Build production-ready multi-agent systems in Python or TypeScript.
Latest updates
| Date | Language | Update Description | | ---------- | ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | 2025/08/25 | Python | 🚀 ACP is now part of A2A under the Linux Foundation! 👉 Learn more | | 2025/06/03 | Python | Release experimental Requirement Agent. | | 2025/05/15 | Python | New protocol integrations: ACP and MCP. | | 2025/02/19 | Python | Launched Python library alpha. See getting started guide. | | 2025/02/07 | TypeScript | Introduced Backend module to simplify working with AI services (chat, embedding). | | 2025/01/28 | TypeScript | Added support for DeepSeek R1, check out the Competitive Analysis Workflow example. | | 2025/01/09 | TypeScript | Introduced Workflows, a way of building multi-agent systems. Added support for Model Context Protocol. | | 2024/12/09 | TypeScript | Added support for LLaMa 3.3. See multi-agent workflow example using watsonx or explore other available providers. | | 2024/11/21 | TypeScript | Added an experimental Streamlit agent. |
For a full changelog, see our releases page.
What is BeeAI Framework?
BeeAI Framework is a comprehensive toolkit for building intelligent, autonomous agents and multi-agent systems. It provides everything you need to create agents that can reason, take actions, and collaborate to solve complex problems.
[!TIP] Get started quickly with the beeai-framework-py-starter [Python] or beeai-framework-ts-starter [TypeScript] template.
Key Features
| Feature | Description | | ------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | 🤖 Requirement Agent | Create predictable, controlled behavior across different LLMs by setting rules the agent must follow. | | 🤖 Agents | Create intelligent agents that can reason, act, and adapt | | 🔌 Backend | Connect to any LLM provider with unified interfaces | | 🔧 Tools | Extend agents with built in tools (web search, weather, code execution, and more) or custom tools | | 🔍 RAG | Build retrieval-augmented generation systems with vector stores and document processing | | 📝 Templates | Build dynamic prompts with enhanced Mustache syntax | | 🧠 Memory | Manage conversation history with built in memory strategies | | 📊 Observability | Monitor agent behavior with events, logging, and robust error handling | | 🚀 Serve | Host agents in servers with support for multiple protocols such as A2A and MCP | | 💾 Cache | Optimize performance and reduce costs with intelligent caching | | 💿 Serialization | Save and load agent state for persistence across sessions | | 🔄 Workflows | Orchestrate multi-agent systems with complex execution flows |
Quickstart
Installation
To install the Python library:
pip install beeai-framework
To install the TypeScript library:
npm install beeai-framework
Multi-Agent Example
import asyncio
from beeai_framework.agents.requirement import RequirementAgent
from beeai_framework.agents.requirement.requirements.conditional import ConditionalRequirement
from beeai_framework.backend import ChatModel
from beeai_framework.errors import FrameworkError
from beeai_framework.middleware.trajectory import GlobalTrajectoryMiddleware
from beeai_framework.tools import Tool
from beeai_framework.tools.handoff import HandoffTool
from beeai_framework.tools.search.wikipedia import WikipediaTool
from beeai_framework.tools.think import ThinkTool
from beeai_framework.tools.weather import O