Open Computer Agent Description
The Open Computer Agent is an AI assistant that operates within a web browser, created by Hugging Face, designed to automate tasks like web browsing, filling out forms, and retrieving information. Utilizing advanced vision-language models such as Qwen-VL, it mimics mouse and keyboard actions, allowing it to perform a variety of functions, from booking tickets to checking operating hours and navigating to locations. The agent can effectively identify and engage with various elements on web pages by analyzing their image coordinates. As part of the smolagents initiative by Hugging Face, it prioritizes both flexibility and transparency, providing an open-source framework for developers to explore, alter, and expand for specialized uses. Although still in the developmental phase and encountering certain obstacles, this agent signifies a pioneering shift toward AI functioning as a proactive digital assistant, adept at executing online tasks independently without requiring direct user involvement. Furthermore, its ongoing evolution may lead to even greater possibilities in automating complex web interactions in the future.
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Sendbird
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Sendbird’s AI Agent Platform enables businesses to automate customer support across a wide range of channels, including SMS, web, mobile apps, and social media. This solution leverages AI to provide proactive, continuous support by anticipating customer needs and engaging them on their preferred platforms. Businesses can build and manage their own AI agents with an easy-to-use interface, ensuring smooth customer interactions. The platform integrates seamlessly with existing systems, providing businesses with insights into customer conversations, improving agent performance, and offering reliable support in high-traffic environments.
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Agent S2
Agent S2 represents a versatile, expandable, and modular framework for computer-based agents, created by Simular. These autonomous AI agents are capable of direct interaction with graphical user interfaces (GUIs) across desktops, mobile devices, web browsers, and various software applications, effectively emulating human control through mouse and keyboard inputs. Building on the foundational aspects of the original Agent S framework, Agent S2 boosts both performance and modularity by incorporating cutting-edge frontier foundation models alongside specialized models. It has achieved remarkable success, particularly in outperforming prior benchmarks in evaluations such as OSWorld and AndroidWorld. Central to its design are several key principles, which include proactive hierarchical planning that allows the agent to adapt its strategies dynamically after completing each subtask; visual grounding that facilitates accurate GUI interaction through the use of raw screenshots; an enhanced Agent-Computer Interface (ACI) that assigns intricate tasks to specialized modules; and an agentic memory system designed to support continuous learning from past experiences. This innovative approach not only improves efficiency but also ensures that agents can better adapt to the ever-evolving technological landscape.
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Qwen2.5-VL
Qwen2.5-VL marks the latest iteration in the Qwen vision-language model series, showcasing notable improvements compared to its predecessor, Qwen2-VL. This advanced model demonstrates exceptional capabilities in visual comprehension, adept at identifying a diverse range of objects such as text, charts, and various graphical elements within images. Functioning as an interactive visual agent, it can reason and effectively manipulate tools, making it suitable for applications involving both computer and mobile device interactions. Furthermore, Qwen2.5-VL is proficient in analyzing videos that are longer than one hour, enabling it to identify pertinent segments within those videos. The model also excels at accurately locating objects in images by creating bounding boxes or point annotations and supplies well-structured JSON outputs for coordinates and attributes. It provides structured data outputs for documents like scanned invoices, forms, and tables, which is particularly advantageous for industries such as finance and commerce. Offered in both base and instruct configurations across 3B, 7B, and 72B models, Qwen2.5-VL can be found on platforms like Hugging Face and ModelScope, further enhancing its accessibility for developers and researchers alike. This model not only elevates the capabilities of vision-language processing but also sets a new standard for future developments in the field.
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Pricing
Pricing Starts At:
Free
Free Version:
Yes
Company Details
Company:
Hugging Face
Year Founded:
2016
Headquarters:
United States
Website:
huggingface.co/spaces/smolagents/computer-agent
Media
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Product Details
Platforms
Web-Based
Types of Training
Training Docs
Customer Support
Online Support
Open Computer Agent Features and Options
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