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T3AS requires a few configuration steps to set up and run properly. Follow the sequence below to ensure a smooth integration.

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1. Extension Settings

Configure the basic extension settings, including your API key and other required parameters.
  1. Open the Extension Configuration module in the TYPO3 backend.
  2. Locate T3AS (TYPO3 AI Search) in the list.
  3. Depending on your AI provider, enter the API key in the appropriate tab:
  4. ChatGPT Tab:
  • Enter API Key.
  • Select Model (e.g., gpt-3.5-turbo).
  • Select Text Embedding Model (e.g., text-embedding-3-small).
  • Adjust Temperature if needed (default 0.7).
  1. Custom LLM Tab:
  • Enable Custom AI Engine by checking the box.
  • Enter the API Endpoint.
  • Enter the API Key for your Custom LLM.
  1. Gemini Tab:
  • If applicable, enter the API key and other configuration options specific to Gemini.

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2. Site Configuration

Define the search type for your website. T3AS supports:
  • sitecontent
  • ke_search
  • indexed_search
  • Solr
Choose the search source that matches your project setup.
  • Go to Sites module in the TYPO3 backend.
  • Edit your site configuration.
  • In the T3AS Settings Tab, select the Search Type that matches your setup and configur other settings as per your requiredment!
  • Save and close the configuration.
Please find more details about each configuration below.

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Search Engine Settings

  • Enable AI Search Globally Activates AI search across the site.
  • Choose Search Engine Defines the search engine to be used for AI results. Example: Site Content Note: Supported search engines include Site Content, Ke Search, Indexed Search, and Solr.
  • Search Class Enter the CSS/id class for usage of AI search results through TypoScript. Example: ke_search_sword for Ke Search.
  • Result Style Defines the display style of AI-generated results. Example: Summarize
  • Instructions Custom system instructions for the AI assistant.

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Widget Settings

  • Widget Mode Defines how the search widget/modal is displayed. Example: Modal Box (Centered)
  • Widget/Modal Trigger Button Position Sets the position of the trigger button. Example: Left (bottom)
  • Trigger Button Size Adjusts the size of the trigger button. Example: Normal
  • Search Icon Defines the icon displayed in the search box. Example: Universal Icon
  • Trigger Button Background Sets the background style of the trigger button. Example: Solid

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Layout Settings

  • Select Style Style for the search box and results. Example: Customized Style (plugin) Note: The default style matches the existing website color scheme.
  • Border Radius Adjusts the roundness of the search box corners. Example: Semi Rounded
  • Primary Color Defines the primary color of the search box design. Example: #ffa23b
  • Secondary Color Defines the secondary color for highlights or accents. Example: #baadc2
  • Text Color Sets the color of text inside the search box. Example: #962dff
  • Select Loader Defines the loader animation while fetching results. Example: Skeleton Loader
  • Recent Search Enables the display of recent search queries.
  • Search Form Type Defines how the search input is displayed. Example: With Button
  • Button Type Type of button used for the search form. Example: Search Icon

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Predefined Questions

  • Predefined Questions Enables predefined search suggestions.
  • Question Position Defines the placement of predefined questions. Example: Bottom Search Note: Options include below search or near bottom.
  • Number of Questions to Show Maximum number of questions displayed. Example: 5
  • Questions Storage Folder(s) Folder(s) where predefined questions are stored. Example: 681

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Solr Settings

If the selected search engine is Solr, please provide the following details in case your Solr server is secured with HTTP authentication.
  • Solr Username Username for Solr authentication.
  • Solr Password Password for Solr authentication.

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Hosted-Solr Server Integration for Solr

The Hosted-Solr Server feature enables you to connect your TYPO3 instance directly to the Hosted-Solr service for improved search indexing and data retrieval. The following guide outlines how to configure T3AS and Hosted Solr in your TYPO3 instance using the Site Configuration module.
  • Step 1: Open Site Configuration
Extension Banner
  1. In the TYPO3 backend, navigate to Site Management → Sites
  2. Edit site configuration
  • Step 2:Scroll down to the Solr section in the same T3AS tab and Configure Solr Integration
Extension Banner
  • Step 4: Define Solr Connection Settings
Extension Banner
  • Step 5: Save Configuration

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Getting Started

  1. Create an Account: Sign up on the Hosted-Solr platform using your email address.
  2. Create a Solr Core: Once your account is active, create a new Solr core.
  3. Configure in TYPO3: Add your Solr core connection details within the TYPO3 Site Settings.
This integration allows you to seamlessly manage your Solr configuration and maintain consistent communication between TYPO3 and the Hosted-Solr environment.

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Verifying the Connection

After configuration, ensure that Solr is properly connected:
  • Navigate to the Info module inside the Solr tab within your TYPO3 backend.
  • Verify that the Solr connection status and indexing information appear correctly.

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Additional Fields Support

The extension now supports fetching additional fields from Solr beyond the standard predefined set. This means you can include custom or project-specific fields in your search configuration to enhance indexing and display flexibility.
  1. Go to the Extension Settings in TYPO3.
  2. Specify which fields should be retrieved from Solr.
  3. Save your settings to enable greater control over search results and data output.
By leveraging this feature, you can tailor your Solr-based search experience to match the exact needs of your TYPO3 project.
Several default fields are automatically included for content retrieval from Solr: id, site, type, uid, content, pid, url, changed, and access. Ensure that Solr is properly configured and that the content field is available in your Solr-indexed data.
When configuring T3AS with ke_search or indexed_search, make sure the following conditions are met:
  1. All Website Data Indexed
  • Ensure that the complete website content is indexed by the respective search extension before enabling T3AS.
  1. Scheduler Execution
  • Run all required schedulers as outlined in the Scheduler configuration section to keep the data fresh and available for AI-powered search.

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Scheduler Tasks

T3AS relies on scheduled tasks to fetch, process, and maintain search data. Create and enable the following schedulers:

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1. Fetch Data Scheduler – Collects content to be indexed.

  • Go to Scheduler module.
  • Create a new task → Select Execute console commands.
  • From the dropdown, choose T3AS: Fetch Data Scheduler.
  • Define frequency (e.g., every 30 minutes).
  • Save and activate the task.
Command: nst3as:fetch:data – Fetch data

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Running the Fetch Data Command

You can execute the fetch data command directly from the CLI to fetch and process content from your configured search engine (Solr, ke_search, indexed_search, or sitecontent). Example Command (Composer-based installation):
For non-composer installations: Please refer to the TYPO3 Scheduler documentation for the correct command syntax. Use typo3/sysext/core/bin/typo3 instead of vendor/bin/typo3 in your command.
The command processes records from your search index and displays progress information including the number of records found, processing status, and results summary. Fetch Data CLI Command Output Example output showing the fetch data command processing 50 records with 47 successful and 3 errors Arguments : Please find the in depth description about each argument for this scheduler rootPageId: Define the Root Page ID of the TYPO3 site from which crawling begins. contentRestriction: Define whether user-restricted content should be fetched.
  • 0 = All content is included
  • 1 = User-restricted content is excluded
Note Only applicable when search engine is not set to sitecontent. excludeLanguageIds:
  • List of language IDs to be excluded during crawling.
  • Ignored if a sitemap URL is provided.
Note: Works only with ke_search, indexed_search, and Solr. maxLinkCrawl:
  • Maximum number of links to crawl.eg 100
  • Only relevant when using sitecontent with excludeLanguageIds.
trainDirectory:
  • Public directory path to crawl files (e.g., PDFs). /fileadmin/pdfs/
  • Only applicable when search engine is set to sitecontent.
siteMapUrls:
  • One or more sitemap URLs to crawl (comma-separated).
  • Example:https://example.com/sitemap.xml, https://example.com/sitemap-news.xml
  • Only applicable when search engine is set to sitecontent.
  • Go to Scheduler module.
  • Create a new task → Select Execute console commands.
  • From the dropdown, choose T3AS: Embedding Scheduler.
  • Schedule it after Fetch Data Scheduler.
  • Save and enable.
Command: nst3as:generate:embeddings – Generate embeddings for untrained data

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Running the Embedding Generation Command

After fetching data, you need to generate vector embeddings for AI-based search. This command processes untrained data and creates embeddings that enable semantic search capabilities. Example Command (Composer-based installation):
For non-composer installations: Please refer to the TYPO3 Scheduler documentation for the correct command syntax. Use typo3/sysext/core/bin/typo3 instead of vendor/bin/typo3 in your command.
The command will:
  • Find all untrained items that need embeddings
  • Process each item sequentially
  • Display progress with a progress bar showing completion percentage
  • Show estimated time remaining and memory usage
Embedding Generation CLI Command Output Example output showing embedding generation in progress (29/47 items processed, 59% complete) Note: The embedding generation process can take some time depending on the amount of data. Make sure to adjust PHP timeout settings if needed (see below).

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Adjust PHP Timeout During Training

If you encounter timeout issues while training your TYPO3 data, you can increase the PHP execution time in your environment. Steps:
  1. Locate the max_execution_time setting in your php.ini file.
  2. Increase its value (for example, 300 seconds) to allow the training process to run longer.
  3. Save the changes
This ensures that the AI training process completes successfully without being interrupted by PHP timeouts.

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3. Retrain Scheduler – Updates the model with new or changed content.

This scheduler is only required when using ke_search, indexed_search, or Solr. If data is updated, first re-index the data in your search extension and then run this scheduler to refresh the AI model.

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4. Clear Logs Scheduler – Cleans up old logs to maintain performance.

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Injecting AI Search result in TYPO3 Search Extensions

Use this when you already run ke_search, indexed_search, or Solr and want the T3AS AI overview to appear together with that search UI. Setup has two parts:
  1. Set Search Class in T3AS → Search → Settings so T3AS can read the visitor query from the third-party search field (see Search tab).
  2. Add the Fluid injection snippet to that extension’s search template (preferably in a site package override, not by editing the extension in vendor/ / typo3conf/ext directly).

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Search Class values

Enter only the class name in Search Class (for example tx-solr-q), without a leading .. The value must match the CSS class on the live search input for your setup. If your theme renames the input class, use that class instead.

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Fluid injection snippet

Add this line where the AI overview should render (usually near the search form or above the classic result list):
  1. Set Search Class to ke_search_sword.
  2. In your override of SearchForm.html, add the injection snippet.
AI overview injected below a ke_search form Example: AI overview rendered with the ke_search form after the Fluid snippet is in place.
  1. Set Search Class to tx-indexedsearch-searchbox-sword.
  2. In your override of EXT:indexed_search/Resources/Private/Templates/Search/Search.fluid.html, add the injection snippet (typically after the search form and before the result loop).
Fluid injectAiSearchResults snippet in indexed_search Search.fluid.html indexed_search template — add <f:cObject typoscriptObjectPath="lib.injectAiSearchResults" /> after the form render.

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Solr

  1. Set Search Class to tx-solr-q.
  2. In your override of EXT:solr/Resources/Private/Templates/Search/Results.html, add the injection snippet (typically after the search form partial).
Fluid injectAiSearchResults snippet in Solr Results.html Solr Results.html — add <f:cObject typoscriptObjectPath="lib.injectAiSearchResults" /> after the search form. After saving the Search Class and template override, flush TYPO3 caches and test a search on the frontend. The AI overview should appear with the existing search results when a matching query is submitted.

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Enable AI Search plugin using TypoScript

To render the standalone AI Search plugin via TypoScript (not the third-party form injection above), add the following Fluid view helper where the plugin should appear. Set searchPid to the page ID that contains the T3AS Search plugin (for example 4):

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T3AS History Logs

This module provides a detailed history of all search queries performed through the AI Search integration. It allows administrators to track search keywords, usage frequency, and corresponding results across different languages. This helps in monitoring user behavior, improving search relevance, and optimizing content accordingly.

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Interactive demos

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Additional content from live docs

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1. AI Features (AI Foundation)

Shared AI settings for T3AS are managed in AI Foundation — not under Admin Tools > Settings > Configure Extensions. Configure AI Foundation first, then return to T3AS for search, training, and source-specific setup.
  1. Go to the TYPO3 backend.
  2. Open AI Foundation → AI Features.
  3. Open the T3AS (ns_t3as) feature card and configure the shared settings.
  4. Click Save.
  5. Return to T3AS to continue with source, training, and search-specific settings.
For the shared module overview, see AI Foundation AI Features.

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AI Search Features

T3AS focuses on AI search, training, and answer delivery on top of the shared AI Foundation setup. Use these features when you want to connect project content to AI search, control answer behavior, and monitor how search performs after rollout. Key T3AS capabilities include:
  • Search and answer generation based on trained project content
  • Data source syncing and training queue management
  • Scheduler-based background processing
  • Usage analytics, logs, and request statistics
  • Prompt-controlled search answers and instructions
For shared model routing and central AI behavior, see AI Foundation AI Features.

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2. Dashboard

Purpose The Dashboard gives an overview of your AI training pipeline for the current site. What you see
  • Which AI/embedding model is in use (e.g. OpenAI, Gemini, Mistral, Custom).
  • Status of the Search and Chatbot modules (if installed): active/inactive, AI engine, base model, embedding model.
  • Status of your data sources and training (e.g. how many items are pending, completed, or failed).
  • Training Pipeline section: data sources count, queue size, and a link to CLI reference.
  • Usage Analytics summary (e.g. total interactions, search queries, chat sessions over the last 7 days).
  • A link to the Scheduler to run or check the automatic training task.
Scheduler link From the Dashboard you can open the TYPO3 Scheduler and locate the automatic training task (typically named T3AS Training for this site). Use Run All or Run Task Now to process the training queue immediately.

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3. Data Source

Purpose Add and manage the sources of content that will be used for AI search, such as website pages, PDFs, and Q&A records. Adding a data source
  1. Click + Add Source.
  2. Choose the type of source, for example:
  • Sitemap XML – Your sitemap URL(s) (e.g. https://example.com/sitemap.xml).
  • PDF Documents – Folder path where PDFs are stored (and optionally upload PDFs).
  • TYPO3 Pages – Content from specific TYPO3 pages.
  • Web Pages – A website URL; optionally limit to a path (e.g. https://example.com/blog/*).
  • Q&A Pairs – Manual question-and-answer content.
  • Indexed Search / Ke Search / Solr – If the corresponding extensions are installed and indexed content is available.
  1. Fill in the requested details (URLs, folder path, page selection, etc.) and give the source a Name (e.g. Main Website) and optional Description.
  2. Set Sync interval: how often content should be refreshed (e.g. Hourly, Daily, Weekly). Custom means no automatic schedule (manual sync only).
  3. Set Used by (formerly Type) to control where this source is available.
  4. Set Enabled to on if the source should be active.
  5. Click Save.
After saving, T3AS will:
  • Create or update the data source.
  • Sync content into the training queue (new or changed items).
  • Automatically create the T3AS Training Scheduler task for this site (if it does not exist yet) and run it at the frequency you set (e.g. Hourly, Daily, Weekly). You do not need to create the scheduler task manually—it is created when the source is saved and will execute according to the chosen sync interval.
Editing or deleting a source Use the actions next to each data source to edit (type, URLs, interval, usage) or delete it.

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Source Groups | Page-Level Source Configuration

Source Groups allow administrators and editors to organize data sources and control which content is available to AI Search and the AI Chatbot on a page-by-page basis. This gives you precise control over retrieval because only the selected Source Groups are considered for that page. Source Groups are used only during content retrieval. They do not affect AI training, vector indexing, Scheduler execution, embedding generation, or data synchronization. The filtering is applied by the VectorService during retrieval.

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Backend Configuration

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Manage Source Groups

Go to Data Sources -> Source Groups to manage Source Groups. Administrators can:
  • create Source Groups
  • edit Source Groups
  • delete Source Groups
Manage source groups dialog Create, edit, or delete Source Groups. The Global group is a system default and cannot be changed.
The Global Source Group is a system group and cannot be edited or deleted.

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Assign Source Groups to Data Sources

When creating or editing a data source, users can:
  • select one or more Source Groups
  • rely on the Global Source Group, which is assigned automatically
  • configure the Used by field (formerly Type) to control where the source is available
Available Used by options:
  • AI Search
  • AI Chatbot
  • Both AI Search and AI Chatbot
This setting controls where the data source can be used after retrieval starts.

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Page-Level Configuration (T3AS / T3AC)

  1. Open the desired TYPO3 page.
  2. Open Page Properties.
  3. Go to the AI Search tab.
  4. Find the Source groups field.
  5. Select the Source Groups that should be available on that page.
Page-level Source groups in page properties Choose Source Groups under Page Properties → AI Search so AI Search and AI Chatbot use only those sources on that page. Only data sources assigned to the selected Source Groups are used on that page and their child/recursive pages. This filtering applies to both AI Search and AI Chatbot, and different pages can use different Source Groups.

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Practical Example

A company has separate documentation for Products, HR, and Internal Policies. Three Source Groups are created:
  • Products
  • HR
  • Internal
On product pages, only the Products Source Group is selected, so AI Search and AI Chatbot return product-related information. On HR pages, only the HR Source Group is selected, so HR content is used while product information is excluded.
Source Groups only affect content retrieval. Existing training data, embeddings, vector indexing, and scheduled synchronization continue to operate normally.
If no custom Source Groups are selected, the Global Source Group remains available according to the configured behavior.

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Header / Footer for Sitemap and Web-Page Source Types

These options help you keep repeated layout content out of the main page body while still making shared site information available to AI retrieval. Index site header and Index site footer options in Add Source Enable Index site header and Index site footer when adding or editing a Sitemap XML or Web Pages data source. Index Site Header Use Index Site Header when the site header contains useful shared information that should be indexed only once. Purpose:
  • extract the website <header> content one time for each unique header
  • store that content as a separate training item
  • remove the same header content from the page body before indexing
Benefits:
  • reduces duplicate information across many pages
  • keeps repeated navigation or shared header text from being indexed over and over
  • preserves useful shared site information for retrieval
When to enable:
  • when the header contains meaningful text that supports AI answers
  • when many pages share the same header content
Recommended use cases:
  • websites with shared product navigation or service overviews in the header
  • websites where the header contains reusable company or category information
Index Site Footer Use Index Site Footer when the site footer contains shared information that should be indexed only once. Purpose:
  • extract the website <footer> content one time for each unique footer
  • store that content as a separate training item
  • exclude that footer content from the page body during indexing
Benefits:
  • prevents duplicate footer text from being trained again on every page
  • keeps the main page content cleaner for retrieval
  • preserves useful global site information such as company details or support links
When to enable:
  • when the footer contains helpful shared text for search or chatbot answers
  • when the same footer appears on many pages
Recommended use cases:
  • websites with shared contact details, policy references, or company summaries in the footer
  • large sites where repeated footer content would otherwise be indexed many times
Enable Index Site Header and/or Index Site Footer in the data source form when creating or editing a Sitemap XML or Web Pages source.
Deleting a data source also removes its training queue and embedded data for that source.
Sync Sync (per source or Sync all) refreshes content from the source into the training queue.
  • Sync does not run AI training by itself.
  • Training is performed by the Scheduler task or manually (see Training Center).

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Source Groups | Page-Level Source Configuration

Source Groups allow administrators and editors to organize data sources and control which content is available to AI Search and the AI Chatbot on a page-by-page basis. This gives you precise control over retrieval because only the selected Source Groups are considered for that page. Source Groups are used only during content retrieval. They do not affect AI training, vector indexing, Scheduler execution, embedding generation, or data synchronization. The filtering is applied by the VectorService during retrieval.

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Backend Configuration

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Manage Source Groups

Go to Data Sources -> Source Groups to manage Source Groups. Administrators can:
  • create Source Groups
  • edit Source Groups
  • delete Source Groups
Manage source groups dialog Create, edit, or delete Source Groups. The Global group is a system default and cannot be changed.
The Global Source Group is a system group and cannot be edited or deleted.

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Assign Source Groups to Data Sources

When creating or editing a data source, users can:
  • select one or more Source Groups
  • rely on the Global Source Group, which is assigned automatically
  • configure the Used by field (formerly Type) to control where the source is available
Available Used by options:
  • AI Search
  • AI Chatbot
  • Both AI Search and AI Chatbot
This setting controls where the data source can be used after retrieval starts.

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Page-Level Configuration (T3AS / T3AC)

  1. Open the desired TYPO3 page.
  2. Open Page Properties.
  3. Go to the AI Search tab.
  4. Find the Source groups field.
  5. Select the Source Groups that should be available on that page.
Page-level Source groups in page properties Choose Source Groups under Page Properties → AI Search so AI Search and AI Chatbot use only those sources on that page. Only data sources assigned to the selected Source Groups are used on that page and their child/recursive pages. This filtering applies to both AI Search and AI Chatbot, and different pages can use different Source Groups.

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Practical Example

A company has separate documentation for Products, HR, and Internal Policies. Three Source Groups are created:
  • Products
  • HR
  • Internal
On product pages, only the Products Source Group is selected, so AI Search and AI Chatbot return product-related information. On HR pages, only the HR Source Group is selected, so HR content is used while product information is excluded.
Source Groups only affect content retrieval. Existing training data, embeddings, vector indexing, and scheduled synchronization continue to operate normally.
If no custom Source Groups are selected, the Global Source Group remains available according to the configured behavior.

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Header / Footer for Sitemap and Web-Page Source Types

These options help you keep repeated layout content out of the main page body while still making shared site information available to AI retrieval. Index site header and Index site footer options in Add Source Enable Index site header and Index site footer when adding or editing a Sitemap XML or Web Pages data source. Index Site Header Use Index Site Header when the site header contains useful shared information that should be indexed only once. Purpose:
  • extract the website <header> content one time for each unique header
  • store that content as a separate training item
  • remove the same header content from the page body before indexing
Benefits:
  • reduces duplicate information across many pages
  • keeps repeated navigation or shared header text from being indexed over and over
  • preserves useful shared site information for retrieval
When to enable:
  • when the header contains meaningful text that supports AI answers
  • when many pages share the same header content
Recommended use cases:
  • websites with shared product navigation or service overviews in the header
  • websites where the header contains reusable company or category information
Index Site Footer Use Index Site Footer when the site footer contains shared information that should be indexed only once. Purpose:
  • extract the website <footer> content one time for each unique footer
  • store that content as a separate training item
  • exclude that footer content from the page body during indexing
Benefits:
  • prevents duplicate footer text from being trained again on every page
  • keeps the main page content cleaner for retrieval
  • preserves useful global site information such as company details or support links
When to enable:
  • when the footer contains helpful shared text for search or chatbot answers
  • when the same footer appears on many pages
Recommended use cases:
  • websites with shared contact details, policy references, or company summaries in the footer
  • large sites where repeated footer content would otherwise be indexed many times
Enable Index Site Header and/or Index Site Footer in the data source form when creating or editing a Sitemap XML or Web Pages source.
Deleting a data source also removes its training queue and embedded data for that source.
Sync Sync (per source or Sync all) refreshes content from the source into the training queue.
  • Sync does not run AI training by itself.
  • Training is performed by the Scheduler task or manually (see Training Center).

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Command-line tools

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What is command-line scheduler execution?

Command-line scheduler execution means running the TYPO3 Scheduler task directly from your terminal. This is useful when you want to process the training queue immediately, without waiting for the next scheduled interval.

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How to run the scheduler task

  1. Open your terminal in the TYPO3 project root (where DDEV is available).
  2. Identify the correct T3AS Training task in the TYPO3 Scheduler first.
  3. Run that task manually from TYPO3 or execute it from the command line with the task ID from your own instance.
  4. Check the terminal output to confirm the task completed successfully.
If you are using DDEV, you can run the T3AS training task manually from the command line after confirming the correct task ID in System -> Scheduler. Legacy installation:
Composer installation:

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What happens after running the command?

  • TYPO3 executes the selected T3AS Training scheduler task.
  • Items in the training queue are processed.
  • You can verify progress and completion directly in the command output.

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Example output

Example command-line output for TYPO3 scheduler task run Example of scheduler task output in the terminal. Example command-line output showing queue processing and training completion Example showing queue processing and training completion summary. For more options and details, see the TYPO3 Scheduler documentation: https://docs.typo3.org/c/typo3/cms-scheduler/13.4/en-us/Administration/ConsoleTools/Running.html#providing-options-to-the-shell-script

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What is command-line scheduler execution?

Command-line scheduler execution means running the TYPO3 Scheduler task directly from your terminal. This is useful when you want to process the training queue immediately, without waiting for the next scheduled interval.

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How to run the scheduler task

  1. Open your terminal in the TYPO3 project root (where DDEV is available).
  2. Identify the correct T3AS Training task in the TYPO3 Scheduler first.
  3. Run that task manually from TYPO3 or execute it from the command line with the task ID from your own instance.
  4. Check the terminal output to confirm the task completed successfully.
If you are using DDEV, you can run the T3AS training task manually from the command line after confirming the correct task ID in System -> Scheduler. Legacy installation:
Composer installation:

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What happens after running the command?

  • TYPO3 executes the selected T3AS Training scheduler task.
  • Items in the training queue are processed.
  • You can verify progress and completion directly in the command output.

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Example output

Example command-line output for TYPO3 scheduler task run Example of scheduler task output in the terminal. Example command-line output showing queue processing and training completion Example showing queue processing and training completion summary. For more options and details, see the TYPO3 Scheduler documentation: https://docs.typo3.org/c/typo3/cms-scheduler/13.4/en-us/Administration/ConsoleTools/Running.html#providing-options-to-the-shell-script

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Command t3af:history:cleanup — history log cleanup

T3AF History Cleanup is the shared console command t3af:history:cleanup (AI Foundation / T3CS). It deletes AI Search and Chatbot usage history older than the retention period. This is separate from training-queue cleanup (--retention-days on nst3af:training). Use it to keep Usage Analytics history within a privacy or storage limit. If the task does not exist yet, create it in the TYPO3 Scheduler module:
  1. Create a new task and select Execute console commands.
  2. Choose t3af:history:cleanup.
  3. Set the days argument and the frequency on the Timing tab.
  4. Save the task.
Argument days : Retention in days before deletion. Edit this argument on the scheduler task. Default is 90 when omitted. Example commands Composer / TYPO3 v13+ (typical):
The first command uses the default of 90 days. Setting days to 3 deletes usage history older than 3 days (CLI: t3af:history:cleanup 3). Scheduler task t3af:history:cleanup with days argument set to 3 Configure days on the t3af:history:cleanup scheduler task. Default retention is 90 days when the argument is omitted. More options for other AI Foundation scheduler commands (MCP cleanup, and so on) are listed under AI Foundation → Scheduler & CLI in the TYPO3 backend.

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4.Training Center

Purpose View the training queue (items collected from all data sources) and control training and cleanup. What you see
  • Summary counts: Total items, Pending, Embedding (processing), Completed, Failed, and Tokens used.
  • All Sources: List or summary of data sources and item counts.
  • Training Queue table: Items with columns such as Item, Status, Tokens, Created, Actions.
  • Filters: By data source, status (All Statuses), or search text.
  • Actions: Select All, Delete, Re-queue (reset).
Queue item statuses:
  • Pending – Waiting to be processed.
  • Processing / Embedding – Currently being sent to the embeddings service.
  • Completed – Successfully trained.
  • Failed – Error during training.
Actions Sync Refreshes content from the data source into the queue (same as in the Data Source tab). Reset (Re-queue) Puts a failed or completed item back to Pending so it will be processed again on the next training run. Delete Removes selected queue items.
Deleted items will not be trained again unless they are added again by a new sync.
Run training Use the link to the Scheduler module and run the T3AS Training task for this site. When the task runs, it:
  • Processes all Pending queue items (generates embeddings).
  • Runs cleanup of old completed/failed items according to the retention setting.
Training behaviour (simple terms)
  • Only items in status Pending are processed when training runs.
  • Processing means: the text is sent to the configured embeddings service, and the result is stored for search usage.
  • After success, the item is marked Completed; on error, Failed.
  • How often training runs depends on the Sync interval of your data sources and on the Scheduler actually being triggered (e.g. via cron).

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  1. Search tab

The Search tab controls AI search for the whole site. Here you turn search on, set how answers look, enable Save search history, style the widget, and manage suggested questions. Settings on a single page plugin can override these defaults. Step 1: Open the T3AS module. Step 2: Click the Search tab. Step 3: Configure Settings, Widget, and Questions. Settings Turn AI search on and control answer behaviour.
  • Enable AI Search Globally — Activates AI search across the site
  • Save search history — Stores visitor search queries and answers for analytics
  • Enable Reference Links — Shows source links below the answer (pages, PDFs, etc.)
  • Enable Voiceover — Adds a play button so visitors can hear the answer
  • Enable Search Feedback — Shows thumbs up/down; ratings appear in Usage Analytics
  • Enable Chatbot Mode — Lets visitors ask follow-up questions
  • Result Style — Summarize (short) or Long Answer (detailed)
  • Search Class — CSS class of the third-party search input used when injecting the AI overview (ke_search, indexed_search, or Solr). See Injecting AI Search result in TYPO3 Search Extensions.
  • Instructions — Custom rules for how the AI should write answers
Widget Style the search box and floating trigger button (for modal or floating layouts).
  • Widget Mode — How the widget opens (e.g. Modal Box (Centered))
  • Widget/Modal Trigger Button Position — Trigger button position (e.g. Left (bottom))
  • Trigger Button Size — Size of the floating trigger button
  • Search Icon — Icon on the search box or trigger
  • Trigger Button Background — Background style of the trigger button
  • Select Style — Default Style (site colours) or Customized Style (plugin)
  • Border Radius — Corner roundness (e.g. Semi Rounded)
  • Select Loader — Skeleton Loader or Typing Loader while the answer loads
  • Primary Color / Secondary Color / Text Color — Only when Customized Style is selected
  • Search Form Type — Input layout (e.g. With Button)
  • Button Type — Search Icon or With Label
Questions Set up clickable question suggestions in the search box.
  • Predefined Questions — Enable suggested questions
  • Question Position — Where they appear (e.g. Bottom Search)
  • Number of Questions to Show — How many to display (e.g. 5)
  • Questions Storage Folder(s) — Page ID of the folder with question records (e.g. 681)
These settings apply site-wide. To override them on one page, use the T3AS Search frontend plugin. See T3AS Search Plugin.

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6. Usage Analytics

The Usage Analytics tab records visitor search activity. You can see what was searched, what answer was given, feedback ratings, and reference links used. Step 1: Open the T3AS module. Step 2: Click Usage Analytics. What you see Each row in the log list shows:
  • Search term — What the visitor typed
  • AI answer — Short summary of the result
  • Module — e.g. Search
  • Feedback — Thumbs up or down (when Search Feedback is enabled)
  • Reference links — Number of source links shown
  • Page, language, time — Where and when the search happened
Open a log entry Click a row to see the full detail:
  • Negative feedback and any visitor comment
  • Search badge — Click to filter logs by that search term
  • Reference sources — Pages or files used to build the answer
  • All messages — Full chat history (when Chatbot Mode is on)
  • Delete This Log — Remove a single entry
Filter and export
  • Search queries or responses — Find text in the logs
  • All Modules — Filter by module (e.g. Search only)
  • All Languages — Filter by language
  • Export — Download log data as a file
Enable Search Feedback in Search → Settings or in the plugin Search Results tab to collect thumbs up/down ratings.
When no data exists yet: “No interaction logs yet. Search and search history will appear here when the modules are loaded and users interact.” Enable Save search history in Search → Settings so visitor queries and answers appear in this log. To delete old usage history automatically, use the t3af:history:cleanup scheduler task (see Scheduler on this page). Default retention is 90 days.

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7. AILogs

Purpose View log entries for the current site, including sync, training, and error events. What you see
  • Search: Use the search box (for example: Search in message...) to find specific log text.
  • Channel: Filter by channel (default: [all]).
  • Level: Filter by log level (for example: Any, Error, Warning, Info).
  • Max rows: Set how many rows are shown per page (default: 50).
  • Entry count: The page shows a summary like Showing up to 50 of 745 entries per page.
  • Log table columns:
  • Time
  • Level
  • User
  • Details

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8. AI Statistics

Purpose View AI API usage statistics for the current site. What you see
  • API Usage summary for your search activity.
  • API Requests count.
  • Tokens usage details:
  • Total tokens
  • Context tokens
  • Generated tokens

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9. AI Prompts

Use AI Prompts to control how T3AS writes answers, summaries, and search-related responses. This is useful when you want search output to follow a consistent tone, answer style, or instruction set across the whole site. Best practices:
  • Keep instructions focused on answer quality, tone, and length.
  • Test prompt changes with real user questions.
  • Review AI Foundation AI Prompts when you want shared prompt behavior across multiple AI Universe extensions.

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10. Providers & MCP Tools

T3AS uses AI Foundation for shared provider setup and MCP-based integrations. Review this area when you need to confirm that the correct provider, model, and MCP capabilities are available for search and training workflows. See also:

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Command nst3af:training — all options

You can run the same command manually from the project root (for example with DDEV). Replace <rootPageId> with your site root page ID and <taskUid> with the numeric UID from the Scheduler module (do not assume a fixed ID such as 9). Argument rootPageId (optional when using scheduler:run --task=) Site root page ID. Required for direct CLI runs unless the scheduler passes it via the task. Options --source=ID Process only one data source (must belong to the site). --detailed Verbose output (each URL, PDF, and similar). Enabled by default on the automatic scheduler task. It will show the detailed progress in the CLI command. --dry-run Preview only — no API calls and no database updates. --limit=N Process at most N queue items per data source. --batch-size=N Embedding batch size (default: extension Batch size or 100). Set on the scheduler task from extension settings when the task is created or updated. --skip-cleanup Skip the post-training cleanup phase. --cleanup-only Run cleanup only (no sync, no embedding). --retention-days=N Delete or archive queue rows older than N days (default: extension Retention days or 30). Set on the scheduler task from extension settings. --no-archive Delete old queue rows without writing a CSV archive first. --optimize-db Run OPTIMIZE TABLE after cleanup. --queue-failed Move Failed queue items back to Pending before processing. --force / -f Re-train all: set all queue items (completed/failed/processing) back to Pending and process. It does not automatically set sync_requested. Sync still requires the Sync action from the DataSource tab. What the automatic scheduler task uses Only rootPageId, --batch-size, --retention-days, and --detailed. All other options are for manual CLI or custom scheduler tasks you create yourself. Example commands Composer / TYPO3 v13+ (typical):
Legacy non-Composer installs may use scheduler:execute instead of scheduler:run; see TYPO3 Scheduler CLI documentation. Example command-line output for TYPO3 scheduler task run Example of scheduler task output in the terminal. Example command-line output showing queue processing and training completion Example showing queue processing and training completion summary.

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Extension settings used by training (AI Foundation -> AI Features)

These T3CS / AI Chatbot & Search settings are applied when the scheduler task is configured:
  • Batch size → --batch-size on the task
  • Retention days → --retention-days on the task
  • Chunk size, Max link crawl, rate limits — affect sync and embedding behavior during the run
  • Log archive path (optional) — where cleanup CSV archives are stored
More options for other AI Foundation scheduler commands (MCP cleanup, and so on) are listed under AI Foundation → Scheduler & CLI in the TYPO3 backend.