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An open toolkit for building and benchmarking general virtual agents in the wild

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Would love to see examples for using AgentStudio with some of the common models for autonomous web navigation ([Pix2Act](https://github.com/google-deepmind/pix2act), [MindAct](https://osu-nlp-group.github.io/Mind2Web/), [SeeAct](https://osu-nlp-group.github.io/SeeAct/)) and conversational webnav ([WebLINX models](https://huggingface.co/collections/McGill-NLP/weblinx-models-65c57d4afeeb282d1dcf8434) such as [SLLaMA-WL](https://huggingface.co/McGill-NLP/Sheared-LLaMA-2.7B-weblinx)).

Operate systems initially only provide text-only terminal interfaces, before GUI appears. Terminal is less resource intensive, more lightweight therefore can scale more easily than GUI. Besides, most LLMs are text-only....

tasks:data/grounding/linux/os/tasks.jsonl 2024-07-09 14:28:30,722 ERROR run.py:294 -- [Unhandled Error] ValueError('No prompt added')] 2024-07-09 14:28:30,723 ERROR run.py:295 -- Traceback (most recent call last): File "/home/zsf/codebase/agent-studio/run.py", line 217, in eval_headless agent.reset( File "/home/zsf/codebase/agent-studio/agent_studio/agent/direct_agent.py",...

where is template like tasks.jsonl? task_config_paths: dict = { # "desktop": "data/tasks/filesystem.jsonl", "desktop": "data/grounding/linux/os/tasks.jsonl", }