ChatBubble

Data Display

Conversational message bubble with sender alignment, avatar integration, timestamp display, and delivery status indicators

ChatBubble Component

Conversation UI blocks for chat interfaces, support tools, and collaboration surfaces.

Basic Usage

Render a single incoming message with sender and timestamp.

A
Alex
Hi! Can you help me with my billing issue?
10:22 AM
S
Support Agent
Sure, I can help. Can you share your invoice number?
10:23 AM

Implementation Notes

Keep setup minimal so teams can adopt the component quickly.

  • - Start with clear sender identity and timestamp.
  • - Keep incoming message width readable on mobile screens.
  • - Avoid mixing status indicators in basic examples.

Normal Usage

Show outgoing messages with delivery state.

U
Sure - I have checked your account and fixed it.
10:24 AM

Implementation Notes

This pattern maps to everyday support chats and collaboration workflows.

  • - Use `isMe` to make ownership obvious at a glance.
  • - Pair sent messages with status for delivery confidence.
  • - Keep language short to avoid visual clutter.

Advanced Usage

Use variants and status transitions for richer chat feedback.

U
Syncing your workspace...
Now
U
Done. Your settings were updated.
Now
A
Assistant
Would you like me to apply this to all team spaces?
Now

Implementation Notes

Advanced mode should compose cleanly with app state and callbacks.

  • - Reserve color variants for meaningful conversation states.
  • - Keep status progression deterministic for reliability.
  • - Test long messages and wrapping edge cases.

Real-Life Use Cases

Great for support desks and in-app team messaging experiences.

O
Ops Bot
Incident #4831 has been mitigated. Monitoring ongoing.
11:03 AM
U
Acknowledged. I will notify the customer.
11:04 AM
T
Team Lead
Please include the mitigation timeline in the update.
11:05 AM
U
Timeline added. Customer and leadership channels notified.
11:06 AM

Implementation Notes

Show how the component fits real workflows, not isolated UI demos.

  • - Model both bot and human messages in support timelines.
  • - Keep time context visible for operational accountability.
  • - Include realistic escalation and follow-up messages.

View on GitHub

See the full source code on GitHub