Onyx is a comprehensive enterprise AI platform that provides knowledge retrieval, chat, and document indexing across 50+ third-party sources. The codebase reveals a FastAPI backend with Celery workers, PostgreSQL with Alembic migrations, OpenSearch vector search, Redis caching, and a separate model server. The frontend is a Next.js application with a custom design system (opal), alongside React Native mobile app, Go CLI, Chrome extension, and an embeddable widget. The platform supports deep research, custom agents, MCP servers, sandboxed code execution (Craft), and enterprise features like SSO, SCIM, billing, and multi-tenancy. Architecture is well-structured with clean separation of concerns, but the large codebase shows some drift: platform duplication across web/mobile/CLI, extensive Alembic migration history, and lint debt. The connector framework and design system are high-quality reusable components.

Onyx is a full-stack AI enterprise search and chat platform. The backend is a Python/FastAPI service with Celery workers, PostgreSQL, Redis, and a vector search engine (Vespa/OpenSearch). It ingests documents from 50+ external connectors (Google Drive, Slack, Confluence, Jira, SharePoint, etc.), runs a chunking/embedding/indexing pipeline, and serves RAG chat and search to multiple frontends: Next.js web app, React Native/Expo mobile app, Tauri desktop wrapper, Go CLI, an embeddable web widget, and a Terraform provider. It also includes an MCP server, deep research flows, sandboxed code-execution sessions (Craft), prompt caching, SSO/OAuth/SCIM multi-tenancy, rate limiting, and an admin analytics console. The repository has a hybrid character because it contains substantial data-engineering machinery (indexing pipelines, chunkers, embedding providers, evals) but the dominant identity is a production application rather than a research project.