Open Agent Studio: No-Code RPA Platform Documentation
Open Agent Studio is the first cross platform desktop application built to enable Agentic Process Automation as an open-source alternative and replacement for UIpath and all other RPA tools today.
Download for Windows and Mac at https://openagent.studio .
Windows Install instructions:
https://www.youtube.com/watch?v=8xhFKkD4H-0
We founded Cheat Layer during the pandemic to help people who had lost their jobs and businesses rebuild online using GPT-3. We personally helped hundreds pro bono before turning to AI for help.
In August 2021, we were the first startup to get approved by openAI to sell GPT-3 for automation. We were the first to publish our framework for agents, Project Atlas, in July 2022.
Businesses today are threatening to fire employees and replace them with AI. We believe within 2 years, the AI necessary to generate most of those businesses will be a commodity.
In a future where the AI in your pocket can generate custom, secure, and free versions of all the most expensive business software, we believe there’ll be a level playing field that removes the barrier to build these businesses. More small businesses will build competitive brands through personal relationships, better quality service, and network effects through unique data. We invite you to join us in building this future together faster.
Semantic targets distils the underlying intent of a target to english, so they still work even if services completely change their designs. This enables building robust, future-proof, agents.
Semantic targets can be dynamic or robust based on how strict the language is.
Traditional RPA tools rely heavily on code selectors and computer vision to interact with websites. These selectors are brittle and break whenever the target website updates its design, requiring manual code adjustments.
Open Agent Studio eliminates this issue by using Large Language Models (LLMs) to interpret semantic targets. This allows you to describe what you want to automate in simple English. For example, instead of writing complex code to click a specific button, you can tell Open Agent Studio to “click the button that says ‘Submit’”.
This approach enables robust and adaptable automations that withstand website design changes, making your agents significantly more efficient and reliable.
Open Agent Studio offers a comprehensive suite of features to empower anyone, regardless of their technical skills, to build powerful RPAs.
Installing Open Agent Studio locally, or on-premise, requires an enterprise license. Please contact support@cheatlayer.com for details.
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into the search field”Open Agent Studio provides a number of advanced features for building sophisticated and robust automations.
thread_signals
object within your code to:
thread_signals.notifications.emit
)thread_signals.chat.emit
)graph.global_variables
)Efficiently extract data from websites using various “Magic Scraper” configurations.
Options:
Extracted data can be:
Combine “SemanticDescribe” and “Click” nodes for robust element interaction.
Leverage GPT-4’s capabilities to:
Use variables to pass data between nodes and GPT-4 prompts.
Connect with external platforms and services through API calls using the “Send Data” and “Python Code” nodes.
Automate processes involving:
Easily manage your agents through the intuitive interface.
Features:
Open Agent Studio: No-Code RPA Platform Documentation
Open Agent Studio is the first cross platform desktop application built to enable Agentic Process Automation as an open-source alternative and replacement for UIpath and all other RPA tools today.
Download for Windows and Mac at https://openagent.studio .
Windows Install instructions:
https://www.youtube.com/watch?v=8xhFKkD4H-0
We founded Cheat Layer during the pandemic to help people who had lost their jobs and businesses rebuild online using GPT-3. We personally helped hundreds pro bono before turning to AI for help.
In August 2021, we were the first startup to get approved by openAI to sell GPT-3 for automation. We were the first to publish our framework for agents, Project Atlas, in July 2022.
Businesses today are threatening to fire employees and replace them with AI. We believe within 2 years, the AI necessary to generate most of those businesses will be a commodity.
In a future where the AI in your pocket can generate custom, secure, and free versions of all the most expensive business software, we believe there’ll be a level playing field that removes the barrier to build these businesses. More small businesses will build competitive brands through personal relationships, better quality service, and network effects through unique data. We invite you to join us in building this future together faster.
Semantic targets distils the underlying intent of a target to english, so they still work even if services completely change their designs. This enables building robust, future-proof, agents.
Semantic targets can be dynamic or robust based on how strict the language is.
Traditional RPA tools rely heavily on code selectors and computer vision to interact with websites. These selectors are brittle and break whenever the target website updates its design, requiring manual code adjustments.
Open Agent Studio eliminates this issue by using Large Language Models (LLMs) to interpret semantic targets. This allows you to describe what you want to automate in simple English. For example, instead of writing complex code to click a specific button, you can tell Open Agent Studio to “click the button that says ‘Submit’”.
This approach enables robust and adaptable automations that withstand website design changes, making your agents significantly more efficient and reliable.
Open Agent Studio offers a comprehensive suite of features to empower anyone, regardless of their technical skills, to build powerful RPAs.
Installing Open Agent Studio locally, or on-premise, requires an enterprise license. Please contact support@cheatlayer.com for details.
{{ my_variable }}
into the search field”Open Agent Studio provides a number of advanced features for building sophisticated and robust automations.
thread_signals
object within your code to:
thread_signals.notifications.emit
)thread_signals.chat.emit
)graph.global_variables
)Efficiently extract data from websites using various “Magic Scraper” configurations.
Options:
Extracted data can be:
Combine “SemanticDescribe” and “Click” nodes for robust element interaction.
Leverage GPT-4’s capabilities to:
Use variables to pass data between nodes and GPT-4 prompts.
Connect with external platforms and services through API calls using the “Send Data” and “Python Code” nodes.
Automate processes involving:
Easily manage your agents through the intuitive interface.
Features: