Alternatives to Apache Maka

LangGraph is LangChain's framework for building stateful, multi-actor AI agent applications as controllable graphs. It models workflows as nodes and edges, enabling cycles, branching, and human-in-the-loop patterns that simple chains cannot express. Features built-in persistence for conversation memory, streaming support, and fault tolerance. Provides fine-grained control over execution flow while supporting single-agent and multi-agent architectures with shared or independent state.

Open-source AI agent platform (formerly OpenDevin) for building developer agents that modify code, run shell commands, browse the web, and call APIs through a composable Python SDK and CLI. OpenHands runs agents in sandboxed Docker containers accessed via SSH, supports Claude/GPT/any LLM, and has solved 50%+ of real GitHub issues in software engineering benchmarks.

Python framework for orchestrating autonomous AI agents that collaborate to accomplish complex tasks. Define agents with specific roles, goals, and backstories, then organize them into crews with sequential or parallel task execution. Supports tool usage (web search, file I/O, API calls), memory, delegation between agents, and human-in-the-loop input. Works with OpenAI, Anthropic, local models, and more. 25K+ GitHub stars. Leading multi-agent framework alongside LangGraph and AutoGen.

smolagents is Hugging Face's lightweight agent framework for building AI agents that can use tools, write and execute code, and collaborate in multi-agent setups. Designed for simplicity with minimal abstractions — agents are just LLMs that write Python code to orchestrate tool calls rather than using JSON-based function calling. Supports any LLM provider, integrates with Hugging Face Hub for sharing tools and agents, and runs with as few as 1,000 lines of core library code.