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Chat UI
Single-File AI Chatbot UI with Multimodal & MCP Support: An All-in-One HTML File for a Streamlined Chatbot Conversational Interface
Install
docker run -p 8080:8080 -d aiql/chat-uiclaude mcp add chat-ui -- docker run -p 8080:8080 -d aiql/chat-ui{
"mcpServers": {
"chat-ui": {
"command": "docker",
"args": [
"run",
"-p",
"8080:8080",
"-d",
"aiql/chat-ui"
]
}
}
}Install command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →Chat UI
The UI of Chat is becoming increasingly complex, often encompassing an entire front-end project along with deployment solutions.
This repository aims to construct the entire front-end UI using a single HTML file, aiming for a minimalist approach to create a chatbot.
By simplifying the structure and key functions, developers can quickly set up and experiment with a functional chatbot, adhering to a slimmed-down project design philosophy.
Features
Supports OpenAI-format requests, enabling compatibility with various backends such as
HuggingFace Text Generation Inference (TGI),vLLM, etc.Automatically supports multiple response formats without additional configuration, including standard
OpenAIresponse formats,Cloudflare AIresponse formats, andplain textresponsesSupport various
backend endpoints through custom configurations, providing any project with a universal frontend chatbotSupport the
download of chat history, interrupt the current generation, and repeat the previous generation to quickly test the backend inference capabilitiesSupport
MCP (Model Context Protocol)by acting as a renderer and facilitating community interactions with the backend main process via IPCInquiries with image inputs can be made using
multimodal vision modelsSupport for toggling between
original formatandMarkdown formatdisplaySupport internationalization and localization
i18n
How to use
Option 1: Chat with demo AIQL
The demo will use
Llama-3.3-70B-Instructby default
Multimodal image upload is only supported for vision models
MCP tools call necessitates a desktop backend and LLM support in OpenAI format, referencing Chat-MCP
Option 2: Download Index and open it locally (recommended)
Option 3: Download Index and deploy it by python
cd /path/to/your/directory
python3 -m http.server 8000
Then, open your browser and access
http://localhost:8000
Option 4: fork this repo and link it to Cloudflare pages
Demo: https://www2.aiql.com
Option 5: Deploy your own Chatbot by Docker
docker run -p 8080:8080 -d aiql/chat-ui
Option 6: Deploy within Huggingface
Don't forget add
app_port: 8080inREADME.md
Option 7: Deploy within K8s
Option 8: Integrated as a renderer within the desktop application
Demo: Chat-MCP
How to config
By default, the Chatbot will use API format as OpenAI ChatGPT.
You can insert your OpenAI API Key and change the Endpoint in configuration to use API from any other vendors
You can also download the config template from example and insert your API Key, then use it for quick configuration
Trouble Shooting
If you're experiencing issues opening the page and a simple refresh isn't resolving the issue, please take the following steps:
Reset Interface Configuration
- Click
Refreshicon on the upper right ofInterface Configuration
Reset All Configuration
- Click hidden botton on the right side of the index page
- Click
Reset All Configicon
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