Agentic Frameworks

Open source toolkit from Google for building, evaluating, and deploying AI agents. Model-agnostic and optimized for Gemini, with multi-agent orchestration, tools, and tight Vertex AI integration.

High-performance, full-stack framework for building multi-agent systems with memory, knowledge, and reasoning. Model-agnostic with built-in tools, structured outputs, and a path to production (formerly Phidata).

Multi-agent conversation framework enabling agents to chat with each other to solve tasks. Supports customizable agents, human participation, and diverse conversation patterns.

Role-based multi-agent framework where you define agents with specific roles, goals, and backstories. Agents collaborate to complete complex tasks through delegation and tool use.

Framework for building stateful, multi-agent applications as graphs. Supports cycles, persistence, human-in-the-loop, and streaming. The agent orchestration layer of the LangChain ecosystem.

Data framework for building LLM and agent applications over your own data. Provides data connectors, indexing, retrieval, and agent workflows for production RAG and knowledge assistants.

Lightweight Python SDK for building agentic AI apps. Features agent handoffs, guardrails, tracing, and tool integration with a minimal abstraction layer over the OpenAI API.

Agent framework built on Pydantic for type-safe AI applications. Structured outputs, dependency injection, and model-agnostic design from the team behind Pydantic and FastAPI.

Minimalist agent library focused on code agents that write and execute Python. Simple API with tool calling, multi-step reasoning, and tight Hugging Face Hub integration.