LLMChat.co offers a privacy-first, unified interface for AI chat and agentic workflows, targeting users who need in-depth research and task automation. It provides advanced modes like "Pro Search" and "Deep Research," leveraging multiple LLM providers and storing all data locally in the browser via IndexedDB to ensure user privacy.

How It Works

The platform is built as a monorepo using Next.js and TypeScript, featuring a modular architecture with clear separation of concerns. Its core innovation lies in its workflow orchestration system, enabling agentic capabilities through a step-by-step, event-driven approach. Users can define custom research agents by creating tasks (e.g., taskPlanner, informationGatherer, informationAnalyzer, reportGenerator) that process data and context sequentially, emitting events to update the UI in real-time.

Quick Start & Requirements

• Install: git clone https://github.com/trendy-design/llmchat.git && cd llmchat && bun install (or yarn install)
• Run: bun dev (or yarn dev)
• Prerequisites: Bun (recommended) or Yarn. OpenAI API key (for LLM access).
• Links: Project Repository

Highlighted Details

• Supports multiple LLM providers including OpenAI, Anthropic, Google, Fireworks, Together AI, and xAI.
• Features agentic capabilities like workflow orchestration and reflective analysis.
• Employs local-only storage via IndexedDB (Dexie.js) for enhanced privacy.
• Built with a modern tech stack: Next.js 14, TypeScript, Tailwind CSS, Framer Motion, Shadcn UI, Tiptap, Zustand.

Maintenance & Community

The project is actively maintained by trendy-design. Community channels are not explicitly mentioned in the README.

Licensing & Compatibility

The repository does not explicitly state a license in the provided README. Compatibility for commercial use or closed-source linking would require clarification on licensing.

Limitations & Caveats

The README does not specify a license, which is a significant blocker for understanding commercial use or distribution rights. The project appears to be in active development, and specific LLM provider integrations might require individual API key configurations.