Intelligent Conversational Agent with Real-World Data Integration
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Empower your AI to go beyond simple text generation. This workflow enables a conversational agent to leverage external tools like Wikipedia and a live weather API, providing dynamic and contextually relevant responses. Maintain conversational flow with built-in memory management.
About This Workflow
This n8n workflow orchestrates a powerful conversational AI agent capable of interacting with real-world data. At its core, an Ollama-powered LLM acts as the brain, enhanced by LangChain for sophisticated agent capabilities. The agent is instructed via a system message to act as a helpful assistant, capable of utilizing both a Wikipedia tool for general information retrieval and a live weather API to fetch current weather and forecast data based on location. Crucially, the workflow incorporates window buffer memory, allowing the agent to recall the last 20 messages, ensuring continuity and context within conversations. This setup transforms a basic chatbot into an intelligent assistant that can perform research, provide up-to-date information, and engage in more meaningful interactions.
Key Features
- Dynamic Data Integration: Seamlessly connect to external APIs like weather services and knowledge bases like Wikipedia to enrich AI responses.
- Contextual Conversation: Utilizes buffer memory to maintain conversation history, enabling more natural and coherent dialogue.
- Tool-Augmented Intelligence: Empowers the AI agent to proactively use defined tools to fulfill user requests.
- Flexible LLM Integration: Designed to work with Ollama, allowing for local and customizable language model deployments.
- No-Code Workflow Automation: Built within n8n, offering a visual and intuitive way to configure and deploy sophisticated AI applications.
How To Use
- Trigger Configuration: Set up the 'On new manual Chat Message' node to initiate the workflow when a new message is received.
- LLM Setup: Configure the 'Ollama Chat Model' node with your preferred Ollama model (e.g., 'llama3.2:latest') and ensure your Ollama API credentials are set up.
- Memory Management: Connect the 'Window Buffer Memory' node to the 'AI Agent' to store conversation history (set 'contextWindowLength' to 20).
- System Prompt: Define the 'AI Agent' node's system message to guide its behavior and specify its available tools.
- Tool Integration: Connect the 'Wikipedia' and 'Weather HTTP Request' nodes to the 'AI Agent' node, ensuring the 'AI Agent' can recognize and utilize them.
- API Configuration: For the 'Weather HTTP Request' node, ensure the URL and query parameters are correctly set up to fetch weather data.
- Workflow Execution: Trigger the workflow with a chat message that requires information retrieval or action from the integrated tools.
Apps Used
Workflow JSON
{
"id": "7b9e082d-cdf3-4de3-a61f-0b33ef3f0665",
"name": "Intelligent Conversational Agent with Real-World Data Integration",
"nodes": 21,
"category": "Marketing",
"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: 7b9e082d-cdf3...
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