FastGPT is a production-grade AI Agent building platform that enables users to create, deploy, and manage AI applications through a visual workflow editor. The system provides a full-stack solution including a Next.js frontend with Chakra UI, a comprehensive REST API layer, and a modular backend architecture. Core capabilities include a workflow engine with agent loops, tool calling, dataset (knowledge base) management with vector search, sandboxed code execution (JS/Python), multi-tenant team management with fine-grained permissions, billing and usage tracking, and integration with external platforms (WeChat, Feishu, Dingtalk, MCP). The platform is designed for both open-source community and commercial deployments, with feature gating via license activation. The codebase is organized as a monorepo with clear separation of concerns: shared types and constants in `packages/global`, business logic in `packages/service`, UI components in `packages/web`, data access layer in `packages/dal`, and separate services for sandbox execution and volume management. It relies on MongoDB, Redis, BullMQ, S3-compatible storage, and multiple vector database backends (PG, Milvus, OceanBase, SeekDB, OpenGauss). The architecture is predominantly monolithic with the main application as a Next.js app, but sandbox and volume manager run as independent services, indicating a hybrid monolith/microservices pattern.

aiproxy is a production-grade AI API gateway written in Go, acting as a unified proxy between client applications and over 40 AI provider APIs (OpenAI, Anthropic, Gemini, etc.). It converts protocol formats (OpenAI, Anthropic, Gemini), handles authentication, rate limiting, load balancing, request caching, and detailed usage billing. The system includes a React admin dashboard for managing channels, tokens, models, groups, logs, and consumption. It also supports the Model Context Protocol (MCP) for integrating AI tool servers, both hosted and proxied. The architecture is monolithic with a plugin system for extensibility, storing state in PostgreSQL and Redis. It demonstrates strong engineering practices including comprehensive test coverage, efficient caching (multi-layer with keyed locks), sliding window rate limiting, and a clean adaptor pattern for provider abstraction.