Drag nodes onto a canvas and ship an LLM app: Flowise is an open-source visual builder for AI agents and LLM applications, written in Node.js on LangChain.js and licensed Apache-2.0. You assemble flows by dragging nodes onto a canvas: models, prompts, memory, vector stores, retrievers, and tools, then wire them together and test in the built-in chat panel. Three builder types cover increasing complexity: Assistant for simple RAG chat over uploaded files, Chatflow for single-agent systems with techniques like rerankers and Graph RAG, and Agentflow for multi-agent orchestration with branching, looping, shared flow state, and human-in-the-loop checkpoints. Over 100 integrations connect data sources, vector databases, and both proprietary and open-source models, plus MCP client and server nodes for standard tool interop. Finished flows are exposed as REST APIs, embedded chat widgets, or via JS and Python SDKs - each flow gets an endpoint the moment it is saved, removing the deployment gap between a working prototype and something your application can call. Execution logs, visual step debugging, and external log streaming trace behavior, while input moderation and rate limiting act as guardrails; RBAC, SSO, and workspaces cover team deployments. Self-hosting keeps prompts, encrypted credentials, and conversation data on your own instance, which matters when flows handle internal documents or customer data - and wiring a model, prompt, memory, and vector store on the canvas replaces the boilerplate a hand-coded LangChain project would need.

Baby Buddy is a private self-hosted child care tracker that centralizes feeding sessions, sleep cycles, diaper changes, and developmental health milestones into a collaborative dashboard for parents and caregivers. Caregivers can start quick timers on mobile devices to measure nursing intervals, bottle feedings, naps, and tummy time sessions with single-tap precision. The dashboard automatically calculates daily averages, feeding amounts, and awake windows to help families establish consistent daily sleep and feeding routines. Parents can track diaper changes by recording wetness, stool consistency, and color anomalies to spot digestive health changes early. Physical measurements including weight, height, and head circumference plot directly against World Health Organization growth curves to visualize percentile progression between pediatric visits. Multi-child profiles allow families with twins or multiple young children to switch contexts instantly and monitor individual growth timelines. Granular user permissions let parents invite nannies, babysitters, and relatives with restricted logging permissions while keeping administrative settings private. The built-in REST API and webhook system enable physical smart button clicks and home automation routines to log events instantly without opening a browser. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSD-2-Clause licensed.

Originally built at Netflix to orchestrate microservices powering 230 million subscribers and now trusted in production at Tesla, LinkedIn, and J.P. Morgan, Conductor is the most battle-tested open-source workflow engine available — with 32,000 GitHub stars and horizontal scalability to billions of executions. The architecture cleanly separates orchestration from business logic: workflows are defined in declarative JSON while workers execute tasks in any of seven supported languages (Java, Python, Go, JavaScript, C#, Ruby, Rust) with zero framework constraints. Durable execution persists every state transition, enabling automatic retries, configurable timeouts, crash recovery, and instant replay from any failure point without re-executing completed tasks. Native AI agent orchestration supports 14+ LLM providers (Anthropic, OpenAI, Google Gemini, AWS Bedrock, Mistral, Cohere, HuggingFace, Ollama), MCP tool calling, function calling, human-in-the-loop approval gates, and vector database integration (Pinecone, pgvector, MongoDB Atlas) for RAG pipelines. Deploy with your choice of five persistence backends (PostgreSQL, Redis, MySQL, Cassandra, SQLite), six message brokers, and Elasticsearch or OpenSearch for workflow indexing — all configurable via Docker Compose files included in the repository. The built-in web UI provides workflow visualization, execution monitoring, task queue inspection, and manual intervention controls. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Real-time alerts from your own infrastructure to your phone, with no Firebase, Pushover, or third-party push service in the path: Gotify is a simple, self-hosted notification server written in Go. The model is deliberately minimal: senders push messages with a single HTTP POST to the REST API, receivers subscribe over a WebSocket stream, and a clean React web UI manages the pieces. Senders are namespaced as "applications," each with its own token, so your backup script, Uptime Kuma, CI pipeline, and cron jobs each get an identity, an icon, and independently revocable credentials - centralized alerting from many services with per-source management. Messages carry a title, body, and priority level that maps to notification importance on the client. The official Android app (on both F-Droid and Google Play, notable for working entirely without Google Play Services) shows push notifications for new messages; the web UI itself supports Web Push in the browser; and gotify/cli pushes messages from shell scripts with one command. A server-side plugin system adds custom behavior, and the whole thing runs as a single small binary with SQLite by default - near-zero resource footprint. Because dozens of tools (and Apprise) speak Gotify natively, it slots in as the notification hub for an entire homelab or ops stack.

Accepted as a NeurIPS 2025 Spotlight paper and rapidly approaching 6,000 GitHub stars, AI-Researcher from the Hong Kong University Data Science Lab delivers the first fully autonomous scientific research system — a multi-agent platform that takes a list of reference papers and returns a complete research contribution with working code, validated experiments, and a formatted academic manuscript. The pipeline orchestrates five distinct phases: a Resource Collector systematically gathers materials from arXiv, IEEE Xplore, ACM Digital Library, Google Scholar, GitHub, and Hugging Face; an Idea Generator performs gap analysis against semantic embeddings to produce 3-5 novel hypotheses with feasibility scores; an Algorithm Designer transforms concepts into functional implementations; a Validation Engine automates testing, performance evaluation, and iterative optimization; and a Manuscript Creator generates polished full-length papers with figures, tables, and citations. The Gradio-based web GUI provides intuitive tabs for environment configuration, example selection, and real-time monitoring of research progress, while the production deployment at novix.science offers immediate browser access without local setup. Scientist-Bench provides a standardized benchmark comprising state-of-the-art papers across diverse AI research domains for evaluating autonomous research capabilities. The system supports multiple LLM providers including OpenAI, Anthropic, Google Gemini, and OpenRouter models with per-task routing for cost optimization. Deploy via Python with pip dependencies or Docker containerization. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Open-sourced by the Databricks AI team under Apache 2.0 and reaching over 8,500 GitHub stars within two months of launch, Omnigent introduces the meta-harness concept: a common orchestration layer that sits above existing AI coding agents and makes them interoperable parts of a governed, collaborative system. The platform wraps Claude Code, Codex, Cursor, OpenCode, Hermes, Pi, and any custom agent defined in a simple YAML configuration file into sandboxed sessions with a uniform API, then exposes each session through the terminal, a web UI, a native desktop application, mobile interfaces, and a REST API. Built-in multi-agent workflows include Polly, a coding orchestrator that delegates tasks to parallel sub-agents in separate git worktrees and routes each diff to a reviewer from a different vendor, and Deep Research, which plans sub-queries, searches the live web through MCP servers, reads full pages, and cross-checks claims across independent sources. Contextual security policies go beyond static allow/deny rules by maintaining per-session state to enforce spend caps, model routing, approval gates for destructive actions, PII blocking, and repository-scoped write restrictions across server-wide, per-agent, and per-session levels. The OS sandbox restricts filesystem and network access while intercepting egress requests to inject credentials only on approved calls. Cloud sandbox providers including Modal, Daytona, E2B, CoreWeave, Kubernetes, and Databricks launch disposable execution environments per session. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Sim Studio lets teams build, deploy, and monitor AI agent workflows by dragging blocks onto a visual canvas and wiring them into executable pipelines, backed by over 1,000 integrations. The React Flow editor represents each step as a node: LLM calls, tool invocations, conditional branches, and data transformations form directed acyclic graphs that run as complete agent pipelines. Every major LLM provider works natively, including OpenAI, Anthropic, Google Gemini, Groq, and Cerebras, plus local models through Ollama and vLLM. Integrations span Gmail, Slack, Microsoft Teams, Telegram, WhatsApp, Notion, Google Workspace, Airtable, GitHub, Jira, Linear, Perplexity, Firecrawl, PostgreSQL, Supabase, Pinecone, and Qdrant. Built-in tables provide a database layer, a file store offers shared team storage, and knowledge bases powered by PostgreSQL with pgvector enable retrieval-augmented generation. Finished workflows deploy as REST API endpoints, scheduled jobs, or Slack bots, with block-by-block execution traces for full observability. Real-time collaborative editing via Socket.io supports simultaneous multi-user construction. Alternatively, describe agent behavior in natural language and Sim assembles the workflow automatically. Built on Next.js App Router, Bun runtime, Drizzle ORM, and Tailwind CSS. 29,400+ GitHub stars and 100,000+ builders. Apache-2.0 licensed.

Mixpost puts Facebook, Instagram, X, LinkedIn, YouTube, TikTok, Pinterest, Threads, Bluesky, Mastodon, Pixelfed, and Google Business under a single scheduling dashboard — plan content visually on a drag-and-drop calendar, queue posts for optimal engagement windows, and track audience growth per platform without juggling twelve separate apps or paying per-seat SaaS fees. Built on Laravel with a Vue.js 3 and Inertia.js frontend styled with Tailwind CSS, the Lite edition provides unified content management where each post supports platform-specific customization with individual captions, media attachments, hashtag groups, and first-comment scheduling. Posting queues automate publishing at configurable time slots throughout the day. The media library provides a centralized asset manager with drag-and-drop uploads, stock photo integration via Unsplash, and Tenor GIF search. AI-powered content assistance generates and optimizes post copy. Per-platform analytics dashboards display audience growth, engagement metrics, reach, and impressions with exportable reports. Team workspaces support role-based permissions for collaborative content management across departments. External integrations connect through the REST API, webhooks, n8n, Zapier, and RSS feeds, plus an MCP server for AI assistant publishing. Deploy via Docker Compose with MySQL and Redis. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Dify turns the notoriously complex process of building production-grade AI applications into a visual drag-and-drop experience that teams can actually ship and maintain. With over 87,000 GitHub stars and backing from prominent investors, the platform has become the go-to open-source LLMOps solution for organizations that refuse to be locked into proprietary AI stacks. The visual workflow canvas lets developers wire together LLM calls, conditional logic, iteration loops, tool invocations, and human-in-the-loop checkpoints without writing boilerplate integration code. Its RAG pipeline engine handles the full document lifecycle from ingestion of PDFs, Word documents, and HTML through configurable chunking strategies, embedding with models from OpenAI or open-source alternatives, vector storage in Weaviate, Qdrant, Pinecone, or pgvector, and hybrid semantic-plus-keyword retrieval with citation tracking. Dify integrates with hundreds of model providers including OpenAI GPT-4o, Anthropic Claude, Google Gemini, Mistral, Llama, and any OpenAI-compatible endpoint like Ollama for fully local inference. The agent framework supports both ReAct and function-calling strategies with 50-plus built-in tools spanning Google Search, DALL-E, Stable Diffusion, WolframAlpha, and custom API definitions. Published apps can be deployed as hosted web interfaces, embedded chat widgets, REST API endpoints, or MCP-compatible tools. Enterprise features include role-based access control, SSO integration, and audit logging. A built-in marketplace enables teams to share and reuse model providers, tools, and workflow templates across projects. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed with an open-source community edition.

Command and automate your entire fleet of 3D printers without relying on proprietary cloud services using Bambuddy, a self-hosted management hub that delivers local network control, print scheduling, and job archiving for Bambu Lab hardware. Print shop operators can route slicing output directly from Bambu Studio or Orca Slicer through virtual printer proxies that emulate physical machines while automatically cataloging print files in a searchable 3D repository. The automated dispatch engine assigns queued gcode files to available printers based on required nozzle temperatures, build plate dimensions, and matched multi-color filament slots. Users can inspect live camera streams across multiple printing beds simultaneously, verify empty build plates before dispatching new jobs, and generate stabilized timelapse videos with custom music. Integrated smart plug connectors automatically cut power to idle machines when print cycles finish and trigger push notifications to Discord or mobile devices if thermal anomalies or mechanical pauses occur. Farm managers can schedule maintenance alerts based on cumulative motor runtime, track spool inventory levels across storage locations, and synchronize printing configurations across duplicate hardware setups. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GNU AGPL v3.0 licensed.

Customermates delivers a modern CRM purpose-built for teams who want practical customer management without enterprise-heavy complexity. The platform manages contacts, organizations, deals, services, and tasks through clean pipeline workflows while integrating AI agent capabilities, REST API access, webhook events, n8n automation connections, and Model Context Protocol tooling for AI-native operations. Team collaboration features include role-based permissions, comprehensive audit logging tracking every data change, and workspace organization for multi-team deployments. The deal pipeline provides customizable stages with drag-and-drop management, while task assignments and service tracking connect directly to contact and organization records for complete relationship context. API-first architecture exposes all CRM data through documented endpoints enabling custom integrations, reporting dashboards, and third-party tool connections. The n8n integration enables no-code workflow automation for lead routing, follow-up sequences, notification triggers, and cross-system data synchronization. Self-hosting requires only two files — a Docker Compose configuration and environment variables — with the published image at ghcr.io/customermates/customermates:latest running database migrations automatically on first boot. PostgreSQL provides the data layer with no additional infrastructure dependencies beyond a reverse proxy for TLS termination. The Community Edition includes unlimited users, unlimited records, full API access, n8n automation, and audit logging at zero cost. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

With over 6,500 GitHub stars, HolaOS bills itself as an "open agent computer" that reimagines the traditional operating system as a shared workspace where humans and AI agents collaborate across files, browsers, and 100+ integrated tools simultaneously. Unlike chat-only interfaces, HolaOS places live application UIs—Notion-style editors, browsers, custom workspace apps—side by side with the agent conversation, so operators always see what agents are doing and can intervene at any moment. The persistent memory system stores workspace knowledge locally as Markdown files and embedded vectors via SQLite vec, enabling RAG-powered recall that survives session boundaries without the typical context window bloat. Safe Session Compaction reserves roughly 70% of the model context window for fresh reasoning while folding older history into structured checkpoints that retain goals, constraints, progress, and decisions. Agents connect to Linear, GitHub, Slack, Jira, HubSpot, Gmail, and dozens more through one-click OAuth, automatically fetching relevant signals and converting scattered app data into working memory. BYOK support for Claude, GPT, and Gemini models lets operators use their own API keys at zero markup, while built-in Kimi K3 and GLM-5.2 models provide ready-to-use alternatives. Skills package reusable workflows that any agent can invoke on demand, and scheduled triggers enable autonomous digests, monitors, and reports. The runtime supports independent server deployment alongside the desktop client. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Modified Apache 2.0 licensed.

Browser Use Web UI lets you describe a web task in plain English and watch as an AI agent autonomously navigates pages, clicks buttons, fills forms, and extracts information without writing any automation code. Backed by over 16,000 GitHub stars, the Gradio-based interface supports 14+ LLM providers through a unified abstraction layer: OpenAI GPT, Anthropic Claude, Google Gemini, Azure OpenAI, DeepSeek, and local Ollama models are all configurable via dropdown menus without touching code or environment files. The BrowserUseAgent handles interactive single-task automation with step-by-step LLM decision-making and vision-based page understanding, while the DeepResearchAgent orchestrates multi-step research workflows using Langgraph state machines that spawn parallel browser instances with asyncio concurrency control. Custom browser support connects your existing Chrome profile to preserve logins, cookies, and sessions across agent runs, eliminating re-authentication overhead. Persistent browser sessions maintain complete interaction history between tasks for debugging and demonstration. The Docker deployment bundles Chrome, Playwright, and a VNC server in a single container, exposing the Gradio interface on port 7788 and a noVNC viewer on port 6080 for real-time observation of agent behavior. MCP integration via MultiServerMCPClient enables external tool access. Screen recording captures agent workflows as video for review and documentation. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

With over 7,400 GitHub stars and benchmarked at 0.89 seconds average session lifecycle — 1.7x to 9x faster than competing browser automation platforms — Steel Browser delivers production-grade headless Chrome infrastructure purpose-built for AI agents that need to interact with the modern web. The TypeScript-based server exposes a REST API providing on-demand browser sessions with full CDP (Chrome DevTools Protocol) access, allowing connections from Puppeteer, Playwright, or Selenium through standard WebSocket endpoints without framework lock-in. Each session maintains persistent state including cookies, localStorage, IndexedDB, and authentication credentials across requests, enabling stateful multi-step agent workflows that survive session restarts. Built-in anti-detection includes stealth plugins, browser fingerprint randomization, and configurable user-agent rotation, while the proxy chain manager handles IP rotation through residential, datacenter, or custom proxy pools. CAPTCHA solving integrates natively so agents encounter fewer blocking interrupts during autonomous navigation. The Session Viewer provides real-time WebRTC-streamed visual debugging of live sessions and playback of recorded sessions with full network request logging. Browser Tools APIs convert any page to clean Markdown, readability-optimized text, PDF documents, or high-resolution screenshots with a single API call. The MCP Server integration exposes Steel sessions as tools accessible to Claude, Cursor, and other Model Context Protocol-compatible AI agents. Deploy via Docker with a single container or use Docker Compose for production configurations with automatic resource cleanup and session lifecycle management. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Getting a language model into the chat apps people already use takes a single self-hosted server running AstrBot, which answers in QQ, Telegram, Discord, Slack, Lark, DingTalk, LINE, and WeCom. The model itself is a setting. OpenAI-compatible endpoints, Anthropic, Google Gemini, DeepSeek, Ollama, and LM Studio all work, with fallback models and retry limits for failed requests, and Dify, Coze, or Alibaba Cloud Bailian can take over a conversation too. A bare model cannot act, so the built-in agent calls MCP servers and Skills, delegates to SubAgents, runs scheduled tasks, and executes code in an isolated sandbox. It cannot read your files either, so a knowledge base takes PDF, Word, Markdown, and EPUB uploads and searches them with hybrid dense and BM25 retrieval. Personas shape each bot's personality, and Whisper or Edge TTS adds speech. When an answer looks wrong, the ChatUI shows thinking, tool calls, token counts, and latency, and a per-message trace timeline shows how the bot got there. Because the panel steers the bot, administrator IDs, session whitelists, optional TOTP login, and HTTPS protect it. Backups live under System Settings, and the plugin market installs any of more than 1,000 extensions in one click. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Replacing HubSpot, Zendesk, Intercom, and Linear with a single self-hosted platform, erxes delivers an Experience Operating System trusted by over 4,000 GitHub stars and built on a modern Nx-powered monorepo architecture. The core ships with six foundational modules — My Inbox for omnichannel conversations across email, web chat, voice, and Discord; Contacts for unified customer profiles; Products for catalog management; Segments for behavioral targeting; Automation for visual workflow builders; and Documents for template generation. Beyond the core, a plugin marketplace activates Frontline for ticket management and omnichannel support queues, Sales for deal pipelines and lead scoring, Operations for project boards with cycle management, Content for headless CMS and knowledge bases, and Team for employee directories, time clocks, and internal chat. The technical stack combines GraphQL Federation with Apollo Server v4 and tRPC v11 microservices on Node.js, React 18 micro-frontends via Rspack Module Federation with TailwindCSS 4, MongoDB with Mongoose for persistence, Redis for caching, BullMQ for job queues, and Elasticsearch for full-text search. Deployment supports Docker Compose orchestration with automatic service discovery across all plugin containers. The Global Profile architecture enables agencies to manage multiple client brands under a single login with separated data stores. iOS and Android SDKs embed the messenger widget directly into mobile applications. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPLv3 licensed.

Your house already has lights, locks, sensors, thermostats, and speakers from many brands, and Home Assistant gives them one local control room with no vendor cloud in the loop. To close the shutters when the outdoor temperature holds above 25 °C, or to be alerted when the garage door is left open, build the routine in the visual editor: When, And if, Then do. Scenes, scripts, and blueprints package it for reuse, and run traces show what it did. More than 1,500 integrations cover Zigbee, Z-Wave, Matter, Thread, MQTT, ESPHome, Bluetooth, Hue, and Sonos, and network discovery offers known devices for one-step setup. To see the house at a glance, drag tile, thermostat, gauge, graph, and map cards into a dashboard, then put it on a TV with Home Assistant Cast. The Energy dashboard answers where the power goes, drawing solar, grid, battery, gas, and water as one distribution diagram with cost totals and per-appliance tracking. To talk to the house, use Assist: natural-language commands, wake words, and custom sentences run locally or through Home Assistant Cloud. The map panel shows who is home, plotting people against zones such as Home, Work, and School from the iOS and Android companion apps. Areas and labels keep large setups tidy, and multi-factor authentication guards each account. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Deployed at thousands of enterprises across financial services, healthcare, government, and telecommunications, Apache NiFi is the industry-standard platform for building automated data pipelines through a visual drag-and-drop browser interface that requires zero coding for common integration patterns. The flow-based programming model connects over 300 built-in processors covering relational databases via ExecuteSQL and PutDatabaseRecord, Apache Kafka with PublishKafka and ConsumeKafka, HTTP endpoints through InvokeHTTP and ListenHTTP, cloud storage for AWS S3, Azure Blob, and Google Cloud Storage, SFTP/FTP file transfers, and JSON, XML, CSV, and Avro transformations. Data provenance tracking logs every routing decision, transformation, and delivery for every FlowFile, creating a searchable lineage graph from source to destination with full content replay capability for auditing and debugging. Guaranteed delivery uses configurable backpressure thresholds, prioritized queuing with latency or throughput optimization, and automatic retry with exponential backoff, ensuring no data loss even during downstream outages. The zero-leader clustering architecture distributes processing across nodes with automatic load balancing, while site-to-site protocol enables secure data transfer between NiFi instances across network boundaries. Security includes OpenID Connect and SAML 2.0 single sign-on, role-based access control with fine-grained policies per component, and TLS encryption for all communication. Custom processors can be written in Java and packaged as NAR bundles, or implemented directly in Python through the native scripting framework. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.