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Dialog flow chat bot

only ONE executable file, you can use it directly, including intent detection, AI management, a visual process editor and a response system.

✨ Features

• 🛒 Light Only ONE executable file, it can run smoothly on laptops without GPUs (data files will be created at runtime automatically).
• 🐱‍🏍 AI powered Integrated Huggingface local models (Llama, Phi-3, Gemma, Multilingual E5, MiniLM L6v2, NomicEmbedTextV1_5, etc.), Ollama and OpenAI, this can be used for Chat, Text generation and Intent detection.
• 🚀 Fast Built on Rust and Vue3.
• 😀 Simple Use the mouse to drag and drop with our intuitive node-based editor.
• 🔐 Safe 100% open source, all runtime data is saved locally (Using OpenAI API may expose some data).

Give it a try!

• 🐋 Docker We provided an image on Docker Hub at dialogflowchatbot/demo
• 💻 Binary releases, please check here

By default application will listen to 127.0.0.1:12715, you can use -ip and -port specify new value, e.g.: dialogflow -ip 0.0.0.0 -port 8888

Check out introduction page

https://easyflow-ai.github.io/

Function nodes

Node	Name
	Dialog Node
	Large language model chat node
	Knowledge base answer node
	Conditions node
	Goto node
	Collect node
	External HTTP node
	Send email node
	The end node

Using the different nodes above, to arrange and combine, you can get a conversational bot that can handle problems in different scenarios.

Screenshots

Trying a demo dialog flow

Setup a condition branch

Text generation

Testing a dialog flow

Get started

Docker image

1. docker pull dialogflowchatbot/demo
2. docker run -dp 127.0.0.1:12715:12715 --name dialogflowdemo dialogflowchatbot/demo
3. Open your browser and visit: http://127.0.0.1:12715/

Binary release

1. From Github release page, depending on the operating system, download the application.
2. Run it directly, or use the -ip and -port parameters to perform the listening IP address and port, e.g.: dialogflow -ip 0.0.0.0 -port 8888.
3. Open your browser and visit http://localhost:12715 (by default) or http://new IP:new port to see the application in action
4. Add a main flow and click its name into it
5. Create dialog flow by dragging and drop nodes onto canvas
6. Test it