This workflow automates the process of extracting a resume from a Telegram message, parsing and structuring the data into HTML, and generating a downloadable PDF. It begins by listening for Telegram messages, specifically watching for resume files uploaded by users. When a resume PDF is received, the workflow downloads the file and extracts its text content.

Utilizing OpenAI’s GPT-4-turbo-preview model, it analyzes and extracts detailed resume data such as personal information, employment history, education, projects, and volunteering activities. The extracted data is then formatted into HTML segments for clarity and structured presentation.

Multiple nodes convert raw data into HTML blocks for each section — personal info, skills, employment history, educational background, projects, and volunteering efforts. These blocks are merged into a single comprehensive HTML document, which is then encoded to Base64 for further processing.

The HTML content is sent to Gotenberg, a self-hosted PDF rendering service, to produce a professional PDF version of the resume. The final step uploads this PDF back to Telegram, allowing users to receive their generated resume document directly within the chat.

This workflow is particularly useful for automating resume parsing, creating professional PDF resumes from various input formats, and providing instant, automated resume generation in communication platforms like Telegram.

Node Count	>20 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.chainLlm, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.outputParserAutofixing, @n8n/n8n-nodes-langchain.outputParserStructured, code, convertToFile, extractFromFile, httpRequest, if, merge, noOp, set, stickyNote, telegram, telegramTrigger