Create a Custom Conversational AI Agent with LangChain and Google Gemini
Develop a personalized AI conversational agent using LangChain and Google Gemini for self-hosted environments, offering extensive customization and efficient token usage.
This workflow allows users to build a highly customizable AI conversational agent using LangChain and Google Gemini. It is designed for those who need precise control over agent prompts and wish to minimize token consumption compared to n8n's built-in Conversation Agent. Users can configure various aspects such as interface settings, prompt engineering, model selection, and memory control. The workflow is ideal for self-hosted n8n setups and requires setting up Google Gemini API credentials.
- Platform
- n8n
- Category
- AI
- Price
- $9.99
- Creator
- Owen MacLeod
- share
- stickyNote
- code
- chatTrigger
- lmChatGoogleGemini
- memoryBufferWindow
How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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