How to Integrate with Zapier

Learn how to use the SnackPrompt AI Engine API to build powerful automations and AI-powered workflows in Zapier.

Overview

Zapier offers several ways to integrate external APIs into your automations:

Method	Use Case	Description
Webhooks by Zapier	Receive data	Trigger Zaps when external events occur
API Request (Beta)	Direct API calls	Make HTTP requests to any API
Code by Zapier	Advanced processing	Run JavaScript/Python to process data
Chatbots by Zapier	AI conversations	Build chatbots with custom knowledge

Integration Architecture

┌─────────────────────────────────────────────────────────┐
│                       Zapier                            │
│  ┌─────────────┐    ┌─────────────┐    ┌────────────┐   │
│  │   Trigger   │───▶│  API Request│───▶│   Action  │   │
│  └─────────────┘    └──────┬──────┘    └────────────┘   │
│                            │                            │
│                     ┌──────▼──────┐                     │
│                     │ Code Step   │                     │
│                     │ (optional)  │                     │
│                     └──────┬──────┘                     │
└────────────────────────────┼────────────────────────────┘
                             │
                             ▼
              ┌──────────────────────────────┐
              │  SnackPrompt AI Engine API   │
              │  /v1/kb/search or /v1/kb/chat│
              └──────────────────────────────┘

---

Method 1: API Request (Recommended)

Use the API Request action to call the SnackPrompt AI Engine API directly.

Step 1: Create a New Zap

1. Go to zapier.com and click Create Zap

2. Choose your trigger (e.g., New Email, New Form Submission, Schedule)

Step 2: Add API Request Action

1. Click + to add a new action

2. Search for API Request (Beta) or Webhooks by Zapier

3. Select Custom Request

Step 3: Configure the Request

For Search Endpoint:

Field	Value
Method	POST
URL	https://api-integrations.snackprompt.com/v1/kb/search

Headers:

Key	Value
Content-Type	application/json
x-api-key	YOUR_API_KEY

Body:

{
  "query": "{{trigger_field}}",
  "filters": {
    "tenant_id": "YOUR_TENANT_ID"
  },
  "limit": 5
}

Replace {{trigger_field}} with the field from your trigger that contains the search query.

Step 4: Use the Results

The API returns a list of relevant documents. You can use the results in subsequent actions:

• Send an email with the information found

• Update a CRM record

• Post to Slack

• Create a support ticket

---

Method 2: Webhooks by Zapier (Receive Requests)

Use when you want to receive requests and respond with knowledge base information.

Step 1: Create Webhook Trigger

1. Create a new Zap

2. Select Webhooks by Zapier as trigger

3. Choose Catch Hook

4. Copy the webhook URL provided

Step 2: Add API Request Action

Configure as shown in Method 1, using the data from the webhook:

Body:

{
  "query": "{{catch_hook_query}}",
  "filters": {
    "tenant_id": "YOUR_TENANT_ID"
  },
  "limit": 5
}

Step 3: Return Response (Optional)

If you need to return a response to the webhook caller:

1. Add Webhooks by Zapier action

2. Select Return Response

3. Configure the response body with the API results

---

Method 3: Chat Endpoint for Complete Responses

Use the /v1/kb/chat endpoint when you want the API to handle all the RAG and return a ready response.

Configuration

URL:

https://api-integrations.snackprompt.com/v1/kb/chat

Headers:

Key	Value
Content-Type	application/json
x-api-key	YOUR_API_KEY

Body:

{
  "query": "{{trigger_field}}",
  "filters": {
    "tenant_id": "YOUR_TENANT_ID",
    "tag_names": ["Support", "FAQ"]
  }
}

Response

The API returns:

• answer: AI-generated response ready to use

• sources: Sources used to generate the response

---

Method 4: Code by Zapier (Advanced)

Use when you need to process or transform the API response.

Step 1: Add Code Step

1. Add Code by Zapier action

2. Choose Run JavaScript or Run Python

Step 2: JavaScript Example

Input Data:

• query: The search query from trigger

• api_key: Your API key

• tenant_id: Your tenant ID

Code:

const response = await fetch('https://api-integrations.snackprompt.com/v1/kb/search', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'x-api-key': inputData.api_key
  },
  body: JSON.stringify({
    query: inputData.query,
    filters: {
      tenant_id: inputData.tenant_id
    },
    limit: 5
  })
});

const data = await response.json();

// Format results for easy use
const formattedResults = data.items.map((item, index) => ({
  position: index + 1,
  text: item.payload.original_text,
  score: item.score,
  id: item.payload.snack_item_id
}));

output = {
  results: JSON.stringify(formattedResults),
  firstResult: formattedResults[0]?.text || 'No results found',
  resultCount: formattedResults.length
};

Step 3: Python Example

import requests
import json

response = requests.post(
    'https://api-integrations.snackprompt.com/v1/kb/search',
    headers={
        'Content-Type': 'application/json',
        'x-api-key': input_data['api_key']
    },
    json={
        'query': input_data['query'],
        'filters': {
            'tenant_id': input_data['tenant_id']
        },
        'limit': 5
    }
)

data = response.json()

# Format results
results = []
for i, item in enumerate(data.get('items', [])):
    results.append({
        'position': i + 1,
        'text': item['payload']['original_text'],
        'score': item['score']
    })

output = {
    'results': json.dumps(results),
    'first_result': results[0]['text'] if results else 'No results found',
    'result_count': len(results)
}

---

Practical Use Cases

1. Email Auto-Responder

[New Email in Gmail] → [API Request: /chat] → [Send Reply with answer]

Automatically respond to customer emails using knowledge base information.

2. Slack Support Bot

[New Message in Slack Channel] → [API Request: /search] → [Post Reply to Thread]

Answer questions posted in a support Slack channel.

3. CRM Enrichment

[New Lead in HubSpot] → [API Request: /search] → [Update Lead with relevant docs]

Automatically attach relevant documentation to new leads based on their inquiry.

4. Form Response Handler

[New Typeform Submission] → [API Request: /chat] → [Send Email with answer]

Process form questions and send personalized responses.

5. Scheduled Knowledge Digest

[Schedule: Every Monday] → [API Request: /search] → [Create Notion Page]

Generate weekly digests of popular topics from your knowledge base.

6. Multi-Step Support Flow

[Webhook: Receive Question]
        │
        ▼
[API Request: /search with tag=FAQ]
        │
        ▼
[Filter: Check if results found]
        │
    ┌───┴───┐
    │       │
    ▼       ▼
[Found]  [Not Found]
    │       │
    ▼       ▼
[Reply] [Create Ticket]

---

Configuration Tips

1. Store API Key Securely

Use Zapier's Secret Manager or environment variables:

1. Go to your Zap settings

2. Add a Secret for your API key

3. Reference it as {{secrets.snackprompt_api_key}}

2. Use Filters Wisely

Direct searches with tags when you know the context:

{
  "filters": {
    "tenant_id": "...",
    "tag_names": ["{{detected_category}}"]
  }
}

3. Handle Empty Results

Add a Filter or Paths step after the API call:

[API Request] → [Filter: items length > 0] → [Send Response]
                                          ↘ [Fallback Action]

4. Limit Results for Cost Efficiency

Start with fewer results and increase if needed:

{
  "limit": 3
}

5. Add Error Handling

Use Zapier's built-in error handling:

1. Click on your API Request step

2. Go to Advanced Settings

3. Enable Continue on Error

4. Add a Paths step to handle errors

---

Complete Example: Customer Support Automation

Workflow Overview

1. Customer submits question via form

2. Zap searches knowledge base

3. If answer found, send automated reply

4. If not found, create support ticket

Step-by-Step Setup

Step 1: Trigger - New Form Submission

• App: Typeform, Google Forms, or Jotform

• Trigger: New Response

Step 2: Action - API Request

• URL: https://api-integrations.snackprompt.com/v1/kb/chat

• Method: POST

• Headers:

  Content-Type: application/json
  x-api-key: YOUR_API_KEY

• Body:

  {
    "query": "{{form_question_field}}",
    "filters": {
      "tenant_id": "YOUR_TENANT_ID",
      "tag_names": ["Support"]
    }
  }

Step 3: Paths - Check Response Quality

• Path A: If sources array is not empty

• Path B: If sources array is empty

Step 4A: Send Automated Reply

• App: Gmail or your email service

• To: {{form_email_field}}

• Subject: Re: {{form_subject_field}}

• Body: {{api_response_answer}}

Step 4B: Create Support Ticket

• App: Zendesk, Freshdesk, or Linear

• Create ticket with original question

---

Troubleshooting

Error: "tenant_id is required"

Make sure tenant_id is inside the filters object:

// ❌ Wrong
{ "query": "...", "tenant_id": "..." }

// ✅ Correct
{ "query": "...", "filters": { "tenant_id": "..." } }

Error: "Invalid JSON"

Check your JSON body for:

• Missing commas between fields

• Unescaped quotes in dynamic values

• Trailing commas (not allowed in JSON)

Use a Code step to safely construct JSON:

output = {
  body: JSON.stringify({
    query: inputData.query,
    filters: { tenant_id: inputData.tenant_id }
  })
};

API Returns Empty Results

1. Verify your tenant_id is correct

2. Check if the query matches content in your knowledge base

3. Try removing tag_names filter to search all content

4. Increase the limit parameter

Zap Runs but No Response

1. Check the API Request step output in Zap History

2. Verify the response is being mapped correctly to the next step

3. Ensure the response fields match what you're referencing

Rate Limiting

If you hit rate limits:

1. Add a Delay step before API calls

2. Use Zapier's built-in throttling in Zap settings

3. Consider batching requests with Looping by Zapier

---

Zapier AI Integration

Using with Zapier Central (AI)

Zapier Central can use the SnackPrompt API as a data source:

1. Create an API Connection in Zapier Central

2. Configure the search endpoint

3. Ask Central to query your knowledge base

Chatbots by Zapier

Build a chatbot that uses your knowledge base:

1. Create a new Chatbot

2. Add a Custom Action that calls the /chat endpoint

3. Use the response as the bot's reply

---

Related

• Endpoints Reference

• Available Filters

• Error Hand

External Resources

• Zapier Webhooks Documentation

• API Request Action Docs

• Code by Zapier Guide

• Zapier Paths for Conditional Logic