run-llama/llama-agents

This system is a comprehensive platform for building, deploying, and managing AI agent workflows. It provides a Kubernetes-native control plane and operator to automate the lifecycle of agent deployments, while offering a Python-based runtime for durable, stateful workflow execution with human-in-the-loop capabilities. The architecture supports persistent state management via multiple backends, distributed tracing, and modular CLI tools for development and operations.

This period focused on restructuring the codebase into a monorepo and refactoring the workflow engine to support stateful, serializable contexts and new node types. It also introduced comprehensive examples and tests for workflow servers, clients, and observability, alongside the rebranding of the package to llama-agents.

14 changes

This period focused on building the Llama Agents platform, introducing a new control plane, app server, and Kubernetes operator for managing agent workflows. The work established durable execution, state persistence, and deployment automation, supported by comprehensive test coverage across all new components.

37 changes

run-llama/llama-agents was measured the same way every project in this corpus was: the same rubric, at a pinned commit, with the result published in full. Point the surveyor at a repository you know and see whether you agree with it.