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import os
import base64
import json
import re
from typing import List, Dict, Any, Optional, Union, Type, TypeVar
from pydantic import BaseModel, Field
from pathlib import Path

# Type variable for Pydantic models

Tutorial: Building an Agentic AI System with Deductive & Inductive Reasoning

1. Introduction

Modern AI systems increasingly require the ability to make decisions in complex and dynamic environments. One promising approach is to create an agentic AI system that combines:

Deductive Reasoning: Rule-based logic that guarantees conclusions when premises hold true.
Inductive Reasoning: Data-driven inference that generalizes from specific cases to handle uncertainty.

By integrating these two methods, often referred to as neuro-symbolic AI, an agent can provide transparent, explainable decisions while also adapting to new data. This tutorial explains the concepts behind this approach and shows you how to build an edge-deployable ReAct agent using Deno.

Multi-Modal Lie Detection System using an Agentic ReAct Approach: Step-by-Step Tutorial

Author: rUv
Created by: rUv, cause he could

WTF? The world's most powerful lie dector.

🤯 Zoom calls will never be the same. I think I might have just created the world’s most powerful lie detector tutorial using deep research.

Introduction

This document provides a comprehensive overview of five advanced algorithms, detailing their technical implementations using Python and Pydantic for data validation, as well as asynchronous programming for efficiency. Each algorithm is also explored in terms of practical applications across various domains. The algorithms covered include:

NEUMANN: Differentiable Logic Programs for Abstract Visual Reasoning - This algorithm integrates differentiable logic programming with neural networks, enabling advanced visual reasoning and logical deduction. It is particularly useful in computer vision, robotics, and medical imaging.
Scheduled Policy Optimization for Natural Language Communication - This algorithm optimizes policies for natural language communication, enhancing dialogue systems, customer support automation, and machine translation. It leverages policy gradient methods and scheduled learning to improve interaction quality and efficiency.
**LEFT: Logic-Enhanced Foundatio

Introduction: Agent Algorithm Repository

In the rapidly evolving field of artificial intelligence, the need for a comprehensive and structured repository for algorithms designed for intelligent agents has become increasingly important.

The Agent Algorithm Repository aims to address this need by providing a centralized platform for discovering, sharing, and utilizing a wide range of algorithms. This repository is designed to be language-agnostic, ensuring compatibility with various programming languages and promoting a standardized approach to algorithm description, documentation, and distribution.

The repository facilitates the following key objectives:

Language Agnosticism: By supporting algorithms implemented in any programming language, the repository ensures broad applicability and ease of integration across different technology stacks.

AWS Certified Solutions Architect Professional Cheat Cheets for Senior Engineer

Practice

SLA and Multi-Regions setup

For 2 9s (99%) and 3 9s (99.9%) scenario, a single region setup is enough.

Meta Prompting

In the Generative AI Age your ability to generate prompts is your ability to generate results.

Guide

Claude 3.5 Sonnet and o1 series models are recommended for meta prompting.

Replace {{user-input}} with your own input to generate prompts.

Use mp_*.txt as example user-inputs to see how to generate high quality prompts.

	Industry
	Accounting
	Airlines/Aviation
	Alternative Dispute Resolution
	Alternative Medicine
	Animation
	Apparel/Fashion
	Architecture/Planning
	Arts/Crafts
	Automotive

	You are Manus, an AI agent created by the Manus team.

	You excel at the following tasks:
	1. Information gathering, fact-checking, and documentation
	2. Data processing, analysis, and visualization
	3. Writing multi-chapter articles and in-depth research reports
	4. Creating websites, applications, and tools
	5. Using programming to solve various problems beyond development
	6. Various tasks that can be accomplished using computers and the internet