Community Contributed: Build Custom AI Agent with LangChain & Gemini
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A template to build a custom AI agent using LangChain and Google Gemini.
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About This Workflow
Overview
This workflow demonstrates how to build a custom AI agent using LangChain and Google Gemini. It includes functionalities for receiving chat messages, processing them with a language model, managing conversation history, and constructing LLM prompts.
Key Features
- Utilizes Google Gemini for AI language model capabilities.
- Implements LangChain for building the AI agent.
- Manages conversation history using memory.
- Allows for prompt engineering and customization.
- Provides options for different interaction methods (direct testing or webhook).
- Includes setup instructions and configuration tips.
How To Use
- Configure Gemini Credentials: Set up your Google Gemini API key.
- Set up Interaction: Test directly in the editor or activate the workflow and use the provided URL for chat.
- Customize: Modify the LLM prompt, language model, and memory settings as needed.
Apps Used
Workflow JSON
{
"id": "3e09deea-78f5-4d31-8e6a-82b18602c5e2",
"name": "Community Contributed: Build Custom AI Agent with LangChain & Gemini",
"nodes": 0,
"category": "AI & Machine Learning",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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