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AI Frameworks · mengxi-ream

read-frog

Read Frog is an open-source browser extension that uses AI models (OpenAI, DeepSeek, etc.) to provide immersive translation and language learning features directly in your browser. It supports bilingual display, selection translation, context-aware AI processing, subtitle translation, and text-to-speech across Chrome, Edge, and Firefox.

Source: GitHub — github.com/mengxi-ream/read-frog
8.3k
GitHub stars
555
Forks
TypeScript
Primary language
GPL-3.0
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
Repositorymengxi-ream/read-frog
Ownermengxi-ream
Primary languageTypeScript
LicenseGPL-3.0 — OSI-approved
Stars8.3k
Forks555
Open issues127
Latest releasev1.38.0 (2026-07-07)
Last updated2026-07-07
Sourcehttps://github.com/mengxi-ream/read-frog

What read-frog is

TypeScript/React-based browser extension built with WXT framework. Integrates 20+ AI providers via API calls, processes webpage content (DOM extraction, Markdown rendering), handles real-time streaming responses, and manages state across bilingual/translation-only modes. GPL-3.0 licensed; active development with recent v1.38.0 release (July 2026).

Quickstart

Get the read-frog source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/mengxi-ream/read-frog.gitcd read-frog# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Language Learning Platforms

Embed as a learning tool for language courses or provide as a recommended companion extension. Users can learn context-aware translation patterns while reading authentic content.

Content Localization Services

Use the codebase pattern for building in-browser translation tools for SaaS platforms targeting multilingual audiences. Reusable UI components and AI integration architecture.

Educational/Publishing Platforms

Integrate AI-powered glossaries and explanations into reading interfaces. Context extraction and explanation generation can enhance accessibility for language learners on news/article sites.

Implementation considerations

  • Requires management of multiple AI provider API keys/credentials; recommend secure configuration/vault approach in any integration.
  • DOM manipulation and page content extraction may conflict with strict Content Security Policy (CSP) headers; test on target websites before deployment.
  • Streaming responses from AI models require robust error handling and timeout logic; incomplete responses should degrade gracefully.
  • Context-aware translation extracts full page Markdown; performance impact on large documents should be tested and optimized.
  • Browser extension manifest compatibility varies (v2 vs v3); verify target browser versions and update cycles.

When to avoid it — and what to weigh

  • Proprietary/Closed-Source Commercial Product — GPL-3.0 requires all derivative works to remain open-source. Building a closed commercial product on top is not permitted without dual licensing.
  • High-Availability/Mission-Critical Deployment — Project is under active development with 127 open issues. No SLA, uptime guarantees, or production-grade reliability statements found in README.
  • Cost-Sensitive AI Inference — Extension requires active API subscriptions to third-party AI providers (OpenAI, DeepSeek, etc.). Per-request costs can accumulate for heavy usage; no offline or bundled model option documented.
  • Enterprise Data Privacy Requirements — Extension sends page content to external AI APIs for processing. If page content contains sensitive/PII data, this poses compliance risks (GDPR, HIPAA, etc.).

License & commercial use

GPL-3.0 (GNU General Public License v3.0). This is a strong copyleft license requiring any modifications or derivative works to also be licensed under GPL-3.0 and have source code disclosed. Commercial use of the extension itself is permitted, but redistribution or bundling into proprietary software is not without explicit dual licensing.

Running the extension and monetizing access (e.g., subscription service) is technically permitted under GPL-3.0, provided the source remains open. However, integrating code into a closed-source product, reselling without disclosure, or offering a proprietary version requires explicit dual licensing from the original authors (not documented as available). Requires review of intended commercialization model with legal counsel before proceeding.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationAdequate
License clarityClear
Deployment complexityModerate
DEV.co fitGood
Assessment confidenceHigh
Security considerations

Extension executes JavaScript in page context and sends page content to external AI APIs. Key considerations: (1) Page data travels to third-party AI providers—review privacy policies and data residency requirements. (2) Extension has broad DOM access—only install from verified sources (official stores). (3) API credential storage must use browser's secure storage APIs, not localStorage. (4) Content Security Policy may block extension functionality on restricted sites. (5) No mention of security audit, penetration testing, or vulnerability disclosure policy in provided data.

Alternatives to consider

Google Translate Extension

Native integration, no API keys required, but less language-learning focused; proprietary, no customization.

DeepL Browser Extension

High-quality proprietary translation, free tier available, easier setup; closed-source, limited AI explanation/learning features.

Immersive Translate (Open Source)

Similar open-source bilingual translation extension; check feature parity and maintenance status separately.

Software development agency

Build on read-frog with DEV.co software developers

Understand GPL-3.0 compliance requirements, AI provider integration costs, and data privacy implications. Our team can help evaluate fit, design architecture, and navigate licensing. Let's talk.

Talk to DEV.co

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read-frog FAQ

Can I use Read Frog in a commercial SaaS product?
Only if you remain fully open-source and GPL-3.0 compliant. Closed-source commercial integration requires dual licensing from authors. Requires review before proceeding.
What AI providers does Read Frog support?
20+ providers including OpenAI and DeepSeek (mentioned in README). Full list and setup instructions in official docs (readfrog.app/docs).
Does Read Frog work offline?
No. The extension requires active API connections to third-party AI providers. No local/bundled model option is documented.
Is there a privacy concern with page content?
Yes. Page content and context are sent to external AI APIs for processing. Review the privacy policies of your chosen AI provider and assess data residency/compliance implications.

Custom software development services

DEV.co helps companies turn open-source tools like read-frog into production software. Our software development services cover the full lifecycle — architecture, web development, integration, and maintenance — delivered by software developers and web developers who ship. Engage our software development agency to implement or customize it for your ai frameworks stack.

Ready to Integrate Read Frog into Your Platform?

Understand GPL-3.0 compliance requirements, AI provider integration costs, and data privacy implications. Our team can help evaluate fit, design architecture, and navigate licensing. Let's talk.