AI Chatbot

Overview

The Sparrow AI Chatbot is a built-in assistant within the Sparrow API Testing Tool, designed to help developers move faster when working with APIs. Powered by advanced LLMs like GPT-4o and DeepSeek, the chatbot supports intelligent, multi-turn conversations to assist you in:

• Generating CURL commands
• Writing clean API documentation
• Creating realistic mock data
• Inserting data directly into requests
• Debugging errors in API responses

It reads the current API request context (method, URL, headers, body, etc.) so you don’t have to explain things from scratch.

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Getting Started

1. Open any API request inside the Sparrow API Testing Tool.

2. The Sparrow AI Chatbot panel will appear on the right.

   

3. You can interact with the chatbot in two ways:

   • Click chip buttons for quick actions like Generate CURL, Generate Documentation, Generate Mock Data, etc.

   

   • Type in natural language (e.g., “Can you convert this to curl?”, “Give me test data for this payload”).

   

4. The chatbot uses the current API request (method, URL, headers, body) as context — no need to paste or explain anything.

5. It supports multi-turn conversations. The bot remembers previous messages, so you can ask follow-up questions or refine its suggestions.

6. Each conversation is tied to the specific API request you're working on. Switching APIs resets the chatbot context accordingly.

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Features & How to Use Them

1. Generate CURL

What it does:

• Converts your current API request (URL, method, headers, body) into a well-formatted curl command.

Use Case:

• Share curl commands with teammates
• Use in CLI or documentation
• Debug using terminal tools

How to use:

• Click the “Generate CURL” chip

• Or type:
  "Convert this API request into a curl command"

  

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2. Generate Documentation

What it does:

• Creates a clean API documentation block based on your current request.

Includes:

• Endpoint and method
• Headers and body fields
• Example curl request
• Expected response format

Use Case:

• Create quick API specs
• Share docs with clients
• Add to developer portals

How to use:

• Click the “Generate Documentation” chip

• Or type:
  "Create documentation for this API"

  

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3. Generate Mock Data

What it does:

• Generates realistic sample data for the request body based on field names and types.

Use Case:

• Populate payloads during testing
• Simulate frontend/backend interaction
• Hand off sample requests to QA or frontend devs

How to use:

• Click “Generate Mock Data”

• Or type:
  "Generate mock data for this request"

  

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4. Insert Mock Data

What it does:

• Lets you directly insert generated mock data into the current request (no copy/paste needed).

Options:

• Insert into Request Body
• Insert into Request Headers

Use Case:

• Quickly fill out request details
• Avoid formatting issues
• Save time in test prep

How to use:

• After generating mock data, click “Insert Suggestion” button in the chatbot suggestions to insert the suggestion in the respective Request Body or Request Headers

  

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5. Error Debugging

What it does:

• When an API call returns a 4xx or 5xx error, a “Help Me Debug” button appears automatically in the chatbot panel.
• Clicking this button sends the full request details, response code, and error message to the AI.
• The AI reads the failed request and response and suggests possible causes and actionable fixes (e.g., missing headers, malformed body, invalid tokens).

Use Case:

• Speed up the debugging process with AI assistance
• Identify missing or incorrect elements (headers, query params, request body, etc.)
• Fix common API issues without manually analyzing the response

How to use:

1. Run the API as usual.

2. If a 4xx or 5xx response occurs, click “Help Me Debug” when it appears.

3. The chatbot will analyze the API and show a list of possible issues with suggestions.

4. Click “Fix with AI” to automatically apply the suggested fix to the appropriate part of the request (e.g., Headers, Body, Query Params).

5. Re-run the API using the updated request.

   

   

   

   

   

This flow lets you quickly diagnose and fix errors without switching tabs or scanning logs manually.

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How It Works Behind the Scenes

Multi-Turn Conversation

The chatbot supports contextual, multi-round interactions, meaning:

• It remembers previous prompts and responses
• You can ask follow-up questions without repeating the request
• It understands corrections or refinements based on prior steps

Example Flow:

User: Generate documentation for this API  
Bot: [Returns doc]  
User: Can you simplify it?  
Bot: [Returns a shorter version]  
User: Add example error response too