AI Workflows
Artificial Intelligence tools and workflows
Convert Images to 3D Models with Faller AI and Store in Google Drive
This workflow allows users to **convert a 2D image into a 3D model** by integrating multiple AI and web services. The process begins with a user uploading or providing an image URL, which is then sent to a generative AI model capable of interpreting the content and generating a 3D representation in `.glb` format. The model is then stored and a download link is returned to the user.  --- ### **Main Steps** 1. **Trigger Node**: Initiates the workflow either via HTTP request, webhook, or manual execution. 2. **Image Upload or Input**: The image is acquired via direct upload or URL input. 3. **API Integration**: The image is sent to a 3D generation API (e.g., a service like Kaedim, Luma Labs, or a custom AI model). 4. **Model Generation**: The external API processes the image and creates a 3D model. 5. **File Storage**: The resulting 3D model is stored in cloud storage (e.g., S3, Google Drive, or a local server). 6. **Response to User**: A download link for the 3D model is returned to the user via the same communication channel (HTTP response, email, or chat). --- ### **Advantages** * **Automation**: Eliminates the need for manual 3D modeling, saving time for artists, developers, and designers. * **AI-Powered**: Leverages AI to generate realistic and usable 3D models from simple 2D inputs. * **Scalability**: Can be triggered automatically and scaled up to handle many requests via n8n's automation. * **Integration-Friendly**: Easily extendable with other services like Discord, Telegram, or marketplaces for 3D assets. * **No-Code Configuration**: Built with n8n's visual interface, making it editable without programming knowledge. --- ### **How It Works** 1. **Trigger**: The workflow can be started manually (When clicking “Test workflow”) or automatically at scheduled intervals (Schedule Trigger). 2. **Data Retrieval**: The Get new image node fetches data from a Google Sheet, including the model image, product image, and product ID. 3. **3D Image Creation**: The Create 3D Image node sends the image data to the Fal.run API (Trellis) to generate a 3D model. 4. **Status Check**: The workflow periodically checks the request status (Get status and Wait 60 sec.) until the job is marked as COMPLETED. 5. **Result Processing**: Once completed, the 3D model URL is retrieved (Get Url 3D image), the file is downloaded (Get File 3D image), and uploaded to Google Drive (Upload 3D Image). 6. **Sheet Update**: The final 3D model URL is written back to the Google Sheet (Update result). --- ### **Set Up Steps** 1. **Prepare Google Sheet**: - Create a Google Sheet with columns: **IMAGE MODEL** and **3D RESULT** (empty). - Example sheet: [Google Sheet Template](https://docs.google.com/spreadsheets/d/1C0Et6X3Zwr_6CxeNjhLpDwjAfIGeUvLGFawckKb0utY/edit?usp=sharing). 2. **Obtain Fal.run API Key**: - Sign up at [Fal.ai](https://fal.ai/) and get an API key. - Configure the **Authorization** header in the Create 3D Image node with `Key YOURAPIKEY`. 3. **Configure Workflow Execution**: - Run manually via the **Test workflow** button. - For automation, set up the **Schedule Trigger** node (e.g., every 5 minutes). 4. **Verify Credentials**: Ensure Google Sheets, Google Drive, and Fal.run API credentials are correctly set in n8n. Once configured, the workflow processes new entries in the Google Sheet, generates 3D models, and updates the results automatically. --- ### **Need help customizing?** [Contact me](mailto:info@n3w.it) for consulting and support or add me on [Linkedin](https://www.linkedin.com/in/davideboizza/).
n8n$14.99Automate Job Search and Resume Optimization with AI and Airtable
Streamline your job application process by automating job searches, resume scoring, and customization using AI and Airtable.
n8n$14.99Tesla News and Sentiment Analysis Tool (Powered by DeepSeek Chat)
**This AI-powered agent performs real-time sentiment analysis on Tesla (TSLA) news to support trading decisions**. It aggregates headlines from 5 trusted sources and uses **DeepSeek Chat** to classify sentiment and generate structured summaries. This tool is a critical sub-agent in the broader **Tesla Quant Trading AI Agent** system. **Not standalone** - this agent is designed to be executed by the [Tesla Quant Trading AI Agent](https://n8n.io/workflows/4092-tesla-quant-trading-ai-agent-using-telegram-gpt-41-main-interface/). Requires: **DeepSeek Chat API Key** --- ## Workflow Role This tool processes Tesla-related news and produces output like: ```json { "sentiment": "bullish", "summary": "Tesla stock rallied today after strong delivery numbers and Cybertruck updates. Analysts remain optimistic.", "topHeadlines": [ "Tesla beats Q2 delivery forecast - Yahoo Finance", "Cybertruck ramps up in Texas - Electrek", "Berlin Gigafactory expands battery production - CleanTechnica" ] } ``` Its output feeds directly into the master trading agent's final trade report. --- ## News Sources Used This agent collects real-time headlines from: * Google News (filtered by "Tesla" or "TSLA") * Yahoo Finance (TSLA-specific feed) * Electrek (Tesla archive) * CleanTechnica (Tesla sustainability news) * TeslaNorth (app/product release updates) These five tools are always queried together to ensure market-wide signal coverage. --- ## What the Agent Does 1. Pulls headlines from all 5 Tesla-specific RSS feeds 2. Uses **DeepSeek Chat** to: * Analyze narrative tone (bullish / bearish / neutral) * Identify macro/financial drivers * Generate a 2-3 sentence summary * Return top 3-5 headlines 3. Outputs structured JSON for downstream use --- ## Setup Instructions ### 1. Install & Name * Import this file and name it: `Tesla_News_and_Sentiment_Analyst_Tool` ### 2. Add DeepSeek API Credentials * Go to: **Credentials → Add New → DeepSeek API** * Save as: `DeepSeek account` ### 3. Internet Access Required * Ensure RSS feeds can fetch live headlines * Works best with a cloud-hosted n8n instance or tunnel-enabled local install ### 4. Must Be Triggered by Parent * Triggered via `Execute Workflow` by the Tesla Quant Trading AI Agent * Requires these inputs: * `message`: optional query context * `sessionId`: passed to maintain short-term memory across executions --- ## Agent Architecture | Node Name | Function | | ----------------------------- | ------------------------------------------------- | | `DeepSeek Chat Model` | Performs AI-based sentiment analysis | | `Tesla News and Sentiment Analyst` | Combines results, formats output in strict JSON | | `Simple Memory` | Stores session-level context (short-term memory) | | 5x `RSS` nodes | Aggregate Tesla news from trusted media outlets | --- ## Sticky Notes Included **Trigger from Parent Workflow** - Executed only by main TSLA agent **News Feeds Overview** - Lists and explains each of the 5 feeds **DeepSeek Chat Notes** - Describes LLM behavior and parsing role **Short-term Memory** - Buffers sentiment context during user session **Sentiment Analyst Agent** - Summarizes key responsibilities --- ## Licensing & Attribution © 2025 **Treasurium Capital Limited Company** This architecture, workflow structure, and prompt design are licensed for educational and operational use only. Commercial resale or rebranding prohibited without authorization. **Creator:** [Don Jayamaha](https://linkedin.com/in/donjayamahajr) **Templates:** [https://n8n.io/creators/don-the-gem-dealer/](https://n8n.io/creators/don-the-gem-dealer/) --- **Power your TSLA trading with AI-driven sentiment-built with DeepSeek Chat and 5 trusted news sources.** **This tool is required by the Tesla Quant Trading AI Agent.**
n8n$9.99Ensure Reliable AI Output in JSON Schema Using OpenAI and Custom Validation
This workflow ensures AI-generated output adheres to a specific JSON schema without relying on the unreliable Structured Output Parser. It uses OpenAI's GPT-4.1 series and a custom validation loop to guarantee accurate nutritional data extraction.
n8n$14.99Automate Image Analysis and Feedback in Telegram Using OpenAI
This workflow automates the process of analyzing images received via Telegram and provides insightful feedback using OpenAI, enhancing communication and moderation in Telegram groups.
n8n$4.99Automate Daily AI-Generated Quotes and Images to Telegram
This n8n workflow delivers AI-generated quotes and cinematic images to your Telegram chat every morning, using GPT-4 and Flux-Pro for content creation.
n8n$9.99Automate AI Workflow Evaluation for Historical Event Analysis
This workflow evaluates AI-generated responses to historical event questions by comparing them with reference answers, ensuring accuracy and reliability.
n8n$9.99Automate Creative Asset Management with AI Analysis and Google Sheets
Streamline the management of creative assets by automating analysis, organization, and compliance checks using ScrapeGraphAI and Google Sheets.
n8n$9.99Automate Restaurant Food Waste Forecasting with AI and Google Sheets
This n8n workflow automates daily forecasting of restaurant sales and raw material needs using AI, helping to minimize food waste and optimize inventory. Forecasts are stored in Google Sheets and emailed to staff for review.
n8n$14.99Automate LinkedIn Profile Summaries with GPT-4 and Google Sheets
Effortlessly convert LinkedIn profile URLs into AI-generated summaries using GPT-4, streamlining insights for recruiters and sales teams.
n8n$9.99Integrate OpenAI with Notion for an Embeddable Knowledge Base Chatbot
Create an AI-powered chatbot using OpenAI and Notion to serve as a dynamic knowledge base, easily embeddable on your website for customer support.
n8n$9.99Create 5-Minute Wikipedia Podcasts from Telegram Messages
Transform Telegram messages into engaging 5-minute podcasts using Wikipedia research and AI voice synthesis. This workflow supports both text and voice inputs, providing a seamless experience for users.
n8n$9.99Automate YouTube Video Summarization and Interactive Q&A with GPT-4o-mini via Telegram
This n8n workflow automates the extraction and summarization of YouTube video transcripts, allowing users to interact with the content through AI-driven Q&A via Telegram.
n8n$14.99Automate Video Description Generation with Google Gemini AI
Leverage Google Gemini 2.0 Flash AI to automatically generate detailed descriptions of video content from any public URL, enhancing accessibility, content moderation, and media cataloging.
n8n$9.99Transform Press Releases (PDF & Word) into Polished Articles with Gmail & OpenAI
This n8n workflow automates the transformation of press releases into polished articles. It converts the content of an email and its attachments (PDF or Word documents) into an AI-written article/blog post. ## What does it do? This workflow assists editors and journalists in managing incoming press releases from governments, companies, NGOs, or individuals. The result is a draft article that can easily be reviewed by the editor, who receives it in a reply email containing both the original input and the output, plus an AI-generated self-assessment. This self-assessment represents an additional feedback loop where the AI compares the input with the output to evaluate the quality and accuracy of its transformation. ## How does it work? Triggered by incoming emails in Gmail, it first filters attachments, retaining only Word and PDF files while removing other formats like JPGs. The workflow then follows one of three paths: - If no attachments remain, it processes the inline email message directly. - For PDF attachments, it uses an extractor to obtain the document content. - For Word attachments, it extracts the text content by an HTTP request. In each case, the extracted content is then passed to an AI agent that converts the press release into a well-structured article according to predefined prompts. A separate AI evaluation step provides a self-assessment by comparing the output with the original input to ensure quality and accuracy. Finally, the workflow generates a reply email to the sender containing three components: the original input, the AI-generated article, and the self-assessment. This streamlined process helps editors and journalists efficiently manage incoming press releases, delivering draft articles that require minimal additional editing. ## How to set it up ### 1. Configure Gmail Connection: - Create or use an existing Gmail address - Connect it through the n8n credentials manager - Configure polling frequency according to your needs - Set the trigger event to Message Received Optional: Filter incoming emails by specifying authorized senders - Enable the Download Attachments option ### 2. Set Up AI Integration: - Create an OpenAI account if you don't have one - Create a new AI assistant or use an existing one - Customize the assistant with specific instructions, style guidelines, or response templates - Configure your API credentials in n8n to enable the connection ### 3. Configure Google Drive Integration: - Connect your Google Drive credentials in n8n - Set the operation mode to Upload - Configure the input data field name as data - Set the file naming format to dynamic: {{ $json.fileName }} ### 4. Configure HTTP Request Node: - Set request method to POST - Enter the appropriate Google API endpoint URL - Include all required authorization headers - Structure the request body according to API specifications - Ensure proper error handling for API responses ### 5. Configure HTTP Request Node 2: - Set request method to GET - Enter the appropriate Google API endpoint URL - Include all required authorization headers - Configure query parameters as needed - Implement response validation and error handling ### 6. Configure Self-Assessment Node: - Set operation to Message a Model - Select an appropriate AI model (e.g., GPT-4, Claude) - Configure the following prompt in the Message field: Please analyze and compare the following input and output content: (for example) Original Input: {{ $(HTTP Request3).item.json.data }} {{ $(Gmail Trigger).item.json.text }} Generated Output: {{ $json.output }} Provide a detailed self-assessment that evaluates: 1. Content accuracy and completeness 2. Structure and readability improvements 3. Tone and style appropriateness 4. Any information that may have been omitted or misrepresented 5. Overall quality of the transformation ### 7. Configure Reply Email Node: - Set operation to Send and select your Gmail account - Configure the to field to respond to the original sender: {{ $(Gmail Trigger).item.json.from }} - Set an appropriate subject line: RE: {{ $(Gmail Trigger).item.json.subject }} - Structure the email body with clear sections using the following template: ``` handlebars **EDITED ARTICLE** {{ $(AI Article Writer 2).item.json.output }} **SELF-ASSESSMENT** Rating: 1 (poor) to 5 (excellent) {{ $json.message.content }} **ORIGINAL MESSAGE** {{ $(Gmail Trigger).item.json.text }} **ATTACHMENT CONTENT** {{ $(HTTP Request3).item.json.data }} ``` Note: Adjust the template fields according to the input source (PDF, Word document, or inline message). For inline messages, you may not need the ATTACHMENT CONTENT section.
n8n$14.99Automate Gong.io Sales Call Analysis with AI and CRM Integration
Streamline the analysis of Gong.io sales calls using Azure AI to extract valuable insights and automatically sync them with Notion and Salesforce for enhanced sales, marketing, and product strategies.
n8n$14.99Email Assistant: Convert Natural Language to SQL Queries with Phi4-mini and PostgreSQL
# Who is this for? **Humans** and **Robots** alike. This workflow can be used as a **Chat trigger**, as well as a **Workflow trigger**. It will take a natural language request, and then generate a `SQL` query. The resulting `query` parameter will contain the query, and a `sqloutput` parameter will contain the results of executing such a query. ## What's the use case? This template is most useful paired with other workflows that extract e-mail information and store it in a structured Postgres table, and use LLMs to understand inquiries about information contained in an e-mail inbox and formulate questions that need answering. Plus, the prompt can be easily adapted to formulate SQL queries over any kind of structured database. ## Privacy and Economics As an LLM provider, I'm using **Ollama** locally, as I consider my e-mail extremely sensitive information. As a model, [`phi4-mini`](https://ollama.com/library/phi4-mini) does an excellent job balancing quality and efficiency. ## Setup Upon running for the first time, this workflow will **automatically** trigger a sub-section to read all tables and extract their schema into a local file. Then, either by **chatting** with the workflow in n8n's interface or by using it as a **sub-workflow**, you will get a `query` and a `sqloutput` response. ## Customizations If you want to work with just one particular table yet keep edits at bay, append a condition to the `List all tables in a database` step, like so: ```sql WHERE table_schema=public AND table_name=my_emails_table_name ``` To repurpose this workflow to work with any other data corpus in a structured database, inspect the `AI Agent` **user** and **system** prompts and edit them accordingly.
n8n$14.99Automate AI Workflow Evaluation for Support Ticket Categorization
This workflow evaluates AI performance in categorizing support tickets by comparing generated categories and priorities against expected results from a dataset.
n8n$9.99Fetch Keywords From Google Sheet and Classify Them Using AI
## Who is this template for This template is for marketers, SEO specialists, or content managers who need to analyze keywords to identify which ones contain references to a specific area or topic, in this case - IT software, services, tools, or apps. ## Use case Automating the process of scanning a large list of keywords to determine if they reference known IT products or services (like ServiceNow, Salesforce, etc.), and updating a Google Sheet with this classification. This helps in categorizing keywords for targeted SEO campaigns, content creation, or market analysis. ## How this workflow works 1. Fetches keyword data from a Google Sheet. 2. Processes keywords in batches to prevent rate limiting. 3. Uses an AI agent (OpenAI) to analyze each keyword and determine if it contains a reference to an IT service/software. 4. Updates the original Google Sheet with the results in a Service? column. 5. Continues processing until all keywords are analyzed. ## Set up steps 1. Connect your Google Sheets account credentials. 2. Set the Google Sheet document ID (currently using Copy of Sheet1 1). 3. Configure the OpenAI API credentials for the AI agent. 4. Adjust the batch size (currently 6) if needed based on your API rate limits. 5. Ensure the Google Sheet has the required columns: Number, Keyword, and Service?  The AI agent's prompt is highly customizable to match different identification needs. For example, instead of looking for IT software/services, you could modify the prompt to identify: - Industry-specific terms (healthcare, finance, education) - Geographic references (cities, countries, regions) - Product categories (electronics, clothing, food) - Competitor brand mentions Here's how you could modify the prompt for different use cases: ``` // For identifying educational content keywords Check the keyword I provided and define if this keyword relates to educational content, courses, or learning materials and return yes or no. // For identifying local service keywords Check the keyword I provided and determine if it contains location-specific terms (city names, neighborhoods, regions) that suggest local service intent and return yes or no. // For identifying competitor mentions Check the keyword I provided and determine if it mentions any of our competitors (CompetitorA, CompetitorB, CompetitorC) and return yes or no. ```
n8n$4.99Audio & Video Data Search and Analysis with Clarifai API and AI Agent Integration
Complete MCP server exposing 21 api.clarify.io API operations to AI agents. ## Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator? All 100% free? [Join the community](https://www.skool.com/n8n-nodes-automation-lab-1570/about) 1. **Import** this workflow into your n8n instance 2. **Credentials** Add api.clarify.io credentials 3. **Activate** the workflow to start your MCP server 4. **Copy** the webhook URL from the MCP trigger node 5. **Connect** AI agents using the MCP URL ## How it Works This workflow converts the api.clarify.io API into an MCP-compatible interface for AI agents. - **MCP Trigger**: Serves as your server endpoint for AI agent requests - **HTTP Request Nodes**: Handle API calls to https://api.clarify.io/ - **AI Expressions**: Automatically populate parameters via `$fromAI()` placeholders - **Native Integration**: Returns responses directly to the AI agent ## Available Operations (21 total) ### V1 (21 endpoints) - **GET /v1/bundles**: Add Media to rack - **POST /v1/bundles**: Create a bundle - **DELETE /v1/bundles/{bundle_id}**: Delete a bundle - **GET /v1/bundles/{bundle_id}**: Get a bundle - **PUT /v1/bundles/{bundle_id}**: Update a bundle - **GET /v1/bundles/{bundle_id}/insights**: Get bundle insights - **POST /v1/bundles/{bundle_id}/insights**: Request an insight to be run - **GET /v1/bundles/{bundle_id}/insights/{insight_id}**: Get bundle insight - **DELETE /v1/bundles/{bundle_id}/metadata**: Delete bundle metadata - **GET /v1/bundles/{bundle_id}/metadata**: Get bundle metadata - **PUT /v1/bundles/{bundle_id}/metadata**: Update bundle metadata - **DELETE /v1/bundles/{bundle_id}/tracks**: Delete bundle tracks - **GET /v1/bundles/{bundle_id}/tracks**: Get bundle tracks - **POST /v1/bundles/{bundle_id}/tracks**: Add a track for a bundle - **PUT /v1/bundles/{bundle_id}/tracks**: Update tracks for a bundle - **DELETE /v1/bundles/{bundle_id}/tracks/{track_id}**: Delete a bundle track - **GET /v1/bundles/{bundle_id}/tracks/{track_id}**: Get bundle track - **PUT /v1/bundles/{bundle_id}/tracks/{track_id}**: Add media to a track - **GET /v1/reports/scores**: Generate Group Report - **GET /v1/reports/trends**: Generate Trends Report - **GET /v1/search**: Search Bundles ## AI Integration **Parameter Handling**: AI agents automatically provide values for: - Path parameters and identifiers - Query parameters and filters - Request body data - Headers and authentication **Response Format**: Native api.clarify.io API responses with full data structure **Error Handling**: Built-in n8n HTTP request error management ## Usage Examples Connect this MCP server to any AI agent or workflow: - **Claude Desktop**: Add MCP server URL to configuration - **Cursor**: Add MCP server SSE URL to configuration - **Custom AI Apps**: Use MCP URL as tool endpoint - **API Integration**: Direct HTTP calls to MCP endpoints ## Benefits - **Zero Setup**: No parameter mapping or configuration needed - **AI-Ready**: Built-in `$fromAI()` expressions for all parameters - **Production Ready**: Native n8n HTTP request handling and logging - **Extensible**: Easily modify or add custom logic > **[Free for community use](https://github.com/Cfomodz/community-use)!** Ready to deploy in under 2 minutes.
n8n$14.99Automated Video Translation & Distribution with DubLab to Multiple Platforms
**Automated** n8n workflow: Receives videos via form, dubs/translates them to the selected languages, and—upon completion—uploads them to multiple social media channels and cloud drives, including Box, Dropbox, and YouTube, Telegram, Postiz (Facebook, Instagram, TikTok, Reddit, etc.) ### Workflows 1. Via n8n form, select files to dub for desired languages. 2. Listen to webhook and whenever dubbing finishes, upload to desired platforms. ### Used Stacks - DubLab App (ApiKey, Webhook Setup Required) #### Optional (Upload) - Telegram (Token Required) - Box (OAuth2 Required) - Dropbox (OAuth2 Required) - YouTube (OAuth2 Required) - Postiz (ApiKey Required)
n8n$14.99Automate AI-Driven Tagging for WordPress Blog Posts
Streamline your WordPress content management by automatically generating and applying AI-driven tags to blog posts. This workflow enhances SEO and ensures consistent content categorization.
n8n$19.99Automate LinkedIn Profile Enrichment with UniPile Data
Enhance LinkedIn message sender profiles by integrating UniPile's user and organization data, ensuring comprehensive and consistent information for lead routing.
n8n$9.99Create Reusable Web Scraping Workflows in n8n
Learn how to build reusable workflows in n8n to efficiently scrape web pages and integrate them into larger automation projects.
n8n$4.99
Related categories
Custom AI Systems & Services
Our team of experienced AI builders will help build custom AI systems, workflows, and solutions.
Request Custom Work