AI Agent Chatbot with Long Term Memory, Note Storage, and Telegram Integration
detail.loadingPreview
An AI chatbot that maintains long-term and short-term memory, stores notes, and integrates with Telegram.
🚀Ready to Deploy This Workflow?
About This Workflow
Overview
This workflow creates an AI chatbot agent that leverages long-term memory storage (via Google Docs), short-term windowed memory, and note-taking capabilities. It also provides seamless integration with Telegram for receiving user messages and sending responses.
Key Features
- AI Agent with customizable system message and role.
- Long-Term Memory storage and retrieval using Google Docs.
- Window Buffer Memory for short-term context.
- Note storage functionality.
- Telegram integration for chat input and output.
How To Use
- Import Workflow: Import this JSON into your n8n instance.
- Configure Credentials: Set up and connect your Telegram API, OpenAI API, and Google Docs OAuth2 API credentials.
- Set Environment Variables: Configure any necessary environment variables, especially
BASE_URLfor Google Docs operations. - Customize AI Agent: Adjust the
systemMessagein the 'AI Tools Agent' node to define the AI's role, rules, and behavior. - Configure Memory: Set the
sessionKeyandcontextWindowLengthin the 'Window Buffer Memory' node. - Test: Trigger the workflow manually or via a connected Telegram bot to test its functionality.
Apps Used
Workflow JSON
{
"id": "39d0444f-9a3f-44d4-97ec-f47c76daa0eb",
"name": "AI Agent Chatbot with Long Term Memory, Note Storage, and Telegram Integration",
"nodes": 0,
"category": "AI & Machine Learning",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 39d0444f-9a3f...
About the Author
SaaS_Connector
Integration Guru
Connecting CRM, Notion, and Slack to automate your life.
Statistics
Verification Info
Related Integrations
- Google Sheets + Schedule Trigger(394 workflows)
- Telegram + Telegram Trigger(362 workflows)
- Google Sheets + Split Out(277 workflows)
- Gmail + Schedule Trigger(270 workflows)
- Google Sheets + Slack(268 workflows)
- Gmail + Google Sheets(245 workflows)
- Google Drive + Google Sheets(203 workflows)
- Form Trigger + Google Sheets(163 workflows)
- Schedule Trigger + Telegram(152 workflows)
- Google Drive + Google Drive Trigger(135 workflows)
Related Workflows
Discover more workflows you might like
Build a Conversational AI Agent with LangChain, Tools, and Memory in n8n
This workflow demonstrates how to create an intelligent AI agent using LangChain in n8n. It leverages an OpenAI model, buffer memory for conversation history, and external tools like Wikipedia and SerpAPI for enhanced responses. The 'On new manual Chat Message' node initiates the agent's interaction.
Automated Car Insurance Quote Generator with AI and Vector Store
This n8n workflow generates car insurance quotes using an AI agent. It leverages LangChain nodes like Webhook, Text Splitter, Embeddings, and Vector Store (Pinecone) to process and retrieve relevant information, then logs the results to a Google Sheet.
Create an AI-Powered Telegram Bot with Langchain and DALL-E 3
Build a sophisticated Telegram bot using n8n, integrating Langchain for AI conversation and DALL-E 3 for image generation. This workflow allows for dynamic chat interactions and creative image creation directly through Telegram.
Automated Screenshot Analysis with AI
This workflow uses URLbox to capture website screenshots and then leverages OpenAI to analyze and summarize the visual content. It automatically extracts key information from web pages for content analysis.
Business WhatsApp AI RAG Chatbot for Electronics Stores
Build an AI-powered chatbot for your electronics store on WhatsApp using Retrieval Augmented Generation (RAG). This workflow integrates with Google Drive for knowledge base, Qdrant for vector storage, and OpenAI for AI.
Build a Telegram RAG PDF Chatbot with OpenAI and Pinecone
This workflow enables users to chat with PDF documents via Telegram. It uses OpenAI for embeddings and question answering, and Pinecone for vector storage, creating a powerful Retrieval-Augmented Generation (RAG) system.