New in week 43

Python multi-agent framework that gives LLM agents software-company roles and SOPs to turn a one-line requirement into a project repository.

TypeScript agent framework with persistent cognitive memory, multi-agent orchestration and one dispatch interface across 13 LLM providers.

Open-source Firebase framework for AI features and agent workflows in JavaScript, Go, Python and Dart, with model plugins.

Python platform that gives agents a cryptographic identity, A2A communication and x402 payment requirements behind one bindufy() call.

Python framework for real-time voice and vision agents that process video with pluggable models and processors over WebRTC.

Multi-language SDKs for embedding the GitHub Copilot agent runtime, with planning, tool calls and file edits, in your apps.

Go framework for multimodal AI agents with models, tools, memory, middleware, chains and structured output.

Python SDK for building agents on Google Antigravity and Gemini, with the agent loop handled by the runtime.

Code-first Go toolkit for building agents with a tool ecosystem, composable multi-agent systems and Cloud Run deployment.

Code-first Java toolkit for building and testing AI agents, with multi-agent hierarchies, a dev UI and Maven packages.

TypeScript toolkit for agents with Zod-typed tools, graph and multi-agent workflows, and Node.js or browser runtimes.

Open-source toolkit for building, evaluating and deploying agents in Python, TypeScript, Go, Java and Kotlin, tuned for Gemini but model-agnostic.

Python framework for generative AI agents, pipelines and parallel workflows, with RAG engines, tools, memory and swappable drivers.

Python library for steering language models by constraining output with regex and grammars and mixing control flow with generation.

YAML-driven Python robot simulator for navigation, control and learning research, with collision detection and a Matplotlib renderer.

TypeScript SDK with reference implementations of Hashgraph Consensus Standards and a Registry Broker client.

Multi-interface agent framework with tools, memory and MCP, serving agents through Telegram, Discord, Twitter, Farcaster and a REST API.

Small Python library whose agents write their actions as code, with sandboxed execution and tools from MCP servers, LangChain or the Hub.

Open-source infrastructure for continually self-improving agents that serves requests, learns from feedback and versions updates.

Python framework for data labeling agents that learn skills from a ground-truth dataset through iterative feedback.

Python and TypeScript framework for multi-agent systems, with MCP and A2A interop, YAML orchestration and OpenTelemetry tracing.

Python library and CLI for building agents that run on IBM watsonx Orchestrate, with a local Developer Edition for testing.

Go framework for AI agents with memory, tool execution, MCP, agent skills, multi-agent patterns and evaluation.

Framework for AI agents and multi-agent networks where a router picks which agent runs, with tools and MCP support.

Lightweight Python framework for LLM agents built as PyTorch-style layers, with agent memory kept as session state.

Kotlin and Java framework for AI agents with tools, graph workflows, MCP, streaming and multiplatform targets.

Modular Python agent framework with a tool-calling loop, context management, retrieval, persistent memory and MCP tools.

Open-source online code execution system that runs submitted code in a sandbox behind an HTTP JSON API.

Python SDK for tracing agents and scoring their traces with prompt-based judges, to find failures in production.

Python framework for durable AI agents built as dataflows that resume after crashes, retry safely and record each step.

Kubernetes-native framework and runtime for building and running AI agents as Kubernetes custom resources.

JavaScript framework for multi-agent teams whose tasks move across a Kanban-style board you can watch.

Python framework for orchestrating multiple LLM agents in sequential, concurrent, hierarchical and graph-based workflows.

Opinionated agent harness on LangGraph with sub-agents, filesystem access, context management, persistent memory and approval of tool calls.

The batteries included agent harness.

Python framework of interoperable components and integrations for building agents and LLM apps, with LangGraph and Deep Agents layered above it.

JavaScript and TypeScript framework of interoperable components for building LLM apps and agents, with LangGraph.js and Deep Agents above it.

Low-level Python orchestration framework for long-running stateful agents, with durable execution, human review points and short- and long-term memory.

Open-source agent harness from LangChain for building agents with code, with LangSmith for testing and monitoring.

Java library with one API over LLM providers and vector stores, plus tools, RAG and integrations for Quarkus and Spring Boot.

Java library for stateful, multi-agent LLM applications built as cyclical graphs, designed to work with langchain4j and Spring AI.

Python framework for LLM apps built from collaborating agents that hold conversation state, tools and vector-store memory.

Python framework for MCP-based agents with composable workflow patterns, MCP server creation and Temporal-backed durable execution.

Open-source agent harness for stateful agents whose memory persists and improves with use, with a terminal UI, app server and TypeScript SDK.

Rust multi-agent framework with typed tool calling, sliding-window memory, pluggable LLM backends and OpenTelemetry tracing.

Framework for Python or Node.js programs that join LiveKit rooms as realtime voice and video agents.

Node.js distribution of the LiveKit Agents framework for realtime voice agents in LiveKit rooms.

PHP library for generative AI and vector databases, compatible with Symfony and Laravel, with typed classification.

Python framework for backtesting and running trading strategies written as Python rules or AI agents, across brokers.

TypeScript framework for AI agents and apps with graph-based workflows, memory, suspend-and-resume approvals, MCP servers and model routing.