AI powered Resume Parser

This guide will help you build an AI-powered resume parsing system. The workflow takes a resume as input, extracts key details such as name, contact information, skills, experience, and education, and converts the data into a structured JSON format. This system automates resume processing, enabling efficient candidate analysis and seamless integration with recruitment workflows.

What You'll Build

A Simple API that processes resumes, extracts relevant details, and generates structured JSON output

Getting Started

1. Project Setup

1. Sign up at Lamatic.ai (opens in a new tab) and log in.
2. Navigate to the Projects and click New Project or select your desired project.
3. You'll see different sections like Flows, Context, and Connections

2. Creating a New Flow

1. Navigate to Flows, select New Flow.
2. Click Create from scratch as starting point.

3. Setting Up Your API

1. Click "Choose a Trigger"
2. Select "API Request" under the interface options
3. Configure your API:
   • Add your Input Schema
   • Set url as parameter in input schema
   • Set response type to "Real-time"
   • Click on save

3. Extract File Node

1. Add the "Extract File" node to your flow.
2. Configure the file extraction settings to take the url and type of file. If using a PDF, select 'Join Pages' to extract the text from all pages.
3. The file contents and details will be extracted and are to be passed to extract textual content from the file.

5. Adding AI Text Generation

1. Click the "+" icon to add a new node

2. Choose "Generate Text"

3. Configure the AI model:

   • Select your "Open AI" credentials
   • Choose "gpt-4-turbo" as your Model

4. Click on "+" under Prompts section.

5. Set up your prompt:

Take this data from a resume  and convert it into a structured JSON format. The JSON should include the following fields where applicable: 'name',
'contact' (with subfields 'email', 'phone', and 'address'), 'summary', 'education' (as an array with subfields 'degree', 'institution', 'location', and 'dates'), 
'experience' (as an array with subfields 'job_title', 'company', 'location', 'dates', and 'responsibilities' as an array of strings), 'skills' (as an array of strings), and 'certifications' (as an array of strings). 
If any section is missing or unclear, leave it as an empty string or array in the JSON. Parse the resume content accurately and organize it into the specified structure, ensuring proper nesting and formatting. Provide the output as a valid JSON object.

• You can add variables using the "insert Variable" button

5. Configuring the reponse

1. Click the API response node
2. Add Output Variables by clicking the + icon
3. Select variable from your Generate Text Node

7. Test the flow

1. Click on 'API Request' trigger node
2. Click on Configure test
3. Fill sample value in 'url' and click on test

8. Deployment

1. Click the Deploy button
2. Add the purpose and description of your project
3. Your API is now ready to be integrated into Node.js or Python applications
4. Your flow will run on Lamatic's global edge network for fast, scalable performance

9. What's Next?

• Experiment with different prompts
• Try other AI models
• Add more processing steps to your flow
• Integrate the API into your applications

10. Tips

• Save your tests for reuse across different scenarios
• Use consistent JSON structures for better maintainability
• Test thoroughly before deployment

Now you have a working AI-powered API! You can expand on this foundation to build more complex applications using Lamatic.ai's features.