--- license: apache-2.0 datasets: - ai2lumos/lumos_web_agent_plan_iterative language: - en tags: - language-agent - web-agent - reasoning - planning --- # 🪄 Agent Lumos: Unified and Modular Training for Open-Source Language Agents

🌐[Website]   📝[Paper]   🤗[Data]   🤗[Model]   🤗[Demo]  

We introduce 🪄**Lumos**, Language Agents with **Unified** Formats, **Modular** Design, and **Open-Source** LLMs. **Lumos** unifies a suite of complex interactive tasks and achieves competitive performance with GPT-4/3.5-based and larger open-source agents. **Lumos** has following features: * 🧩 **Modular Architecture**: - 🧩 **Lumos** consists of planning, grounding, and execution modules built based on LLAMA-2-7B/13B and off-the-shelf APIs. - 🤗 **Lumos** utilizes a unified data format that encompasses multiple task types, thereby enabling the developed agent framework to conveniently support a range of interactive tasks. * 🌍 **Diverse Training Data**: - 🌍 **Lumos** is trained with ~56K diverse high-quality subgoal/action annotations from ground-truth reasoning steps in existing benchmarks with GPT-4. - ⚒️ **Lumos** data can be instrumental for future research in developing open-source agents for complex interactive tasks. * 🚀 **Competitive Performance**: - 🚀 **Lumos** is comparable or even beats **GPT-series** agents on web/complex QA tasks Mind2Web and HotpotQA, and **larger open agents** on math and multimodal tasks. - 🚀 **Lumos** exceeds contemporaneous agents that have been **fine-tuned** with in-domain HotpotQA, Mind2Web and ScienceQA annotations, such as **FiReAct**, **AgentLM**, and **AutoAct**. - 🚀 **Lumos** performs better than open agent baseline formulations including **chain-of-thoughts** and **integrated** training. - 🚀 **Lumos** surpasses larger open LLM agents and domain-specific agents on unseen tasks, WebShop and InterCode_SQL. ## Model Overview `lumos_web_agent_plan_iterative-13B` is a **planning** module checkpoint finetuned on **web agent** task in **Lumos-Iterative (Lumos-I)** formulation. The training annotation is shown below: | Training Data | Number | |---|---| |[`lumos_web_agent_plan_iterative-13B`](https://huggingface.co/datasets/ai2lumos/lumos_web_agent_plan_iterative-13B)|1009| ## Citation If you find this work is relevant with your research, please feel free to cite our work! ``` @article{yin2023lumos, title={Agent Lumos: Unified and Modular Training for Open-Source Language Agents}, author={Yin, Da and Brahman, Faeze and Ravichander, Abhilasha and Chandu, Khyathi and Chang, Kai-Wei and Choi, Yejin and Lin, Bill Yuchen}, journal={arXiv preprint arXiv:2311.05657}, year={2023} } ```