Add Prompt Egineering examples

This commit is contained in:
Christian Tzolov
2025-04-14 09:12:16 +02:00
parent e0ba3438ba
commit 5ca8720387
10 changed files with 1405 additions and 0 deletions

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@@ -41,6 +41,8 @@
<module>model-context-protocol/web-search/brave-chatbot</module>
<module>model-context-protocol/sampling/mcp-weather-webmvc-server</module>
<module>model-context-protocol/sampling/mcp-sampling-client</module>
<module>prompt-engineering/prompt-engineering-patterns</module>
</modules>
</project>

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@@ -0,0 +1,33 @@
HELP.md
target/
!.mvn/wrapper/maven-wrapper.jar
!**/src/main/**/target/
!**/src/test/**/target/
### STS ###
.apt_generated
.classpath
.factorypath
.project
.settings
.springBeans
.sts4-cache
### IntelliJ IDEA ###
.idea
*.iws
*.iml
*.ipr
### NetBeans ###
/nbproject/private/
/nbbuild/
/dist/
/nbdist/
/.nb-gradle/
build/
!**/src/main/**/build/
!**/src/test/**/build/
### VS Code ###
.vscode/

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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
wrapperVersion=3.3.2
distributionType=only-script
distributionUrl=https://repo.maven.apache.org/maven2/org/apache/maven/apache-maven/3.9.9/apache-maven-3.9.9-bin.zip

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@@ -0,0 +1,23 @@
# Prompt Engineering with Spring AI
![Spring AI Prompt Engineering](prompt-engineering-spring-ai.png)
## Overview
This repository contains practical implementations of Prompt Engineering techniques using [Spring AI](https://docs.spring.io/spring-ai/reference/index.html). These examples accompany the blog post: [Spring AI Prompt Engineering Patterns](https://spring.io/blog/2025/04/14/spring-ai-prompt-engineering-patterns).
The examples and patterns are based on the comprehensive [Prompt Engineering Guide](https://www.kaggle.com/whitepaper-prompt-engineering) that covers the theory, principles, and patterns of effective prompt engineering.
Here we shows how to translate those concepts into working Java code using Spring AI's fluent [ChatClient API](https://docs.spring.io/spring-ai/reference/api/chatclient.html).
#### Structure
The examples follow the same structure and patterns outlined in the original Goolge Prompt Egineering guide, making it easy to reference between theory and implementation.
## Resources
- [Spring AI Documentation](https://docs.spring.io/spring-ai/reference/index.html)
- [ChatClient API Reference](https://docs.spring.io/spring-ai/reference/api/chatclient.html)
- [Google's Prompt Engineering Guide](https://www.kaggle.com/whitepaper-prompt-engineering)
- [Spring AI Prompt Engineering Patterns Blog](https://spring.io/blog/2025/04/14/spring-ai-prompt-engineering-patterns)

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#!/bin/sh
# ----------------------------------------------------------------------------
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
# ----------------------------------------------------------------------------
# ----------------------------------------------------------------------------
# Apache Maven Wrapper startup batch script, version 3.3.2
#
# Optional ENV vars
# -----------------
# JAVA_HOME - location of a JDK home dir, required when download maven via java source
# MVNW_REPOURL - repo url base for downloading maven distribution
# MVNW_USERNAME/MVNW_PASSWORD - user and password for downloading maven
# MVNW_VERBOSE - true: enable verbose log; debug: trace the mvnw script; others: silence the output
# ----------------------------------------------------------------------------
set -euf
[ "${MVNW_VERBOSE-}" != debug ] || set -x
# OS specific support.
native_path() { printf %s\\n "$1"; }
case "$(uname)" in
CYGWIN* | MINGW*)
[ -z "${JAVA_HOME-}" ] || JAVA_HOME="$(cygpath --unix "$JAVA_HOME")"
native_path() { cygpath --path --windows "$1"; }
;;
esac
# set JAVACMD and JAVACCMD
set_java_home() {
# For Cygwin and MinGW, ensure paths are in Unix format before anything is touched
if [ -n "${JAVA_HOME-}" ]; then
if [ -x "$JAVA_HOME/jre/sh/java" ]; then
# IBM's JDK on AIX uses strange locations for the executables
JAVACMD="$JAVA_HOME/jre/sh/java"
JAVACCMD="$JAVA_HOME/jre/sh/javac"
else
JAVACMD="$JAVA_HOME/bin/java"
JAVACCMD="$JAVA_HOME/bin/javac"
if [ ! -x "$JAVACMD" ] || [ ! -x "$JAVACCMD" ]; then
echo "The JAVA_HOME environment variable is not defined correctly, so mvnw cannot run." >&2
echo "JAVA_HOME is set to \"$JAVA_HOME\", but \"\$JAVA_HOME/bin/java\" or \"\$JAVA_HOME/bin/javac\" does not exist." >&2
return 1
fi
fi
else
JAVACMD="$(
'set' +e
'unset' -f command 2>/dev/null
'command' -v java
)" || :
JAVACCMD="$(
'set' +e
'unset' -f command 2>/dev/null
'command' -v javac
)" || :
if [ ! -x "${JAVACMD-}" ] || [ ! -x "${JAVACCMD-}" ]; then
echo "The java/javac command does not exist in PATH nor is JAVA_HOME set, so mvnw cannot run." >&2
return 1
fi
fi
}
# hash string like Java String::hashCode
hash_string() {
str="${1:-}" h=0
while [ -n "$str" ]; do
char="${str%"${str#?}"}"
h=$(((h * 31 + $(LC_CTYPE=C printf %d "'$char")) % 4294967296))
str="${str#?}"
done
printf %x\\n $h
}
verbose() { :; }
[ "${MVNW_VERBOSE-}" != true ] || verbose() { printf %s\\n "${1-}"; }
die() {
printf %s\\n "$1" >&2
exit 1
}
trim() {
# MWRAPPER-139:
# Trims trailing and leading whitespace, carriage returns, tabs, and linefeeds.
# Needed for removing poorly interpreted newline sequences when running in more
# exotic environments such as mingw bash on Windows.
printf "%s" "${1}" | tr -d '[:space:]'
}
# parse distributionUrl and optional distributionSha256Sum, requires .mvn/wrapper/maven-wrapper.properties
while IFS="=" read -r key value; do
case "${key-}" in
distributionUrl) distributionUrl=$(trim "${value-}") ;;
distributionSha256Sum) distributionSha256Sum=$(trim "${value-}") ;;
esac
done <"${0%/*}/.mvn/wrapper/maven-wrapper.properties"
[ -n "${distributionUrl-}" ] || die "cannot read distributionUrl property in ${0%/*}/.mvn/wrapper/maven-wrapper.properties"
case "${distributionUrl##*/}" in
maven-mvnd-*bin.*)
MVN_CMD=mvnd.sh _MVNW_REPO_PATTERN=/maven/mvnd/
case "${PROCESSOR_ARCHITECTURE-}${PROCESSOR_ARCHITEW6432-}:$(uname -a)" in
*AMD64:CYGWIN* | *AMD64:MINGW*) distributionPlatform=windows-amd64 ;;
:Darwin*x86_64) distributionPlatform=darwin-amd64 ;;
:Darwin*arm64) distributionPlatform=darwin-aarch64 ;;
:Linux*x86_64*) distributionPlatform=linux-amd64 ;;
*)
echo "Cannot detect native platform for mvnd on $(uname)-$(uname -m), use pure java version" >&2
distributionPlatform=linux-amd64
;;
esac
distributionUrl="${distributionUrl%-bin.*}-$distributionPlatform.zip"
;;
maven-mvnd-*) MVN_CMD=mvnd.sh _MVNW_REPO_PATTERN=/maven/mvnd/ ;;
*) MVN_CMD="mvn${0##*/mvnw}" _MVNW_REPO_PATTERN=/org/apache/maven/ ;;
esac
# apply MVNW_REPOURL and calculate MAVEN_HOME
# maven home pattern: ~/.m2/wrapper/dists/{apache-maven-<version>,maven-mvnd-<version>-<platform>}/<hash>
[ -z "${MVNW_REPOURL-}" ] || distributionUrl="$MVNW_REPOURL$_MVNW_REPO_PATTERN${distributionUrl#*"$_MVNW_REPO_PATTERN"}"
distributionUrlName="${distributionUrl##*/}"
distributionUrlNameMain="${distributionUrlName%.*}"
distributionUrlNameMain="${distributionUrlNameMain%-bin}"
MAVEN_USER_HOME="${MAVEN_USER_HOME:-${HOME}/.m2}"
MAVEN_HOME="${MAVEN_USER_HOME}/wrapper/dists/${distributionUrlNameMain-}/$(hash_string "$distributionUrl")"
exec_maven() {
unset MVNW_VERBOSE MVNW_USERNAME MVNW_PASSWORD MVNW_REPOURL || :
exec "$MAVEN_HOME/bin/$MVN_CMD" "$@" || die "cannot exec $MAVEN_HOME/bin/$MVN_CMD"
}
if [ -d "$MAVEN_HOME" ]; then
verbose "found existing MAVEN_HOME at $MAVEN_HOME"
exec_maven "$@"
fi
case "${distributionUrl-}" in
*?-bin.zip | *?maven-mvnd-?*-?*.zip) ;;
*) die "distributionUrl is not valid, must match *-bin.zip or maven-mvnd-*.zip, but found '${distributionUrl-}'" ;;
esac
# prepare tmp dir
if TMP_DOWNLOAD_DIR="$(mktemp -d)" && [ -d "$TMP_DOWNLOAD_DIR" ]; then
clean() { rm -rf -- "$TMP_DOWNLOAD_DIR"; }
trap clean HUP INT TERM EXIT
else
die "cannot create temp dir"
fi
mkdir -p -- "${MAVEN_HOME%/*}"
# Download and Install Apache Maven
verbose "Couldn't find MAVEN_HOME, downloading and installing it ..."
verbose "Downloading from: $distributionUrl"
verbose "Downloading to: $TMP_DOWNLOAD_DIR/$distributionUrlName"
# select .zip or .tar.gz
if ! command -v unzip >/dev/null; then
distributionUrl="${distributionUrl%.zip}.tar.gz"
distributionUrlName="${distributionUrl##*/}"
fi
# verbose opt
__MVNW_QUIET_WGET=--quiet __MVNW_QUIET_CURL=--silent __MVNW_QUIET_UNZIP=-q __MVNW_QUIET_TAR=''
[ "${MVNW_VERBOSE-}" != true ] || __MVNW_QUIET_WGET='' __MVNW_QUIET_CURL='' __MVNW_QUIET_UNZIP='' __MVNW_QUIET_TAR=v
# normalize http auth
case "${MVNW_PASSWORD:+has-password}" in
'') MVNW_USERNAME='' MVNW_PASSWORD='' ;;
has-password) [ -n "${MVNW_USERNAME-}" ] || MVNW_USERNAME='' MVNW_PASSWORD='' ;;
esac
if [ -z "${MVNW_USERNAME-}" ] && command -v wget >/dev/null; then
verbose "Found wget ... using wget"
wget ${__MVNW_QUIET_WGET:+"$__MVNW_QUIET_WGET"} "$distributionUrl" -O "$TMP_DOWNLOAD_DIR/$distributionUrlName" || die "wget: Failed to fetch $distributionUrl"
elif [ -z "${MVNW_USERNAME-}" ] && command -v curl >/dev/null; then
verbose "Found curl ... using curl"
curl ${__MVNW_QUIET_CURL:+"$__MVNW_QUIET_CURL"} -f -L -o "$TMP_DOWNLOAD_DIR/$distributionUrlName" "$distributionUrl" || die "curl: Failed to fetch $distributionUrl"
elif set_java_home; then
verbose "Falling back to use Java to download"
javaSource="$TMP_DOWNLOAD_DIR/Downloader.java"
targetZip="$TMP_DOWNLOAD_DIR/$distributionUrlName"
cat >"$javaSource" <<-END
public class Downloader extends java.net.Authenticator
{
protected java.net.PasswordAuthentication getPasswordAuthentication()
{
return new java.net.PasswordAuthentication( System.getenv( "MVNW_USERNAME" ), System.getenv( "MVNW_PASSWORD" ).toCharArray() );
}
public static void main( String[] args ) throws Exception
{
setDefault( new Downloader() );
java.nio.file.Files.copy( java.net.URI.create( args[0] ).toURL().openStream(), java.nio.file.Paths.get( args[1] ).toAbsolutePath().normalize() );
}
}
END
# For Cygwin/MinGW, switch paths to Windows format before running javac and java
verbose " - Compiling Downloader.java ..."
"$(native_path "$JAVACCMD")" "$(native_path "$javaSource")" || die "Failed to compile Downloader.java"
verbose " - Running Downloader.java ..."
"$(native_path "$JAVACMD")" -cp "$(native_path "$TMP_DOWNLOAD_DIR")" Downloader "$distributionUrl" "$(native_path "$targetZip")"
fi
# If specified, validate the SHA-256 sum of the Maven distribution zip file
if [ -n "${distributionSha256Sum-}" ]; then
distributionSha256Result=false
if [ "$MVN_CMD" = mvnd.sh ]; then
echo "Checksum validation is not supported for maven-mvnd." >&2
echo "Please disable validation by removing 'distributionSha256Sum' from your maven-wrapper.properties." >&2
exit 1
elif command -v sha256sum >/dev/null; then
if echo "$distributionSha256Sum $TMP_DOWNLOAD_DIR/$distributionUrlName" | sha256sum -c >/dev/null 2>&1; then
distributionSha256Result=true
fi
elif command -v shasum >/dev/null; then
if echo "$distributionSha256Sum $TMP_DOWNLOAD_DIR/$distributionUrlName" | shasum -a 256 -c >/dev/null 2>&1; then
distributionSha256Result=true
fi
else
echo "Checksum validation was requested but neither 'sha256sum' or 'shasum' are available." >&2
echo "Please install either command, or disable validation by removing 'distributionSha256Sum' from your maven-wrapper.properties." >&2
exit 1
fi
if [ $distributionSha256Result = false ]; then
echo "Error: Failed to validate Maven distribution SHA-256, your Maven distribution might be compromised." >&2
echo "If you updated your Maven version, you need to update the specified distributionSha256Sum property." >&2
exit 1
fi
fi
# unzip and move
if command -v unzip >/dev/null; then
unzip ${__MVNW_QUIET_UNZIP:+"$__MVNW_QUIET_UNZIP"} "$TMP_DOWNLOAD_DIR/$distributionUrlName" -d "$TMP_DOWNLOAD_DIR" || die "failed to unzip"
else
tar xzf${__MVNW_QUIET_TAR:+"$__MVNW_QUIET_TAR"} "$TMP_DOWNLOAD_DIR/$distributionUrlName" -C "$TMP_DOWNLOAD_DIR" || die "failed to untar"
fi
printf %s\\n "$distributionUrl" >"$TMP_DOWNLOAD_DIR/$distributionUrlNameMain/mvnw.url"
mv -- "$TMP_DOWNLOAD_DIR/$distributionUrlNameMain" "$MAVEN_HOME" || [ -d "$MAVEN_HOME" ] || die "fail to move MAVEN_HOME"
clean || :
exec_maven "$@"

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<# : batch portion
@REM ----------------------------------------------------------------------------
@REM Licensed to the Apache Software Foundation (ASF) under one
@REM or more contributor license agreements. See the NOTICE file
@REM distributed with this work for additional information
@REM regarding copyright ownership. The ASF licenses this file
@REM to you under the Apache License, Version 2.0 (the
@REM "License"); you may not use this file except in compliance
@REM with the License. You may obtain a copy of the License at
@REM
@REM http://www.apache.org/licenses/LICENSE-2.0
@REM
@REM Unless required by applicable law or agreed to in writing,
@REM software distributed under the License is distributed on an
@REM "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
@REM KIND, either express or implied. See the License for the
@REM specific language governing permissions and limitations
@REM under the License.
@REM ----------------------------------------------------------------------------
@REM ----------------------------------------------------------------------------
@REM Apache Maven Wrapper startup batch script, version 3.3.2
@REM
@REM Optional ENV vars
@REM MVNW_REPOURL - repo url base for downloading maven distribution
@REM MVNW_USERNAME/MVNW_PASSWORD - user and password for downloading maven
@REM MVNW_VERBOSE - true: enable verbose log; others: silence the output
@REM ----------------------------------------------------------------------------
@IF "%__MVNW_ARG0_NAME__%"=="" (SET __MVNW_ARG0_NAME__=%~nx0)
@SET __MVNW_CMD__=
@SET __MVNW_ERROR__=
@SET __MVNW_PSMODULEP_SAVE=%PSModulePath%
@SET PSModulePath=
@FOR /F "usebackq tokens=1* delims==" %%A IN (`powershell -noprofile "& {$scriptDir='%~dp0'; $script='%__MVNW_ARG0_NAME__%'; icm -ScriptBlock ([Scriptblock]::Create((Get-Content -Raw '%~f0'))) -NoNewScope}"`) DO @(
IF "%%A"=="MVN_CMD" (set __MVNW_CMD__=%%B) ELSE IF "%%B"=="" (echo %%A) ELSE (echo %%A=%%B)
)
@SET PSModulePath=%__MVNW_PSMODULEP_SAVE%
@SET __MVNW_PSMODULEP_SAVE=
@SET __MVNW_ARG0_NAME__=
@SET MVNW_USERNAME=
@SET MVNW_PASSWORD=
@IF NOT "%__MVNW_CMD__%"=="" (%__MVNW_CMD__% %*)
@echo Cannot start maven from wrapper >&2 && exit /b 1
@GOTO :EOF
: end batch / begin powershell #>
$ErrorActionPreference = "Stop"
if ($env:MVNW_VERBOSE -eq "true") {
$VerbosePreference = "Continue"
}
# calculate distributionUrl, requires .mvn/wrapper/maven-wrapper.properties
$distributionUrl = (Get-Content -Raw "$scriptDir/.mvn/wrapper/maven-wrapper.properties" | ConvertFrom-StringData).distributionUrl
if (!$distributionUrl) {
Write-Error "cannot read distributionUrl property in $scriptDir/.mvn/wrapper/maven-wrapper.properties"
}
switch -wildcard -casesensitive ( $($distributionUrl -replace '^.*/','') ) {
"maven-mvnd-*" {
$USE_MVND = $true
$distributionUrl = $distributionUrl -replace '-bin\.[^.]*$',"-windows-amd64.zip"
$MVN_CMD = "mvnd.cmd"
break
}
default {
$USE_MVND = $false
$MVN_CMD = $script -replace '^mvnw','mvn'
break
}
}
# apply MVNW_REPOURL and calculate MAVEN_HOME
# maven home pattern: ~/.m2/wrapper/dists/{apache-maven-<version>,maven-mvnd-<version>-<platform>}/<hash>
if ($env:MVNW_REPOURL) {
$MVNW_REPO_PATTERN = if ($USE_MVND) { "/org/apache/maven/" } else { "/maven/mvnd/" }
$distributionUrl = "$env:MVNW_REPOURL$MVNW_REPO_PATTERN$($distributionUrl -replace '^.*'+$MVNW_REPO_PATTERN,'')"
}
$distributionUrlName = $distributionUrl -replace '^.*/',''
$distributionUrlNameMain = $distributionUrlName -replace '\.[^.]*$','' -replace '-bin$',''
$MAVEN_HOME_PARENT = "$HOME/.m2/wrapper/dists/$distributionUrlNameMain"
if ($env:MAVEN_USER_HOME) {
$MAVEN_HOME_PARENT = "$env:MAVEN_USER_HOME/wrapper/dists/$distributionUrlNameMain"
}
$MAVEN_HOME_NAME = ([System.Security.Cryptography.MD5]::Create().ComputeHash([byte[]][char[]]$distributionUrl) | ForEach-Object {$_.ToString("x2")}) -join ''
$MAVEN_HOME = "$MAVEN_HOME_PARENT/$MAVEN_HOME_NAME"
if (Test-Path -Path "$MAVEN_HOME" -PathType Container) {
Write-Verbose "found existing MAVEN_HOME at $MAVEN_HOME"
Write-Output "MVN_CMD=$MAVEN_HOME/bin/$MVN_CMD"
exit $?
}
if (! $distributionUrlNameMain -or ($distributionUrlName -eq $distributionUrlNameMain)) {
Write-Error "distributionUrl is not valid, must end with *-bin.zip, but found $distributionUrl"
}
# prepare tmp dir
$TMP_DOWNLOAD_DIR_HOLDER = New-TemporaryFile
$TMP_DOWNLOAD_DIR = New-Item -Itemtype Directory -Path "$TMP_DOWNLOAD_DIR_HOLDER.dir"
$TMP_DOWNLOAD_DIR_HOLDER.Delete() | Out-Null
trap {
if ($TMP_DOWNLOAD_DIR.Exists) {
try { Remove-Item $TMP_DOWNLOAD_DIR -Recurse -Force | Out-Null }
catch { Write-Warning "Cannot remove $TMP_DOWNLOAD_DIR" }
}
}
New-Item -Itemtype Directory -Path "$MAVEN_HOME_PARENT" -Force | Out-Null
# Download and Install Apache Maven
Write-Verbose "Couldn't find MAVEN_HOME, downloading and installing it ..."
Write-Verbose "Downloading from: $distributionUrl"
Write-Verbose "Downloading to: $TMP_DOWNLOAD_DIR/$distributionUrlName"
$webclient = New-Object System.Net.WebClient
if ($env:MVNW_USERNAME -and $env:MVNW_PASSWORD) {
$webclient.Credentials = New-Object System.Net.NetworkCredential($env:MVNW_USERNAME, $env:MVNW_PASSWORD)
}
[Net.ServicePointManager]::SecurityProtocol = [Net.SecurityProtocolType]::Tls12
$webclient.DownloadFile($distributionUrl, "$TMP_DOWNLOAD_DIR/$distributionUrlName") | Out-Null
# If specified, validate the SHA-256 sum of the Maven distribution zip file
$distributionSha256Sum = (Get-Content -Raw "$scriptDir/.mvn/wrapper/maven-wrapper.properties" | ConvertFrom-StringData).distributionSha256Sum
if ($distributionSha256Sum) {
if ($USE_MVND) {
Write-Error "Checksum validation is not supported for maven-mvnd. `nPlease disable validation by removing 'distributionSha256Sum' from your maven-wrapper.properties."
}
Import-Module $PSHOME\Modules\Microsoft.PowerShell.Utility -Function Get-FileHash
if ((Get-FileHash "$TMP_DOWNLOAD_DIR/$distributionUrlName" -Algorithm SHA256).Hash.ToLower() -ne $distributionSha256Sum) {
Write-Error "Error: Failed to validate Maven distribution SHA-256, your Maven distribution might be compromised. If you updated your Maven version, you need to update the specified distributionSha256Sum property."
}
}
# unzip and move
Expand-Archive "$TMP_DOWNLOAD_DIR/$distributionUrlName" -DestinationPath "$TMP_DOWNLOAD_DIR" | Out-Null
Rename-Item -Path "$TMP_DOWNLOAD_DIR/$distributionUrlNameMain" -NewName $MAVEN_HOME_NAME | Out-Null
try {
Move-Item -Path "$TMP_DOWNLOAD_DIR/$MAVEN_HOME_NAME" -Destination $MAVEN_HOME_PARENT | Out-Null
} catch {
if (! (Test-Path -Path "$MAVEN_HOME" -PathType Container)) {
Write-Error "fail to move MAVEN_HOME"
}
} finally {
try { Remove-Item $TMP_DOWNLOAD_DIR -Recurse -Force | Out-Null }
catch { Write-Warning "Cannot remove $TMP_DOWNLOAD_DIR" }
}
Write-Output "MVN_CMD=$MAVEN_HOME/bin/$MVN_CMD"

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<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>3.4.4</version>
<relativePath/> <!-- lookup parent from repository -->
</parent>
<groupId>org.springframework.ai.example</groupId>
<artifactId>prompt-engineering-patterns</artifactId>
<version>0.0.1-SNAPSHOT</version>
<name>prompt-engineering-patterns</name>
<description>Demo project for Spring Boot</description>
<properties>
<java.version>17</java.version>
<spring-ai.version>1.0.0-M7</spring-ai.version>
</properties>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-starter-model-anthropic</artifactId>
</dependency>
</dependencies>
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-bom</artifactId>
<version>${spring-ai.version}</version>
<type>pom</type>
<scope>import</scope>
</dependency>
</dependencies>
</dependencyManagement>
<build>
<plugins>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
</plugin>
</plugins>
</build>
</project>

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package org.springframework.ai.example.prompt_engineering;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.prompt.ChatOptions;
import org.springframework.boot.CommandLineRunner;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;
/**
* @author Christian Tzolov
*/
@SpringBootApplication
public class PromptEngineeringApplication {
ObjectMapper objectMapper = new ObjectMapper();
public static void main(String[] args) {
SpringApplication.run(PromptEngineeringApplication.class, args);
}
@Bean
public CommandLineRunner commandLineRunner(ChatClient.Builder chatClientBuilder) {
return args -> {
ChatClient chatClient = chatClientBuilder.build();
//@formatter:off
// 2. Prompting techniques (page 13)
// 2.1 General prompting / zero shot (page 15)
pt_zero_shot(chatClient);
// 2.2 One-shot & few-shot
pt_ones_shot_few_shots(chatClient);
// 2.3 System, contextual and role prompting
// 2.3.1 System prompting
pt_system_prompting_1(chatClient);
pt_system_prompting_2(chatClient);
pt_system_prompting_2_springai_style(chatClient);
// 2.3.2 Role prompting
pt_role_prompting_1(chatClient);
pt_role_prompting_2(chatClient); // in a humorous style.
// 2.3.3 Contextual prompting
pt_contextual_prompting(chatClient);
// 2.4 Step-back prompting
pt_step_back_prompting(chatClient.mutate());
// 2.5 Chain of Thought (CoT)
pt_chain_of_thought_zero_shot(chatClient);
pt_chain_of_thought_singleshot_fewshots(chatClient);
// 2.6 Self-consistency
pt_self_consistency(chatClient);
// 2.7 Tree of Thoughts (ToT)
pt_tree_of_thoughts_game(chatClient);
pt_tree_of_thoughts_problem(chatClient);
// 2.8 Automatic Prompt Engineering
pt_automatic_prompt_engineering(chatClient);
// 2.9 Code prompting
// 2.9.1 Prompts for writing code
pt_code_prompting_writing_code(chatClient);
// 2.9.2 Prompts for explaining code
pt_code_prompting_explaining_code(chatClient);
// 2.9.3 Prompts for translating code
pt_code_prompting_translating_code(chatClient);
//@formatter:on
};
}
// 2.1 General prompting / zero shot (page 15)
public void pt_zero_shot(ChatClient chatClient) {
// General prompting / zero shot (page 15)
enum Sentiment {
POSITIVE, NEUTRAL, NEGATIVE
}
Sentiment reviewSentiment = chatClient.prompt("""
Classify movie reviews as POSITIVE, NEUTRAL or NEGATIVE.
Review: "Her" is a disturbing study revealing the direction
humanity is headed if AI is allowed to keep evolving,
unchecked. I wish there were more movies like this masterpiece.
Sentiment:
""")
.options(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(0.1)
.maxTokens(5)
.build())
.call()
.entity(Sentiment.class);
System.out.println("Output: " + reviewSentiment);
}
// 2.2 One-shot & few-shot
public void pt_ones_shot_few_shots(ChatClient chatClient) {
// One-shot & few-shot
// When creating prompts for AI models, it is helpful to provide examples.
// These examples can help the model understand what you are asking for.
// - one-shot prompt: provides a single example to the model.
// - few-shot prompt: provides multiple examples to the model.
// A few-shot prompt example, let's use the same gemini-pro model
// configuration settings as before, other than increasing the token limit to
// accommodate the
// need for a longer response. (page 16)
String pizzaOrder = chatClient.prompt("""
Parse a customer's pizza order into valid JSON
EXAMPLE 1:
I want a small pizza with cheese, tomato sauce, and pepperoni.
JSON Response:
```
{
"size": "small",
"type": "normal",
"ingredients": ["cheese", "tomato sauce", "peperoni"]
}
```
EXAMPLE 2:
Can I get a large pizza with tomato sauce, basil and mozzarella.
JSON Response:
```
{
"size": "large",
"type": "normal",
"ingredients": ["tomato sauce", "basil", "mozzarella"]
}
```
Now, I would like a large pizza, with the first half cheese and mozzarella.
And the other tomato sauce, ham and pineapple.
""")
.options(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(0.1)
// Increasing the token limit to accommodate the need for a longer response.
.maxTokens(250)
.build())
.call()
.content();
System.out.println("Output: " + pizzaOrder);
// NOTE: The number of examples you need for few-shot prompting depends on a few
// factors,
// including the complexity of the task, the quality of the examples, and the
// capabilities of the
// generative AI (gen AI) model you are using. As a general rule of thumb, you
// should use at
// least three to five examples for few-shot prompting.
//
// To generate output that is robust to a variety of inputs, it is important to
// include edge
// cases in your examples. Edge cases are inputs that are unusual or unexpected,
// but that the model should still be able to handle.
}
// Sets the overall context and purpose for the language model. It
// defines the 'big picture' of what the model should be doing, like translating
// a language, classifying a review etc.
// 2.3.1 System prompting (1)
public void pt_system_prompting_1(ChatClient chatClient) {
String movieReview = chatClient
.prompt()
.system("Classify movie reviews as positive, neutral or negative. Only return the label in uppercase.")
.user("""
Review: "Her" is a disturbing study revealing the direction
humanity is headed if AI is allowed to keep evolving,
unchecked. It's so disturbing I couldn't watch it.
Sentiment:
""")
.options(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(1.0)
.topK(40)
.topP(0.8)
.maxTokens(5)
.build())
.call()
.content();
System.out.println("Output: " + movieReview);
// We increased the temperature to get a higher creativity level, and I
// specified a higher token limit. However, because of my clear instruction on
// how to return the output the model didn't return extra text
}
// You could use a system prompt to generate a code snippet that is compatible
// with a specific programming language, or you could use a system prompt to
// return a certain structure like output in JSON format.
// 2.3.1 System prompting (2)
public void pt_system_prompting_2(ChatClient chatClient) {
String movieReview = chatClient
.prompt()
.system("""
Classify movie reviews as positive, neutral or negative. Return
valid JSON.
Use the Schema:
```
MOVIE:
{
"sentiment": String "POSITIVE" | "NEGATIVE" | "NEUTRAL",
"name": String
}
MOVIE REVIEWS:
{
"movie_reviews": [MOVIE]
}
```
""")
.user("""
Review: "Her" is a disturbing study revealing the direction
humanity is headed if AI is allowed to keep evolving,
unchecked. It's so disturbing I couldn't watch it.
JSON Response:
""")
.options(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(1.0)
.topK(40)
.topP(0.8)
.maxTokens(1024)
.build())
.call()
.content();
System.out.println("Output: " + movieReview);
}
// 2.3.1 (3) spring-ai System prompting - SpringAI style
public void pt_system_prompting_2_springai_style(ChatClient chatClient) throws JsonProcessingException {
record MovieReviews(Movie[] movie_reviews) {
enum Sentiment {
POSITIVE, NEUTRAL, NEGATIVE
}
record Movie(Sentiment sentiment, String name) {
}
}
MovieReviews movieReviews = chatClient
.prompt()
.system("""
Classify movie reviews as positive, neutral or negative. Return
valid JSON.
""")
.user("""
Review: "Her" is a disturbing study revealing the direction
humanity is headed if AI is allowed to keep evolving,
unchecked. It's so disturbing I couldn't watch it.
JSON Response:
""")
.options(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(1.0)
.topK(40)
.topP(0.8)
.maxTokens(1024)
.build())
.call()
.entity(MovieReviews.class);
System.out.println("Output: " + objectMapper.writeValueAsString(movieReviews));
}
// 2.3.2 Role prompting (1)
public void pt_role_prompting_1(ChatClient chatClient) {
// Goal Act as travel guide and provide 3 travel suggestions
String movieReview = chatClient
.prompt()
.system("""
I want you to act as a travel guide. I will write to you
about my location and you will suggest 3 places to visit near
me. In some cases, I will also give you the type of places I
will visit.
""")
.user("""
My suggestion: "I am in Amsterdam and I want to visit only museums."
Travel Suggestions:
""")
.options(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(1.0)
.topK(40)
.topP(0.8)
.maxTokens(1024)
.build())
.call()
.content();
System.out.println("Output: " + movieReview);
}
// 2.3.2 Role prompting (2)
public void pt_role_prompting_2(ChatClient chatClient) {
// Goal Act as travel guide and provide 3 travel suggestions
//
// In a humorous style.
String movieReview = chatClient
.prompt()
.system("""
I want you to act as a travel guide. I will write to you about
my location and you will suggest 3 places to visit near me in
a humorous style.
""")
.user("""
My suggestion: "I am in Amsterdam and I want to visit only museums."
Travel Suggestions:
""")
.options(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(1.0)
.topK(40)
.topP(0.8)
.maxTokens(1024)
.build())
.call()
.content();
System.out.println("Output: " + movieReview);
}
// 2.3.3 Contextual prompting
public void pt_contextual_prompting(ChatClient chatClient) {
// Goal: Suggest articles for a blog about retro games
String movieReview = chatClient
.prompt()
.user(u -> u.text("""
Suggest 3 topics to write an article about with a few lines of
description of what this article should contain.
Context: {context}
""")
.param("context", "You are writing for a blog about retro 80's arcade video games."))
.options(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(1.0)
.topK(40)
.topP(0.8)
.maxTokens(1024)
.build())
.call()
.content();
System.out.println("Output: " + movieReview);
}
// 2.4 Step-back prompting
public void pt_step_back_prompting(ChatClient.Builder chatClientBuilder) {
// (SpringAI tip) Set common options for the chat client.
var chatClient = chatClientBuilder
.defaultOptions(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(1.0)
.topK(40)
.topP(0.8)
.maxTokens(1024)
.build())
.build();
// Goal: Write a storyline for a level of a first-person shooter video game.
String stepBack = chatClient
.prompt("""
Based on popular first-person shooter action games, what are
5 fictional key settings that contribute to a challenging and
engaging level storyline in a first-person shooter video game?
""")
.call()
.content();
System.out.println("StepBack Output: " + stepBack + "\n");
String story = chatClient
.prompt()
.user(u -> u.text("""
Write a one paragraph storyline for a new level of a first-
person shooter video game that is challenging and engaging.
Context: {step-back}
""")
.param("step-back", stepBack))
.call()
.content();
System.out.println("Output: " + story);
}
// 2.5 Chain of Thought (CoT)
// 'zero-shot' Chain of thought.
public void pt_chain_of_thought_zero_shot(ChatClient chatClient) {
String output = chatClient
.prompt("""
When I was 3 years old, my partner was 3 times my age. Now,
I am 20 years old. How old is my partner?
Let's think step by step.
""")
.call()
.content();
System.out.println("Output: " + output + "\n");
}
public void pt_chain_of_thought_singleshot_fewshots(ChatClient chatClient) {
String output = chatClient
.prompt("""
Q: When my brother was 2 years old, I was double his age. Now
I am 40 years old. How old is my brother? Let's think step
by step.
A: When my brother was 2 years, I was 2 * 2 = 4 years old.
That's an age difference of 2 years and I am older. Now I am 40
years old, so my brother is 40 - 2 = 38 years old. The answer
is 38.
Q: When I was 3 years old, my partner was 3 times my age. Now,
I am 20 years old. How old is my partner? Let's think step
by step.
A:
""")
.call()
.content();
System.out.println("Output: " + output + "\n");
}
// 2.6 Self-consistency
public void pt_self_consistency(ChatClient chatClient) {
String email = """
Hi,
I have seen you use Wordpress for your website. A great open
source content management system. I have used it in the past
too. It comes with lots of great user plugins. And it's pretty
easy to set up.
I did notice a bug in the contact form, which happens when
you select the name field. See the attached screenshot of me
entering text in the name field. Notice the JavaScript alert
box that I inv0k3d.
But for the rest it's a great website. I enjoy reading it. Feel
free to leave the bug in the website, because it gives me more
interesting things to read.
Cheers,
Harry the Hacker.
""";
record EmailClassification(Classification classification, String reasoning) {
enum Classification {
IMPORTANT, NOT_IMPORTANT
}
}
int importantCount = 0;
int notImportantCount = 0;
for (int i = 0; i < 5; i++) {
EmailClassification output = chatClient
.prompt()
.user(u -> u.text("""
Email: {email}
Classify the above email as IMPORTANT or NOT IMPORTANT. Let's
think step by step and explain why.
""")
.param("email", email))
.options(ChatOptions.builder()
.model("claude-3-5-haiku-latest")
.temperature(1.0)
.topK(60)
.topP(0.9)
.maxTokens(1024)
.build())
.call()
.entity(EmailClassification.class);
if (output.classification() == EmailClassification.Classification.IMPORTANT) {
importantCount++;
} else {
notImportantCount++;
}
System.out
.println("Classification: [" + output.classification() + "], Reason: " + output.reasoning() + "\n");
}
if (importantCount > notImportantCount) {
System.out.println("The email is IMPORTANT. Count: " + importantCount);
} else {
System.out.println("The email is NOT IMPORTANT. Count: " + notImportantCount);
}
}
// 2.7 Tree of Thoughts (ToT)
// Implementation of Section 2.7: Tree of Thoughts (ToT) - Game solving example
public void pt_tree_of_thoughts_game(ChatClient chatClient) {
// Step 1: Generate multiple initial moves
String initialMoves = chatClient
.prompt("""
You are playing a game of chess. The board is in the starting position.
Generate 3 different possible opening moves. For each move:
1. Describe the move in algebraic notation
2. Explain the strategic thinking behind this move
3. Rate the move's strength from 1-10
""")
.options(ChatOptions.builder()
.temperature(0.7)
.build())
.call()
.content();
System.out.println("Initial Moves: " + initialMoves + "\n");
// Step 2: Evaluate and select the most promising move
String bestMove = chatClient
.prompt()
.user(u -> u.text("""
Analyze these opening moves and select the strongest one:
{moves}
Explain your reasoning step by step, considering:
1. Position control
2. Development potential
3. Long-term strategic advantage
Then select the single best move.
""").param("moves", initialMoves))
.call()
.content();
System.out.println("Best Move: " + bestMove + "\n");
// Step 3: Explore future game states from the best move
String gameProjection = chatClient
.prompt()
.user(u -> u.text("""
Based on this selected opening move:
{best_move}
Project the next 3 moves for both players. For each potential branch:
1. Describe the move and counter-move
2. Evaluate the resulting position
3. Identify the most promising continuation
Finally, determine the most advantageous sequence of moves.
""").param("best_move", bestMove))
.call()
.content();
System.out.println("Game Projection: " + gameProjection + "\n");
}
// Implementation of Section 2.7: Tree of Thoughts (ToT) - Problem solving
public void pt_tree_of_thoughts_problem(ChatClient chatClient) {
String problem = "Design a system to recommend movies to users based on their viewing history.";
// Step 1: Generate multiple solution approaches
String approaches = chatClient
.prompt()
.user(u -> u.text("""
Problem: {problem}
Generate 3 different approaches to solve this problem:
1. A content-based filtering approach
2. A collaborative filtering approach
3. A hybrid approach
For each approach, describe:
- The core algorithm/technique
- Key data requirements
- Potential advantages and limitations
""").param("problem", problem))
.call()
.content();
System.out.println("Approaches: " + approaches + "\n");
// Step 2: Evaluate approaches and select the most promising
String bestApproach = chatClient
.prompt()
.user(u -> u.text("""
Evaluate these solution approaches:
{approaches}
Compare them based on:
1. Scalability
2. Accuracy
3. Implementation complexity
4. Cold-start handling
Select the most promising approach with detailed reasoning.
""").param("approaches", approaches))
.call()
.content();
System.out.println("Best Approach: " + bestApproach + "\n");
// Step 3: Refine and elaborate on the selected approach
String refinedSolution = chatClient
.prompt()
.user(u -> u.text("""
Based on the selected approach:
{best_approach}
Develop a detailed implementation plan:
1. System architecture
2. Data processing pipeline
3. Algorithm implementation details
4. Evaluation methodology
Address any limitations identified earlier and propose solutions.
""").param("best_approach", bestApproach))
.call()
.content();
System.out.println("Refined Solution: " + refinedSolution + "\n");
}
// 2.8 Automatic Prompt Engineering
public void pt_automatic_prompt_engineering(ChatClient chatClient) {
String orderVariants = chatClient
.prompt("""
We have a band merchandise t-shirt webshop, and to train a
chatbot we need various ways to order: "One Metallica t-shirt
size S". Generate 10 variants, with the same semantics but keep
the same meaning.
""")
.options(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(1.0)
.topK(40)
.topP(0.9)
.maxTokens(1024)
.build())
.call()
.content();
System.out.println("Variants: " + orderVariants + "\n");
String output = chatClient
.prompt()
.user(u -> u.text("""
Please perform BLEU (Bilingual Evaluation Understudy) evaluation on the following variants:
----
{variants}
----
Select the instruction candidate with the highest evaluation score.
""").param("variants", orderVariants))
.options(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(1.0)
.topK(40)
.topP(0.9)
.maxTokens(1024)
.build())
.call()
.content();
System.out.println("Output: " + output + "\n");
}
// 2.9.1 Prompts for writing code
public void pt_code_prompting_writing_code(ChatClient chatClient) {
// Goal: Write a prompt to write code in Bash to rename files in a folder.
String output = chatClient
.prompt("""
Write a code snippet in Bash, which asks for a folder name.
Then it takes the contents of the folder and renames all the
files inside by prepending the name draft to the file name.
""")
.options(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(0.1)
.topP(1.0)
.maxTokens(1024)
.build())
.call()
.content();
System.out.println("Output: " + output + "\n");
}
// 2.9.2 Prompts for explaining code
public void pt_code_prompting_explaining_code(ChatClient chatClient) {
// Goal: Write a prompt to explain Bash code.
String code = """
#!/bin/bash
echo "Enter the folder name: "
read folder_name
if [ ! -d "$folder_name" ]; then
echo "Folder does not exist."
exit 1
fi
files=( "$folder_name"/* )
for file in "${files[@]}"; do
new_file_name="draft_$(basename "$file")"
mv "$file" "$new_file_name"
done
echo "Files renamed successfully."
""";
String output = chatClient
.prompt()
.user(u -> u.text("""
Explain to me the below Bash code:
```
{code}
```
""").param("code", code))
.options(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(0.1)
.topP(1.0)
.maxTokens(1024)
.build())
.call()
.content();
System.out.println("Output: " + output + "\n");
}
// 2.9.3 Prompts for translating code
public void pt_code_prompting_translating_code(ChatClient chatClient) {
// Goal: Write a prompt to translate Bash code to Python
String bashCode = """
```bash
#!/bin/bash
echo "Enter the folder name: "
read folder_name
if [ ! -d "$folder_name" ]; then
echo "Folder does not exist."
exit 1
fi
files=( "$folder_name"/* )
for file in "${files[@]}"; do
new_file_name="draft_$(basename "$file")"
mv "$file" "$new_file_name"
done
echo "Files renamed successfully."
```
""";
String output = chatClient
.prompt()
.user(u -> u.text("""
Translate the below Bash code to a Python snippet:
{code}
""").param("code", bashCode))
.options(ChatOptions.builder()
.model("claude-3-7-sonnet-latest")
.temperature(0.1)
.topP(1.0)
.maxTokens(1024)
.build())
.call()
.content();
System.out.println("Output: " + output + "\n");
}
}

View File

@@ -0,0 +1,44 @@
spring.application.name=prompt-engineering
spring.main.web-application-type=none
# 1. First you start by choosing a model. E.g. Anthropic Claude, OpenAI, etc.
# 2. Once you choose your model you will need to figure out the model configuration.
# Most LLMs come with various configuration options that control the LLMs output.
# 2.1 select the provider's specifc model and set the connection and access options
spring.ai.anthropic.chat.options.model=claude-3-7-sonnet-latest
spring.ai.anthropic.api-key=${ANTHROPIC_API_KEY}
#spring.ai.openai.api-key=${OPENAI_API_KEY}
# 2.2 Output length controls the number of tokens to generate in a response.
spring.ai.anthropic.chat.options.max-tokens=500
# 2.3 Sampling controls the randomness of the models output.
# 2.3.1 Temperature
# Temperature controls the degree of randomness in token selection.
# Lower temperatures are good for prompts that expect a more deterministic response,
# while higher temperatures can lead to more diverse or unexpected results.
spring.ai.anthropic.chat.options.temperature=0.7
# 2.3.2 Top-K and top-P
# The best way to choose between top-K and top-P is to experiment with both methods
# (or both together) and see which one produces the results you are looking for.
# Top-K
# Selects the top K most likely tokens from the models predicted distribution.
# The higher top-K, the more creative and varied the models output;
# the lower top-K, the more restive and factual the models output.
#spring.ai.anthropic.chat.options.top-k=
# Top-P
# Selects the top tokens whose cumulative probability does not exceed a certain value (P).
# Values for P range from 0 (greedy decoding) to 1 (all tokens in the LLMs vocabulary).
#spring.ai.anthropic.chat.options.top-p=1.0
# ...
#spring.ai.anthropic.chat.options.stop-sequences=