feat(ai): implement persistent Hyper AI workspace with follow-up learning sessions

[imuniqueshiv]

Pull Request

Summary

Implement the next phase of the Hyper AI Workspace by introducing persistent personal learning sessions, a canonical topic cache architecture, and a more reliable follow-up question workflow. Students can now continue learning from where they left off without requiring authentication or server-side user storage.

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Related Issue

N/A

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Type of Change

• Feature
• Bug Fix
• Documentation
• Refactor
• Performance Improvement
• CI / Build
• Other

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What Changed?

• Implemented a local session service for persistent per-topic learning sessions using browser localStorage.
• Added automatic session restoration after page refreshes and browser restarts.
• Introduced automatic session saving after explanation generation, follow-up questions, and AI responses.
• Added session expiration (30 days) and automatic cleanup with a maximum of 100 stored topic sessions.
• Implemented "Saved on this device", "Last studied", and "Continue Learning" indicators in the AI Workspace.
• Improved follow-up question workflow by resolving topic explanations server-side instead of depending on client-provided cached data.
• Added server-side fallback for explanation retrieval to improve reliability when cached data is unavailable.
• Improved AI Workspace state initialization and session restoration flow.
• Added strongly typed local learning session models.

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Screenshots (UI Changes Only)

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Testing

• Verified automatic session creation for new topics.
• Verified conversation restoration after browser refresh.
• Verified conversation restoration after closing and reopening the browser.
• Verified follow-up questions continue working after restoring a session.
• Verified automatic cleanup of expired sessions.
• Verified maximum session limit handling.
• Ran npm run format:check.
• Ran npm run lint.
• Ran npm run typecheck.
• Ran npm run build.

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Checklist

• My branch is up to date with the latest main.
• My code follows the project's coding standards.
• I have formatted the modified files.
• npm run format:check passes.
• npm run lint passes.
• npm run typecheck passes.
• npm run build passes.
• Documentation updates were not required.
• I have tested my changes locally.
• This Pull Request focuses on a single feature.

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Additional Notes

This PR completes Phase 2.5 of the Hyper AI Workspace. Topic explanations remain shared through the existing canonical Redis cache, while each student's follow-up conversation is stored locally on their own device. This provides persistent learning sessions without authentication, backend user storage, or additional server costs, while preserving the existing AI workflow and keeping the architecture scalable.

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Project	Deployment	Actions	Updated (UTC)
hyper-learning-tech	Ready	Preview, Comment	Jul 6, 2026 5:18am

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Review details

⚙️ Run configuration

Configuration used: defaults

Review profile: CHILL

Plan: Pro

Run ID: ad0033cd-daf0-45f8-98b9-d029d6023e80

📥 Commits

Reviewing files that changed from the base of the PR and between 9debf3c and c4e63c9.

📒 Files selected for processing (4)

• app/rgpv/[branch]/[semester]/[subject]/ai/page.tsx
• components/ai/workspace-chat.tsx
• lib/ai/session-service.ts
• types/ai.ts

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Commit unit tests in branch HyperAIWorkspace1

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[github-actions]

🎉 Congratulations @imuniqueshiv!

Thank you for contributing to HyperLearningTech.

Your pull request has been successfully merged into main.

📦 Merge Summary

• PR: feat(ai): implement persistent Hyper AI workspace with follow-up learning sessions #59 - feat(ai): implement persistent Hyper AI workspace with follow-up learning sessions
• Status: ✅ Merged
• Repository: HyperLearningTech

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• Follow the CONTRIBUTING.md guidelines.
• Keep each Pull Request focused on a single feature or fix.
• Run formatting, linting, type checking, and a production build before opening a PR.

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Happy Coding! 🚀