add rag-view frontend

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Example Questions and Expected Answers
=======================================
These questions are based on the default context file (guest-example.txt).
Use them to test RAG query behavior with different settings.
--- Questions with answers found in context ---
1. What port does the Notification Service run on?
Expected answer: 8082
2. How long are access tokens valid in Project Aurora?
Expected answer: 30 minutes
3. What is the database naming convention?
Expected answer: aurora_{service_name}
4. Who is the lead developer?
Expected answer: Maria Chen
5. What message broker does Aurora use?
Expected answer: RabbitMQ on port 5672
6. What happens when CPU goes above 70%?
Expected answer: HPA scales pods, from 2 to 10 replicas
--- Question to test onlyContext mode ---
7. What is the capital of France?
With onlyContext=true: should respond that the answer is not found in context
With onlyContext=false: should answer "Paris"

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Project Aurora - Internal Technical Documentation
Project Aurora is an internal microservices platform developed by NovaTech Solutions
in Q3 2024. The platform consists of five core services: Gateway Service (port 8080),
User Management Service (port 8081), Notification Service (port 8082), Analytics
Service (port 8083), and Billing Service (port 8084).
The Gateway Service uses Spring Cloud Gateway and requires a minimum of 512MB RAM.
All inter-service communication is handled via RabbitMQ running on port 5672.
The default exchange name is "aurora.exchange" and the dead letter queue is
"aurora.dlq".
Database configuration: each service has its own PostgreSQL schema. The naming
convention is aurora_{service_name}. For example, the User Management Service
uses the schema aurora_user_management. Connection pooling is managed by HikariCP
with a maximum pool size of 15 connections per service.
Authentication is handled by the User Management Service using JWT tokens with
RS256 algorithm. Access tokens expire after 30 minutes, refresh tokens after 7 days.
The public key for token verification is available at
http://user-service:8081/.well-known/jwks.json.
Deployment: all services are containerized using Docker and orchestrated with
Kubernetes. The production cluster runs on 3 nodes with a minimum of 8GB RAM each.
Horizontal Pod Autoscaler is configured to scale between 2 and 10 replicas based
on CPU utilization threshold of 70%.
The lead developer is Maria Chen (maria.chen@novatech.example.com).
The project manager is Alex Kumar (alex.kumar@novatech.example.com).
Weekly sync meetings are held every Wednesday at 14:00 CET.