Silo is a pure front-end application designed for simultaneous multi-model chat and text-to-image generation, primarily utilizing SiliconCloud APIs. It targets users seeking a fast, serverless AI interaction experience, offering flexibility through browser plugins, PWA support, and extensive model integration without requiring server-side infrastructure. The project aims to provide a unified, efficient interface for diverse AI models.

How It Works

Silo operates entirely within the user's browser, eliminating the need for server-side relays or infrastructure. It connects to various large language and image generation models via APIs, notably SiliconCloud, enabling users to interact with multiple models concurrently. This pure front-end architecture facilitates easy deployment, CDN hosting, and rapid responses. Key design choices include configurable model parameters, an OpenAI-compatible endpoint for broader integration, and a flexible system for adding new models through custom configurations or code.

Quick Start & Requirements

• Installation: Available as a browser extension (auto-submitted to Chrome Web Store, zip available on GitHub Releases), a web application (e.g., https://silo-chat.vercel.app), or via Docker (ghcr.io/kwokkwok/silo:latest, port 3000).
• Prerequisites: Requires API keys for services like SiliconCloud (e.g., SILO_EXPERIENCE_SK, SILO_PAID_SK via environment variables for Docker).
• Setup: Minimal setup for web/plugin use; Docker requires environment variable configuration.
• Links: Chrome Web Store (auto-submitted), GitHub Releases, Vercel AI Playground (reference), ChatHub (reference).

Highlighted Details

• Browser plugin offers text explanation and page summarization capabilities.
• PWA support allows installation as a local application on supported devices.
• URL parameters enable search engine integration (e.g., https://silo-chat.vercel.app/#/chat?q=%s) and temporary model/prompt settings.
• Supports configuration for diverse models including Gemini, Claude, Grok, DeepSeek, Zhipu, and OpenAI-compatible endpoints.
• Features model parameter tuning, night/zen modes, multi-language support, and optimized input experiences.

Maintenance & Community

No specific details regarding notable contributors, sponsorships, or community channels (like Discord/Slack) were found in the provided README text.

Licensing & Compatibility

The project is licensed under the MIT license. Its pure front-end nature suggests broad compatibility for commercial use, though reliance on third-party API terms of service is implicit.

Limitations & Caveats

As a pure front-end application, API keys configured by the user are exposed client-side. This presents a security risk, and users are explicitly warned that configured keys may be maliciously used, necessitating cautious configuration.