Quickstart: Your First Call in 5 Minutes

In this tutorial, you'll make your first call to the SnackPrompt AI Engine API and receive semantic search results.

Prerequisites

Before you begin, you need:

• A valid tenant_id (provided by the platform administrator)

• Data already ingested in the Knowledge Base (if you don't have any, follow the Ingesting Data tutorial first)

• A tool to make HTTP requests (curl, Postman, Insomnia, etc.)

Step 1: Make a Semantic Search

Let's start with a simple search. Run the command below, replacing YOUR_TENANT_ID with your tenant_id:

curl -X POST https://api-integrations.snackprompt.com/v1/kb/search \
  -H "Content-Type: application/json" \
  -d '{
    "query": "what are the available products?",
    "filters": {
      "tenant_id": "YOUR_TENANT_ID"
    },
    "limit": 5
  }'

Step 2: Understand the Response

If everything is correct, you'll receive a response like this:

{
  "items": [
    {
      "id": "abc123-uuid",
      "score": 0.85,
      "payload": {
        "tenant_id": "YOUR_TENANT_ID",
        "snack_elemental_id": "elemental-456",
        "snack_item_id": "item-789",
        "original_text": "Our products include: Management software, Integration API, Analytics Dashboard...",
        "tag_names": ["Products", "Catalog"]
      }
    },
    {
      "id": "def456-uuid",
      "score": 0.72,
      "payload": {
        "tenant_id": "YOUR_TENANT_ID",
        "snack_elemental_id": "elemental-456",
        "snack_item_id": "item-790",
        "original_text": "Product price list effective from...",
        "tag_names": ["Products", "Prices"]
      }
    }
  ],
  "total_found": 2
}

What Each Field Means

Field	Description
items	List of results found
id	Unique identifier of the result in the vector database
score	Semantic similarity (0 to 1, higher is more relevant)
payload.original_text	The original document content
payload.snack_elemental_id	ID of the source elemental (document/table)
payload.tag_names	Tags associated with the content
total_found	Total number of results found

Step 3: Try the Chat

Now that you've seen how search works, try chat to get more elaborate answers:

curl -X POST https://api-integrations.snackprompt.com/v1/kb/chat \
  -H "Content-Type: application/json" \
  -d '{
    "query": "what are the available products and how much do they cost?",
    "filters": {
      "tenant_id": "YOUR_TENANT_ID"
    }
  }'

The response will include an AI-generated answer based on your data:

{
  "answer": "Based on the available data, the products offered are: Management software ($99/month), Integration API ($199/month), and Analytics Dashboard ($149/month). All plans include technical support.",
  "sources": [
    {
      "id": "abc123-uuid",
      "score": 0.85,
      "snack_item_id": "item-789",
      "text": "Our products include..."
    }
  ]
}

Possible Errors

Error: tenant_id required

{
  "detail": "tenant_id is required in filters"
}

Solution: Make sure to include tenant_id inside the filters object.

Error: No results found

{
  "items": [],
  "total_found": 0
}

Solution: Check if you've already sent data to the Knowledge Base. Follow the Ingesting Data tutorial.

Next Steps

Now that you've made your first call, continue learning:

1. Ingesting Data - Learn how to send your own data

2. Semantic Search - Learn advanced search techniques

3. Chat with your Data - Explore all chat options

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Estimated time: 5 minutes ✅