Package: ai-agents
An Open-source Framework for Autonomous Language Agents[📄 Paper][📄 Doc][🌐 Website][🤖️ Demos][🔥 Discord][🔥 Wechat Group]OverviewAgentsis an open-source library/framework for building autonomous language agents. The library is carefully engineered to support important features includinglong-short term memory,tool usage,web navigation,multi-agent communication, and brand new features includinghuman-agent interactionandsymbolic control. WithAgents, one can customize a language agent or a multi-agent system by simply filling in a config file in natural language and deploy the language agents in a terminal, a Gradio interface, or a backend service.One major difference betweenAgentsand other existing frameworks for language agents is that our framework allows users to provide fine-grained control and guidance to language agents via anSOP (Standard Operation Process). An SOP defines subgoals/subtasks for the overall task and allows users to customize a fine-grained workflow for the language agents.📢 Updates[x] 2023.10.7Support LLM-based SOP generation🎉🎉🎉🎉SOP Generation for Multi-Agent[on Huggingface Space]SOP Generation for Single-Agent[on Huggingface Space]We recommend strongly that you can create your OWN DEMO  by clicking the three dots at the top right and selectingDuplicate this Spaceon Huggingface Space.[x] 2023.9.20 Deploy Demos on Huggingface Space[x] 2023.9.12 Official Release💡 HighlightsLong-short Term Memory: Language agents in the library are equipped with both long-term memory implemented via VectorDB + Semantic Search and short-term memory (working memory) maintained and updated by an LLM.Tool Usage: Language agents in the library can use any external tools viafunction-callingand developers can add customized tools/APIshere.Web Navigation: Language agents in the library can use search engines to navigate the web and get useful information.Multi-agent Communication: In addition to single language agents, the library supports building multi-agent systems in which language agents can communicate with other language agents and the environment. Different from most existing frameworks for multi-agent systems that use pre-defined rules to control the order for agents' action,Agentsincludes acontrollerfunction that dynamically decides which agent will perform the next action using an LLM by considering the previous actions, the environment, and the target of the current states. This makes multi-agent communication more flexible.Human-Agent interaction: In addition to letting language agents communicate with each other in an environment, our framework seamlessly supports human users to play the role of the agent by himself/herself and input his/her own actions, and interact with other language agents in the environment.Symbolic Control: Different from existing frameworks for language agents that only use a simple task description to control the entire multi-agent system over the whole task completion process,Agentsallows users to use anSOP (Standard Operation Process)that defines subgoals/subtasks for the overall task to customize fine-grained workflows for the language agents.🛠 InstallationOption 1.  Build from sourcegit clone https://github.com/aiwaves-cn/agents.git
cd agents
pip install -e .Option 2.  Install via PyPIpip install ai-agents📦 Usage🛠️ Generate the config fileOption 1. Fill in the config template manuallyModifyexample/{Muti|Single_Agent}/{target_agent}/config.jsonOption 2. Try ourWebUIfor customizing the config file.Haven't figured out how to write the JSON file yet? Check out ourdocumentation!Option 3. Try Huggingface Space for generating the SOP automatically.SOP Generation for Multi-Agent[on Huggingface Space]SOP Generation for Single-Agent[on Huggingface Space]We recommend strongly that you can create your OWN DEMO  by clicking the three dots at the top right and selectingDuplicate this Spaceon Huggingface Space.🤖️ The Agent HubWe provide anAgentHub, where you can search for interesting Agents shared by us or other developers, try them out or use them as the starting point to customize your own agent. We encourage you to share your customized agents to help others build their own agents more easily! You can share your customized agents by submitting PRs that adds configs and customized codeshere. You can also send us your own config files and codes for customized agents byemail, and we will share your examples and acknowledge your contribution in future updates!📷 Examples and DemosWe have provided exemplar config files, code, and demos for both single-agent and multi-agent systemshere.Web demosNote1.Due to massive traffic,  our online demos may suffer from long queue time and unstable issues.Please follow ourquick start guide) and deploy language agents locally for testing. Or checkout ourwebsite.
2.Software Company is unable to generate executable code online,if you wish to generate executable code directly, please run it locally :)Customer Service AgentDebate[now on  Huggingface Space]Software Company[now on  Huggingface Space]Fiction StudioContributing to AgentsWe appreciate your interest in contributing to our open-source initiative. Please feel free to submit a PR or share your thoughts on how to improve the library in Issues!Note：When running the code, we will download an embedding model, which will cause the code to run slowly. We will adjust it to the API interface laterCurrently, the shopping assistant cannot be used. We will replace the API later. Stay tuned📚 DocumentationPlease check ourdocumentationfor detailed documentation of the framework.⭐ Star HistoryCitationIf you find our repo useful in your research, please kindly consider cite:@misc{zhou2023agents,
      title={Agents: An Open-source Framework for Autonomous Language Agents}, 
      author={Wangchunshu Zhou and Yuchen Eleanor Jiang and Long Li and Jialong Wu and Tiannan Wang and Shi Qiu and Jintian Zhang and Jing Chen and Ruipu Wu and Shuai Wang and Shiding Zhu and Jiyu Chen and Wentao Zhang and Ningyu Zhang and Huajun Chen and Peng Cui and Mrinmaya Sachan},
      year={2023},
      eprint={2309.07870},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}