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AI Traffic Optimisation System
Inference Service
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AI Traffic Optimisation System
GitHub
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Home
AI Traffic Optimisation System
External Links
External Links
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Inference Service
Inference Service Documentation
GitHub Repository
API Gateway
Inference Service
Inference Service
Table of contents
To do
SUMO
LSTM
Security
System Architecture
System Architecture
System Architecture
1. High-Level
2. Request-Response Flow
3. System Components
4. Data Flow Through System
5. Deployment Architecture
6. Detailed Internal Flow - Action Prediction
7. Error Handling Flow
8. Inter-Service Communication Protocol
9. Model Loading & Caching Strategy
10. Complete End-to-End Workflow
11. Architecture Decision Rationale
12. Performance Characteristics
13. Scalability Considerations
14. Security Architecture
15. Monitoring & Observability Points
16. Deployment Patterns
Setup
Setup
Quick Start
Quick Start
Quick Start
Setup Complete
Setup Complete
Overview
What Was Created
Quick Start (5 Minutes)
Architecture Overview
API Endpoints
Using Different Models
Testing
Environment Variables
Development vs Production
MkDocs Setup
Documentation Files
Next Steps
Support
API
API
Documentation
Documentation
API Docs
Java API Gateway
Python Inference Service
API Setup
API Setup
Overview
🚗 API Setup Guide
📡 API Usage Examples
🔐 Environment Variables
🐳 Docker Compose Configuration
📊 Monitoring and Logging
🔄 Using Different Models
⚡ Performance Tuning
🐛 Troubleshooting
🌍 Production Deployment
Features
About
About
Support
File Manifest
File Manifest
Overview
Inference Service Manifest
API Gateway Manifest
File Statistics
Integration with Existing Project
Environment Setup
How to Use Each Component
Quick Reference
Changelog
Table of contents
To do
RL Inference Service
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