AI-Powered Chat System with DeepSeek and Ollama Integration

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This n8n workflow creates an advanced AI chat system by integrating multiple language models and external APIs. When a chat message is received, it processes the input through various AI services, including DeepSeek and Ollama, to generate insightful, reasoning-based, and conversational responses. The workflow leverages nodes for handling chat triggers, API requests, memory buffers, and language model execution.

The process begins with a webhook trigger that detects an incoming chat message. This message triggers different language processing nodes, such as DeepSeek, Ollama, and an AI assistant agent, which interpret, reason, and generate responses based on the input. Sticky notes document detailed configurations and API endpoints, providing a clear reference for setting up external models and APIs.

The workflow is highly flexible, suitable for use cases like customer support chatbots, AI research tools, or interactive virtual assistants that require complex reasoning and multi-model integrations. Its modular design allows users to customize and extend the system with additional language models or APIs, making it a powerful solution for advanced conversational AI setups.

Node Count

11 – 20 Nodes

Nodes Used

@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chainLlm, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.lmChatOllama, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, httpRequest, stickyNote

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