Implement AI-Powered Search in Codebase Visualizer Dashboard

[kleneway]

Feature Request

Description

Enhance the Codebase Visualizer dashboard by adding an AI-powered search feature. This search will allow users to describe a file, and the system will intelligently locate it by analyzing the entire codebase context. The goal is to improve navigation and file discovery within the dashboard, leveraging advanced AI capabilities for a smarter user experience.

Requirements

• Search Box Integration

  • Place the search box at the top of the Codebase Visualizer in the dashboard.
  • Ensure the search component is easily accessible and prominently displayed.

• AI-Powered Search Functionality

  • Use the Llama3.1 70b model in conjunction with Cerebras to process search queries.
  • The AI should return the top ten files that most closely match the user's description.
  • Write a smart search prompt that passes the filepaths and overviews from the context of the entire codebase, along with a prompt that explains the goal of getting back the ten most relevant files.

• Backend Implementation

  • Utilize the codebase-context TRPC router to handle search queries and interact with the AI model.
  • Ensure efficient query processing to maintain responsiveness.

• Frontend Enhancements

  • Develop a separate search query component that integrates seamlessly with the existing component context.
  • Use Framer Motion for smooth animations to enhance user experience.
  • Incorporate loading states to inform users while the search is in progress.
  • Support both light and dark modes to align with user preferences and existing dashboard themes.

• Selection Handling

  • When a user selects a file from the search results, update the Codebase Visualizer to highlight and focus on the selected file.
  • Use the full standardized file path format to maintain consistency across the platform.

Acceptance Criteria

• Users can enter descriptive text into the search box and receive relevant file suggestions within 2 seconds.
• The search feature accurately identifies and displays the top ten matching files based on the user's description.
• The search box and results are fully responsive and display correctly in both light and dark modes.
• Selecting a file from the search results updates the Codebase Visualizer accordingly without errors.
• Smooth animations are implemented using Framer Motion, enhancing the overall user experience.

Additional Information

• Dependencies: Ensure compatibility with the existing Codebase Visualizer components and the TRPC router setup.
• Performance: Optimize AI model integration to prevent lag or slowdowns in the dashboard.
• User Experience: Prioritize intuitive design and seamless interactions to encourage user adoption of the new search feature.

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@jacob-ai-bot

[jacob-local-kevin[bot]]

JACoB here...

You mentioned me on this issue and I am busy taking a look at it.

I'll continue to comment on this issue with status as I make progress.

[jacob-local-kevin[bot]]

Update

I've completed my initial work on this issue and have created a pull request: JACoB PR for Issue Implement AI-Powered Search in Codebase Visualizer Dashboard.

The changes currently result in an error, so I'll be making some additional changes before it is ready to merge.