Redesign this prototype using the shadcn/ui component library, based on the prototype (attached images), applying the following improvements:
Redesign as per example: Examples of priority conversations include:• When a customer explicitly requests to speak with a human agent• When a customer gives negative feedback. The AI response in these cases should be conveyed more clearly so that agents can identify and resolve them quickly.
The redesign should consider that the live chat panel should be collapsed and only expanded when necessary.
The "AI Assistant Chats" section should be merged with the "Dashboard" screen, with the Dashboard being highlighted on the screen and the chat service section being below the KPIs. KPIs should be prioritized as follows: KPI 1 - HIGHEST PRIORITY - AI performance and accuracy metrics (e.g. throughput to human agents) KPI 2 - High priority: % of issues (e.g. report of damaged camera hardware) KPI 3 - Medium priority: User feedback on AI responses (e.g. whether AI was helpful in providing support) KPI 4 - Lowest priority: Number of visits (e.g.) Note: AI performance is also closely tied to user feedback, and these data sets may need to be visually or structurally linked.
Customer Support Dashboard Redesign with shadcn/ui
I'll redesign the RAG System dashboard using shadcn/ui components, focusing on the requirements you've specified. The new design will feature a collapsible chat panel, prioritized KPIs, and better visualization of high-priority conversations.
Key Features of the Redesign
1. Integrated Dashboard with AI Assistant
I've merged the AI Assistant Chats with the Dashboard as requested, creating a unified interface where:
- The Dashboard is prominently displayed with prioritized KPIs
- The chat service is accessible through a collapsible panel in the bottom right
2. Prioritized KPIs
The KPIs are arranged in order of priority:
- Highest Priority: AI performance metrics (throughput rate, retrieval accuracy)
- High Priority: Issue reports (categorized by severity)
- Medium Priority: User feedback on AI responses
- Lowest Priority: Visit statistics
3. Collapsible Chat Panel
The live chat panel is now:
- Collapsed by default
- Expandable when needed
- Positioned in the bottom right corner to minimize screen space usage
- Includes suggested actions for common tasks
4. High-Priority Conversation Highlighting
Priority conversations are clearly highlighted:
- Negative feedback is tagged with red indicators
- Requests for human agents are prominently displayed
- A "Priority" button for urgent cases that need human attention
5. Visual Linking of AI Performance and User Feedback
The design visually connects AI performance metrics with user feedback by:
- Using consistent color coding
- Placing related metrics in proximity
- Showing trends over time for both metrics
6. Responsive Design
The interface is fully responsive and adapts to different screen sizes while maintaining functionality.
Implementation Details
- Used shadcn/ui components throughout for consistent styling
- Implemented a collapsible sidebar using the shadcn sidebar component 1
- Created custom chart components for visualizing metrics
- Used a card-based layout for clear information hierarchy
- Added visual indicators for priority conversations
Sources
Redesign this prototype using the shadcn/ui component library, based on the prototype (images attached), applying the following improvements:
- Consider increasing the visibility of the AI assistant within the interface by keeping a visible AI chat window accessible on the side, where users can see it and start a chat.
- Enable contextual visual feedback through a time-based knowledge graph. When users chat with the AI, keywords or phrases mentioned - such as “Refund” - could dynamically trigger visual highlights in the knowledge graph, such as changes in color, scale, movement, or other forms of visual emphasis to help users connect the dialogue with information nodes.
Knowledge Graph Interface with Enhanced AI Integration
I'll redesign the Knowledge Graph interface using shadcn/ui components, focusing on making the AI assistant more visible and adding contextual visual feedback through the knowledge graph.
Key Features of the Redesign
1. Persistent AI Chat Panel
I've implemented a resizable side panel that keeps the AI assistant visible at all times:
- Resizable Interface: Users can adjust the width of the chat panel to their preference
- Expandable View: The chat panel can be maximized to full screen when needed
- Contextual Suggestions: The AI suggests relevant queries based on the conversation context
2. Interactive Knowledge Graph Visualization
The knowledge graph now provides dynamic visual feedback based on chat interactions:
- Keyword Highlighting: When users mention concepts like "Refund" or "Warranty" in the chat, corresponding nodes are highlighted in the graph
- Visual Emphasis: Highlighted nodes use animations (pulsing effect), color changes, and size increases to draw attention
- Connected Relationships: When related concepts are mentioned, the connections between them are also highlighted
3. Improved User Experience
The redesign enhances the overall user experience with:
- Dark Mode Support: A dark theme optimized for knowledge graph visualization
- Responsive Layout: The interface adapts to different screen sizes
- Intuitive Navigation: Clear navigation between different sections of the application
- Interactive Elements: Zoom controls, filters, and search functionality for the knowledge graph
4. Real-time Interaction Between Chat and Graph
The integration between the chat and knowledge graph creates a seamless experience:
- Bidirectional Communication: Chat messages trigger graph highlights, and graph interactions can suggest chat topics
- Visual Learning: Users can see the relationships between concepts as they discuss them
- Contextual Understanding: The system visually maps the conversation to the knowledge structure
This redesign creates a more integrated experience where the AI assistant and knowledge graph work together to help users explore and understand information more effectively.