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clean up

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Ralph Soika 2025-09-20 14:49:57 +02:00
parent e862b1ac09
commit 1bd6e0f4c5
15 changed files with 0 additions and 2759 deletions
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147
dynamixs-ai-rag/pom.xml
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<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 http://maven.apache.org/maven-v4_0_0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<artifactId>dynamixs-ai</artifactId>
<groupId>ai.dynamixs</groupId>
<version>1.0.0</version>
</parent>
<artifactId>dynamixs-ai-rag</artifactId>
<packaging>jar</packaging>
<name>Dynamixs AI RAG Library</name>
<build>
<plugins>
<!-- use JDK settings for compiling -->
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.8.1</version>
<configuration>
<source>${java.source}</source>
<target>${java.target}</target>
</configuration>
</plugin>
<!-- Testing JUnit 5 -->
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-surefire-plugin</artifactId>
<version>2.22.2</version>
</plugin>
<!-- issue #572
hack for:
https://stackoverflow.com/questions/75116023/unable-to-make-protected-final-java-lang-class-java-lang-classloader-defineclass
-->
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-surefire-plugin</artifactId>
<version>3.3.1</version>
<executions>
<execution>
<id>default-test</id>
<phase>test</phase>
<goals>
<goal>test</goal>
</goals>
<configuration>
<argLine>
--add-opens java.base/java.lang=ALL-UNNAMED
</argLine>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
</build>
<dependencies>
<!-- Jakarta EE -->
<dependency>
<groupId>jakarta.platform</groupId>
<artifactId>jakarta.jakartaee-api</artifactId>
<version>${jakarta.version}</version>
<scope>provided</scope>
</dependency>
<!-- Microprofile -->
<dependency>
<groupId>org.eclipse.microprofile</groupId>
<artifactId>microprofile</artifactId>
<version>${microprofile.version}</version>
<type>pom</type>
<scope>provided</scope>
</dependency>
<!-- Imixs Workflow -->
<dependency>
<groupId>org.imixs.workflow</groupId>
<artifactId>imixs-workflow-core</artifactId>
</dependency>
<dependency>
<groupId>org.imixs.workflow</groupId>
<artifactId>imixs-workflow-engine</artifactId>
</dependency>
<dependency>
<groupId>org.imixs.workflow</groupId>
<artifactId>imixs-workflow-jax-rs</artifactId>
</dependency>
<dependency>
<groupId>org.imixs.workflow</groupId>
<artifactId>imixs-workflow-faces</artifactId>
</dependency>
<dependency>
<groupId>org.imixs.workflow</groupId>
<artifactId>imixs-workflow-index-lucene</artifactId>
</dependency>
<!-- Marty -->
<dependency>
<groupId>org.imixs.workflow</groupId>
<artifactId>imixs-marty</artifactId>
</dependency>
<!-- Imixs-Archive -->
<dependency>
<groupId>org.imixs.workflow</groupId>
<artifactId>imixs-archive-api</artifactId>
</dependency>
<!-- Imixs-AI -->
<dependency>
<groupId>org.imixs.workflow</groupId>
<artifactId>imixs-ai-workflow</artifactId>
</dependency>
<!-- DaraStax Java Driver -->
<dependency>
<groupId>org.apache.cassandra</groupId>
<artifactId>java-driver-core</artifactId>
<version>${apache.cassandra.driver.version}</version>
</dependency>
<dependency>
<groupId>org.apache.cassandra</groupId>
<artifactId>java-driver-query-builder</artifactId>
<version>${apache.cassandra.driver.version}</version>
</dependency>
<dependency>
<groupId>org.apache.cassandra</groupId>
<artifactId>java-driver-mapper-runtime</artifactId>
<version>${apache.cassandra.driver.version}</version>
</dependency>
<!-- Metrics
<dependency>
<groupId>org.imixs.workflow</groupId>
<artifactId>imixs-metrics-monitor</artifactId>
</dependency>
-->
</dependencies>
</project>

69
dynamixs-ai-rag/src/main/java/ai/dynamixs/DynamixsSetupService.java
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/*******************************************************************************
* Imixs Workflow
* Copyright (C) 2001, 2011 Imixs Software Solutions GmbH,
* http://www.imixs.com
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* General Public License for more details.
*
* You can receive a copy of the GNU General Public
* License at http://www.gnu.org/licenses/gpl.html
*
* Project:
* http://www.imixs.org
* http://java.net/projects/imixs-workflow
*
* Contributors:
* Imixs Software Solutions GmbH - initial API and implementation
* Ralph Soika - Software Developer
*******************************************************************************/
package ai.dynamixs;
import java.util.logging.Logger;
import org.imixs.workflow.engine.SetupEvent;
import jakarta.annotation.security.DeclareRoles;
import jakarta.annotation.security.RolesAllowed;
import jakarta.ejb.Stateless;
import jakarta.enterprise.event.Observes;
/**
* This DynamixsSetupService reacts on the
* 'org.imixs.workflow.engine.SetupEvent' and initializes a Cassandra Session.
* If the connection can not be established immediately the method retries a
* connection every 10 seconds.
*
*
*
*
* @author rsoika
*
*/
@DeclareRoles({ "org.imixs.ACCESSLEVEL.NOACCESS", "org.imixs.ACCESSLEVEL.READERACCESS",
"org.imixs.ACCESSLEVEL.AUTHORACCESS", "org.imixs.ACCESSLEVEL.EDITORACCESS",
"org.imixs.ACCESSLEVEL.MANAGERACCESS" })
@RolesAllowed({ "org.imixs.ACCESSLEVEL.NOACCESS", "org.imixs.ACCESSLEVEL.READERACCESS",
"org.imixs.ACCESSLEVEL.AUTHORACCESS", "org.imixs.ACCESSLEVEL.EDITORACCESS",
"org.imixs.ACCESSLEVEL.MANAGERACCESS" })
@Stateless
public class DynamixsSetupService {
private static Logger logger = Logger.getLogger(DynamixsSetupService.class.getName());
/**
* Init....
*
* @param setupEvent
*/
public void setup(@Observes SetupEvent setupEvent) {
//
}
}

386
dynamixs-ai-rag/src/main/java/ai/dynamixs/rag/RAGAdapter.java
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/*
* Imixs-Workflow
*
* Copyright (C) 2001-2020 Imixs Software Solutions GmbH,
* http://www.imixs.com
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* General Public License for more details.
*
* You can receive a copy of the GNU General Public
* License at http://www.gnu.org/licenses/gpl.html
*
* Project:
* https://www.imixs.org
* https://github.com/imixs/imixs-workflow
*
* Contributors:
* Imixs Software Solutions GmbH - Project Management
* Ralph Soika - Software Developer
*/
package ai.dynamixs.rag;
import java.util.List;
import java.util.Optional;
import java.util.logging.Level;
import java.util.logging.Logger;
import java.util.stream.Collectors;
import org.eclipse.microprofile.config.inject.ConfigProperty;
import org.imixs.ai.workflow.OpenAIAPIService;
import org.imixs.workflow.ItemCollection;
import org.imixs.workflow.SignalAdapter;
import org.imixs.workflow.engine.EventLogService;
import org.imixs.workflow.engine.WorkflowService;
import org.imixs.workflow.exceptions.AdapterException;
import org.imixs.workflow.exceptions.PluginException;
import ai.dynamixs.rag.cluster.ClusterException;
import ai.dynamixs.rag.cluster.ClusterService;
import ai.dynamixs.rag.cluster.RetrievalResult;
import ai.dynamixs.rag.events.RAGEventService;
import jakarta.inject.Inject;
/**
* The RAGAdapter is used for Retrieval-Augmented Generation workflows.
* <p>
* The adapter operates in two modes:
* <p>
* In the 'INDEX' mode the adapter evaluates an associated imixs-ai prompt
* definition and generates - based on the given prompt template - a text to be
* indexed in the RAG database.
*
* <pre>
* {@code
<imixs-ai name="INDEX">
<endpoint><propertyvalue>llm.service.endpoint</propertyvalue></endpoint>
<debug>true</debug>
</imixs-ai>
* }
* </pre>
* <p>
* In the 'RETRIEVAL' mode, the adapter evaluates an associated imixs-ai prompt
* definition to get retrieval embeddings from the RAG database.
*
* <pre>
* {@code
<imixs-ai name="RETRIEVAL">
<endpoint><propertyvalue>llm.service.endpoint</propertyvalue></endpoint>
<debug>true</debug>
</imixs-ai>
* }
* </pre>
*
* In both modes the Endpoint defines the Rest API endpoint of the llama-cpp
* http server or any compatible OpenAI / Open API rest service endpoint.
* <p>
* The Prompt Template is based on the concepts of Imixs-AI:
*
* <pre>
* {@code
<?xml version="1.0" encoding="UTF-8"?>
<IndexDefinition>
< index_options>{"n_predict": 4096, "temperature": 0}< /index_options>
<![CDATA[<text><itemvalue>$workflowgroup</itemvalue>: <itemvalue>$workflowstatus</itemvalue>
# Summary
<itemvalue>$workflowsummary</itemvalue>
<itemvalue>offer.summary</itemvalue>
]]></text>
</IndexDefinition>
* }
* </pre>
*
* The index Process is
*
* @author Ralph Soika
* @version 1.0
*
*/
public class RAGAdapter implements SignalAdapter {
public static final String ML_ENTITY = "entity";
public static final String API_ERROR = "API_ERROR";
public static final String RAG_INDEX = "INDEX";
public static final String RAG_RETRIEVAL = "RETRIEVAL";
private static Logger logger = Logger.getLogger(RAGAdapter.class.getName());
@Inject
@ConfigProperty(name = OpenAIAPIService.ENV_LLM_SERVICE_ENDPOINT)
Optional<String> serviceEndpoint;
@Inject
private WorkflowService workflowService;
@Inject
EventLogService eventLogService;
@Inject
private OpenAIAPIService llmService;
@Inject
private ClusterService clusterService;
/**
* Default Constructor
*/
public RAGAdapter() {
super();
}
/**
* CDI Constructor to inject WorkflowService
*
* @param workflowService
*/
@Inject
public RAGAdapter(WorkflowService workflowService) {
super();
this.workflowService = workflowService;
}
public void setWorkflowService(WorkflowService workflowService) {
this.workflowService = workflowService;
}
/**
* This method parses the LLM Event definitions.
*
* For each PROMPT the method posts a context data (e.g text from an attachment)
* to the Imixs-AI Analyse service endpoint
*
* @throws PluginException
*/
public ItemCollection execute(ItemCollection workitem, ItemCollection event)
throws AdapterException, PluginException {
logger.finest("...running api adapter...");
// read optional configuration form the model or imixs.properties....
List<ItemCollection> llmIndexDefinitions = workflowService.evalWorkflowResultXML(event, "imixs-ai",
RAG_INDEX, workitem, false);
List<ItemCollection> llmRetrievalDefinitions = workflowService.evalWorkflowResultXML(event, "imixs-ai",
RAG_RETRIEVAL, workitem, false);
// verify if we have an INDEX configuration
if (llmIndexDefinitions != null && llmIndexDefinitions.size() > 0) {
createIndex(llmIndexDefinitions, workitem, event);
}
// verify if we have an RETRIEVAL configuration
if (llmRetrievalDefinitions != null && llmRetrievalDefinitions.size() > 0) {
createRetrieval(llmRetrievalDefinitions, workitem, event);
}
return workitem;
}
/**
* Creates a RAG Index for a Workitem based on IndexDefinitions
*
* @param llmIndexDefinitions
* @param workitem
* @param event
* @throws PluginException
* @throws AdapterException
*/
private void createIndex(List<ItemCollection> llmIndexDefinitions, ItemCollection workitem, ItemCollection event)
throws PluginException, AdapterException {
long processingTime = System.currentTimeMillis();
String llmAPIEndpoint = null;
boolean llmAPIDebug = false;
try {
for (ItemCollection indexDefinition : llmIndexDefinitions) {
llmAPIEndpoint = parseLLMEndpointByBPMN(indexDefinition);
// do we have a valid endpoint?
if (llmAPIEndpoint == null || llmAPIEndpoint.isEmpty()) {
throw new PluginException(RAGAdapter.class.getSimpleName(), API_ERROR,
"imixs-ai configuration error: no llm service endpoint defined!");
}
if ("true".equalsIgnoreCase(indexDefinition.getItemValueString("debug"))) {
llmAPIDebug = true;
}
logger.info("├── post RAG index request: " + llmAPIEndpoint);
String promptTemplate = llmService.loadPromptTemplate(event);
indexDefinition.setItemValue("promptTemplate", promptTemplate);
indexDefinition.setItemValue("debug", llmAPIDebug);
indexDefinition.setItemValue("endpoint", llmAPIEndpoint);
if (llmAPIDebug) {
logger.info("│ ├── PromptTemplate: ");
logger.info(promptTemplate);
}
// Build the prompt template...
String llmPrompt = llmService.buildPrompt(promptTemplate, workitem);
if (llmPrompt.isBlank()) {
throw new PluginException(
RAGAdapter.class.getSimpleName(), API_ERROR,
"Unable to parse prompt for RAG indexing");
}
indexDefinition.setItemValue("prompt", llmPrompt);
// send eventLog ....
eventLogService.createEvent(
RAGEventService.EVENTLOG_TOPIC_RAG_EVENT_INDEX,
workitem.getUniqueID(),
indexDefinition);
// if (llmAPIDebug) {
// logger.info("│ ├── Total Prompt Length = " + llmPrompt.length());
// logger.info("│ ├── Prompt: ");
// logger.info(llmPrompt);
// }
// // remove old embeddings
// clusterService.removeAllEmbeddings(workitem.getUniqueID());
// // chunk text....
// List<String> chunk_list = RAGUtil.chunkMarkupDocument(llmPrompt);
// for (String chunk : chunk_list) {
// if (llmAPIDebug) {
// logger.info("│ ├── 🔸 chunk: ");
// logger.info(chunk);
// }
// List<Float> indexResult = llmService.postEmbedding(chunk, llmAPIEndpoint,
// llmAPIDebug);
// // write to cassandra
// clusterService.insertVector(workitem.getUniqueID(),
// workitem.getModelVersion(),
// workitem.getTaskID(),
// chunk,
// indexResult);
// if (llmAPIDebug) {
// logger.info("│ ├── ⇨ " + indexResult.size() + " floats stored in RAG db.");
// }
// }
if (llmAPIDebug) {
logger.info(
"├── ✅ Total processing time: " + (System.currentTimeMillis() - processingTime) + "ms");
}
}
} catch (PluginException e) {
logger.severe("├── ⚠️ Failed to post embeddings: " + e.getMessage());
throw e;
}
}
/**
* Creates a RAG retrieval for a Worktiem based on RetrievalDefinitions
*
* @param llmRetrievalfDefinitions
* @param workitem
* @param event
* @throws PluginException
* @throws AdapterException
*/
private void createRetrieval(List<ItemCollection> llmRetrievalfDefinitions, ItemCollection workitem,
ItemCollection event) throws PluginException, AdapterException {
long processingTime = System.currentTimeMillis();
String llmAPIEndpoint = null;
boolean llmAPIDebug = false;
try {
for (ItemCollection indexDefinition : llmRetrievalfDefinitions) {
llmAPIEndpoint = parseLLMEndpointByBPMN(indexDefinition);
// do we have a valid endpoint?
if (llmAPIEndpoint == null || llmAPIEndpoint.isEmpty()) {
throw new PluginException(RAGAdapter.class.getSimpleName(), API_ERROR,
"imixs-ai configuration error: no llm service endpoint defined!");
}
if ("true".equalsIgnoreCase(indexDefinition.getItemValueString("debug"))) {
llmAPIDebug = true;
}
logger.info("├── post RAG Retrievalf request: " + llmAPIEndpoint);
String promptTemplate = llmService.loadPromptTemplate(event);
logger.info("│ ├── PromptTemplate: ");
logger.info(promptTemplate);
String llmPrompt = llmService.buildPrompt(promptTemplate, workitem);
if (llmPrompt.isBlank()) {
throw new PluginException(
RAGAdapter.class.getSimpleName(), API_ERROR,
"Unable to parse prompt for RAG indexing");
}
if (llmAPIDebug) {
logger.info("│ ├── Total Prompt Length = " + llmPrompt.length());
logger.info("│ ├── Prompt: ");
logger.info(llmPrompt);
}
// retrieve prompt....
List<Float> embeddings = llmService.postEmbedding(llmPrompt, llmAPIEndpoint, llmAPIDebug);
if (llmAPIDebug) {
logger.info("├── ⇨ " + embeddings.size() + " floats stored in RAG db.");
}
// search cassandra
List<RetrievalResult> retrievalResultList = clusterService.searchEmbeddings(embeddings, 5);
List<String> listOfIds = retrievalResultList.stream()
.map(RetrievalResult::getUniqueId)
.collect(Collectors.toList());
workitem.setItemValue("product.ref", listOfIds);
if (llmAPIDebug) {
logger.info(
"├── found " + retrievalResultList.size() + " matches");
logger.info(
"├── ✅ Total processing time: " + (System.currentTimeMillis() - processingTime) + "ms");
}
}
} catch (PluginException e) {
logger.severe("├── ⚠️ Failed to post embeddings: " + e.getMessage());
throw e;
} catch (ClusterException e) {
throw new PluginException(RAGAdapter.class.getSimpleName(), API_ERROR, e.getMessage(), e);
}
}
/**
* This helper method parses the ml api endpoint either provided by a model
* definition or a imixs.property or an environment variable.
* <p>
* If not api endpoint is defined by the model the adapter uses the default api
* endpoint.
*
* @param llmPrompt
* @return
* @throws PluginException
*/
private String parseLLMEndpointByBPMN(ItemCollection llmPrompt) throws PluginException {
boolean debug = logger.isLoggable(Level.FINE);
String llmAPIEndpoint = null;
// Test if the model provides a API Endpoint.
llmAPIEndpoint = null;
if (llmPrompt != null) {
llmAPIEndpoint = llmPrompt.getItemValueString("endpoint");
}
// switch to default api endpoint?
if (llmAPIEndpoint == null || llmAPIEndpoint.isEmpty()) {
// set defautl api endpoint if defined
if (serviceEndpoint.isPresent() && !serviceEndpoint.get().isEmpty()) {
llmAPIEndpoint = serviceEndpoint.get();
}
}
if (debug) {
logger.info("......llm api endpoint " + llmAPIEndpoint);
}
// adapt text...
llmAPIEndpoint = workflowService.adaptText(llmAPIEndpoint, null);
if (!llmAPIEndpoint.endsWith("/")) {
llmAPIEndpoint = llmAPIEndpoint + "/";
}
return llmAPIEndpoint;
}
}

107
dynamixs-ai-rag/src/main/java/ai/dynamixs/rag/RAGPlugin.java
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/*
* Imixs-Workflow
*
* Copyright (C) 2001-2020 Imixs Software Solutions GmbH,
* http://www.imixs.com
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* General Public License for more details.
*
* You can receive a copy of the GNU General Public
* License at http://www.gnu.org/licenses/gpl.html
*
* Project:
* https://www.imixs.org
* https://github.com/imixs/imixs-workflow
*
* Contributors:
* Imixs Software Solutions GmbH - Project Management
* Ralph Soika - Software Developer
*/
package ai.dynamixs.rag;
import java.util.List;
import java.util.logging.Logger;
import org.imixs.workflow.ItemCollection;
import org.imixs.workflow.engine.EventLogService;
import org.imixs.workflow.engine.WorkflowService;
import org.imixs.workflow.engine.plugins.AbstractPlugin;
import org.imixs.workflow.exceptions.PluginException;
import ai.dynamixs.rag.events.RAGEventService;
import jakarta.inject.Inject;
/**
* The RAGIndexPlugin updates the workflow meta data for existing embeddings.
* The plugin can be deactivated with:
* <p>
*
* <pre>
{@code
<rag-index name="DISABLE">
<debug>false</debug>
</rag-index>
}
* </pre>
* <p>
* The tag 'debug' is optional
*
*
* @author rsoika
*
*/
public class RAGPlugin extends AbstractPlugin {
private static final Logger logger = Logger.getLogger(RAGPlugin.class.getName());
@Inject
private WorkflowService workflowService;
@Inject
EventLogService eventLogService;
@Override
public ItemCollection run(ItemCollection workitem, ItemCollection event) throws PluginException {
List<ItemCollection> deleteDefinitions = null;
List<ItemCollection> disableDefinitions = null;
logger.finest("running TaxonomyPlugin");
String workflowResult = event.getItemValueString("workflow.result");
if (workflowResult.contains("<rag-index")) {
deleteDefinitions = workflowService.evalWorkflowResultXML(event, "rag-index",
"DELETE", workitem, false);
disableDefinitions = workflowService.evalWorkflowResultXML(event,
"rag-index",
"DISABLE", workitem, false);
}
// disabled?
if (disableDefinitions != null && disableDefinitions.size() > 0) {
// no op!
return workitem;
}
// delete mode?
if (deleteDefinitions != null && deleteDefinitions.size() > 0) {
eventLogService.createEvent(RAGEventService.EVENTLOG_TOPIC_RAG_EVENT_DELETE, workitem.getUniqueID());
return workitem;
}
// default update meta information
eventLogService.createEvent(RAGEventService.EVENTLOG_TOPIC_RAG_EVENT_UPDATE, workitem.getUniqueID());
return workitem;
}
}

101
dynamixs-ai-rag/src/main/java/ai/dynamixs/rag/RAGUtil.java
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/*
* Imixs-Workflow
*
* Copyright (C) 2001-2020 Imixs Software Solutions GmbH,
* http://www.imixs.com
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* General Public License for more details.
*
* You can receive a copy of the GNU General Public
* License at http://www.gnu.org/licenses/gpl.html
*
* Project:
* https://www.imixs.org
* https://github.com/imixs/imixs-workflow
*
* Contributors:
* Imixs Software Solutions GmbH - Project Management
* Ralph Soika - Software Developer
*/
package ai.dynamixs.rag;
import java.util.ArrayList;
import java.util.List;
import java.util.logging.Logger;
import java.util.regex.Matcher;
import java.util.regex.Pattern;
/**
* The RAGUtil provides methods to chunk markup text
*
* @author Ralph Soika
* @version 1.0
*
*/
public class RAGUtil {
private static Logger logger = Logger.getLogger(RAGAdapter.class.getName());
/**
* This helper method creates smaller text chunks from a large markup text.
*/
public static List<String> chunkMarkupDocument(String markupText) {
List<String> chunks = new ArrayList<>();
StringBuilder currentChunk = new StringBuilder();
// Regex für Abschnitts-Header (# oder **)
Pattern sectionPattern = Pattern.compile("^(# .+|\\*\\*.+\\*\\*)", Pattern.MULTILINE);
Matcher matcher = sectionPattern.matcher(markupText);
int lastEnd = 0;
while (matcher.find()) {
// Text zwischen den Headern
String sectionContent = markupText.substring(lastEnd, matcher.start()).trim();
if (!sectionContent.isEmpty()) {
// Füge Inhalt zum aktuellen Chunk hinzu
if (currentChunk.length() + sectionContent.length() > 500) {
flushChunk(chunks, currentChunk);
}
currentChunk.append(sectionContent).append("\n");
}
// Header selbst behandeln
String header = matcher.group(1);
if (currentChunk.length() + header.length() > 300) {
flushChunk(chunks, currentChunk);
}
currentChunk.append(header).append("\n");
lastEnd = matcher.end();
}
// Restlichen Text nach dem letzten Header
String remainingContent = markupText.substring(lastEnd).trim();
if (!remainingContent.isEmpty()) {
currentChunk.append(remainingContent);
flushChunk(chunks, currentChunk);
} else if (currentChunk.length() > 0) {
chunks.add(currentChunk.toString().trim());
}
return chunks;
}
private static void flushChunk(List<String> chunks, StringBuilder currentChunk) {
if (currentChunk.length() > 0) {
chunks.add(currentChunk.toString().trim());
currentChunk.setLength(0);
}
}
}

99
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/*******************************************************************************
* Imixs Workflow
* Copyright (C) 2001, 2011 Imixs Software Solutions GmbH,
* http://www.imixs.com
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* General Public License for more details.
*
* You can receive a copy of the GNU General Public
* License at http://www.gnu.org/licenses/gpl.html
*
* Project:
* http://www.imixs.org
* http://java.net/projects/imixs-workflow
*
* Contributors:
* Imixs Software Solutions GmbH - initial API and implementation
* Ralph Soika - Software Developer
*******************************************************************************/
package ai.dynamixs.rag.cluster;
/**
* The ClusterService provides methods to persist the content of a Imixs AI
* dataset into a Cassandra keystore.
* <p>
* The ClusterService creates a Core-KeySpace automatically which is used for
* the internal management.
*
* @author rsoika
* @version 1.0
*/
public class ClusterException extends Exception {
private static final long serialVersionUID = 1L;
protected String errorContext = "UNDEFINED";
protected String errorCode = "UNDEFINED";
public static final String INVALID_DOCUMENT_OBJECT = "INVALID_DOCUMENT_OBJECT";
public static final String INVALID_KEYSPACE = "INVALID_KEYSPACE";
public static final String CLUSTER_ERROR = "CLUSTER_ERROR";
public static final String INVALID_WORKITEM = "INVALID_WORKITEM";
public static final String MD5_ERROR = "MD5_ERROR";
public static final String MISSING_CONTACTPOINT = "MISSING_CONTACTPOINT";
public static final String SYNC_ERROR = "SYNC_ERROR";
public ClusterException(String aErrorCode, String message) {
super(message);
errorCode = aErrorCode;
}
public ClusterException(String aErrorContext, String aErrorCode, String message) {
super(message);
errorContext = aErrorContext;
errorCode = aErrorCode;
}
public ClusterException(String aErrorContext, String aErrorCode, String message, Exception e) {
super(message, e);
errorContext = aErrorContext;
errorCode = aErrorCode;
}
public ClusterException(String aErrorCode, String message, Exception e) {
super(message, e);
errorCode = aErrorCode;
}
public String getErrorContext() {
return errorContext;
}
public void setErrorContext(String errorContext) {
this.errorContext = errorContext;
}
public String getErrorCode() {
return errorCode;
}
public void setErrorCode(String errorCode) {
this.errorCode = errorCode;
}
}

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package ai.dynamixs.rag.cluster;
import java.net.InetSocketAddress;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Optional;
import java.util.UUID;
import java.util.logging.Level;
import java.util.logging.Logger;
import java.util.stream.Collectors;
import org.eclipse.microprofile.config.inject.ConfigProperty;
import com.datastax.oss.driver.api.core.CqlSession;
import com.datastax.oss.driver.api.core.CqlSessionBuilder;
import com.datastax.oss.driver.api.core.InvalidKeyspaceException;
import com.datastax.oss.driver.api.core.cql.BoundStatement;
import com.datastax.oss.driver.api.core.cql.PreparedStatement;
import com.datastax.oss.driver.api.core.cql.ResultSet;
import com.datastax.oss.driver.api.core.cql.Row;
import com.datastax.oss.driver.api.core.data.CqlVector;
import com.datastax.oss.driver.api.core.servererrors.InvalidQueryException;
import jakarta.annotation.PostConstruct;
import jakarta.annotation.PreDestroy;
import jakarta.annotation.Resource;
import jakarta.ejb.Singleton;
import jakarta.ejb.Startup;
import jakarta.ejb.Timeout;
import jakarta.ejb.Timer;
import jakarta.ejb.TimerConfig;
import jakarta.ejb.TimerService;
import jakarta.inject.Inject;
/**
* The ClusterService provides methods to persist the content of a Imixs
* Document into a Cassandra keystore.
* <p>
* The service saves the content in XML format. The size of an XML
* representation of a Imixs document is only slightly different in size from
* the serialized map object. This is the reason why we do not store the
* document map in a serialized object format.
* <p>
* The ClusterService creates a Core-KeySpace automatically which is used for
* the internal management.
*
* @author rsoika
*
*/
@Singleton
@Startup
public class ClusterService {
public static final String KEYSPACE_REGEX = "^[a-z_]*[^-]$";
public static final int SEARCH_LIMIT_MAX = 100;
// mandatory environment settings
public static final String ENV_EMBEDDINGS_CLUSTER_CONTACTPOINTS = "EMBEDDINGS_CLUSTER_CONTACTPOINTS";
public static final String ENV_EMBEDDINGS_CLUSTER_KEYSPACE = "EMBEDDINGS_CLUSTER_KEYSPACE";
public static final int DIMENSIONS = 768;
// public static final int DIMENSIONS = 384;
// optional environment settings
public static final String ENV_EMBEDDINGS_CLUSTER_AUTH_USER = "EMBEDDINGS_CLUSTER_AUTH_USER";
public static final String ENV_EMBEDDINGS_CLUSTER_AUTH_PASSWORD = "EMBEDDINGS_CLUSTER_AUTH_PASSWORD";
public static final String ENV_EMBEDDINGS_CLUSTER_SSL = "EMBEDDINGS_CLUSTER_SSL";
public static final String ENV_EMBEDDINGS_CLUSTER_SSL_TRUSTSTOREPATH = "EMBEDDINGS_CLUSTER_SSL_TRUSTSTOREPATH";
public static final String ENV_EMBEDDINGS_CLUSTER_SSL_TRUSTSTOREPASSWORD = "EMBEDDINGS_CLUSTER_SSL_TRUSTSTOREPASSWORD";
public static final String ENV_EMBEDDINGS_CLUSTER_SSL_KEYSTOREPATH = "EMBEDDINGS_CLUSTER_SSL_KEYSTOREPATH";
public static final String ENV_EMBEDDINGS_CLUSTER_SSL_KEYSTOREPASSWORD = "EMBEDDINGS_CLUSTER_SSL_KEYSTOREPASSWORD";
public static final String ENV_EMBEDDINGS_CLUSTER_REPLICATION_FACTOR = "EMBEDDINGS_CLUSTER_REPLICATION_FACTOR";
public static final String ENV_EMBEDDINGS_CLUSTER_REPLICATION_CLASS = "EMBEDDINGS_CLUSTER_REPLICATION_CLASS";
// workflow rest service endpoint
public static final String ENV_WORKFLOW_SERVICE_ENDPOINT = "WORKFLOW_SERVICE_ENDPOINT";
public static final String ENV_WORKFLOW_SERVICE_USER = "WORKFLOW_SERVICE_USER";
public static final String ENV_WORKFLOW_SERVICE_PASSWORD = "WORKFLOW_SERVICE_PASSWORD";
public static final String ENV_WORKFLOW_SERVICE_AUTHMETHOD = "WORKFLOW_SERVICE_AUTHMETHOD";
private static Logger logger = Logger.getLogger(ClusterService.class.getName());
@Inject
@ConfigProperty(name = ENV_EMBEDDINGS_CLUSTER_REPLICATION_FACTOR, defaultValue = "1")
String repFactor;
@Inject
@ConfigProperty(name = ENV_EMBEDDINGS_CLUSTER_REPLICATION_CLASS, defaultValue = "SimpleStrategy")
String repClass;
@Inject
@ConfigProperty(name = ENV_EMBEDDINGS_CLUSTER_CONTACTPOINTS)
Optional<String> contactPoint;
@Inject
@ConfigProperty(name = ENV_EMBEDDINGS_CLUSTER_KEYSPACE)
Optional<String> keySpace;
@Inject
@ConfigProperty(name = ENV_EMBEDDINGS_CLUSTER_AUTH_USER)
Optional<String> userid;
@Inject
@ConfigProperty(name = ENV_EMBEDDINGS_CLUSTER_AUTH_PASSWORD)
Optional<String> password;
@Inject
@ConfigProperty(name = ENV_EMBEDDINGS_CLUSTER_SSL, defaultValue = "false")
boolean bUseSSL;
@Inject
@ConfigProperty(name = ENV_EMBEDDINGS_CLUSTER_SSL_TRUSTSTOREPATH)
Optional<String> truststorePath;
@Inject
@ConfigProperty(name = ENV_EMBEDDINGS_CLUSTER_SSL_TRUSTSTOREPASSWORD)
Optional<String> truststorePwd;
@Inject
@ConfigProperty(name = ENV_EMBEDDINGS_CLUSTER_SSL_KEYSTOREPATH)
Optional<String> keystorePath;
@Inject
@ConfigProperty(name = ENV_EMBEDDINGS_CLUSTER_SSL_KEYSTOREPASSWORD)
Optional<String> keystorePwd;
private CqlSession session;
private PreparedStatement insertVectorStmt;
// private PreparedStatement searchVectorStmt;
private final Map<String, PreparedStatement> searchVectorStatements = new HashMap<>();
private PreparedStatement selectVectorStmt;
private PreparedStatement removeVectorStmt;
private PreparedStatement selectChunksStmt = null;
private PreparedStatement updateChunkStmt = null;
@Resource
private TimerService timerService;
@PostConstruct
public void init() {
scheduleClusterCheck();
}
/**
* Versucht, die Session herzustellen. Bei Fehler wird ein neuer Timer geplant.
*/
private void scheduleClusterCheck() {
try {
logger.log(Level.INFO, "├── connecting Cassandra cluster...");
getSession();
logger.log(Level.INFO, "├── ✅ successfully connected to cassandra!");
} catch (ClusterException e) {
logger.log(Level.WARNING, "├── " + e.getMessage());
logger.log(Level.WARNING, "├── ⚠️ cluster not ready yet. retrying in 10 seconds...");
// retry in 10 sec
timerService.createSingleActionTimer(10000, new TimerConfig());
}
}
/**
* called by timer. Tries to connect cassandra clauster
*/
@Timeout
public void retryClusterCheck(Timer timer) {
scheduleClusterCheck(); // retry Check
}
@PreDestroy
private void tearDown() {
// close session and cluster object
if (session != null) {
session.close();
}
}
/**
* Returns the Cassandra Session object. If the session is not yet created, the
* method tries to init the session the first time. If initialization failed the
* method throws a ClusterException
* <p>
* Note: the initialization is only successful if the cassandra cluster is fully
* started.
* <p>
* The method also verifies the keyspace and creates a table schema if not yet
* available.
*
* @return
*/
public CqlSession getSession() throws ClusterException {
if (session == null) {
try {
logger.info("├── initializing cluster and keyspace...");
session = initSessionWithKeyspace();
logger.info("│ ├── ✅ schema status = OK");
createSchema();
} catch (Exception e) {
throw new ClusterException(ClusterException.CLUSTER_ERROR,
"Failed to init cassandra session: " + e.getMessage(), e);
}
}
return session;
}
/**
* This method opens the configured keyspace. If the keyspace does no yet exist
* it creates a new keyspace with the table schema
*
* @return
* @throws ClusterException
*/
private CqlSession initSessionWithKeyspace() throws ClusterException {
// validate keyspace name
String keySpacename = keySpace.orElseThrow(
() -> new ClusterException(ClusterException.INVALID_KEYSPACE, "EMBEDDINGS_CLUSTER_KEYSPACE not set!"));
if (!isValidKeyspaceName(keySpacename)) {
throw new ClusterException(ClusterException.INVALID_KEYSPACE,
"keyspace '" + keySpacename + "' name invalid.");
}
try {
// try to connect keyspace ...
session = createSession(keySpacename);
logger.info("│ ├── ✅ keyspace '" + keySpacename + "' status = OK");
return session;
} catch (InvalidQueryException | InvalidKeyspaceException e) {
logger.warning("│ ├── ⚠️ Keyspace does not yet exist, creating new keyspace...");
// Create a basic session object to create the keyspace....
session = createSession(null);
createKeySpace(keySpacename);
// close and reconnect session...
session.close();
session = createSession(keySpacename);
return session;
}
}
/**
* This method creates a Cassandra Cluster object. The cluster is defined by
* ContactPoints provided in the environmetn variable
* 'EMBEDDINGS__CLUSTER_CONTACTPOINTS' or in the imixs.property
* 'archive.cluster.contactpoints'
*
* @return Cassandra Cluster instacne
*/
private CqlSession createSession(String keyspace) throws ClusterException {
CqlSessionBuilder builder = CqlSession.builder();
// Boolean used to check if at least one host could be resolved
boolean found = false;
if (!contactPoint.isPresent() || contactPoint.get().isEmpty()) {
throw new ClusterException(ClusterException.MISSING_CONTACTPOINT,
"missing cluster contact points - verify configuration!");
}
logger.info("│ ├── cluster connecting: " + contactPoint.get());
String[] hosts = contactPoint.get().split(",");
for (String host : hosts) {
try {
logger.info("│ ├── adding host: " + host + ":9042");
builder.addContactPoint(new InetSocketAddress(host, 9042));
// One host could be resolved
found = true;
} catch (IllegalArgumentException e) {
// This host could not be resolved so we log a message and keep going
logger.warning("...the host '" + host + "' is unknown so it will be ignored");
}
}
if (!found) {
// No host could be resolved so we throw an exception
throw new IllegalStateException("All provided hosts are unknown - check cluster status and configuration!");
}
// set optional credentials...
if (userid.isPresent() && !userid.get().isEmpty()) {
builder = builder.withAuthCredentials(userid.get(), password.get());
}
if (keyspace != null) {
builder.withKeyspace(keyspace);
}
builder.withLocalDatacenter("datacenter1");
return builder.build();
}
/**
* Test if the keyspace name is valid.
*
* @param keySpace
* @return
*/
public boolean isValidKeyspaceName(String keySpace) {
if (keySpace == null || keySpace.isEmpty()) {
return false;
}
return keySpace.matches(KEYSPACE_REGEX);
}
/**
* This method creates a cassandra keySpace
*
* @param cluster
*/
private void createKeySpace(String keySpace) throws ClusterException {
logger.info("│ ├── creating new keyspace '" + keySpace + "'...");
String statement = "CREATE KEYSPACE IF NOT EXISTS " + keySpace + " WITH replication = {'class': '" + repClass
+ "', 'replication_factor': " + repFactor + "};";
session.execute(statement);
logger.info("│ ├── ✅ keyspace '" + keySpace + "' created.");
}
/**
* This method creates the keySpace schema.
*
* CREATE TABLE embeddings.document_vectors ( business_document_id uuid,
* chunk_id text, chunk_text text, content_vector VECTOR <FLOAT, 768>, PRIMARY
* KEY (business_document_id, chunk_id) ); );
*
* @param cluster
*/
private void createSchema() throws ClusterException {
logger.info("│ ├── verify schema...");
// now create table schemas
String query = "CREATE TABLE IF NOT EXISTS document_vectors (\n" + //
" id text,\n" + //
" chunk_id uuid,\n" + //
" model_version text,\n" + //
" task_id int,\n" + //
" content_chunk text,\n" + //
" content_vector VECTOR <FLOAT, " + DIMENSIONS + ">,\n" + //
" PRIMARY KEY (id, chunk_id)\n" + //
");";
session.execute(query);
logger.info("│ ├── verify index...");
query = "CREATE INDEX IF NOT EXISTS edv_ann_index\n" + //
" ON document_vectors(content_vector) USING 'sai';";
session.execute(query);
// Additional indexes for metadata filtering
query = "CREATE INDEX IF NOT EXISTS idx_model_version " + //
" ON document_vectors(model_version) USING 'sai';";
session.execute(query);
query = "CREATE INDEX IF NOT EXISTS idx_task_id " + //
" ON document_vectors(task_id) USING 'sai';";
session.execute(query);
logger.info("│ ├── ✅ database schema OK.");
}
/**
* Inserts an embedding together with a content chunk into the database. The
* uniqueID is the reference to the corresponding workitem holding the full meta
* data.
*
* @param uniqueID
* @param modelVersion
* @param taskId
* @param content
* @param vector
* @throws ClusterException
*/
public void insertVector(String uniqueID, String modelVersion, int taskId, String content, List<Float> vector)
throws ClusterException {
// Prepare statement?
if (insertVectorStmt == null) {
String insertQuery = "INSERT INTO document_vectors "
+ "(id, chunk_id, model_version, task_id, content_chunk, content_vector) VALUES (?, ?, ?, ?, ?, ?)";
insertVectorStmt = session.prepare(insertQuery);
}
try {
// Generiere UUID
UUID chunk_id = UUID.randomUUID();
// CqlVector
CqlVector<Float> cqlVector = CqlVector.newInstance(vector);
BoundStatement boundStmt = insertVectorStmt.bind(uniqueID, chunk_id, modelVersion, taskId, content,
cqlVector);
session.execute(boundStmt);
} catch (Exception e) {
throw new ClusterException(ClusterException.CLUSTER_ERROR,
"Failed to insert embeddings into keyspace: " + e.getMessage(), e);
}
}
/**
* Removes all embeddings for a given uniqueID. The method returns true if
* entries have existed.
*
* @param uniqueID
* @param content
* @param vector
* @throws ClusterException
*/
public boolean removeAllEmbeddings(String uniqueID) throws ClusterException {
// Prepare statement if not already done
if (removeVectorStmt == null) {
String deleteQuery = "DELETE FROM document_vectors WHERE id = ?";
removeVectorStmt = session.prepare(deleteQuery);
}
try {
// test if entries exist
long count = countIndexEntries(uniqueID);
if (count > 0) {
// remove all
BoundStatement deleteBoundStmt = removeVectorStmt.bind(uniqueID);
session.execute(deleteBoundStmt);
logger.info("│ ├── ✅ Removed " + count + " entries for uniqueID: " + uniqueID);
return true;
} else {
// logger.info("│ ├── ℹ️ No entries found for uniqueID: " + uniqueID);
}
} catch (Exception e) {
throw new ClusterException(ClusterException.CLUSTER_ERROR,
"Failed to remove entries for uniqueID '" + uniqueID + "': " + e.getMessage(), e);
}
return false;
}
/**
* This method returns the number of index entries with the given uniqueId. The
* method can be used to test if index data is available.
*
* @param uniqueId
* @return - count of entries, or 0 if no entries exist
* @throws ClusterException
*/
public long countIndexEntries(String uniqueId) throws ClusterException {
if (selectVectorStmt == null) {
String selectQuery = "SELECT COUNT(*) FROM document_vectors WHERE id = ?";
selectVectorStmt = session.prepare(selectQuery);
}
try {
// test if entries exist
BoundStatement selectBoundStmt = selectVectorStmt.bind(uniqueId);
ResultSet resultSet = session.execute(selectBoundStmt);
Row row = resultSet.one();
if (row != null) {
long count = row.getLong(0);
return count;
}
} catch (Exception e) {
throw new ClusterException(ClusterException.CLUSTER_ERROR,
"Failed to lookup entries for uniqueID '" + uniqueId + "': " + e.getMessage(), e);
}
return 0;
}
/**
* Performs a semantic search on the document vector database using cosine
* similarity.
* <p>
* This method searches for the most relevant document chunks based on the
* provided query embedding. If multiple chunks exist for the same document ID,
* only the chunk with the highest similarity score is returned. The results are
* sorted by relevance score in descending order.
* <p>
* The params 'modelVrsions' and 'taskIds' are optional and can be used to
* refine the search result to specific process instances only.
*
* @param queryEmbedding The embedding vector of the search query as a list of
* float values. The dimensionality must match the
* DIMENSIONS constant used in the database schema.
* @return A list of {@link RetrievalResult} objects containing the most
* relevant documents, limited to a maximum of 5 results. Each result
* includes the document ID, the best matching content chunk, and the
* similarity score. The list is sorted by similarity score in
* descending order (most relevant first).
* @throws ClusterException if the database query fails or if there's an error
* processing the embedding vector
*
* @see RetrievalResult
* @since 1.0
*/
public List<RetrievalResult> searchEmbeddings(List<Float> embedding,
int maxResults,
List<String> modelVersions,
List<Integer> taskIds,
Integer taskIdRangeStart,
Integer taskIdRangeEnd) throws ClusterException {
if (maxResults <= 0) {
throw new ClusterException(ClusterException.CLUSTER_ERROR,
"maxResults must be greater than 0, but was: " + maxResults);
}
// Calculate a reasonable DB limit based on maxResults
// Factor 3-4 times to have enough chunks for deduplication.
int searchLimit = Math.min(maxResults * 4, SEARCH_LIMIT_MAX); // Max 100
StringBuilder queryBuilder = new StringBuilder();
queryBuilder.append("SELECT id, model_version, task_id, content_chunk, ")
.append("similarity_cosine(content_vector, ?) ")
.append("FROM document_vectors ");
List<String> whereConditions = new ArrayList<>();
// Model version filtering (with wildcard support)
if (modelVersions != null && !modelVersions.isEmpty()) {
List<String> modelConditions = new ArrayList<>();
for (String modelVersion : modelVersions) {
if (modelVersion.endsWith("*")) {
// Wildcard search using LIKE
modelConditions.add("model_version LIKE ?");
} else {
// Exact match
modelConditions.add("model_version = ?");
}
}
whereConditions.add("(" + String.join(" OR ", modelConditions) + ")");
}
// Task ID filtering - either list or range
if (taskIds != null && !taskIds.isEmpty()) {
whereConditions.add("task_id IN " + formatInClause(taskIds.size()));
} else if (taskIdRangeStart != null && taskIdRangeEnd != null) {
whereConditions.add("task_id >= ? AND task_id <= ?");
} else if (taskIdRangeStart != null) {
whereConditions.add("task_id >= ?");
} else if (taskIdRangeEnd != null) {
whereConditions.add("task_id <= ?");
}
if (!whereConditions.isEmpty()) {
queryBuilder.append("WHERE ").append(String.join(" AND ", whereConditions)).append(" ");
}
queryBuilder.append("ORDER BY content_vector ANN OF ? LIMIT ").append(searchLimit);
// Prepare statement (with caching)
String statementKey = buildStatementKey(searchLimit, modelVersions, taskIds,
taskIdRangeStart, taskIdRangeEnd);
PreparedStatement searchStmt = searchVectorStatements.get(statementKey);
if (searchStmt == null) {
searchStmt = session.prepare(queryBuilder.toString());
searchVectorStatements.put(statementKey, searchStmt);
}
try {
// use CqlVector
CqlVector<Float> cqlVector = CqlVector.newInstance(embedding);
// Build parameters list
List<Object> params = new ArrayList<>();
params.add(cqlVector); // First parameter for similarity calculation
// Add model version parameters
if (modelVersions != null && !modelVersions.isEmpty()) {
for (String modelVersion : modelVersions) {
if (modelVersion.endsWith("*")) {
// Convert wildcard to LIKE pattern
params.add(modelVersion.substring(0, modelVersion.length() - 1) + "%");
} else {
params.add(modelVersion);
}
}
}
// Add task ID parameters
if (taskIds != null && !taskIds.isEmpty()) {
params.addAll(taskIds);
} else if (taskIdRangeStart != null && taskIdRangeEnd != null) {
params.add(taskIdRangeStart);
params.add(taskIdRangeEnd);
} else if (taskIdRangeStart != null) {
params.add(taskIdRangeStart);
} else if (taskIdRangeEnd != null) {
params.add(taskIdRangeEnd);
}
params.add(cqlVector);
ResultSet resultRows = session.execute(searchStmt.bind(params.toArray()));
// track best Similarity per uniqueID
Map<String, RetrievalResult> bestMatches = new HashMap<>();
for (Row row : resultRows) {
String id = row.getString(0);
String contentChunk = row.getString(3);
Float similarity = row.getFloat(4);
// test if we already have a match
RetrievalResult existingMatch = bestMatches.get(id);
if (existingMatch == null || similarity > existingMatch.getScore()) {
// better match found!
bestMatches.put(id, new RetrievalResult(id, contentChunk, similarity));
logger.info("│ ├── Found/Updated document: " + id + " with score: " + similarity);
}
}
// Sortiere nach Score (absteigend) und gebe Top 5 zurück
List<RetrievalResult> result = bestMatches.values().stream()
.sorted((a, b) -> Float.compare(b.getScore(), a.getScore()))
.limit(maxResults)
.peek(match -> {
System.out.println("--------------");
System.out.println("- $UniqueID: " + match.getUniqueId());
System.out.println("- Relevance Score: " + match.getScore());
System.out.println("");
System.out.println("- Best Matching Content: ");
System.out.println(match.getContent());
System.out.println("");
})
.collect(Collectors.toList());
logger.info("│ ├── ✅ Retrieved " + result.size() + " relevant documents");
return result;
} catch (Exception e) {
throw new ClusterException(ClusterException.CLUSTER_ERROR,
"Failed to select embeddings from keyspace: " + e.getMessage(), e);
}
}
public List<RetrievalResult> searchEmbeddings(List<Float> embedding,
int maxResults) throws ClusterException {
return searchEmbeddings(embedding, maxResults, null, null, null, null);
}
// Range-based search
public List<RetrievalResult> searchEmbeddingsWithTaskRange(List<Float> embedding, int maxResults,
List<String> modelVersions,
int taskIdStart, int taskIdEnd)
throws ClusterException {
return searchEmbeddings(embedding, maxResults, modelVersions, null, taskIdStart, taskIdEnd);
}
// Wildcard model search
public List<RetrievalResult> searchEmbeddingsWithModelWildcard(List<Float> embedding, int maxResults,
String modelPattern,
List<Integer> taskIds)
throws ClusterException {
return searchEmbeddings(embedding, maxResults, Arrays.asList(modelPattern), taskIds, null, null);
}
/**
* Update the workflow meta data. The method returns true if a index with the
* given uniqueId was found
*
* @param uniqueId
* @param modelVersion
* @param taskId
* @return true if an update was performed
* @throws ClusterException
*/
public boolean updateMetaData(String uniqueId, String modelVersion, int taskId)
throws ClusterException {
// Prepare statements if not already done
if (selectChunksStmt == null) {
String selectQuery = "SELECT chunk_id FROM document_vectors WHERE id = ?";
selectChunksStmt = session.prepare(selectQuery);
}
if (updateChunkStmt == null) {
String updateQuery = "UPDATE document_vectors SET model_version = ?, task_id = ? WHERE id = ? AND chunk_id = ?";
updateChunkStmt = session.prepare(updateQuery);
}
try {
// 1. Alle chunk_ids für die uniqueId ermitteln
BoundStatement selectBoundStmt = selectChunksStmt.bind(uniqueId);
ResultSet resultSet = session.execute(selectBoundStmt);
List<UUID> chunkIds = new ArrayList<>();
for (Row row : resultSet) {
chunkIds.add(row.getUuid("chunk_id"));
}
if (chunkIds.isEmpty()) {
logger.info("│ ├── ℹ️ No entries found for uniqueID: " + uniqueId);
return false;
}
// 2. Jede gefundene chunk_id einzeln updaten
int updateCount = 0;
for (UUID chunkId : chunkIds) {
BoundStatement updateBoundStmt = updateChunkStmt.bind(modelVersion, taskId, uniqueId, chunkId);
session.execute(updateBoundStmt);
updateCount++;
}
logger.info("│ ├── Updated metadata for " + updateCount + " entries with uniqueID: " +
uniqueId + " (model: " + modelVersion + ", task: " + taskId + ")");
return true;
} catch (Exception e) {
throw new ClusterException(ClusterException.CLUSTER_ERROR,
"Failed to update metadata for uniqueID '" + uniqueId + "': " + e.getMessage(), e);
}
}
/**
* Helper method to prepare a IN clause
*
* @param size
* @return
*/
private String formatInClause(int size) {
return "(" + String.join(",", Collections.nCopies(size, "?")) + ")";
}
/**
* Helper method to build a key for specific select statement with parameters.
* This key is used to cache prepared statements
*
* @param dbLimit
* @param modelVersions
* @param taskIds
* @param taskIdRangeStart
* @param taskIdRangeEnd
* @return
*/
private String buildStatementKey(int dbLimit, List<String> modelVersions, List<Integer> taskIds,
Integer taskIdRangeStart, Integer taskIdRangeEnd) {
StringBuilder keyBuilder = new StringBuilder("search_").append(dbLimit);
if (modelVersions != null) {
keyBuilder.append("_mv").append(modelVersions.size());
// Add wildcard indicator
long wildcardCount = modelVersions.stream().mapToLong(mv -> mv.endsWith("*") ? 1 : 0).sum();
keyBuilder.append("w").append(wildcardCount);
}
if (taskIds != null && !taskIds.isEmpty()) {
keyBuilder.append("_ti").append(taskIds.size());
} else if (taskIdRangeStart != null || taskIdRangeEnd != null) {
keyBuilder.append("_tr");
if (taskIdRangeStart != null)
keyBuilder.append("s");
if (taskIdRangeEnd != null)
keyBuilder.append("e");
}
return keyBuilder.toString();
}
}

70
dynamixs-ai-rag/src/main/java/ai/dynamixs/rag/cluster/RetrievalResult.java
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@ -1,70 +0,0 @@
package ai.dynamixs.rag.cluster;
/**
* Represents a single result from a semantic search operation in the RAG
* (Retrieval-Augmented Generation) system.
*
* This immutable data class encapsulates the information about a document that
* was retrieved based on semantic similarity to a query. Each result contains
* the document's unique identifier, the content of the best matching chunk, and
* the similarity score that indicates how well the document matches the search
* query.
*
* <p>
* The similarity score is typically a cosine similarity value between the query
* embedding and the document's content embedding, where higher values indicate
* better matches.
* </p>
*
* <p>
* <strong>Usage Example:</strong>
* </p>
*
* <pre>{@code
* List<RetrievalResult> results = searchEmbeddings(queryVector);
* for (RetrievalResult result : results) {
* System.out.println("Document: " + result.getUniqueId() +
* " (Score: " + result.getScore() + ")");
* System.out.println("Content: " + result.getContent());
* }
* }</pre>
*
* @author Your Name
* @version 1.0
* @since 1.0
* @see #getUniqueId()
* @see #getContent()
* @see #getScore()
*/
public class RetrievalResult {
private final String uniqueId;
private final String content;
private final Float score;
public RetrievalResult(String uniqueID, String content, Float score) {
this.uniqueId = uniqueID;
this.content = content;
this.score = score;
}
public String getUniqueId() {
return uniqueId;
}
public String getContent() {
return content;
}
public Float getScore() {
return score;
}
@Override
public String toString() {
return "RetrievalResult{" +
"$uniqueId='" + uniqueId + '\'' +
", score=" + score +
", content='" + content.substring(0, Math.min(50, content.length())) + "...'" +
'}';
}
}

145
dynamixs-ai-rag/src/main/java/ai/dynamixs/rag/events/RAGEventScheduler.java
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@ -1,145 +0,0 @@
/*
* Imixs-Workflow
*
* Copyright (C) 2001-2020 Imixs Software Solutions GmbH,
* http://www.imixs.com
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* General Public License for more details.
*
* You can receive a copy of the GNU General Public
* License at http://www.gnu.org/licenses/gpl.html
*
* Project:
* https://www.imixs.org
* https://github.com/imixs/imixs-workflow
*
* Contributors:
* Imixs Software Solutions GmbH - Project Management
* Ralph Soika - Software Developer
*/
package ai.dynamixs.rag.events;
import static org.imixs.workflow.engine.AsyncEventSchedulerConfig.ASYNCEVENT_PROCESSOR_DEADLOCK;
import static org.imixs.workflow.engine.AsyncEventSchedulerConfig.ASYNCEVENT_PROCESSOR_ENABLED;
import static org.imixs.workflow.engine.AsyncEventSchedulerConfig.ASYNCEVENT_PROCESSOR_INITIALDELAY;
import static org.imixs.workflow.engine.AsyncEventSchedulerConfig.ASYNCEVENT_PROCESSOR_INTERVAL;
import java.util.logging.Level;
import java.util.logging.Logger;
import org.eclipse.microprofile.config.inject.ConfigProperty;
import org.imixs.workflow.engine.AsyncEventService;
import org.imixs.workflow.engine.EventLogService;
import jakarta.annotation.PostConstruct;
import jakarta.annotation.Resource;
import jakarta.annotation.security.DeclareRoles;
import jakarta.annotation.security.RunAs;
import jakarta.ejb.Singleton;
import jakarta.ejb.Startup;
import jakarta.ejb.Timeout;
import jakarta.ejb.Timer;
import jakarta.ejb.TimerConfig;
import jakarta.ejb.TimerService;
import jakarta.inject.Inject;
/**
* The RAGEventScheduler starts a scheduler service to process RAG events in an
* asynchronous way by calling the RAGEventService.
* <p>
* The AsyncEventScheduler runs on a non-persistent ejb timer with the same
* interval settings as the AsyncEventProcessor
* <p>
* RAGEventScheduler 'ASYNCEVENT_PROCESSOR_INTERVAL' and an optional delay
* defined by 'ASYNCEVENT_PROCESSOR_INITIALDELAY'. To enable the processor
* 'ASYNCEVENT_PROCESSOR_ENABLED' must be set to true (default=false).
* 'ASYNCEVENT_PROCESSOR_DEADLOCK' deadlock timeout
* <p>
* In a clustered environment this timer runs in each cluster member that
* contains the EJB. So this means the non-persistent EJB Timer scales
* horizontal within a clustered environment – e.g. a Kubernetes cluster.
*
* @see AsyncEventService
* @version 1.1
* @author rsoika
*
*/
@DeclareRoles({ "org.imixs.ACCESSLEVEL.MANAGERACCESS" })
@RunAs("org.imixs.ACCESSLEVEL.MANAGERACCESS")
@Startup
@Singleton
public class RAGEventScheduler {
// enabled
@Inject
@ConfigProperty(name = ASYNCEVENT_PROCESSOR_ENABLED, defaultValue = "false")
boolean enabled;
// timeout interval in ms
@Inject
@ConfigProperty(name = ASYNCEVENT_PROCESSOR_INTERVAL, defaultValue = "1000")
long interval;
// initial delay in ms
@Inject
@ConfigProperty(name = ASYNCEVENT_PROCESSOR_INITIALDELAY, defaultValue = "0")
long initialDelay;
// deadlock timeout interval in ms
@Inject
@ConfigProperty(name = ASYNCEVENT_PROCESSOR_DEADLOCK, defaultValue = "60000")
long deadLockInterval;
private static final Logger logger = Logger.getLogger(RAGEventScheduler.class.getName());
@Resource
TimerService timerService;
@Inject
RAGEventService ragEventService;
@Inject
EventLogService eventLogService;
@PostConstruct
public void init() {
if (enabled) {
// Registering a non-persistent Timer Service.
final TimerConfig timerConfig = new TimerConfig();
timerConfig.setInfo("Imixs-Workflow AsyncEventScheduler");
timerConfig.setPersistent(false);
timerService.createIntervalTimer(initialDelay, interval, timerConfig);
logger.log(Level.INFO, "├── ✅ Started RAGEventScheduler - initalDelay={0} inverval={1}",
new Object[] { initialDelay, interval });
}
}
/**
* The method delegates the event processing to the stateless ejb
* AsyncEventProcessor.
* <p>
* Before processing the eventLog the method releases possible dead locks first.
* Both methods are running in separate transactions
*
*/
@Timeout
public void run(Timer timer) {
eventLogService.releaseDeadLocks(deadLockInterval,
RAGEventService.EVENTLOG_TOPIC_RAG_EVENT_INDEX,
RAGEventService.EVENTLOG_TOPIC_RAG_EVENT_UPDATE,
RAGEventService.EVENTLOG_TOPIC_RAG_EVENT_DELETE);
ragEventService.processEventLog();
}
}

214
dynamixs-ai-rag/src/main/java/ai/dynamixs/rag/events/RAGEventService.java
View file

@ -1,214 +0,0 @@
/*
* Imixs-Workflow
*
* Copyright (C) 2001-2020 Imixs Software Solutions GmbH,
* http://www.imixs.com
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* General Public License for more details.
*
* You can receive a copy of the GNU General Public
* License at http://www.gnu.org/licenses/gpl.html
*
* Project:
* https://www.imixs.org
* https://github.com/imixs/imixs-workflow
*
* Contributors:
* Imixs Software Solutions GmbH - Project Management
* Ralph Soika - Software Developer
*/
package ai.dynamixs.rag.events;
import java.util.List;
import java.util.logging.Level;
import java.util.logging.Logger;
import org.imixs.ai.workflow.OpenAIAPIService;
import org.imixs.workflow.ItemCollection;
import org.imixs.workflow.engine.AsyncEventScheduler;
import org.imixs.workflow.engine.EventLogService;
import org.imixs.workflow.engine.WorkflowService;
import org.imixs.workflow.engine.jpa.EventLog;
import org.imixs.workflow.exceptions.PluginException;
import ai.dynamixs.rag.RAGUtil;
import ai.dynamixs.rag.cluster.ClusterException;
import ai.dynamixs.rag.cluster.ClusterService;
import jakarta.annotation.security.DeclareRoles;
import jakarta.annotation.security.RolesAllowed;
import jakarta.ejb.Stateless;
import jakarta.ejb.TransactionAttribute;
import jakarta.ejb.TransactionAttributeType;
import jakarta.inject.Inject;
import jakarta.persistence.OptimisticLockException;
/**
* The AsyncEventService can be used to process workflow events in an
* asynchronous batch process. The AsyncEventService lookup eventLog entries of
* the topic "async.event".
* <p>
* The processor look up the workItem and starts a processing life cycle.
* <p>
* The AsyncEventService is called only by the AsyncEventScheduler which is
* implementing a ManagedScheduledExecutorService.
* <p>
* To prevent concurrent processes to handle the same workitems the batch
* process uses a Optimistic lock strategy. After fetching new event log entries
* the processor updates the eventLog entry in a new transaction and set the
* topic to 'batch.process.lock'. After that update we can be sure that no other
* process is dealing with these entries. After completing the processing step
* the eventlog entry will be removed.
* <p>
* To avoid ad deadlock the processor set an expiration time on the lock, so the
* lock will be auto-released after 1 minute (batch.processor.deadlock).
*
* @see AsyncEventScheduler
* @version 1.0
* @author rsoika
*
*/
@DeclareRoles({ "org.imixs.ACCESSLEVEL.NOACCESS", "org.imixs.ACCESSLEVEL.READERACCESS",
"org.imixs.ACCESSLEVEL.AUTHORACCESS", "org.imixs.ACCESSLEVEL.EDITORACCESS",
"org.imixs.ACCESSLEVEL.MANAGERACCESS" })
@RolesAllowed({ "org.imixs.ACCESSLEVEL.NOACCESS", "org.imixs.ACCESSLEVEL.READERACCESS",
"org.imixs.ACCESSLEVEL.AUTHORACCESS", "org.imixs.ACCESSLEVEL.EDITORACCESS",
"org.imixs.ACCESSLEVEL.MANAGERACCESS" })
@Stateless
public class RAGEventService {
public static final String EVENTLOG_TOPIC_RAG_EVENT_INDEX = "rag.event.index";
public static final String EVENTLOG_TOPIC_RAG_EVENT_DELETE = "rag.event.delete";
public static final String EVENTLOG_TOPIC_RAG_EVENT_UPDATE = "rag.event.update";
private static final Logger logger = Logger.getLogger(RAGEventService.class.getName());
@Inject
EventLogService eventLogService;
@Inject
private WorkflowService workflowService;
@Inject
private ClusterService clusterService;
@Inject
private OpenAIAPIService llmService;
/**
* The method lookups for RAG event log entries and updates the RAG index
* information
* <p>
* Each eventLogEntry provides optional a prompt template
*
*/
@TransactionAttribute(value = TransactionAttributeType.REQUIRES_NEW)
public void processEventLog() {
long l = System.currentTimeMillis();
// test for new event log entries by timeout...
List<EventLog> events = eventLogService.findEventsByTimeout(100,
RAGEventService.EVENTLOG_TOPIC_RAG_EVENT_INDEX,
RAGEventService.EVENTLOG_TOPIC_RAG_EVENT_UPDATE,
RAGEventService.EVENTLOG_TOPIC_RAG_EVENT_DELETE);
if (events.size() > 0) {
logger.log(Level.INFO, "├── 🔃 processing {0} RAG events....", events.size());
for (EventLog eventLogEntry : events) {
try {
// first try to lock the eventLog entry....
if (eventLogService.lock(eventLogEntry)) {
ItemCollection workitem = workflowService.getWorkItem(eventLogEntry.getRef());
if (workitem == null) {
logger.log(Level.WARNING, "│ ├── ⚠️ unable to read workitem: " + eventLogEntry.getRef());
eventLogService.removeEvent(eventLogEntry.getId());
continue;
}
switch (eventLogEntry.getTopic()) {
case RAGEventService.EVENTLOG_TOPIC_RAG_EVENT_DELETE + ".lock":
// remove embeddings
clusterService.removeAllEmbeddings(eventLogEntry.getRef());
break;
case RAGEventService.EVENTLOG_TOPIC_RAG_EVENT_UPDATE + ".lock":
// update workflow status
clusterService.updateMetaData(eventLogEntry.getRef(), workitem.getModelVersion(),
workitem.getTaskID());
break;
case RAGEventService.EVENTLOG_TOPIC_RAG_EVENT_INDEX + ".lock":
// get indexDefinition
ItemCollection indexDefinition = new ItemCollection(eventLogEntry.getData());
String llmAPIEndpoint = indexDefinition.getItemValueString("endpoint");
boolean debug = indexDefinition.getItemValueBoolean("debug");
// String llmPromptTemplate =
// indexDefinition.getItemValueString("promptTemplate");
String llmPrompt = indexDefinition.getItemValueString("prompt");
if (debug) {
logger.info("│ ├── Total Prompt Length = " + llmPrompt.length());
logger.info("│ ├── Prompt: ");
logger.info(llmPrompt);
}
// remove old embeddings
clusterService.removeAllEmbeddings(workitem.getUniqueID());
// chunk text....
List<String> chunk_list = RAGUtil.chunkMarkupDocument(llmPrompt);
for (String chunk : chunk_list) {
if (debug) {
logger.info("│ ├── 🔸 chunk: ");
logger.info(chunk);
}
List<Float> indexResult = llmService.postEmbedding(chunk, llmAPIEndpoint, debug);
// write to cassandra
clusterService.insertVector(workitem.getUniqueID(),
workitem.getModelVersion(),
workitem.getTaskID(),
chunk,
indexResult);
if (debug) {
logger.info("│ ├── ⇨ " + indexResult.size() + " floats stored in RAG db.");
}
}
break;
default:
// no op
}
// finally remove the event log entry...
eventLogService.removeEvent(eventLogEntry.getId());
}
} catch (OptimisticLockException e) {
// lock was not possible - continue....
logger.log(Level.INFO, "...unable to lock AsyncEvent: {0}", e.getMessage());
} catch (ClusterException e) {
logger.log(Level.WARNING, e.getErrorCode() + " - " + e.getMessage());
// remove the event log entry...
eventLogService.removeEvent(eventLogEntry.getId());
} catch (PluginException e) {
logger.log(Level.WARNING, e.getErrorCode() + " - " + e.getMessage());
// remove the event log entry...
eventLogService.removeEvent(eventLogEntry.getId());
}
}
logger.log(Level.INFO, "├── ✅ {0} RAGEvents processed in {1}ms",
new Object[] { events.size(), System.currentTimeMillis() - l });
}
}
}

30
dynamixs-ai-rag/src/main/resources/META-INF/COPYRIGHT
View file

@ -1,30 +0,0 @@
Imixs-Office-Workflow
Copyright (C) 2001-2018 Imixs Software Solutions GmbH,
http://www.imixs.com
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
Project:
http://www.imixs.org
Contributors:
Imixs Software Solutions GmbH - initial API and implementation
Ralph Soika - Software Developer

621
dynamixs-ai-rag/src/main/resources/META-INF/LICENSE
View file

@ -1,621 +0,0 @@
GNU GENERAL PUBLIC LICENSE
Version 3, 29 June 2007
Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
Preamble
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software and other kinds of works.
The licenses for most software and other practical works are designed
to take away your freedom to share and change the works. By contrast,
the GNU General Public License is intended to guarantee your freedom to
share and change all versions of a program--to make sure it remains free
software for all its users. We, the Free Software Foundation, use the
GNU General Public License for most of our software; it applies also to
any other work released this way by its authors. You can apply it to
your programs, too.
When we speak of free software, we are referring to freedom, not
price. Our General Public Licenses are designed to make sure that you
have the freedom to distribute copies of free software (and charge for
them if you wish), that you receive source code or can get it if you
want it, that you can change the software or use pieces of it in new
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To protect your rights, we need to prevent others from denying you
these rights or asking you to surrender the rights. Therefore, you have
certain responsibilities if you distribute copies of the software, or if
you modify it: responsibilities to respect the freedom of others.
For example, if you distribute copies of such a program, whether
gratis or for a fee, you must pass on to the recipients the same
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or can get the source code. And you must show them these terms so they
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Developers that use the GNU GPL protect your rights with two steps:
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For the developers' and authors' protection, the GPL clearly explains
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Finally, every program is threatened constantly by software patents.
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The precise terms and conditions for copying, distribution and
modification follow.
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<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="https://jakarta.ee/xml/ns/jakartaee"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="https://jakarta.ee/xml/ns/jakartaee https://jakarta.ee/xml/ns/jakartaee/beans_3_0.xsd"
bean-discovery-mode="all" version="3.0">
</beans>

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dynamixs-ai-rag/src/main/resources/copyright.txt
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Imixs Workflow Technology
Copyright (C) 2010 Imixs Software Solutions GmbH,
http://www.imixs.com
Contributors:
Imixs Software Solutions GmbH - initial implementation
Ralph Soika

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dynamixs-ai-rag/src/main/resources/licence.txt
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??