Using a custom body field, show a list of addresse...
# ask-stanley-ai
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Using a custom body field, show a list of addresses on a Purchase Order that are sourced from the Vendor
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AI generated answer (using internal Slack threads):
To display a list of addresses on a Purchase Order that are sourced from the Vendor, you can create a custom body field of type 'Text Area' on the Purchase Order transaction form. This field can be sourced from the Vendor record. Here are the steps to achieve this: 1. Navigate to
Customization > Lists, Records, & Fields > Transaction Body Fields > New
. 2. In the Label field, enter a name for your custom field (e.g., "Vendor Addresses"). 3. Set the Type to 'Text Area'. 4. In the Applies To subtab, check the 'Purch Ord' box to apply this field to Purchase Orders. 5. In the Sourcing & Filtering subtab, set the Source List to 'Vendor' and the Source From to the address field from the Vendor record. 6. Save the custom field. Once this is set up, when you select a Vendor on a Purchase Order, the custom field will automatically populate with the Vendor's address. Please note that you might want to make this field read-only to prevent accidental changes. This can be done by checking the 'Store Value' box in the custom field settings. Also, if you want to show multiple addresses from the Vendor, you might need to use a SuiteScript or a workflow to concatenate the addresses into a single text string, as the custom field can only source from a single field on the Vendor record. ****** Disclaimer: This response was generated by an artificial intelligence assistant based on previous conversations from multiple Slack channels, and may contain inaccuracies or mistakes. ******
Slack thread 1: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.860444069
Slack thread 2: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.847477317
Slack thread 3: here (available only if the original thread was posted in the last 90 days)
Similarity score: 0.842354119
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