AI-powered CV filtering with Llama3.1 LLM, Google Drive & Sheets

Name: AI-powered CV filtering with Llama3.1 LLM, Google Drive & Sheets
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Rating: 4.5 (56 reviews)
Author: Lakindu Siriwardana

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This visual workflow represents an AI-powered automated CV filtering system created using tools like n8n, Google Drive, Google Sheets, and Ollama (LLM)

⚙️ Key Features

📂 Google Drive Integration – Automatically searches and downloads CVs (PDF/DOCX/PPTX) from a shared folder.
📋 Criteria Matching – Reads and applies filtering rules from a Google Sheet.
🧠 LLM-Based Analysis – Uses a Large Language Model (Ollama) to assess and interpret CV content.
🧪 Smart Parsing – Includes structured and auto-fixing output parsers to ensure data accuracy.
📊 Automated Results Output – Writes matching candidates and analysis to a Google Sheet.
🔁 Loop and Aggregate Logic – Handles multiple CVs with iterative processing and aggregation.
🚀 No-Code Automation with n8n – Fully visual, modifiable without programming.

🛠️ How It Works

Trigger: Workflow is initiated via a Webhook (from a UI “Start Workflow” button).

CV Search: Searches for CV files in a designated Google Drive folder. Loop Over Files: Each file is downloaded. Text is extracted (from PDFs or other formats). Criteria Input: Matching rules are fetched from a predefined Google Sheet. Merge & Aggregate: Combines file text and criteria for unified processing.

LLM Processing: Text + criteria are sent to the Basic LLM Chain.

Utilizes Ollama Model for advanced language understanding.

Structured or auto-fixing output parsers enhance reliability.

Custom Code Execution: Optionally enriches or reformats the data.

Output: Results are appended to a shared Google Sheet (the output sheet).

Lakindu Siriwardana

0 workflows

Nodes

set gmail telegram agent google-gemini

Complexity

advanced

Published 30 Jul 2025

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AI-powered CV filtering with Llama3.1 LLM, Google Drive & Sheets

⚙️ Key Features

📂 Google Drive Integration – Automatically searches and downloads CVs (PDF/DOCX/PPTX) from a shared folder.

📋 Criteria Matching – Reads and applies filtering rules from a Google Sheet.

🧠 LLM-Based Analysis – Uses a Large Language Model (Ollama) to assess and interpret CV content.

🧪 Smart Parsing – Includes structured and auto-fixing output parsers to ensure data accuracy.

📊 Automated Results Output – Writes matching candidates and analysis to a Google Sheet.

🔁 Loop and Aggregate Logic – Handles multiple CVs with iterative processing and aggregation.

🚀 No-Code Automation with n8n – Fully visual, modifiable without programming.

🛠️ How It Works