Update READMEs

Author: Yuriy Bezsonov

samples/spring-ai-te-agent/README.md

@@ -2,52 +2,50 @@
 
 A comprehensive AI-powered agent ecosystem built with Spring AI framework, demonstrating modern AI application patterns including RAG, persistent memory, tool integration, and microservices communication via Model Context Protocol (MCP).
 
-## Overview
+## Architecture Overview
 
-The ecosystem consists of four microservices that work together:
+The ecosystem consists of three microservices that work together:
 
 1. **[AI Agent](ai-agent/README.md)** - Central AI assistant with chat interface, document analysis, and RAG capabilities
 2. **[Travel Service](travel/README.md)** - Hotel and flight booking service with MCP integration
-3. **[Weather Service](weather/README.md)** - Weather forecast service with MCP integration
-4. **[Backoffice Service](backoffice/README.md)** - Expense management and currency conversion service with MCP integration
+3. **[Backoffice Service](backoffice/README.md)** - Expense management and currency conversion service with MCP integration
 
-The AI Agent connects to Travel, Weather, and Backoffice services through MCP, enabling it to book travel, get weather forecasts, manage expenses, and provide comprehensive business assistance.
+The AI Agent connects to Travel and Backoffice services through Model Context Protocol (MCP), enabling it to book travel, manage expenses, and provide comprehensive business assistance.
 
 ## Quick Start
 
 ### Prerequisites
+
 - Java 21+
 - Maven 3.8+
 - Docker (for Testcontainers)
 - AWS account with Amazon Bedrock access
 
 ### Running the Services
 
-1. **Start Weather Service** (port 8081):
-   ```bash
-   cd weather/
-   mvn spring-boot:run
-   ```
+1. **Start Travel Service** (port 8082):
 
-2. **Start Travel Service** (port 8082):
    ```bash
    cd travel/
    mvn spring-boot:test-run
    ```
 
-3. **Start Backoffice Service** (port 8083):
+2. **Start Backoffice Service** (port 8083):
+
    ```bash
    cd backoffice/
    mvn spring-boot:test-run
    ```
 
-4. **Start AI Agent** (port 8080):
+3. **Start AI Agent** (port 8080):
+
    ```bash
    cd ai-agent/
    mvn spring-boot:test-run
    ```
 
 4. **Access the application**:
+
    ```
    http://localhost:8080
    ```
@@ -57,23 +55,21 @@ Each service uses Testcontainers for automatic database setup - no manual config
 ## Services
 
 ### AI Agent
+
 - **Chat interface** with persistent memory using JDBC
 - **Document analysis** (PDF, images) with multimodal AI models
 - **RAG implementation** using pgvector for knowledge base
 - **Tool integration** and MCP client for microservices
-- **Models**: OpenAI GPT-OSS-120B, Claude Sonnet 4, Amazon Nova
+- **Models**: Claude Sonnet 4, Amazon Nova
 
 ### Travel Service
+
 - **Hotel & flight booking** with comprehensive search
 - **Airport information** and flight management
 - **MCP server** exposing travel tools to AI Agent
 
-### Weather Service
-- **Weather forecasts** for any city worldwide
-- **Historical and future weather data** with external API integration
-- **MCP server** exposing weather tools to AI Agent
-
 ### Backoffice Service
+
 - **Expense management** with approval workflows
 - **Currency conversion** with real-time exchange rates
 - **MCP server** exposing business tools to AI Agent
@@ -99,18 +95,18 @@ Each service uses Testcontainers for automatic database setup - no manual config
 ## AWS Configuration
 
 Configure AWS credentials for Bedrock access:
+
 ```bash
 aws configure
 ```
 
 Ensure access to required models:
-- `openai.gpt-oss-120b-1:0`
+
 - `global.anthropic.claude-sonnet-4-20250514-v1:0`
 - `us.amazon.nova-pro-v1:0` (optional)
 
 ## Documentation
 
 - [AI Agent Documentation](ai-agent/README.md) - Detailed setup and architecture
 - [Travel Service Documentation](travel/README.md) - Travel booking API
-- [Weather Service Documentation](weather/README.md) - Weather forecast API
 - [Backoffice Service Documentation](backoffice/README.md) - Expense management API

samples/spring-ai-te-agent/ai-agent/README.md

@@ -1,129 +1,65 @@
 # Spring AI Agent
 
-A comprehensive AI-powered agent built with Spring AI framework, featuring multimodal chat capabilities, document analysis, RAG (Retrieval-Augmented Generation), persistent memory, tool integration, and Testcontainers support for development.
+A comprehensive AI-powered agent built with Spring AI framework, featuring multimodal chat capabilities, document analysis, RAG (Retrieval-Augmented Generation), persistent memory, tool integration, and Model Context Protocol (MCP) client functionality.
 
-## Related Documentation
+## Features
 
-This project is part of a larger microservices ecosystem:
+- **Multimodal Chat Interface** - Text conversations with document upload support (PDF, JPG, JPEG, PNG)
+- **Persistent Memory** - JDBC-based chat memory for conversation continuity across sessions
+- **RAG Implementation** - Knowledge base integration using pgvector for document retrieval
+- **Tool Integration** - Custom function calling capabilities for extended functionality
+- **MCP Client** - Connects to Travel and Backoffice services via Model Context Protocol
+- **Multiple AI Models** - Support for Claude Sonnet 4 and Amazon Nova
 
-- [Travel Service Documentation](../travel/README.md) - Travel booking service with hotel and flight management
-- [Backoffice Service Documentation](../backoffice/README.md) - Expense management and currency conversion service
-
-## Project Overview
-
-### Description
-
-The Spring AI Agent is a demonstration of how to build modern AI-powered applications using the Spring AI framework. It provides a complete set of capabilities for interacting with AI models, including:
-
-- Text-based conversations with persistent memory using JDBC-based chat memory
-- Document analysis (PDF, JPG, JPEG, PNG) with multimodal AI models
-- Retrieval-Augmented Generation (RAG) for knowledge base integration using pgvector
-- Tool integration for enhanced capabilities (DateTime tools)
-- Model Context Protocol (MCP) client for connecting to external services
-- Testcontainers integration for seamless development and testing
-
-The application serves as the central component in a microservices architecture, connecting to specialized services like the Travel and Backoffice applications through the Model Context Protocol (MCP).
-
-### Purpose
-
-This application serves as:
-
-1. A reference implementation for Spring AI integration in enterprise applications
-2. A demonstration of key AI application patterns (RAG, memory, tools, MCP)
-3. A practical example of building AI assistants with Spring Boot
-4. A showcase for integrating with Amazon Bedrock and other AI services
-
-### Technology Stack
-
-- **Java 21**: Latest LTS version with modern language features
-- **Spring Boot 3.5.7**: Core framework for building the application
-- **Spring AI 1.0.3**: AI integration framework
-- **Amazon Bedrock**: AI model provider (OpenAI GPT-OSS-120B, Claude Sonnet 4, Nova Pro/Premier)
-- **PostgreSQL 16**: Database with pgvector extension for vector operations
-- **Testcontainers 1.21.3**: Integration testing with containerized dependencies
-- **Thymeleaf**: Server-side templating for the web interface
-- **Docker**: Containerization for database and application
-
-## Getting Started
+## Quick Start
 
 ### Prerequisites
 
-- Java 21 or higher
-- Maven 3.8 or higher
+- Java 21+
+- Maven 3.8+
 - Docker (for Testcontainers)
 - AWS account with Amazon Bedrock access
 
-### Development with Testcontainers
-
-The application uses Testcontainers for seamless development and testing. No manual database setup is required!
-
-#### Prerequisites for Full Functionality
-
-Before starting the AI agent, ensure the dependent services are running:
-
-1. **Start Travel Service** (port 8081):
-   ```bash
-   cd travel/
-   mvn spring-boot:test-run
-   ```
-
-2. **Start Backoffice Service** (port 8082):
-   ```bash
-   cd backoffice/
-   mvn spring-boot:test-run
-   ```
-
-These services provide MCP tools that the AI agent can use for travel booking and expense management.
-
-#### Running the AI Agent
+### Running the Application
 
 ```bash
-cd ai-agent/
 mvn spring-boot:test-run
 ```
 
-This will:
-- Automatically start a PostgreSQL container with pgvector extension
-- Initialize the `ai_agent_db` database
-- Configure the application to use the containerized database
-- Connect to the travel and backoffice services via MCP
-- Start the application on port 8080
+The application will start on port 8080 with automatic PostgreSQL setup via Testcontainers.
 
-The container will be named `ai-agent-postgres` for easy identification.
+Access the web interface at: http://localhost:8080
 
-### AWS Configuration
+## Configuration
 
-1. Configure AWS credentials:
-   ```bash
-   aws configure
-   ```
+### AWS Bedrock Setup
 
-2. Ensure you have access to Amazon Bedrock and the required models (Claude Sonnet 4).
+Configure AWS credentials and region:
 
-### Building and Running the Application
+```bash
+aws configure
+export AWS_REGION=us-east-1
+```
 
-1. **With Testcontainers (Recommended for Development):**
-   ```bash
-   cd ai-agent/
-   mvn spring-boot:test-run
-   ```
+Ensure access to required models:
 
-2. **Traditional Build and Run:**
-   ```bash
-   cd ai-agent/
-   mvn clean package
-   mvn spring-boot:run
-   ```
+- `global.anthropic.claude-sonnet-4-20250514-v1:0`
+- `us.amazon.nova-pro-v1:0` (optional)
 
-3. The application will be available at:
-   ```
-   http://localhost:8080
-   ```
+## Architecture
 
-## Contributing
+The AI Agent follows a layered architecture:
 
-Contributions are welcome! Please feel free to submit a Pull Request.
+- **Web Layer** - Thymeleaf templates and REST controllers
+- **Service Layer** - Chat service with memory and RAG integration
+- **Integration Layer** - MCP client for external services
+- **Data Layer** - PostgreSQL with pgvector extension
 
-## License
+## Technology Stack
 
-This project is licensed under the MIT License - see the LICENSE file for details.
+- **Spring Boot 3.5.7** - Core framework
+- **Spring AI 1.0.3** - AI integration framework
+- **Amazon Bedrock** - AI model provider
+- **PostgreSQL 16** with pgvector extension
+- **Testcontainers 1.21.3** - Development and testing
+- **Thymeleaf** - Web templating engine