# nodes

node_type: zoom
package_name: n8n-nodes-base
display_name: Zoom
description: Consume Zoom API
category: input
development_style: programmatic
version: 1
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Zoom node documentation
  description: Learn how to use the Zoom node in n8n. Follow technical documentation to integrate Zoom node into your workflows.
  contentType: [integration, reference]
  ---

  # Zoom node

  Use the Zoom node to automate work in Zoom, and integrate Zoom with other applications. n8n has built-in support for a wide range of Zoom features, including creating, retrieving, deleting, and updating meetings. 

  On this page, you'll find a list of operations the Zoom node supports and links to more resources.

  /// note | Credentials
  Refer to [Zoom credentials](/integrations/builtin/credentials/zoom.md) for guidance on setting up authentication. 
  ///

  --8<-- "_snippets/integrations/builtin/app-nodes/ai-tools.md"

  ## Operations

  * Meeting
      * Create a meeting
      * Delete a meeting
      * Retrieve a meeting
      * Retrieve all meetings
      * Update a meeting

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'zoom') ]]

  --8<-- "_snippets/integrations/builtin/app-nodes/operation-not-supported.md"

properties_schema:
  [{"displayName":"Authentication","name":"authentication","type":"options","options":[{"name":"Access Token","value":"accessToken"},{"name":"OAuth2","value":"oAuth2"}],"default":"accessToken"},{"displayName":"Resource","name":"resource","type":"options","noDataExpression":true,"options":[{"name":"Meeting","value":"meeting"}],"default":"meeting"},{"displayName":"Operation","name":"operation","type":"options","noDataExpression":true,"displayOptions":{"show":{"resource":["meeting"]}},"options":[{"name":"Create","value":"create","description":"Create a meeting","action":"Create a meeting"},{"name":"Delete","value":"delete","description":"Delete a meeting","action":"Delete a meeting"},{"name":"Get","value":"get","description":"Retrieve a meeting","action":"Get a meeting"},{"name":"Get Many","value":"getAll","description":"Retrieve many meetings","action":"Get many meetings"},{"name":"Update","value":"update","description":"Update a meeting","action":"Update a meeting"}],"default":"create"},{"displayName":"Topic","name":"topic","type":"string","default":"","displayOptions":{"show":{"operation":["create"],"resource":["meeting"]}},"description":"Topic of the meeting"},{"displayName":"Additional Fields","name":"additionalFields","type":"collection","placeholder":"Add Field","default":{},"displayOptions":{"show":{"operation":["create"],"resource":["meeting"]}},"options":[{"displayName":"Agenda","name":"agenda","type":"string","default":"","description":"Meeting agenda"},{"displayName":"Duration","name":"duration","type":"number","typeOptions":{"minValue":0},"default":0,"description":"Meeting duration (minutes)"},{"displayName":"Password","name":"password","type":"string","typeOptions":{"password":true},"default":"","description":"Password to join the meeting with maximum 10 characters"},{"displayName":"Schedule For","name":"scheduleFor","type":"string","default":"","description":"Schedule meeting for someone else from your account, provide their email ID"},{"displayName":"Settings","name":"settings","type":"collection","placeholder":"Add Setting","default":{},"options":[{"displayName":"Audio","name":"audio","type":"options","options":[{"name":"Both Telephony and VoiP","value":"both"},{"name":"Telephony","value":"telephony"},{"name":"VOIP","value":"voip"}],"default":"both","description":"Determine how participants can join audio portion of the meeting"},{"displayName":"Alternative Hosts","name":"alternativeHosts","type":"string","default":"","description":"Alternative hosts email IDs"},{"displayName":"Auto Recording","name":"autoRecording","type":"options","options":[{"name":"Record on Local","value":"local"},{"name":"Record on Cloud","value":"cloud"},{"name":"Disabled","value":"none"}],"default":"none"},{"displayName":"Host Meeting in China","name":"cnMeeting","type":"boolean","default":false},{"displayName":"Host Meeting in India","name":"inMeeting","type":"boolean","default":false},{"displayName":"Host Video","name":"hostVideo","type":"boolean","default":false,"description":"Whether to start a video when host joins the meeting"},{"displayName":"Join Before Host","name":"joinBeforeHost","type":"boolean","default":false,"description":"Whether to allow participants to join the meeting before host starts it"},{"displayName":"Muting Upon Entry","name":"muteUponEntry","type":"boolean","default":false,"description":"Whether to mute participants upon entry"},{"displayName":"Participant Video","name":"participantVideo","type":"boolean","default":false,"description":"Whether to start a video when participant joins the meeting"},{"displayName":"Registration Type","name":"registrationType","type":"options","options":[{"name":"Attendees register once and can attend any of the occurrences","value":1},{"name":"Attendees need to register for every occurrence","value":2},{"name":"Attendees register once and can choose one or more occurrences to attend","value":3}],"default":1,"description":"Registration type. Used for recurring meetings with fixed time only."},{"displayName":"Watermark","name":"watermark","type":"boolean","default":false,"description":"Whether to add a watermark when viewing a shared screen"}]},{"displayName":"Start Time","name":"startTime","type":"dateTime","default":"","description":"Start time should be used only for scheduled or recurring meetings with fixed time"},{"displayName":"Timezone Name or ID","name":"timeZone","type":"options","typeOptions":{"loadOptionsMethod":"getTimezones"},"default":"","description":"Time zone used in the response. The default is the time zone of the calendar. Choose from the list, or specify an ID using an <a href=\"https://docs.n8n.io/code-examples/expressions/\">expression</a>."},{"displayName":"Type","name":"type","type":"options","options":[{"name":"Instant Meeting","value":1},{"name":"Scheduled Meeting","value":2},{"name":"Recurring Meeting with No Fixed Time","value":3},{"name":"Recurring Meeting with Fixed Time","value":8}],"default":2,"description":"Meeting type"}]},{"displayName":"ID","name":"meetingId","type":"string","default":"","required":true,"displayOptions":{"show":{"operation":["get"],"resource":["meeting"]}},"description":"Meeting ID"},{"displayName":"Additional Fields","name":"additionalFields","type":"collection","placeholder":"Add Field","default":{},"displayOptions":{"show":{"operation":["get"],"resource":["meeting"]}},"options":[{"displayName":"Occurrence ID","name":"occurrenceId","type":"string","default":"","description":"To view meeting details of a particular occurrence of the recurring meeting"},{"displayName":"Show Previous Occurrences","name":"showPreviousOccurrences","type":"boolean","default":false,"description":"Whether to view meeting details of all previous occurrences of the recurring meeting"}]},{"displayName":"Return All","name":"returnAll","type":"boolean","displayOptions":{"show":{"operation":["getAll"],"resource":["meeting"]}},"default":false,"description":"Whether to return all results or only up to a given limit"},{"displayName":"Limit","name":"limit","type":"number","displayOptions":{"show":{"operation":["getAll"],"resource":["meeting"],"returnAll":[false]}},"typeOptions":{"minValue":1,"maxValue":300},"default":30,"description":"Max number of results to return"},{"displayName":"Filters","name":"filters","type":"collection","placeholder":"Add Filter","default":{},"displayOptions":{"show":{"operation":["getAll"],"resource":["meeting"]}},"options":[{"displayName":"Type","name":"type","type":"options","options":[{"name":"Scheduled","value":"scheduled","description":"This includes all valid past meetings, live meetings and upcoming scheduled meetings"},{"name":"Live","value":"live","description":"All ongoing meetings"},{"name":"Upcoming","value":"upcoming","description":"All upcoming meetings including live meetings"}],"default":"live","description":"Meeting type"}]},{"displayName":"ID","name":"meetingId","type":"string","default":"","required":true,"displayOptions":{"show":{"operation":["delete"],"resource":["meeting"]}},"description":"Meeting ID"},{"displayName":"Additional Fields","name":"additionalFields","type":"collection","placeholder":"Add Field","default":{},"displayOptions":{"show":{"operation":["delete"],"resource":["meeting"]}},"options":[{"displayName":"Occurrence ID","name":"occurrenceId","type":"string","default":"","description":"Meeting occurrence ID"},{"displayName":"Schedule Reminder","name":"scheduleForReminder","type":"boolean","default":false,"description":"Whether to notify hosts and alternative hosts about meeting cancellation via email"}]},{"displayName":"ID","name":"meetingId","type":"string","default":"","required":true,"displayOptions":{"show":{"operation":["update"],"resource":["meeting"]}},"description":"Meeting ID"},{"displayName":"Update Fields","name":"updateFields","type":"collection","placeholder":"Add Field","default":{},"displayOptions":{"show":{"operation":["update"],"resource":["meeting"]}},"options":[{"displayName":"Agenda","name":"agenda","type":"string","default":"","description":"Meeting agenda"},{"displayName":"Duration","name":"duration","type":"number","typeOptions":{"minValue":0},"default":0,"description":"Meeting duration (minutes)"},{"displayName":"Password","name":"password","type":"string","typeOptions":{"password":true},"default":"","description":"Password to join the meeting with maximum 10 characters"},{"displayName":"Schedule For","name":"scheduleFor","type":"string","default":"","description":"Schedule meeting for someone else from your account, provide their email ID"},{"displayName":"Settings","name":"settings","type":"collection","placeholder":"Add Setting","default":{},"options":[{"displayName":"Audio","name":"audio","type":"options","options":[{"name":"Both Telephony and VoiP","value":"both"},{"name":"Telephony","value":"telephony"},{"name":"VOIP","value":"voip"}],"default":"both","description":"Determine how participants can join audio portion of the meeting"},{"displayName":"Alternative Hosts","name":"alternativeHosts","type":"string","default":"","description":"Alternative hosts email IDs"},{"displayName":"Auto Recording","name":"autoRecording","type":"options","options":[{"name":"Record on Local","value":"local"},{"name":"Record on Cloud","value":"cloud"},{"name":"Disabled","value":"none"}],"default":"none"},{"displayName":"Host Meeting in China","name":"cnMeeting","type":"boolean","default":false},{"displayName":"Host Meeting in India","name":"inMeeting","type":"boolean","default":false},{"displayName":"Host Video","name":"hostVideo","type":"boolean","default":false,"description":"Whether to start a video when host joins the meeting"},{"displayName":"Join Before Host","name":"joinBeforeHost","type":"boolean","default":false,"description":"Whether to allow participants to join the meeting before host starts it"},{"displayName":"Muting Upon Entry","name":"muteUponEntry","type":"boolean","default":false,"description":"Whether to mute participants upon entry"},{"displayName":"Participant Video","name":"participantVideo","type":"boolean","default":false,"description":"Whether to start a video when participant joins the meeting"},{"displayName":"Registration Type","name":"registrationType","type":"options","options":[{"name":"Attendees Register Once and Can Attend Any of the Occurrences","value":1},{"name":"Attendees Need to Register for Every Occurrence","value":2},{"name":"Attendees Register Once and Can Choose One or More Occurrences to Attend","value":3}],"default":1,"description":"Registration type. Used for recurring meetings with fixed time only."},{"displayName":"Watermark","name":"watermark","type":"boolean","default":false,"description":"Whether to add watermark when viewing a shared screen"}]},{"displayName":"Start Time","name":"startTime","type":"dateTime","default":"","description":"Start time should be used only for scheduled or recurring meetings with fixed time"},{"displayName":"Timezone Name or ID","name":"timeZone","type":"options","typeOptions":{"loadOptionsMethod":"getTimezones"},"default":"","description":"Time zone used in the response. The default is the time zone of the calendar. Choose from the list, or specify an ID using an <a href=\"https://docs.n8n.io/code-examples/expressions/\">expression</a>."},{"displayName":"Topic","name":"topic","type":"string","default":"","description":"Meeting topic"},{"displayName":"Type","name":"type","type":"options","options":[{"name":"Instant Meeting","value":1},{"name":"Scheduled Meeting","value":2},{"name":"Recurring Meeting with No Fixed Time","value":3},{"name":"Recurring Meeting with Fixed Time","value":8}],"default":2,"description":"Meeting type"}]}]

operations:
  [{"type":"resource","resource":"meeting","name":"Meeting"},{"type":"operation","operation":"create","name":"Create","action":"Create a meeting","resources":["meeting"]},{"type":"operation","operation":"delete","name":"Delete","action":"Delete a meeting","resources":["meeting"]},{"type":"operation","operation":"get","name":"Get","action":"Get a meeting","resources":["meeting"]},{"type":"operation","operation":"getAll","name":"Get Many","action":"Get many meetings","resources":["meeting"]},{"type":"operation","operation":"update","name":"Update","action":"Update a meeting","resources":["meeting"]}]

credentials_required:
  [{"name":"zoomApi","required":true,"displayOptions":{"show":{"authentication":["accessToken"]}}},{"name":"zoomOAuth2Api","required":true,"displayOptions":{"show":{"authentication":["oAuth2"]}}}]


node_type: zulip
package_name: n8n-nodes-base
display_name: Zulip
description: Consume Zulip API
category: output
development_style: programmatic
version: 1
credentials_required: [{"name":"zulipApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Zulip node documentation
  description: Learn how to use the Zulip node in n8n. Follow technical documentation to integrate Zulip node into your workflows.
  contentType: [integration, reference]
  ---

  # Zulip node

  Use the Zulip node to automate work in Zulip, and integrate Zulip with other applications. n8n has built-in support for a wide range of Zulip features, including creating, deleting, and getting users and streams, as well as sending messages. 

  On this page, you'll find a list of operations the Zulip node supports and links to more resources.

  /// note | Credentials
  Refer to [Zulip credentials](/integrations/builtin/credentials/zulip.md) for guidance on setting up authentication. 
  ///

  ## Operations

  * Message
      * Delete a message
      * Get a message
      * Send a private message
      * Send a message to stream
      * Update a message
      * Upload a file
  * Stream
      * Create a stream.
      * Delete a stream.
      * Get all streams.
      * Get subscribed streams.
      * Update a stream.
  * User
      * Create a user.
      * Deactivate a user.
      * Get a user.
      * Get all users.
      * Update a user.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'zulip') ]]

properties_schema:
  [{"displayName":"Resource","name":"resource","type":"options","noDataExpression":true,"options":[{"name":"Message","value":"message"},{"name":"Stream","value":"stream"},{"name":"User","value":"user"}],"default":"message"},{"displayName":"Operation","name":"operation","type":"options","noDataExpression":true,"displayOptions":{"show":{"resource":["message"]}},"options":[{"name":"Delete","value":"delete","description":"Delete a message","action":"Delete a message"},{"name":"Get","value":"get","description":"Get a message","action":"Get a message"},{"name":"Send Private","value":"sendPrivate","description":"Send a private message","action":"Send a private message"},{"name":"Send to Stream","value":"sendStream","description":"Send a message to stream","action":"Send a message to a stream"},{"name":"Update","value":"update","description":"Update a message","action":"Update a message"},{"name":"Upload a File","value":"updateFile","action":"Upload a file"}],"default":"sendPrivate"},{"displayName":"To","name":"to","type":"multiOptions","typeOptions":{"loadOptionsMethod":"getUsers"},"required":true,"default":[],"displayOptions":{"show":{"resource":["message"],"operation":["sendPrivate"]}},"description":"The destination stream, or a comma-separated list containing the usernames (emails) of the recipients. Choose from the list, or specify IDs using an <a href=\"https://docs.n8n.io/code-examples/expressions/\">expression</a>."},{"displayName":"Content","name":"content","type":"string","required":true,"default":"","displayOptions":{"show":{"resource":["message"],"operation":["sendPrivate"]}},"description":"The content of the message"},{"displayName":"Stream Name or ID","name":"stream","type":"options","typeOptions":{"loadOptionsMethod":"getStreams"},"required":true,"default":"","displayOptions":{"show":{"resource":["message"],"operation":["sendStream"]}},"description":"The destination stream, or a comma-separated list containing the usernames (emails) of the recipients. Choose from the list, or specify an ID using an <a href=\"https://docs.n8n.io/code-examples/expressions/\">expression</a>."},{"displayName":"Topic Name or ID","name":"topic","type":"options","typeOptions":{"loadOptionsDependsOn":["stream"],"loadOptionsMethod":"getTopics"},"required":true,"displayOptions":{"show":{"resource":["message"],"operation":["sendStream"]}},"default":"","description":"The topic of the message. Only required if type is stream, ignored otherwise. Choose from the list, or specify an ID using an <a href=\"https://docs.n8n.io/code-examples/expressions/\">expression</a>."},{"displayName":"Content","name":"content","type":"string","required":true,"default":"","displayOptions":{"show":{"resource":["message"],"operation":["sendStream"]}},"description":"The content of the message"},{"displayName":"Message ID","name":"messageId","type":"string","required":true,"default":"","displayOptions":{"show":{"resource":["message"],"operation":["update"]}},"description":"Unique identifier for the message"},{"displayName":"Update Fields","name":"updateFields","type":"collection","placeholder":"Add Field","default":{},"displayOptions":{"show":{"resource":["message"],"operation":["update"]}},"options":[{"displayName":"Content","name":"content","type":"string","default":"","description":"The content of the message"},{"displayName":"Propagate Mode","name":"propagateMode","type":"options","options":[{"name":"Change One","value":"changeOne"},{"name":"Change Later","value":"changeLater"},{"name":"Change All","value":"changeAll"}],"default":"changeOne","description":"Which message(s) should be edited: just the one indicated in message_id, messages in the same topic that had been sent after this one, or all of them"},{"displayName":"Topic","name":"topic","type":"string","default":"","description":"The topic of the message. Only required for stream messages."}]},{"displayName":"Message ID","name":"messageId","type":"string","required":true,"default":"","displayOptions":{"show":{"resource":["message"],"operation":["get"]}},"description":"Unique identifier for the message"},{"displayName":"Message ID","name":"messageId","type":"string","required":true,"default":"","displayOptions":{"show":{"resource":["message"],"operation":["delete"]}},"description":"Unique identifier for the message"},{"displayName":"Binary Property","name":"dataBinaryProperty","type":"string","required":true,"default":"data","displayOptions":{"show":{"resource":["message"],"operation":["updateFile"]}},"description":"Name of the binary property to which to write the data of the read file"},{"displayName":"Operation","name":"operation","type":"options","noDataExpression":true,"displayOptions":{"show":{"resource":["stream"]}},"options":[{"name":"Create","value":"create","description":"Create a stream","action":"Create a stream"},{"name":"Delete","value":"delete","description":"Delete a stream","action":"Delete a stream"},{"name":"Get Many","value":"getAll","description":"Get many streams","action":"Get many streams"},{"name":"Get Subscribed","value":"getSubscribed","description":"Get subscribed streams","action":"Get subscribed streams"},{"name":"Update","value":"update","description":"Update a stream","action":"Update a stream"}],"default":"create"},{"displayName":"JSON Parameters","name":"jsonParameters","type":"boolean","default":false,"displayOptions":{"show":{"resource":["stream"],"operation":["create"]}}},{"displayName":"Additional Fields","name":"additionalFieldsJson","type":"json","typeOptions":{"alwaysOpenEditWindow":true},"default":"","displayOptions":{"show":{"resource":["stream"],"operation":["create"],"jsonParameters":[true]}},"description":"JSON format parameters for stream creation"},{"displayName":"Subscriptions","name":"subscriptions","type":"fixedCollection","default":{},"displayOptions":{"show":{"resource":["stream"],"operation":["create"],"jsonParameters":[false]}},"required":true,"description":"A list of dictionaries containing the the key name and value specifying the name of the stream to subscribe. If the stream does not exist a new stream is created.","typeOptions":{"multipleValues":true},"options":[{"displayName":"Subscription Properties","name":"properties","values":[{"displayName":"Name","name":"name","type":"string","required":true,"default":"","description":"Name of Subscription"},{"displayName":"Description","name":"description","type":"string","required":true,"default":"","description":"Description of Subscription"}]}]},{"displayName":"Additional Fields","name":"additionalFields","type":"collection","placeholder":"Add Field","default":{},"displayOptions":{"show":{"resource":["stream"],"operation":["create"],"jsonParameters":[false]}},"options":[{"displayName":"Announce","name":"announce","type":"boolean","default":false,"description":"If announce is True and one of the streams specified in subscriptions has to be created (i.e. doesnt exist to begin with), an announcement will be made notifying that a new stream was created."},{"displayName":"Authorization Errors Fatal","name":"authorizationErrorsFatal","type":"boolean","default":false,"description":"Whether authorization errors (such as when the requesting user is not authorized to access a private stream) should be considered fatal or not. When True, an authorization error is reported as such. When set to False, the returned JSON payload indicates that there was an authorization error, but the response is still considered a successful one."},{"displayName":"History Public to Subscribers","name":"historyPublicToSubscribers","type":"boolean","default":false,"description":"Whether the streams message history should be available to newly subscribed members, or users can only access messages they actually received while subscribed to the stream"},{"displayName":"Invite Only","name":"inviteOnly","type":"boolean","default":false,"description":"Whether the streams specified in subscriptions are invite-only or not"},{"displayName":"Principals","name":"principals","type":"fixedCollection","default":{},"description":"A list of email addresses of the users that will be subscribed/unsubscribed to the streams specified in the subscriptions argument. If not provided, then the requesting user/bot is subscribed.","typeOptions":{"multipleValues":true},"options":[{"displayName":"Principals Properties","name":"properties","values":[{"displayName":"Principal Email","name":"email","type":"string","placeholder":"name@email.com","required":true,"default":"","description":"Principal email address"}]}]},{"displayName":"Stream Post Policy","name":"streamPostPolicy","type":"options","default":"","description":"Policy for which users can post messages to the stream","options":[{"name":"1","value":1,"description":"Any user can post"},{"name":"2","value":2,"description":"Only administrators can post"},{"name":"3","value":3,"description":"Only new members can post"}]}]},{"displayName":"Additional Fields","name":"additionalFields","type":"collection","placeholder":"Add Field","default":{},"displayOptions":{"show":{"resource":["stream"],"operation":["getAll"]}},"options":[{"displayName":"Include All Active","name":"includeAllActive","type":"boolean","default":true,"description":"Whether to include all active streams. The user must have administrative privileges to use this parameter."},{"displayName":"Include Default","name":"includeDefault","type":"boolean","default":true,"description":"Whether to include all default streams for the users realm"},{"displayName":"Include Owner Subscribed","name":"includeOwnersubscribed","type":"boolean","default":true,"description":"Whether the user is a bot, include all streams that the bots owner is subscribed to"},{"displayName":"Include Public","name":"includePublic","type":"boolean","default":true,"description":"Whether to include all public streams"},{"displayName":"Include Subscribed","name":"includeSubscribed","type":"boolean","default":true,"description":"Whether to include all streams that the user is subscribed to"}]},{"displayName":"Additional Fields","name":"additionalFields","type":"collection","placeholder":"Add Field","default":{},"displayOptions":{"show":{"resource":["stream"],"operation":["getSubscribed"]}},"options":[{"displayName":"Include Subscribers","name":"includeSubscribers","type":"boolean","default":true,"description":"Whether each returned stream object should include a subscribers field containing a list of the user IDs of its subscribers"}]},{"displayName":"Stream ID","name":"streamId","type":"string","required":true,"default":"","displayOptions":{"show":{"resource":["stream"],"operation":["update"]}},"description":"ID of stream to update"},{"displayName":"JSON Parameters","name":"jsonParameters","type":"boolean","default":false,"displayOptions":{"show":{"resource":["stream"],"operation":["update"]}}},{"displayName":"Additional Fields","name":"additionalFieldsJson","type":"json","typeOptions":{"alwaysOpenEditWindow":true},"default":"","displayOptions":{"show":{"resource":["stream"],"operation":["update"],"jsonParameters":[true]}},"description":"JSON format parameters for stream creation"},{"displayName":"Additional Fields","name":"additionalFields","type":"collection","placeholder":"Add Field","default":{},"displayOptions":{"show":{"resource":["stream"],"operation":["update"],"jsonParameters":[false]}},"options":[{"displayName":"Announcement Only","name":"isAnnouncementOnly","type":"boolean","default":false,"description":"Whether the stream is limited to announcements"},{"displayName":"Description","name":"description","type":"string","default":"","description":"The new description for the stream","placeholder":"Place of discussion"},{"displayName":"Is Private","name":"isPrivate","type":"boolean","default":false,"description":"Whether the stream is a private stream"},{"displayName":"History Public to Subscribers","name":"historyPublicToSubscribers","type":"boolean","default":false,"description":"Whether the streams message history should be available to newly subscribed members, or users can only access messages they actually received while subscribed to the stream"},{"displayName":"New Name","name":"newName","type":"string","default":"","description":"The new name for the stream","placeholder":"Italy"},{"displayName":"Stream Post Policy","name":"streamPostPolicy","type":"options","default":"","description":"Policy for which users can post messages to the stream","options":[{"name":"1","value":1,"description":"Any user can post"},{"name":"2","value":2,"description":"Only administrators can post"},{"name":"3","value":3,"description":"Only new members can post"}]}]},{"displayName":"Stream ID","name":"streamId","type":"string","required":true,"default":"","displayOptions":{"show":{"resource":["stream"],"operation":["delete"]}},"description":"ID of stream to delete"},{"displayName":"Operation","name":"operation","type":"options","noDataExpression":true,"displayOptions":{"show":{"resource":["user"]}},"options":[{"name":"Create","value":"create","description":"Create a user","action":"Create a user"},{"name":"Deactivate","value":"deactivate","description":"Deactivate a user","action":"Deactivate a user"},{"name":"Get","value":"get","description":"Get a user","action":"Get a user"},{"name":"Get Many","value":"getAll","description":"Get many users","action":"Get many users"},{"name":"Update","value":"update","description":"Update a user","action":"Update a user"}],"default":"create"},{"displayName":"Email","name":"email","type":"string","placeholder":"name@email.com","required":true,"displayOptions":{"show":{"resource":["user"],"operation":["create"]}},"default":"","description":"The email address of the new user"},{"displayName":"Full Name","name":"fullName","type":"string","required":true,"displayOptions":{"show":{"resource":["user"],"operation":["create"]}},"default":"","description":"The full name of the new user"},{"displayName":"Password","name":"password","type":"string","typeOptions":{"password":true},"required":true,"displayOptions":{"show":{"resource":["user"],"operation":["create"]}},"default":"","description":"The password of the new user"},{"displayName":"Short Name","name":"shortName","type":"string","required":true,"displayOptions":{"show":{"resource":["user"],"operation":["create"]}},"default":"","description":"The short name of the new user. Not user-visible."},{"displayName":"User ID","name":"userId","type":"string","required":true,"displayOptions":{"show":{"resource":["user"],"operation":["get"]}},"default":"","description":"The ID of user to get"},{"displayName":"Additional Fields","name":"additionalFields","type":"collection","placeholder":"Add Field","default":{},"displayOptions":{"show":{"resource":["user"],"operation":["get","getAll"]}},"options":[{"displayName":"Client Gravatar","name":"clientGravatar","type":"boolean","default":false,"description":"Whether the client supports computing gravatars URLs. If enabled, avatar_url will be included in the response only if there is a Zulip avatar, and will be null for users who are using gravatar as their avatar."},{"displayName":"Custom Profile Fields","name":"includeCustomProfileFields","type":"boolean","default":false,"description":"Whether the client wants custom profile field data to be included in the response"}]},{"displayName":"User ID","name":"userId","type":"string","required":true,"displayOptions":{"show":{"resource":["user"],"operation":["update"]}},"default":"","description":"The ID of user to update"},{"displayName":"Additional Fields","name":"additionalFields","type":"collection","placeholder":"Add Field","default":{},"displayOptions":{"show":{"resource":["user"],"operation":["update"]}},"options":[{"displayName":"Full Name","name":"fullName","type":"string","default":"","description":"The users full name"},{"displayName":"Is Admin","name":"isAdmin","type":"boolean","default":false,"description":"Whether the target user is an administrator"},{"displayName":"Is Guest","name":"isGuest","type":"boolean","default":false,"description":"Whether the target user is a guest"},{"displayName":"Profile Data","name":"profileData","type":"fixedCollection","default":{},"description":"A dictionary containing the to be updated custom profile field data for the user","typeOptions":{"multipleValues":true},"options":[{"displayName":"Property","name":"property","values":[{"displayName":"ID","name":"id","type":"string","required":true,"default":"","description":"ID of custom profile data value"},{"displayName":"Value","name":"value","type":"string","default":"","description":"Value of custom profile data"}]}]},{"displayName":"Role","name":"role","type":"options","options":[{"name":"Guest","value":600},{"name":"Member","value":400},{"name":"Organization Administrator","value":200},{"name":"Organization Moderator","value":300},{"name":"Organization Owner","value":100}],"default":"","description":"Role for the user"}]},{"displayName":"User ID","name":"userId","type":"string","required":true,"displayOptions":{"show":{"resource":["user"],"operation":["deactivate"]}},"default":"","description":"The ID of user to deactivate"}]

operations:
  [{"type":"resource","resource":"message","name":"Message"},{"type":"resource","resource":"stream","name":"Stream"},{"type":"resource","resource":"user","name":"User"},{"type":"operation","operation":"delete","name":"Delete","action":"Delete a message","resources":["message"]},{"type":"operation","operation":"get","name":"Get","action":"Get a message","resources":["message"]},{"type":"operation","operation":"sendPrivate","name":"Send Private","action":"Send a private message","resources":["message"]},{"type":"operation","operation":"sendStream","name":"Send to Stream","action":"Send a message to a stream","resources":["message"]},{"type":"operation","operation":"update","name":"Update","action":"Update a message","resources":["message"]},{"type":"operation","operation":"updateFile","name":"Upload a File","action":"Upload a file","resources":["message"]},{"type":"operation","operation":"create","name":"Create","action":"Create a stream","resources":["stream"]},{"type":"operation","operation":"delete","name":"Delete","action":"Delete a stream","resources":["stream"]},{"type":"operation","operation":"getAll","name":"Get Many","action":"Get many streams","resources":["stream"]},{"type":"operation","operation":"getSubscribed","name":"Get Subscribed","action":"Get subscribed streams","resources":["stream"]},{"type":"operation","operation":"update","name":"Update","action":"Update a stream","resources":["stream"]},{"type":"operation","operation":"create","name":"Create","action":"Create a user","resources":["user"]},{"type":"operation","operation":"deactivate","name":"Deactivate","action":"Deactivate a user","resources":["user"]},{"type":"operation","operation":"get","name":"Get","action":"Get a user","resources":["user"]},{"type":"operation","operation":"getAll","name":"Get Many","action":"Get many users","resources":["user"]},{"type":"operation","operation":"update","name":"Update","action":"Update a user","resources":["user"]}]


node_type: agent
package_name: @n8n/n8n-nodes-langchain
display_name: Agent
description: Seamlessly coordinates LLMs & tools per user input
category: transform
development_style: programmatic
version: 1
operations: []
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Agent","name":"agent","type":"options","noDataExpression":true,"options":[{"name":"Conversational Agent","value":"conversationalAgent","description":"Selects tools to accomplish its task and uses memory to recall previous conversations"},{"name":"OpenAI Functions Agent","value":"openAiFunctionsAgent","description":"Utilizes OpenAI's Function Calling feature to select the appropriate tool and arguments for execution"},{"name":"ReAct Agent","value":"reActAgent","description":"Strategically select tools to accomplish a given task"},{"name":"SQL Agent","value":"sqlAgent","description":"Answers questions about data in an SQL database"}],"default":"conversationalAgent"},{"displayName":"Text","name":"text","type":"string","required":true,"displayOptions":{"show":{"agent":["conversationalAgent"]}},"default":"={{ $json.input }}"},{"displayName":"Options","name":"options","type":"collection","displayOptions":{"show":{"agent":["conversationalAgent"]}},"default":{},"placeholder":"Add Option","options":[{"displayName":"Human Message","name":"humanMessage","type":"string","default":"TOOLS\n------\nAssistant can ask the user to use tools to look up information that may be helpful in answering the users original question. The tools the human can use are:\n\n{tools}\n\n{format_instructions}\n\nUSER'S INPUT\n--------------------\nHere is the user's input (remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else):\n\n{{input}}","description":"The message that will provide the agent with a list of tools to use","typeOptions":{"rows":6}},{"displayName":"System Message","name":"systemMessage","type":"string","default":"Assistant is a large language model trained by OpenAI.\n\nAssistant is designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language model, Assistant is able to generate human-like text based on the input it receives, allowing it to engage in natural-sounding conversations and provide responses that are coherent and relevant to the topic at hand.\n\nAssistant is constantly learning and improving, and its capabilities are constantly evolving. It is able to process and understand large amounts of text, and can use this knowledge to provide accurate and informative responses to a wide range of questions. Additionally, Assistant is able to generate its own text based on the input it receives, allowing it to engage in discussions and provide explanations and descriptions on a wide range of topics.\n\nOverall, Assistant is a powerful system that can help with a wide range of tasks and provide valuable insights and information on a wide range of topics. Whether you need help with a specific question or just want to have a conversation about a particular topic, Assistant is here to assist.","description":"The message that will be sent to the agent before the conversation starts","typeOptions":{"rows":6}},{"displayName":"Max Iterations","name":"maxIterations","type":"number","default":10,"description":"The maximum number of iterations the agent will run before stopping"}]},{"displayName":"Text","name":"text","type":"string","required":true,"displayOptions":{"show":{"agent":["openAiFunctionsAgent"]}},"default":"={{ $json.input }}"},{"displayName":"Options","name":"options","type":"collection","displayOptions":{"show":{"agent":["openAiFunctionsAgent"]}},"default":{},"placeholder":"Add Option","options":[{"displayName":"System Message","name":"systemMessage","type":"string","default":"You are a helpful AI assistant.","description":"The message that will be sent to the agent before the conversation starts","typeOptions":{"rows":6}},{"displayName":"Max Iterations","name":"maxIterations","type":"number","default":10,"description":"The maximum number of iterations the agent will run before stopping"}]},{"displayName":"Text","name":"text","type":"string","required":true,"displayOptions":{"show":{"agent":["reActAgent"]}},"default":"={{ $json.input }}"},{"displayName":"Options","name":"options","type":"collection","displayOptions":{"show":{"agent":["reActAgent"]}},"default":{},"placeholder":"Add Option","options":[{"displayName":"Human Message Template","name":"humanMessageTemplate","type":"string","default":"{input}\n\n{agent_scratchpad}","description":"String to use directly as the human message template","typeOptions":{"rows":6}},{"displayName":"Prefix Message","name":"prefix","type":"string","default":"Answer the following questions as best you can. You have access to the following tools:","description":"String to put before the list of tools","typeOptions":{"rows":6}},{"displayName":"Suffix Message for Chat Model","name":"suffixChat","type":"string","default":"Begin! Reminder to always use the exact characters `Final Answer` when responding.","description":"String to put after the list of tools that will be used if chat model is used","typeOptions":{"rows":6}},{"displayName":"Suffix Message for Regular Model","name":"suffix","type":"string","default":"Begin!\n\n\tQuestion: {input}\n\tThought:{agent_scratchpad}","description":"String to put after the list of tools that will be used if regular model is used","typeOptions":{"rows":6}}]},{"displayName":"Data Source","name":"dataSource","type":"options","displayOptions":{"show":{"agent":["sqlAgent"]}},"default":"sqlite","description":"SQL database to connect to","options":[{"name":"MySQL","value":"mysql","description":"Connect to a MySQL database"},{"name":"Postgres","value":"postgres","description":"Connect to a Postgres database"},{"name":"SQLite","value":"sqlite","description":"Use SQLite by connecting a database file as binary input"}]},{"displayName":"Prompt","name":"input","type":"string","displayOptions":{"show":{"agent":["sqlAgent"]}},"default":"","required":true,"typeOptions":{"rows":5}},{"displayName":"Options","name":"options","type":"collection","displayOptions":{"show":{"agent":["sqlAgent"]}},"default":{},"placeholder":"Add Option","options":[{"displayName":"Ignored Tables","name":"ignoredTables","type":"string","default":"","description":"Comma-separated list of tables to ignore from the database. If empty, no tables are ignored."},{"displayName":"Include Sample Rows","name":"includedSampleRows","type":"number","description":"Number of sample rows to include in the prompt to the agent. It helps the agent to understand the schema of the database but it also increases the amount of tokens used.","default":3},{"displayName":"Included Tables","name":"includedTables","type":"string","default":"","description":"Comma-separated list of tables to include in the database. If empty, all tables are included."},{"displayName":"Prefix Prompt","name":"prefixPrompt","type":"string","default":"You are an agent designed to interact with an SQL database.\nGiven an input question, create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer.\nUnless the user specifies a specific number of examples they wish to obtain, always limit your query to at most {top_k} results using the LIMIT clause.\nYou can order the results by a relevant column to return the most interesting examples in the database.\nNever query for all the columns from a specific table, only ask for a the few relevant columns given the question.\nYou have access to tools for interacting with the database.\nOnly use the below tools. Only use the information returned by the below tools to construct your final answer.\nYou MUST double check your query before executing it. If you get an error while executing a query, rewrite the query and try again.\n\nDO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.\n\nIf the question does not seem related to the database, just return \"I don't know\" as the answer.","description":"Prefix prompt to use for the agent","typeOptions":{"rows":10}},{"displayName":"Suffix Prompt","name":"suffixPrompt","type":"string","default":"Begin!\n\nQuestion: {input}\nThought: I should look at the tables in the database to see what I can query.\n{agent_scratchpad}","description":"Suffix prompt to use for the agent","typeOptions":{"rows":4}},{"displayName":"Top K","name":"topK","type":"number","default":10,"description":"Number of top results agent should return"}]}]

credentials_required:
  [{"name":"mySql","required":true,"testedBy":"mysqlConnectionTest","displayOptions":{"show":{"agent":["sqlAgent"],"/dataSource":["mysql"]}}},{"name":"postgres","required":true,"displayOptions":{"show":{"agent":["sqlAgent"],"/dataSource":["postgres"]}}}]


node_type: chainSummarization
package_name: @n8n/n8n-nodes-langchain
display_name: Summarization Chain
description: Transforms text into a concise summary
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Specify the document to load in the document loader sub-node","name":"notice","type":"notice","default":""},{"displayName":"Type","name":"type","type":"options","description":"The type of summarization to run","default":"map_reduce","options":[{"name":"Map Reduce (Recommended)","value":"map_reduce","description":"Individually summarizes each document using an LLM (Map step), then combines these summaries into a global summary (Reduce step), with an optional compression step to ensure fit"},{"name":"Refine","value":"refine","description":"Iteratively updates its answer by looping over the documents and passing the current document along with the latest intermediate answer to an LLM, suitable for analyzing large document sets, albeit with more LLM calls"},{"name":"Stuff","value":"stuff","description":"Inserts all documents into a prompt, then passes it to an LLM for summarization, ideal for small document sets"}]},{"displayName":"Options","name":"options","type":"collection","default":{},"placeholder":"Add Option","options":[{"displayName":"Combine Map Prompt","name":"combineMapPrompt","type":"string","displayOptions":{"show":{"/type":["map_reduce"]}},"default":"Write a concise summary of the following:\n\n\n\"{text}\"\n\n\nCONCISE SUMMARY:","typeOptions":{"rows":6}},{"displayName":"Prompt","name":"prompt","type":"string","default":"Write a concise summary of the following:\n\n\n\"{text}\"\n\n\nCONCISE SUMMARY:","displayOptions":{"hide":{"/type":["refine"]}},"typeOptions":{"rows":6}},{"displayName":"Refine Prompt","name":"refinePrompt","type":"string","displayOptions":{"show":{"/type":["refine"]}},"default":"Your job is to produce a final summary\nWe have provided an existing summary up to a certain point: \"{existing_answer}\"\nWe have the opportunity to refine the existing summary\n(only if needed) with some more context below.\n------------\n\"{text}\"\n------------\n\nGiven the new context, refine the original summary\nIf the context isn't useful, return the original summary.\n\nREFINED SUMMARY:","typeOptions":{"rows":6}},{"displayName":"Refine Question Prompt","name":"refineQuestionPrompt","type":"string","displayOptions":{"show":{"/type":["refine"]}},"default":"Write a concise summary of the following:\n\n\n\"{text}\"\n\n\nCONCISE SUMMARY:","typeOptions":{"rows":6}}]}]


node_type: chainLlm
package_name: @n8n/n8n-nodes-langchain
display_name: Basic LLM Chain
description: A simple chain to prompt a large language mode
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Prompt","name":"prompt","type":"string","required":true,"default":"={{ $json.input }}"},{"displayName":"The options below to add prompts are only valid for chat models, they will be ignored for other models.","name":"notice","type":"notice","default":""},{"displayName":"Chat Messages","name":"messages","type":"fixedCollection","typeOptions":{"multipleValues":true},"default":{},"placeholder":"Add prompt","options":[{"name":"messageValues","displayName":"Prompt","values":[{"displayName":"Type Name or ID","name":"type","type":"options","options":[{"name":"AI","value":"AIMessagePromptTemplate"},{"name":"System","value":"SystemMessagePromptTemplate"},{"name":"User","value":"HumanMessagePromptTemplate"}],"default":"SystemMessagePromptTemplate"},{"displayName":"Message","name":"message","type":"string","required":true,"default":""}]}]}]


node_type: chainRetrievalQa
package_name: @n8n/n8n-nodes-langchain
display_name: Retrieval Q&A Chain
description: Retrieves answers to queries based on retrieved documents
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Query","name":"query","type":"string","required":true,"default":"={{ $json.input }}"}]


node_type: documentBinaryInputLoader
package_name: @n8n/n8n-nodes-langchain
display_name: Binary Input Loader
description: Use binary data from a previous step in the workflow
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Loader Type","name":"loader","type":"options","default":"jsonLoader","required":true,"options":[{"name":"CSV Loader","value":"csvLoader","description":"Load CSV files"},{"name":"Docx Loader","value":"docxLoader","description":"Load Docx documents"},{"name":"EPub Loader","value":"epubLoader","description":"Load EPub files"},{"name":"JSON Loader","value":"jsonLoader","description":"Load JSON files"},{"name":"PDF Loader","value":"pdfLoader","description":"Load PDF documents"},{"name":"Text Loader","value":"textLoader","description":"Load plain text files"}]},{"displayName":"Binary Data Key","name":"binaryDataKey","type":"string","default":"data","required":true,"description":"Name of the binary property from which to read the file buffer"},{"displayName":"Split Pages","name":"splitPages","type":"boolean","default":true,"displayOptions":{"show":{"loader":["pdfLoader"]}}},{"displayName":"Column","name":"column","type":"string","default":"","description":"Column to extract from CSV","displayOptions":{"show":{"loader":["csvLoader"]}}},{"displayName":"Separator","name":"separator","type":"string","description":"Separator to use for CSV","default":",","displayOptions":{"show":{"loader":["csvLoader"]}}},{"displayName":"Pointers","name":"pointers","type":"string","default":"","description":"Pointers to extract from JSON, e.g. \"/text\" or \"/text, /meta/title\"","displayOptions":{"show":{"loader":["jsonLoader"]}}},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Metadata","name":"metadata","type":"fixedCollection","description":"Metadata to add to each document. Could be used for filtering during retrieval","typeOptions":{"multipleValues":true},"default":{},"placeholder":"Add property","options":[{"name":"metadataValues","displayName":"Fields to Set","values":[{"displayName":"Name","name":"name","type":"string","default":"","required":true},{"displayName":"Value","name":"value","type":"string","default":""}]}]}]}]


node_type: documentJsonInputLoader
package_name: @n8n/n8n-nodes-langchain
display_name: JSON Input Loader
description: Use JSON data from a previous step in the workflow
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Pointers","name":"pointers","type":"string","default":"","description":"Pointers to extract from JSON, e.g. \"/text\" or \"/text, /meta/title\""},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Metadata","name":"metadata","type":"fixedCollection","description":"Metadata to add to each document. Could be used for filtering during retrieval","typeOptions":{"multipleValues":true},"default":{},"placeholder":"Add property","options":[{"name":"metadataValues","displayName":"Fields to Set","values":[{"displayName":"Name","name":"name","type":"string","default":"","required":true},{"displayName":"Value","name":"value","type":"string","default":""}]}]}]}]


node_type: embeddingsCohere
package_name: @n8n/n8n-nodes-langchain
display_name: Embeddings Cohere
description: Use Cohere Embeddings
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"cohereApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Embeddings Cohere node documentation
  description: Learn how to use the Embeddings Cohere node in n8n. Follow technical documentation to integrate Embeddings Cohere node into your workflows.
  contentType: [integration, reference]
  ---

  # Embeddings Cohere node

  Use the Embeddings Cohere node to generate [embeddings](/glossary.md#ai-embedding) for a given text.

  On this page, you'll find the node parameters for the Embeddings Cohere node, and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/cohere.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Model**: Select the model to use to generate the embedding. Choose from:
      * **Embed-English-v2.0(4096 Dimensions)**
  	* **Embed-English-Light-v2.0(1024 Dimensions)**
  	* **Embed-Multilingual-v2.0(768 Dimensions)**

  Learn more about available models in [Cohere's models documentation](https://docs.cohere.com/docs/models){:target=_blank .external-link}.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'embeddings-cohere') ]]

  ## Related resources

  Refer to [Langchain's Cohere embeddings documentation](https://js.langchain.com/docs/integrations/text_embedding/cohere/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Each model is using different dimensional density for embeddings. Please make sure to use the same dimensionality for your vector store. The default model is using 768-dimensional embeddings.","name":"notice","type":"notice","default":""},{"displayName":"Model","name":"modelName","type":"options","description":"The model which will generate the embeddings. <a href=\"https://docs.cohere.com/docs/models\">Learn more</a>.","default":"embed-english-v2.0","options":[{"name":"Embed-English-v2.0(4096 Dimensions)","value":"embed-english-v2.0"},{"name":"Embed-English-Light-v2.0(1024 Dimensions)","value":"embed-english-light-v2.0"},{"name":"Embed-Multilingual-v2.0(768 Dimensions)","value":"embed-multilingual-v2.0"}]}]


node_type: embeddingsAwsBedrock
package_name: @n8n/n8n-nodes-langchain
display_name: Embeddings AWS Bedrock
description: Use Embeddings AWS Bedrock
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"aws","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Embeddings AWS Bedrock node documentation
  description: Learn how to use the Embeddings AWS Bedrock node in n8n. Follow technical documentation to integrate Embeddings AWS Bedrock node into your workflows.
  contentType: [integration, reference]
  ---

  # Embeddings AWS Bedrock node

  Use the Embeddings AWS Bedrock node to generate [embeddings](/glossary.md#ai-embedding) for a given text.

  On this page, you'll find the node parameters for the Embeddings AWS Bedrock node, and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/aws.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Model**: Select the model to use to generate the embedding.

  Learn more about available models in the [Amazon Bedrock documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html){:target=_blank .external-link}. 

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'embeddings-aws-bedrock') ]]

  ## Related resources

  Refer to [LangChains's AWS Bedrock embeddings documentation](https://js.langchain.com/docs/integrations/platforms/aws/#text-embedding-models){:target=_blank .external-link} and the [AWS Bedrock documentation](https://docs.aws.amazon.com/bedrock/){:target=_blank .external-link} for more information about AWS Bedrock.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Model","name":"model","type":"options","description":"The model which will generate the completion. <a href=\"https://docs.aws.amazon.com/bedrock/latest/userguide/foundation-models.html\">Learn more</a>.","typeOptions":{"loadOptions":{"routing":{"request":{"method":"GET","url":"/foundation-models"},"output":{"postReceive":[{"type":"rootProperty","properties":{"property":"modelSummaries"}},{"type":"filter","properties":{"pass":"={{ !'anthropic.claude-instant-v1-100k,anthropic.claude-v2,amazon.titan-text-express-v1'.match($responseItem.modelId) }}"}},{"type":"setKeyValue","properties":{"name":"={{$responseItem.modelName}}","description":"={{$responseItem.modelArn}}","value":"={{$responseItem.modelId}}"}},{"type":"sort","properties":{"key":"name"}}]}}}},"routing":{"send":{"type":"body","property":"model"}},"default":""}]


node_type: embeddingsGooglePalm
package_name: @n8n/n8n-nodes-langchain
display_name: Embeddings Google PaLM
description: Use Google PaLM Embeddings
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"googlePalmApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Embeddings Google PaLM node documentation
  description: Learn how to use the Embeddings Google PaLM node in n8n. Follow technical documentation to integrate Embeddings Google PaLM node into your workflows.
  contentType: [integration, reference]
  ---

  # Embeddings Google PaLM node

  Use the Embeddings Google PaLM node to generate [embeddings](/glossary.md#ai-embedding) for a given text.

  On this page, you'll find the node parameters for the Embeddings Google PaLM node, and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/googleai.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Model**: Select the model to use to generate the embedding.

  n8n dynamically loads models from the Google PaLM API and you'll only see the models available to your account.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'embeddings-google-palm') ]]

  ## Related resources

  Refer to [Langchain's Google PaLM embeddings documentation](https://js.langchain.com/v0.2/docs/integrations/text_embedding/google_palm/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Each model is using different dimensional density for embeddings. Please make sure to use the same dimensionality for your vector store. The default model is using 768-dimensional embeddings.","name":"notice","type":"notice","default":""},{"displayName":"Model","name":"modelName","type":"options","description":"The model which will generate the embeddings. <a href=\"https://developers.generativeai.google/api/rest/generativelanguage/models/list\">Learn more</a>.","typeOptions":{"loadOptions":{"routing":{"request":{"method":"GET","url":"/v1beta3/models"},"output":{"postReceive":[{"type":"rootProperty","properties":{"property":"models"}},{"type":"filter","properties":{"pass":"={{ $responseItem.name.startsWith('models/embedding') }}"}},{"type":"setKeyValue","properties":{"name":"={{$responseItem.name}}","value":"={{$responseItem.name}}","description":"={{$responseItem.description}}"}},{"type":"sort","properties":{"key":"name"}}]}}}},"routing":{"send":{"type":"body","property":"model"}},"default":"models/embedding-gecko-001"}]


node_type: embeddingsHuggingFaceInference
package_name: @n8n/n8n-nodes-langchain
display_name: Embeddings Hugging Face Inference
description: Use HuggingFace Inference Embeddings
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"huggingFaceApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Embeddings HuggingFace Inference node documentation
  description: Learn how to use the Embeddings HuggingFace Inference node in n8n. Follow technical documentation to integrate Embeddings HuggingFace Inference node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Embeddings HuggingFace Inference node

  Use the Embeddings HuggingFace Inference node to generate [embeddings](/glossary.md#ai-embedding) for a given text.

  On this page, you'll find the node parameters for the Embeddings HuggingFace Inference, and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/huggingface.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Model**: Select the model to use to generate the embedding.

  Refer to the [Hugging Face models documentation](https://huggingface.co/models?other=embeddings){:target=_blank .external-link} for available models.

  ## Node options

  * **Custom Inference Endpoint**: Enter the URL of your deployed model, hosted by HuggingFace. If you set this, n8n ignores the **Model Name**.

  Refer to [HuggingFace's guide to inference](https://huggingface.co/inference-endpoints){:target=_blank .external-link} for more information.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'embeddings-hugging-face-inference') ]]

  ## Related resources

  Refer to [Langchain's HuggingFace Inference embeddings documentation](https://js.langchain.com/docs/integrations/text_embedding/hugging_face_inference/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Each model is using different dimensional density for embeddings. Please make sure to use the same dimensionality for your vector store. The default model is using 768-dimensional embeddings.","name":"notice","type":"notice","default":""},{"displayName":"Model Name","name":"modelName","type":"string","default":"sentence-transformers/distilbert-base-nli-mean-tokens","description":"The model name to use from HuggingFace library"},{"displayName":"Options","name":"options","placeholder":"Add Option","description":"Additional options to add","type":"collection","default":{},"options":[{"displayName":"Custom Inference Endpoint","name":"endpointUrl","default":"","description":"Custom endpoint URL","type":"string"}]}]


node_type: embeddingsOpenAi
package_name: @n8n/n8n-nodes-langchain
display_name: Embeddings OpenAI
description: Use Embeddings OpenAI
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"openAiApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Embeddings OpenAI node documentation
  description: Learn how to use the Embeddings OpenAI node in n8n. Follow technical documentation to integrate Embeddings OpenAI node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Embeddings OpenAI node

  Use the Embeddings OpenAI node to generate [embeddings](/glossary.md#ai-embedding) for a given text.

  On this page, you'll find the node parameters for the Embeddings OpenAI node, and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/openai.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"


  ## Node options

  * **Model**: Select the model to use for generating embeddings.
  * **Base URL**: Enter the URL to send the request to. Use this if you are using a self-hosted OpenAI-like model. 
  * **Batch Size**: Enter the maximum number of documents to send in each request.
  * **Strip New Lines**: Select whether to remove new line characters from input text (turned on) or not (turned off). n8n enables this by default.
  * **Timeout**: Enter the maximum amount of time a request can take in seconds. Set to `-1` for no timeout.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'embeddings-openai') ]]

  ## Related resources

  Refer to [LangChains's OpenAI embeddings documentation](https://js.langchain.com/docs/integrations/text_embedding/openai/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Options","name":"options","placeholder":"Add Option","description":"Additional options to add","type":"collection","default":{},"options":[{"displayName":"Base URL","name":"baseURL","default":"https://api.openai.com/v1","description":"Override the default base URL for the API","type":"string"},{"displayName":"Batch Size","name":"batchSize","default":512,"typeOptions":{"maxValue":2048},"description":"Maximum number of documents to send in each request","type":"number"},{"displayName":"Strip New Lines","name":"stripNewLines","default":true,"description":"Whether to strip new lines from the input text","type":"boolean"},{"displayName":"Timeout","name":"timeout","default":-1,"description":"Maximum amount of time a request is allowed to take in seconds. Set to -1 for no timeout.","type":"number"}]}]


node_type: embeddingsTensorFlow
package_name: @n8n/n8n-nodes-langchain
display_name: Embeddings TensorFlow
description: Use Embeddings TensorFlow
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"The TensorFlow model we use for generating embeddings is using 512-dimensional embeddings. Please make sure to use the same dimensionality for your vector store. Be aware that running this model with high-dimensional embeddings may result in high CPU usage on the machine.","name":"notice","type":"notice","default":""}]


node_type: lmChatAnthropic
package_name: @n8n/n8n-nodes-langchain
display_name: Anthropic Chat Model
description: Language Model Anthropic
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"anthropicApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Anthropic Chat Model node documentation
  description: Learn how to use the Anthropic Chat Model node in n8n. Follow technical documentation to integrate Anthropic Chat Model node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Anthropic Chat Model node

  Use the Anthropic Chat Model node to use Anthropic's Claude family of chat models with conversational [agents](/glossary.md#ai-agent).

  On this page, you'll find the node parameters for the Anthropic Chat Model node, and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/anthropic.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Model**: Select the model that generates the completion. Choose from:
  	* **Claude**
  	* **Claude Instant**

  Learn more in the [Anthropic model documentation](https://docs.anthropic.com/claude/reference/selecting-a-model){:target=_blank .external-link}.

  ## Node options

  * **Maximum Number of Tokens**: Enter the maximum number of tokens used, which sets the completion length.
  * **Sampling Temperature**: Use this option to control the randomness of the sampling process. A higher temperature creates more diverse sampling, but increases the risk of hallucinations.
  * **Top K**: Enter the number of token choices the model uses to generate the next token.
  * **Top P**: Use this option to set the probability the completion should use. Use a lower value to ignore less probable options. 

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'anthropic-chat-model') ]]

  ## Related resources

  Refer to [LangChains's Anthropic documentation](https://js.langchain.com/docs/integrations/chat/anthropic/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"

  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Model","name":"model","type":"options","options":[{"name":"Claude","value":"claude-2"},{"name":"Claude Instant","value":"claude-instant-1"}],"description":"The model which will generate the completion. <a href=\"https://docs.anthropic.com/claude/reference/selecting-a-model\">Learn more</a>.","default":"claude-2"},{"displayName":"Options","name":"options","placeholder":"Add Option","description":"Additional options to add","type":"collection","default":{},"options":[{"displayName":"Maximum Number of Tokens","name":"maxTokensToSample","default":32768,"description":"The maximum number of tokens to generate in the completion","type":"number"},{"displayName":"Sampling Temperature","name":"temperature","default":0.7,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.","type":"number"},{"displayName":"Top K","name":"topK","default":-1,"typeOptions":{"maxValue":1,"minValue":-1,"numberPrecision":1},"description":"Used to remove \"long tail\" low probability responses. Defaults to -1, which disables it.","type":"number"},{"displayName":"Top P","name":"topP","default":1,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered. We generally recommend altering this or temperature but not both.","type":"number"}]}]


node_type: lmGooglePalm
package_name: @n8n/n8n-nodes-langchain
display_name: Google PaLM Language Model
description: Language Model Google PaLM
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"googlePalmApi","required":true}]
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Model","name":"modelName","type":"options","description":"The model which will generate the completion. <a href=\"https://developers.generativeai.google/api/rest/generativelanguage/models/list\">Learn more</a>.","typeOptions":{"loadOptions":{"routing":{"request":{"method":"GET","url":"/v1beta3/models"},"output":{"postReceive":[{"type":"rootProperty","properties":{"property":"models"}},{"type":"filter","properties":{"pass":"={{ $responseItem.name.startsWith('models/text') }}"}},{"type":"setKeyValue","properties":{"name":"={{$responseItem.name}}","value":"={{$responseItem.name}}","description":"={{$responseItem.description}}"}},{"type":"sort","properties":{"key":"name"}}]}}}},"routing":{"send":{"type":"body","property":"model"}},"default":"models/text-bison-001"},{"displayName":"Options","name":"options","placeholder":"Add Option","description":"Additional options to add","type":"collection","default":{},"options":[{"displayName":"Maximum Number of Tokens","name":"maxOutputTokens","default":1024,"description":"The maximum number of tokens to generate in the completion","type":"number"},{"displayName":"Sampling Temperature","name":"temperature","default":0.7,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.","type":"number"},{"displayName":"Top K","name":"topK","default":40,"typeOptions":{"maxValue":1,"minValue":-1,"numberPrecision":1},"description":"Used to remove \"long tail\" low probability responses. Defaults to -1, which disables it.","type":"number"},{"displayName":"Top P","name":"topP","default":0.9,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered. We generally recommend altering this or temperature but not both.","type":"number"}]}]


node_type: lmChatAwsBedrock
package_name: @n8n/n8n-nodes-langchain
display_name: AWS Bedrock Chat Model
description: Language Model AWS Bedrock
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"aws","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: AWS Bedrock Chat Model node documentation
  description: Learn how to use the AWS Bedrock Chat Model node in n8n. Follow technical documentation to integrate AWS Bedrock Chat Model node into your workflows.
  contentType: [integration, reference]
  ---

  # AWS Bedrock Chat Model node

  The AWS Bedrock Chat Model node allows you use LLM models utilising AWS Bedrock platform.

  On this page, you'll find the node parameters for the AWS Bedrock Chat Model node, and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/aws.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"
  	
  ## Node parameters

  * **Model**: Select the model that generates the completion.

  Learn more about available models in the [Amazon Bedrock model documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html){:target=_blank .external-link}.

  ## Node options

  * **Maximum Number of Tokens**: Enter the maximum number of tokens used, which sets the completion length.
  * **Sampling Temperature**: Use this option to control the randomness of the sampling process. A higher temperature creates more diverse sampling, but increases the risk of hallucinations.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'aws-bedrock-chat-model') ]]

  ## Related resources

  Refer to [LangChains's AWS Bedrock Chat Model documentation](https://js.langchain.com/docs/integrations/chat/bedrock/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Model","name":"model","type":"options","description":"The model which will generate the completion. <a href=\"https://docs.aws.amazon.com/bedrock/latest/userguide/foundation-models.html\">Learn more</a>.","typeOptions":{"loadOptions":{"routing":{"request":{"method":"GET","url":"/foundation-models?&byOutputModality=TEXT"},"output":{"postReceive":[{"type":"rootProperty","properties":{"property":"modelSummaries"}},{"type":"filter","properties":{"pass":"={{ !['anthropic.claude-instant-v1-100k'].includes($responseItem.modelId) }}"}},{"type":"setKeyValue","properties":{"name":"={{$responseItem.modelName}}","description":"={{$responseItem.modelArn}}","value":"={{$responseItem.modelId}}"}},{"type":"sort","properties":{"key":"name"}}]}}}},"routing":{"send":{"type":"body","property":"model"}},"default":""},{"displayName":"Options","name":"options","placeholder":"Add Option","description":"Additional options to add","type":"collection","default":{},"options":[{"displayName":"Maximum Number of Tokens","name":"maxTokensToSample","default":2000,"description":"The maximum number of tokens to generate in the completion","type":"number"},{"displayName":"Sampling Temperature","name":"temperature","default":0.7,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.","type":"number"}]}]


node_type: lmChatGooglePalm
package_name: @n8n/n8n-nodes-langchain
display_name: Google PaLM Chat Model
description: Chat Model Google PaLM
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"googlePalmApi","required":true}]
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Model","name":"modelName","type":"options","description":"The model which will generate the completion. <a href=\"https://developers.generativeai.google/api/rest/generativelanguage/models/list\">Learn more</a>.","typeOptions":{"loadOptions":{"routing":{"request":{"method":"GET","url":"/v1beta3/models"},"output":{"postReceive":[{"type":"rootProperty","properties":{"property":"models"}},{"type":"filter","properties":{"pass":"={{ $responseItem.name.startsWith('models/chat') }}"}},{"type":"setKeyValue","properties":{"name":"={{$responseItem.name}}","value":"={{$responseItem.name}}","description":"={{$responseItem.description}}"}},{"type":"sort","properties":{"key":"name"}}]}}}},"routing":{"send":{"type":"body","property":"model"}},"default":"models/chat-bison-001"},{"displayName":"Options","name":"options","placeholder":"Add Option","description":"Additional options to add","type":"collection","default":{},"options":[{"displayName":"Sampling Temperature","name":"temperature","default":0.7,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.","type":"number"},{"displayName":"Top K","name":"topK","default":40,"typeOptions":{"maxValue":1,"minValue":-1,"numberPrecision":1},"description":"Used to remove \"long tail\" low probability responses. Defaults to -1, which disables it.","type":"number"},{"displayName":"Top P","name":"topP","default":0.9,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered. We generally recommend altering this or temperature but not both.","type":"number"}]}]


node_type: lmChatOllama
package_name: @n8n/n8n-nodes-langchain
display_name: Ollama Chat Model
description: Language Model Ollama
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"ollamaApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Ollama Chat Model node documentation
  description: Learn how to use the Ollama Chat Model node in n8n. Follow technical documentation to integrate Ollama Chat Model node into your workflows.
  contentType: [integration, reference]
  priority: high
  ---

  # Ollama Chat Model node

  The Ollama Chat Model node allows you use local Llama 2 models with conversational [agents](/glossary.md#ai-agent).

  On this page, you'll find the node parameters for the Ollama Chat Model node, and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/ollama.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Model**: Select the model that generates the completion. Choose from:
  	* **Llama2**
  	* **Llama2 13B**
  	* **Llama2 70B**
  	* **Llama2 Uncensored**

  Refer to the Ollama [Models Library documentation](https://ollama.com/library){:target=_blank .external-link} for more information about available models.

  ## Node options

  * **Sampling Temperature**: Use this option to control the randomness of the sampling process. A higher temperature creates more diverse sampling, but increases the risk of hallucinations.
  * **Top K**: Enter the number of token choices the model uses to generate the next token.
  * **Top P**: Use this option to set the probability the completion should use. Use a lower value to ignore less probable options. 

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'ollama-chat-model') ]]

  ## Related resources

  Refer to [LangChains's Ollama Chat Model documentation](https://js.langchain.com/docs/integrations/chat/ollama/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"

  ## Common issues

  For common questions or issues and suggested solutions, refer to [Common issues](/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatollama/common-issues.md).

  --8<-- "_glossary/ai-glossary.md"

  --8<-- "_snippets/self-hosting/starter-kits/self-hosted-ai-starter-kit.md"

properties_schema:
  [{"displayName":"Model","name":"model","type":"options","default":"llama2","description":"The model which will generate the completion. To download models, visit <a href=\"https://ollama.ai/library\">Ollama Models Library</a>.","typeOptions":{"loadOptions":{"routing":{"request":{"method":"GET","url":"/api/tags"},"output":{"postReceive":[{"type":"rootProperty","properties":{"property":"models"}},{"type":"setKeyValue","properties":{"name":"={{$responseItem.name}}","value":"={{$responseItem.name}}"}},{"type":"sort","properties":{"key":"name"}}]}}}},"routing":{"send":{"type":"body","property":"model"}},"required":true},{"displayName":"Options","name":"options","placeholder":"Add Option","description":"Additional options to add","type":"collection","default":{},"options":[{"displayName":"Sampling Temperature","name":"temperature","default":0.7,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.","type":"number"},{"displayName":"Top K","name":"topK","default":-1,"typeOptions":{"maxValue":1,"minValue":-1,"numberPrecision":1},"description":"Used to remove \"long tail\" low probability responses. Defaults to -1, which disables it.","type":"number"},{"displayName":"Top P","name":"topP","default":1,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered. We generally recommend altering this or temperature but not both.","type":"number"}]}]


node_type: lmChatOpenAi
package_name: @n8n/n8n-nodes-langchain
display_name: OpenAI Chat Model
description: For advanced usage with an AI chain
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"openAiApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: OpenAI Chat Model node documentation
  description: Learn how to use the OpenAI Chat Model node in n8n. Follow technical documentation to integrate OpenAI Chat Model node into your workflows.
  contentType: [integration, reference]
  priority: high
  ---

  # OpenAI Chat Model node

  Use the OpenAI Chat Model node to use OpenAI's chat models with conversational [agents](/glossary.md#ai-agent).

  On this page, you'll find the node parameters for the OpenAI Chat Model node and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/openai.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  ### Model

  Select the model to use to generate the completion.

  n8n dynamically loads models from OpenAI and you'll only see the models available to your account.

  ## Node options

  Use these options to further refine the node's behavior.

  ### Base URL

  Enter a URL here to override the default URL for the API.

  ### Frequency Penalty

  Use this option to control the chances of the model repeating itself. Higher values reduce the chance of the model repeating itself.

  ### Maximum Number of Tokens

  Enter the maximum number of tokens used, which sets the completion length.

  ### Response Format

  Choose **Text** or **JSON**. **JSON** ensures the model returns valid JSON.

  ### Presence Penalty

  Use this option to control the chances of the model talking about new topics. Higher values increase the chance of the model talking about new topics.

  ### Sampling Temperature

  Use this option to control the randomness of the sampling process. A higher temperature creates more diverse sampling, but increases the risk of hallucinations.

  ### Timeout

  Enter the maximum request time in milliseconds.

  ### Max Retries

  Enter the maximum number of times to retry a request.

  ### Top P

  Use this option to set the probability the completion should use. Use a lower value to ignore less probable options. 

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'openai-chat-model') ]]

  ## Related resources

  Refer to [LangChains's OpenAI documentation](https://js.langchain.com/docs/integrations/chat/openai/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"

  ## Common issues

  For common questions or issues and suggested solutions, refer to [Common issues](/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatopenai/common-issues.md).

  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Model","name":"model","type":"options","description":"The model which will generate the completion. <a href=\"https://beta.openai.com/docs/models/overview\">Learn more</a>.","typeOptions":{"loadOptions":{"routing":{"request":{"method":"GET","url":"={{ $parameter.options?.baseURL?.split(\"/\").slice(-1).pop() || \"v1\"  }}/models"},"output":{"postReceive":[{"type":"rootProperty","properties":{"property":"data"}},{"type":"filter","properties":{"pass":"={{ $responseItem.id.startsWith('gpt-') && !$responseItem.id.includes('instruct') }}"}},{"type":"setKeyValue","properties":{"name":"={{$responseItem.id}}","value":"={{$responseItem.id}}"}},{"type":"sort","properties":{"key":"name"}}]}}}},"routing":{"send":{"type":"body","property":"model"}},"default":"gpt-3.5-turbo"},{"displayName":"Options","name":"options","placeholder":"Add Option","description":"Additional options to add","type":"collection","default":{},"options":[{"displayName":"Base URL","name":"baseURL","default":"https://api.openai.com/v1","description":"Override the default base URL for the API","type":"string"},{"displayName":"Frequency Penalty","name":"frequencyPenalty","default":0,"typeOptions":{"maxValue":2,"minValue":-2,"numberPrecision":1},"description":"Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim","type":"number"},{"displayName":"Maximum Number of Tokens","name":"maxTokens","default":-1,"description":"The maximum number of tokens to generate in the completion. Most models have a context length of 2048 tokens (except for the newest models, which support 32,768).","type":"number","typeOptions":{"maxValue":32768}},{"displayName":"Presence Penalty","name":"presencePenalty","default":0,"typeOptions":{"maxValue":2,"minValue":-2,"numberPrecision":1},"description":"Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics","type":"number"},{"displayName":"Sampling Temperature","name":"temperature","default":0.7,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.","type":"number"},{"displayName":"Timeout","name":"timeout","default":0,"description":"Maximum amount of time a request is allowed to take in seconds","type":"number"},{"displayName":"Top P","name":"topP","default":1,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered. We generally recommend altering this or temperature but not both.","type":"number"}]}]


node_type: lmOpenAi
package_name: @n8n/n8n-nodes-langchain
display_name: OpenAI Model
description: For advanced usage with an AI chain
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"openAiApi","required":true}]
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Model","name":"model","type":"options","description":"The model which will generate the completion. <a href=\"https://beta.openai.com/docs/models/overview\">Learn more</a>.","typeOptions":{"loadOptions":{"routing":{"request":{"method":"GET","url":"={{ $parameter.options?.baseURL?.split(\"/\").slice(-1).pop() || \"v1\"  }}/models"},"output":{"postReceive":[{"type":"rootProperty","properties":{"property":"data"}},{"type":"filter","properties":{"pass":"={{$responseItem.owned_by.startsWith('system')"}},{"type":"setKeyValue","properties":{"name":"={{$responseItem.id}}","value":"={{$responseItem.id}}"}},{"type":"sort","properties":{"key":"name"}}]}}}},"routing":{"send":{"type":"body","property":"model"}},"default":"gpt-3.5-turbo-instruct"},{"displayName":"Options","name":"options","placeholder":"Add Option","description":"Additional options to add","type":"collection","default":{},"options":[{"displayName":"Base URL","name":"baseURL","default":"https://api.openai.com/v1","description":"Override the default base URL for the API","type":"string"},{"displayName":"Frequency Penalty","name":"frequencyPenalty","default":0,"typeOptions":{"maxValue":2,"minValue":-2,"numberPrecision":1},"description":"Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim","type":"number"},{"displayName":"Maximum Number of Tokens","name":"maxTokens","default":-1,"description":"The maximum number of tokens to generate in the completion. Most models have a context length of 2048 tokens (except for the newest models, which support 32,768).","type":"number","typeOptions":{"maxValue":32768}},{"displayName":"Presence Penalty","name":"presencePenalty","default":0,"typeOptions":{"maxValue":2,"minValue":-2,"numberPrecision":1},"description":"Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics","type":"number"},{"displayName":"Sampling Temperature","name":"temperature","default":0.7,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.","type":"number"},{"displayName":"Timeout","name":"timeout","default":0,"description":"Maximum amount of time a request is allowed to take in seconds","type":"number"},{"displayName":"Top P","name":"topP","default":1,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered. We generally recommend altering this or temperature but not both.","type":"number"}]}]


node_type: lmCohere
package_name: @n8n/n8n-nodes-langchain
display_name: Cohere Model
description: Language Model Cohere
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"cohereApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Cohere Model node documentation
  description: Learn how to use the Cohere Model node in n8n. Follow technical documentation to integrate Cohere Model node into your workflows.
  contentType: [integration, reference]
  ---

  # Cohere Model node

  Use the Cohere Model node to use Cohere's models.

  On this page, you'll find the node parameters for the Cohere Model node, and links to more resources.

  This node lacks tools support, so it won't work with the [AI Agent](/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/index.md) node. Instead, connect it with the [Basic LLM Chain](/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainllm.md) node.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/cohere.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node Options

  * **Maximum Number of Tokens**: Enter the maximum number of tokens used, which sets the completion length.
  * **Sampling Temperature**: Use this option to control the randomness of the sampling process. A higher temperature creates more diverse sampling, but increases the risk of hallucinations.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'cohere-model') ]]

  ## Related resources

  Refer to [LangChains's Cohere documentation](https://js.langchain.com/docs/integrations/llms/cohere/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Options","name":"options","placeholder":"Add Option","description":"Additional options to add","type":"collection","default":{},"options":[{"displayName":"Maximum Number of Tokens","name":"maxTokens","default":250,"description":"The maximum number of tokens to generate in the completion. Most models have a context length of 2048 tokens (except for the newest models, which support 32,768).","type":"number","typeOptions":{"maxValue":32768}},{"displayName":"Model","name":"model","type":"string","description":"The name of the model to use","default":""},{"displayName":"Sampling Temperature","name":"temperature","default":0,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.","type":"number"}]}]


node_type: lmOllama
package_name: @n8n/n8n-nodes-langchain
display_name: Ollama Model
description: Language Model Ollama
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"ollamaApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Ollama Model node documentation
  description: Learn how to use the Ollama Model node in n8n. Follow technical documentation to integrate Ollama Model node into your workflows.
  contentType: [integration, reference]
  priority: high
  ---

  # Ollama Model node

  The Ollama Model node allows you use local Llama 2 models.

  On this page, you'll find the node parameters for the Ollama Model node, and links to more resources.

  This node lacks tools support, so it won't work with the [AI Agent](/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/index.md) node. Instead, connect it with the [Basic LLM Chain](/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainllm.md) node.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/ollama.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Model**: Select the model that generates the completion. Choose from:
  	* **Llama2**
  	* **Llama2 13B**
  	* **Llama2 70B**
  	* **Llama2 Uncensored**

  Refer to the Ollama [Models Library documentation](https://ollama.com/library){:target=_blank .external-link} for more information about available models.

  ## Node options

  * **Sampling Temperature**: Use this option to control the randomness of the sampling process. A higher temperature creates more diverse sampling, but increases the risk of hallucinations.
  * **Top K**: Enter the number of token choices the model uses to generate the next token.
  * **Top P**: Use this option to set the probability the completion should use. Use a lower value to ignore less probable options.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'ollama-model') ]]

  ## Related resources

  Refer to [LangChains's Ollama documentation](https://js.langchain.com/docs/integrations/llms/ollama/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"

  ## Common issues

  For common questions or issues and suggested solutions, refer to [Common issues](/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmollama/common-issues.md).

  --8<-- "_glossary/ai-glossary.md"

  --8<-- "_snippets/self-hosting/starter-kits/self-hosted-ai-starter-kit.md"

properties_schema:
  [{"displayName":"Model","name":"model","type":"options","default":"llama2","description":"The model which will generate the completion. To download models, visit <a href=\"https://ollama.ai/library\">Ollama Models Library</a>.","typeOptions":{"loadOptions":{"routing":{"request":{"method":"GET","url":"/api/tags"},"output":{"postReceive":[{"type":"rootProperty","properties":{"property":"models"}},{"type":"setKeyValue","properties":{"name":"={{$responseItem.name}}","value":"={{$responseItem.name}}"}},{"type":"sort","properties":{"key":"name"}}]}}}},"routing":{"send":{"type":"body","property":"model"}},"required":true},{"displayName":"Options","name":"options","placeholder":"Add Option","description":"Additional options to add","type":"collection","default":{},"options":[{"displayName":"Sampling Temperature","name":"temperature","default":0.7,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.","type":"number"},{"displayName":"Top K","name":"topK","default":-1,"typeOptions":{"maxValue":1,"minValue":-1,"numberPrecision":1},"description":"Used to remove \"long tail\" low probability responses. Defaults to -1, which disables it.","type":"number"},{"displayName":"Top P","name":"topP","default":1,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered. We generally recommend altering this or temperature but not both.","type":"number"}]}]


node_type: lmOpenHuggingFaceInference
package_name: @n8n/n8n-nodes-langchain
display_name: Hugging Face Inference Model
description: Language Model HuggingFaceInference
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"huggingFaceApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Hugging Face Inference Model node documentation
  description: Learn how to use the Hugging Face Inference Model node in n8n. Follow technical documentation to integrate Hugging Face Inference Model node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Hugging Face Inference Model node

  Use the Hugging Face Inference Model node to use Hugging Face's models.

  On this page, you'll find the node parameters for the Hugging Face Inference Model node, and links to more resources.

  This node lacks tools support, so it won't work with the [AI Agent](/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/index.md) node. Instead, connect it with the [Basic LLM Chain](/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainllm.md) node.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/huggingface.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Model**: Select the model to use to generate the completion.

  ## Node options

  * **Custom Inference Endpoint**: Enter a custom inference endpoint URL.
  * **Frequency Penalty**: Use this option to control the chances of the model repeating itself. Higher values reduce the chance of the model repeating itself.
  * **Maximum Number of Tokens**: Enter the maximum number of tokens used, which sets the completion length.
  * **Presence Penalty**: Use this option to control the chances of the model talking about new topics. Higher values increase the chance of the model talking about new topics.
  * **Sampling Temperature**: Use this option to control the randomness of the sampling process. A higher temperature creates more diverse sampling, but increases the risk of hallucinations.
  * **Top K**: Enter the number of token choices the model uses to generate the next token.
  * **Top P**: Use this option to set the probability the completion should use. Use a lower value to ignore less probable options.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'hugging-face-inference-model') ]]

  ## Related resources

  Refer to [LangChains's Hugging Face Inference Model documentation](https://js.langchain.com/docs/integrations/llms/huggingface_inference/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Model","name":"model","type":"string","default":"gpt2"},{"displayName":"Options","name":"options","placeholder":"Add Option","description":"Additional options to add","type":"collection","default":{},"options":[{"displayName":"Custom Inference Endpoint","name":"endpointUrl","default":"","description":"Custom endpoint URL","type":"string"},{"displayName":"Frequency Penalty","name":"frequencyPenalty","default":0,"typeOptions":{"maxValue":2,"minValue":-2,"numberPrecision":1},"description":"Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim","type":"number"},{"displayName":"Maximum Number of Tokens","name":"maxTokens","default":128,"description":"The maximum number of tokens to generate in the completion. Most models have a context length of 2048 tokens (except for the newest models, which support 32,768).","type":"number","typeOptions":{"maxValue":32768}},{"displayName":"Presence Penalty","name":"presencePenalty","default":0,"typeOptions":{"maxValue":2,"minValue":-2,"numberPrecision":1},"description":"Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics","type":"number"},{"displayName":"Sampling Temperature","name":"temperature","default":1,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls randomness: Lowering results in less random completions. As the temperature approaches zero, the model will become deterministic and repetitive.","type":"number"},{"displayName":"Top K","name":"topK","default":1,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls the top tokens to consider within the sample operation to create new text","type":"number"},{"displayName":"Top P","name":"topP","default":1,"typeOptions":{"maxValue":1,"minValue":0,"numberPrecision":1},"description":"Controls diversity via nucleus sampling: 0.5 means half of all likelihood-weighted options are considered. We generally recommend altering this or temperature but not both.","type":"number"}]}]


node_type: memoryBufferWindow
package_name: @n8n/n8n-nodes-langchain
display_name: Window Buffer Memory
description: Stores the chat history in a windowed buffer. Refreshes on restart.
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Simple Memory node documentation
  description: Learn how to use the Simple Memory node in n8n. Follow technical documentation to integrate Simple Memory node into your workflows.
  contentType: [integration, reference]
  priority: high
  ---

  # Simple Memory node

  Use the Simple Memory node to [persist](/glossary.md#ai-memory) chat history in your workflow.

  On this page, you'll find a list of operations the Simple Memory node supports, and links to more resources.

  /// warning | Don't use this node if running n8n in queue mode
  If your n8n instance uses [queue mode](/hosting/scaling/queue-mode.md), this node doesn't work in an active production workflow. This is because n8n can't guarantee that every call to Simple Memory will go to the same worker.
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  Configure these parameters to configure the node:

  * **Session Key**: Enter the key to use to store the memory in the workflow data.
  * **Context Window Length**: Enter the number of previous interactions to consider for context.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'window-buffer-memory') ]]

  ## Related resources

  Refer to [LangChain's Buffer Window Memory documentation](https://v03.api.js.langchain.com/classes/langchain.memory.BufferWindowMemory.html){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"

  ## Common issues

  For common questions or issues and suggested solutions, refer to [Common issues](/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.memorybufferwindow/common-issues.md).

  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Session Key","name":"sessionKey","type":"string","default":"chat_history","description":"The key to use to store the memory in the workflow data"},{"displayName":"Context Window Length","name":"contextWindowLength","type":"number","default":5,"description":"The number of previous messages to consider for context"}]


node_type: memoryMotorhead
package_name: @n8n/n8n-nodes-langchain
display_name: Motorhead
description: Use Motorhead Memory
category: transform
development_style: programmatic
version: 1
properties_schema: [{"displayName":"Session ID","name":"sessionId","type":"string","required":true,"default":""}]
operations: []
credentials_required: [{"name":"motorheadApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Motorhead node documentation
  description: Learn how to use the Motorhead node in n8n. Follow technical documentation to integrate Motorhead node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Motorhead node

  Use the Motorhead node to use Motorhead as a [memory](/glossary.md#ai-memory) server.

  On this page, you'll find a list of operations the Motorhead node supports, and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/motorhead.md).
  ///

  ## Node parameters

  * **Session ID**: Enter the ID to use to store the memory in the workflow data.

  ## Node reference

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'motorhead') ]]

  ## Related resources

  Refer to [LangChain's Motorhead documentation](https://js.langchain.com/docs/integrations/memory/motorhead_memory){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"

  ## Single memory instance

  [[% include "_includes/integrations/cluster-nodes/memory-shared.html" %]]

  --8<-- "_glossary/ai-glossary.md"


node_type: memoryRedisChat
package_name: @n8n/n8n-nodes-langchain
display_name: Redis Chat Memory
description: Stores the chat history in Redis.
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"redis","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Redis Chat Memory node documentation
  description: Learn how to use the Redis Chat Memory node in n8n. Follow technical documentation to integrate Redis Chat Memory node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Redis Chat Memory node

  Use the Redis Chat Memory node to use Redis as a [memory](/glossary.md#ai-memory) server.

  On this page, you'll find a list of operations the Redis Chat Memory node supports, and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/redis.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Session Key**: Enter the key to use to store the memory in the workflow data.
  * **Session Time To Live**: Use this parameter to make the session expire after a given number of seconds.
  * **Context Window Length**: Enter the number of previous interactions to consider for context.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'redis-chat-memory') ]]

  ## Related resources

  Refer to [LangChain's Redis Chat Memory documentation](https://js.langchain.com/docs/integrations/memory/redis){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"

  ## Single memory instance

  [[% include "_includes/integrations/cluster-nodes/memory-shared.html" %]]

  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Session Key","name":"sessionKey","type":"string","default":"chat_history","description":"The key to use to store the memory in the workflow data"},{"displayName":"Session Time To Live","name":"sessionTTL","type":"number","default":0,"description":"For how long the session should be stored in seconds. If set to 0 it will not expire."}]


node_type: memoryChatRetriever
package_name: @n8n/n8n-nodes-langchain
display_name: Chat Messages Retriever
description: Retrieve chat messages from memory and use them in the workflow
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Simplify Output","name":"simplifyOutput","type":"boolean","description":"Whether to simplify the output to only include the sender and the text","default":true}]


node_type: memoryXata
package_name: @n8n/n8n-nodes-langchain
display_name: Xata
description: Use Xata Memory
category: transform
development_style: programmatic
version: 1
properties_schema: [{"displayName":"Session ID","name":"sessionId","type":"string","required":true,"default":""}]
operations: []
credentials_required: [{"name":"xataApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Xata node documentation
  description: Learn how to use the Xata node in n8n. Follow technical documentation to integrate Xata node into your workflows.
  contentType: [integration, reference]
  ---

  # Xata node

  Use the Xata node to use Xata as a [memory](/glossary.md#ai-memory) server.
  On this page, you'll find a list of operations the Xata node supports, and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/xata.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  -   **Session ID**: Enter the ID to use to store the memory in the workflow data.
  -   **Context Window Length**: Enter the number of previous interactions to consider for context.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'xata') ]]

  ## Related resources

  Refer to [LangChain's Xata documentation](https://js.langchain.com/docs/integrations/memory/xata){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"

  ## Single memory instance

  [[% include "_includes/integrations/cluster-nodes/memory-shared.html" %]]

  --8<-- "_glossary/ai-glossary.md"


node_type: memoryZep
package_name: @n8n/n8n-nodes-langchain
display_name: Zep
description: Use Zep Memory
category: transform
development_style: programmatic
version: 1
properties_schema: [{"displayName":"Session ID","name":"sessionId","type":"string","required":true,"default":""}]
operations: []
credentials_required: [{"name":"zepApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Zep node documentation
  description: Learn how to use the Zep node in n8n. Follow technical documentation to integrate Zep node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Zep node

  Use the Zep node to use Zep as a [memory](/glossary.md#ai-memory) server.

  On this page, you'll find a list of operations the Zep node supports, and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/zep.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Session ID**: Enter the ID to use to store the memory in the workflow data.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'zep') ]]

  ## Related resources

  Refer to [LangChain's Zep documentation](https://js.langchain.com/docs/integrations/memory/zep_memory){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"

  ## Single memory instance

  [[% include "_includes/integrations/cluster-nodes/memory-shared.html" %]]

  --8<-- "_glossary/ai-glossary.md"


node_type: outputParserAutofixing
package_name: @n8n/n8n-nodes-langchain
display_name: Auto-fixing Output Parser
description: Automatically fix the output if it is not in the correct format
category: transform
development_style: programmatic
version: 1
properties_schema: []
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Auto-fixing Output Parser node documentation
  description: Learn how to use the Auto-fixing Output Parser node in n8n. Follow technical documentation to integrate Auto-fixing Output Parser node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Auto-fixing Output Parser node

  The Auto-fixing Output Parser node wraps another output parser. If the first one fails, it calls out to another LLM to fix any errors.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'auto-fixing-output-parser') ]]

  ## Related resources

  Refer to [LangChain's output parser documentation](https://js.langchain.com/docs/concepts/output_parsers/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"


node_type: outputParserItemList
package_name: @n8n/n8n-nodes-langchain
display_name: Item List Output Parser
description: Return the results as separate items
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Item List Output Parser node documentation
  description: Learn how to use the Item List Output Parser node in n8n. Follow technical documentation to integrate Item List Output Parser node into your workflows.
  contentType: [integration, reference]
  priority: high
  ---

  # Item List Output Parser node

  Use the Item List Output Parser node to return a list of items with a specific length and separator.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node options

  * **Number of Items**: Enter the maximum items to return. Set to `-1` for unlimited items.
  * **Separator**: Select the separator used to split the results into separate items. Defaults to a new line.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'item-list-output-parser') ]]

  ## Related resources

  Refer to [LangChain's output parser documentation](https://js.langchain.com/docs/concepts/output_parsers){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Number Of Items","name":"numberOfItems","type":"number","default":-1,"description":"Defines many many items should be returned maximally. If set to -1, there is no limit."},{"displayName":"Separator","name":"separator","type":"string","default":"\\n","description":"Defines the separator that should be used to split the results into separate items. Defaults to a new line but can be changed depending on the data that should be returned."}]}]


node_type: outputParserStructured
package_name: @n8n/n8n-nodes-langchain
display_name: Structured Output Parser
description: Return data in a defined JSON format
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Structured Output Parser node documentation
  description: Learn how to use the Structured Output Parser node in n8n. Follow technical documentation to integrate Structured Output Parser node into your workflows.
  contentType: [integration, reference]
  priority: high
  ---

  # Structured Output Parser node

  Use the Structured Output Parser node to return fields based on a JSON Schema.

  On this page, you'll find the node parameters for the Structured Output Parser node, and links to more resources.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Schema Type**: Define the output structure and validation. You have two options to provide the schema:

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-sub-nodes/schema-type-structuring.md"

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'structured-output-parser') ]]

  ## Related resources

  Refer to [LangChain's output parser documentation](https://js.langchain.com/docs/concepts/output_parsers){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"

  ## Common issues

  For common questions or issues and suggested solutions, refer to [Common issues](/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.outputparserstructured/common-issues.md).

  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"JSON Schema","name":"jsonSchema","type":"json","description":"JSON Schema to structure and validate the output against","default":"{\n  \"type\": \"object\",\n  \"properties\": {\n    \"state\": {\n      \"type\": \"string\"\n    },\n    \"cities\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"string\"\n      }\n    }\n  }\n}","typeOptions":{"rows":10,"editor":"json","editorLanguage":"json"},"required":true},{"displayName":"The schema has to be defined in the <a target=\"_blank\" href=\"https://json-schema.org/\">JSON Schema</a> format. Look at <a target=\"_blank\" href=\"https://json-schema.org/learn/miscellaneous-examples.html\">this</a> page for examples.","name":"notice","type":"notice","default":""}]


node_type: retrieverContextualCompression
package_name: @n8n/n8n-nodes-langchain
display_name: Contextual Compression Retriever
description: Enhances document similarity search by contextual compression.
category: transform
development_style: programmatic
version: 1
properties_schema: []
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Contextual Compression Retriever node documentation
  description: Learn how to use the Contextual Compression Retriever node in n8n. Follow technical documentation to integrate Contextual Compression Retriever node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Contextual Compression Retriever node

  The Contextual Compression Retriever node improves the answers returned from [vector store](/glossary.md#ai-vector-store) document similarity searches by taking into account the context from the query.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'contextual-compression-retriever') ]]

  ## Related resources

  Refer to [LangChain's contextual compression retriever documentation](https://js.langchain.com/docs/how_to/contextual_compression/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"


node_type: retrieverVectorStore
package_name: @n8n/n8n-nodes-langchain
display_name: Vector Store Retriever
description: Use a Vector Store as Retriever
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Vector Store Retriever node documentation
  description: Learn how to use the Vector Store Retriever node in n8n. Follow technical documentation to integrate Vector Store Retriever node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Vector Store Retriever node

  Use the Vector Store Retriever node to retrieve documents from a [vector store](/glossary.md#ai-vector-store).

  On this page, you'll find the node parameters for the Vector Store Retriever node, and links to more resources.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Limit**: Enter the maximum number of results to return.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'vector-store-retriever') ]]

  ## Related resources

  Refer to [LangChain's vector store retriever documentation](https://js.langchain.com/docs/how_to/vectorstore_retriever/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Top K","name":"topK","type":"number","default":4,"description":"Number of top results to fetch from vector store"}]


node_type: retrieverMultiQuery
package_name: @n8n/n8n-nodes-langchain
display_name: MultiQuery Retriever
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
description:
  Automates prompt tuning, generates diverse queries and expands document pool for enhanced retrieval.

documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: MultiQuery Retriever node documentation
  description: Learn how to use the MultiQuery Retriever node in n8n. Follow technical documentation to integrate MultiQuery Retriever node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # MultiQuery Retriever node

  The MultiQuery Retriever node automates the process of prompt tuning by using an LLM to generate multiple queries from different perspectives for a given user input query.

  On this page, you'll find the node parameters for the MultiQuery Retriever node, and links to more resources.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node options

  * **Query Count**: Enter how many different versions of the query to generate.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'multiquery-retriever') ]]

  ## Related resources

  Refer to [LangChain's retriever conceptual documentation](https://js.langchain.com/docs/concepts/retrievers){:target=_blank .external-link} and [LangChain's multiquery retriever API documentation](https://v03.api.js.langchain.com/classes/langchain.retrievers_multi_query.MultiQueryRetriever.html){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Options","name":"options","placeholder":"Add Option","description":"Additional options to add","type":"collection","default":{},"options":[{"displayName":"Query Count","name":"queryCount","default":3,"typeOptions":{"minValue":1},"description":"Number of different versions of the given question to generate","type":"number"}]}]


node_type: retrieverWorkflow
package_name: @n8n/n8n-nodes-langchain
display_name: Workflow Retriever
description: Use an n8n Workflow as Retriever
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Workflow Retriever node documentation
  description: Learn how to use the Workflow Retriever node in n8n. Follow technical documentation to integrate Workflow Retriever node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Workflow Retriever node

  Use the Workflow Retriever node to retrieve data from an n8n workflow for use in a Retrieval QA Chain or another Retriever node.

  On this page, you'll find the node parameters for the Workflow Retriever node, and links to more resources.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  ### Source

  Tell n8n which workflow to call. You can choose either:

  * **Database** and enter a workflow ID.
  * **Parameter** and copy in a complete [workflow JSON](/workflows/export-import.md).

  ### Workflow values

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-sub-nodes/workflow-values.md"

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'workflow-retriever') ]]

  ## Related resources

  Refer to [LangChain's general retriever documentation](https://js.langchain.com/docs/concepts/retrievers/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"The workflow will receive \"query\" as input and the output of the last node will be returned and converted to Documents","name":"executeNotice","type":"notice","default":""},{"displayName":"Source","name":"source","type":"options","options":[{"name":"Database","value":"database","description":"Load the workflow from the database by ID"},{"name":"Parameter","value":"parameter","description":"Load the workflow from a parameter"}],"default":"database","description":"Where to get the workflow to execute from"},{"displayName":"Workflow ID","name":"workflowId","type":"string","displayOptions":{"show":{"source":["database"]}},"default":"","required":true,"description":"The workflow to execute"},{"displayName":"Workflow JSON","name":"workflowJson","type":"string","typeOptions":{"editor":"json","rows":10},"displayOptions":{"show":{"source":["parameter"]}},"default":"\n\n\n","required":true,"description":"The workflow JSON code to execute"},{"displayName":"Workflow Values","name":"fields","placeholder":"Add Value","type":"fixedCollection","description":"Set the values which should be made available in the workflow","typeOptions":{"multipleValues":true,"sortable":true},"default":{},"options":[{"name":"values","displayName":"Values","values":[{"displayName":"Name","name":"name","type":"string","default":"","placeholder":"e.g. fieldName","description":"Name of the field to set the value of. Supports dot-notation. Example: data.person[0].name.","requiresDataPath":"single"},{"displayName":"Type","name":"type","type":"options","description":"The field value type","options":[{"name":"String","value":"stringValue"},{"name":"Number","value":"numberValue"},{"name":"Boolean","value":"booleanValue"},{"name":"Array","value":"arrayValue"},{"name":"Object","value":"objectValue"}],"default":"stringValue"},{"displayName":"Value","name":"stringValue","type":"string","default":"","displayOptions":{"show":{"type":["stringValue"]}},"validateType":"string","ignoreValidationDuringExecution":true},{"displayName":"Value","name":"numberValue","type":"string","default":"","displayOptions":{"show":{"type":["numberValue"]}},"validateType":"number","ignoreValidationDuringExecution":true},{"displayName":"Value","name":"booleanValue","type":"options","default":"true","options":[{"name":"True","value":"true"},{"name":"False","value":"false"}],"displayOptions":{"show":{"type":["booleanValue"]}},"validateType":"boolean","ignoreValidationDuringExecution":true},{"displayName":"Value","name":"arrayValue","type":"string","default":"","placeholder":"e.g. [ arrayItem1, arrayItem2, arrayItem3 ]","displayOptions":{"show":{"type":["arrayValue"]}},"validateType":"array","ignoreValidationDuringExecution":true},{"displayName":"Value","name":"objectValue","type":"string","default":"={}","typeOptions":{"editor":"json","editorLanguage":"json","rows":2},"displayOptions":{"show":{"type":["objectValue"]}},"validateType":"object","ignoreValidationDuringExecution":true}]}]}]


node_type: textSplitterCharacterTextSplitter
package_name: @n8n/n8n-nodes-langchain
display_name: Character Text Splitter
description: Split text into chunks by characters
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Character Text Splitter node documentation
  description: Learn how to use the Character Text Splitter node in n8n. Follow technical documentation to integrate Character Text Splitter node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Character Text Splitter node

  Use the Character Text Splitter node to split document data based on characters.

  On this page, you'll find the node parameters for the Character Text Splitter node, and links to more resources.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Separator**: Select the separator used to split the document into separate items.
  * **Chunk Size**: Enter the number of characters in each chunk.
  * **Chunk Overlap**: Enter how much overlap to have between chunks.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'character-text-splitter') ]]

  ## Related resources

  Refer to [LangChain's text splitter documentation](https://js.langchain.com/docs/concepts/text_splitters){:target=_blank .external-link} and [LangChain's API documentation for character text splitting](https://v03.api.js.langchain.com/classes/langchain.text_splitter.CharacterTextSplitter.html){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Separator","name":"separator","type":"string","default":""},{"displayName":"Chunk Size","name":"chunkSize","type":"number","default":1000},{"displayName":"Chunk Overlap","name":"chunkOverlap","type":"number","default":0}]


node_type: textSplitterRecursiveCharacterTextSplitter
package_name: @n8n/n8n-nodes-langchain
display_name: Recursive Character Text Splitter
description: Split text into chunks by characters recursively, recommended for most use cases
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Recursive Character Text Splitter node documentation
  description: Learn how to use the Recursive Character Text Splitter node in n8n. Follow technical documentation to integrate Recursive Character Text Splitter node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Recursive Character Text Splitter node

  The Recursive Character Text Splitter node splits document data recursively to keep all paragraphs, sentences then words together as long as possible.

  On this page, you'll find the node parameters for the Recursive Character Text Splitter node, and links to more resources.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Chunk Size**: Enter the number of characters in each chunk.
  * **Chunk Overlap**: Enter how much overlap to have between chunks.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'recursive-character-text-splitter') ]]

  ## Related resources

  Refer to [LangChain's text splitter documentation](https://js.langchain.com/docs/concepts/text_splitters){:target=_blank .external-link} and [LangChain's recursively split by character documentation](https://v03.api.js.langchain.com/classes/langchain.text_splitter.RecursiveCharacterTextSplitter.html){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Chunk Size","name":"chunkSize","type":"number","default":1000},{"displayName":"Chunk Overlap","name":"chunkOverlap","type":"number","default":0}]


node_type: textSplitterTokenSplitter
package_name: @n8n/n8n-nodes-langchain
display_name: Token Splitter
description: Split text into chunks by tokens
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Token Splitter node documentation
  description: Learn how to use the Token Splitter node in n8n. Follow technical documentation to integrate Token Splitter node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Token Splitter node

  The Token Splitter node splits a raw text string by first converting the text into BPE tokens, then splits these tokens into chunks and converts the tokens within a single chunk back into text.

  On this page, you'll find the node parameters for the Token Splitter node, and links to more resources.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  * **Chunk Size**: Enter the number of characters in each chunk.
  * **Chunk Overlap**: Enter how much overlap to have between chunks.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'token-splitter') ]]

  ## Related resources

  Refer to [LangChain's token documentation](https://js.langchain.com/docs/concepts/tokens/){:target=_blank .external-link} and [LangChain's text splitter documentation](https://js.langchain.com/docs/concepts/text_splitters/){:target=_blank .external-link} for more information about the service.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Chunk Size","name":"chunkSize","type":"number","default":1000},{"displayName":"Chunk Overlap","name":"chunkOverlap","type":"number","default":0}]


node_type: toolCalculator
package_name: @n8n/n8n-nodes-langchain
display_name: Calculator
description: Use Calculator
category: transform
development_style: programmatic
version: 1
properties_schema: []
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Calculator node documentation
  description: Learn how to use the Calculator node in n8n. Follow technical documentation to integrate Calculator node into your workflows.
  contentType: [integration, reference]
  priority: high
  ---

  # Calculator node

  The Calculator node is a [tool](/glossary.md#ai-tool) that allows an [agent](/glossary.md#ai-agent) to run mathematical calculations.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'calculator') ]]

  ## Related resources

  --8<-- "_snippets/integrations/builtin/cluster-nodes/tools-link.md"

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"


node_type: toolCode
package_name: @n8n/n8n-nodes-langchain
display_name: Code Tool
description: Create a tool via code
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Custom Code Tool node documentation
  description: Learn how to use the Custom Code Tool node in n8n. Follow technical documentation to integrate Custom Code Tool node into your workflows.
  contentType: [integration, reference]
  priority: high
  ---

  # Custom Code Tool node

  Use the Custom Code Tool node to write code that an [agent](/glossary.md#ai-agent) can run.

  On this page, you'll find the node parameters for the Custom Code Tool node and links to more resources.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  ### Description

  Give your custom code a description. This tells the agent when to use this tool. For example:

  > Call this tool to get a random color. The input should be a string with comma separated names of colors to exclude.

  ### Language

  You can use JavaScript or Python.

  ### JavaScript / Python box

  Write the code here.

  You can access the tool input using `query`. For example, to take the input string and lowercase it:

  ```js
  let myString = query;
  return myString.toLowerCase();
  ```

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'code-tool') ]]

  ## Related resources

  --8<-- "_snippets/integrations/builtin/cluster-nodes/tools-link.md"

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"

  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Name","name":"name","type":"string","default":"","placeholder":"My_Tool"},{"displayName":"Description","name":"description","type":"string","default":"","placeholder":"Call this tool to get a random color. The input should be a string with comma separted names of colors to exclude.","typeOptions":{"rows":3}},{"displayName":"Language","name":"language","type":"options","noDataExpression":true,"options":[{"name":"JavaScript","value":"javaScript"},{"name":"Python (Beta)","value":"python"}],"default":"javaScript"},{"displayName":"JavaScript","name":"jsCode","type":"string","displayOptions":{"show":{"language":["javaScript"]}},"typeOptions":{"editor":"codeNodeEditor","editorLanguage":"javaScript"},"default":"","hint":"You can access the input the tool receives via the input property \"query\". The returned value should be a single string.","description":"JavaScript code to execute.<br><br>Tip: You can use luxon vars like <code>$today</code> for dates and <code>$jmespath</code> for querying JSON structures. <a href=\"https://docs.n8n.io/nodes/n8n-nodes-base.function\">Learn more</a>.","noDataExpression":true},{"displayName":"Python","name":"pythonCode","type":"string","displayOptions":{"show":{"language":["python"]}},"typeOptions":{"editor":"codeNodeEditor","editorLanguage":"python"},"default":"","hint":"You can access the input the tool receives via the input property \"query\". The returned value should be a single string.","description":"Python code to execute.<br><br>Tip: You can use luxon vars like <code>_today</code> for dates and <code>$_mespath</code> for querying JSON structures. <a href=\"https://docs.n8n.io/nodes/n8n-nodes-base.function\">Learn more</a>.","noDataExpression":true}]


node_type: toolSerpApi
package_name: @n8n/n8n-nodes-langchain
display_name: SerpAPI
description: Search in Google using SerpAPI
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"serpApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: SerpApi (Google Search) node documentation
  description: Learn how to use the SerpApi (Google Search) node in n8n. Follow technical documentation to integrate SerpApi (Google Search) node into your workflows.
  contentType: [integration, reference]
  priority: high
  ---

  # SerpApi (Google Search) node

  The SerpAPI node allows an [agent](/glossary.md#ai-agent) in your workflow to call Google's Search API.

  On this page, you'll find the node parameters for the SerpAPI node, and links to more resources.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/serp.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node options

  * **Country**: Enter the country code you'd like to use. Refer to [Google GL Parameter: Supported Google Countries](https://serpapi.com/google-countries){:target=_blank .external-link} for supported countries and country codes.
  * **Device**: Select the device to use to get the search results.
  * **Explicit Array**: Choose whether to force SerpApi to fetch the Google results even if a cached version is already present (turned on) or not (turned off).
  * **Google Domain**: Enter the Google Domain to use. Refer to [Supported Google Domains](https://serpapi.com/google-domains) for supported domains.
  * **Language**: Enter the language code you'd like to use. Refer to [Google HL Parameter: Supported Google Languages](https://serpapi.com/google-languages){:target=_blank .external-link} for supported languages and language codes.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'serpapi') ]]

  ## Related resources

  Refer to [Serp's documentation](https://serpapi.com/search-api){:target=_blank .external-link} for more information about the service. You can also view [LangChain's documentation on their Serp integration](https://js.langchain.com/docs/integrations/tools/serpapi/){:target=_blank .external-link}.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Country","name":"gl","type":"string","default":"us","description":"Defines the country to use for search. Head to <a href=\"https://serpapi.com/google-countries\">Google countries page</a> for a full list of supported countries."},{"displayName":"Device","name":"device","type":"options","options":[{"name":"Desktop","value":"desktop"},{"name":"Mobile","value":"mobile"},{"name":"Tablet","value":"tablet"}],"default":"desktop","description":"Device to use to get the results"},{"displayName":"Explicit Array","name":"no_cache","type":"boolean","default":false,"description":"Whether to force SerpApi to fetch the Google results even if a cached version is already present. Cache expires after 1h. Cached searches are free, and are not counted towards your searches per month."},{"displayName":"Google Domain","name":"google_domain","type":"string","default":"google.com","description":"Defines the country to use for search. Head to <a href=\"https://serpapi.com/google-countries\">Google countries page</a> for a full list of supported countries."},{"displayName":"Language","name":"hl","type":"string","default":"en","description":"Defines the language to use. It's a two-letter language code. (e.g., `en` for English, `es` for Spanish, or `fr` for French). Head to <a href=\"https://serpapi.com/google-languages\">Google languages page</a> for a full list of supported languages."}]}]


node_type: toolWikipedia
package_name: @n8n/n8n-nodes-langchain
display_name: Wikipedia
description: Search in Wikipedia
category: transform
development_style: programmatic
version: 1
properties_schema: []
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Wikipedia node documentation
  description: Learn how to use the Wikipedia node in n8n. Follow technical documentation to integrate Wikipedia node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Wikipedia node

  The Wikipedia node is a [tool](/glossary.md#ai-tool) that allows an [agent](/glossary.md#ai-agent) to search and return information from Wikipedia.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'wikipedia') ]]

  ## Related resources

  --8<-- "_snippets/integrations/builtin/cluster-nodes/tools-link.md"

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"

  --8<-- "_glossary/ai-glossary.md"


node_type: toolWolframAlpha
package_name: @n8n/n8n-nodes-langchain
display_name: Wolfram|Alpha
description: Connects to WolframAlpha's computational intelligence engine.
category: transform
development_style: programmatic
version: 1
properties_schema: []
operations: []
credentials_required: [{"name":"wolframAlphaApi","required":true}]
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Wolfram|Alpha tool node documentation
  description: Learn how to use the Wolfram|Alpha tool node in n8n. Follow technical documentation to integrate Wolfram|Alpha tool node into your workflows.
  contentType: [integration, reference]
  priority: medium
  ---

  # Wolfram|Alpha tool node

  Use the Wolfram|Alpha tool node to connect your [agents](/glossary.md#ai-agent) and [chains](/glossary.md#ai-chain) to Wolfram|Alpha's computational intelligence engine.

  /// note | Credentials
  You can find authentication information for this node [here](/integrations/builtin/credentials/wolframalpha.md).
  ///

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'wolframoralpha') ]]

  ## Related resources

  Refer to [Wolfram|Alpha's documentation](https://products.wolframalpha.com/api){:target=_blank .external-link} for more information about the service. You can also view [LangChain's documentation on their WolframAlpha Tool](https://js.langchain.com/docs/integrations/tools/wolframalpha/){:target=_blank .external-link}.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"

  --8<-- "_glossary/ai-glossary.md"


node_type: toolWorkflow
package_name: @n8n/n8n-nodes-langchain
display_name: Workflow Tool
description: Create a tool via a workflow
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
documentation:
  ---
  #https://www.notion.so/n8n/Frontmatter-432c2b8dff1f43d4b1c8d20075510fe4
  title: Call n8n Workflow Tool node documentation
  description: Learn how to use the Call n8n Workflow Tool node in n8n. Follow technical documentation to integrate Call n8n Workflow Tool node into your workflows.
  contentType: [integration, reference]
  priority: high
  ---

  # Call n8n Workflow Tool node

  The Call n8n Workflow Tool node is a [tool](/glossary.md#ai-tool) that allows an [agent](/glossary.md#ai-agent) to run another n8n workflow and fetch its output data. 

  On this page, you'll find the node parameters for the Call n8n Workflow Tool node, and links to more resources.

  --8<-- "_snippets/integrations/builtin/cluster-nodes/sub-node-expression-resolution.md"

  ## Node parameters

  ### Description

  Enter a custom code a description. This tells the agent when to use this tool. For example:

  > Call this tool to get a random color. The input should be a string with comma separated names of colors to exclude.

  ### Source

  Tell n8n which workflow to call. You can choose either:

  * **Database** to select the workflow from a list or enter a workflow ID.
  * **Define Below** and copy in a complete [workflow JSON](/workflows/export-import.md).

  ### Workflow Inputs

  When using **Database** as workflow source, once you choose a sub-workflow (and define the **Workflow Input Schema** in the sub-workflow), you can define the **Workflow Inputs**.

  Select the **Refresh** button to pull in the input fields from the sub-workflow.

  You can define the workflow input values using any combination of the following options:

  * providing fixed values
  * using expressions to reference data from the current workflow
  * [letting the AI model specify the parameter](/advanced-ai/examples/using-the-fromai-function.md) by selecting the button AI button on the right side of the field
  * using the [`$fromAI()` function](/advanced-ai/examples/using-the-fromai-function.md#use-the-fromai-function) in expressions to control the way the model fills in data and to mix AI generated input with other custom input

  To reference data from the current workflow, drag fields from the input panel to the field with the Expressions mode selected.

  To get started with the `$fromAI()` function, select the "Let the model define this parameter" button on the right side of the field and then use the **X** on the box to revert to user-defined values. The field will change to an expression field pre-populated with the `$fromAI()` expression. From here, you can customize the expression to add other static or dynamic content, or tweak the `$fromAI()` function parameters.

  ## Templates and examples

  <!-- see https://www.notion.so/n8n/Pull-in-templates-for-the-integrations-pages-37c716837b804d30a33b47475f6e3780 -->
  [[ templatesWidget(page.title, 'workflow-tool') ]]

  ## Related resources

  --8<-- "_snippets/integrations/builtin/cluster-nodes/tools-link.md"

  --8<-- "_snippets/integrations/builtin/cluster-nodes/langchain-overview-link.md"
  --8<-- "_glossary/ai-glossary.md"

properties_schema:
  [{"displayName":"Name","name":"name","type":"string","default":"","placeholder":"My_Color_Tool"},{"displayName":"Description","name":"description","type":"string","default":"","placeholder":"Call this tool to get a random color. The input should be a string with comma separted names of colors to exclude.","typeOptions":{"rows":3}},{"displayName":"The workflow will receive \"query\" as input and the output of the last node will be returned as response","name":"executeNotice","type":"notice","default":""},{"displayName":"Source","name":"source","type":"options","options":[{"name":"Database","value":"database","description":"Load the workflow from the database by ID"},{"name":"Parameter","value":"parameter","description":"Load the workflow from a parameter"}],"default":"database","description":"Where to get the workflow to execute from"},{"displayName":"Workflow ID","name":"workflowId","type":"string","displayOptions":{"show":{"source":["database"]}},"default":"","required":true,"description":"The workflow to execute"},{"displayName":"Workflow JSON","name":"workflowJson","type":"string","typeOptions":{"editor":"json","rows":10},"displayOptions":{"show":{"source":["parameter"]}},"default":"\n\n\n","required":true,"description":"The workflow JSON code to execute"},{"displayName":"Response Property Name","name":"responsePropertyName","type":"string","default":"response","description":"The name of the property of the last node that will be returned as response"},{"displayName":"Workflow Values","name":"fields","placeholder":"Add Value","type":"fixedCollection","description":"Set the values which should be made available in the workflow","typeOptions":{"multipleValues":true,"sortable":true},"default":{},"options":[{"name":"values","displayName":"Values","values":[{"displayName":"Name","name":"name","type":"string","default":"","placeholder":"e.g. fieldName","description":"Name of the field to set the value of. Supports dot-notation. Example: data.person[0].name.","requiresDataPath":"single"},{"displayName":"Type","name":"type","type":"options","description":"The field value type","options":[{"name":"String","value":"stringValue"},{"name":"Number","value":"numberValue"},{"name":"Boolean","value":"booleanValue"},{"name":"Array","value":"arrayValue"},{"name":"Object","value":"objectValue"}],"default":"stringValue"},{"displayName":"Value","name":"stringValue","type":"string","default":"","displayOptions":{"show":{"type":["stringValue"]}},"validateType":"string","ignoreValidationDuringExecution":true},{"displayName":"Value","name":"numberValue","type":"string","default":"","displayOptions":{"show":{"type":["numberValue"]}},"validateType":"number","ignoreValidationDuringExecution":true},{"displayName":"Value","name":"booleanValue","type":"options","default":"true","options":[{"name":"True","value":"true"},{"name":"False","value":"false"}],"displayOptions":{"show":{"type":["booleanValue"]}},"validateType":"boolean","ignoreValidationDuringExecution":true},{"displayName":"Value","name":"arrayValue","type":"string","default":"","placeholder":"e.g. [ arrayItem1, arrayItem2, arrayItem3 ]","displayOptions":{"show":{"type":["arrayValue"]}},"validateType":"array","ignoreValidationDuringExecution":true},{"displayName":"Value","name":"objectValue","type":"string","default":"={}","typeOptions":{"editor":"json","editorLanguage":"json","rows":2},"displayOptions":{"show":{"type":["objectValue"]}},"validateType":"object","ignoreValidationDuringExecution":true}]}]}]


node_type: manualChatTrigger
package_name: @n8n/n8n-nodes-langchain
display_name: Manual Chat Trigger
description: Runs the flow on new manual chat message
category: trigger
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"This node is where a manual chat workflow execution starts. To make one, go back to the canvas and click ‘Chat’","name":"notice","type":"notice","default":""},{"displayName":"Chat and execute workflow","name":"openChat","type":"button","typeOptions":{"action":"openChat"},"default":""}]


node_type: vectorStoreInMemory
package_name: @n8n/n8n-nodes-langchain
display_name: In-Memory Vector Store
description: Work with your data in In-Memory Vector Store
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Operation Mode","name":"mode","type":"options","noDataExpression":true,"default":"retrieve","options":[{"name":"Get Many","value":"load","description":"Get many ranked documents from vector store for query","action":"Get many ranked documents from vector store for query"},{"name":"Insert Documents","value":"insert","description":"Insert documents into vector store","action":"Insert documents into vector store"},{"name":"Retrieve Documents (For Agent/Chain)","value":"retrieve","description":"Retrieve documents from vector store to be used with AI nodes","action":"Retrieve documents from vector store to be used with AI nodes"}]},{"displayName":"Memory Key","name":"memoryKey","type":"string","default":"vector_store_key","description":"The key to use to store the vector memory in the workflow data. The key will be prefixed with the workflow ID to avoid collisions."},{"displayName":"The embbded data are stored in the server memory, so they will be lost when the server is restarted. Additionally, if the amount of data is too large, it may cause the server to crash due to insufficient memory.","name":"notice","type":"notice","default":"","displayOptions":{"show":{"mode":["insert"]}}},{"displayName":"Clear Store","name":"clearStore","type":"boolean","default":false,"description":"Whether to clear the store before inserting new data","displayOptions":{"show":{"mode":["insert"]}}},{"displayName":"Prompt","name":"prompt","type":"string","default":"","required":true,"description":"Search prompt to retrieve matching documents from the vector store using similarity-based ranking","displayOptions":{"show":{"mode":["load"]}}},{"displayName":"Limit","name":"topK","type":"number","default":4,"description":"Number of top results to fetch from vector store","displayOptions":{"show":{"mode":["load"]}}}]


node_type: vectorStoreInMemoryInsert
package_name: @n8n/n8n-nodes-langchain
display_name: In Memory Vector Store Insert
description: Insert data into an in-memory vector store
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"The embbded data are stored in the server memory, so they will be lost when the server is restarted. Additionally, if the amount of data is too large, it may cause the server to crash due to insufficient memory.","name":"notice","type":"notice","default":""},{"displayName":"Clear Store","name":"clearStore","type":"boolean","default":false,"description":"Whether to clear the store before inserting new data"},{"displayName":"Memory Key","name":"memoryKey","type":"string","default":"vector_store_key","description":"The key to use to store the vector memory in the workflow data. The key will be prefixed with the workflow ID to avoid collisions."}]


node_type: vectorStoreInMemoryLoad
package_name: @n8n/n8n-nodes-langchain
display_name: In Memory Vector Store Load
description: Load embedded data from an in-memory vector store
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: []
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Memory Key","name":"memoryKey","type":"string","default":"vector_store_key","description":"The key to use to store the vector memory in the workflow data. The key will be prefixed with the workflow ID to avoid collisions."}]


node_type: vectorStorePinecone
package_name: @n8n/n8n-nodes-langchain
display_name: Pinecone Vector Store
description: Work with your data in Pinecone Vector Store
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"pineconeApi","required":true}]
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Operation Mode","name":"mode","type":"options","noDataExpression":true,"default":"retrieve","options":[{"name":"Get Many","value":"load","description":"Get many ranked documents from vector store for query","action":"Get many ranked documents from vector store for query"},{"name":"Insert Documents","value":"insert","description":"Insert documents into vector store","action":"Insert documents into vector store"},{"name":"Retrieve Documents (For Agent/Chain)","value":"retrieve","description":"Retrieve documents from vector store to be used with AI nodes","action":"Retrieve documents from vector store to be used with AI nodes"}]},{"displayName":"Pinecone Index","name":"pineconeIndex","type":"string","default":"","required":true},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Clear Namespace","name":"clearNamespace","type":"boolean","default":false,"description":"Whether to clear the namespace before inserting new data"},{"displayName":"Pinecone Namespace","name":"pineconeNamespace","type":"string","description":"Partition the records in an index into namespaces. Queries and other operations are then limited to one namespace, so different requests can search different subsets of your index.","default":""}],"displayOptions":{"show":{"mode":["insert"]}}},{"displayName":"Prompt","name":"prompt","type":"string","default":"","required":true,"description":"Search prompt to retrieve matching documents from the vector store using similarity-based ranking","displayOptions":{"show":{"mode":["load"]}}},{"displayName":"Limit","name":"topK","type":"number","default":4,"description":"Number of top results to fetch from vector store","displayOptions":{"show":{"mode":["load"]}}},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Pinecone Namespace","name":"pineconeNamespace","type":"string","description":"Partition the records in an index into namespaces. Queries and other operations are then limited to one namespace, so different requests can search different subsets of your index.","default":""},{"displayName":"Metadata Filter","name":"metadata","type":"fixedCollection","description":"Metadata to filter the document by","typeOptions":{"multipleValues":true},"default":{},"placeholder":"Add filter field","options":[{"name":"metadataValues","displayName":"Fields to Set","values":[{"displayName":"Name","name":"name","type":"string","default":"","required":true},{"displayName":"Value","name":"value","type":"string","default":""}]}]}],"displayOptions":{"show":{"mode":["load"]}}},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Pinecone Namespace","name":"pineconeNamespace","type":"string","description":"Partition the records in an index into namespaces. Queries and other operations are then limited to one namespace, so different requests can search different subsets of your index.","default":""},{"displayName":"Metadata Filter","name":"metadata","type":"fixedCollection","description":"Metadata to filter the document by","typeOptions":{"multipleValues":true},"default":{},"placeholder":"Add filter field","options":[{"name":"metadataValues","displayName":"Fields to Set","values":[{"displayName":"Name","name":"name","type":"string","default":"","required":true},{"displayName":"Value","name":"value","type":"string","default":""}]}]}],"displayOptions":{"show":{"mode":["retrieve"]}}}]


node_type: vectorStorePineconeInsert
package_name: @n8n/n8n-nodes-langchain
display_name: Pinecone: Insert
description: Insert data into Pinecone Vector Store index
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"pineconeApi","required":true}]
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Pinecone Index","name":"pineconeIndex","type":"string","default":"","required":true},{"displayName":"Pinecone Namespace","name":"pineconeNamespace","type":"string","default":""},{"displayName":"Specify the document to load in the document loader sub-node","name":"notice","type":"notice","default":""},{"displayName":"Clear Namespace","name":"clearNamespace","type":"boolean","default":false,"description":"Whether to clear the namespace before inserting new data"}]


node_type: vectorStorePineconeLoad
package_name: @n8n/n8n-nodes-langchain
display_name: Pinecone: Load
description: Load data from Pinecone Vector Store index
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"pineconeApi","required":true}]
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Pinecone Index","name":"pineconeIndex","type":"string","default":"","required":true},{"displayName":"Pinecone Namespace","name":"pineconeNamespace","type":"string","default":""},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Metadata Filter","name":"metadata","type":"fixedCollection","description":"Metadata to filter the document by","typeOptions":{"multipleValues":true},"default":{},"placeholder":"Add filter field","options":[{"name":"metadataValues","displayName":"Fields to Set","values":[{"displayName":"Name","name":"name","type":"string","default":"","required":true},{"displayName":"Value","name":"value","type":"string","default":""}]}]}]}]


node_type: vectorStoreSupabase
package_name: @n8n/n8n-nodes-langchain
display_name: Supabase Vector Store
description: Work with your data in Supabase Vector Store
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"supabaseApi","required":true}]
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Operation Mode","name":"mode","type":"options","noDataExpression":true,"default":"retrieve","options":[{"name":"Get Many","value":"load","description":"Get many ranked documents from vector store for query","action":"Get many ranked documents from vector store for query"},{"name":"Insert Documents","value":"insert","description":"Insert documents into vector store","action":"Insert documents into vector store"},{"name":"Retrieve Documents (For Agent/Chain)","value":"retrieve","description":"Retrieve documents from vector store to be used with AI nodes","action":"Retrieve documents from vector store to be used with AI nodes"}]},{"displayName":"Table Name","name":"tableName","type":"string","default":"","required":true,"description":"Name of the table to load from"},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Query Name","name":"queryName","type":"string","default":"match_documents","description":"Name of the query to use for matching documents"}],"displayOptions":{"show":{"mode":["insert"]}}},{"displayName":"Prompt","name":"prompt","type":"string","default":"","required":true,"description":"Search prompt to retrieve matching documents from the vector store using similarity-based ranking","displayOptions":{"show":{"mode":["load"]}}},{"displayName":"Limit","name":"topK","type":"number","default":4,"description":"Number of top results to fetch from vector store","displayOptions":{"show":{"mode":["load"]}}},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Query Name","name":"queryName","type":"string","default":"match_documents","description":"Name of the query to use for matching documents"},{"displayName":"Metadata Filter","name":"metadata","type":"fixedCollection","description":"Metadata to filter the document by","typeOptions":{"multipleValues":true},"default":{},"placeholder":"Add filter field","options":[{"name":"metadataValues","displayName":"Fields to Set","values":[{"displayName":"Name","name":"name","type":"string","default":"","required":true},{"displayName":"Value","name":"value","type":"string","default":""}]}]}],"displayOptions":{"show":{"mode":["load"]}}},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Query Name","name":"queryName","type":"string","default":"match_documents","description":"Name of the query to use for matching documents"},{"displayName":"Metadata Filter","name":"metadata","type":"fixedCollection","description":"Metadata to filter the document by","typeOptions":{"multipleValues":true},"default":{},"placeholder":"Add filter field","options":[{"name":"metadataValues","displayName":"Fields to Set","values":[{"displayName":"Name","name":"name","type":"string","default":"","required":true},{"displayName":"Value","name":"value","type":"string","default":""}]}]}],"displayOptions":{"show":{"mode":["retrieve"]}}}]


node_type: vectorStoreSupabaseInsert
package_name: @n8n/n8n-nodes-langchain
display_name: Supabase: Insert
description: Insert data into Supabase Vector Store index [https://supabase.com/docs/guides/ai/langchain]
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"supabaseApi","required":true}]
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Please refer to the <a href=\"https://supabase.com/docs/guides/ai/langchain\" target=\"_blank\">Supabase documentation</a> for more information on how to setup your database as a Vector Store.","name":"setupNotice","type":"notice","default":""},{"displayName":"Table Name","name":"tableName","type":"string","default":"","required":true,"description":"Name of the table to insert into"},{"displayName":"Query Name","name":"queryName","type":"string","default":"match_documents","required":true,"description":"Name of the query to use for matching documents"},{"displayName":"Specify the document to load in the document loader sub-node","name":"notice","type":"notice","default":""}]


node_type: vectorStoreSupabaseLoad
package_name: @n8n/n8n-nodes-langchain
display_name: Supabase: Load
description: Load data from Supabase Vector Store index
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"supabaseApi","required":true}]
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Table Name","name":"tableName","type":"string","default":"","required":true,"description":"Name of the table to load from"},{"displayName":"Query Name","name":"queryName","type":"string","default":"match_documents","required":true,"description":"Name of the query to use for matching documents"},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Metadata Filter","name":"metadata","type":"fixedCollection","description":"Metadata to filter the document by","typeOptions":{"multipleValues":true},"default":{},"placeholder":"Add filter field","options":[{"name":"metadataValues","displayName":"Fields to Set","values":[{"displayName":"Name","name":"name","type":"string","default":"","required":true},{"displayName":"Value","name":"value","type":"string","default":""}]}]}]}]


node_type: vectorStoreZep
package_name: @n8n/n8n-nodes-langchain
display_name: Zep Vector Store
description: Work with your data in Zep Vector Store
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"zepApi","required":true}]
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Operation Mode","name":"mode","type":"options","noDataExpression":true,"default":"retrieve","options":[{"name":"Get Many","value":"load","description":"Get many ranked documents from vector store for query","action":"Get many ranked documents from vector store for query"},{"name":"Insert Documents","value":"insert","description":"Insert documents into vector store","action":"Insert documents into vector store"},{"name":"Retrieve Documents (For Agent/Chain)","value":"retrieve","description":"Retrieve documents from vector store to be used with AI nodes","action":"Retrieve documents from vector store to be used with AI nodes"}]},{"displayName":"Collection Name","name":"collectionName","type":"string","default":"","required":true},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Embedding Dimensions","name":"embeddingDimensions","type":"number","default":1536,"description":"Whether to allow using characters from the Unicode surrogate blocks"},{"displayName":"Is Auto Embedded","name":"isAutoEmbedded","type":"boolean","default":true,"description":"Whether to automatically embed documents when they are added"}],"displayOptions":{"show":{"mode":["insert"]}}},{"displayName":"Prompt","name":"prompt","type":"string","default":"","required":true,"description":"Search prompt to retrieve matching documents from the vector store using similarity-based ranking","displayOptions":{"show":{"mode":["load"]}}},{"displayName":"Limit","name":"topK","type":"number","default":4,"description":"Number of top results to fetch from vector store","displayOptions":{"show":{"mode":["load"]}}},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Embedding Dimensions","name":"embeddingDimensions","type":"number","default":1536,"description":"Whether to allow using characters from the Unicode surrogate blocks"},{"displayName":"Metadata Filter","name":"metadata","type":"fixedCollection","description":"Metadata to filter the document by","typeOptions":{"multipleValues":true},"default":{},"placeholder":"Add filter field","options":[{"name":"metadataValues","displayName":"Fields to Set","values":[{"displayName":"Name","name":"name","type":"string","default":"","required":true},{"displayName":"Value","name":"value","type":"string","default":""}]}]}],"displayOptions":{"show":{"mode":["load"]}}},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Embedding Dimensions","name":"embeddingDimensions","type":"number","default":1536,"description":"Whether to allow using characters from the Unicode surrogate blocks"},{"displayName":"Metadata Filter","name":"metadata","type":"fixedCollection","description":"Metadata to filter the document by","typeOptions":{"multipleValues":true},"default":{},"placeholder":"Add filter field","options":[{"name":"metadataValues","displayName":"Fields to Set","values":[{"displayName":"Name","name":"name","type":"string","default":"","required":true},{"displayName":"Value","name":"value","type":"string","default":""}]}]}],"displayOptions":{"show":{"mode":["retrieve"]}}}]


node_type: vectorStoreZepInsert
package_name: @n8n/n8n-nodes-langchain
display_name: Zep Vector Store: Insert
description: Insert data into Zep Vector Store index
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"zepApi","required":true}]
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Collection Name","name":"collectionName","type":"string","default":"","required":true},{"displayName":"Specify the document to load in the document loader sub-node","name":"notice","type":"notice","default":""},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Embedding Dimensions","name":"embeddingDimensions","type":"number","default":1536,"description":"Whether to allow using characters from the Unicode surrogate blocks"},{"displayName":"Is Auto Embedded","name":"isAutoEmbedded","type":"boolean","default":true,"description":"Whether to automatically embed documents when they are added"}]}]


node_type: vectorStoreZepLoad
package_name: @n8n/n8n-nodes-langchain
display_name: Zep Vector Store: Load
description: Load data from Zep Vector Store index
category: transform
development_style: programmatic
version: 1
operations: []
credentials_required: [{"name":"zepApi","required":true}]
updated_at: 2025-06-12 12:00:45
properties_schema:
  [{"displayName":"Collection Name","name":"collectionName","type":"string","default":"","required":true},{"displayName":"Options","name":"options","type":"collection","placeholder":"Add Option","default":{},"options":[{"displayName":"Embedding Dimensions","name":"embeddingDimensions","type":"number","default":1536,"description":"Whether to allow using characters from the Unicode surrogate blocks"},{"displayName":"Metadata Filter","name":"metadata","type":"fixedCollection","description":"Metadata to filter the document by","typeOptions":{"multipleValues":true},"default":{},"placeholder":"Add filter field","options":[{"name":"metadataValues","displayName":"Fields to Set","values":[{"displayName":"Name","name":"name","type":"string","default":"","required":true},{"displayName":"Value","name":"value","type":"string","default":""}]}]}]}]


