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beeai framework

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Basic Information

BeeAI Framework is an open-source developer toolkit for building production-ready intelligent agents and multi-agent systems in Python and TypeScript. It provides libraries, examples, and starter templates to create autonomous agents that can reason, take actions, collaborate and solve complex tasks. The repo supplies modules for agent definitions, workflow orchestration, backend integrations to LLM providers, tool plugins, retrieval-augmented generation, memory strategies, observability, serving agents over protocols, caching and serialization for persistence. The project includes example workflows and language-specific starters to accelerate onboarding. It is maintained under an Apache 2.0 license and developed within the Linux Foundation AI & Data community. The README and examples show how to compose agent roles, connect tools and providers, run multi-agent workflows, and host agents with protocol support and integrations that help developers assemble end-to-end agent systems.

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App URL
https://github.com/i-am-bee/beeai-framework
Github Repository
https://github.com/i-am-bee/beeai-framework/blob/main/README.md

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App Details

Features
The framework exposes modular capabilities aimed at multi-agent development: agent construction for reasoning and action, workflow orchestration to coordinate multiple agents and execution flows, and a Backend module that standardizes connections to different LLM providers. Tools extend agents with web search, weather, code execution and other external capabilities. RAG support includes document processing and vector stores for retrieval-augmented generation. Templates enable dynamic prompts with enhanced Mustache syntax. Memory modules provide flexible conversation history strategies. Observability features include event handling, logging and error management. Serve functionality allows hosting agents with protocol integrations such as A2A and MCP. Additional utilities include intelligent caching to reduce cost and serialization to persist agent state. The repo provides Python and TypeScript versions and multiple examples to demonstrate these features.
Use Cases
BeeAI Framework helps developers accelerate building, testing and deploying autonomous agent systems by providing unified building blocks and real examples. It simplifies provider integration so teams can swap or configure LLM backends through a common interface and supports tools and RAG to enrich agent capabilities with external data and document retrieval. Workflow orchestration lets developers define multi-step collaborative agents with roles and expected outputs, while memory and serialization help preserve state across sessions. Observability, events and error handling improve debugging and monitoring of agent behavior. Serving and protocol integrations enable deploying agents in production with supported communication protocols. Starters, contribution guides and example projects reduce setup time and promote community contributions, making it easier to iterate on agent designs and run repeatable experiments.

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