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‎infrastructure/scripts/spring-ai/Dockerfile‎

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FROM public.ecr.aws/docker/library/nginx:1.28.0
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FROM public.ecr.aws/docker/library/nginx:1.29.0
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# Create a HTML page with timestamp using shell command directly in RUN
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RUN echo '<html><body><h1>Hello World!</h1><p>Build timestamp: '$(date)'</p></body></html>' > /usr/share/nginx/html/index.html

‎samples/spring-ai/README.md‎

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# Spring AI Microservices Ecosystem
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This repository contains a comprehensive ecosystem of Spring AI-powered microservices that demonstrate how to build modern AI applications using the Spring AI framework.
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## Overview
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The ecosystem consists of three main applications and a shared database infrastructure:
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1. **AI Assistant** - The central application that provides a chat interface with AI capabilities
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2. **Travel Service** - A specialized service for travel booking and management
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3. **Backoffice Service** - A specialized service for expense management and currency conversion
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4. **Database Infrastructure** - Shared PostgreSQL database with pgvector extension
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These applications work together through the Model Context Protocol (MCP), allowing the AI Assistant to leverage specialized capabilities from the Travel and Backoffice services.
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## Architecture
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The overall architecture follows a microservices pattern with the AI Assistant as the central component:
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![Assistant Architecture](assistant/docs/architecture.png)
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The AI Assistant connects to the Travel and Backoffice services through the MCP protocol, allowing it to:
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- Search for and book hotels and flights (via Travel service)
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- Create and manage expenses (via Backoffice service)
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- Convert currencies (via Backoffice service)
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## Projects
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### [AI Assistant](assistant/README.md)
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The AI Assistant is the central application in the ecosystem, providing:
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- Text-based conversations with persistent memory
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- Document analysis (PDF, JPG, JPEG, PNG)
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- Retrieval-Augmented Generation (RAG) for knowledge base integration
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- Tool integration for enhanced capabilities
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- Model Context Protocol (MCP) client for connecting to external services
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**Key Technologies:**
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- Spring AI with Amazon Bedrock (Claude Sonnet 4)
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- PostgreSQL with pgvector for vector embeddings
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- Thymeleaf web interface
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![assistant-ui](assistant/docs/assistant-ui.png)
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### [Travel Service](travel/README.md)
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The Travel service provides specialized functionality for travel management:
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- Hotel search and booking
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- Flight search and booking
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- Airport information
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- Weather forecasts for destinations
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- MCP server for AI integration
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**Key Technologies:**
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- Spring Boot with Spring Data JPA
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- PostgreSQL for data storage
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- Spring AI MCP Server for AI integration
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### [Backoffice Service](backoffice/README.md)
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The Backoffice service provides specialized functionality for business operations:
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- Expense management (create, track, update, approve)
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- Currency conversion with real-time exchange rates
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- MCP server for AI integration
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**Key Technologies:**
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- Spring Boot with Spring Data JPA
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- PostgreSQL for data storage
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- Spring AI MCP Server for AI integration
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### [Database Infrastructure](database/README.md)
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The shared database infrastructure provides:
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- PostgreSQL 16 with pgvector extension for vector embeddings
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- Multiple databases for different application domains
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- pgAdmin web interface for database management
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## Getting Started
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1. Start the database infrastructure:
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```bash
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cd database/
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./start-postgres.sh
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```
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2. Start the Travel service:
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```bash
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cd travel/
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mvn spring-boot:run
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```
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3. Start the Backoffice service:
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```bash
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cd backoffice/
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mvn spring-boot:run
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```
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4. Start the AI Assistant:
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```bash
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cd assistant/
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mvn spring-boot:run
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```
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5. Access the AI Assistant web interface:
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```
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http://localhost:8080
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```
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## Key Spring AI Features
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This ecosystem demonstrates several key features of the [Spring AI framework](https://docs.spring.io/spring-ai/reference/index.html):
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1. **AI Integration** - Using Spring AI to integrate with AI models (Amazon Bedrock)
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2. **System Prompts** - Configuring AI behavior with system prompts
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3. **Chat Memory** - Implementing persistent conversation memory
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4. **RAG** - Implementing Retrieval-Augmented Generation for knowledge base integration
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5. **Tool Integration** - Extending AI capabilities with custom tools
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6. **MCP** - Using the Model Context Protocol for microservices integration
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For more details on each feature, refer to the [AI Assistant documentation](assistant/README.md).
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## Prerequisites
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- Java 21 or higher
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- Maven 3.8 or higher
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- Docker and Docker Compose
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- AWS account with Amazon Bedrock access
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## License
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This project is licensed under the MIT License - see the LICENSE file for details.

‎samples/spring-ai/assistant/.gitignore‎

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HELP.md
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target/
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.mvn/wrapper/maven-wrapper.jar
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!**/src/main/**/target/
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!**/src/test/**/target/
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### STS ###
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.apt_generated
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.classpath
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.factorypath
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.project
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.settings
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.springBeans
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.sts4-cache
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### IntelliJ IDEA ###
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.idea
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*.iws
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*.iml
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*.ipr
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### NetBeans ###
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/nbproject/private/
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/nbbuild/
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/dist/
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/nbdist/
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/.nb-gradle/
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build/
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!**/src/main/**/build/
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!**/src/test/**/build/
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### VS Code ###
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.vscode/

‎samples/spring-ai/assistant/.mvn/wrapper/maven-wrapper.properties‎

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# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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wrapperVersion=3.3.2
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distributionType=only-script
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distributionUrl=https://repo.maven.apache.org/maven2/org/apache/maven/apache-maven/3.9.10/apache-maven-3.9.10-bin.zip

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