CPA Manager Plus is a full-stack, self-hosted management panel for AI gateway proxies (CPA / CLIProxyAPI). It provides a rich React dashboard to monitor usage across multiple AI providers, manage credentials and API keys, configure provider-specific settings, automate quota cooldowns and account health actions, and inspect credential health via Codex/xAI probes. The Go backend persists all data in SQLite, runs background workers for data rollups, migrations, and collector polling, and exposes a comprehensive REST API. The codebase is well-structured with a clean layered architecture (HTTP handlers, services, repositories), extensive unit and integration tests in both Go and TypeScript, a demo mode with synthetic data, and i18n support. It is actively maintained with a rigorous release process and frequent updates.
Homer is a production-grade, all-in-one HEP (Homer Encapsulation Protocol) capture and API server for SIP, RTP, RTCP, OTLP, and log data. It powers Homer 11.x data lake with DuckDB, Parquet, and Apache Arrow. The system ingests packets over UDP, TCP, TLS, HTTP, and WebSocket, decodes them using a custom zero-copy SIP parser, and stores them in a columnar DuckLake (DuckDB-backed) storage with SQLite catalog, supporting S3 and Azure backends. It provides a REST API (Echo) for search, dashboards, alerts, and configuration, an Arrow FlightSQL server for Grafana integration, and a React/TypeScript dashboard with drag-and-drop widgets, call flow visualization, and even browser-based games (chess, Doom). Architecture is modular with four main components: Ingest (transport servers), Storage (DuckLake manager with sharded writers, compactor, tiered mover), Node (FlightSQL server, catalog metadata), and Coordinator (REST API, auth, Lua correlation engine, LLM integration). Data flows from HEP/OTLP/Line Protocol receivers through decoders into DuckLake, then served via FlightSQL or REST. External dependencies include DuckDB, S3/Azure SDKs, Lua (golua), OTLP protobuf, and InfluxDB Line Protocol parser. The codebase demonstrates strong engineering practices: object pools for hot-path allocations, idempotent stop patterns, retry with backoff for catalog operations, and a Lua sandbox for scripting. However, it also carries some feature creep (games, LLM) and technical debt (dual SIP parsers, SQL injection risks via string interpolation in some services, and a few commented-out tests). Overall, it is a well-maintained, high-quality observability platform for VoIP and telemetry data.
Flow Kit is an AI video production pipeline orchestrator that manages the end-to-end workflow of creating cinematic videos via Google Flow. It consists of a FastAPI backend (Python) with SQLite persistence, a React dashboard (TypeScript, shadcn/ui) for monitoring and control, a Chrome MV3 extension that bridges the local agent to flow.google.com for batchexecute RPCs, and a worker queue for asynchronous processing. The system supports project creation, character/entity management, scene image/video generation (Veo 3, Omni Flash), AI-powered video review with contact sheets and dimension scoring, TTS narration via OmniVoice, music generation via Suno API, post-processing (concat, branding, SFX), and YouTube upload with channel rules and SEO metadata. The architecture is modular with a provider abstraction layer (Flow, assistant, muse2api), an event bus for real-time updates, and a skill-based workflow system (40+ markdown recipes) that serves as the single source of truth for AI agents (Claude Code, Codex, agy). The codebase is actively maintained with recent migrations (September 2026 Flow API migration) and a comprehensive test suite, though it carries technical debt from multiple fallback layers, hardcoded payload shapes, and tight coupling to Google Flow's internal API.
A full-stack personal running activity dashboard that syncs workout data from over a dozen platforms (Strava, Garmin, Nike, Keep, Coros, etc.) via Python scripts, stores it in SQLite, and renders interactive web visualizations (React + Mapbox) and SVG posters (grid, heatmap, year summaries). It also includes a terminal UI (Textual) and an optional AI-powered share image generator. The architecture is a hybrid monolith: a shared SQLite database backs both the frontend (exported as JSON) and SVG generation. The frontend is themeable with two built-in themes (classic, dashboard). While the sync scripts are tightly coupled to each provider's API, the SVG poster drawer library and the terminal UI's data aggregation layer are well-isolated and potentially reusable. The project is actively maintained with frequent commits, CI/CD pipelines, and Docker support, though it carries moderate technical drift due to many unpinned dependencies and reliance on third-party APIs that may change.
This is the frontend administrative dashboard for Apache ShenYu, an API gateway. Built with React 16, Ant Design 3.x, and the Dva state management framework, it provides a comprehensive set of CRUD interfaces for managing gateway plugins, selectors, rules, metadata, authentication, roles, users, namespaces, alerts, instances, API documentation, and more. The architecture follows a classic single-page application pattern with client-side routing, modal-based forms, and permission-aware UI components. All data flows through a centralized service layer to the ShenYu Admin backend. While functionally complete and actively maintained, the codebase carries significant technical debt: outdated dependencies (roadhog, antd 3.x, React 16, Dva), mixed class and functional components, duplicated CRUD patterns, and leftover boilerplate from Ant Design Pro. The code is predominantly in JavaScript with some TypeScript files, and internationalization is handled via JSON locale files. It is not a data research repository.