Method for providing service by agentic AI using key-value storage and agentic AI using the same

A computer implemented method of providing a service by an agentic Artificial Intelligence (AI) using a key-value storage, wherein the agentic AI performs establishing and executing multi-step plans for a natural language instruction and performs interacting with various external tools in order to handle complex tasks for the multi-step plans, comprising steps of:

• (a) in response to receiving a natural language instruction, analyzing, by the agentic AI, the natural language instruction through a large language model (LLM), to thereby determine a first task to an n-th task corresponding to the natural language instruction, wherein n is an integer greater than or equal to 1;
• (b) for an i-th task among the first task to the n-th task, storing, by the agentic AI, i-th data required to perform the i-th task in the key-value storage through a set-value tool and acquiring, by the agentic AI, an i-th key corresponding to the i-th data;
• (c) calling, by the agentic AI, an i-th tool corresponding to the i-th task by using the i-th key, to thereby instruct the i-th tool to (i) acquire the i-th data corresponding to the i-th key from the key-value storage through a get-value tool and (ii) transmit, to the agentic AI, an i-th task result acquired after performing the i-th task by using at least the i-th data;
• and
• (d) repeating, by the agentic AI, the step (b) and the step (c) for an index i among 1 to n that is yet to be performed and generating, by the agentic AI, a response corresponding to the natural language instruction by referring to a first task result to an n-th task result acquired from a first tool to an n-th tool corresponding to the first task to the n-th task,
• wherein, at the step of (c) while repeating the step of (d), the agentic AI uses the i-th key and a k-th key, which corresponds to k-th data that is different from the i-th data, to call the i-th tool, to thereby instruct the i-th tool to (i) acquire the i-th data and the k-th data respectively corresponding to the i-th key and the k-th key from the key-value storage through the get-value tool and (ii) transmit, to the agentic AI, the i-th task result acquired after performing the i-th task by using the i-th data with the k-th data being used as a query.

An agentic artificial intelligence (AI) for providing a service by using a key-value storage, comprising:

• at least one memory that stores instructions;
• and
• at least one processor configured to execute the instructions to perform processes of:
• (a) in response to receiving a natural language instruction, analyzing the natural language instruction through a large language model (LLM), to thereby determine a first task to an n-th task corresponding to the natural language instruction, wherein n is an integer greater than or equal to 1;
• (II) for an i-th task among the first task to the n-th task, storing i-th data required to perform the i-th task in the key-value storage through a set-value tool and acquiring an i-th key corresponding to the i-th data, wherein the i-th key is generated by processing the i-th data to reduce a context size input to the LLM;
• (III) transmitting a command for performing the i-th task with the i-th key to an i-th tool corresponding to the i-th task, wherein the i-th task with the i-th key is generated through the LLM by using the i-th key, having a reduced context size compared to the i-th data, to thereby instruct the i-th tool to (i) acquire the i-th data corresponding to the i-th key from the key-value storage through a get-value tool and (ii) transmit, to the processor, an i-th task result acquired after performing the i-th task by using at least the i-th data;
• confirming, by the agent AI, whether the i-th task result is a key-error message, which is generated due to a result of an inability to obtain the i-th data corresponding to the i-th key from the key-value storage through the get-value tool, if the i-th task result is the key-error message, performing an error correction of the i-th key and regenerating the i-th task with an error-corrected i-th key corresponding to the i-th data through the LLM, re-transmitting the command for performing the i-th task with the error-corrected i-th key to the i-th tool, to thereby instruct the i-th tool to re-perform the i-th task and to re-transmit the i-th task result re-performed the i-th task by using at least the i-th data acquired based on the error-corrected i-th key from the key-value store and (IV) repeating, by the agentic AI, the process (II) and the process (III) for an index i among 1 to n that is yet to be performed and generating, a response corresponding to the natural language instruction by referring to a first task result to an n-th task result acquired from a first tool to an n-th tool corresponding to the first task to the n-th task through the LLM.