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Build a WhatsApp assistant with memory, Google Suite & multi-AI research and imaging

Iniyavan JCIniyavan JC
3593 views
2/3/2026
LoggingJiraEvent ProcessingWebhookSystem
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image.pngThe "WhatsApp Productivity Assistant with Memory and AI Imaging" is a comprehensive n8n workflow that transforms your WhatsApp into a powerful, multi-talented AI assistant. It's designed to handle a wide range of tasks by understanding user messages, analyzing images, and connecting to various external tools and services. The assistant can hold natural conversations, remember past interactions using a MongoDB vector store (RAG), and decide which tool is best suited for a user's request. Whether you need to check your schedule, research a topic, get the latest news, create an image, or even analyze a picture you send, this workflow orchestrates it all seamlessly through a single WhatsApp chat interface.

The workflow is structured into several interconnected components:

  • WhatsApp Trigger & Incoming Message Processing: This is the entry point, starting when a message (text or image) is received via WhatsApp. A Route Message by Type (Image/Text) node then intelligently routes the message based on its content type. A Typing.... node sends a typing indicator to the user for a better experience. If an image is received, it's downloaded, processed via an HTTP Request, and analyzed by the Analyze image node. The Code1 node then standardizes both text and image analysis output into a single, unified input for the main AI agent.
  • Core AI Agent: This is the brain of the operation. The AI Agent1 node receives the user's input, maintains short-term conversational memory using Simple Memory, and uses a powerful language model (gpt-oss-120b2 or gpt-oss-120b1) to decide which tool or sub-agent to use. It orchestrates all the other agents and tools.
  • Productivity Tools Agent: This group of nodes connects the assistant to your personal productivity suite. It includes sub-agents and tools for managing Google Calendar, Google Tasks, and Gmail, allowing you to schedule events, manage to-dos, and read emails. It leverages a language model (gpt-4.1-mini or gemini-2.5-flash) for understanding and executing commands within these tools.
  • Research Tool Agent: This agent handles all research-related queries. It has access to multiple search tools (Brave Web Search, Brave News Search, Wikipedia, Tavily, and a custom perprlexcia search) to find the most accurate and up-to-date information from the web. It uses a language model (gpt-oss-120b or gpt-4.1-nanoChat Model1) for reasoning.
  • Long-Term Memory Webhook:image.png A dedicated sub-workflow (Webhook2) that processes conversation history, extracts key information using Extract Memory Info, and stores it in a MongoDB Atlas Vector Store for long-term memory. This allows the AI agent to remember past preferences and facts.
  • Image Generation Webhook: image.png A specialized sub-workflow (Webhook3) triggered when a user asks to create an image. It uses a dedicated AI Agent with MongoDB Atlas Vector Store1 for contextual image prompt generation, Clean Prompt Text1 to refine the prompt, an HTTP Request to an external image generation API (e.g., Together.xyz), and then converts and sends the generated image back to the user via WhatsApp.

Use Cases

  • Personal Assistant: Schedule appointments, create tasks, read recent emails, and manage your daily agenda directly from WhatsApp.
  • Information Retrieval: Ask any factual, news, or research-based question and get real-time answers from various web sources.
  • Creative Content Generation: Request the AI to generate images based on your descriptions for logos, artwork, or social media content.
  • Smart Communication: Engage in natural, contextual conversations with an AI that remembers past interactions.
  • Image Analysis: Send an image and ask the AI to describe its contents or answer questions about it.

Pre-conditions

Before importing and running this template, you will need:

  • Self-hosted n8n Instance: This template requires a self-hosted n8n instance as it uses webhooks that need public accessibility.
  • WhatsApp Business Account: A Meta Developer Account configured for WhatsApp Business Platform API access.
  • MongoDB Atlas Account: A MongoDB Atlas cluster with a database and collection set up for the vector store.
  • Google Cloud Project: Configured with API access for Google Calendar, Google Tasks, and Gmail.
  • API Keys/Accounts for:
    • OpenWeatherMap: For weather forecasts.
    • Groq, OpenRouter, or Vercel AI Gateway: For various Language Models (e.g., gpt-oss-120b, gpt-5-nano, gpt-4o-mini).
    • Mistral Cloud: For embedding models (e.g., codestral-embed-2505).
    • Brave Search: For web and news searches.
    • Tavily API: For structured search results.
    • Together.xyz or similar Image Generation API: For creating images.
    • Perplexity API (or self-hosted instance): For the perprlexcia tool (the current URL http://self hoseted perplexcia/api/search implies a self-hosted or custom endpoint).
  • Publicly Accessible URLs: Your n8n instance and any custom webhook endpoints (like perprlexcia) must be publicly accessible.

Requirements (n8n Credentials)

You will need to set up the following credentials within your n8n instance:

  • WhatsApp OAuth account: For the WhatsApp Trigger node.
  • WhatsApp account: For Send message2, Send message3, Download media, and Typing.... nodes.
  • Google Palm Api account: For Analyze image, Google Gemini Chat Model, gemini-2.5-flash, and Google Gemini Chat Model5 nodes.
  • OpenWeatherMap account: For the Get Weather Forecast node.
  • Groq account: For gpt-oss-120b node.
  • Google Calendar OAuth2Api account: For the Google Calendar tools.
  • MongoDB account: For MongoDB Atlas Vector Store nodes.
  • OpenRouter account: For gpt-5-nano and gpt-4.1-nanoChat Model1 nodes.
  • Gmail account : For Get many messages and Get a message nodes (ensure correct Gmail OAuth2 setup for each).
  • Google Tasks account: For the Google Tasks tools.
  • Bearer Auth account: For HTTP Request5 (used in media download).
  • Brave Search account: For Brave Web Search and Brave News Search nodes.
  • Vercel Ai Gateway Api account: For gpt-4.1-mini, gpt-oss-120b, gpt-oss-120b2, and gpt-4.1-nano nodes.
  • HTTP Header Auth account: For Tavily web search (create a new one named "Tavily API Key" with Authorization: Bearer YOUR_TAVILY_API_KEY) and HTTP Request (for Together.xyz, e.g., "Together.xyz API Key").
  • Mistral Cloud account: For codestral-embed-2505, codestral-embed-, and codestral-embed-2506 nodes.

n8n WhatsApp Assistant with Multi-AI Research and Imaging

This n8n workflow creates a versatile WhatsApp assistant capable of engaging in conversational AI, performing multi-AI research, and generating images. It leverages various AI models and tools to provide a rich and interactive experience directly through WhatsApp.

What it does

This workflow orchestrates a sophisticated AI assistant accessible via WhatsApp:

  1. Receives WhatsApp Messages: It listens for incoming messages on a configured WhatsApp Business Cloud account.
  2. Initial Message Processing: The incoming message is processed to extract relevant information.
  3. Conditional AI Routing: It intelligently routes the message to different AI models or tools based on the message content.
    • AI Agent: If the message requires complex reasoning or tool usage, it's directed to an AI Agent.
    • Basic LLM Chain: For simpler conversational responses, it uses a Basic LLM Chain.
  4. AI Agent Capabilities:
    • Memory: The AI Agent utilizes a Simple Memory to maintain conversation context.
    • Research (Wikipedia): It can perform research using the Wikipedia tool to answer factual questions.
    • Thinking Tool: A "Think" tool is available for the agent to process complex requests internally before responding.
    • AI Agent Tool: The agent can potentially call other AI agents as tools for specialized tasks.
    • Image Generation: Although not explicitly named, the presence of Convert to File and Default Data Loader suggests potential for image processing or generation, likely through an external API called by the HTTP Request node.
  5. Language Model Selection: The workflow supports multiple Large Language Models (LLMs) for flexibility:
    • Google Gemini Chat Model
    • Groq Chat Model
    • OpenRouter Chat Model
    • Vercel AI Gateway Chat Model
    • Google Gemini (as a general AI node)
  6. Embeddings for Context: It uses Mistral Cloud Embeddings, indicating the ability to convert text into numerical representations for similarity search or context retrieval, likely with a vector store.
  7. Vector Store Integration: A MongoDB Atlas Vector Store is integrated, suggesting the workflow can store and retrieve conversational history or knowledge base documents for enhanced memory and context.
  8. Sends WhatsApp Replies: After processing, the workflow sends the AI-generated response back to the user via WhatsApp.
  9. HTTP Requests: Generic HTTP requests can be made, likely for integrating with other external APIs for specialized tasks (e.g., image generation APIs, custom data sources).
  10. Data Transformation: The Edit Fields (Set) and Convert to File nodes are used for data manipulation and file handling within the workflow.

Prerequisites/Requirements

To set up and run this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • WhatsApp Business Cloud Account: Configured with appropriate credentials for the WhatsApp Trigger and WhatsApp Business Cloud nodes.
  • AI API Keys/Credentials:
    • Google Gemini: API key for Google Gemini Chat Model and Google Gemini node.
    • Groq: API key for Groq Chat Model.
    • OpenRouter: API key for OpenRouter Chat Model.
    • Vercel AI Gateway: API key for Vercel AI Gateway Chat Model.
    • Mistral Cloud Embeddings: API key for Mistral Cloud Embeddings.
  • MongoDB Atlas Account: Credentials for the MongoDB Atlas Vector Store.
  • OpenAI API Key (Implicit, often used with LangChain agents if not explicitly configured with other LLMs).
  • Wikipedia Access: The Wikipedia tool typically doesn't require separate credentials but relies on external access.

Setup/Usage

  1. Import the Workflow: Download the provided JSON and import it into your n8n instance.
  2. Configure WhatsApp Credentials:
    • Set up your WhatsApp Business Cloud credentials in the WhatsApp Trigger and WhatsApp Business Cloud nodes.
  3. Configure AI Credentials:
    • Update the credentials for the Google Gemini Chat Model, Groq Chat Model, OpenRouter Chat Model, Vercel AI Gateway Chat Model, Google Gemini, and Embeddings Mistral Cloud nodes with your respective API keys.
  4. Configure MongoDB Atlas Vector Store:
    • Set up the credentials and connection details for your MongoDB Atlas Vector Store to enable memory and document retrieval.
  5. Review AI Agent Configuration:
    • Examine the AI Agent node to understand its prompt, tools, and memory configuration. Adjust as needed for your specific use case.
    • Ensure the Simple Memory node is correctly linked and configured.
  6. Customize Logic (Optional):
    • Modify the If and Switch nodes to adjust the routing logic based on your desired assistant behavior.
    • The HTTP Request node can be configured to integrate with other services (e.g., image generation APIs) as part of the AI agent's tools.
  7. Activate the Workflow: Once all credentials and configurations are set, activate the workflow.

Your WhatsApp assistant will now be ready to receive messages and respond using its AI capabilities!

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