ZipXtract extracts archives including RAR, ZIP, TAR, and BZ2 formats through a fully open source Android app.
Open source
24 alternativesNotesgpt
notesGPT records voice notes, transcribes and summarizes them, and extracts tasks.
About Notesgpt
notesGPT records voice notes, transcribes them, and creates summaries with action items. It stores audio with Convex File Storage, uses Together Inference with Whisper for transcription and Mixtral for text processing, and uses Together Embeddings with Convex vector search for search.
It is distributed as open source code under an MIT license for self-deployment. Running a copy requires setting up Convex, Clerk, and Together accounts and adding their environment variables and API keys.
Key features
- Record voice notes stored with Convex File Storage
- Transcribe voice notes with Whisper via Together Inference
- Summarize notes with Mixtral via Together Inference
- Generate action items from notes
- Search notes with embeddings and Convex vector search
- Authenticate users with Clerk
Best for: Developers who want to deploy their own voice-note transcription and summarization app.
Good for
- Open source code under MIT license for self-deployment
- Combines recording, transcription, summarization, action items and search
- Lists required services and environment variables for setup
Watch out for
- Self-deployment requires Convex, Clerk and Together accounts and API keys
Notesgpt at a glance
- Website
- github.com/nutlope/notesgpt
- Category
- Mobile Apps › Android Productivity Apps
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Notesgpt FAQ
What is needed to run my own copy?
Set up Convex, Clerk and Together accounts, add environment variables including CLERK_ISSUER_URL and TOGETHER_API_KEY, then run npm install and npm run dev.
How does notesGPT handle transcription and summaries?
It uses Together Inference with Whisper for transcription and Mixtral for the language model.
How is note search handled?
It uses Together Embeddings with Convex vector search.
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