Codeless Chatbot Development Using Intent-Based Code Retrieval
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Solution Overview
Problem
Existing chatbot development involves complex software development and redundant programming, necessitating a need for more efficient and streamlined methods and systems.
Innovation Solution
A system utilizing an artificial intelligence neural network model and natural language processing tool to automatically retrieve chatbot computer programming code based on conversation design inputs, implementing an iterative process to develop a chatbot conversation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional chatbot development methods are used, then functional capability can be achieved, but development complexity and time requirements increase significantly
Solution Approach 1:
The system enables developers to build chatbots through self-service interfaces without requiring specialized knowledge of bot framework internals. The visual editor and pre-configured templates allow users to configure chatbots through drag-and-drop operations and form-based interfaces, eliminating the need for manual code writing and complex configuration management.
Solution Approach 2:
The patent introduces an intermediary layer between the developer and the bot framework infrastructure. This intermediary provides abstracted configuration interfaces, pre-built templates, and automated code generation that mediates the complex underlying framework operations, allowing developers to work with simplified concepts while the system handles the complexity of framework integration, deployment, and runtime management.
2Adaptability or versatility
If custom chatbot frameworks are developed, then specific functional requirements can be met, but development time and resource investment increase
Solution Approach 1:
The system performs preliminary actions by providing pre-configured chatbot templates and pre-built functional components that can be directly applied to common scenarios. These templates include pre-defined conversation flows, integration configurations, and business logic that have been prepared in advance, allowing developers to quickly deploy functional chatbots without building everything from scratch.
Solution Approach 2:
The system enables dynamic configuration of chatbot functionality through visual editors and runtime modification capabilities. Developers can dynamically add, remove, or modify conversation flows, integrations, and business logic without requiring framework redevelopment. The system adapts to changing functional requirements through flexible configuration interfaces that allow real-time customization of chatbot behavior and capabilities.
3Reliability
If comprehensive training data is collected and processed, then chatbot intelligence improves, but data processing complexity and time requirements increase
Solution Approach 1:
The system extracts and separates the complex data processing tasks from the developer's workflow by providing built-in, automated data processing capabilities within the configuration environment. The system automatically handles data collection, cleaning, annotation, and training pipeline management as integrated features of the chatbot configuration process, removing the need for developers to implement separate complex data processing infrastructure.
Data Source
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AI summary
Embodiments include implementing an iterative process to automatically develop a chatbot conversation for a conversation designer by receiving a conversation design input of one or more conversation design inputs from the conversation designer, identifying an intent based on the conversation design input, generating a development event based on the intent, retrieving a conversation chat flow from a set of conversation chat flows of a code sheet based on the development event, the code sheet comprising a set of conversations, the set of conversation chat flows, and a set of rules for code retrieval based on the set of conversations and the set of conversation chat flows, retrieving a chatbot computer program code based on the conversation chat flow and the set of rules from the code sheet, and repeating the iterative process until the chatbot computer program code is automatically retrieved from a code repository for each conversation design input.