Chatbot Interface Generation for API Definition Parsing
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Solution Overview
Problem
Non-technical users find it difficult to invoke APIs that interact with networked applications due to the complexity of API calls, which limits their ability to utilize these interfaces effectively.
Innovation Solution
A method and system for generating a chatbot interface for APIs that interact with networked applications, involving the parsing of API definition documents to identify intents and entities, converting this information into a chatbot data structure, and training it to generate a conversation specification, allowing non-technical users to interact with APIs using natural language.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a traditional API interface is used, then the API can interact with networked applications effectively, but non-technical users find it difficult to invoke due to complexity
Solution Approach 1:
A chatbot interface is introduced as an intermediary layer between non-technical users and the underlying API. The chatbot translates natural language user inputs into structured API calls, masking the complexity of the API while preserving its functionality. This mediator handles the conversion process automatically, allowing users to interact with networked applications using simple conversational language rather than complex API syntax.
2Adaptability or versatility
If a user-friendly interface is provided for non-technical users, then API accessibility improves, but the system requires additional interface generation capabilities
Solution Approach 1:
The system automatically generates the chatbot interface by parsing the API definition document itself. Rather than requiring manual creation of interface specifications, the system extracts intent and entity information directly from the existing API documentation and self-generates the corresponding chatbot configuration. This self-service approach enables the system to adapt to new APIs automatically without requiring additional manual interface generation effort.
3Productivity
If the API definition document is automatically parsed to generate chatbot interface, then interface generation efficiency improves, but parsing accuracy requirements increase
Solution Approach 1:
The system performs preliminary parsing of the API definition document during the interface generation phase, extracting intent and entity information before the chatbot is deployed. By conducting this analysis upfront and storing the extracted structures, the system avoids the need for complex real-time parsing during user interactions. This preliminary action allows the use of standard parsing techniques while maintaining high accuracy, as the parsing is performed on well-structured API documentation rather than dynamic user inputs.
Data Source
AI summary
Method and system are provided for generating a chatbot interface for an application programming interface (API) that interacts with networked applications. The method may include: receiving as an input a definition document for an API that interacts with networked applications and parsing the definition document to identify intents and entities and obtain examples of the identified intents and entities. The method may convert the definition document to a chatbot data structure including: extracting the intents and entities and their relationship to objects and fields in the API from the definition document; and training the chatbot data structure with the example intents and entities to generate a conversation specification in the chatbot data structure. The method may then generate a chatbot interface for the API.


