Automated AI product photography and Instagram post generator (Deepseek/Segmind)
Automatically generate professional-grade product photography and ready-to-use Instagram posts using the power of AI, delivered straight to your Telegram for approval.
Setup is incredibly simple: All you need is your product image URL and a API key from Segmind.
Who is this for?
This template is ideal for:
- E-commerce store owners looking to create high-quality product visuals affordably (The estimated cost is approximately $0.10 per product photography and accompanying Instagram post).
- Dropshippers needing unique product images to stand out.
- Social Media Managers & Marketers seeking to automate content creation for platforms like Instagram.
- Small Businesses wanting professional marketing assets without the high cost or effort.
- Anyone needing consistent, eye-catching product photos and social media captions on a regular schedule.
What problem is this workflow solving?
Creating professional product images is often expensive and time-consuming, requiring photographers, studios, and editing time. Consistently generating fresh and engaging social media content, especially for visual platforms like Instagram, adds another layer of complexity and effort. This workflow eliminates these bottlenecks by automating both high-quality image generation and relevant caption creation, freeing up your time and budget.
What this workflow does:
This n8n workflow automates the entire process on a schedule you define (e.g., every hour, every day):
- Scheduled Start: Triggers automatically based on your chosen time interval (e.g., every hour).
- Product Analysis: Takes your input product image URL and uses AI (GPT) to understand the product details.
- AI Prompt Generation: Based on the product analysis and your preference (whether to include a human model or not), it uses AI (Deepseek) to craft a sophisticated prompt specifically for generating professional product photography via Segmind.
- Instagram Post Creation: Simultaneously, the AI (Deepseek) generates an engaging Instagram post caption, complete with relevant hashtags, tailored to your product.
- AI Image Generation: Sends the product image, the generated prompt, and product details to the Segmind API to create a brand new, studio-quality product photograph.
- Telegram Validation: Downloads the newly generated product photo and sends both the photo and the generated Instagram post text directly to your specified Telegram chat. This allows you to quickly review and approve the content before using it.
Setup: Get Running in Minutes!
This workflow is designed for maximum ease of setup:
- Get Segmind API Key: Sign up or log in to Segmind and grab your API key here: https://cloud.segmind.com/console/api-keys
- Enter API Key: In the n8n workflow, click on the
SegmindAPIKeynode and paste your copied API key into theValuefield. - Enter Product Image URL: Click the
InputYourImageURLnode and paste the web address (URL) of your product image into theValuefield. - (Optional) Human Model Preference: Click the
ImageInstructionnode. Set theHumanModelvalue totrueif you want a human model potentially included in the photo, orfalseif you want the product showcased alone or in a setting. - Set Your Schedule: Click the
Schedule Triggernode. Define how often you want the workflow to run (e.g., under Interval, set1and selectHoursfrom the dropdown for hourly runs). - Configure Telegram: Make sure you have a Telegram Bot credential configured in n8n. Then, in the
SendProductPhotographyandSendInstagramPostnodes, enter the correctChat IDfor where you want to receive the validation messages. [A video guidance is made to help you with telegram setup] - Activate Workflow: Toggle the workflow to "Active" in the top right corner of n8n.
That's it! The workflow will now automatically generate and send product photos and Instagram posts to your Telegram at your defined interval.
How to customize this workflow:
While the default setup works great, you can easily tweak it:
- Photography Style: Modify the main prompt within the
AI Agent1node to guide the AI towards a specific aesthetic (e.g., "minimalist background," "bright natural lighting," "dark moody atmosphere"). - Instagram Post Tone: Adjust the instructions within the
AI Agent1node to change the style or focus of the generated Instagram captions. - Schedule: Change the trigger interval in the
Schedule Triggernode anytime. - AI Models: Experiment by changing the selected models in the
OpenAI,OpenAI Chat Model1(Deepseek).
Category:
Marketing, Social Media, E-commerce, Automation, AI, Content Creation, Product Photography
Automated AI Product Photography and Instagram Post Generator
This n8n workflow automates the creation of AI-generated product photography and Instagram posts. It streamlines the process from generating image prompts and descriptions to creating the images and then crafting an engaging Instagram post, including relevant hashtags. The workflow also incorporates a human-in-the-loop approval step via Telegram before publishing.
What it does
- Triggers on Schedule: The workflow starts on a predefined schedule (e.g., daily, weekly).
- Generates Product Idea: Uses an AI Agent (LangChain) and OpenAI Chat Model to generate a product idea, including its name, description, and key features.
- Creates Image Prompt and Description: Leverages the AI Agent and OpenAI Chat Model again to generate a detailed image prompt suitable for an AI image generator, along with a creative description for the product.
- Generates Product Image: Utilizes OpenAI's DALL-E to create a product image based on the generated image prompt.
- Prepares Instagram Post Content: Uses the AI Agent and OpenAI Chat Model to craft an Instagram post caption, including relevant hashtags, based on the product description and image.
- Human Approval via Telegram: Sends the generated image and Instagram post content to a Telegram chat for human review and approval.
- Waits for Approval: Pauses the workflow until an approval or rejection message is received via Telegram.
- Conditionally Continues:
- If Approved: Proceeds to the next step (which would typically be posting to Instagram, though the actual Instagram posting node is not present in this JSON).
- If Rejected: The workflow stops or could be configured to notify of rejection.
- Updates Fields (Placeholder): An "Edit Fields (Set)" node is present, likely intended for further data manipulation or preparation before the final posting step.
Prerequisites/Requirements
- n8n Instance: A running n8n instance.
- OpenAI API Key: For the OpenAI Chat Model and OpenAI (DALL-E) nodes. This needs to be configured as an n8n credential.
- Telegram Bot Token: For the Telegram node to send and receive messages. This needs to be configured as an n8n credential.
- Telegram Chat ID: The ID of the Telegram chat where approval messages will be sent and received.
Setup/Usage
- Import the workflow: Download the provided JSON and import it into your n8n instance.
- Configure Credentials:
- Set up your OpenAI API Key credential in n8n.
- Set up your Telegram Bot Token credential in n8n.
- Update Telegram Chat ID: In the "Telegram" node (ID: 49), replace the placeholder chat ID with your actual Telegram chat ID.
- Customize AI Prompts: Review the prompts within the "AI Agent" and "OpenAI Chat Model" nodes to tailor the generated content (product ideas, image prompts, Instagram captions) to your specific needs and brand voice.
- Adjust Schedule: Configure the "Schedule Trigger" node (ID: 839) to your desired frequency for generating new posts.
- Add Instagram Posting Node (Optional): Currently, the workflow includes an "If" condition for approval but does not have a node to actually post to Instagram. You will need to add an Instagram node (or other social media node) after the "If" node's "True" branch to complete the automation.
- Activate the workflow: Once configured, activate the workflow in n8n.
Related Templates
Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets
This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitor’s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger — Manually start the workflow or schedule it to run periodically. Input Setup — Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) — Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring — Clean and convert GPT output into JSON format. Data Storage (Google Sheets) — Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the “Set Input Fields” node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors → Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection → Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report → Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization → Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs → Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting It’s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.
Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax
Spark your creativity instantly in any chat—turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. 📋 What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing 🔧 Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation 🔑 Required Credentials OpenAI API Setup Go to platform.openai.com → API keys (sidebar) Click "Create new secret key" → Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai → Dashboard → API Keys Generate a new API key → Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) ⚙️ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflow—chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" 🎯 Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration ⚠️ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions
Automate invoice processing with OCR, GPT-4 & Salesforce opportunity creation
PDF Invoice Extractor (AI) End-to-end pipeline: Watch Drive ➜ Download PDF ➜ OCR text ➜ AI normalize to JSON ➜ Upsert Buyer (Account) ➜ Create Opportunity ➜ Map Products ➜ Create OLI via Composite API ➜ Archive to OneDrive. --- Node by node (what it does & key setup) 1) Google Drive Trigger Purpose: Fire when a new file appears in a specific Google Drive folder. Key settings: Event: fileCreated Folder ID: google drive folder id Polling: everyMinute Creds: googleDriveOAuth2Api Output: Metadata { id, name, ... } for the new file. --- 2) Download File From Google Purpose: Get the file binary for processing and archiving. Key settings: Operation: download File ID: ={{ $json.id }} Creds: googleDriveOAuth2Api Output: Binary (default key: data) and original metadata. --- 3) Extract from File Purpose: Extract text from PDF (OCR as needed) for AI parsing. Key settings: Operation: pdf OCR: enable for scanned PDFs (in options) Output: JSON with OCR text at {{ $json.text }}. --- 4) Message a model (AI JSON Extractor) Purpose: Convert OCR text into strict normalized JSON array (invoice schema). Key settings: Node: @n8n/n8n-nodes-langchain.openAi Model: gpt-4.1 (or gpt-4.1-mini) Message role: system (the strict prompt; references {{ $json.text }}) jsonOutput: true Creds: openAiApi Output (per item): $.message.content → the parsed JSON (ensure it’s an array). --- 5) Create or update an account (Salesforce) Purpose: Upsert Buyer as Account using an external ID. Key settings: Resource: account Operation: upsert External Id Field: taxid_c External Id Value: ={{ $json.message.content.buyer.tax_id }} Name: ={{ $json.message.content.buyer.name }} Creds: salesforceOAuth2Api Output: Account record (captures Id) for downstream Opportunity. --- 6) Create an opportunity (Salesforce) Purpose: Create Opportunity linked to the Buyer (Account). Key settings: Resource: opportunity Name: ={{ $('Message a model').item.json.message.content.invoice.code }} Close Date: ={{ $('Message a model').item.json.message.content.invoice.issue_date }} Stage: Closed Won Amount: ={{ $('Message a model').item.json.message.content.summary.grand_total }} AccountId: ={{ $json.id }} (from Upsert Account output) Creds: salesforceOAuth2Api Output: Opportunity Id for OLI creation. --- 7) Build SOQL (Code / JS) Purpose: Collect unique product codes from AI JSON and build a SOQL query for PricebookEntry by Pricebook2Id. Key settings: pricebook2Id (hardcoded in script): e.g., 01sxxxxxxxxxxxxxxx Source lines: $('Message a model').first().json.message.content.products Output: { soql, codes } --- 8) Query PricebookEntries (Salesforce) Purpose: Fetch PricebookEntry.Id for each Product2.ProductCode. Key settings: Resource: search Query: ={{ $json.soql }} Creds: salesforceOAuth2Api Output: Items with Id, Product2.ProductCode (used for mapping). --- 9) Code in JavaScript (Build OLI payloads) Purpose: Join lines with PBE results and Opportunity Id ➜ build OpportunityLineItem payloads. Inputs: OpportunityId: ={{ $('Create an opportunity').first().json.id }} Lines: ={{ $('Message a model').first().json.message.content.products }} PBE rows: from previous node items Output: { body: { allOrNone:false, records:[{ OpportunityLineItem... }] } } Notes: Converts discount_total ➜ per-unit if needed (currently commented for standard pricing). Throws on missing PBE mapping or empty lines. --- 10) Create Opportunity Line Items (HTTP Request) Purpose: Bulk create OLIs via Salesforce Composite API. Key settings: Method: POST URL: https://<your-instance>.my.salesforce.com/services/data/v65.0/composite/sobjects Auth: salesforceOAuth2Api (predefined credential) Body (JSON): ={{ $json.body }} Output: Composite API results (per-record statuses). --- 11) Update File to One Drive Purpose: Archive the original PDF in OneDrive. Key settings: Operation: upload File Name: ={{ $json.name }} Parent Folder ID: onedrive folder id Binary Data: true (from the Download node) Creds: microsoftOneDriveOAuth2Api Output: Uploaded file metadata. --- Data flow (wiring) Google Drive Trigger → Download File From Google Download File From Google → Extract from File → Update File to One Drive Extract from File → Message a model Message a model → Create or update an account Create or update an account → Create an opportunity Create an opportunity → Build SOQL Build SOQL → Query PricebookEntries Query PricebookEntries → Code in JavaScript Code in JavaScript → Create Opportunity Line Items --- Quick setup checklist 🔐 Credentials: Connect Google Drive, OneDrive, Salesforce, OpenAI. 📂 IDs: Drive Folder ID (watch) OneDrive Parent Folder ID (archive) Salesforce Pricebook2Id (in the JS SOQL builder) 🧠 AI Prompt: Use the strict system prompt; jsonOutput = true. 🧾 Field mappings: Buyer tax id/name → Account upsert fields Invoice code/date/amount → Opportunity fields Product name must equal your Product2.ProductCode in SF. ✅ Test: Drop a sample PDF → verify: AI returns array JSON only Account/Opportunity created OLI records created PDF archived to OneDrive --- Notes & best practices If PDFs are scans, enable OCR in Extract from File. If AI returns non-JSON, keep “Return only a JSON array” as the last line of the prompt and keep jsonOutput enabled. Consider adding validation on parsing.warnings to gate Salesforce writes. For discounts/taxes in OLI: Standard OLI fields don’t support per-line discount amounts directly; model them in UnitPrice or custom fields. Replace the Composite API URL with your org’s domain or use the Salesforce node’s Bulk Upsert for simplicity.