n8n Workflow: Score Resumes Against Job Descriptions with Google Drive, Google Sheets, and GPT-4o

This n8n workflow automates the process of scoring resumes against job descriptions (JDs) using AI. It retrieves job descriptions from Google Sheets, fetches resumes from Google Drive, extracts their content, and then uses an AI agent (GPT-4o via Azure OpenAI) to score each resume against a specific JD.

What it does

1. Triggers Manually: The workflow is initiated by a manual trigger.
2. Retrieves Job Descriptions: It reads job description data from a specified Google Sheet.
3. Lists Resumes: It connects to Google Drive to list all resume files (e.g., PDFs) from a designated folder.
4. Extracts Resume Content: For each resume file found in Google Drive, it extracts the text content.
5. Scores Resumes with AI: It then uses an AI Agent powered by Azure OpenAI (likely GPT-4o, given the directory name context) to compare the extracted resume content against the job description. The AI agent provides a score or evaluation.
6. Outputs Results: The final scores or evaluations are then available for further processing (e.g., writing back to Google Sheets, sending notifications, etc. - Note: The provided JSON only shows the AI agent as the last step, but typically this would be followed by an output action).

Prerequisites/Requirements

To use this workflow, you will need:

• n8n Instance: A running instance of n8n.
• Google Sheets Account: With a spreadsheet containing your job descriptions.
• Google Drive Account: With a folder containing the resumes you want to score.
• Azure OpenAI Service: An Azure OpenAI deployment with access to a chat model (e.g., GPT-4o).
• n8n Credentials: Configured credentials for:
  • Google Sheets
  • Google Drive
  • Azure OpenAI Chat Model

Setup/Usage

1. Import the Workflow: Import the provided JSON into your n8n instance.
2. Configure Credentials:
   • Set up your Google Sheets credential.
   • Set up your Google Drive credential.
   • Set up your Azure OpenAI Chat Model credential, ensuring it points to your deployed model.
3. Configure Google Sheets Node (ID: 18):
   • Specify the Spreadsheet ID and Sheet Name where your job descriptions are located.
   • Ensure the column containing the job descriptions is correctly identified.
4. Configure Google Drive Node (ID: 58):
   • Specify the Folder ID in Google Drive where your resume files are stored.
   • Adjust any file type filters if necessary (e.g., *.pdf).
5. Configure Extract from File Node (ID: 1235):
   • This node will automatically process the binary data from Google Drive. Ensure it's set to extract text from the appropriate file types (e.g., PDF).
6. Configure AI Agent Node (ID: 1119):
   • Model: Ensure the "Azure OpenAI Chat Model" (ID: 1253) is selected as the language model.
   • Prompt: Define the prompt that instructs the AI to score the resumes against the job descriptions. This prompt should clearly state the scoring criteria and expected output format.
   • Input: Map the extracted resume content and the job description from the previous nodes to the AI agent's input.
7. Execute the Workflow: Click "Execute Workflow" on the "When clicking ‘Execute workflow’" (Manual Trigger) node to run the process.

After execution, the output of the AI Agent node will contain the scores or evaluations for each resume. You can then add further nodes to store this data (e.g., another Google Sheets node to update the spreadsheet with scores).