I'll help you create a frontend component for reviewing conversations based on your PRD. This will be a mix of project management features like todos and checkboxes to track conversation reviews.

Let's create a conversation review component that allows you to track and manage reviews of bot conversations.

Features Implemented

This conversation review component includes:

1. Dashboard Overview:

   • Statistics showing review status, upvotes, downvotes, and neutral ratings
   • Percentage calculations for quick insights

2. Filtering and Search:

   • Filter by review status (All, Not Reviewed, Reviewed, Needs New Review)
   • Search by interaction ID, account ID, or channel ID

3. Interaction Cards:

   • Expandable cards showing conversation details
   • Status badges indicating review state
   • Message history display
   • Category tags

4. Review Functionality:

   • Vote system (up, down, neutral)
   • Category selection with checkboxes
   • Asana task linking
   • Reviewer ID tracking
   • Timestamp recording

5. Responsive Design:

   • Works well on mobile, tablet, and desktop screens
   • Adapts layout based on screen size
   • Collapsible sections to manage information density

6. Status Tracking:

   • Clear visual indicators for review status
   • Automatic status updates when reviews are saved
   • Tracking of new messages that require additional review

7. Data Storage:

   • Structured to match your JSON format requirements
   • Ready to connect to your database backend
   • Includes all required fields from your PRD

How to Use

1. Viewing Conversations:

   • The main dashboard shows statistics and all conversations
   • Use the tabs to filter by review status
   • Use the search box to find specific conversations

2. Reviewing a Conversation:

   • Click "Review" on any conversation card
   • Select appropriate categories using checkboxes
   • Vote on the quality of the interaction (up, down, neutral)
   • Add an Asana link if needed
   • Enter your reviewer ID
   • Click "Save Review" to complete

3. Editing Reviews:

   • For already reviewed conversations, click "Edit Review"
   • Make your changes and save again

Next Steps

To fully implement this in your environment, you would need to:

1. Connect to your database to store and retrieve the interaction data
2. Integrate with Sendbird to pull conversation data
3. Set up authentication for reviewers
4. Implement API endpoints for saving reviews
5. Add more detailed analytics if needed

Would you like me to explain any specific part of the implementation in more detail?

I'll add a comment section to the review form so reviewers can add notes about the conversation.

I've added a comment section to the review form. Now reviewers can add detailed notes about each conversation they review. Here's what I've implemented:

1. Updated Data Model:

   • Added a comment field to the Interaction interface
   • Added sample comments to the mock data to demonstrate how it works

2. Comment Input in Review Form:

   • Added a textarea for entering comments when reviewing a conversation
   • The textarea provides ample space for detailed notes
   • Placeholder text guides reviewers on what to include

3. Comment Display:

   • When a comment exists, it's displayed in a formatted box when viewing the interaction
   • Comments maintain their formatting with whitespace preserved
   • The comment section only appears if a comment has been added

This feature allows reviewers to:

• Document specific issues or strengths in the bot's responses
• Provide context for their vote (up/down/neutral)
• Add notes for other team members who might review the conversation later
• Include action items or suggestions for improvement

The comment field is optional, so reviewers can choose whether to add detailed notes or just provide a basic review with categories and a vote.

Would you like me to make any adjustments to the comment section, such as changing the placement, adding character limits, or including any specific guidance text?