README.md

---
title: Talk to your Multi-Agentic Architect System
emoji: 👁
colorFrom: purple
colorTo: green
sdk: docker
pinned: false
license: mit
---


# Title

Empower people with ability to harness the value of Enterprise Architecture through Generative AI to positively impact individuals and organisations.\n


## Overview

`Trigger`: How disruptive may Generative AI be for Enterprise Architecture Capability (People, Process and Tools)? \n
`Motivation`: Master GenAI while disrupting Enterprise Architecture to empower individuals and organisations with ability to harness EA value and make people lives better, safer and more efficient. \n
`Ability`: Exploit my carrer background and skillset across system development, business accumen, innovation and architecture to accelerate GenAI exploration. \n\n

> That's how the `EA4ALL-Agentic system` was born and ever since continuously evolving.

## Benefits

`Empower individuals with Knowledge`: understand and talk about Business and Technology strategy, IT landscape, Architectue Artefacts in a single click of button. \n
`Increase efficiency and productivity`: generate a documented architecture with diagram, model and descriptions. Accelerate Business Requirement identification and translation to Target Reference Architecture. Automated steps and reduced times for task execution.\n
`Improve agility`: plan, execute, review and iterate over EA inputs and outputs. Increase the ability to adapt, transform and execute at pace and scale in response to changes in strategy, threats and opportunities. \n
`Increase collaboration`: democratise architecture work and knowledge with anyone using natural language.\n
`Cost optimisation`: intelligent allocation of architects time for valuable business tasks. \n
`Business Growth`: create / re-use of (new) products and services, and people experience enhancements. \n
`Resilience`: assess solution are secured by design, poses any risk and how to mitigate, apply best-practices. \n


## Knowledge context

Synthetic dataset is used to exemplify the Agentic System capabilities.

### IT Landscape Question and Answering

    - Application name
        - Business fit: appropriate, inadequate, perfect
        - Technical fit: adequate, insufficient, perfect
        - Business_criticality: operational, medium, high, critical
        - Roadmap: maintain, invest, divers
        - Architect responsible
        - Hosting: user device, on-premise, IaaS, SaaS
        - Business capability
        - Business domain
        - Description  
    
### Architecture Diagram Visual Question and Answering

    - Architecture Visual Artefacts
        - jpeg, png

        **Disclaimer**
                - Your data & image are not accessible or shared with anyone else nor used for training purpose.
                - EA4ALL-VQA Agent should be used ONLY FOR Architecture Diagram images.
                - This feature should NOT BE USED to process inappropriate content.

### Reference Architecture Generation

    - Clock in/out Use-case

## Log / Traceability

    For purpose of continuous improvement, agentic workflows are logged in. 

## Architecture

<italic>Core architecture built upon python, langchain, meta-faiss, gradio and Openai.<italic>

    - Python
        - Pandas
        - Langchain
        - Langsmith
        - Langgraph
        - Huggingface

    - RAG (Retrieval Augmented Generation)
        - Vectorstore

    - Prompt Engineering
        - Strategy & tactics: Task / Sub-tasks
        - Agentic Workflow

    - Models: 
        - OpenAI
        - Llama
    
    - Hierarchical-Agent-Teams: 
        - Tabular-question-and-answering
        - Supervisor
        - Visual Questions Answering 
        - Diagram Component Analysis
        - Risk & Vulnerability and Mitigation options
        - Well-Architected Design Assessment
        - Vision and Target Reference Architecture
    
    - User Interface
        - Gradio

    - Hosting: Huggingface Space
    
## Agentic System Architecture
![Agent System Container](images/ea4all_agent_container.png)

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference