Framework for building offensive and defensive security agents that run real pentests autonomously. Uses a ReACT loop over 300+ models (OpenAI, Anthropic, DeepSeek, local Ollama) with built-in recon, exploitation, and privilege-escalation tools.
React components for building LLM chat and agent interfaces: message bubbles, prompt sets, conversation lists, and sender inputs under a RICH interaction paradigm, plus a streaming Markdown renderer and hooks for wiring UI to model data streams.
Splits autonomous R&D into two cooperating agents: one proposes hypotheses, the other writes and tests code — iterating on quant-finance factors, Kaggle pipelines, and model research. Hits a ~30% medal rate on MLE-Bench, nearly double AIDE's.
Combines drag-and-drop field binding with natural-language prompts so an AI agent derives the transformations behind charts your raw tables can't produce. Reads from databases, files, images, and websites; 30+ chart types and branchable threads.
Register React components with Zod schemas so an LLM agent can select, fill, and stream their props from user requests, turning chat into live interactive UI. Works with OpenAI, Anthropic, Gemini, and Mistral, plus MCP servers like Linear.
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.
Builds real-time multimodal conversational AI agents with voice-assistant examples, VAD, turn detection, RTC/WebSocket transport, avatars, transcription, and edge-device demos.
Provides a Python framework for building generative-AI agents and workflows with Pydantic-style type safety and composable capabilities. Model-agnostic provider support, built-in observability, human-in-the-loop tool approval, and durable execution for production use cases.
Crawls 30+ social platforms (Weibo, Xiaohongshu, Douyin), parses their video and image content, then has five specialized agents debate in a moderated forum to synthesize public-opinion reports. Can fuse public sentiment with a private business database.
Multi-tenant agent harness that makes enterprise knowledge retrievable, graph-reasonable, and deliverable by LLM-powered agents. Integrates RAG + a Milvus-based knowledge graph, LangGraph orchestration, and document parsing for citation-backed answers and graph reasoning; deployable via Docker (requires a compatible LLM API).
Local-first runtime for autonomous AI agents that run on-device and stay model-agnostic across OpenAI, Anthropic, Gemini, Grok, and local models. A plugin system adds chat platforms (Discord, Telegram, X), voice, browser automation, RAG, and wallets.