zahir khan
Building intelligent automation workflows that connect systems, data, and AI
Templates by zahir khan
Generate 3D models from images using Hunyuan3D v2 and Google Sheets
This workflow automates the conversion of 2D images into high-quality 3D models (.glb format) by integrating Google Sheets with the Hunyuan3D v2 model on Fal.ai. It handles the entire pipeline—from fetching image URLs to polling for completion and saving the final asset—eliminating manual modeling time for artists and developers. How it works This template operates on a schedule to process images in batches or individually: Data Retrieval: The workflow fetches new rows from a Google Sheet where the RESULT_GLB column is empty. AI Generation: It sends the IMAGE_URL to the Hunyuan3D v2 API on Fal.ai to initiate the 3D generation process. Status Polling: The workflow automatically enters a loop, checking the job status every 30 seconds until the model is marked "COMPLETED." Result Update: Once finished, it retrieves the download link for the .glb file and writes it back to the specific row in your Google Sheet. Use Cases Game Development: Rapidly create prototype props and assets from concept art. E-commerce: Convert product photos into 3D models for web viewers. AR/VR: Generate background assets for immersive environments from simple 2D inputs. Setup steps Google Sheet: Create a new sheet with two header columns: IMAGEURL and RESULTGLB. Add the images you want to convert in the first column. Fal.ai Credentials: Sign up at Fal.ai and generate an API Key. In n8n, create a Header Auth credential with the name Authorization and value Key YOURAPIKEY. Configure Nodes: Update the Get new image and Update Result nodes to select your specific Google Sheet. Ensure the HTTP Request nodes are using your Fal.ai Header Auth credential.
By zahir khanGenerate and schedule themed social posts with Notion, OpenAI, Fal.ai and Postiz
This workflow automates your daily social media content creation by generating unique, on-brand posts based on specific themes stored in Notion. It creates images using Fal.ai, writes captions with OpenAI, and schedules them to multiple platforms via Postiz. 📺 How It Works Daily Trigger: The workflow runs automatically every day at a set time. Context Fetching: It pulls your "Brand Guidelines" and the specific "Post Theme" for the day (e.g., Expert Advice, System, or Activity) from Notion. Image Generation: It uses OpenAI to craft a detailed image prompt based on the theme, then sends it to Fal.ai to generate a high-quality visual. Caption Writing: It uses OpenAI again to write an engaging caption that adheres to your brand voice. Scheduling: Finally, it uploads the media to Postiz and schedules it for publication on LinkedIn, X (Twitter), Facebook, and Instagram. 🔧 How to set up Notion: Create a "Brand Guidelines" database and a "Post Themes" database. Configure Nodes: Update the Notion nodes in the workflow to point to your specific Database IDs. Credentials: Connect your accounts for OpenAI, Fal.ai, Google Drive, Notion, and Postiz. Postiz IDs: In the final HTTP Request nodes, replace the integration_id fields with the specific IDs from your Postiz account for each social platform. 📋 Requirements n8n (Self-hosted or Cloud) Notion account OpenAI API Key Fal.ai API Key Postiz instance (or account) Google Drive account (for temporary image storage)
By zahir khanScore job applications and write AI feedback with OpenAI and Notion
Screen resumes & save candidate scores to Notion with OpenAI This template helps you automate the initial screening of job candidates by analyzing resumes against your specific job descriptions using AI. 📺 How It Works The workflow automatically monitors a Notion database for new job applications. When a new candidate is added: It checks if the candidate has already been processed to avoid duplicates. It downloads the resume file (supporting both PDF and DOCX formats). It extracts the raw text and sends it to OpenAI along with the specific job description and requirements. The AI acts as a "Senior Technical Recruiter," scoring the candidate on skills, experience, and stability. Finally, it updates the Notion entry with a fit score (0-100), a one-line summary, detected skills, and a detailed analysis. 📄 Notion Database Structure You will need two databases in Notion: Jobs (containing descriptions/requirements) and Candidates (containing resume files). Candidates DB Fields: AI Comments (Text), Resume Score (Text), Top Skills Detected (Text), Feedback (Select), One Line Summary (Text), Resume File (Files & Media). Jobs DB Fields: Job Description (Text), Requirements (Text). 👤 Who’s it for This workflow is for recruiters, HR managers, founders, and hiring teams who want to reduce the time spent on manual resume screening. Whether you are handling high-volume applications or looking for specific niche skills, this tool ensures every resume gets a consistent, unbiased first-pass review. 🔧 How to set up Create the required databases in Notion (as described above). Import the .json workflow into your n8n instance. Set up credentials for Notion and OpenAI. Link those credentials in the workflow nodes. Update Database IDs: Open the "Fetch Job Description" and "On New Candidate" nodes and select your specific Notion databases. Run a test with a sample candidate and validate the output in Notion. 📋 Requirements An n8n instance (Cloud or Self-hosted) A Notion account OpenAI API Key (GPT-4o or GPT-4 Turbo recommended for best reasoning) 🧩 How to customize the workflow The system is fully modular. You can: Adjust the Persona: In the Analyze Candidate agent nodes, edit the system prompt to change the "Recruiter" persona (e.g., make it stricter or focus on soft skills). Change Scoring: Modify the scoring matrix in the prompt to weight "Education" or "Experience" differently. Filter Logic: Add a node to automatically disqualify candidates below a certain score (e.g., < 50) and move them to a "Rejected" status in Notion. Multi-language: Update the prompt to translate summaries into your local language if the resume is in English.
By zahir khan