AI-Powered Interview Preparation System using Ollama and LangChain for Campus Placements

## Overview

VAAGMI is an AI-powered, end-to-end interview preparation and mentoring automation system for campus placements. It enables placement cells to generate hyper-personalized 4-page interview preparation PDFs for shortlisted students, by combining job descriptions (JDs), candidate data, and LLMs via LangChain and Ollama.

⚠️ Note: This template requires self-hosted n8n to run community nodes like LangChain and Ollama.

## What This Workflow Does

• Accepts a CSV of shortlisted students and a JD via form upload
• Analyzes student profile vs JD using Ollama LLM via LangChain
• Generates personalized interview preparation PDFs
• Sends the PDF to each student via email
• Logs all data in Google Sheets and prevents duplicate processing

## Workflow Preview

📷 Please add a workflow screenshot here showing the main nodes and flow

## Step-by-Step Flow

## 1. Form Submission

• CSV of shortlisted students + JD + company name is submitted via HTTP Request form trigger.

## 2. Data Parsing and Google Sheet Logging

• CSV parsed → structured rows added to Google Sheet named with company + batch.

## 3. Candidate Filtering

• Only students with N8N_Agent = Not Generated are selected to avoid reprocessing.

## 4. AI-Powered Report Generation

LangChain agent (via Ollama + Gemini Search Tool) generates a 4-page Markdown report:

• Page 1: Profile Summary, Skill Gap Analysis, Company Insights
• Page 2: 15–20 Personalized Interview Questions
• Page 3: 5 Group Discussion Topics + Strategy
• Page 4: Custom Preparation Plan + Suggested Resources

## 5. PDF Creation

• Markdown → Stylish PDF via APITemplate.io

## 6. Email Delivery

• Each student receives a personalized email with the attached report.

## 7. Google Sheet Status Update

• Marks the student’s row as “Generated” in N8N_Agent column.

## Prerequisites

• Self-hosted n8n with Community Nodes enabled
• Local or Docker-hosted Ollama with LLaMA3.2 or equivalent model
• Activated LangChain and Gemini Search Tool nodes
• APITemplate.io API Key
• Connected Google Sheets account
• SMTP setup or Gmail node for email delivery

## Customization Tips

• Replace the LLM prompt in the LangChain node with your own tone/style
• Modify the PDF template on APITemplate.io to reflect your institution branding
• Update the email copy for formal or informal tones
• Add new filters (e.g., minimum CGPA, branch) for student selection