[Agentic applications](https://langchain-ai.github.io/langgraph/concepts/agentic_concepts/) give an LLM freedom over control flow in order to solve problems. While this freedom can be extremely powerful, the black box nature of LLMs can make it difficult
A Vitest-like CLI for AI agent evaluations. Test your LLM apps with simple, declarative evals.
Much like tests in traditional software, evals are an important part of bringing LLM applications to production. The goal of this package is to help provide a starting point for you to write evals for your LLM applications, from which you can write more c
Rust Agent SDK for building LLM agents
Multi-provider LLM client for Rust — streaming, non-streaming, tool calls, MCP, DeepSeek, OpenAI, Anthropic, Gemini, Codex
A batteries-included Rust toolkit for building intelligent agents with LLM integration, multi-protocol tool support, multi-agent orchestration, and MentisDB-backed durable memory.
A Rust SDK for building AI agents with multi-provider LLM support
Universal transport library for CLI AI agents (Claude Code, Codex, Gemini, OpenCode). Pipe, PTY, ACP (Agent Client Protocol), and Daemon transports.
A Rust client library for the DeepSeek API with support for chat completions, streaming, and tools
Agent runtime with tool-calling loop for AI coding assistants
Simple, effective agent loop with tool execution and event streaming
A lightweight Agent Runtime Kernel for building AI agents in Rust
Rust SDK for orchestrating LLM-powered agents, shared task execution, and teammate coordination
AI coding agent runtime with tool execution
AWS integrations for the Rust deep agents SDK.