Data components in Langflow

Data components load data from a source into your flow.

They may perform some processing or type checking, like converting raw HTML data into text, or ensuring your loaded file is of an acceptable type.

Use a data component in a flow

The URL data component loads content from a list of URLs.

In the component's URLs field, enter a comma-separated list of URLs you want to load. Alternatively, connect a component that outputs the Message type, like the Chat Input component, to supply your URLs with a component.

To output a Data type, in the Output Format dropdown, select Raw HTML. To output a Message type, in the Output Format dropdown, select Text. This option applies postprocessing with the data_to_text helper function.

In this example of a document ingestion pipeline, the URL component outputs raw HTML to a text splitter, which splits the raw content into chunks for a vector database to ingest.

API Request

This component makes HTTP requests using URLs or cURL commands.

1. To use this component in a flow, connect the Data output to a component that accepts the input. For example, connect the API Request component to a Chat Output component.

2. In the API component's URLs field, enter the endpoint for your request. This example uses https://dummy-json.mock.beeceptor.com/posts, which is a list of technology blog posts.

3. In the Method field, enter the type of request. This example uses GET to retrieve a list of blog posts. The component also supports POST, PATCH, PUT, and DELETE.

4. Optionally, enable the Use cURL button to create a field for pasting curl requests. The equivalent call in this example is curl -v https://dummy-json.mock.beeceptor.com/posts.

5. Click Playground, and then click Run Flow. Your request returns a list of blog posts in the result field.

Filter API request data

The API Request component retrieved a list of JSON objects in the result field. For this example, you will use the Lambda Filter to extract the desired data nested within the result field.

1. Connect a Lambda Filter to the API request component, and a Language model to the Lambda Filter. This example connects a Groq model component.
2. In the Groq model component, add your Groq API key.
3. To filter the data, in the Lambda filter component, in the Instructions field, use natural language to describe how the data should be filtered. For this example, enter:

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I want to explode the result column out into a Data object

tip

Avoid punctuation in the Instructions field, as it can cause errors.

4. To run the flow, in the Lambda Filter component, click .
5. To inspect the filtered data, in the Lambda Filter component, click . The result is a structured DataFrame.

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| userId | id | title | body | link | comment_count |

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|---|----|-------|------|------|---------------|

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| 1 | 1 | Introduction to Artificial Intelligence | Learn the basics of AI ...| https://example.com/article1 | 8 |

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| 2 | 2 | Web Development with React | Build modern web applications ...| https://example.com/article2 | 12 |

Inputs

Name	Display Name	Info
urls	URLs	Enter one or more URLs, separated by commas.
curl	cURL	Paste a curl command to populate the dictionary fields for headers and body.
method	Method	The HTTP method to use.
use_curl	Use cURL	Enable cURL mode to populate fields from a cURL command.
query_params	Query Parameters	The query parameters to append to the URL.
body	Body	The body to send with the request as a dictionary (for POST, PATCH, PUT).
headers	Headers	The headers to send with the request as a dictionary.
timeout	Timeout	The timeout to use for the request.
follow_redirects	Follow Redirects	Whether to follow http redirects.
save_to_file	Save to File	Save the API response to a temporary file
include_httpx_metadata	Include HTTPx Metadata	Include properties such as headers, status_code, response_headers, and redirection_history in the output.

Outputs

Name	Display Name	Info
data	Data	The result of the API requests. Returns a Data object containing source URL and results.
dataframe	DataFrame	Converts the API response data into a tabular DataFrame format.

Directory

This component recursively loads files from a directory, with options for file types, depth, and concurrency.

Inputs

Input	Type	Description
path	MessageTextInput	Path to the directory to load files from
types	MessageTextInput	File types to load (leave empty to load all types)
depth	IntInput	Depth to search for files
max_concurrency	IntInput	Maximum concurrency for loading files
load_hidden	BoolInput	If true, hidden files are loaded
recursive	BoolInput	If true, the search is recursive
silent_errors	BoolInput	If true, errors do not raise an exception
use_multithreading	BoolInput	If true, multithreading is used

Outputs

Output	Type	Description
data	List[Data]	Loaded file data from the directory

File

This component loads and parses files of various supported formats and converts the content into a Data object. It supports multiple file types and provides options for parallel processing and error handling.

To load a document, follow these steps:

1. Click the Select files button.
2. Select a local file or a file loaded with File management, and then click Select file.

The loaded file name appears in the component.

The default maximum supported file size is 100 MB. To modify this value, see --max-file-size-upload.

Inputs

Name	Display Name	Info
path	Files	Path to file(s) to load. Supports individual files or bundled archives.
file_path	Server File Path	Data object with a file_path property pointing to the server file or a Message object with a path to the file. Supersedes 'Path' but supports the same file types.
separator	Separator	Specify the separator to use between multiple outputs in Message format.
silent_errors	Silent Errors	If true, errors do not raise an exception.
delete_server_file_after_processing	Delete Server File After Processing	If true, the Server File Path is deleted after processing.
ignore_unsupported_extensions	Ignore Unsupported Extensions	If true, files with unsupported extensions are not processed.
ignore_unspecified_files	Ignore Unspecified Files	If true, Data with no file_path property is ignored.
use_multithreading	[Deprecated] Use Multithreading	Set 'Processing Concurrency' greater than 1 to enable multithreading. This option is deprecated.
concurrency_multithreading	Processing Concurrency	When multiple files are being processed, the number of files to process concurrently. Default is 1. Values greater than 1 enable parallel processing for 2 or more files.

Outputs

Name	Display Name	Info
data	Data	Parsed content of the file as a Data object.
dataframe	DataFrame	File content as a DataFrame object.
message	Message	File content as a Message object.

Supported File Types

Text files:

• .txt - Text files
• .md, .mdx - Markdown files
• .csv - CSV files
• .json - JSON files
• .yaml, .yml - YAML files
• .xml - XML files
• .html, .htm - HTML files
• .pdf - PDF files
• .docx - Word documents
• .py - Python files
• .sh - Shell scripts
• .sql - SQL files
• .js - JavaScript files
• .ts, .tsx - TypeScript files

Archive formats (for bundling multiple files):

• .zip - ZIP archives
• .tar - TAR archives
• .tgz - Gzipped TAR archives
• .bz2 - Bzip2 compressed files
• .gz - Gzip compressed files

Gmail Loader

info

Google components are available in the Components menu under Bundles. For more information, see Integrate Google OAuth with Langflow.

This component loads emails from Gmail using provided credentials and filters.

For more on creating a service account JSON, see Service Account JSON.

Inputs

Input	Type	Description
json_string	SecretStrInput	JSON string containing OAuth 2.0 access token information for service account access
label_ids	MessageTextInput	Comma-separated list of label IDs to filter emails
max_results	MessageTextInput	Maximum number of emails to load

Outputs

Output	Type	Description
data	Data	Loaded email data

Google Drive Loader

info

Google components are available in the Components menu under Bundles. For more information, see Integrate Google OAuth with Langflow.

This component loads documents from Google Drive using provided credentials and a single document ID.

For more on creating a service account JSON, see Service Account JSON.

Inputs

Input	Type	Description
json_string	SecretStrInput	JSON string containing OAuth 2.0 access token information for service account access
document_id	MessageTextInput	Single Google Drive document ID

Outputs

Output	Type	Description
docs	Data	Loaded document data

Google Drive Search

info

Google components are available in the Components menu under Bundles. For more information, see Integrate Google OAuth with Langflow.

This component searches Google Drive files using provided credentials and query parameters.

For more on creating a service account JSON, see Service Account JSON.

Inputs

Input	Type	Description
token_string	SecretStrInput	JSON string containing OAuth 2.0 access token information for service account access
query_item	DropdownInput	The field to query
valid_operator	DropdownInput	Operator to use in the query
search_term	MessageTextInput	The value to search for in the specified query item
query_string	MessageTextInput	The query string used for searching (can be edited manually)

Outputs

Output	Type	Description
doc_urls	List[str]	URLs of the found documents
doc_ids	List[str]	IDs of the found documents
doc_titles	List[str]	Titles of the found documents
Data	Data	Document titles and URLs in a structured format

SQL Query

This component executes SQL queries on a specified database.

Inputs

Name	Display Name	Info
query	Query	The SQL query to execute.
database_url	Database URL	The URL of the database.
include_columns	Include Columns	Include columns in the result.
passthrough	Passthrough	If an error occurs, return the query instead of raising an exception.
add_error	Add Error	Add the error to the result.

Outputs

Name	Display Name	Info
result	Result	The result of the SQL query execution.

URL

This component fetches content from one or more URLs, processes the content, and returns it in various formats. It supports output in plain text, raw HTML, or JSON, with options for cleaning and separating multiple outputs.

1. To use this component in a flow, connect the DataFrame output to a component that accepts the input. For example, connect the URL component to a Chat Output component.

2. In the URL component's URLs field, enter the URL for your request. This example uses langflow.org.

3. Optionally, in the Max Depth field, enter how many pages away from the initial URL you want to crawl. Select 1 to crawl only the page specified in the URLs field. Select 2 to crawl all pages linked from that page. The component crawls by link traversal, not by URL path depth.

4. Click Playground, and then click Run Flow. The text contents of the URL are returned to the Playground as a structured DataFrame.

5. In the URL component, change the output port to Message, and then run the flow again. The text contents of the URL are returned as unstructured raw text, which you can extract patterns from with the Regex Extractor tool.

6. Connect the URL component to a Regex Extractor and Chat Output.

7. In the Regex Extractor tool, enter a pattern to extract text from the URL component's raw output. This example extracts the first paragraph from the "In the News" section of https://en.wikipedia.org/wiki/Main_Page.

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In the news\s*\n(.*?)(?=\n\n)

Result:

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Peruvian writer and Nobel Prize in Literature laureate Mario Vargas Llosa (pictured) dies at the age of 89.

Inputs

Name	Display Name	Info
urls	URLs	Enter one or more URLs. URLs are automatically validated and cleaned.
format	Output Format	Output Format. Use Text to extract text from the HTML, Raw HTML for the raw HTML content, or JSON to extract JSON from the HTML.
separator	Separator	Specify the separator to use between multiple outputs. Default for Text is \n\n. Default for Raw HTML is \n<!-- Separator -->\n.
clean_extra_whitespace	Clean Extra Whitespace	Whether to clean excessive blank lines in the text output. Only applies to Text format.

Outputs

Name	Display Name	Info
data	Data	List of Data objects containing fetched content and metadata.
text	Text	Fetched content as formatted text, with applied separators and cleaning.
dataframe	DataFrame	Content formatted as a DataFrame object.

Webhook

This component defines a webhook trigger that runs a flow when it receives an HTTP POST request.

If the input is not valid JSON, the component wraps it in a payload object so that it can be processed and still trigger the flow. The component does not require an API key.

When a Webhook component is added to the workspace, a new Webhook cURL tab becomes available in the API pane that contains an HTTP POST request for triggering the webhook component. For example:

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curl -X POST \

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"http://127.0.0.1:7860/api/v1/webhook/**YOUR_FLOW_ID**" \

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-H 'Content-Type: application/json'\

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-d '{"any": "data"}'

To test the webhook component:

1. Add a Webhook component to the flow.
2. Connect the Webhook component's Data output to the Data input of a Parser component.
3. Connect the Parser component's Parsed Text output to the Text input of a Chat Output component.
4. In the Parser component, under Mode, select Stringify. This mode passes the webhook's data as a string for the Chat Output component to print.
5. To send a POST request, copy the code from the Webhook cURL tab in the API pane and paste it into a terminal.
6. Send the POST request.
7. Open the Playground. Your JSON data is posted to the Chat Output component, which indicates that the webhook component is correctly triggering the flow.

Inputs

Name	Display Name	Description
data	Payload	Receives a payload from external systems through HTTP POST requests.
curl	cURL	The cURL command template for making requests to this webhook.
endpoint	Endpoint	The endpoint URL where this webhook receives requests.

Outputs

Name	Display Name	Description
output_data	Data	Outputs processed data from the webhook input, and returns an empty Data object if no input is provided. If the input is not valid JSON, the component wraps it in a payload object.