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<!DOCTYPE html>
<html>
<head>
<title>Integrated Quantum-Resistant Healthcare Information System</title>
<script src="https://cdn.jsdelivr.net/npm/mermaid@10/dist/mermaid.min.js"></script>
<style>
body {
font-family: Arial, sans-serif;
max-width: 1200px;
margin: 0 auto;
padding: 20px;
background-color: #f5f5f5;
}
h1, h2, h3, h4 {
color: #333;
border-bottom: 2px solid #eee;
padding-bottom: 10px;
margin-top: 40px;
}
h1 {
margin-top: 0;
}
.diagram-container {
background-color: white;
padding: 20px;
margin: 20px 0;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.description {
color: #666;
font-size: 14px;
margin: 10px 0;
}
.code-block {
background-color: #e8e8e8;
padding: 10px;
border-radius: 4px;
margin: 15px 0;
overflow-x: auto;
}
ul, ol {
margin-left: 20px;
}
li {
margin: 5px 0;
}
pre {
background-color: #e8e8e8;
padding: 8px;
border-radius: 4px;
font-size: 90%;
overflow-x: auto;
}
.mermaid {
margin: 20px 0;
display: flex;
justify-content: center;
}
</style>
</head>
<body>
<h1>Integrated Quantum-Resistant Healthcare Information System</h1>
<div class="description">
A comprehensive, quantum-resistant system built on M3-optimized architecture,
integrating multiple specialized agents for healthcare, research, and blockchain operations,
following a Hybrid Agile–Waterfall approach.
</div>
<div class="diagram-container">
<h2>0. Complete IQHIS System Architecture</h2>
<div class="description">
Comprehensive view of the Integrated Quantum-Resistant Healthcare Information System showing implementation status: Completed (✅), In Progress (⏳), Planned (🔲)
</div>
<div class="mermaid">
flowchart TB
subgraph Core["Core Infrastructure (⏳)"]
direction TB
subgraph QL["Quantum Layer"]
QBA["QuantumBaseAgent (✅)"] --> QKD["Quantum Key Distribution (⏳)"]
QKD --> QC["Quantum Circuits (🔲)"]
end
subgraph M3["M3 Optimization (✅)"]
HA["Hardware Acceleration"] --> ML["ML Operations"]
ML --> IP["Image Processing"]
IP --> QS["Quantum-Safe Crypto"]
end
subgraph AG["AutoGen Layer (⏳)"]
ACore["Core API (✅)"] --> ASwitch["Model Switching (✅)"]
ASwitch --> AHealth["Healthcare Agents (⏳)"]
AHealth --> ARoute["Advanced Routing (🔲)"]
end
end
subgraph Health["Healthcare Components (⏳)"]
direction TB
subgraph Clinical["Clinical Agents"]
Card["Cardiology (✅)"] --> Rad["Radiology (✅)"]
Rad --> Gen["Genomics (⏳)"]
Gen --> Imm["Immunology (🔲)"]
end
subgraph Remote["Remote Care (🔲)"]
Tele["Telemedicine"] --> Rehab["Rehabilitation"]
Rehab --> BH["Behavioral Health"]
end
subgraph Safety["Safety & Wellness (⏳)"]
Pharm["Pharmacovigilance (✅)"] --> Sec["Security (⏳)"]
Sec --> Nut["Nutrition (🔲)"]
end
end
subgraph Block["Blockchain Layer (⏳)"]
direction TB
subgraph IOTA["IOTA Integration"]
Node["Node (✅)"] --> Tangle["Tangle (✅)"]
Tangle --> Smart["Smart Contracts (⏳)"]
Smart --> QR["Quantum Resistance (🔲)"]
end
subgraph NFT["NFT System (🔲)"]
NFTH["Healthcare NFTs (⏳)"] --> IPFS["IPFS Storage (🔲)"]
IPFS --> Access["Access Control (🔲)"]
end
end
subgraph Sec["Security Architecture (✅)"]
direction TB
PQC["Post-Quantum Crypto"] --> KE["Key Encapsulation"]
KE --> DS["Digital Signatures"]
DS --> QRN["Quantum Random Numbers"]
end
subgraph Dev["Development Infrastructure (⏳)"]
direction TB
Zeta["Zeta-Second Implementation (⏳)"] --> CICD["CI/CD Pipeline (⏳)"]
CICD --> Test["Testing Framework (✅)"]
Test --> Monitor["Monitoring (🔲)"]
end
Core --> Health
Core --> Block
Block --> Sec
Health --> Sec
Core --> Dev
Dev --> Sec
classDef default fill:#fff,stroke:#333,stroke-width:1px;
classDef implemented fill:#bfb,stroke:#333,stroke-width:2px;
classDef progress fill:#fbf,stroke:#333,stroke-width:2px;
classDef planned fill:#fdb,stroke:#333,stroke-width:2px;
class M3,Sec implemented;
class Core,Health,Block,Dev progress;
class Remote,NFT,Monitor planned;
</div>
</div>
<div class="diagram-container">
<h2>1. Overall Hybrid Agile–Waterfall System Flow with AutoGen Integration</h2>
<div class="description">Illustrates how the Waterfall phases combine with Agile sprints and AutoGen's multi-modal, healthcare-specific model setup for a balanced approach in healthcare software compliance.</div>
<div class="mermaid">
%%{init: {'theme': 'default', 'themeVariables': { 'fontFamily': 'arial', 'fontSize': '14px'}}}%%
flowchart TD
subgraph P["1. Planning & Requirements (Waterfall)"]
direction TB
P1["Stakeholder Interviews"] --> P2["Risk Analysis (FMEA)"]
P2 --> P3["Requirements Spec"]
P3 --> P4["Design Controls Setup"]
end
subgraph A["2. Architecture & High-Level Design (Waterfall)"]
direction TB
A1["Draft System Architecture"] --> A2["Data Flow Diagrams"]
A2 --> A3["Agent/LLM Specification"]
A3 --> A4["Traceability Matrix"]
end
subgraph I["3. Iterative Development & Sprints (Agile)"]
direction TB
I1["Sprint Planning"] --> I2["Sprint Execution"]
I2 --> I3["Frequent Demos & Feedback"]
I3 --> I4["Continuous Integration / Testing"]
end
subgraph V["4. Verification & Validation (Waterfall Checkpoints)"]
direction TB
V1["Design Review"] --> V2["System Integration Tests"]
V2 --> V3["User Acceptance Tests (UAT)"]
V3 --> V4["Regulatory Documentation"]
end
subgraph D["5. Deployment & Release"]
direction TB
D1["Infrastructure Setup"] --> D2["Container Orchestration"]
D2 --> D3["Blue-Green / Canary Releases"]
D3 --> D4["Regulatory Submission Package"]
end
subgraph M["6. Maintenance & Continuous Improvement"]
direction TB
M1["Monitoring & Metrics"] --> M2["Updates / Patches"]
M2 --> M3["New Feature Backlog"]
M3 --> M1
end
P --> A
A --> I
I --> V
V --> D
D --> M
classDef default fill:#fff,stroke:#333,stroke-width:1px;
classDef planning fill:#f9f,stroke:#333,stroke-width:2px;
classDef architecture fill:#bbf,stroke:#333,stroke-width:2px;
classDef iterative fill:#bfb,stroke:#333,stroke-width:2px;
classDef validation fill:#fbf,stroke:#333,stroke-width:2px;
classDef deployment fill:#ff9,stroke:#333,stroke-width:2px;
classDef maintenance fill:#9ff,stroke:#333,stroke-width:2px;
class P planning;
class A architecture;
class I iterative;
class V validation;
class D deployment;
class M maintenance;
</div>
</div>
<div class="diagram-container">
<h2>2. Current System Architecture Status</h2>
<div class="description">
Current state of the system architecture showing implemented components (✅), in-progress features (⏳), and planned additions (🔲).
</div>
<div class="mermaid">
flowchart TB
subgraph Frontend["Frontend Layer (✅)"]
direction TB
UI["User Interface"] --> API["API Gateway (✅)"]
UI --> Analytics["Analytics Dashboard (🔲)"]
UI --> Workflow["Workflow Manager (⏳)"]
end
subgraph Security["Security Layer (✅)"]
direction TB
Auth["RapidAPI Authentication (✅)"] --> Enc["Data Encryption (✅)"]
Enc --> Access["Access Control (✅)"]
Access --> Audit["Audit Logging (⏳)"]
end
subgraph Core["Core Components (✅)"]
direction TB
Sim["Simulation Engine (✅)"] --> Val["Validation Engine (✅)"]
Val --> Store["Data Storage (✅)"]
Store --> Log["System Logging (✅)"]
end
subgraph Healthcare["Healthcare Features (⏳)"]
direction TB
Proto["Protocol Library (✅)"] --> Scen["Scenario Generator (✅)"]
Scen --> Valid["Clinical Validation (⏳)"]
Valid --> Report["Reporting System (🔲)"]
end
subgraph Monitor["Monitoring (⏳)"]
direction TB
Metrics["System Metrics (⏳)"] --> Alert["Alerting (🔲)"]
Alert --> Health["Health Checks (✅)"]
Health --> Perf["Performance Tracking (🔲)"]
end
Frontend --> Security
Security --> Core
Core --> Healthcare
Core --> Monitor
classDef default fill:#fff,stroke:#333,stroke-width:1px;
classDef implemented fill:#bfb,stroke:#333,stroke-width:2px;
classDef progress fill:#fbf,stroke:#333,stroke-width:2px;
classDef planned fill:#fdb,stroke:#333,stroke-width:2px;
class Frontend,Security,Core implemented;
class Healthcare,Monitor progress;
class Analytics,Report,Alert,Perf planned;
</div>
</div>
<div class="diagram-container">
<h2>3. Agent System Architecture with AutoGen Integration</h2>
<div class="description">
Comprehensive multi-agent system architecture showcasing M3-optimized components, AutoGen-powered specialized healthcare agents,
quantum-resistant features, and their interactions within the system framework.
</div>
<div class="mermaid">
flowchart TB
subgraph Frontend["Frontend Layer"]
direction TB
UI["User Interface"] --> API["API Gateway"]
UI --> Analytics["Analytics Dashboard"]
UI --> Workflow["Workflow Manager"]
end
subgraph M3["M3/Metal Optimization Layer"]
direction TB
Accel["Hardware Acceleration"] --> MLOps["ML Operations"]
Accel --> ImgProc["Image Processing"]
Accel --> Crypto["Quantum-Safe Cryptography"]
end
subgraph Orchestration["Quantum-Resistant Orchestration"]
direction TB
QOrch["QuantumOrchestrator"] --> Core["Core Agents"]
QOrch --> Health["Healthcare Agents"]
QOrch --> Research["Research Agents"]
subgraph AutoGen["AutoGen Multi-Agent Layer"]
AGCore["AutoGen Core API"]
AGSwitch["Dynamic LLM Switching"]
AGModels["Model Selection & Routing"]
AGHealth["Healthcare-Specific Agents"]
AGCore --> AGSwitch
AGSwitch --> AGModels
AGModels --> AGHealth
subgraph ModelTypes["Model Types"]
Local["Local Models (Ollama)"]
Remote["Remote Models (OpenAI)"]
AGModels --> Local
AGModels --> Remote
end
end
subgraph Core["Core System Agents"]
QBA["QuantumBaseAgent"]
BC["BlockchainAgent"]
DB["DatabaseAgent"]
DevOps["EnhancedDevOpsAgent"]
Audit["AuditAgent"]
end
subgraph Health["Specialized Healthcare Agents"]
direction TB
subgraph Imaging["Imaging & Diagnostics"]
DP["DigitalPathologyAgent"]
RAD["RadiologyAgent"]
end
subgraph Clinical["Clinical Specialties"]
CARD["CardiologyAgent"]
GEN["GenomicsAgent"]
IMM["ImmunologyAgent"]
end
subgraph Remote["Remote Care"]
TELE["TelemedicineAgent"]
REHAB["RehabilitationAgent"]
BH["BehavioralHealthAgent"]
end
subgraph Safety["Safety & Wellness"]
PHARM["PharmacovigilanceAgent"]
NUT["NutritionAndWellnessAgent"]
SEC["SecurityComplianceAgent"]
end
end
subgraph Research["Research & Analytics"]
ML["MLAgent"]
Ollama["OllamaAgent"]
IoT["IoTAgent"]
Res["ResearchAgent"]
QComp["QuantumComputeAgent"]
end
end
subgraph Storage["Secure Storage Layer"]
direction TB
DB_["PostgreSQL"] --> Cache["Quantum-Safe Cache"]
DB_ --> FS["Encrypted File Storage"]
BC_["IOTA Node"] --> Tangle["Quantum-Resistant Tangle"]
end
subgraph Models["Pre-trained Models"]
direction TB
MONAI["MONAI Models"]
HF["Hugging Face Models"]
TF["TensorFlow Models"]
OLLAMA["Ollama Healthcare Models"]
GPT["OpenAI GPT Models"]
QML["Quantum ML Models"]
end
API --> QOrch
QOrch --> M3
Health --> Models
Core --> Storage
Health --> Storage
Research --> Storage
M3 --> Models
AutoGen --> Models
Health --> AutoGen
AutoGen --> Core
QBA --> AGCore
classDef default fill:#fff,stroke:#333,stroke-width:1px
classDef frontend fill:#bbf,stroke:#333,stroke-width:2px
classDef m3 fill:#f9f,stroke:#333,stroke-width:2px
classDef orchestration fill:#bfb,stroke:#333,stroke-width:2px
classDef storage fill:#ff9,stroke:#333,stroke-width:2px
classDef models fill:#fdb,stroke:#333,stroke-width:2px
classDef autogen fill:#e6ffe6,stroke:#333,stroke-width:2px
classDef quantum fill:#ffe6cc,stroke:#333,stroke-width:2px
class Frontend,UI,API,Analytics,Workflow frontend
class M3,Accel,MLOps,ImgProc,Crypto m3
class Orchestration,QOrch,Core,Health,Research orchestration
class Storage,DB_,Cache,FS,BC_,Tangle storage
class Models,MONAI,HF,TF,OLLAMA,GPT,QML models
class AutoGen,AGCore,AGSwitch,AGModels,AGHealth,ModelTypes autogen
class QBA,QComp,SEC quantum
</div>
</div>
<!-- =============================================================================
QUANTUM-RESISTANT SECURITY ARCHITECTURE
============================================================================= -->
<div class="diagram-container">
<h2>3.5 Quantum-Resistant Security Architecture</h2>
<div class="description">
Enhanced view of the system's quantum-resistant security layers, encryption mechanisms, and integrated AutoGen security features.
</div>
<div class="mermaid">
flowchart TB
subgraph QR["Quantum-Resistant Layer"]
PQC[Post-Quantum Cryptography] --> KEM[Key Encapsulation]
PQC --> DS[Digital Signatures]
PQC --> HE[Homomorphic Encryption]
PQC --> QRN[Quantum Random Numbers]
end
subgraph Security["Security Components"]
Auth[Authentication] --> MFA[Multi-Factor Auth]
Auth --> JWT[Quantum-Safe JWT]
Auth --> Bio[Biometric Auth]
Enc[Encryption] --> AE[At-Rest Encryption]
Enc --> TE[Transit Encryption]
Enc --> FE[Field-Level Encryption]
Monitor[Security Monitoring] --> Audit[Real-time Audit]
Monitor --> Threat[Threat Detection]
Monitor --> AI[AI-based Analysis]
end
subgraph AutoGen["AutoGen Security"]
ModelSec[Model Security] --> TokenVal[Token Validation]
ModelSec --> PromptSec[Prompt Security]
ModelSec --> DataSan[Data Sanitization]
AgentSec[Agent Security] --> Access[Access Control]
AgentSec --> Logging[Secure Logging]
AgentSec --> Isolation[Agent Isolation]
end
subgraph Compliance["Healthcare Compliance"]
HIPAA[HIPAA Controls] --> Audit[Audit Logging]
HIPAA --> PHI[PHI Protection]
HIPAA --> BAA[Business Associates]
FDA[FDA Compliance] --> Val[Validation]
FDA --> Doc[Documentation]
FDA --> Track[Traceability]
end
subgraph Metal["Metal-Based Optimization"]
GPU[GPU Acceleration] --> ML[ML Processing]
GPU --> Crypto[Crypto Operations]
GPU --> Image[Image Processing]
TPU[TPU Processing] --> QML[Quantum ML]
TPU --> Tensor[Tensor Ops]
end
User[Healthcare Provider] --> Auth
Auth --> QR
QR --> AutoGen
AutoGen --> Data[(Protected Data)]
Data --> Metal
Metal --> Compliance
style QR fill:#f9f,stroke:#333,stroke-width:2px
style Security fill:#bbf,stroke:#333,stroke-width:2px
style Compliance fill:#bfb,stroke:#333,stroke-width:2px
style Metal fill:#fbf,stroke:#333,stroke-width:2px
style AutoGen fill:#e6ffe6,stroke:#333,stroke-width:2px
</div>
</div>
<div class="diagram-container">
<h2>4. Data Flow Architecture</h2>
<div class="description">Enhanced sequence of data flow between system components, including AutoGen integration and quantum-safe processing steps.</div>
<div class="mermaid">
sequenceDiagram
participant U as User
participant F as Frontend
participant AG as API Gateway
participant QO as QuantumOrchestrator
participant AC as AutoGenCoordinator
participant QA as QuantumAgent
participant HA as HealthcareAgents
participant D as SecureDatabase
Note over U,D: Initialization Phase
U->>F: Request Healthcare Action
F->>AG: Secure API Call
AG->>QO: Route Request with Quantum Signature
Note over QO,HA: Model Selection & Processing
QO->>AC: Initialize AutoGen Processing
AC->>QA: Request Quantum Verification
QA->>QA: Verify Quantum Signatures
par Parallel Processing
AC->>AC: Select Optimal Model (Ollama/OpenAI)
QA->>QA: Generate Quantum Keys
end
Note over AC,HA: Healthcare Processing
AC->>HA: Delegate Healthcare Tasks
activate HA
HA->>D: Quantum-Safe Data Operation
D-->>HA: Encrypted Response
deactivate HA
Note over HA,U: Response & Validation
HA-->>AC: Process Results
AC-->>QO: Validate & Package Response
QO-->>AG: Apply Quantum Encryption
AG-->>F: Return Secure Response
F-->>U: Display Validated Results
Note over U,D: Continuous Monitoring
par Audit & Compliance
QO->>D: Log Transaction
AC->>D: Store Model Performance
QA->>D: Record Quantum Metrics
end
</div>
</div>
<div class="diagram-container">
<h2>5. Development Guidelines</h2>
<div class="description">Key development practices and standards.</div>
<div class="mermaid">
flowchart TB
DG[Development Guidelines] --> VC[Version Control]
DG --> CQ[Code Quality]
DG --> DOC[Documentation]
DG --> SEC[Security]
DG --> PERF[Performance]
VC --> VC1[Git Flow]
VC --> VC2[CI/CD]
VC --> VC3[Branching Strategy]
CQ --> CQ1[Code Reviews]
CQ --> CQ2[Testing]
CQ --> CQ3[Static Analysis]
DOC --> DOC1[API Docs]
DOC --> DOC2[Architecture]
DOC --> DOC3[Workflows]
SEC --> SEC1[Encryption]
SEC --> SEC2[Audits]
SEC --> SEC3[Access Control]
PERF --> PERF1[Testing]
PERF --> PERF2[Monitoring]
PERF --> PERF3[Optimization]
</div>
</div>
<div class="diagram-container">
<h2>6. Environment Configuration Architecture</h2>
<div class="description">Visual representation of the system's configuration components and their relationships.</div>
<div class="mermaid">
flowchart TB
subgraph Core["Core Configuration"]
direction TB
ENV["NODE_ENV=production"] --> M3["M3_OPTIMIZATION"]
M3 --> QR["QUANTUM_RESISTANT"]
end
subgraph API["API & Network"]
direction TB
EP["API_ENDPOINT"] --> BN["BLOCKCHAIN_NODE"]
BN --> IOTA["IOTA Configuration"]
IOTA --> OL["Ollama Configuration"]
end
subgraph Security["Security Settings"]
direction TB
EL["ENCRYPTION_LEVEL"] --> AE["AUDIT_ENABLED"]
AE --> JWT["JWT_SECRET"]
end
subgraph M3Opt["M3 Optimization"]
direction TB
MD["METAL_DEVICE_WRAPPER"] --> NO["NODE_OPTIONS"]
end
subgraph Storage["Storage & Data"]
direction TB
DB["PostgreSQL Config"] --> EMR["EMR/OMOP Settings"]
EMR --> NFT["NFT Storage"]
end
Core --> API
Core --> Security
Core --> M3Opt
API --> Storage
Security --> Storage
classDef default fill:#fff,stroke:#333,stroke-width:1px
classDef core fill:#bbf,stroke:#333,stroke-width:2px
classDef api fill:#bfb,stroke:#333,stroke-width:2px
classDef security fill:#f9f,stroke:#333,stroke-width:2px
classDef m3 fill:#fbf,stroke:#333,stroke-width:2px
classDef storage fill:#ff9,stroke:#333,stroke-width:2px
class Core core
class API api
class Security security
class M3Opt m3
class Storage storage
</div>
</div>
<div class="diagram-container">
<h2>7. NFT Integration Architecture</h2>
<div class="description">Visualization of NFT integration with healthcare agents and the underlying infrastructure.</div>
<div class="mermaid">
flowchart TB
subgraph NFTFlow["NFT Integration Flow"]
direction TB
subgraph Input["Healthcare Data Input"]
IMG["Medical Images"] --> META["Metadata Generation"]
DIAG["Diagnostic Reports"] --> META
LAB["Lab Results"] --> META
end
subgraph Process["NFT Processing"]
IPFS["IPFS Storage"] --> HASH["Content Hashing"]
HASH --> MINT["NFT Minting"]
MINT --> QS["Quantum Signing"]
end
subgraph Verify["Verification Layer"]
PROOF["Proof Generation"] --> VALID["Validation"]
VALID --> CHAIN["Blockchain Record"]
end
subgraph Optimize["M3 Optimization"]
ACC["Hardware Acceleration"] --> PROC["Parallel Processing"]
PROC --> CACHE["Result Caching"]
end
end
Input --> Process
Process --> Verify
Process --> Optimize
Optimize --> Verify
classDef default fill:#fff,stroke:#333,stroke-width:1px
classDef input fill:#bbf,stroke:#333,stroke-width:2px
classDef process fill:#bfb,stroke:#333,stroke-width:2px
classDef verify fill:#f9f,stroke:#333,stroke-width:2px
classDef optimize fill:#fbf,stroke:#333,stroke-width:2px
class Input input
class Process process
class Verify verify
class Optimize optimize
</div>
</div>
<div class="diagram-container">
<h2>8. AutoGen Configuration and Model Switching Architecture</h2>
<div class="description">
Enhanced visualization of AutoGen's dynamic model switching capabilities, configuration management, and quantum-safe integration for healthcare-specific LLM deployment.
</div>
<div class="mermaid">
flowchart TB
subgraph Config["Configuration Layer"]
direction TB
YAML["autogen.yaml"] --> Parser["Config Parser"]
Parser --> Factory["Model Factory"]
Factory --> Cache["Model Cache"]
end
subgraph Models["Model Selection & Routing"]
direction TB
Factory --> Local["Local Healthcare Models"]
Factory --> Remote["Remote GPT Models"]
subgraph Local["Local Models"]
OL["Ollama Healthcare"]
HF["HuggingFace Local"]
QML["Quantum ML Models"]
end
subgraph Remote["Remote Models"]
GPT4["GPT-4"]
GPT35["GPT-3.5"]
CLAUDE["Claude Models"]
end
end
subgraph Agents["AutoGen Agents"]
direction TB
HA["Healthcare Assistant"]
GA["General Assistant"]
UP["User Proxy"]
QA["Quantum Assistant"]
HA --> Local
GA --> Remote
QA --> QML
UP --> HA
UP --> GA
UP --> QA
end
subgraph Security["Security Layer"]
direction TB
QE["Quantum Encryption"]
AL["Audit Logging"]
CM["Consent Management"]
PQC["Post-Quantum Cryptography"]
QE --> PQC
AL --> PQC
CM --> PQC
end
subgraph Monitoring["Performance Monitoring"]
PM["Performance Metrics"]
RM["Resource Monitor"]
LM["Latency Monitor"]
SM["Security Monitor"]
end
Models --> Security
Security --> Storage[(Secure Storage)]
Models --> Monitoring
Agents --> Monitoring
classDef config fill:#f9f,stroke:#333,stroke-width:2px
classDef models fill:#bbf,stroke:#333,stroke-width:2px
classDef agents fill:#bfb,stroke:#333,stroke-width:2px
classDef security fill:#fbf,stroke:#333,stroke-width:2px
classDef storage fill:#ff9,stroke:#333,stroke-width:2px
classDef monitoring fill:#e6ffe6,stroke:#333,stroke-width:2px
class Config,YAML,Parser,Factory,Cache config
class Models,Local,Remote,OL,HF,GPT4,GPT35,CLAUDE,QML models
class Agents,HA,GA,UP,QA agents
class Security,QE,AL,CM,PQC security
class Storage storage
class Monitoring,PM,RM,LM,SM monitoring
</div>
<div class="description">
Key Components:
<ul>
<li>Configuration Layer: Enhanced model selection and parameter management via YAML configuration with caching</li>
<li>Model Selection & Routing: Dynamic switching between local healthcare models, quantum ML models, and remote GPT models</li>
<li>AutoGen Agents: Specialized agents for healthcare, quantum computing, and general tasks</li>
<li>Security Layer: Advanced quantum-safe encryption and compliance measures</li>
<li>Performance Monitoring: Real-time metrics and resource optimization</li>
</ul>
</div>
</div>
<!-- =============================================================================
NEW SECTION: 9. Zeta-Second Quantum Development Flow
============================================================================= -->
<div class="diagram-container">
<h2>9. Zeta-Second Quantum Development Flow</h2>
<div class="description">
An ultra-accelerated development flow inspired by quantum superposition principles, integrating Qiskit on IBM Quantum for real-time healthcare agent deployment.
</div>
<div class="mermaid">
flowchart TB
subgraph QDF["Zeta-Second Quantum Development Flow"]
direction TB
Q0["Day Q₀: Initialization & Superposition"] --> Q1["Day Q₁: Parallel HPC & Security"]
Q1 --> Q2["Day Q₂: Clinical Flow & Model Integration"]
Q2 --> Q3["Day Q₃: Testing & Multi-Modal Overlaps"]
Q3 --> Q4["Day Q₄: AI-Driven Refinement"]
Q4 --> Q5["Day Q₅: Comprehensive Collapse"]
Q5 --> Q6["Day Q₆: Release & Reflection"]
Q6 --> Q0["Next Iteration Cycle"]
end
classDef default fill:#fff,stroke:#333,stroke-width:1px;
classDef qdf fill:#e6ffe6,stroke:#333,stroke-width:2px;
class QDF qdf;
</div>
</div>
<!-- =============================================================================
NEW SECTION: 10. Detailed Zeta-Second Development Steps
============================================================================= -->
<div class="diagram-container">
<h2>10. Detailed Zeta-Second Development Steps</h2>
<div class="description">
Step-by-step breakdown of the zeta-second development methodology, ensuring rapid iteration while maintaining compliance and quality.
</div>
<div class="mermaid">
sequenceDiagram
participant Q0 as Day Q₀: Initialization
participant Q1 as Day Q₁: Parallel HPC & Security
participant Q2 as Day Q₂: Clinical Flow Integration
participant Q3 as Day Q₃: Testing Overlaps
participant Q4 as Day Q₄: AI Refinement
participant Q5 as Day Q₅: Comprehensive Collapse
participant Q6 as Day Q₆: Release & Reflection
Q0->>Q1: Initialize Environment & Superpose Tasks
Q1->>Q2: Execute HPC Concurrency & Quantum Security
Q2->>Q3: Integrate Clinical Flows & Models
Q3->>Q4: Conduct Testing & Multi-Modal Overlaps
Q4->>Q5: Apply AI-Driven Refinements
Q5->>Q6: Collapse Ephemeral States & Finalize
Q6->>Q0: Reflect & Prepare for Next Cycle
</div>
</div>
<!-- =============================================================================
NEW SECTION: 11. Integrated Code Workflow
============================================================================= -->
<div class="diagram-container">
<h2>11. Integrated Code Workflow</h2>
<div class="description">
How the quantum agents, AutoGen integration, and Docker configurations interact within the development flow.
</div>
<div class="mermaid">
flowchart LR
subgraph CodeFlow["Integrated Code Workflow"]
direction TB
QBA["QuantumBaseAgent"] -->|Encrypts Data| A["AutoGenCoordinator"]
A -->|Selects Model| AG["AutoGen Agents"]
AG -->|Processes Request| H["Healthcare Agents"]
H -->|Fetches Data| D["DatabaseAgent"]
D -->|Stores Results| S["Secure Storage"]
S -->|Logs Compliance| QE["Quantum Encryption"]
QE -->|Ensures Security| Security["Quantum-Resistant Security"]
end
classDef default fill:#fff,stroke:#333,stroke-width:1px;
classDef codeflow fill:#ffcccc,stroke:#333,stroke-width:2px;
class CodeFlow codeflow;
</div>
</div>
<!-- =============================================================================
NEW SECTION: 12. Implementation Integration
============================================================================= -->
<div class="diagram-container">
<h2>12. Implementation Integration</h2>
<div class="description">
Step-by-step integration of QuantumBaseAgent, AutoGenCoordinator, and Docker configurations into the overall system.
</div>
<div class="mermaid">
flowchart LR
subgraph Integration["Implementation Integration"]
direction TB
Code["Codebase"] -->|Quantum Logic| QBA["QuantumBaseAgent"]
Code -->|Model Selection| A["AutoGenCoordinator"]
QBA -->|Encrypted Data| A
A -->|Model Choice| AG["AutoGen Agents"]
AG -->|Healthcare Tasks| H["Healthcare Agents"]
H -->|Data Operations| D["DatabaseAgent"]
D -->|Store Securely| S["Secure Storage"]
S -->|Encrypted Logs| QE["Quantum Encryption"]
QE -->|Compliance| C["Compliance Modules"]
C -->|Audit Trails| Audit["Audit Logging"]
end
classDef default fill:#fff,stroke:#333,stroke-width:1px;
classDef integration fill:#cceeff,stroke:#333,stroke-width:2px;
class Integration integration;
</div>
</div>
<!-- =============================================================================
NEW SECTION: 13. Zeta-Second Development Code Integration Example
============================================================================= -->
<div class="diagram-container">
<h2>13. Zeta-Second Development Code Integration Example</h2>
<div class="description">
Example code snippets demonstrating the integration of QuantumBaseAgent and AutoGenCoordinator within the system.
</div>
<div class="code-block">
<pre>
# iqhis_main.py
import asyncio
import logging
from pathlib import Path
from agents.quantum.quantum_base_agent import QuantumBaseAgent, QuantumConfig
from agents.autogen.autogen_coordinator import AutoGenCoordinator
# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger("IQHIS")
async def run_iqhis_system():
"""Main entry point for the IQHIS system."""
logger.info("Starting IQHIS system integration...")
# Initialize components
quantum_config = QuantumConfig(
algorithm="Kyber1024",
key_rotation_hours=24,
key_size=1024
)
q_agent = QuantumBaseAgent(quantum_config)
auto_gen = AutoGenCoordinator("/app/config/autogen.yaml")
# Process sample request
sample_request = {
"specialty": "cardiology",
"patient_data": {"symptoms": ["chest pain", "shortness of breath"]},
}
response = await auto_gen.process_healthcare_request(sample_request)
# Finish
logger.info("IQHIS system run complete.")
if __name__ == "__main__":
asyncio.run(run_iqhis_system())
</pre>
</div>
</div>
<!-- =============================================================================
NEW SECTION: 14. Updated Docker Configuration
============================================================================= -->
<div class="diagram-container">
<h2>14. Updated Docker Configuration for Zeta-Second Flow</h2>
<div class="description">
Enhanced Docker Compose configuration to support the accelerated zeta-second development cycles.
</div>
<div class="code-block">
<pre>
# docker-compose.yml
version: '3.8'
services:
iqhis-main:
build:
context: .
dockerfile: Dockerfile.iqhis
volumes:
- ./config:/app/config
depends_on:
- quantum-agent
- autogen-coordinator
networks:
- iqhis-net
quantum-agent:
build:
context: .
dockerfile: Dockerfile.quantum
environment:
- QUANTUM_ALGORITHM=Kyber1024
- KEY_ROTATION_HOURS=24
networks:
- iqhis-net
autogen-coordinator:
build:
context: .
dockerfile: Dockerfile.autogen
environment:
- MODEL_CONFIG_PATH=/app/config/autogen.yaml
depends_on:
- quantum-agent
- ollama
networks: