53AIHub is an open-source enterprise AI knowledge management and agent orchestration platform. The codebase reveals a multi-tenant SaaS/self-hosted system that allows organizations to build, deploy, and operate AI agents across multiple backends (OpenAI, Coze, Dify, Gemini, etc.), manage knowledge bases with full RAG pipelines (document parsing, chunking, embedding, graph extraction, wiki generation), record and transcribe meetings with insight extraction, and provide a unified search and chat interface. The architecture is a Go monolith backend using Gin and GORM, with a monorepo frontend comprising three React apps (admin console, end-user portal, and embeddable agent plugin) sharing a common business logic and component library. Data flows center on document ingestion pipelines, real-time agent relay with tool execution, and recording/speech processing. The system integrates with vector stores (Qdrant), Elasticsearch, Redis, and various LLM providers. While primarily an application, it contains substantial data processing pipelines characteristic of a data_research project, particularly the RAG and recording insight modules.
Evolution API is a production-grade, multi-tenant WhatsApp API gateway built with Node.js, TypeScript, and Express. It manages independent WhatsApp instances via Baileys (WhatsApp Web), Meta Business API, and its own Evolution API channel, providing REST endpoints for messaging, chat management, groups, labels, and media. The system integrates deeply with chatbot platforms (Typebot, OpenAI, Dify, Flowise, N8N, EvoAI, EvolutionBot) and event systems (Webhook, WebSocket, RabbitMQ, SQS, NATS, Kafka, Pusher), and includes storage via S3/MinIO and CRM sync with Chatwoot. The architecture follows a modular controller-service pattern with Prisma ORM (supporting MySQL and PostgreSQL), Redis caching, and centralized configuration. It is actively maintained with frequent updates, extensive migrations, and CI/CD pipelines.
This is the server platform for the XiaoZhi (小智) ESP32 voice-assistant ecosystem: a large multi-component monorepo that turns low-cost ESP32 hardware into an AI voice assistant. The core is a Python asyncio service (main/xiaozhi-server) that maintains WebSocket connections with devices and runs a real-time audio pipeline — VAD, ASR, intent/LLM orchestration, tool calling, and TTS — streaming audio back to the device. Device onboarding, OTA firmware updates, and the WebSocket handshake are partly in the Python server and partly in a Java Spring Boot management API (main/manager-api) backed by MySQL + Redis, which exposes a broad admin surface: users, devices, agents, model-provider configuration (LLM/ASR/TTS/VAD/memory/intent), RAGFlow-backed knowledge bases, voice clone, voiceprint, chat history, and MCP tool management. Two management frontends exist (a Vue 2 web console and a uni-app/Vue 3 mobile app), plus a Live2D digital-human web client and an offline theme generator for firmware assets. It is an application, not a research repository — no notebooks, data pipelines, or analytical datasets; the 'data' features (RAG ingestion, voice cloning, chat-history reporting, performance testers) are all operational application features.