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.
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 OpenAI
response formats, Cloudflare AI
response formats, and plain text
responses
Support various backend endpoints through custom configurations
, providing any project with a universal frontend chatbot
Support the download of chat history
, interrupt the current generation, and repeat the previous generation to quickly test the backend inference capabilities
Support MCP (Model Context Protocol)
by acting as a renderer and facilitating community interactions with the backend main process via IPC
Inquiries with image inputs can be made using multimodal vision models
Support for toggling between original format
and Markdown format
display
Support internationalization and localization i18n
The demo will use
Llama-3.3-70B-Instruct
by default
Multimodal image upload is only supported for vision models
Option 2: Download Index and open it locally (recommended) Option 3: Download Index and deploy it by pythonMCP tools call necessitates a desktop backend and LLM support in OpenAI format, referencing Chat-MCP
cd /path/to/your/directory python3 -m http.server 8000
Then, open your browser and access
http://localhost:8000
Option 5: Deploy your own Chatbot by DockerDemo: https://www2.aiql.com
docker run -p 8080:8080 -d aiql/chat-ui
Option 7: Deploy within K8s Option 8: Integrated as a renderer within the desktop applicationDon't forget add
app_port: 8080
inREADME.md
Demo: Chat-MCP
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
If you're experiencing issues opening the page and a simple refresh isn't resolving the issue, please take the following steps:
Reset Interface ConfigurationRefresh
icon on the upper right of Interface Configuration
Reset All Config
iconNetwork
section.Introduce the image as sidecar container
spec: template: metadata: labels: app: my-app spec: containers: - name: chat-ui image: aiql/chat-ui ports: - containerPort: 8080
Add service
apiVersion: v1 kind: Service metadata: name: chat-ui-service spec: selector: app: my-app ports: - protocol: TCP port: 8080 targetPort: 8080 type: LoadBalancer
You can access the port or add other ingress
apiVersion: networking.k8s.io/v1 kind: Ingress metadata: name: my-app-ingress annotations: nginx.ingress.kubernetes.io/rewrite-target: /$1 spec: rules: - host: chat-ui.example.com http: paths: - path: / pathType: Prefix backend: service: name: chat-ui-service port: number: 8080
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