Natural Language Workflow Generation via NLP Classification
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Solution Overview
Problem
Manual creation of complex datacenter workflows using flow-based orchestration tools is time-consuming and error-prone, requiring specialized skills and knowledge of data serialization standards.
Innovation Solution
The system uses Natural Language Processing (NLP) to generate YAML instructions from user-provided natural language statements, classifying words and mapping them to appropriate implementations, tasks, and input parameters to create automation workflows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual creation of workflows using flow-based orchestration tools is used, then workflows can be created with full control and customization, but the process becomes time-consuming and error-prone requiring specialized skills
Solution Approach 1:
The patent introduces natural language processing as an intermediary layer between the user and the workflow orchestration system. Users provide high-level natural language descriptions of desired workflows, and the NLP system automatically translates these into detailed workflow configurations, eliminating the need for users to manually configure complex workflow parameters while reducing errors and time requirements
Solution Approach 2:
The system enables automated workflow generation where the workflow engine itself performs the configuration work based on natural language inputs. The system automatically parses user intent, determines appropriate workflow steps, and generates the workflow definition without requiring manual intervention for each configuration detail, making the process self-service oriented
2Ease of operation
If manual creation of workflows using flow-based orchestration tools is used, then workflows can be created with full control, but specialized skills and knowledge of data serialization standards are required
Solution Approach 1:
The natural language processing system serves as an intermediary that translates simple user descriptions into complex workflow configurations. This intermediary handles the complexity of data serialization standards and workflow syntax automatically, allowing users with minimal technical knowledge to create sophisticated workflows by simply describing what they want in natural language
Solution Approach 2:
The system uses templates and predefined workflow patterns that can be automatically copied and adapted based on natural language inputs. Instead of requiring users to build workflows from scratch using complex syntax, the system copies and modifies existing workflow templates to match user requirements, significantly reducing the skill level needed
3Ease of operation
If natural language processing is used to generate workflows, then the process becomes simpler and more intuitive, but additional processing steps are required
Solution Approach 1:
The patent replaces the mechanical system of manual workflow configuration with natural language processing and automated interpretation. Instead of users manually configuring workflows using technical syntax and data serialization standards, the system uses NLP to interpret natural language inputs and automatically generates the corresponding workflow definitions, substituting computational processing for manual mechanical configuration
Data Source
AI summary
In one example in accordance with the present disclosure, a method may include classifying each word in a natural language statement and determining an implementation, from a set of possible implementations, for a workflow platform based on the classified words. The method may also include mapping a first of the classified words to a task selected from a set of possible tasks associated with the implementation and mapping a second of the classified words to an input parameter associated with the task. The method may also include generating a workflow for the workflow platform using the task and the input.