# Documented Data ## Overview #### Why Use Documented Data? If you'd like to use generated answers, but critical data is missing from your website and/or in a format that cannot be read by our web-scraping tool (PDFs, images, videos), then you will want to create a documented response! Documented data is pulled from uploaded documents in the dashboard and it reads the same way as scraped URL data. This data can be adjusted directly within the dashboard. ## Add New Documented Data {% embed url="" fullWidth="true" %} How to Add Documented Data {% endembed %} To add new documented data, follow the steps below: 1. While in the [Satisfi Dashboard](https://dashboard.satis.fi/Users/Login), go to Studio -> NLP Manager -> Responses 2. Under LLM Content Group, find and Open the "**doc\_sample\_response**" name 3. Click on the Clone button 4. Create a new response name using doc\_\[topic] 5. Follow the guidelines specified for adding content, such as: * Add the topic header * Add relevant content * Use a 5-dash separator between topics if multiple topics are within one response 6. Hit Publish 7. Training will automatically occur to update your chat {% hint style="info" %} You can have any number of cloned doc\_responses divided by categories of content, like policies, tickets, kids, food, and much more {% endhint %} *** ## Update/Delete Existing Documented Data {% embed url="" fullWidth="true" %} How to Edit and Delete Documented Data {% endembed %} To update documented data, follow the steps below: 1. While in the [Satisfi Dashboard](https://dashboard.satis.fi/Users/Login), go to **Studio -> NLP Manager -> Responses** 2. Locate the corresponding response labeled as “doc\_” and click on it 3. Hit **Edit** and update the response 4. When done, press **Ready to Publish -> Publish** To delete documented data, follow the steps below: 1. While in the [Satisfi Dashboard](https://dashboard.satis.fi/Users/Login), go to Studio -> NLP Manager -> Responses 2. Locate the corresponding response labeled as “doc\_” and click on it 3. Click the trash can icon and confirm *** ## Our Recommendations ### Enrich Your Responses Since documented data is used to create generated responses, you are unable to add enrichments directly in documented data. To learn how to add enrichments to generated responses, click the link below! {% content-ref url="enrich-generated-responses" %} [enrich-generated-responses](https://docs.satisfilabs.com/resource-center/ai-agent-engine/manage-your-content/response-types/generated-responses/enrich-generated-responses) {% endcontent-ref %} ### Check Your Format We provide a sample of how your documented data should be formatted in your LLM volume. You can find the example in your library under the response name "doc\_sample\_response". Below are a few formats we recommend when adding documented data: *-----* *The following inputs are related to buying tickets:*\ \&#xNAN;*How do I buy tickets?*\ \&#xNAN;*Can I purchase tickets?*\ \&#xNAN;*Are tickets available?*\ \&#xNAN;*Answer:*\ \&#xNAN;*Yes, tickets are available for purchase on the website.* *-----* *Season Tickets:*\ \&#xNAN;*When do single-game tickets go on sale?*\ \&#xNAN;*Answer:*\ \&#xNAN;*Single-game tickets go on sale at the beginning of the season.* *-----* *Parking Information:* *Parking lots open four hours before the first pitch Parking is first come, first serve and is subject to availability. Parking is $15 in all lots.* {% hint style="info" %} When cloning the sample documented response name (doc\_sample\_response), be sure to remove any sample information listed and review your data before publishing! {% endhint %} ### Inspect for Quality We always recommend that you review responses that are generated and exposed within your chat. {% hint style="danger" %} If your documented data is not being understood by the LLM, this may be due to poor formatting within the response. To fix this: * Find the corresponding labeled response in the library * Click **Edit** * Ensure that: * There is a header description related to the data's topic * All sections are separated by a 5 “-----” * No section is very short or extremely long {% endhint %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.satisfilabs.com/resource-center/ai-agent-engine/manage-your-content/response-types/generated-responses/documented-data.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.