# dialogflow

**Repository Path**: dialogflowai/dialogflow

## Basic Information

- **Project Name**: dialogflow
- **Description**: 单个文件的智能对话机器人。包含意图识别、知识库、AI模型管理、可视化对话机器人编辑器和应答逻辑于一体的工具。
- **Primary Language**: Rust
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: https://dialogflowai.github.io/
- **GVP Project**: No

## Statistics

- **Stars**: 5
- **Forks**: 1
- **Created**: 2025-05-26
- **Last Updated**: 2025-12-16

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

[简体中文](./README_zh-CN.md) | English

# Dialog flow AI
**only ONE executable file**, you can use it directly, including intent detection, AI management, a visual process editor and a response system.  
<img src="https://img.shields.io/badge/Latest_version-v1.19.3-blue" /> <img src="https://img.shields.io/badge/MSRV-1.88.0-green" /> [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/dialogflowai/dialogflow)

![All in ONE](./doc/assets/allinone.png)

![Dialog flow editor](./doc/assets/screenshots/flow-editor-en.png)

![Dialog flow editor](./doc/assets/screenshots/chat_demo_eng.gif)

# ✨ 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 [dialogflowai/dialogflow](https://hub.docker.com/r/dialogflowai/dialogflow/)
* 💻 **Binary releases**, please check [here](https://github.com/dialogflowai/dialogflow/releases)

> 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`

<!-- # Releases and source code
* 💾 If you're looking for **binary releases**, please check [here](https://github.com/dialogflowai/dialogflow/releases)
* 🎈 The **back end** of this application is [here](https://github.com/dialogflowchatbot/dialogflow-backend)
* 🎨 The **front end** of this application is [here](https://github.com/dialogflowchatbot/dialogflow-frontend) -->

# Check out introduction page
[https://dialogflowai.github.io/](https://dialogflowai.github.io/)

# Function nodes
|Node|Name|
|----|----|
|![DialogNode](./doc/assets/screenshots/dialogNode.png)|Dialog Node|
|![LLM chat node](./doc/assets/screenshots/llmChatNode.png)|Large language model chat node|
|![](./doc/assets/screenshots/knowledgeBaseAnswerNode.png)|Knowledge base answer node|
|![](./doc/assets/screenshots/conditionNode.png)|Conditions node|
|![](./doc/assets/screenshots/gotoNode.png)|Goto node|
|![](./doc/assets/screenshots/collectNode.png)|Collect node|
|![](./doc/assets/screenshots/externalApiNode.png)|External HTTP node|
|![](./doc/assets/screenshots/sendEmailNode.png)|Send email node|
|![](./doc/assets/screenshots/theEndNode.png)|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
![Homepage](./doc/assets/screenshots/homepage.png)

![Robot detail](./doc/assets/screenshots/robotDetail.png)

### Trying a demo dialog flow
![Demo](./doc/assets/screenshots/demo1.gif)

### Setup a condition branch
![Setup a condition branch](./doc/assets/screenshots/condition1.gif)

### Text generation

![Text generation](./doc/assets/screenshots/textGeneration.gif "Text generation")

### Testing a dialog flow
![Flow testing tool](./doc/assets/screenshots/testing.png "Flow testing tool")


# Get started

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

### Binary release
1. From [Github release page](https://github.com/dialogflowai/dialogflow/releases), depending on the operating system, download the application.
1. 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`.
1. Open your browser and visit http://localhost:12715 (by default) or http://`new IP`:`new port` to see the application in action
1. Add a main flow and click its name into it
1. Create dialog flow by dragging and drop nodes onto canvas
1. Test it