Ingesting Data into the Knowledge Base

In this tutorial, you'll learn how to send data to the SnackPrompt AI Engine Knowledge Base.

What is an Elemental?

An elemental is the basic unit of data in SnackPrompt. It can be:

• A table with columns and items

• A document with sections

• A file with structured content

When you send an elemental, the API:

1. Processes the content

2. Generates embeddings (vector representations)

3. Stores in the Knowledge Base

4. Makes the data searchable

How to create a simple Knowledge Base

Step 1: Set up your Knowledge Base

The first step is to ensure your data is accessible to the AI. In Snackprompt, you can transform any element into a data source:

1. Create a Table, Document, or Prompt.

2. Populate it with your data.

3. Enable the Knowledge Base toggle in the settings menu.

For a detailed step-by-step on this process, see our guide: Creating your first Knowledge Base.

What Happens During Ingestion?

When you send an elemental, the API executes the following steps:

1. Receives the elemental_id
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2. Fetches complete data from SnackPrompt platform
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3. Processes the content (parsing)
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4. Splits into chunks (smaller pieces)
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5. Generates embeddings
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6. Stores in our Vector Database
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7. Data available for search!

Stored Metadata

During ingestion, the following metadata is stored with each chunk:

Field	Description
tenant_id	Tenant ID (for isolation)
user_id	User ID
snack_elemental_id	Source elemental ID
snack_column_id	Column ID (if applicable)
snack_item_id	Specific item ID
source	Source type (elemental, document, file)
type_name	Elemental type (Table, Document, etc.)
category_name	Elemental category
original_text	Original chunk content
tag_ids	Associated tag IDs
tag_names	Associated tag names

Tag Inheritance

Tags are inherited in cascade:

Document (document tags)
    └── Column (column tags)
            └── Item (item tags)

The final item will have the merge of all tags (no duplicates).

Next Steps

Now that your data is in the Knowledge Base:

1. Semantic Search - Learn how to search your data

2. Chat with your Data - Chat with your data using AI

3. Filter by Tags - Use tags to filter results

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Estimated time: 10 minutes ✅