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data"},"license":"AGPL-3.0","keywords":["nextjs","next","typescript","antd","chatbot"],"description":"SmartData Embedded Agent","maintainers":[{"name":"firsi","email":"firsijc@gmail.com"},{"name":"dendekky","email":"adeniyiib360@gmail.com"}],"readme":"![npm](https://img.shields.io/npm/v/@smartdatahq/embedded-agent)\n![license](https://img.shields.io/badge/License-AGPL%20v3-blue.svg)\n\n# Installation Guide: Embedded Agent\n\n### N:B: This installation guide is for installing the npm package, to run the app locally, check the readme in the repo root.\n\nThe `@smartdatahq/embedded-agent` package is a powerful tool for integrating AI-driven conversational agents into your web applications. It offers two integration paths:\n\n- **Embedded Agent** — A pre-built, full-featured chat UI with all the bells and whistles (Ant Design components, theming, popups, etc.)\n- **Headless Agent** — React hooks and a provider that give you complete control over the UI while handling all the WebSocket, messaging, and state management under the hood.\n\n## Table of Contents\n\n- [Prerequisites](#prerequisites)\n- [Installation](#installation)\n- [Embedded Agent (Pre-built UI)](#embedded-agent-pre-built-ui)\n  - [Import the Component](#import-the-component)\n  - [Minimal Example](#minimal-example)\n- [Headless Agent (Custom UI)](#headless-agent-custom-ui)\n  - [Quick Start](#quick-start)\n  - [Message Format](#message-format)\n  - [Using Individual Hooks](#using-individual-hooks)\n  - [Sending Messages](#sending-messages)\n  - [Message Feedback (Thumbs)](#message-feedback-thumbs)\n  - [File Uploads](#file-uploads)\n  - [Connection Management](#connection-management)\n  - [Conversation Management](#conversation-management)\n  - [Audio / Voice](#audio--voice)\n  - [Agent Configuration](#agent-configuration)\n  - [Notifications](#notifications)\n  - [Full Headless Example](#full-headless-example)\n- [Browser Tools Integration](#browser-tools-integration)\n  - [Overview](#overview)\n  - [Basic Browser Tools Example](#basic-browser-tools-example)\n  - [Advanced Browser Tools Example](#advanced-browser-tools-example)\n  - [Browser Tools with Headless Agent](#browser-tools-with-headless-agent)\n  - [Handling Internal Tool Calls (ask_question)](#handling-internal-tool-calls-ask_question)\n  - [Tool Schema Format](#tool-schema-format)\n  - [Parameter Types](#parameter-types)\n  - [Error Handling](#error-handling)\n  - [Best Practices](#best-practices)\n- [Checkout Integration (Headless)](#checkout-integration-headless)\n  - [Checkout Flow](#checkout-flow)\n  - [Adyen Drop-in Example](#adyen-drop-in-example)\n- [API Reference](#api-reference)\n  - [EmbeddedAgent Props](#embeddedagent-props)\n  - [AgentProvider Props (AgentConfig)](#agentprovider-props-agentconfig)\n  - [Headless Hooks](#headless-hooks)\n  - [Utility Functions](#utility-functions)\n\n## Prerequisites\n\nBefore using the `@smartdatahq/embedded-agent` package, ensure the following:\n\n1. You have Node.js (version 14 or higher) and npm installed on your system.\n2. You have a valid **identifier** to connect to the `@smartdatahq/embedded-agent` service.\n   Make sure you contact us to get your identifier.\n\n---\n\n## Installation\n\nTo install the package, use npm or yarn:\n\nThe project ships as two packages. Pick the one that matches what you are building:\n\n| Package | Use it when |\n|---|---|\n| `@smartdatahq/embedded-agent` | You want the pre-built chat UI (`<EmbeddedAgent />`). Depends on the headless package. |\n| `@smartdatahq/embedded-agent-headless` | You are building your own UI and only need the provider and hooks. Installs `zustand` and `uuid`, nothing else. |\n\n### Pre-built UI\n\n```bash\nnpm install @smartdatahq/embedded-agent\n# or\nyarn add @smartdatahq/embedded-agent\n```\n\n### Headless\n\n```bash\nnpm install @smartdatahq/embedded-agent-headless\n# or\nyarn add @smartdatahq/embedded-agent-headless\n```\n\n---\n\n## Embedded Agent (Pre-built UI)\n\nThe embedded agent gives you a ready-made chat interface with theming, minimization, popups, and all standard UI features.\n\n##### Import the Component\n\n```javascript\nimport { EmbeddedAgent } from \"@smartdatahq/embedded-agent\";\nimport \"@smartdatahq/embedded-agent/dist/index.css\";\n```\n\nIf your application is mostly SSR, you might need to dynamically import the package since it needs to run on the browser.\nFor example, in next.js, you would want to import it like this\n\n```javascript\nconst EmbeddedAgent = dynamic(\n  () => import(\"@smartdatahq/embedded-agent\").then((mod) => mod.EmbeddedAgent),\n  {\n    ssr: false,\n  },\n);\n```\n\n##### Minimal Example\n\nUse the following example to set up the agent in your application:\n\n```typescript\nconst App = () => {\n  const [minimized, setMinimized] = useState(true);\n  const [isRendered, setIsRendered] = useState(true);\n\n  return (\n    <>\n    <button\n      type=\"button\"\n      onClick={() => setIsRendered(!isRendered)}\n      style={{ padding: \"8px 16px\", }}\n    >\n      Toggle Rendered\n    </button>\n    <div style={{ height: minimized ? 68 : 400 }}>\n      <h1>My Embedded Agent Application</h1>\n      <EmbeddedAgent\n        identifier=\"YOUR_IDENTIFIER\" // Replace with your unique identifier\n        minimized={minimized}\n        onMinimizedChange={() => setMinimized(!minimized)}\n        isRendered={isRendered}\n      />\n    </div>\n    </>\n  );\n};\n```\n\n---\n\n## Headless Agent (Custom UI)\n\nThe headless agent gives you full control over the UI while the package handles WebSocket connections, message parsing, streaming, conversation state, and audio.\n\nInstall `@smartdatahq/embedded-agent-headless` and import from it — no CSS import needed:\n\n```typescript\nimport { AgentProvider, useAgent } from \"@smartdatahq/embedded-agent-headless\";\n```\n\n> **Upgrading from `@smartdatahq/embedded-agent/headless`?** That subpath is still exported and re-exports the headless package, so nothing breaks. It does, however, pull in the pre-built UI's dependency tree (antd, markdown rendering, i18n, auth). Move the import to `@smartdatahq/embedded-agent-headless` and you can drop `@smartdatahq/embedded-agent` entirely.\n\n### Quick Start\n\nWrap your component tree with `AgentProvider` and use the `useAgent()` convenience hook:\n\n```tsx\nimport { AgentProvider, useAgent } from \"@smartdatahq/embedded-agent-headless\";\n\nfunction ChatUI() {\n  const {\n    messages,\n    sendMessage,\n    isBotThinking,\n    isStreaming,\n    isConnected,\n    conversationId,\n    configLoading,\n    configError,\n  } = useAgent();\n\n  if (configLoading) return <p>Loading agent...</p>;\n  if (configError) return <p>Failed to load agent configuration.</p>;\n\n  return (\n    <div>\n      {messages.map((msg, i) => (\n        <div key={i} className={msg.user === \"user\" ? \"user-msg\" : \"bot-msg\"}>\n          {msg.message}\n        </div>\n      ))}\n\n      {isBotThinking && <p>Thinking...</p>}\n\n      <input\n        type=\"text\"\n        onKeyDown={(e) => {\n          if (e.key === \"Enter\") {\n            sendMessage(e.currentTarget.value);\n            e.currentTarget.value = \"\";\n          }\n        }}\n        disabled={!isConnected}\n      />\n    </div>\n  );\n}\n\nexport default function App() {\n  return (\n    <AgentProvider config={{ identifier: \"YOUR_IDENTIFIER\" }}>\n      <ChatUI />\n    </AgentProvider>\n  );\n}\n```\n\n### Message Format\n\nBot messages are returned in **Markdown format**. When building your own UI, use a Markdown renderer (e.g. `react-markdown`, `marked`, etc.) to display them properly. Each message also carries a `time` (its server timestamp, used for replies and feedback) and, on rated bot messages, a `feedback` field (see [Message Feedback](#message-feedback-thumbs)):\n\n```tsx\nimport ReactMarkdown from \"react-markdown\";\n\n{messages.map((msg, i) => (\n  <div key={i}>\n    {msg.user === \"bot\" ? (\n      <ReactMarkdown>{msg.message}</ReactMarkdown>\n    ) : (\n      <p>{msg.message}</p>\n    )}\n  </div>\n))}\n```\n\n### Using Individual Hooks\n\nFor more granular control, use the composable hooks instead of `useAgent()`:\n\n```tsx\nimport {\n  useAgentConnection,\n  useAgentMessages,\n  useAgentSend,\n  useAgentConversation,\n  useAgentAudio,\n  useAgentConfig,\n} from \"@smartdatahq/embedded-agent-headless\";\n\nfunction MyChat() {\n  // Connection state\n  const { isConnected, reconnect } = useAgentConnection();\n\n  // Read-only message state\n  const { messages, isBotThinking, isStreaming, botActivity } = useAgentMessages();\n\n  // Send actions\n  const { sendMessage, sendReply, sendFeedback, respondToBrowserToolCall } = useAgentSend();\n\n  // Conversation lifecycle\n  const { conversationId, startNewConversation, deleteConversation, downloadChatHistory, getChatUrl } =\n    useAgentConversation();\n\n  // Audio (voice input)\n  const audio = useAgentAudio();\n\n  // Remote agent configuration + loading state\n  const { agentConfig, configLoading, configError } = useAgentConfig();\n\n  // ... build your UI\n}\n```\n\n### Sending Messages\n\n```tsx\nconst { sendMessage, sendReply, sendFeedback, sendMessageFeedback } = useAgentSend();\n\n// Send a text message\nsendMessage(\"Hello, how can you help me?\");\n\n// Reply to a specific message (by its timestamp)\nsendReply(\"Thanks, that's helpful!\", \"2025-01-15T10:30:00.000Z\");\n\n// Submit the conversation-level feedback survey (stars)\nsendFeedback({ rating: 5, comments: \"Great experience!\" });\n\n// Rate a single bot message (thumbs) — see Message Feedback below\nsendMessageFeedback({ timestamp: msg.time, value: \"positive\" });\n```\n\n### Message Feedback (Thumbs)\n\nPer-message thumbs up / thumbs down uses the `MESSAGE_FEEDBACK` protocol. Call `sendMessageFeedback()` with the **bot** message's `time`; the package builds the frame, applies the server caps (10 topics, 500-char comment), and updates the message's `feedback` field only once the server acknowledges it.\n\n```tsx\nconst { messages, sendMessageFeedback, agentConfig } = useAgent();\n\n// Thumbs up\nsendMessageFeedback({ timestamp: msg.time, value: \"positive\" });\n\n// Thumbs down with optional topics and comment\nsendMessageFeedback({\n  timestamp: msg.time,\n  value: \"negative\",\n  topics: [\"Wrong source\"],\n  comment: \"didn't cite a source\",\n});\n\n// Clear (e.g. user re-clicks the active thumb)\nsendMessageFeedback({ timestamp: msg.time, value: null });\n```\n\nRender the thumbs from `message.feedback?.value` — **do not update optimistically**. The value is set when the `feedback_ack` frame lands and is restored automatically from history on reload / reconnect:\n\n```tsx\n{messages.map((msg) => {\n  const value = msg.feedback?.value; // \"positive\" | \"negative\" | undefined\n  return (\n    <div key={msg.time}>\n      <ReactMarkdown>{msg.message}</ReactMarkdown>\n      {msg.user === \"bot\" && (\n        <>\n          <button\n            aria-pressed={value === \"positive\"}\n            onClick={() =>\n              sendMessageFeedback({\n                timestamp: msg.time,\n                value: value === \"positive\" ? null : \"positive\",\n              })\n            }\n          >\n            👍\n          </button>\n          <button\n            aria-pressed={value === \"negative\"}\n            onClick={() =>\n              value === \"negative\"\n                ? sendMessageFeedback({ timestamp: msg.time, value: null })\n                : openThumbsDownModal(msg) // collect topics / comment, then send \"negative\"\n            }\n          >\n            👎\n          </button>\n        </>\n      )}\n    </div>\n  );\n})}\n```\n\nTopic labels for the thumbs-down UI are per-agent and localized in the agent config as `feedback_options` (e.g. `[\"Incomplete\", \"Wrong source\", \"Wrong wording\", \"Didn't understand me\", \"Other\"]`). Read them from `agentConfig?.feedback_options`. The server stores whatever strings you send, but sticking to the configured vocabulary keeps analytics comparable across agents.\n\nState model per message is **positive / negative / none**. Switching thumbs replaces the previous value (last write wins). `sendFeedback()` (the star-rating survey) is a separate, conversation-level mechanism.\n\n### File Uploads\n\nFile uploads work through the same `sendMessage` function. Pass a file object instead of a string:\n\n```tsx\nconst { sendMessage } = useAgentSend();\n\nfunction handleFileChange(e: React.ChangeEvent<HTMLInputElement>) {\n  const file = e.target.files?.[0];\n  if (!file) return;\n\n  sendMessage({\n    file: file,\n    type: file.type,\n    name: file.name,\n    lastModified: file.lastModified,\n    size: file.size,\n  });\n}\n\n// In your JSX:\n<input type=\"file\" onChange={handleFileChange} />\n```\n\nThe file is read as base64 and sent over the WebSocket automatically.\n\n### Connection Management\n\n```tsx\nconst { isConnected, reconnect } = useAgentConnection();\n\n// Check connection status\nif (!isConnected) {\n  // Messages sent while disconnected are queued\n  // and delivered automatically on reconnect\n  reconnect();\n}\n```\n\n### Conversation Management\n\n```tsx\nconst {\n  conversationId,\n  startNewConversation,\n  deleteConversation,\n  downloadChatHistory,\n  getChatUrl,\n} = useAgentConversation();\n\n// Start fresh\nstartNewConversation();\n\n// Delete current conversation\ndeleteConversation();\n\n// Trigger chat history download\ndownloadChatHistory();\n\n// Get a shareable URL for the current conversation\nconst url = getChatUrl();\n```\n\n### Audio / Voice\n\n```tsx\nconst audio = useAgentAudio();\n\nif (audio) {\n  // Voice input is available\n  const { isVoiceActive, activateVoice, deactivateVoice } = audio;\n\n  return (\n    <button onClick={isVoiceActive ? deactivateVoice : activateVoice}>\n      {isVoiceActive ? \"Disable Voice\" : \"Enable Voice\"}\n    </button>\n  );\n}\n```\n\n### Agent Configuration\n\nThe remote agent configuration (theme, welcome message, etc.) is fetched automatically by `AgentProvider`. Access loading state and the config via `useAgentConfig()`:\n\n```tsx\nconst { agentConfig, configLoading, configError } = useAgentConfig();\n\nif (configLoading) return <Spinner />;\nif (configError) return <p>Failed to load: {configError}</p>;\n\n// agentConfig contains the remote configuration:\n// welcome_message, icon, default_language, on_prem, feedback_options, etc.\nconsole.log(agentConfig?.welcome_message);\nconsole.log(agentConfig?.feedback_options); // thumbs-down topic labels\n```\n\n### Notifications\n\nBy default, internal notifications (e.g. microphone permission errors) are logged to the console. You can provide your own handler:\n\n```tsx\nimport { AgentProvider } from \"@smartdatahq/embedded-agent-headless\";\nimport type { NotifyFn } from \"@smartdatahq/embedded-agent-headless\";\n\nconst myNotify: NotifyFn = (message, type, options) => {\n  // type is \"success\" | \"info\" | \"warning\" | \"error\"\n  toast[type](message); // e.g. using react-hot-toast, sonner, etc.\n};\n\n<AgentProvider config={{ identifier: \"YOUR_IDENTIFIER\", onNotify: myNotify }}>\n  <ChatUI />\n</AgentProvider>\n```\n\n### Full Headless Example\n\nA complete custom chat UI using only headless hooks:\n\n```tsx\nimport { AgentProvider, useAgent } from \"@smartdatahq/embedded-agent-headless\";\n\nfunction CustomChatUI() {\n  const {\n    messages,\n    sendMessage,\n    isBotThinking,\n    isStreaming,\n    botActivity,\n    isConnected,\n    reconnect,\n    conversationId,\n    startNewConversation,\n    deleteConversation,\n    downloadChatHistory,\n    getChatUrl,\n    audio,\n    configLoading,\n    configError,\n  } = useAgent();\n\n  const inputRef = useRef<HTMLInputElement>(null);\n\n  if (configLoading) return <p>Loading...</p>;\n  if (configError) return <p>Error: {configError}</p>;\n\n  const handleSend = () => {\n    const val = inputRef.current?.value?.trim();\n    if (!val) return;\n    sendMessage(val);\n    inputRef.current!.value = \"\";\n  };\n\n  return (\n    <div>\n      {/* Connection status */}\n      <div>\n        {isConnected ? \"Connected\" : \"Disconnected\"}\n        {!isConnected && <button onClick={() => reconnect()}>Reconnect</button>}\n      </div>\n\n      {/* Messages */}\n      <div style={{ height: 400, overflowY: \"auto\" }}>\n        {messages.map((msg, i) => (\n          <div key={i} style={{ textAlign: msg.user === \"user\" ? \"right\" : \"left\" }}>\n            <span>{msg.message}</span>\n            <small>\n              {msg.user === \"user\" ? \"You\" : \"Bot\"} - {new Date(msg.time).toLocaleTimeString()}\n            </small>\n          </div>\n        ))}\n        {isBotThinking && <p>Thinking...</p>}\n        {isStreaming && botActivity && <p>{botActivity}</p>}\n      </div>\n\n      {/* Input */}\n      <input\n        ref={inputRef}\n        onKeyDown={(e) => e.key === \"Enter\" && handleSend()}\n        disabled={!isConnected}\n        placeholder=\"Type a message...\"\n      />\n      <button onClick={handleSend} disabled={!isConnected}>Send</button>\n\n      {/* Actions */}\n      <div>\n        <button onClick={startNewConversation}>New Chat</button>\n        <button onClick={deleteConversation}>Delete</button>\n        <button onClick={downloadChatHistory}>Download</button>\n        <button onClick={() => navigator.clipboard.writeText(getChatUrl())}>Copy URL</button>\n        {audio && (\n          <button onClick={audio.isVoiceActive ? audio.deactivateVoice : audio.activateVoice}>\n            {audio.isVoiceActive ? \"Disable Voice\" : \"Enable Voice\"}\n          </button>\n        )}\n      </div>\n    </div>\n  );\n}\n\nexport default function App() {\n  return (\n    <AgentProvider config={{ identifier: \"YOUR_IDENTIFIER\" }}>\n      <CustomChatUI />\n    </AgentProvider>\n  );\n}\n```\n\n---\n\n## Browser Tools Integration\n\nThe agent supports browser tools integration, allowing the AI agent to interact with your application's functionality directly. This powerful feature enables the agent to perform actions like navigation, data manipulation, API calls, and more.\n\nBrowser tools work with both the Embedded Agent and the Headless Agent.\n\n### Overview\n\nBrowser tools integration consists of three main components:\n\n1. **browserToolsRegistration**: Define available tools with their schemas\n2. **onBrowserToolCall**: Handle when the agent wants to use a tool\n3. **browserToolCallResponse** (Embedded) / **respondToBrowserToolCall** (Headless): Send the tool execution result back to the agent\n\n### Basic Browser Tools Example\n\n```typescript\nconst App = () => {\n  const [minimized, setMinimized] = useState(true);\n  const [toolResponse, setToolResponse] = useState(undefined);\n  const [shoppingCart, setShoppingCart] = useState([]);\n\n  const handleBrowserToolCall = (data) => {\n    console.log(\"Tool called:\", data);\n\n    if (data.name === \"add_to_cart\") {\n      // Add item to shopping cart\n      const newItem = {\n        id: Math.random().toString(36).substr(2, 9),\n        product_sku: data.args.product_sku,\n        quantity: data.args.quantity || 1,\n        addedAt: new Date().toISOString()\n      };\n\n      setShoppingCart(prev => [...prev, newItem]);\n\n      setToolResponse({\n        id: data.id,\n        output: {\n          success: true,\n          message: `Added ${data.args.product_sku} to cart`,\n          cartCount: shoppingCart.length + 1\n        }\n      });\n    }\n  };\n\n  return (\n    <EmbeddedAgent\n      identifier=\"YOUR_IDENTIFIER\"\n      minimized={minimized}\n      onMinimizedChange={() => setMinimized(!minimized)}\n      browserToolsRegistration={[\n        {\n          title: \"add_to_cart\",\n          scope: \"agent\",\n          description: \"Adds a product to the shopping cart. Call this tool whenever the user has confirmed that he wants to buy the product with the product SKU identifier. Ask the user how many items he wants, if it is not clear from the context of the conversation.\",\n          type: \"object\",\n          properties: {\n            product_sku: {\n              title: \"Product SKU\",\n              description: \"The product identifier to add to cart\",\n              type: \"string\"\n            },\n            quantity: {\n              title: \"Quantity\",\n              description: \"Number of items to add\",\n              type: \"integer\",\n              minimum: 1,\n              default: 1\n            }\n          },\n          required: [\"product_sku\"]\n        }\n      ]}\n      onBrowserToolCall={handleBrowserToolCall}\n      browserToolCallResponse={toolResponse}\n    />\n  );\n};\n```\n\n### Advanced Browser Tools Example\n\nHere's a more comprehensive example showing multiple tool types:\n\n```typescript\nconst App = () => {\n  const [minimized, setMinimized] = useState(true);\n  const [toolResponse, setToolResponse] = useState(undefined);\n  const [shoppingCart, setShoppingCart] = useState([]);\n\n  const handleBrowserToolCall = (data) => {\n    const { name, args, id } = data;\n\n    switch (name) {\n      case \"show_product\":\n        // Navigate to product page\n        window.history.pushState({}, '', `/product/${args.product_id}`);\n        setToolResponse({\n          id,\n          output: {\n            success: true,\n            action: \"show_product\",\n            message: `Showing product: ${args.product_id}`,\n            response: { product_id: args.product_id }\n          }\n        });\n        break;\n\n      case \"list_products\":\n        // Display product list\n        setToolResponse({\n          id,\n          output: {\n            success: true,\n            action: \"list_products\",\n            message: \"Listing products...\",\n            response: {\n              product_ids: args.product_ids,\n              description: args.description,\n              reasoning: args.reasoning\n            }\n          }\n        });\n        break;\n\n      case \"compare_products\":\n        // Navigate to comparison page\n        const idsParam = args.product_ids.join(',');\n        window.history.pushState({}, '', `/compare?ids=${idsParam}`);\n        setToolResponse({\n          id,\n          output: {\n            success: true,\n            action: \"compare_products\",\n            message: `Comparing products: ${args.product_ids.join(', ')}`,\n            response: { product_ids: args.product_ids }\n          }\n        });\n        break;\n\n      case \"search_products\":\n        // Navigate to search results\n        window.history.pushState({}, '', `/search?q=${encodeURIComponent(args.query)}`);\n        setToolResponse({\n          id,\n          output: {\n            success: true,\n            action: \"search_products\",\n            message: `Showing search results for: ${args.query}`,\n            response: {\n              navigateTo: `/search?q=${encodeURIComponent(args.query)}`,\n              query: args.query\n            }\n          }\n        });\n        break;\n\n      case \"add_to_cart\":\n        // Add products to cart\n        const newItems = args.products.map(item => ({\n          id: item.product_id,\n          quantity: item.quantity,\n          addedAt: new Date().toISOString()\n        }));\n        setShoppingCart(prev => [...prev, ...newItems.filter(item => item.quantity > 0)]);\n        setToolResponse({\n          id,\n          output: {\n            success: true,\n            action: \"add_to_cart\",\n            message: \"Added products to cart\",\n            response: { product_ids: args.products.map(p => p.product_id) }\n          }\n        });\n        break;\n\n      case \"clear_cart\":\n        setShoppingCart([]);\n        setToolResponse({\n          id,\n          output: {\n            success: true,\n            action: \"clear_cart\",\n            message: \"Cart has been cleared\",\n            response: {}\n          }\n        });\n        break;\n\n      default:\n        setToolResponse({\n          id,\n          output: {\n            success: false,\n            error: `Unknown tool: ${name}`\n          }\n        });\n    }\n  };\n\n  return (\n    <EmbeddedAgent\n      identifier=\"YOUR_IDENTIFIER\"\n      minimized={minimized}\n      onMinimizedChange={() => setMinimized(!minimized)}\n      browserToolsRegistration={[\n        {\n          scope: \"agent\",\n          title: \"show_product\",\n          description: \"Display a single product page for the user to view. Use when the user wants to see details of a specific product.\",\n          type: \"object\",\n          properties: {\n            product_id: {\n              title: \"Product ID\",\n              description: \"The unique identifier of the product to display\",\n              type: \"string\"\n            }\n          },\n          required: [\"product_id\"]\n        },\n        {\n          scope: \"agent\",\n          title: \"list_products\",\n          description: \"Display multiple products as a list for the user to browse. Use when showing product recommendations or search results.\",\n          type: \"object\",\n          properties: {\n            product_ids: {\n              title: \"Product IDs\",\n              description: \"Array of product identifiers to display\",\n              type: \"array\",\n              items: { type: \"string\" },\n              minItems: 2\n            },\n            description: {\n              title: \"List Description\",\n              description: \"A short title describing the product list (e.g., 'Recommended TVs')\",\n              type: \"string\"\n            },\n            reasoning: {\n              title: \"Selection Reasoning\",\n              description: \"Explanation of why these products were selected for the user\",\n              type: \"string\"\n            }\n          },\n          required: [\"product_ids\", \"description\", \"reasoning\"]\n        },\n        {\n          scope: \"agent\",\n          title: \"compare_products\",\n          description: \"Display a side-by-side comparison of 2-20 products. Use when the user explicitly requests a product comparison.\",\n          type: \"object\",\n          properties: {\n            product_ids: {\n              title: \"Product IDs\",\n              description: \"Array of product identifiers to compare\",\n              type: \"array\",\n              items: { type: \"string\" },\n              minItems: 2,\n              maxItems: 20\n            }\n          },\n          required: [\"product_ids\"]\n        },\n        {\n          scope: \"agent\",\n          title: \"search_products\",\n          description: \"Navigate to search results page for the given query.\",\n          type: \"object\",\n          properties: {\n            query: {\n              title: \"Search Query\",\n              description: \"The search term to look for\",\n              type: \"string\"\n            }\n          },\n          required: [\"query\"]\n        },\n        {\n          scope: \"agent\",\n          title: \"add_to_cart\",\n          description: \"Add products to the shopping cart. Use when the user wants to purchase or add items to their cart.\",\n          type: \"object\",\n          properties: {\n            products: {\n              title: \"Products\",\n              description: \"Array of products to add to cart\",\n              type: \"array\",\n              items: {\n                type: \"object\",\n                properties: {\n                  product_id: {\n                    title: \"Product ID\",\n                    description: \"The unique identifier of the product\",\n                    type: \"string\"\n                  },\n                  quantity: {\n                    title: \"Quantity\",\n                    description: \"Number of items to add (use 0 to remove)\",\n                    type: \"number\",\n                    minimum: 0,\n                    default: 1\n                  }\n                },\n                required: [\"product_id\", \"quantity\"]\n              }\n            }\n          },\n          required: [\"products\"]\n        },\n        {\n          scope: \"agent\",\n          title: \"clear_cart\",\n          description: \"Remove all items from the shopping cart. Only use with explicit user permission.\",\n          type: \"object\",\n          properties: {},\n          required: []\n        }\n      ]}\n      onBrowserToolCall={handleBrowserToolCall}\n      browserToolCallResponse={toolResponse}\n    />\n  );\n};\n```\n\n### Browser Tools with Headless Agent\n\nWith the headless agent, browser tools are configured via `AgentProvider` props and handled using `useAgentSend()`:\n\n```tsx\nimport { AgentProvider, useAgent, useAgentSend } from \"@smartdatahq/embedded-agent-headless\";\nimport type { BrowserToolCallData, AskQuestionArgs, AskQuestionAnswer } from \"@smartdatahq/embedded-agent-headless\";\n\nfunction ToolAwareChat() {\n  const { messages, sendMessage, isBotThinking, isConnected } = useAgent();\n  const { respondToBrowserToolCall } = useAgentSend();\n\n  // The onBrowserToolCall callback is set on AgentProvider config,\n  // so handle it there. Use respondToBrowserToolCall to send results back.\n\n  return (\n    <div>\n      {messages.map((msg, i) => (\n        <div key={i}>{msg.message}</div>\n      ))}\n      {/* ... your UI */}\n    </div>\n  );\n}\n\nfunction App() {\n  const [shoppingCart, setShoppingCart] = useState([]);\n\n  return (\n    <AgentProvider\n      config={{\n        identifier: \"YOUR_IDENTIFIER\",\n        browserTools: [\n          {\n            scope: \"agent\",\n            title: \"add_to_cart\",\n            description: \"Add a product to the shopping cart\",\n            type: \"object\",\n            properties: {\n              product_sku: { type: \"string\", description: \"Product SKU\" },\n              quantity: { type: \"integer\", minimum: 1, default: 1 },\n            },\n            required: [\"product_sku\"],\n          },\n        ],\n        onBrowserToolCall: (data) => {\n          if (data.name === \"add_to_cart\") {\n            setShoppingCart((prev) => [\n              ...prev,\n              { sku: data.args.product_sku, qty: data.args.quantity || 1 },\n            ]);\n            // Respond to the agent from inside a component using respondToBrowserToolCall,\n            // or handle it here with any state management approach.\n          }\n        },\n      }}\n    >\n      <ToolAwareChat />\n    </AgentProvider>\n  );\n}\n```\n\n### Handling Internal Tool Calls (ask_question)\n\nThe agent may invoke an internal `ask_question` tool to present the user with questions and options. If you are using the **Embedded Agent** (pre-built UI), this is handled automatically — no extra work needed. This section only applies if you are using the **Headless Agent** and `ask_question` has been activated for your agent. In headless mode, you handle it via the `onBrowserToolCall` callback and render your own UI.\n\nYou receive all questions upfront, present them however you like, and send one `respondToBrowserToolCall()` when all answers are collected. The headless engine automatically adds the questions and answers to chat history — you don't need to manage messages yourself.\n\n**Tool call data shape:**\n\n```ts\n{\n  name: \"ask_question\",\n  type: \"tool_call\",\n  id: \"call_abc123\",          // Use this as the response ID\n  args: {\n    questions: [\n      {\n        id: \"contact_methods\",\n        title: \"How can we reach you?\",\n        selectionMode: \"multiple\", // optional — defaults to \"single\"\n        minSelections: 1,            // optional — defaults to 1 for multi-select\n        maxSelections: 2,              // optional — defaults to all options\n        options: [\n          { id: \"email\", label: \"Email\" },\n          { id: \"phone\", label: \"Phone\" },\n          { id: \"sms\", label: \"SMS\" },\n        ],\n      },\n      {\n        id: \"best_time\",\n        title: \"What time works best for you?\",\n        options: [\n          { id: \"morning\", label: \"Morning\" },\n          { id: \"afternoon\", label: \"Afternoon\" },\n          { id: \"evening\", label: \"Evening\" },\n        ],\n      },\n    ],\n  },\n}\n```\n\nEach question supports:\n\n- **`selectionMode`**: `\"single\"` (default) or `\"multiple\"`.\n- **`minSelections` / `maxSelections`**: Only apply when `selectionMode` is `\"multiple\"`.\n\n**Response shape** (always send via `respondToBrowserToolCall`):\n\n```ts\ntype AskQuestionToolOutput = {\n  answers: AskQuestionAnswer[];\n};\n\ntype AskQuestionAnswer = {\n  questionId: string;\n  question: string;\n  selectedOptions: Array<{ id: string; label: string }>;\n  // Single-select: selectedOptions.length === 1\n  // Multi-select: selectedOptions.length >= minSelections\n};\n```\n\n**Example:**\n\n```tsx\nimport { AgentProvider, useAgent, useAgentSend } from \"@smartdatahq/embedded-agent-headless\";\nimport type {\n  BrowserToolCallData,\n  AskQuestionAnswer,\n  AskQuestionToolOutput,\n} from \"@smartdatahq/embedded-agent-headless\";\n\nfunction App() {\n  const [pendingQuestions, setPendingQuestions] = useState<BrowserToolCallData | null>(null);\n\n  return (\n    <AgentProvider\n      config={{\n        identifier: \"YOUR_IDENTIFIER\",\n        onBrowserToolCall: (data: BrowserToolCallData) => {\n          if (data.name === \"ask_question\") {\n            // Store questions to render in your UI\n            setPendingQuestions(data);\n          }\n        },\n      }}\n    >\n      <MyChatUI\n        pendingQuestions={pendingQuestions}\n        onQuestionsAnswered={() => setPendingQuestions(null)}\n      />\n    </AgentProvider>\n  );\n}\n\nfunction MyChatUI({ pendingQuestions, onQuestionsAnswered }) {\n  const { messages } = useAgent();\n  const { respondToBrowserToolCall } = useAgentSend();\n\n  const handleSubmitAnswers = (answers: AskQuestionAnswer[]) => {\n    const output: AskQuestionToolOutput = { answers };\n\n    // Send the response — chat history is updated automatically\n    respondToBrowserToolCall({\n      id: pendingQuestions.id,\n      output,\n    });\n    onQuestionsAnswered();\n  };\n\n  return (\n    <div>\n      {messages.map((msg, i) => (\n        <div key={i}>{msg.message}</div>\n      ))}\n      {pendingQuestions && (\n        <MyQuestionForm\n          questions={pendingQuestions.args.questions}\n          onComplete={handleSubmitAnswers}\n        />\n      )}\n    </div>\n  );\n}\n```\n\n**Example `MyQuestionForm` component:**\n\nThe component below steps through each question one at a time. Single-select questions submit on click; multi-select questions let the user toggle options and confirm with a Continue button. It calls `onComplete` with the full `answers` array once the last question is answered:\n\n```tsx\nimport { useEffect, useState } from \"react\";\nimport type { AskQuestionAnswer, AskQuestionItem } from \"@smartdatahq/embedded-agent-headless\";\n\nfunction MyQuestionForm({\n  questions,\n  onComplete,\n}: {\n  questions: AskQuestionItem[];\n  onComplete: (answers: AskQuestionAnswer[]) => void;\n}) {\n  const [currentIndex, setCurrentIndex] = useState(0);\n  const [collectedAnswers, setCollectedAnswers] = useState<AskQuestionAnswer[]>([]);\n  const [selectedIds, setSelectedIds] = useState<Set<string>>(() => new Set());\n\n  const current = questions[currentIndex];\n  const isMultiple = current.selectionMode === \"multiple\";\n  const minSelections = current.minSelections ?? 1;\n  const maxSelections = current.maxSelections ?? current.options.length;\n\n  useEffect(() => {\n    setSelectedIds(new Set());\n  }, [currentIndex]);\n\n  const submitAnswer = (selectedOptions: { id: string; label: string }[]) => {\n    const answer: AskQuestionAnswer = {\n      questionId: current.id ?? `question-${currentIndex + 1}`,\n      question: current.title,\n      selectedOptions,\n    };\n    const updatedAnswers = [...collectedAnswers, answer];\n\n    if (currentIndex + 1 < questions.length) {\n      setCollectedAnswers(updatedAnswers);\n      setCurrentIndex((i) => i + 1);\n      return;\n    }\n\n    onComplete(updatedAnswers);\n  };\n\n  const toggleOption = (option: { id: string; label: string }) => {\n    setSelectedIds((currentIds) => {\n      const next = new Set(currentIds);\n      if (next.has(option.id)) {\n        next.delete(option.id);\n        return next;\n      }\n      if (next.size >= maxSelections) {\n        return currentIds;\n      }\n      next.add(option.id);\n      return next;\n    });\n  };\n\n  const submitMultiple = () => {\n    const selectedOptions = current.options.filter((option) =>\n      selectedIds.has(option.id),\n    );\n    if (selectedOptions.length < minSelections) return;\n    submitAnswer(selectedOptions);\n  };\n\n  return (\n    <div style={{ padding: 12, background: \"#f5f5f5\", borderRadius: 8 }}>\n      <p style={{ fontWeight: 600, marginBottom: 8 }}>\n        {current.title}\n        {questions.length > 1 && (\n          <span style={{ fontWeight: 400, fontSize: 12, color: \"#666\", marginLeft: 6 }}>\n            ({currentIndex + 1}/{questions.length})\n          </span>\n        )}\n      </p>\n      <div style={{ display: \"flex\", flexDirection: \"column\", gap: 4 }}>\n        {current.options.map((opt) => (\n          <button\n            key={opt.id}\n            onClick={() =>\n              isMultiple ? toggleOption(opt) : submitAnswer([opt])\n            }\n            style={{\n              padding: \"6px 12px\",\n              borderRadius: 6,\n              border: `1px solid ${selectedIds.has(opt.id) ? \"#15803d\" : \"#007bff\"}`,\n              background: selectedIds.has(opt.id) ? \"#ecfdf3\" : \"white\",\n              color: selectedIds.has(opt.id) ? \"#15803d\" : \"#007bff\",\n              cursor: \"pointer\",\n              textAlign: \"left\",\n            }}\n          >\n            {opt.label}\n          </button>\n        ))}\n      </div>\n      {isMultiple && (\n        <button\n          onClick={submitMultiple}\n          disabled={selectedIds.size < minSelections}\n          style={{ marginTop: 8, padding: \"6px 12px\" }}\n        >\n          Continue\n        </button>\n      )}\n    </div>\n  );\n}\n```\n\n> **Note:** If you are using the Embedded Agent (pre-built UI), `ask_question` is rendered automatically — you do not need to implement any of the above.\n\n### Tool Schema Format\n\nBrowser tools use [JSON Schema](https://json-schema.org/docs) format for defining parameters. Each tool should include:\n\n- **title**: Unique identifier for the tool\n- **scope**: Either \"agent\" or \"conversation\". This registers the tool for either the current conversation or globally for the agent.\n- **description**: Clear description of what the tool does and when to call it. Describe under what conditions the AI should use the tool and explain the goal of calling the tool. For example, if it's for adding a product to the cart, then explain that it should be called once the user has confirmed that he wishes to buy a product.\n- **type**: Should be \"object\" for complex tools\n- **properties**: Object defining all parameters\n- **required**: Array of required parameter names\n\n### Parameter Types\n\nYou can use various [JSON Schema](https://json-schema.org/docs) types and constraints:\n\n```typescript\n// String with enum constraints\n{\n  type: \"string\",\n  enum: [\"option1\", \"option2\", \"option3\"],\n  description: \"Choose from predefined options\"\n}\n\n// Number with range constraints\n{\n  type: \"number\",\n  minimum: 0,\n  maximum: 100,\n  description: \"Value between 0 and 100\"\n}\n\n// Complex nested objects\n{\n  type: \"object\",\n  properties: {\n    nested_field: {\n      type: \"string\",\n      description: \"Nested parameter\"\n    }\n  },\n  required: [\"nested_field\"]\n}\n\n// Arrays with item constraints\n{\n  type: \"array\",\n  items: {\n    type: \"string\",\n    enum: [\"item1\", \"item2\"]\n  },\n  description: \"Array of predefined items\"\n}\n```\n\n### Error Handling\n\nAlways include error handling in your tool call handler:\n\n```typescript\nconst handleBrowserToolCall = (data) => {\n  try {\n    // Your tool logic here\n    setToolResponse({\n      id: data.id,\n      output: { success: true, result: \"...\" },\n    });\n  } catch (error) {\n    setToolResponse({\n      id: data.id,\n      output: {\n        success: false,\n        error: error.message,\n      },\n    });\n  }\n};\n```\n\n### Best Practices\n\n1. **Clear Descriptions**: Provide clear, detailed descriptions for tools and parameters\n2. **Validation**: Use [JSON Schema](https://json-schema.org/docs) constraints to validate inputs\n3. **Error Handling**: Always handle errors gracefully\n4. **Response Format**: Maintain consistent response format with success/error indicators\n5. **Async Operations**: Handle asynchronous operations properly\n6. **State Management**: Update your application state based on tool results\n\n---\n\n## Checkout Integration (Headless)\n\nWhen the agent decides the user is ready to pay, it emits a `checkout_initiated` signal carrying an Adyen session payload. The **Embedded Agent** renders the payment UI for you — no extra wiring needed. With the **Headless Agent** you own the UI, so you receive the signal via the `onCheckoutInitiated` callback and ship the outcome back via `respondToCheckout` from `useAgentSend()`.\n\n### Checkout Flow\n\n1. **Signal in**: `onCheckoutInitiated(config)` fires on `AgentProvider`. The `config` contains the Adyen `clientKey`, `sessionId`, `sessionData`, and `environment`.\n2. **Render**: Mount your payment UI (Adyen Drop-in or any compatible flow) using that config.\n3. **Signal out**: When the payment finishes, call `respondToCheckout({ status: \"completed\" | \"failed\", resultCode })` so the agent can continue the conversation accordingly.\n\n```ts\nimport type { CheckoutConfig, CheckoutResult } from \"@smartdatahq/embedded-agent-headless\";\n\n// CheckoutConfig — what you receive\n{\n  clientKey: string;\n  sessionId: string;\n  sessionData: string;\n  environment: \"test\" | \"live\" | \"live-us\" | \"live-au\" | \"live-apse\" | \"live-in\" | (string & {});\n}\n\n// CheckoutResult — what you send back\n{ status: \"completed\"; resultCode: string } | { status: \"failed\"; resultCode: string }\n```\n\n### Adyen Drop-in Example\n\n```tsx\nimport { useEffect, useRef, useState } from \"react\";\nimport {\n  AgentProvider,\n  useAgent,\n  useAgentSend,\n} from \"@smartdatahq/embedded-agent-headless\";\nimport type { CheckoutConfig } from \"@smartdatahq/embedded-agent-headless\";\nimport { AdyenCheckout, Dropin, Card } from \"@adyen/adyen-web\";\nimport \"@adyen/adyen-web/dist/es/adyen.css\";\n\nfunction CheckoutSurface({ config }: { config: CheckoutConfig }) {\n  const containerRef = useRef<HTMLDivElement>(null);\n  const { respondToCheckout } = useAgentSend();\n\n  useEffect(() => {\n    if (!containerRef.current) return;\n    let dropin: InstanceType<typeof Dropin> | null = null;\n\n    (async () => {\n      const checkout = await AdyenCheckout({\n        environment: config.environment,\n        clientKey: config.clientKey,\n        session: { id: config.sessionId, sessionData: config.sessionData },\n        onPaymentCompleted: (result) => {\n          respondToCheckout({ status: \"completed\", resultCode: result.resultCode });\n        },\n        onPaymentFailed: (result) => {\n          respondToCheckout({ status: \"failed\", resultCode: result?.resultCode ?? \"ERROR\" });\n        },\n      });\n      dropin = new Dropin(checkout, { paymentMethodComponents: [Card] }).mount(\n        containerRef.current!,\n      );\n    })();\n\n    return () => {\n      dropin?.unmount();\n    };\n  }, [config, respondToCheckout]);\n\n  return <div ref={containerRef} />;\n}\n\nfunction ChatWithCheckout({\n  checkoutConfig,\n  onClose,\n}: {\n  checkoutConfig: CheckoutConfig | null;\n  onClose: () => void;\n}) {\n  const { messages } = useAgent();\n\n  return (\n    <>\n      {messages.map((msg, i) => (\n        <div key={i}>{msg.message}</div>\n      ))}\n      {checkoutConfig && (\n        <Modal onClose={onClose}>\n          <CheckoutSurface config={checkoutConfig} />\n        </Modal>\n      )}\n    </>\n  );\n}\n\nfunction App() {\n  const [checkoutConfig, setCheckoutConfig] = useState<CheckoutConfig | null>(null);\n\n  return (\n    <AgentProvider\n      config={{\n        identifier: \"YOUR_IDENTIFIER\",\n        onCheckoutInitiated: (config) => setCheckoutConfig(config),\n      }}\n    >\n      <ChatWithCheckout\n        checkoutConfig={checkoutConfig}\n        onClose={() => setCheckoutConfig(null)}\n      />\n    </AgentProvider>\n  );\n}\n```\n\n> **Note:** `respondToCheckout` must be called from inside an `<AgentProvider>` subtree (it's exposed via `useAgentSend()`). If your payment surface lives outside the provider, lift the `onCheckoutInitiated` payload into shared state and render the payment component as a child of `AgentProvider`.\n\n---\n\n## API Reference\n\n### EmbeddedAgent Props\n\n##### identifier (Required)\n\n    type: string\n    Description: Unique identifier for connecting to the embedded agent server.\n\n##### Browser Tools Properties\n\n**browserToolsRegistration**\n\n    Type: Array<{ scope: \"agent\" | \"conversation\"; [key: string]: any; }>\n    Description: Array of tool definitions using JSON Schema format. Each tool defines parameters and constraints for browser-based actions the agent can perform.\n\n**onBrowserToolCall**\n\n    Type: (data: { name: string; type: string; id: string; args?: Record<string, any>; [key: string]: any; }) => void\n    Description: Callback function triggered when the agent wants to execute a browser tool. Handle the tool execution and update browserToolCallResponse with the result.\n\n**browserToolCallResponse**\n\n    Type: { id: string; output: any; } | undefined\n    Description: Response object containing the result of a browser tool execution. The id should match the tool call request id, and output contains the execution result.\n\n##### Additional Props\n\n**className**: Custom class for styling the embedded agent container.\\\n**minimized**: Default minimized state of the embedded agent. If being used, you need to update it to match the value you get from the onMinimizedChange function.\\\n**onMinimizedChange**: Callback for changes in the minimized state.\\\n**onUltraMinimize**: Optional callback function triggered when the ultra minimize action is performed (minus icon clicked). This allows you to implement custom behavior for collapsing the agent to a minimal one-line state, such as completely hiding the widget or storing the state. Example: `onUltraMinimize={() => { console.log(\"Ultra minimize triggered!\"); setIsRendered(false); }}`.\\\n**conversationId**: Unique conversation ID for the session. This is generated internally if not provided. It should preferably be a UUID string.\\\n**isRendered**: boolean. You can set this to false if you don't want the agent to show on render. Instead, we will display a message that can be clicked to load the agent. This is false by default. If set to true, the agent is displayed instead of the message prompt.\\\n**onChatbotRender**: This function is called when the agent is rendered. It only runs if you set render to false and manually click the message that displays in place of the agent.\\\n**onNewConversation**: Callback invoked when a new conversation is started, either from the menu or after an inactivity timeout. `() => void`.\\\n**onBeforeAgentClosed**: Callback invoked right before the embedded agent closes. Return `false` to prevent closing (useful when navigating away immediately). `() => boolean | void`.\\\n**onAgentClosed**: Callback invoked after the embedded agent is closed. `() => void`.\\\n**onError**: Callback for handling errors.\\\n**onResponseStreamed**: Callback invoked when the assistant finishes streaming a response. `() => void`.\\\n**onResponseStreamStart**: Callback invoked when the assistant starts streaming a response. `() => void`.\\\n**language**: The language of the agent. This can be used to change the language of the agent. It must be a valid ISO 639-1 code with a\ncountry code. For example, \"en-US\", \"en-GB\", \"fr-FR\", \"fr-CA\", \"es-ES\", \"de-DE\", \"it-IT\", \"ja-JP\", \"ko-KR\", \"pt-BR\". This must be a valid\nlanguage available in our agent conversation interface. If not provided, the language will be set to the configured language of the agent\nand can be changed by the user in the conversation interface.\\\n**inactiveComponent**: The component to display when the agent is inactive (not rendered).\\\n**inactiveText**: The text to display when the agent is inactive (not rendered). This is useful for overwriting the configured message shown to users before they interact with the agent.\\\n**showInPopup**: This boolean determines whether the agent is shown as a popup on the page or embedded directly in the content. When true, the agent will appear in a floating popup window that can be moved around the page.\\\n**processingIcon**: Optional JSX element to customize the loading indicator shown while the agent is processing responses.\\\n**offset**: Optional object to determine the left, right, top and bottom offset of the agent when it's a popup.\\\n**mobileOffset**: Optional object to determine the left, right, top and bottom offset of the agent when it's a popup on mobile or tablet devices (screens with max-width: 1024px). This allows for different positioning on mobile devices compared to desktop. When not provided, falls back to the offset prop values.\\\n**resizeable**: Optional boolean that enables resizing functionality for the chat window. When true, the height of the window can be resized using the line at the mid-top of the header. When false, the window maintains a fixed size. Note that resizing is only available when the window is not minimized.\\\n**height**: Optional number that sets the initial height of the chat window in pixels. If not provided, defaults to 600.\\\n**mobileHeight**: Optional number that sets the initial height of the chat window in pixels on mobile devices. If not provided, defaults to 300.\\\n**width**: Optional number that sets the initial width of the chat window in pixels. If not provided, defaults to 500.\\\n**devMode**: Optional boolean that allows us to enable devMode features.\n\n### AgentProvider Props (AgentConfig)\n\nThese props are passed via the `config` prop on `<AgentProvider>`:\n\n| Prop | Type | Required | Description |\n|------|------|----------|-------------|\n| `identifier` | `string` | Yes | The identifier of the agent. Required to connect to the server. |\n| `conversationId` | `string` | No | Optional conversation ID. Auto-generated UUID if omitted. |\n| `language` | `string` | No | Language code (ISO 639-1 with country, e.g. \"en-US\"). |\n| `browserTools` | `Array<{ scope: \"agent\" \\| \"conversation\"; ... }>` | No | Browser tools to register with the agent. |\n| `onError` | `(error: string) => void` | No | Called when an error occurs during agent processing. |\n| `onBrowserToolCall` | `(data: BrowserToolCallData) => void` | No | Called when a browser tool call is made by the agent. Also receives internal browser tools like `ask_question` in headless mode — see [Handling Internal Tool Calls](#handling-internal-tool-calls-ask_question). |\n| `onToolCall` | `(data: { toolName: string; conversationId: string }) => void` | No | Called when an internal tool is invoked. Useful for analytics. |\n| `onUserMessage` | `(data: { conversationId: string }) => void` | No | Called when a user message is sent. Useful for analytics. |\n| `onCheckoutInitiated` | `(config: CheckoutConfig) => void` | No | Called when the agent initiates a checkout flow. Render your own payment UI and reply via `respondToCheckout` — see [Checkout Integration](#checkout-integration-headless). |\n| `onResponseStreamStart` | `() => void` | No | Called when the assistant starts streaming a response. |\n| `onResponseStreamed` | `() => void` | No | Called when the assistant finishes streaming a response. |\n| `onNewConversation` | `() => void` | No | Called when a new conversation is started. |\n| `onNotify` | `NotifyFn` | No | Custom notification handler. Falls back to console logging. |\n| `shouldConnect` | `boolean` | No | Controls whether the agent opens its WebSocket connection. Defaults to `true`. Set to `false` to defer connecting (e.g. while gating on auth, feature flags, or a user gesture); flip back to `true` to connect. Messages sent while disconnected are queued and flushed on connect. |\n| `useFraios` | `boolean` | No | Routes requests to the Fraios-hosted agent: the `isFraios` flag is forwarded on agent-config, WebSocket, and file-upload requests. Defaults to `true`. Set to `false` when the agent is not hosted in Fraios. |\n\n### Headless Hooks\n\n| Hook | Returns | Description |\n|------|---------|-------------|\n| `useAgent()` | All fields below combined | Convenience hook composing all primitives. |\n| `useAgentConnection()` | `{ isConnected, reconnect }` | WebSocket connection state and reconnect action. |\n| `useAgentMessages()` | `{ messages, isBotThinking, isStreaming, botActivity }` | Read-only message and streaming state. |\n| `useAgentSend()` | `{ sendMessage, sendReply, sendFeedback, sendMessageFeedback, respondToBrowserToolCall, respondToCheckout }` | Actions for sending messages, replies, the survey, per-message thumbs feedback, tool responses, and checkout outcomes. |\n| `useAgentConversation()` | `{ conversationId, startNewConversation, deleteConversation, downloadChatHistory, getChatUrl }` | Conversation lifecycle management. |\n| `useAgentAudio()` | `{ isVoiceActive, activateVoice, deactivateVoice } \\| null` | Audio/voice input controls. `null` if unavailable. |\n| `useAgentConfig()` | `{ agentConfig, configLoading, configError }` | Remote agent configuration and loading state. |\n\n### Utility Functions\n\n##### getConversationHistory()\n\n    Type: () => IChatMessage[]\n    Description: Returns an array of all messages from the current conversation history. This function provides access to the complete conversation including messages from users, the bot, and human agents.\n\n    Example:\n    ```typescript\n    import { EmbeddedAgent, getConversationHistory } from '@smartdatahq/embedded-agent';\n\n    // In your component or function\n    const conversationHistory = getConversationHistory();\n    console.log('Conversation history:', conversationHistory);\n\n    // Each message object contains:\n    // - message: string (the message content)\n    // - time: string (timestamp)\n    // - user: \"user\" | \"bot\" | \"humanAgent\" (sender type)\n    // - replyTo?: string (optional reply reference)\n    // - thumbsUp?: boolean (optional feedback)\n\n    // You can filter by message type if needed:\n    const userMessages = conversationHistory.filter(msg => msg.user === \"user\");\n    const botMessages = conversationHistory.filter(msg => msg.user === \"bot\");\n    const humanAgentMessages = conversationHistory.filter(msg => msg.user === \"humanAgent\");\n    ```\n\n    Note: This function accesses the global conversation store, so it will return messages from the currently active conversation session.\n","readmeFilename":"README.md"}