coderplay

Apache Flink Agents Architecture

Apache Flink Agents is an Agentic AI framework built on top of Apache Flink that provides a distributed, real-time, event-driven architecture for building intelligent agent systems. This document provides a comprehensive overview of the architecture, components, and design patterns used in the framework.

Table of Contents

1. Overview
2. Core Architecture
3. Module Structure
4. Event-Driven Architecture

coderplay

Flink Checkpointing: End-to-End Guide

Table of Contents

1. Overview
2. Architecture Components
3. Checkpoint Lifecycle
4. Barrier Mechanism
5. State Snapshotting
6. Recovery Process
7. Configuration

coderplay

Flink State Types

Flink supports 8 main state types organized in a hierarchy. Here's the complete list with detailed explanations:

1. Keyed State Types (for KeyedStream)

Core State Types:

1. ValueState<T>

• Stores a single value per key

coderplay

Mem0 Architecture Documentation

Table of Contents

1. Overview
2. High-Level Architecture
3. Core Components
4. Data Flow
5. Storage Architecture
6. Memory Levels & Scoping
7. Configuration System

coderplay

Agno Framework Design Document

Table of Contents

1. Introduction
2. Architectural Philosophy
3. High-Level System Architecture
4. Agent Architecture
5. Agentic Context Architecture
6. Agent History Management

coderplay

WrenAI Architecture Documentation

Overview

WrenAI is a comprehensive AI-powered data modeling and query generation platform that transforms natural language questions into SQL queries. The system consists of multiple interconnected services that work together to provide intelligent data analysis capabilities.

High-Level Architecture

graph TB

coderplay

How AutoGPT Implements Observe → Reasoning → Action → Observe Feedback Loops

AutoGPT implements a sophisticated feedback loop system through its interaction loop architecture that closely follows the observe-reasoning-action pattern. Here's a detailed breakdown:

1. OBSERVE Phase - Information Gathering

Previous Action Results

AutoGPT observes the results of previous actions through the ActionResult system:

coderplay

{  
  "ociVersion": "1.0.1-dev",  
  "process": {  
  "terminal": true,  
  "user": {  
  "uid": 0,  
  "gid": 0  
  },  
  "args": [  
      "/bin/bash"  

coderplay

import com.carrotsearch.randomizedtesting.RandomizedRunner;
import org.jboss.byteman.contrib.bmunit.BMRule;
import org.jboss.byteman.contrib.bmunit.BMRules;
import org.jboss.byteman.contrib.bmunit.BMRunnerUtil;
import org.jboss.byteman.contrib.bmunit.BMScript;
import org.jboss.byteman.contrib.bmunit.BMScripts;
import org.jboss.byteman.contrib.bmunit.BMUnit;
import org.jboss.byteman.contrib.bmunit.BMUnitConfig;
import org.jboss.byteman.contrib.bmunit.BMUnitConfigState;

coderplay

$ sudo   /usr/local/sbin/ply -D  -c 'kprobe:vfs_read{ printf("%v: %v\n", comm(), arg(0)); }'
symtable:
ast:
`-> <script> (type:script/none size:0x0 loc:nowhere)
    `-> kprobe:vfs_read (type:probe/none size:0x0 loc:nowhere)
        `-> <auto>.printf (type:call/none size:0x0 loc:reg/0)
            |-> "%v: %v\n"(type:str/str size:0x8 loc:virtual)
            `-> <rec> (type:rec/none size:0x20 loc:stack/-0x20)
                |-> 0 (type:int/int size:0x8 loc:stack/-0x20)