AI Chat Summarizer with Persistent Memory
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This workflow automates the summarization of recent chat messages using an advanced AI agent, leveraging MongoDB for persistent conversation memory. It can proactively generate summaries on a schedule or manual trigger and send them back to your designated chat channels.
About This Workflow
This powerful n8n workflow intelligently processes and summarizes your chat conversations. It seamlessly integrates with chat platforms via TelePilot nodes to fetch recent messages and sends AI-generated summaries back. At its core, an AI Agent powered by OpenRouter's language models is enhanced with MongoDB Chat Memory, providing consistent, context-aware interactions. Whether you need daily digest reports of team communications or periodic summaries of active discussions, this workflow keeps you informed without constant manual monitoring, ensuring no crucial information is missed and enhancing productivity.
Key Features
- Intelligent Chat Summarization: Automatically condenses recent chat activity into concise, AI-generated summaries.
- Persistent Conversation Memory: Utilizes MongoDB to store chat history, enabling the AI agent to maintain context and deliver more relevant responses across sessions.
- Flexible Triggering Options: Initiate summaries manually, or set up a recurring schedule for automated, timely updates.
- Advanced AI Integration: Connects with OpenRouter for access to a diverse range of cutting-edge language models, ensuring high-quality outputs.
- Seamless Chat Platform Integration: Leverages TelePilot nodes for robust interaction with chat platforms, including fetching messages and sending summaries.
How To Use
- Configure TelePilot Nodes: Set up your TelePilot credentials for
Get Chat Id By Name,Last Messages History, andSend Summary To Chatto connect securely with your target chat platform. - Set up OpenRouter Chat Model: Provide your OpenRouter API key within the
OpenRouter Chat Modelnode to grant the AI agent access to various language models. - Connect MongoDB Chat Memory: Configure your MongoDB connection details in the
MongoDB Chat Memorynode to enable persistent storage and retrieval of chat history for contextual AI interactions. - Define Trigger Mechanism: Choose your preferred trigger: use
Schedule Triggerfor automated summaries at defined intervals orWhen clicking ‘Execute workflow’for on-demand manual execution. - Refine Message Filters: Adjust the
Filter Last 2 hoursnode to specify the desired time window for messages to be summarized, and review theSkip Empty Messagenode's configuration as needed.
Apps Used
Workflow JSON
{
"id": "683c1254-06ca-437d-b580-9a5b34ed74a0",
"name": "AI Chat Summarizer with Persistent Memory",
"nodes": 21,
"category": "Operations",
"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: 683c1254-06ca...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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