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Artificial Evaluation and Scheduling System for Candidates

This project automates the resume screening process using n8n and a Large Language Model (LLM) to efficiently process job applications.

✨ How It Works
A workflow is triggered by a new email containing a resume attachment.

The resume text is extracted and sent to an AI model (e.g., Google Gemini, OpenAI).

The AI analyzes the resume against a job role and returns a structured JSON object with key information and a score.

The workflow checks for a dedicated Google Sheet.

If the sheet exists, it appends the new candidate's data as a new row.

If the sheet does not exist, it creates a new one with the correct headers and then appends the data.

All extracted data, including the resume score and a brief justification, is saved in the Google Sheet for easy review.

🛠️ Setup
Credentials:

Set up Google Sheets and Gmail credentials via OAuth 2.0.

Obtain and configure API keys for your chosen AI model (e.g., OpenAI or Google Gemini).

If needed, add credentials for a PDF-to-text API to handle resume file formats.

Google Sheet:

Create a blank Google Spreadsheet to serve as the master file. The workflow will handle creating the specific data sheet within it.

Workflow:

Build the n8n workflow using the following key nodes: Gmail Trigger, Google Sheets, HTTP Request (for parsing PDFs), an AI node, and an If node for conditional logic.

Configure the If node's condition to check for the sheet's existence.

🚀 Key Takeaway
By activating this workflow, you can automate a significant portion of the initial hiring process, saving time and ensuring a consistent, data-driven approach to candidate screening.