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integrationGoogle Gemini Chat Model node

Gmail and Google Gemini Chat Model integration

Save yourself the work of writing custom integrations for Gmail and Google Gemini Chat Model and use n8n instead. Build adaptable and scalable Communication, AI, and Langchain workflows that work with your technology stack. All within a building experience you will love.

How to connect Gmail and Google Gemini Chat Model

  • Step 1: Create a new workflow
  • Step 2: Add and configure nodes
  • Step 3: Connect
  • Step 4: Customize and extend your integration
  • Step 5: Test and activate your workflow

Step 1: Create a new workflow and add the first step

In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.

Gmail and Google Gemini Chat Model integration: Create a new workflow and add the first step

Step 2: Add and configure Gmail and Google Gemini Chat Model nodes

You can find Gmail and Google Gemini Chat Model in the nodes panel. Drag them onto your workflow canvas, selecting their actions. Click each node, choose a credential, and authenticate to grant n8n access. Configure Gmail and Google Gemini Chat Model nodes one by one: input data on the left, parameters in the middle, and output data on the right.

Gmail and Google Gemini Chat Model integration: Add and configure Gmail and Google Gemini Chat Model nodes

Step 3: Connect Gmail and Google Gemini Chat Model

A connection establishes a link between Gmail and Google Gemini Chat Model (or vice versa) to route data through the workflow. Data flows from the output of one node to the input of another. You can have single or multiple connections for each node.

Gmail and Google Gemini Chat Model integration: Connect Gmail and Google Gemini Chat Model

Step 4: Customize and extend your Gmail and Google Gemini Chat Model integration

Use n8n's core nodes such as If, Split Out, Merge, and others to transform and manipulate data. Write custom JavaScript or Python in the Code node and run it as a step in your workflow. Connect Gmail and Google Gemini Chat Model with any of n8n’s 1000+ integrations, and incorporate advanced AI logic into your workflows.

Gmail and Google Gemini Chat Model integration: Customize and extend your Gmail and Google Gemini Chat Model integration

Step 5: Test and activate your Gmail and Google Gemini Chat Model workflow

Save and run the workflow to see if everything works as expected. Based on your configuration, data should flow from Gmail to Google Gemini Chat Model or vice versa. Easily debug your workflow: you can check past executions to isolate and fix the mistake. Once you've tested everything, make sure to save your workflow and activate it.

Gmail and Google Gemini Chat Model integration: Test and activate your Gmail and Google Gemini Chat Model workflow

Proxmox AI Agent with n8n and Generative AI Integration

Proxmox AI Agent with n8n and Generative AI Integration

This template automates IT operations on a Proxmox Virtual Environment (VE) using an AI-powered conversational agent built with n8n. By integrating Proxmox APIs and generative AI models (e.g., Google Gemini), the workflow converts natural language commands into API calls, enabling seamless management of your Proxmox nodes, VMs, and clusters.

Watch Video on Youtube

How It Works
Trigger Mechanism
The workflow can be triggered through multiple channels like chat (Telegram, email, or n8n's built-in chat).
Interact with the AI agent conversationally.

AI-Powered Parsing
A connected AI model (Google Gemini or other compatible models like OpenAI or Claude) processes your natural language input to determine the required Proxmox API operation.

API Call Generation
The AI parses the input and generates structured JSON output, which includes:
response_type: The HTTP method (GET, POST, PUT, DELETE).
url: The Proxmox API endpoint to execute.
details: Any required payload parameters for the API call.

Proxmox API Execution
The structured output is used to make HTTP requests to the Proxmox VE API. The workflow supports various operations, such as:
Retrieving cluster or node information.
Creating, deleting, starting, or stopping VMs.
Migrating VMs between nodes.
Updating or resizing VM configurations.

Response Formatting
The workflow formats API responses into a user-friendly summary. For example:
Success messages for operations (e.g., "VM started successfully").
Error messages with missing parameter details.

Extensibility
You can enhance the workflow by connecting additional triggers, external services, or AI models. It supports:
Telegram/Slack integration for real-time notifications.
Backup and restore workflows.
Cloud monitoring extensions.

Key Features
Multi-Channel Input**: Use chat, email, or custom triggers to communicate with the AI agent.
Low-Code Automation**: Easily customize the workflow to suit your Proxmox environment.
Generative AI Integration**: Supports advanced AI models for precise command interpretation.
Proxmox API Compatibility**: Fully adheres to Proxmox API specifications for secure and reliable operations.
Error Handling**: Detects and informs you of missing or invalid parameters in your requests.

Example Use Cases
Create a Virtual Machine
Input: "Create a VM with 4 cores, 8GB RAM, and 50GB disk on psb1."
Action: Sends a POST request to Proxmox to create the VM with specified configurations.

Start a VM
Input: "Start VM 105 on node psb2."
Action: Executes a POST request to start the specified VM.

Retrieve Node Details
Input: "Show the memory usage of psb3."
Action: Sends a GET request and returns the node's resource utilization.

Migrate a VM
Input: "Migrate VM 202 from psb1 to psb3."
Action: Executes a POST request to move the VM with optional online migration.

Pre-Requisites
Proxmox API Configuration
Enable the Proxmox API and generate API keys in the Proxmox Data Center.
Use the Authorization header with the format:
PVEAPIToken=<user>@<realm>!<token-id>=<token-value>

n8n Setup
Add Proxmox API credentials in n8n using Header Auth.
Connect a generative AI model (e.g., Google Gemini) via the relevant credential type.

Access the Workflow
Import this template into your n8n instance.
Replace placeholder credentials with your Proxmox and AI service details.

Additional Notes
This template is designed for Proxmox 7.x and above.
For advanced features like backup, VM snapshots, and detailed node monitoring, you can extend this workflow.
Always test with a non-production Proxmox environment before deploying in live systems.

Nodes used in this workflow

Popular Gmail and Google Gemini Chat Model workflows

+4

🤖🧑‍💻 AI Agent for Top n8n Creators Leaderboard Reporting

This n8n workflow is designed to automate the aggregation, processing, and reporting of community statistics related to n8n creators and workflows. Its primary purpose is to generate insightful reports that highlight top contributors, popular workflows, and key trends within the n8n ecosystem. Here's how it works and why it's important: How It Works Data Retrieval: The workflow fetches JSON data files from a GitHub repository containing statistics about creators and workflows. It uses HTTP requests to access these files dynamically based on pre-defined global variables. Data Processing: The data is parsed into separate streams for creators and workflows. It processes the data to identify key metrics such as unique weekly and monthly inserters/visitors. Ranking and Filtering: The workflow sorts creators by their weekly inserts and workflows by their popularity. It selects the top 10 creators and top 50 workflows for detailed analysis. Report Generation: Using AI tools like GPT-4 or Google Gemini, the workflow generates a Markdown report summarizing trends, contributors, and workflow statistics. The report includes tables with detailed metrics (e.g., unique visitors, inserters) and insights into why certain workflows are popular. Distribution: The report is saved locally or uploaded to Google Drive. It can also be shared via email or Telegram for broader accessibility. Automation: A schedule trigger ensures the workflow runs daily or as needed, keeping the reports up-to-date. Why It's Important Community Insights**: This workflow provides actionable insights into the n8n community by identifying impactful contributors and popular workflows. This fosters collaboration and innovation within the ecosystem. Time Efficiency**: By automating data collection, processing, and reporting, it saves significant time and effort for community managers or administrators. Recognition of Contributors**: Highlighting top creators encourages engagement and recognizes individuals driving value in the community. Trend Analysis**: The workflow helps uncover patterns in usage, enabling better decision-making for platform improvements or feature prioritization. Scalability**: With its modular design, this workflow can be easily adapted to include additional metrics or integrate with other tools.
+8

Personal Portfolio CV Rag Chatbot - with Conversation Store and Email Summary

Personal Portfolio CV Rag Chatbot - with Conversation Store and Email Summary Target Audience This template is perfect for: Individuals looking to create a working professional and interactive personal portfolio chatbot. Developers interested in integrating RAG Chatbot functionality with conversation storage. Description Create a stunning Personal Portfolio CV with integrated RAG Chatbot capabilities, including conversation storage and daily email summaries. 2.Features: Training: Setup Ingestion stage Upload your CV to Google Drive and let the Drive trigger updates to read your resume cv and convert it into your vector database (RAG purpose). Modify any parts as needed. Chat & Track: Use any frontend/backend interface to call the chat API and chat history API. Reporting Daily Chat Conversations: Receive daily automatic summaries of chat conversations. Data stored via NocoDB. 3.Setup Guide: Step-by-Step Instructions: Ensure all credentials are ready. Follow the notes provided. Ingestion: Upload your CV to Google Drive. The Drive triggers RAG update in your vector database. You can change the folder name, files and indexname of the vector database accordingly. Chat: Use any frontend/backend interface to call the chat API (refer to the notes for details) . [optional] Use any frontend/backend interface to call the update chat history API (refer to the notes for details). 3.Tracking Chat: Get daily automatic summaries of chat conversations.Format email conversations report as you like. You are ready to go!

#️⃣Nostr #damus AI Powered Reporting + Gmail + Telegram

The n8n Nostr Community Node is a tool that integrates Nostr functionality into n8n workflows, allowing users to interact with the Nostr protocol seamlessly. It provides both read and write capabilities and can be used for various automation tasks. Disclaimer This node is ideal for self-hosted n8n setups, as ++community nodes are not supported on n8n cloud++. It opens up exciting possibilities for integrating workflows with the decentralized Nostr protocol. n8n Community Node for Nostr n8n-nodes-nostrobots Features Write Operations**: Send notes and events (kind1) to the Nostr network. Read Operations**: Fetch events based on criteria such as event ID, public key, hashtags, mentions, or search terms. Utility Functions**: Convert events into different formats like naddr or nevent and handle key transformations between bech32 and hex formats. Trigger Events**: Monitor the Nostr network for specific mentions or events and trigger workflows automatically. Use Cases Automating note posting without exposing private keys. Setting up notifications for mentions or specific events. Creating bots or AI assistants that respond to mentions on Nostr. Installation Install n8n on your system. Add the Nostr Community Node to your instance. Configure your credentials using a Nostr secret key (supports bech32 or hex formats).
+2

Proxmox AI Agent with n8n and Generative AI Integration

Proxmox AI Agent with n8n and Generative AI Integration This template automates IT operations on a Proxmox Virtual Environment (VE) using an AI-powered conversational agent built with n8n. By integrating Proxmox APIs and generative AI models (e.g., Google Gemini), the workflow converts natural language commands into API calls, enabling seamless management of your Proxmox nodes, VMs, and clusters. Watch Video on Youtube How It Works Trigger Mechanism The workflow can be triggered through multiple channels like chat (Telegram, email, or n8n's built-in chat). Interact with the AI agent conversationally. AI-Powered Parsing A connected AI model (Google Gemini or other compatible models like OpenAI or Claude) processes your natural language input to determine the required Proxmox API operation. API Call Generation The AI parses the input and generates structured JSON output, which includes: response_type: The HTTP method (GET, POST, PUT, DELETE). url: The Proxmox API endpoint to execute. details: Any required payload parameters for the API call. Proxmox API Execution The structured output is used to make HTTP requests to the Proxmox VE API. The workflow supports various operations, such as: Retrieving cluster or node information. Creating, deleting, starting, or stopping VMs. Migrating VMs between nodes. Updating or resizing VM configurations. Response Formatting The workflow formats API responses into a user-friendly summary. For example: Success messages for operations (e.g., "VM started successfully"). Error messages with missing parameter details. Extensibility You can enhance the workflow by connecting additional triggers, external services, or AI models. It supports: Telegram/Slack integration for real-time notifications. Backup and restore workflows. Cloud monitoring extensions. Key Features Multi-Channel Input**: Use chat, email, or custom triggers to communicate with the AI agent. Low-Code Automation**: Easily customize the workflow to suit your Proxmox environment. Generative AI Integration**: Supports advanced AI models for precise command interpretation. Proxmox API Compatibility**: Fully adheres to Proxmox API specifications for secure and reliable operations. Error Handling**: Detects and informs you of missing or invalid parameters in your requests. Example Use Cases Create a Virtual Machine Input: "Create a VM with 4 cores, 8GB RAM, and 50GB disk on psb1." Action: Sends a POST request to Proxmox to create the VM with specified configurations. Start a VM Input: "Start VM 105 on node psb2." Action: Executes a POST request to start the specified VM. Retrieve Node Details Input: "Show the memory usage of psb3." Action: Sends a GET request and returns the node's resource utilization. Migrate a VM Input: "Migrate VM 202 from psb1 to psb3." Action: Executes a POST request to move the VM with optional online migration. Pre-Requisites Proxmox API Configuration Enable the Proxmox API and generate API keys in the Proxmox Data Center. Use the Authorization header with the format: PVEAPIToken=<user>@<realm>!<token-id>=<token-value> n8n Setup Add Proxmox API credentials in n8n using Header Auth. Connect a generative AI model (e.g., Google Gemini) via the relevant credential type. Access the Workflow Import this template into your n8n instance. Replace placeholder credentials with your Proxmox and AI service details. Additional Notes This template is designed for Proxmox 7.x and above. For advanced features like backup, VM snapshots, and detailed node monitoring, you can extend this workflow. Always test with a non-production Proxmox environment before deploying in live systems.

AI Fitness Coach Strava Data Analysis and Personalized Training Insights

Detailed Title "Triathlon Coach AI Workflow: Strava Data Analysis and Personalized Training Insights using n8n" Description This n8n workflow enables you to build an AI-driven virtual triathlon coach that seamlessly integrates with Strava to analyze activity data and provide athletes with actionable training insights. The workflow processes data from activities like swimming, cycling, and running, delivers personalized feedback, and sends motivational and performance improvement advice via email or WhatsApp. Workflow Details Trigger: Strava Activity Updates Node:** Strava Trigger Purpose:** Captures updates from Strava whenever an activity is recorded or modified. The data includes metrics like distance, pace, elevation, heart rate, and more. Integration:** Uses Strava API for real-time synchronization. Step 1: Data Preprocessing Node:** Code Purpose:** Combines and flattens the raw Strava activity data into a structured format for easier processing in subsequent nodes. Logic:** A recursive function flattens JSON input to create a clean and readable structure. Step 2: AI Analysis with Google Gemini Node:** Google Gemini Chat Model Purpose:** Leverages Google Gemini's advanced language model to analyze the activity data. Functionality:** Identifies key performance metrics. Provides feedback and insights specific to the type of activity (e.g., running, swimming, or cycling). Offers tailored recommendations and motivational advice. Step 3: Generate Structured Output Node:** Structure Output Purpose:** Processes the AI-generated response to create a structured format, such as headings, paragraphs, and bullet lists. Output:** Formats the response for clear communication. Step 4: Convert to HTML Node:** Convert to HTML Purpose:** Converts the structured output into an HTML format suitable for email or other presentation methods. Output:** Ensures the response is visually appealing and easy to understand. Step 5: Send Email with Training Insights Node:** Send Email Purpose:** Sends a detailed email to the athlete with performance insights, training recommendations, and motivational messages. Integration:** Utilizes Gmail or SMTP for secure and efficient email delivery. Optional Step: WhatsApp Notifications Node:** WhatsApp Business Cloud Purpose:** Sends a summary of the activity analysis and key recommendations via WhatsApp for instant access. Integration:** Connects to WhatsApp Business Cloud for automated messaging. Additional Notes Customization: You can modify the AI prompt to adapt the recommendations to the athlete's specific goals or fitness levels. The workflow is flexible and can accommodate additional nodes for more advanced analysis or output formats. Scalability: Ideal for individual athletes or coaches managing multiple athletes. Can be expanded to include additional metrics or insights based on user preferences. Performance Metrics Handled: Swimming: SWOLF, stroke count, pace. Cycling: Cadence, power zones, elevation. Running: Pacing, stride length, heart rate zones. Implementation Steps Set Up Strava API Key: Log in to Strava Developers to generate your API key. Integrate the API key into the Strava Trigger node. Configure Google Gemini Integration: Use your Google Gemini (PaLM) API credentials in the Google Gemini Chat Model node. Customize Email and WhatsApp Messaging: Update the Send Email and WhatsApp Business Cloud nodes with the recipient’s details. Automate Execution: Deploy the workflow and use n8n's scheduling features or cron jobs for periodic execution. Developer Notes Author:** Amjid Ali improvements. Resources:** See in Action: Syncbricks Youtube PayPal: Support the Developer Courses : SyncBricks LMS By using this workflow, triathletes and coaches can elevate training to the next level with AI-powered insights and actionable recommendations.

Screen Applicants With AI, notify HR and save them in a Google Sheet

What this workflow does This workflow helps HR teams screen CVs with AI, store compatibility ratings in Google Sheets, and send email notifications to candidates and HR. It simplifies the recruitment process. CV Submission Form: Candidates submit their details and CV (PDF) through a web form, triggering the workflow in n8n. PDF Extraction & AI Rating: The submitted CV is processed to extract text, and AI analyzes it to generate a compatibility rating. Results Storage & Notifications: Ratings are stored in a Google Sheet for easy access and organization. Confirmation emails are automatically sent to both HR and the candidate. Setup Use the provided template to configure your form and connect it to n8n. Ensure your Google Sheets and email service integrations are active. Customization Instructions: Modify the email template to match your organization’s branding. Adjust the AI compatibility rating thresholds based on your requirements. Ensure you have updated the prompt for cv screening.

Build your own Gmail and Google Gemini Chat Model integration

Create custom Gmail and Google Gemini Chat Model workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.

Gmail supported actions

Add Label
Delete
Get
Get Many
Mark as Read
Mark as Unread
Remove Label
Reply
Send
Send and Wait for Approval
Create
Delete
Get
Get Many
Create
Delete
Get
Get Many
Add Label
Delete
Get
Get Many
Remove Label
Reply
Trash
Untrash

FAQs

  • Can Gmail connect with Google Gemini Chat Model?

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  • Can I use Google Gemini Chat Model’s API with n8n?

  • Is n8n secure for integrating Gmail and Google Gemini Chat Model?

  • How to get started with Gmail and Google Gemini Chat Model integration in n8n.io?

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