator behavior, but it can also search for multiple words by regex matching.

To use the Conditional router component to check incoming messages with regex matching, do the following:

1. Connect the If-Else component's Text Input port to a Chat Input component.
2. In the If-Else component, enter the following values.

• In the Match Text field, enter .*(urgent|warning|caution).*. The component looks for these values. The regex match is case sensitive, so to look for all permutations of warning, enter warning|Warning|WARNING.
• In the Operator field, enter regex. The component looks for the strings urgent, warning, and caution. For more operators, see Operator behavior.
• In the Message field, enter New Message Detected. This field is optional. The message is sent to both the True and False ports. The component is now set up to send a New Message Detected message out of its True port if it matches any of the strings. If no strings are detected, it sends a message out of the False port.

3. Create two identical flows to process the messages. Connect an Open AI component, a Prompt, and a Chat Output component together.
4. Connect one chain to the If-Else component's True port, and one chain to the False port.

The flow looks like this:

5. Add your OpenAI API key to both OpenAI components.
6. In both Prompt components, enter the behavior you want each route to take. When a match is found:

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Send a message that a new message has been received and added to the Urgent queue.

When a match is not found:

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Send a message that a new message has been received and added to the backlog.

7. Open the Playground.
8. Send the flow some messages. Your messages route differently based on the if-else component's evaluation.

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User

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A new user was created.

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AI

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A new message has been received and added to the backlog.

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User

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Sign-in warning: new user locked out.

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AI

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A new message has been received and added to the Urgent queue. Please review it at your earliest convenience.

Parameters

Inputs

Name	Type	Description
input_text	String	The primary text input for the operation.
match_text	String	The text to compare against.
operator	Dropdown	The operator used to compare texts. Options include equals, not equals, contains, starts with, ends with, and regex. The default is equals.
case_sensitive	Boolean	When set to true, the comparison is case sensitive. This setting does not apply to regex comparison. The default is false.
message	Message	The message to pass through either route.
max_iterations	Integer	The maximum number of iterations allowed for the conditional router. The default is 10.
default_route	Dropdown	The route to take when max iterations are reached. Options include true_result or false_result. The default is false_result.

Outputs

Name	Type	Description
true_result	Message	The output produced when the condition is true.
false_result	Message	The output produced when the condition is false.

Operator Behavior

The If-else component includes a comparison operator to compare the values in input_text and match_text.

All options respect the case_sensitive setting except regex.

• equals: Exact match comparison.
• not equals: Inverse of exact match.
• contains: Checks if match_text is found within input_text.
• starts with: Checks if input_text begins with match_text.
• ends with: Checks if input_text ends with match_text.
• regex: Performs regular expression matching. It is always case sensitive and ignores the case_sensitive setting.

Listen

This component listens for a notification and retrieves its associated state.

Parameters

Inputs

Name	Type	Description
name	String	The name of the notification to listen for.

Outputs

Name	Type	Description
output	Data	The state associated with the notification.

Loop

tip

For another Loop component example, see the Research Translation Loop template.

This component iterates over a list of Data objects, outputting one item at a time and aggregating results from loop inputs.

In this example, the Loop component iterates over a CSV file through the Item port until there are no rows left to process. Then, the Loop component performs the actions connected to the Done port, which in this case is loading the structured data into Chroma DB.

Think of it this way: the Item port forms the "main" loop that repeats until a "complete" condition is reached.

1. The Loop component accepts Data from the Load CSV component, and outputs the data from the Item port.
2. Each CSV row is converted to a Message and processed into structured data with the Structured Output component. The dotted line connected from the Structured Output component's Looping port tells you where the loop begins again.
3. The Loop component repeatedly extracts rows by Text Key until there are no more rows to extract.

Once all items are processed, the action connected to the Done port is performed. In this example, the data is loaded into Chroma DB.

Follow along with this step-by-step video guide for creating this flow and adding agentic RAG: Mastering the Loop Component & Agentic RAG in Langflow.

Parameters

Inputs

Name	Type	Description
data	Data/List	The initial list of Data objects to process.

Outputs

Name	Type	Description
item	Data	The current item being processed from the data list.
done	Data	The aggregated results after all items are processed.

Notify

This component generates a notification for the Listen component to use.

Parameters

Inputs

Name	Type	Description
name	String	The name of the notification.
data	Data	The data to store in the notification.
append	Boolean	When set to true, the record is added to the existing notification.

Outputs

Name	Type	Description
output	Data	The data stored in the notification.

Pass

This component forwards the input message, unchanged.

Parameters

Inputs

Name	Display Name	Info
input_message	Input Message	The message to forward.
ignored_message	Ignored Message	A second message that is ignored. Used as a workaround for continuity.

Outputs

Name	Display Name	Info
output_message	Output Message	The forwarded message from the input.

Run flow

This component allows you to run any flow stored in your Langflow database without opening the flow editor.

The Run Flow component can also be used as a tool when connected to an Agent. The name and description metadata that the Agent uses to register the tool are created automatically.

When you select a flow, the component fetches the flow's graph structure and uses it to generate the inputs and outputs for the Run Flow component.

To use the Run Flow component as a tool, do the following:

1. Add the Run Flow component to the Simple Agent flow.
2. In the Flow Name menu, select the sub-flow you want to run. The appearance of the Run Flow component changes to reflect the inputs and outputs of the selected flow.
3. On the Run Flow component, enable Tool Mode.
4. Connect the Run Flow component to the Toolset input of the Agent. Your flow should now look like this:
5. Run the flow. The Agent uses the Run Flow component as a tool to run the selected sub-flow.

Parameters

Inputs

Name	Type	Description
flow_name_selected	Dropdown	The name of the flow to run.
flow_tweak_data	Dict	Dictionary of tweaks to customize the flow's behavior.
dynamic inputs	Various	Additional inputs that are generated based on the selected flow.

Outputs

Name	Type	Description
run_outputs	A List of types Data, Message, or DataFrame	All outputs are generated from running the flow.

Legacy components

Legacy components are available for use but are no longer supported.

Data Conditional Router

important

This component is in Legacy, which means it is no longer in active development as of Langflow version 1.3.

This component routes Data objects based on a condition applied to a specified key, including boolean validation. It can process either a single Data object or a list of Data objects.

This component is particularly useful in workflows that require conditional routing of complex data structures, enabling dynamic decision-making based on data content.

Inputs

Name	Type	Description
data_input	Data	The Data object or list of Data objects to process. This input can handle both single items and lists.
key_name	String	The name of the key in the Data object to check.
operator	Dropdown	The operator to apply. Options: "equals", "not equals", "contains", "starts with", "ends with", "boolean validator". Default: "equals".
compare_value	String	The value to compare against. Not shown/used when operator is "boolean validator".

Outputs

Name	Type	Description
true_output	Data/List	Output when the condition is met.
false_output	Data/List	Output when the condition is not met.

Operator behavior

• equals: Exact match comparison between the key's value and compare_value.
• not equals: Inverse of exact match.
• contains: Checks if compare_value is found within the key's value.
• starts with: Checks if the key's value begins with compare_value.
• ends with: Checks if the key's value ends with compare_value.
• boolean validator: Treats the key's value as a boolean. The following values are considered true:
  • Boolean true.
  • Strings: "true", "1", "yes", "y", "on" (case-insensitive).
  • Any other value is converted using Python's bool() function.

List processing

The following actions occur when processing a list of Data objects:

• Each object in the list is evaluated individually
• Objects meeting the condition go to true_output
• Objects not meeting the condition go to false_output
• If all objects go to one output, the other output is empty

Deprecated components

Deprecated components have been replaced by newer alternatives and should not be used in new projects.

Flow as tool

important

This component is deprecated as of Langflow version 1.1.2. Instead, use the Run flow component

This component constructs a tool from a function that runs a loaded flow.

Inputs

Name	Type	Description
flow_name	Dropdown	The name of the flow to run.
tool_name	String	The name of the tool.
tool_description	String	The description of the tool.
return_direct	Boolean	If true, returns the result directly from the tool.

Outputs

Name	Type	Description
api_build_tool	Tool	The constructed tool from the flow.

Sub flow

important

This component is deprecated as of Langflow version 1.1.2. Instead, use the Run flow component

This SubFlowComponent generates a component from a flow with all of its inputs and outputs.

This component can integrate entire flows as components within a larger workflow. It dynamically generates inputs based on the selected flow and executes the flow with provided parameters.

Inputs

Name	Type	Description
flow_name	Dropdown	The name of the flow to run.

Outputs

Name	Type	Description
flow_outputs	List[Data]	The outputs generated from the flow.