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05.2026

Rage AI: Multi-Model Agentic AI Platform

A full-stack agentic AI platform integrating OpenAI and Google Gemini with LangGraph state graphs, dynamic tool calling, and OAuth integrations.

Next.jsTypeScriptLangChainLangGraphPostgreSQLPrismaOpenAIGoogle Gemini
Rage AI: Multi-Model Agentic AI Platform cover

Introduction

Rage AI is an agentic AI workspace that bridges advanced Large Language Models with real-world tool execution. It allows users to orchestrate complex tasks across cloud services, run multi-turn agent workflows, and switch dynamically between frontier models.

Why I Built It

Simple chat interfaces fail when problems require external actions, long-running context, or multi-step reasoning. Rage AI was engineered to explore cyclic graph agent workflows (via LangGraph) that maintain explicit state, evaluate interim outputs, and call dynamically registered tools.

Key Capabilities

  • Multi-Model Orchestration: Seamless switching between OpenAI GPT models and Google Gemini with streaming responses and persistent conversation threads.
  • State Graph Agent Workflow: Built using LangGraph with conditional routing, self-correction, and structured tool invocation.
  • Third-Party Integrations: OAuth 2.0 connectors for GitHub, Gmail, Google Drive, Google Calendar, and Notion with automatic token refresh handling.
  • Granular Security: Organization and user-scoped data layers, encrypted OAuth credentials, soft deletion, and fine-grained permissions per tool.
  • Modern User Experience: Built with Next.js 15, TypeScript, Tailwind CSS, and Markdown rendering with code highlighting and citation support.

Explore the source code on GitHub