Run and manage open and community LLMs locally via a compact CLI and REST API—supports model import, Docker deployment, and official Python/JS SDKs for local inference, RAG, and dev workflows.
Ensures LLM outputs match precise, schema-defined structures by enforcing Python types, Pydantic models, JSON schemas or grammars at generation time. Provider-agnostic integrations (OpenAI, transformers, vLLM, Ollama, etc.) and function-call style mapping reduce brittle post-processing and make structured generation reliable for production pipelines.
Self-hostable chat client that unifies many LLM providers (OpenAI, Claude, Gemini, Ollama, DeepSeek) behind one UI. Adds file-upload knowledge-base RAG, vision/TTS, an MCP plugin system, and an agent marketplace, with one-click Vercel or Docker deployment.
Runs retrieval-augmented Q&A over your own documents on local hardware, so files never leave your machine. Blends semantic, keyword, and late-chunking retrieval, with a router that picks RAG or a direct LLM answer per query and verifies it.
Connects AI coding clients to multiple model providers through MCP, adding multi-model review, planning, debugging, and CLI-to-CLI delegation while keeping the main agent in control.
Self-hosted browser chat interface for interacting with local or remote LLMs. Supports multiple backends (Ollama, OpenAI-compatible endpoints, llama.cpp), RAG/document chat, plugins/actions, and Docker-based deployment — aimed at teams that need private, customizable LLM UIs.
Transforms websites into structured data for AI agents and analytics. Uses configurable graph-based scraping pipelines and LLM integrations, available as a self-hosted Python library or a managed cloud API with SDKs.
Self-hostable “bookmark everything” app for saving links, notes, images and PDFs with automatic fetching of previews, full-text search, OCR, and LLM-based automatic tagging and summarization (supports local models via ollama). Targets users who want AI-assisted organization in a self-hosted stack.
Build AI workflows once and run them across model providers — GoogleAI, OpenAI, Claude, Ollama — through one SDK. Composable primitives for RAG, tool use, and agents, plus a local dev UI for tracing and debugging, with SDKs in JS/TS, Go, and Python.
Continuously records your screen and audio 24/7 to a local, searchable timeline you can query in natural language. Stores screenshots with accessibility data in SQLite, and a plugin system runs scheduled AI agents on what it captures.
Self-hostable alternative to Google NotebookLM: organize PDFs, videos, audio, web pages, and Office docs, then chat over them, take AI-assisted notes, and search via full-text and vector. Routes to 18+ model providers and generates 1-4 speaker podcasts.
Orchestrates configurable deep-research agent workflows that combine LLMs, web search, and MCP tools to produce structured research reports and evaluation outputs. Supports LangGraph Studio, multiple model providers (OpenAI, Anthropic, local models), and Deep Research Bench evaluation for benchmarked comparisons.