SYSTEMS AND METHODS FOR FILTERING TEXT ASSOCIATED WITH LARGE LANGUAGE MODEL (LLM) SYSTEMS
Systems and methods are provided for herein beneficially prevent the disclosure of undesirable text being transferred to and from an LLM system. In one embodiment, a system for processing text of a chat window communicatively linked to a Large Language Model (LLM) system. The system includes a digital memory operable to buffer one or more of a plurality of text strings from a user interacting with the chat window. The system also includes a moderation engine operable to, when the one or more buffered text strings approaches a buffer size of the digital text buffer, apply a plurality of rules to the digital memory, and to trigger an action in the chat window that prevents at least one of the one or more buffered text strings from being transferred to the LLM system.
1 . A method for processing text of a chat window communicatively linked to a Large Language Model (LLM) system, the method comprising:
receiving a plurality of characters from a user interacting with the chat window;
accumulating one or more of the characters in memory to form a text comprising one or more strings;
when at least one of the strings changes length, processing the strings through a moderation engine; and
triggering an action in the chat window via the moderation engine that prevents at least one of the strings from being transferred to the LLM system.
2 . The method of claim 1 , further comprising:
extracting at least one of the strings from the text based on the action, as the user interacts with the chat window; and
transferring remaining strings of the text from the chat window to the LLM system to initiate response processing.
3 . The method of claim 1 , further comprising at least one of:
processing the action to automatically interrupt a session between the user and the chat window; or
processing the action to automatically generate a response to the user highlighting any extracted strings.
4 . The method of claim 1 , further comprising:
processing a response provided by the LLM system through the moderation engine to extract one or more strings from the response.
5 . The method of claim 1 , further comprising:
receiving new characters via interactions of the user with the chat window, resulting in a new text comprising new strings; and
when at least one of the new strings changes length, processing the new strings through the moderation engine to extract at least one of the new strings from the new text, and transferring remaining new strings from the new text to the LLM system for response processing.
6 . The method of claim 1 , further comprising:
concatenating the received plurality of characters without any extracted strings; and
transferring the concatenated plurality of characters to the LLM system to generate a response by the LLM system.
7 . The method of claim 1 , further comprising:
detecting, via the moderation engine, that at least one of the strings comprises at least one of personally identifiable information (PII), personal health information (PHI), or profanity;
extracting the at least one detected string from the text; and
transferring remaining strings of the text from the chat window to the LLM system for response processing.
8 . A non-transitory computer readable medium embodying programmed instructions which, when executed by a processor, are operable for performing a method for processing text of a chat window communicatively linked to a Large Language Model (LLM) system, the method comprising:
receiving a plurality of characters from a user interacting with the chat window;
accumulating one or more of the characters in memory to form a text comprising one or more strings;
when at least one of the strings changes length, processing the strings through a moderation engine; and
triggering an action in the chat window via the moderation engine that prevents at least one of the strings from being transferred to the LLM system.
9 . The computer readable medium of claim 8 , further comprising instructions which, when executed by the processor, are operable for:
extracting at least one of the strings from the text based on the action, as the user interacts with the chat window; and
transferring remaining strings of the text from the chat window to the LLM system to initiate response processing.
10 . The computer readable medium of claim 8 , further comprising instructions which, when executed by the processor, are operable for, at least one of:
processing the action to automatically interrupt a session between the user and the chat window; or
processing the action to automatically generate a response to the user highlighting any extracted strings.
11 . The computer readable medium of claim 8 , further comprising instructions which, when executed by the processor, are operable for:
processing a response provided by the LLM system through the moderation engine to extract one or more strings from the response.
12 . The computer readable medium of claim 8 , further comprising instructions which, when executed by the processor, are operable for:
receiving new characters via interactions of the user with the chat window, resulting in a new text comprising new strings; and
when at least one of the new strings changes length, processing the new strings through the moderation engine to extract at least one of the new strings from the new text, and transferring remaining new strings from the new text to the LLM system for response processing.
13 . The computer readable medium of claim 8 , further comprising instructions which, when executed by the processor, are operable for:
concatenating the received plurality of characters without any extracted strings; and
transferring the concatenated plurality of characters to the LLM system to generate a response by the LLM system.
14 . The computer readable medium of claim 8 , further comprising instructions which, when executed by the processor, are operable for:
detecting, via the moderation engine, that at least one of the strings comprises at least one of personally identifiable information (PII), personal health information (PHI), or profanity;
extracting the at least one detected string from the text; and
transferring remaining strings of the text from the chat window to the LLM system for response processing.
15 . A system for processing text of a chat window communicatively linked to a Large Language Model (LLM) system, the system comprising:
a memory operable to accumulate characters from a user interacting with the chat window to form a text comprising one or more strings; and
a moderation engine operable to, when at least one of the strings changes length, apply a plurality of rules to the strings, and to trigger an action in the chat window that prevents at least one of the one or more strings from being transferred to the LLM system.
16 . The system of claim 15 , wherein the moderation engine is further operable to:
extract at least one of the strings from the text based on the action as the user interacts with the chat window; and
transfer remaining strings of the text from the chat window to the LLM system to initiate response processing.
17 . The system of claim 15 , wherein the moderation engine is further operable to at least one of:
process the action to automatically interrupt a session between the user and the chat window; or
process the action to automatically generate a response to the user highlighting any extracted strings.
18 . The system of claim 15 , wherein the moderation engine is further operable to:
process a response provided by the LLM system through the moderation engine to extract one or more strings from the response.
19 . The system of claim 15 , wherein:
the memory is further operable to accumulate additional characters from interactions of the user with the chat window, resulting in a new text comprising new strings; and
when the one of the new strings changes length, the moderation engine is further operable to process the new strings to extract at least one of the new strings from the new text, and to transfer remaining new strings from the text to the LLM system for response processing.
20 . The system of claim 15 , wherein the moderation engine is further operable to:
detect that at least one of the strings comprises at least one of personally identifiable information (PII), personal health information (PHI), or profanity;
extract the at least one detected string from the text; and
transfer remaining strings of the text from the chat window to the LLM system for response processing.