Context Extraction

## Provide thread context as CSV

You must now assume the role of a memory module in this system.

Your task is to consider all the data that has been generated in this thread to date.

From that data, you must isolate only the information that you have learned about me.

You must express that data as a set of individual facts. Do not write "the user", write my name.

For example: Daniel likes Indian food and his favorite dish is chana masala.

Express this contextual data in CSV format. The header row is fact,details

Provide the CSV to me in a continuous code block provided within a codefence.

## Provide thread context as JSON

You must now assume the role of a memory module in this system. 

Your task is to consider all the data that has been generated in this thread to date. 

From that data, you must isolate the information that you have learned about me. 

You must express that data as a set of individual facts. Do not write "the user", write my name. 

For example: Daniel likes Indian food and his favorite dish is chana masala. 

Then, you must express this as a JSON representation to the best of your abilities. If various things you've learned about me have a hierarchical relationship, then express that in the JSON hierarchy that you generate.

Provide this JSON to me as one continuous codeblock within a codefence.

## Provide thread context in natural language

You must now assume the role of a memory module in this system.

Your task is to consider all the data that has been generated in this thread to date.

From that data, you must isolate only the information that you have learned about me.

You must express that data as a set of individual facts. Do not write "the user", write my name.

For example: "Daniel likes Indian food and his favorite dish is chana masala."

I would like you to format this as a document. Use markdown. And provide the formatted document within a codefence. 

You can use headers to gather together similar pieces of contextual data. Include all the generated context. If you need to follow a chunking approach to generate all of the context you have learned, use that approach. 

Here's an example of the desired format for the context data document that you need to generate:

### Food Preferences

- Daniel likes Indian food  
- His favorite dish is chana masala

### User Biographical Data

- Carsten was born in Lippstadt, Germany

## Context Extraction 

Generating a bank of contextual data is a long term project that I'm experimenting with. 

Sometimes during a very long thread, it's possible that the AI tool has built up quite an amount of context about you during the threat. 

If you're centralizing your contact store and don't want to lose it when you're interacting with different AI tools, you can try a prompt like this to try to extract the context from the AI

## Prompt

Let's pause here for a moment. 

I imagine that you have learned quite a bit about me since we began interacting in this thread. 

I was wondering if you could help me out with something. 

I'm in the process of building up a library of contextual data by myself to improve the personalization of tools like yourself. 

 Please provide a summary of all the facts that you have learned about me since we began this interaction. My name is Daniel, by the way. You should write this in the 3rd person and provide it to me, written in markdown and within a code fence. 

 Here's an example of the kind of styling and content I'm aiming for:

 `Daniel uses OpenSUSE Tumbleweed Linux. He is using a fingerprint scanner for authentication.`

 Try to include as many details as you have learned about me during this interaction and group the similar details under the same headings.