Character-based chat and storywriting with large language models: TavernAI is the open-source frontend that leaves model choice to you. It generates no text itself; it connects to the backend of your choice - OpenAI (including GPT-4), Anthropic Claude, KoboldAI and KoboldCpp, Oobabooga's Text Generation Web UI, NovelAI, Ollama, and the crowdsourced Horde - so cost, model quality, and content policy are decided by your backend, not the interface. Characters are defined by portable card files in PNG or JSON format with personality, scenario, and example dialogue, and tens of thousands of community-made cards from sites like Chub.ai import directly. Conversations support group chats with multiple characters, a story mode for long-form writing, message swiping to branch between alternative responses, and full editing of any message. World Info injects lore into context when keywords trigger, keeping long roleplays consistent. Themes, custom backgrounds, and configurable generation settings round out the interface. It runs on Node.js, and the SillyTavern project began as a fork of it.

Your AI characters deserve a home that is actually yours: PocketRisu is a private roleplay chat server where your stories, personas, and worlds live on hardware you control instead of someone else's cloud. Create characters or import them from the wider RisuAI ecosystem, including character cards, modules, lorebooks, and presets, then chat from your computer, tablet, or phone against the same single server. Conversations keep generating on the server even when your screen locks or the connection drops, and reconnecting restores the finished reply instead of a lost message. Switch between OpenAI, Claude, Gemini, DeepInfra, OpenRouter, Ollama, and more, set separate auxiliary models for background tasks, and shape behavior with presets, regex scripts, and plugins. Lorebooks and long-term memory features help long stories stay consistent, automatic translation smooths cross-language roleplay, and text-to-speech plus embedded images, audio, and video make scenes richer. Everything, from characters and chats to inlay images, sits in one SQLite database on your server, so backup and restore are a server-side job rather than a browser export ritual. A built-in dashboard shows disk use per character and module, reclaims snapshot space, and keeps the database optimized, while multilingual interface options welcome players in Korean, English, Japanese, Chinese, and beyond. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPL-3.0 licensed.

Project AIRI is the most popular open-source AI companion platform — a self-hosted recreation of Neuro-sama that brings AI-powered virtual characters into your world across web, desktop, and mobile. The system renders Live2D, Spine, and VRM 3D character models with auto-blink, eye tracking, and lip-sync driven by real-time voice synthesis, while the xsAI abstraction layer connects to 40+ LLM providers including OpenAI GPT-4, Anthropic Claude, Google Gemini, DeepSeek, and local models via Ollama and OpenRouter. Built from day one on WebGPU, WebAudio, Web Workers, WebAssembly, and WebSocket technologies, the browser version runs entirely client-side with PWA offline support while the server runtime enables persistent memory via PostgreSQL with pgvector embeddings and DuckDB WASM for client-side storage. The Minecraft agent plays autonomously using mineflayer with pathfinding, and a Factorio integration provides cooperative gameplay. Social integrations deploy your companion as a Discord bot joining voice channels, a Telegram bot, and a Twitter/X agent posting and replying autonomously. The desktop Stage Tamagotchi app provides an always-on-screen companion for Windows and macOS, while Stage Pocket brings the experience to mobile. Voice features include client-side speech recognition via VAD, multiple TTS providers including ElevenLabs, and screen vision capabilities. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Every AI agent gets a face, a colour, and a job in Murmur, a chat app that makes running Hermes Agent as friendly as texting a colleague. Start from a template (Researcher, Writer, Planner, Coder, Coach, or Chef) or describe a new agent from scratch, then talk to one at a time or drop several into a group room and call on a single one with an at-mention. Replies stream in live, long jobs show a plan that ticks itself off, and every step appears in plain words. Connect a model with a ChatGPT plan, a local model server, or an API key from OpenRouter, OpenAI, Anthropic, and others, with the model and thinking effort chosen per agent or chat. Agents can reach Notion, Linear, Todoist, Figma, and dozens of other apps, and they ask for an Allow or Don't allow before changing anything important. Morning briefings run as routines, a memory view shows what each agent knows with controls to edit or forget it, and WhatsApp or Telegram can be linked by scanning a code. A voice call mode lets an agent answer out loud, and slash commands set long-running goals or ask quick side questions. Chats sync across browser, desktop, and phone. Solo builders, homelab fans, and small teams get a calm front door to their own agents. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Sapphire is a self-hosted AI companion you can shape into a personal assistant, smart-home voice, or research partner that remembers conversations and acts through the tools you choose. Choose from twelve built-in personas or build your own, with each persona bundling its prompt, voice, tools, and model, and share personas, prompts, and toolsets as portable JSON files. Talk hands-free with wake word, speech-to-text, streaming text-to-speech, and barge-in, or type in chats that each keep their own prompt, tools, voice, and memory scope. Recall past details through semantic memory search, knowledge folders with file upload and folder watching, entity records for people and places, and hierarchical goals with a timestamped progress journal. Connect Discord, Telegram, email, Google Calendar, Home Assistant, Twilio phone calls, webcams, and image generation, then extend everything through one-click plugins, toolsets, and both an MCP server and an MCP client. Schedule heartbeats, morning greetings, alarms, background agents, daemons, and webhooks so the assistant checks in, follows goals overnight, and reports back when work finishes. Keep control with a privacy vault for encrypted chats, plugin signing and trust levels, in-app backup and restore, and a dashboard showing token metrics and system controls. 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.

Your lecture slides go in one end, and a personal tutor who has actually read them comes out the other: OpenTutor turns uploaded course material into structured notes, flashcards, quizzes, and a chat tutor that answers from your own documents. Drop in a PDF, DOCX, or PPTX file, or connect Canvas LMS, and within seconds the workspace fills with generated study material organized into twelve composable blocks you can rearrange as your habits change. Ask the tutor questions and every answer cites the source material it came from, with a Socratic mode that prods you toward the answer and depth that adjusts when your replies show fatigue or repeated mistakes. Practice with seven question types, from multiple choice and fill-in-blank to matching, ordering, and coding, and wrong answers are tracked with diagnostic feedback that reshapes later difficulty. Flashcards return on an FSRS 4.5 spaced-repetition schedule tuned to what you are about to forget, and an experimental knowledge graph maps concept mastery, prerequisites, and weak spots into a learning path. Plan study sessions on the calendar, watch progress in analytics, export your work, and connect ten or more LLM providers or a local Ollama model so your documents never have to leave your server. 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 34,000+ GitHub stars and a v1.5 release driven by 36 merged community pull requests, DeepTutor from Hong Kong University's Data Science Lab delivers a full agent-native learning workspace that goes far beyond chatbot wrappers. Eight integrated surfaces — Chat, Deep Solve, Quiz Generation, Deep Research, Math Animator, Co-Writer, Book generation, and Mastery Practice — share a unified context so the objective follows the learner, not the tool. The platform's three-layer memory architecture (L1 working, L2 session, L3 long-term) makes personalization inspectable rather than opaque, letting users see exactly what the system remembers and why. Knowledge retrieval operates across five pluggable engines — LlamaIndex with FAISS vectors, PageIndex for page-level citations, GraphRAG for knowledge-graph traversal, LightRAG for local or server-offloaded retrieval, and linked Obsidian vaults — with document parsing via MinerU, Docling, markitdown, or PyMuPDF4LLM. Partners extend the tutoring brain to 15+ messaging platforms including Slack, Discord, Telegram, Matrix with E2EE, and Mattermost, each carrying private memory with branch, resume, and replay capabilities. Subagent integration brings Claude Code, Codex, Gemini, and Kimi directly into learning sessions. The system supports 30+ LLM providers from OpenAI and Anthropic to Ollama for fully local operation, with multi-user isolation, admin controls, and a full CLI interface. 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.

Tell LearnBuddy what you want to learn, in one conversation, and it works out where to start, what to do each day, and when yesterday's material needs another look. You describe the goal, whether that is a language, programming, nutrition, writing, or a career change, and three to five adaptive questions measure your actual baseline instead of making you pick a level from a dropdown. From there it builds a personalized path of four to twenty-four weeks and tells you daily what to study and what to review, so opening the app answers the question instead of raising it. Forgetting is treated as a scheduling problem: reviews resurface at spaced intervals, weekly self-checks test whether the plan still fits, and the roadmap replans dynamically when you race ahead or fall behind. Two editions run from the same codebase: try the hosted Cloud experience, or settle into Personal mode with your own model API key and your learning data stored on your own server. Optional OpenClaw and Feishu integration can bring the daily guidance into the chat tools you already live in. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Bloom hires you a private tutor for any subject, then teaches one lesson at a time and rewrites the next lesson around what you actually understood. You begin with a topic, an uploaded PDF, text, or Markdown source, or a set of project files, and Bloom drafts a syllabus of concrete mastery items at simple, standard, or deep expansion. Each lesson arrives focused and readable, with a chapter sidebar for quick jumps and a collapsible syllabus tracking what is already mastered. Reading is active work: highlight any passage and a question thread opens beside it, streaming an answer that stays attached to that sentence for later follow-ups. Reflection questions close every lesson, and your answers, annotations, and highlighted gaps become the raw material for the next lesson, which opens by reviewing the previous answers. Source mode keeps page numbers and sections so lessons can cite where an idea came from, and project files render each document as its own page for highlight questions without generated lessons. Finished courses produce an evaluation and a summary, followed by three recommended next topics drawn from your learning history. A personal center shows a study calendar, daily activity, and streaks across your courses. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Build, deploy, and monitor chatbots and LLM-powered agents on one open-source conversational AI platform: Botpress. Its Studio is a visual development environment: a drag-and-drop canvas arranges conversation logic with nodes for messages, questions, choices, and actions, while a built-in emulator simulates conversations for debugging before anything goes live. Agents ground their answers in a knowledge base assembled from uploaded documents, ingested websites, and past conversations via retrieval-augmented generation, and the LLM layer connects to multiple model providers - GPT-4, Claude, Mistral - with a configurable model strategy. An autonomous engine handles reasoning, tool orchestration, persistent memory across sessions, and sandboxed code execution, and custom code actions in TypeScript extend agents past prebuilt workflows. Over 100 integrations deploy the same bot to WhatsApp, Telegram, Slack, Microsoft Teams, and web chat, and connect it to HubSpot, Zendesk, Zapier, and arbitrary APIs and webhooks. Human handoff, conversation analytics, and quality monitoring cover production operation. Originating in 2017 from a Montreal team, the community edition is developed openly on GitHub.

Every major model provider behind one ChatGPT-style interface: LibreChat spans OpenAI, Anthropic, Google, Azure, AWS Bedrock, Vertex AI, Groq, Mistral, OpenRouter, DeepSeek, and any OpenAI-compatible endpoint including local Ollama. You can switch models mid-conversation and compare providers without changing tools. Its Agents framework builds no-code custom assistants with tool access via Model Context Protocol servers, file search over uploaded documents through an optional pgvector-backed RAG service, and a sandboxed Code Interpreter that executes Python, JavaScript, Go, C++, Java, PHP, and Rust. Artifacts render React components, HTML, and Mermaid diagrams directly in chat, and image generation works through DALL-E and other configured providers. Multi-user support is enterprise-grade, with OAuth, SAML, LDAP, and two-factor authentication, per-user conversation history in MongoDB, and Meilisearch-powered search across all messages and files, plus reusable presets, forkable threads, and persistent memory across conversations. The economics favor teams: instead of a ChatGPT Plus seat per person, everyone shares one instance billed per API token, with access to every provider rather than one - and providers see individual API calls, not your accumulated organizational knowledge. Deployment is Docker Compose; API keys and endpoints are configured through .env and librechat.yaml.

Large language models get a polished front end that can run fully offline: Open WebUI is the self-hosted front end of choice. It talks to local model runners, primarily Ollama, and to any OpenAI-compatible API, so LM Studio, vLLM, Groq, Mistral, OpenRouter, and cloud providers all plug into the same chat interface and can be mixed per conversation. RAG is built in: upload files to knowledge bases or reference them in chat with the # command, backed by a choice of nine vector databases (ChromaDB and PGVector officially maintained) and multiple extraction engines including Tika and Docling, with hybrid BM25-plus-vector search and cross-encoder reranking. Web search results from providers like SearXNG, Brave, and Tavily inject directly into conversations. Extensibility comes from Python tools and functions that run inside the chat, a Pipelines plugin framework, and native MCP support. Multi-user features include RBAC, SSO, and group permissions, and the instance itself exposes an OpenAI-compatible API your own apps can call.