Telegram CV Extraction to Structured PDF

Recruiters, HR professionals, or job seekers who receive resumes via Telegram and need quick structured parsing. Users send a PDF resume via Telegram bot. The workflow extracts text, uses AI to parse into structured data (personal info, employment, education, etc.), formats into HTML sections, merges them, generates a clean PDF, and sends it back. This automates resume data extraction and reformatting for easier review. 1. Create a Telegram bot and get API credentials. 2. Set up OpenAI API key in n8n. 3. Install and run Gotenberg service (self-hosted or via Docker). 4. Configure node credentials and activate the workflow. n8n instance, Telegram Bot API credentials, OpenAI API access, Gotenberg for PDF conversion (port 3000). PDF resumes only. Edit JSON schema in Structured Output Parser for new fields. Adjust HTML in Code nodes for styling. Add more AI prompts or sections as needed. Key Technologies: n8n Workflow Automation,Telegram Integration,OpenAI GPT-4 Turbo (via Langchain),Gotenberg PDF Generator,JavaScript Code Nodes for Formatting Automation Value: Saves hours of manual data entry from resumes Improves accuracy with AI parsing over manual reading Enables instant feedback via Telegram chat Scales for high-volume recruiting without extra staff Outputs professional PDFs for sharing or archiving Best Practices: Use structured JSON schemas in AI parsers to enforce output consistency. Implement low temperature (0) for deterministic AI responses in data extraction. Use merge nodes for parallel processing of sections to optimize flow efficiency. Host Gotenberg locally for privacy and control over PDF generation. Add error handling (e.g., IF nodes) for invalid PDFs or AI failures to improve robustness. Customize HTML via code nodes for branding or layout tweaks without external tools.