Embeddable AI assistant for any website. One line of code to add a chat widget that understands page content and queries your backend APIs via function calling.
Framework: DeepAgents · Category: Chat · Language: TypeScript
Two layers of context awareness:
| Layer | Capability | Setup Cost |
|---|---|---|
| A. Page Context | AI automatically understands the current page content | Zero config (embed.js extracts it) |
| B. Business API | AI queries your backend in real time via function calling | Provide an api-schema.json |
<script src="https://your-ai-chat-assistant.edgeone.app/embed.js" async></script>A floating chat bubble appears in the bottom-right corner. Clicking it opens an iframe pointing to /widget on the same origin — the AI automatically reads the current page content. No backend changes needed.
<script
src="https://your-ai-chat-assistant.edgeone.app/embed.js"
data-color="#10b981"
data-position="bottom-left"
async>
</script>| Attribute | Default | Description |
|---|---|---|
data-color |
#6366f1 |
Accent color (bubble, buttons, avatar) |
data-position |
bottom-right |
bottom-right or bottom-left |
Edit ai-chat-assistant.config.json in the project root:
{
"name": "AI Chat Assistant",
"welcome": "Hi! How can I help you?",
"systemPrompt": "You are a helpful assistant.",
"suggestedQuestions": ["What is this page about?"]
}| Variable | Required | Description |
|---|---|---|
AI_GATEWAY_MODEL |
No | Model ID. Defaults to @makers/deepseek-v3 |
DATA_API_BASE_URL |
No | Your backend API base URL |
DATA_API_KEY |
No | Auth token for your backend API |
AI_GATEWAY_API_KEYandAI_GATEWAY_BASE_URLare automatically injected when deploying via one-click deploy.
Place an api-schema.json in the project root to let AI query your backend:
{
"tools": [
{
"name": "search_posts",
"description": "Search blog posts by keyword",
"endpoint": "GET /api/posts",
"parameters": {
"q": { "type": "string", "description": "Search keyword" }
}
}
]
}Set DATA_API_BASE_URL to your backend address.
Prerequisites:
- Node.js 18+
- EdgeOne CLI (
npm i -g edgeone) - An
AI_GATEWAY_API_KEY— get one from Makers Console → Models → API Key
npm install
cp .env.example .env
# Edit .env and fill in AI_GATEWAY_API_KEY and AI_GATEWAY_BASE_URL
edgeone makers devOpen http://localhost:8088 to view the app.
Built-in models are free within quota, great for testing. For production, bring your own key (BYOK) from any OpenAI-compatible provider.
MIT