Orchestrates low-code multi-agent teams that plan, research, code and deliver results to Telegram, Discord, and WhatsApp. Includes handoffs, guardrails, memory and RAG, and integrates 100+ LLM providers via MCP for production-ready agent workflows.
Runs coding agents and automations from a self-hosted developer control center, with local, remote, cloud, and ACP-compatible backends for managed engineering workflows.
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.
Hands-on coding tutorial series for large language models with slides and runnable notebooks covering fine-tuning, prompting, RLHF, safety, steganography, watermarking, multimodal models, GUI agents, and deployment. Community-maintained, free course materials for students and researchers.
Turns any website into clean markdown, structured JSON, or screenshots through a single API — handling JavaScript rendering, rotating proxies, rate limits, and full-site crawling so LLM apps get web data without running scraping infrastructure.
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.
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.
aisuite is a lightweight Python library that provides a unified API for working with multiple Generative AI providers. It supports models from OpenAI, Anthropic, Google, Hugging Face, AWS, Cohere, Mistral, Ollama, and others—abstracting away SDK differences, authentication details, and parameter variations. Modeled after OpenAI’s API style, it enables developers to build LLM-based or agentic applications across providers with minimal setup.