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AgentResponse and related components for LLM interactions","maintainers":[{"name":"optishanedev","email":"shane.whitlock@optilogic.com"},{"name":"just-zach","email":"zacurt@gmail.com"},{"name":"opti-johnny","email":"johnny.simmons@optilogic.com"}],"readme":"# @optilogic/chat\n\nChat UI components for opti-ui - Components for displaying LLM/AI agent interactions.\n\n## Installation\n\n```bash\nnpm install @optilogic/chat @optilogic/core @optilogic/editor slate slate-react slate-history\n```\n\n## Setup\n\nMake sure you have configured `@optilogic/core` with the Tailwind preset and CSS variables.\n\n## Without Tailwind\n\nAn app that does not run Tailwind imports one stylesheet, from core. It carries the tokens, the base styles and the utilities of every `@optilogic` package:\n\n```tsx\nimport \"@optilogic/core/opti-ui.css\";\n```\n\n## Usage\n\n### AgentResponse\n\nDisplay AI agent responses with thinking indicators, tool calls, and feedback actions:\n\n```tsx\nimport { AgentResponse, useAgentResponseAccumulator, type FeedbackValue } from '@optilogic/chat';\nimport { useState } from 'react';\n\nfunction ChatView({ socket }) {\n  const { state, handleMessage } = useAgentResponseAccumulator();\n  const [feedback, setFeedback] = useState<FeedbackValue>(null);\n\n  socket.onmessage = (e) => handleMessage(JSON.parse(e.data));\n\n  return (\n    <AgentResponse\n      state={state}\n      feedback={feedback}\n      onFeedbackChange={setFeedback}\n      onResponseCopy={(response) => console.log('Copied:', response)}\n    />\n  );\n}\n```\n\n#### Feedback follow-up (thumbs up/down)\n\nThe action bar always renders thumbs up/down controls, and by default a\nthumbs-**down** opens our follow-up popover (category + free-text) — this works\nout of the box with no state wiring, because vote and popover state are\n**uncontrolled by default**. To use the default, just hook up persistence:\n\n```tsx\n// Thumbs + follow-up popover work as-is; wire only what you want to store.\n<AgentResponse\n  state={state}\n  onFeedbackChange={(vote) => saveVote(vote)}\n  onFeedbackDetailsSubmit={(details) => saveFeedbackDetails(details)}\n/>\n```\n\nTurn the follow-up off with `feedbackPrompt=\"none\"`, or customize it via\n`feedbackCategories`, `feedbackPromptTitle`, etc. Take control of any piece by\npassing its controlled prop (`feedback`, `feedbackDetails`, `feedbackPromptOpen`).\nA vote records instantly and is never blocked on the follow-up. The library owns\nthe UI and accessibility; **persistence and any \"send to support\" routing stay\nwith you** via typed callbacks.\n\n```tsx\nimport {\n  AgentResponse,\n  emptyFeedbackDetails,\n  type FeedbackValue,\n  type FeedbackDetails,\n  type SupportFeedbackPayload,\n} from '@optilogic/chat';\nimport { useState } from 'react';\n\nfunction ResponseWithFeedback({ state, messageId, conversationId }) {\n  const [feedback, setFeedback] = useState<FeedbackValue>(null);\n  const [details, setDetails] = useState<FeedbackDetails>(emptyFeedbackDetails);\n\n  return (\n    <AgentResponse\n      state={state}\n      feedback={feedback}\n      onFeedbackChange={(vote) => {\n        setFeedback(vote);\n        // Attribute to your account/message/conversation and upsert (not insert)\n        // so vote changes update the same record.\n        void saveVote({ messageId, conversationId, vote });\n      }}\n      // \"down\" (default) | \"up\" | \"both\" | \"none\"\n      feedbackPrompt=\"down\"\n      feedbackPromptTitle=\"Help us improve Ada — what went wrong?\"\n      feedbackDetails={details}\n      onFeedbackDetailsChange={setDetails}\n      onFeedbackDetailsSubmit={(d) => {\n        void saveFeedbackDetails({ messageId, conversationId, ...d });\n      }}\n      // Opt-in: render a \"send to support\" checkbox. Its state is returned in\n      // FeedbackDetails.sendToSupport — you assemble + route the payload.\n      sendToSupportLabel=\"Also send this to Support\"\n    />\n  );\n}\n```\n\n`SupportFeedbackPayload` is exported as the recommended shape for routing feedback\nto a support system. The library only fills `vote`, `category`, and `comment`; the\n`context` (conversation URL, message/conversation IDs, user environment details)\nis yours to supply, since only your app knows its own routing and environment:\n\n```tsx\nfunction toSupportPayload(\n  vote: FeedbackValue,\n  details: FeedbackDetails,\n  conversationUrl: string,\n): SupportFeedbackPayload {\n  return {\n    vote,\n    category: details.category,\n    comment: details.comment,\n    context: { conversationUrl, env: collectEnvironmentDetails() },\n  };\n}\n```\n\nFeedback state is controlled-or-uncontrolled throughout: omit `feedbackDetails` /\n`feedbackPromptOpen` to let the component manage them, or pass them to take full\ncontrol. Categories default to a built-in set (`defaultFeedbackCategories`) and can\nbe replaced via `feedbackCategories`.\n\n### UserPrompt\n\nDisplay user messages in the chat:\n\n```tsx\nimport { UserPrompt } from '@optilogic/chat';\n\nfunction ChatMessage() {\n  return (\n    <UserPrompt\n      content=\"What is the weather today?\"\n      timestamp={new Date()}\n    />\n  );\n}\n```\n\nLabel a message with `tags` — e.g. to distinguish prompts routed through the MCP\nconnector from ones typed in the web UI. Tags sit bottom-right on the timestamp\nrow. They're presentational: your app decides what to tag and supplies the labels\n(each with an optional `variant`).\n\n```tsx\nimport { UserPrompt } from '@optilogic/chat';\n\n<UserPrompt\n  content=\"Load the Q4 shipment file into the Demand table.\"\n  tags={[{ label: 'MCP' }]}\n/>;\n```\n\n### UserPromptInput\n\nInput component for user messages:\n\n```tsx\nimport { UserPromptInput } from '@optilogic/chat';\n\nfunction ChatInput() {\n  return (\n    <UserPromptInput\n      onSubmit={(text) => console.log('Submitted:', text)}\n      placeholder=\"Type your message...\"\n    />\n  );\n}\n```\n\n### HITLQuestionPanel\n\nDisplay an interactive panel for human-in-the-loop clarifying questions. Replaces the input area when the agent needs user clarification:\n\n```tsx\nimport { HITLQuestionPanel, type HITLQuestion } from '@optilogic/chat';\n\nconst question: HITLQuestion = {\n  reason: \"I need clarification before proceeding with the data mapping.\",\n  questions: [\n    \"Which table should I load the shipment data into?\",\n    \"Should I overwrite existing rows or append?\",\n  ],\n  options: {\n    \"Which table should I load the shipment data into?\": [\"Customers\", \"Demand\", \"Shipments\"],\n    \"Should I overwrite existing rows or append?\": [\"Overwrite\", \"Append\"],\n  },\n  context: \"Source file has 1,200 rows with columns: origin, destination, quantity, date\",\n  timeoutSeconds: 300,\n  receivedAt: Date.now(),\n};\n\nfunction ChatInput() {\n  return (\n    <HITLQuestionPanel\n      question={question}\n      onSubmit={(response) => console.log('Response:', response)}\n      onStop={() => console.log('Agent stopped')}\n    />\n  );\n}\n```\n\n### HITLInteractionRecord\n\nDisplay a completed HITL Q&A interaction in the chat history:\n\n```tsx\nimport { HITLInteractionRecord, type HITLInteraction } from '@optilogic/chat';\n\nconst interaction: HITLInteraction = {\n  question: { /* HITLQuestion object */ },\n  response: \"Q: Which table?\\nA: Shipments\",\n  respondedAt: Date.now(),\n};\n\nfunction CompletedInteraction() {\n  return <HITLInteractionRecord interaction={interaction} />;\n}\n```\n\n### AgentResponse with HITL Interactions\n\nHITL interactions can also be displayed as a collapsible section within AgentResponse:\n\n```tsx\nimport { AgentResponse, type HITLInteraction } from '@optilogic/chat';\n\nfunction ChatView() {\n  const hitlInteractions: HITLInteraction[] = [/* completed interactions */];\n\n  return (\n    <AgentResponse\n      state={state}\n      hitlInteractions={hitlInteractions}\n      defaultHITLExpanded={false}\n    />\n  );\n}\n```\n\n### AgentResponse with Status Content\n\nDisplay ephemeral status messages in the metadata row during agent processing:\n\n```tsx\nimport { AgentResponse, TruncatedMessage } from '@optilogic/chat';\n\nfunction ChatView() {\n  const [statusMessage, setStatusMessage] = useState<string>();\n\n  // Parent controls when to show/clear status content\n  // e.g., set during processing, clear on completion\n\n  return (\n    <AgentResponse\n      state={state}\n      statusContent={\n        statusMessage\n          ? <TruncatedMessage message={statusMessage} />\n          : undefined\n      }\n    />\n  );\n}\n```\n\n### TruncatedMessage\n\nStandalone component that renders a single-line string with CSS-based truncation:\n\n```tsx\nimport { TruncatedMessage } from '@optilogic/chat';\n\n<TruncatedMessage message=\"Searching the knowledge base for relevant documents...\" />\n```\n\n## Components\n\n### AgentResponse\nMain component for displaying AI agent responses with:\n- Streaming content support\n- Thinking/reasoning indicators\n- Tool call visualization\n- Copy and feedback actions\n- Metadata display (tokens, timing)\n- Ephemeral status content slot in metadata row\n- Optional collapsible HITL interaction history\n\n### UserPrompt\nComponent for displaying user messages in the chat interface.\n\n### UserPromptInput\nInput component for composing user messages with tag support.\n\n### HITLQuestionPanel\nInteractive panel for displaying agent clarifying questions with:\n- Predefined option buttons (toggleable selection)\n- Free-form text input\n- Countdown timer with visual warning state\n- Keyboard support (Enter to submit, Shift+Enter for newlines)\n\n### HITLInteractionRecord\nRead-only display of a completed HITL Q&A interaction with:\n- Per-question inline answers\n- Context display\n- Fallback for non-structured response formats\n\n### HITLSection\nCollapsible sub-component for rendering HITL interactions within AgentResponse. Follows the same expand/collapse pattern as ThinkingSection.\n\n### TruncatedMessage\nStandalone utility component for single-line text truncation with:\n- CSS-based ellipsis truncation\n- Native title tooltip for full text on hover\n- Designed for use in MetadataRow status slot or anywhere else\n\n## Hooks\n\n### useAgentResponseAccumulator\nManages state for streaming agent responses, handling incremental updates and message accumulation.\n\n### useThinkingTimer\nTracks elapsed time during agent thinking phases.\n\n## Utilities\n\n### buildResponseString\nCombines selected options and free-form text into a single formatted string for the backend. Used internally by HITLQuestionPanel and can be used to construct responses programmatically.\n\n## License\n\nMIT\n","readmeFilename":"README.md"}