AI-powered interview preparation system using local LLM for campus placements

Overview 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 N8NAgent = 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 N8NAgent 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