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I hope to add modifications to the sliced document after Import. I have encapsulated the Handle implementation of QA slicing based on step.
The problem
For example, the following are my prompt words:
I will give you a paragraph of text, study them, and organize the learning results. The requirements are:
1. Ask up to 25 questions.
2. Provide answers to each question.
3. The answer should be detailed and complete, and can include markup elements such as regular text, links, codes, tables, announcements, media links, etc.
4. Return multiple questions and answers in format:
Q1: Question.
A1: Answer.
Q2:
A2:
My text: "" {$input}} ""
In this case, after importing the document, I may need to manually modify the QA extracted by llm. I hope this can be implemented from Kernel Memory because it is compatible with multiple different vector databases
Proposed solution
Add the ability to modify and re vector sliced documents in MemoryServerless
Importance
would be great to have
The text was updated successfully, but these errors were encountered:
Context / Scenario
I hope to add modifications to the sliced document after Import. I have encapsulated the Handle implementation of QA slicing based on step.
The problem
For example, the following are my prompt words:
In this case, after importing the document, I may need to manually modify the QA extracted by llm. I hope this can be implemented from Kernel Memory because it is compatible with multiple different vector databases
Proposed solution
Add the ability to modify and re vector sliced documents in MemoryServerless
Importance
would be great to have
The text was updated successfully, but these errors were encountered: