Library / Chatbots & Messaging Bots
Chatbots & Messaging Bots
Build a Custom Chat Agent with LangChain and Gemini
When a chat message is received, a Gemini model with stored conversation history answers it using a prompt that defines the agent's personality.
What it does
👇 Prompt Engineering - Define agent personality and conversation structure in the Construct & Execute LLM Prompt node's template variable - ⚠️ Template must preserve {chat_history} and {input} placeholders for proper LangChain operation
The steps
- When chat message received
- Google Gemini Chat Model
- Store conversation history
- Construct & Execute LLM Prompt
Similar automations
AI Agents & AssistantsCustom Self-Hosted AI Agent with LangChain and Gemini7 stepsAI Agents & AssistantsBuild a Wikipedia Agent with the LangChain Code Node11 stepsContent Writing & GenerationSummarize YouTube Transcripts with LangChain Code and OpenAI4 stepsRAG & Knowledge BasesAnswer Questions with a LangChain Workflow Content Retriever5 steps