Adaptive API integration framework with automated scenario simulation and self-healing mechanism

1 . A method for application programming interface (API) management of information retrieval, comprising:

generating descriptions for each API on an API list, the generating the descriptions comprising:

executing queries on the API list based on API documentation or API specifications;

executing natural language processing to extract input examples and corresponding meanings, and output examples and corresponding meanings for the each API in the API list; and

generating the descriptions for the each API on the API list from the input examples and corresponding meanings and the output examples and corresponding meanings;

generating an API execution scenario that defines ones of the APIs in the API list to execute, the generating the API execution scenario comprising providing the generated descriptions and user query history to a machine learning algorithm configured to extract similar APIs to the user query history to generate the API execution scenario comprising the extracted similar APIs; and

executing the generated API execution scenario in response to user queries facilitated by user query handling.

2 . The method of claim 1 , wherein the generated descriptions and the generated API execution scenario are dynamically updated in response to modifications or additions to the API list.

3 . The method of claim 1 , wherein the generating the descriptions comprises:

comparing the input examples and the output examples of the each API in the API list to identify APIs in the API list having similar values to the input examples and the output examples; and

grouping the identified APIs as related APIs.

4 . The method of claim 3 , wherein the generating the API execution scenario comprises utilizing the grouped related APIs, executing reinforcement learning models trained on past execution patterns to determine dependencies between the grouped related APIs.

5 . The method of claim 1 , wherein the generating the API execution scenario comprises determining a combination of ones of the extracted similar APIs and execution order from the ones of the extracted similar APIs to generate the API execution scenario.

6 . The method of claim 5 , wherein the generating the API execution scenario comprises referencing the user query history for success rates and execution times to determine the combination of the ones of the extracted similar APIs.

7 . The method of claim 1 , further comprising executing a self-correction process comprising:

upon detecting an anomaly from monitoring API execution status:

identifying APIs from the executed API execution scenario causing the anomaly; and

generating another API execution scenario that omits the identified APIs causing the anomaly for the execution.

8 . The method of claim 1 , further comprising facilitating the user query handling, the facilitating the user query handling comprising recording user queries, query execution results, execution logs, and success/failure information as the user query history.

9 . A system for application programming interface (API) management of information retrieval, comprising:

a processor, configured to:

generate descriptions for each API on an API list, the generating the descriptions by:

executing queries on the API list based on API documentation or API specifications;

executing natural language processing to extract input examples and corresponding meanings, and output examples and corresponding meanings for the each API in the API list; and

generating the descriptions for the each API on the API list from the input examples and corresponding meanings and the output examples and corresponding meanings;

generate an API execution scenario that defines ones of the APIs in the API list to execute, by providing the generated descriptions and user query history to a machine learning algorithm configured to extract similar APIs to the user query history to generate the API execution scenario comprising the extracted similar APIs; and

execute the generated API execution scenario in response to user queries facilitated by user query handling.

10 . The system of claim 9 , wherein the generated descriptions and the generated API execution scenario are dynamically updated in response to modifications or additions to the API list.

11 . The system of claim 9 , wherein the processor is configured to generate the descriptions by:

comparing the input examples and the output examples of the each API in the API list to identify APIs in the API list having similar values to the input examples and the output examples; and

grouping the identified APIs as related APIs.

12 . The system of claim 11 , wherein the processor is configured to generate the API execution scenario by utilizing the grouped related APIs, executing reinforcement learning models trained on past execution patterns to determine dependencies between the grouped related APIs.

13 . The system of claim 9 , wherein the processor is configured to generate the API execution scenario by determining a combination of ones of the extracted similar APIs and execution order from the ones of the extracted similar APIs to generate the API execution scenario.

14 . The system of claim 13 , wherein the processor is configured to generate the API execution scenario by referencing the user query history for success rates and execution times to determine the combination of the ones of the extracted similar APIs.

15 . The system of claim 9 , wherein the processor is further configured to execute a self-correction process comprising:

upon detecting an anomaly from monitoring API execution status:

identifying APIs from the executed API execution scenario causing the anomaly; and

generating another API execution scenario that omits the identified APIs causing the anomaly for the execution.

16 . The system of claim 9 , wherein the processor is configured to facilitate the user query handling, by recording user queries, query execution results, execution logs, and success/failure information as the user query history.