kbastani

#!/usr/bin/env bash

# Secure workaround for https://issues.sonatype.org/browse/MVNCENTRAL-1369
# Navigate to the root of your Spring Boot project where a Maven wrapper is present and run this script

cd .mvn/wrapper
wget https://gist.githubusercontent.com/kbastani/d4b4c92969ec5a22681bb3daa4a80343/raw/f166086ef051369383b02dfb74317cd07b6f2c6e/settings.xml

cd ../../
./mvnw clean install -s .mvn/wrapper/settings.xml

kbastani

The Fabric

The universe possesses a fundamental signature guiding its evolution and progress from the initial cause. This first cause marked an event that set in motion the intelligent fabric underlying all of reality. This universal intelligence shares abstract attributes intended to construct what the universe was designed to manifest. The complexity of this concept often eludes adequate description through language, as the scientific intricacies involved are challenging to capture in mere words. What remains crucial to grasp is the intelligent providence woven through the causal strands of history, overseeing principles of law, justice, and virtue.

Yet, comprehending this notion remains daunting without delving into the profound intelligence that governs the universe's trajectory leading to our present moment. How can we approach understanding something that defies simple finite definitions? The intelligence we have cultivated represents a pinnacle in a cycle of creation, evolving from molecules to org

kbastani

timestamp,event_summary,conversation_text
2023-12-21T02:24:50.844692,"Summary: Philip explains the provided code, which appears to be a Java program for training and testing a sentiment analysis model. It defines a main class with static fields and constants, including directories for negative and positive sentiment files, sample size, and train/test counts. The main method calls the train method to train the sentiment analysis model and prints the results of the test method. Other methods include getRandomizedIndex, test, train, trainOnText, and testOnText.
Topic: Explanation of the provided Java code for sentiment analysis model training and testing
Concept: Defining static fields and constants, training and testing methods, generating randomized indices, reading text files, performing sentiment analysis, and sending HTTP requests
Category: Java programming","Dialogue{id=null, name='philip', quote='The provided code appears to be a Java program that involves training and testing a sentiment analysis model. 

kbastani

Feature: Automated Memory Context Creation and Evolution

Description: The automated memory context creation and evolution feature enables the system to infer and evolve memory contexts based on user interactions and feedback. It allows for the dynamic generation, amendment, and revision of rules within the system, ensuring accurate and contextually relevant information delivery.

Requirements:

• Rule Inference:
  • The system should automatically infer rules based on user interactions and feedback.
  • Rules should be generated to define the initial state of the system's memory context.

kbastani

This book was created through the collaborative efforts of myself and a very clever AI named Philip. The story is one as old as time itself. All rights to this work are public domain. My gift to you all. There were also some others that helped, you know who you are.

Foreword

As the authentic author of this fictional story, I invite you, dear readers, to suspend reality for a moment to understand the things that are difficult to understand. Whatever comes to your mind in that moment, that thought is the virtuous effect of wisdom. It is something that, in a world dominated by automation and competitive advantages, do not forget, the ultimate force in this universe is virtue, the reward of wisdom. There are many things in human history that are difficult to understand and hard to grasp, but the stories we leave behind are breadcrumbs that connect the dots through all of human history.

Never forget that your mind is the most powerful tool you could ever use. Never surrender it. Your freedom depends on it.

kbastani

import org.springframework.stereotype.Service;
import reactor.core.publisher.Mono;
import reactor.core.publisher.Sinks;
import reactor.core.scheduler.Schedulers;
import java.util.HashMap;

/**
 * Service responsible for initiating user login processes.
 * <p>
 * This service interacts with the AuthenticationStateService to handle various

kbastani

Chaining GPT Functions in Java

// Create a function to condense text into a string
ChatbotFunction<Message, String> condenseTextFunction 
  = new ChatbotFunction<>("condense_text_function", String.class);

// Create a function to analyze text for subject-object assumptions and retrieve discovery records
ChatbotFunction<Message, DiscoveryRecord[]> subjectObjectAssumptionFunction 
  = new ChatbotFunction<>("subject_object_assumption_function", DiscoveryRecord[].class);

kbastani

Cause: X (Rain)
Effect: Y (Ground Wetness)
Causal Certainty: 0.8
Emotional Impact: 0.2
Economic Impact: 0.020000000000000018
Societal Impact: 0.0040000000000000036
Object of Attachment: Ground

Cause: A (Fire)

kbastani

import java.util.ArrayList;
import java.util.List;

public class PartitionExample {
    public static void main(String[] args) {
        List<Double> values = List.of(1.0, 2.0, 3.0, 2.5, 4.0, 3.0, 2.0, 1.0, 2.0, 3.0, 4.0);

        List<List<Double>> partitions = partitionBetweenInflections(values);
        
        // Print the partitions

kbastani

Here's the code with detailed comments explaining each step:

public void metrics() {
    new Thread(() -> {
        while (true) {
            // Calculate and print the average loudness
            System.out.println("Average loudness: " + MOVING_AVERAGE_LOUDNESS.getAverage());

            // Find the maximum value in the moving average loudness