Reviselyt

Reviselyt is a free and open-source learning tool that helps students and developers turn long PDFs and notes into concise, revision-ready bullet points using open-source AI models. Built with Next.js, Supabase, and AI APIs, it is designed for faster learning, exam preparation, interview revision, and everyday knowledge refresh

⭐ If you find this project useful, please consider starring the repository.

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How It Works

1. Upload PDF files or paste plain text
2. AI generates 5–10 concise bullet points
3. Powered by open-source transformer models
4. Summaries are saved for future revision
5. Daily free usage limits (Free Tier)
6. Clean and distraction-free user interface
7. Secure authentication and document storage

⏱ Processing may take 10–30 seconds depending on content length.

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Key Features

Dashboard Management

The dashboard gives you a complete overview of all your generated summaries in one place. You can quickly track your previous documents, check their type (PDF or Text), and manage them with ease.

Each document entry provides quick actions to view the generated summary or delete it whenever needed. Pagination support ensures smooth navigation even when you have multiple summaries.

At the top of the dashboard, quick action cards allow you to start instantly by uploading a PDF or generating a summary from plain text.

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PDF & Text Upload

Reviselyt supports both PDF-based and text-based summarization. For text summaries, simply provide a title and paste your content. For PDFs, upload a text-based document, add a title, and submit it for processing.

The upload experience is intentionally minimal and distraction-free, allowing you to generate summaries within seconds without unnecessary steps.

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Summary View

Once the summary is generated, Reviselyt presents the content in a side-by-side layout. The original material appears on one side, while the AI-generated bullet summary is displayed on the other — making revision faster and more effective.

Text-based Summary

For pasted text, the summary view helps you quickly scan key points without rereading long paragraphs.

PDF-based Summary

For PDF uploads, Reviselyt extracts the text and generates structured bullet points, allowing you to revise large documents efficiently.

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Free Tier Limits

Feature	Limit
PDF Summaries	1 per day
Text Summaries	2 per day

Limits reset automatically every day.

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Tech Stack

• Next.js (App Router)
• TypeScript
• Tailwind CSS
• Supabase (Authentication & Database)
• Hugging Face (AI models)
• Pixabay API (Visual assets)

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Open Source

Reviselyt is built in public and open source.
Issues, feature requests, and pull requests are welcome.

• Powered by open-source transformer models
• AI-powered summaries using public models
• No user data is sold or tracked
• Content is processed only to generate summaries

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Local Development Setup

1. Clone the repository

git clone https://github.com/tanushree-coder-girl/reviselyt.git
cd reviselyt

2. Install dependencies

npm install
# or
yarn install

3. Supabase Setup

Reviselyt uses Supabase for authentication, database storage, and file uploads.
To run the project locally, you must configure your own Supabase project.

• Create a Supabase project: Go to: https://supabase.com
• Create a new project
• Database setup : Run the schema file provided in the repository in the Supabase SQL Editor (required step).
  This will manually create all required tables, RLS policies, and triggers. lib/supabase/schema.sql
• This will create: documents summaries summary_cache usage_limits Row Level Security (RLS) policies Auto-creation of usage limits for new users

4. Storage bucket setup (Required for PDF uploads)

PDF uploads require a Supabase Storage bucket.

• Go to Supabase Dashboard → Storage
• Create a new bucket: Name: documents

Storage RLS policies (IMPORTANT)

Run the following SQL to allow authenticated users to upload and access files:

# Allow authenticated users to upload files

create policy "Allow authenticated uploads"
on storage.objects
for insert
to authenticated
with check (
  bucket_id = 'documents'
);

# Allow authenticated users to read files

create policy "Allow authenticated reads"
on storage.objects
for select
to authenticated
using (
  bucket_id = 'documents'
);

# Allow authenticated users to delete files

create policy "Allow authenticated deletes"
on storage.objects
for delete
to authenticated
using (
  bucket_id = 'documents'
);

5. Environment Variables

Create a .env.local file using the example below.

cp .env.example .env.local

Fill in your own values.

NEXT_PUBLIC_SUPABASE_URL=
NEXT_PUBLIC_SUPABASE_PUBLISHABLE_KEY=
HF_API_TOKEN=
PIXABAY_API_KEY=

6. Run locally

npm run dev

Visit http://localhost:3000

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Contributing

Contributions are welcome! Please check CONTRIBUTING.md for guidelines before getting started.

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License

Licensed under the GNU Affero General Public License v3.0 (AGPL-3.0).

See the LICENSE file for full details.