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Generates and deploys full-stack React apps from natural-language prompts on Cloudflare’s platform, combining AI code generation, previews, Workers, Durable Objects, and containers.
Runs autonomous AI-agent workforces where each agent, skill, and company process lives as version-controlled code you own. Agents act in isolated sandboxes and submit deliverables for human review, with 3,000+ connectors plus MCP support.
Enables agents to autonomously operate GUIs and complete complex computer tasks — includes the Agent S papers and the gui-agents SDK, grounding-model support, and runnable S3 agent implementations for Windows/macOS/Linux.
Agentive operating system for physical robots that lets developers compose agent-native modules in Python to connect perception, spatial memory, and control across humanoids, quadrupeds, drones, and simulators.
Turns any website into a structured, text-like interface that LLM agents can read and act on, handling clicks, forms, scraping, anti-detection and CAPTCHAs. Ships as an open-source Python library plus a hosted cloud API for running browser agents at scale.
Framework for building and orchestrating multi-agent LLM systems, with agent types, tool integration, and human-in-the-loop workflows. Supports multi-agent conversation patterns, multiple LLM providers, and RAG-style tooling for research and prototyping agentic workflows.
A self-hostable virtual companion: a VRM or Live2D character you own that voice-chats in real time, plays Minecraft and Factorio, and runs models in-browser via WebGPU or across 25+ LLM providers like Ollama, OpenAI, and Claude.
Terminal-native AI coding agent that brings conversational, multi-model code assistance into your shell. Integrates with 300+ models and providers, offers an interactive TUI, Zsh ':' plugin, semantic workspace search, and Git-oriented workflows for in-terminal edits, commits, and command suggestions.
A library of specialized AI agents that automate data science steps: loading, cleaning, wrangling, feature engineering, SQL queries, EDA, and ML modeling via H2O and MLflow. Higher-level analyst workflows chain these under a supervisor agent.
Elixir-native autonomous agent framework that models state changes as pure cmd/2 operations and describes side effects with typed directives; integrates with OTP supervision and optional LLM plugins for AI-driven agents.
A 100-line LLM framework built on one graph abstraction of nodes and flows, with zero dependencies and no vendor wrappers. The tiny core composes agents, workflows, and RAG, and is small enough for a coding agent to read and extend on its own.
Simulates a trading firm using LLM agents in specialized roles — fundamentals, sentiment, news and technical analysts feed bull/bear researcher debates, then a trader and risk team decide. Works across US, global and crypto markets and 10+ LLM providers.