Simple LLM Chatbot App

This is a basic conversational chatbot built using Zedflows. It uses a 2-node workflow to power a personalized assistant that remembers previous messages per user.

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What It Does

• Takes user input via a text field
• Sends the message to an LLM
• Maintains a conversation using memory (per user)
• Replies back with a contextual response

Workflow Setup

The app consists of a single workflow with 2 main nodes:

1. Trigger Node: Text Input

• Presents a chat input field to the user
• Accepts their message (e.g. "Tell me a joke")
• Passes this text to the next node
• Each input is scoped to the user (via session or ID)

2. LLM Node: Chat with Memory

• Connected to the trigger
• Uses a Memory Tool to keep conversation history per user
• Memory scope is user-specific, so each session is personalized
• Supports multiple turns in the same context

How to Build It in Zedflows

1. Create a new Workflow
2. Add a Trigger Node
   • Choose type: Text Input
   • Customize placeholder: "Ask me anything..."
3. Add an LLM Node
   • Set prompt: "You are a helpful assistant. Answer conversationally."
   • Enable Memory Tool
4. Connect the Trigger → LLM
5. Optionally create an App

🌐 Result

Users visit your app, type a message, and get a smart response. The assistant remembers what was said earlier in the chat, so it can hold natural conversations.

This is the perfect base to:

• Expand with APIs or vector search
• Turn into a customer support bot

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