prerna.engine.impl.vector.WeaviateVectorDatabaseEngine Maven / Gradle / Ivy
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package prerna.engine.impl.vector;
import java.io.File;
import java.io.IOException;
import java.nio.file.Paths;
import java.text.SimpleDateFormat;
import java.util.ArrayList;
import java.util.Date;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;
import org.apache.commons.io.FileUtils;
import org.apache.commons.io.FilenameUtils;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import com.google.gson.internal.LinkedTreeMap;
import io.weaviate.client.Config;
import io.weaviate.client.WeaviateAuthClient;
import io.weaviate.client.WeaviateClient;
import io.weaviate.client.base.Result;
import io.weaviate.client.v1.auth.exception.AuthException;
import io.weaviate.client.v1.batch.api.ObjectsBatcher;
import io.weaviate.client.v1.batch.model.BatchDeleteResponse;
import io.weaviate.client.v1.data.model.WeaviateObject;
import io.weaviate.client.v1.filters.Operator;
import io.weaviate.client.v1.filters.WhereFilter;
import io.weaviate.client.v1.graphql.model.GraphQLResponse;
import io.weaviate.client.v1.graphql.query.argument.NearVectorArgument;
import io.weaviate.client.v1.graphql.query.fields.Field;
import io.weaviate.client.v1.schema.model.Schema;
import io.weaviate.client.v1.schema.model.WeaviateClass;
import prerna.cluster.util.ClusterUtil;
import prerna.cluster.util.DeleteFilesFromEngineRunner;
import prerna.engine.api.IModelEngine;
import prerna.engine.api.VectorDatabaseTypeEnum;
import prerna.om.Insight;
import prerna.util.Constants;
import prerna.util.Utility;
public class WeaviateVectorDatabaseEngine extends AbstractVectorDatabaseEngine {
private static final Logger classLogger = LogManager.getLogger(WeaviateVectorDatabaseEngine.class);
public static final String WEAVIATE_CLASSNAME = "WEAVIATE_CLASSNAME";
public static final String AUTOCUT = "AUTOCUT";
private WeaviateClient client = null;
private String host = null;
private String protocol = "https";
private String apiKey = null;
private String className = null;
private int autocut = 1;
@Override
public void open(Properties smssProp) throws Exception {
super.open(smssProp);
this.host = smssProp.getProperty(Constants.HOSTNAME);
if(this.host == null || (this.host=this.host.trim()).isEmpty()) {
throw new IllegalArgumentException("Must define the host");
}
if(this.host.startsWith("https://")) {
this.host = this.host.substring("https://".length(), host.length());
} else if(this.host.startsWith("http://")) {
this.protocol = "http";
this.host = this.host.substring("http://".length(), host.length());
}
this.apiKey = smssProp.getProperty(Constants.API_KEY);
if(this.apiKey == null || (this.apiKey=this.apiKey.trim()).isEmpty()) {
throw new IllegalArgumentException("Must define the api key");
}
this.className = smssProp.getProperty(WEAVIATE_CLASSNAME);
connect2Weviate(this.protocol, this.host, this.apiKey);
createClass(this.className);
String autoCutStr = smssProp.getProperty(AUTOCUT);
if(autoCutStr != null && !(autoCutStr=autoCutStr.trim()).isEmpty()) {
try {
this.autocut = Integer.parseInt(autoCutStr);
} catch(NumberFormatException e) {
classLogger.error(Constants.STACKTRACE, e);
throw new IllegalArgumentException("Invalid input for autocut. Must be a positive integer value. Value was: " + autoCutStr);
}
}
}
@Override
protected String getDefaultDistanceMethod() {
return "Cosine Similarity";
}
/**
*
* @param protocol
* @param host
* @param apiKey
*/
private void connect2Weviate(String protocol, String host, String apiKey) {
try {
Config config = new Config(protocol, host);
this.client = WeaviateAuthClient.apiKey(config, apiKey);
} catch (AuthException e) {
classLogger.error(Constants.STACKTRACE, e);
}
}
/**
*
* @param className
*/
private void createClass(String className) {
// check to see if the class is available
// if not create a class
Schema s = client.schema().getter().run().getResult();
if(s == null) {
throw new IllegalArgumentException("Unable to pull the weaviate schema");
}
List classes = s.getClasses();
boolean foundClass = false;
for(int classIndex = 0; !foundClass && classIndex < classes.size(); classIndex++) {
WeaviateClass wc = classes.get(classIndex);
String curName = wc.getClassName();
foundClass = curName.equalsIgnoreCase(className);
}
if(!foundClass) {
// see if the properties have been passed
// if not create it
//String [] classProps =
WeaviateClass emptyClass = WeaviateClass.builder()
.className(className)
.build();
// Add the class to the schema
Result result = client.schema().classCreator()
.withClass(emptyClass)
.run();
}
}
@Override
public void addEmbeddings(VectorDatabaseCSVTable vectorCsvTable, Insight insight, Map parameters) throws Exception {
if (!modelPropsLoaded) {
verifyModelProps();
}
if (insight == null) {
throw new IllegalArgumentException("Insight must be provided to run Model Engine Encoder");
}
IModelEngine embeddingsEngine = Utility.getModel(this.embedderEngineId);
// send all the strings to embed in one shot
try {
vectorCsvTable.generateAndAssignEmbeddings(embeddingsEngine, insight);
} catch (Exception e) {
classLogger.error(Constants.STACKTRACE, e);
throw new IllegalArgumentException("Error occurred creating the embeddings for the generated chunks. Detailed error message = " + e.getMessage());
}
ObjectsBatcher batcher = client.batch().objectsBatcher();
for(int rowIndex = 0; rowIndex < vectorCsvTable.rows.size(); rowIndex++) {
VectorDatabaseCSVRow row = vectorCsvTable.getRows().get(rowIndex);
Map properties = new HashMap<>();
properties.put("Source", row.getSource());
properties.put("Modality", row.getModality());
properties.put("Divider", row.getDivider());
properties.put("Part", row.getPart());
properties.put("Tokens", row.getTokens());
properties.put("Content", row.getContent());
List embedding = row.getEmbeddings();
Float[] vector = new Float[embedding.size()];
for(int vecIndex = 0;vecIndex < vector.length; vecIndex++) {
vector[vecIndex] = embedding.get(vecIndex).floatValue();
}
batcher.withObject(WeaviateObject.builder()
.className(className)
.properties(properties)
.vector(vector)
.build()
);
}
batcher.run();
}
@Override
public void removeDocument(List fileNames, Map parameters) throws IOException {
String indexClass = this.defaultIndexClass;
if (parameters.containsKey("indexClass")) {
indexClass = (String) parameters.get("indexClass");
}
List sourceNames = new ArrayList<>();
for(String document : fileNames) {
String documentName = FilenameUtils.getName(document);
File f = new File(document);
if(f.exists() && f.getName().endsWith(".csv")) {
sourceNames.addAll(VectorDatabaseCSVTable.pullSourceColumn(f));
} else {
sourceNames.add(documentName);
}
}
List filesToRemoveFromCloud = new ArrayList();
// need to get the source names and then delete it based on the names
for (int fileIndex = 0; fileIndex < sourceNames.size(); fileIndex++) {
String fileName = fileNames.get(fileIndex);
BatchDeleteResponse result = client.batch().objectsBatchDeleter()
.withClassName(className)
.withWhere(WhereFilter.builder()
.path("source")
.operator(Operator.Equal)
.valueText(fileName)
.build())
.run().getResult();
//{'dryRun': False, 'match': {'class': 'Vector_Table', 'where': {'operands': None, 'operator': 'Like', 'path': ['content'], 'valueString': 'interpreted very broadly'}}, 'output': 'minimal', 'results': {'failed': 0, 'limit': 100000, 'matches': 1, 'objects': None, 'successful': 1}}
long success = result.getResults().getSuccessful();
classLogger.info("Deleted File " + fileName + " <> " + (success == 1));
String documentName = Paths.get(fileName).getFileName().toString();
// remove the physical documents
File documentFile = new File(this.schemaFolder.getAbsolutePath() + DIR_SEPARATOR + indexClass + DIR_SEPARATOR + "documents", documentName);
try {
if (documentFile.exists()) {
FileUtils.forceDelete(documentFile);
filesToRemoveFromCloud.add(documentFile.getAbsolutePath());
}
} catch (IOException e) {
classLogger.error(Constants.STACKTRACE, e);
}
}
if (ClusterUtil.IS_CLUSTER) {
Thread deleteFilesFromCloudThread = new Thread(new DeleteFilesFromEngineRunner(engineId, this.getCatalogType(), filesToRemoveFromCloud.stream().toArray(String[]::new)));
deleteFilesFromCloudThread.start();
}
}
@Override
public List> nearestNeighborCall(Insight insight, String searchStatement, Number limit, Map parameters) {
if (insight == null) {
throw new IllegalArgumentException("Insight must be provided to run Model Engine Encoder");
}
if(limit == null) {
limit = 3;
}
int cutter = autocut;
if(parameters.containsKey(AUTOCUT)) {
cutter = Integer.parseInt(parameters.get(AUTOCUT) + "");
}
List> retOut = new ArrayList<>();
Float [] vector = getEmbeddingsFloat(searchStatement, insight);
Field content = Field.builder().name("content").build();
Field source = Field.builder().name("source").build();
Field divider = Field.builder().name("divider").build();
Field part = Field.builder().name("part").build();
Field modality = Field.builder().name("modality").build();
Field _additional = Field.builder()
.name("_additional")
.fields(new Field[]{
Field.builder().name("certainty").build(), // only supported if distance==cosine
Field.builder().name("distance").build() // always supported
}).build();
NearVectorArgument nearVector = NearVectorArgument.builder().vector(vector).build();
GraphQLResponse response = client.graphQL().get().withClassName(className)
.withFields(content, source, divider, part, modality, _additional)
.withNearVector(nearVector)
.withAutocut(cutter)
.withLimit(limit.intValue())
.run()
.getResult();
// hashmap = LinkedTreeMap
// each level is a hashmap
// get is first level
// followed by vector table
// followed list of contents - array list
// the contents is again another hashmap
// get
LinkedTreeMap getMap = (LinkedTreeMap)((LinkedTreeMap)response.getData()).get("Get");
// vector table
ArrayList outputs = (ArrayList)getMap.get(className);
// each of the output is another treemap with each of the fields.. yay
for(int outputIndex = 0;outputIndex < outputs.size();outputIndex++) {
LinkedTreeMap thisOutput = (LinkedTreeMap)outputs.get(outputIndex);
LinkedTreeMap additional = (LinkedTreeMap)thisOutput.get("_additional");
Map outputMap = new HashMap();
outputMap.put("Source", thisOutput.get("source"));
outputMap.put("Divider", thisOutput.get("divider"));
outputMap.put("Modality", thisOutput.get("modality"));
outputMap.put("Part", thisOutput.get("part"));
outputMap.put("Content", thisOutput.get("content"));
outputMap.put("Score", additional.get("certainty"));
outputMap.put("Distance", additional.get("distance"));
retOut.add(outputMap);
}
return retOut;
}
@Override
public List> listDocuments(Map parameters) {
//TODO: needs to grab 'Source' from the database
//TODO: needs to grab 'Source' from the database
//TODO: needs to grab 'Source' from the database
//TODO: needs to grab 'Source' from the database
//TODO: needs to grab 'Source' from the database
//TODO: needs to grab 'Source' from the database
String indexClass = this.defaultIndexClass;
if (parameters.containsKey("indexClass")) {
indexClass = (String) parameters.get("indexClass");
}
File documentsDir = new File(this.schemaFolder.getAbsolutePath() + DIR_SEPARATOR + indexClass + DIR_SEPARATOR + DOCUMENTS_FOLDER_NAME);
List> fileList = new ArrayList<>();
File[] files = documentsDir.listFiles();
if (files != null) {
for (File file : files) {
String fileName = file.getName();
long fileSizeInBytes = file.length();
double fileSizeInMB = (double) fileSizeInBytes / (1024);
SimpleDateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss");
String lastModified = dateFormat.format(new Date(file.lastModified()));
Map fileInfo = new HashMap<>();
fileInfo.put("fileName", fileName);
fileInfo.put("fileSize", fileSizeInMB);
fileInfo.put("lastModified", lastModified);
fileList.add(fileInfo);
}
}
return fileList;
}
@Override
public List> listAllRecords(Map parameters) {
throw new IllegalArgumentException("This method has not been implemented yet");
}
@Override
public VectorDatabaseTypeEnum getVectorDatabaseType() {
return VectorDatabaseTypeEnum.WEAVIATE;
}
/////////////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////////////////
// public static void main(String [] args)
// {
// WeaviateVectorDatabaseEngine w = new WeaviateVectorDatabaseEngine();
// String apiKey = "Xxxxxxxxx";
// String host = "wsandbox-13hnmiur.weaviate.network";
//
// w.connect2Weviate("https", host, apiKey);
//
// Meta meta = w.client.misc().metaGetter().run().getResult();
//
// // Print the meta information
// System.out.println(meta);
//
// //w.client.schema().classGetter().run();
// Result metas = w.client.misc().metaGetter().run();
//
// Schema s = w.client.schema().getter().run().getResult();
//
// System.err.println(s);
//
// WeaviateClass thisClass = w.client.schema().classGetter().withClassName("Document").run().getResult();
//
// System.err.println(thisClass);
//
// //["can I buy car as gift for my client"]
// double [] qvector = new double[] {-0.008417927, 0.036340643, -0.028145125, -0.01415344, -0.004852608, -0.035720587, 0.021391913, 0.045452762, 0.01792769, 0.020785337, 0.010884669, 0.019599143, 0.028441673, 0.0077978713, -0.00053749373, 0.01288637, 0.043053415, 0.012212397, -0.010338751, 0.017563745, 0.004829019, 0.026864577, -0.065564126, -0.05227337, -0.026001891, 0.021108845, 0.023184681, -0.03911741, 0.076563366, 0.001592262, -0.06696599, -0.004067429, 0.00061415817, -0.0155418245, -0.0257997, 0.012070863, 0.011444067, -0.021459311, -0.029142607, -0.021823255, -0.002328578, -0.0015627756, 0.023845175, 0.019639583, -0.061789874, -0.02073142, -0.00039616995, -0.08384228, -0.025503151, -0.07187252, 0.005179485, 0.016876291, -0.011140779, 0.0073126103, 0.028199043, -0.02655455, 0.012529164, -0.016027085, -0.020920131, 0.03302469, 0.020866213, -0.00833705, 0.0059848833, -0.013668179, 0.0046099774, 0.045614514, -0.00089217216, -0.012906589, 0.017563745, -0.016566264, -0.01415344, -7.245213e-05, -0.0139916865, 0.032701187, 0.025085287, 0.005283951, 0.019437391, 0.013324453, 0.03442656, 0.024869615, 0.055373646, 0.016404511, 0.05860872, -0.030760143, -0.03534316, 0.029007811, 0.031083649, -0.0042325524, 0.023804737, -0.032943815, -0.055751074, 0.04725901, 0.021095365, 0.0029132497, 0.0040809084, 0.048876546, -0.0042797304, 0.026473671, 0.031919375, -0.0047144433, 0.0007182028, -0.000442295, 0.038713027, 0.053675234, 0.0026217562, 0.04515621, 0.00048104845, -0.038200807, 0.00911212, -0.0075215423, 0.029466113, -0.058177378, 0.012576343, -0.04922701, 0.0063555683, 0.03434568, -0.009307572, 0.00050168886, -0.018089443, 0.0042561414, 0.039548755, 0.013445768, 0.009968066, -0.032916855, 0.03585538, -0.060010586, -0.019396951, 0.04397002, 0.0046335664, -0.04248728, 0.034264803, -0.035774503, 0.008532502, 0.0068138703, 0.0060286913, -0.0074878437, -0.013425549, 0.009563682, -0.016633661, 0.0014094467, 0.017388511, 0.04216377, -0.008768393, 0.06502494, 0.02275334, 0.029169565, 0.030517511, -0.023818217, -0.08810179, 0.036044095, -0.026770221, -0.008283132, 0.00042144395, 0.016337113, 0.001023597, -0.038524315, -0.024559587, -0.020650543, 0.02273986, 0.030220963, -0.03361779, 0.024074327, -0.02779466, 0.03793122, 0.021850215, 0.028199043, -0.030975813, 0.037715547, -0.016498867, -0.04316125, 0.026864577, 0.042864703, -0.014328673, 0.0022392764, 0.040276647, -0.0013934398, 0.035289243, 0.012481986, 0.0054423343, 0.013695138, -0.037985135, 0.057206854, 0.05060192, 0.05305518, 0.035208367, -0.013412069, 0.0041280864, 0.016269716, -0.00505143, -0.017536785, -0.022537667, -0.0048660873, 0.012542644, 0.031245403, -0.043403883, 0.031407155, -0.006928446, -0.028792141, -0.0038921959, -0.029223483, -0.059471406, -0.022537667, -0.032728143, 0.046638954, 0.0032451816, -0.048633914, -0.0034777024, 0.028846057, -0.0008871174, -0.01970698, 0.00682398, 0.03251247, -0.008626859, -0.03253943, 0.035316203, 0.01567662, -0.02349471, 0.047420762, -0.07489192, -0.011262095, 0.03156891, -0.012596562, 0.0217289, 0.027322879, -0.023845175, 0.018749937, 0.009489545, 0.016027085, 0.030167045, 0.027228521, -0.036205847, 0.041381963, -0.026446713, 0.0449675, 0.011531684, 0.013674919, 0.020300075, -0.002677359, 0.010931848, 0.03235072, 0.052489042, -0.004657156, 0.036017135, -0.012246096, -0.03189242, 0.00021777763, -0.0019309336, 0.012178698, 0.02273986, -0.003942744, -0.022065887, -0.00405058, 0.009496284, 0.043269087, -0.049173094, 0.025489671, 0.03895566, 0.049388766, -0.0055535403, 0.006011842, 0.006618418, 0.049954902, -0.022564627, 0.010419628, 0.03005921, -0.028199043, 0.048606955, 0.01035897, -0.009684997, -0.04623457, -0.013439028, -0.053216934, -0.041355003, -0.009752394, -0.029250441, -0.019396951, 0.011599081, -0.011686698, 0.008997544, -0.0535674, 0.018305115, -0.002480222, -0.026905015, -0.0022645504, 0.028711263, 0.050925422, -0.051356766, 0.010298313, -0.012947028, 0.006898117, -0.0018534266, 0.007818091, 0.027430713, -0.025327917, 0.014503906, 0.012259575, -0.0025425644, 0.034803983, -0.052354246, -0.02124364, 0.009968066, 0.011531684, 0.04874175, 0.027471153, -0.025179643, -0.029843539, -8.0508216e-05, -0.008006803, 0.02199849, 0.03235072, -0.033159487, -0.020758377, 0.018049005, 0.00057708967, -0.03563971, 0.037850343, 0.031245403, -0.021944571, -0.02779466, 0.036798943, 0.0077843918, 0.012704397, -0.019140841, 0.02248375, -0.0145443445, 0.023090325, 0.0012746521, -0.07413706, -0.007939406, -0.025624465, -0.008013543, -0.052974302, -0.033267323, 0.0048660873, -0.021270597, 0.009058202, 0.012704397, -0.04364651, -0.00075737754, 0.02554359, 0.034723107, -0.027511591, 0.045129254, 0.009334531, -0.0041381964, -0.022726381, 0.022146763, -0.029034771, -0.020138323, -0.0043403883, 0.0054490743, -0.0048660873, -0.025503151, 0.01694369, 0.031164527, 0.07979844, -0.0034911819, -0.003511401, -0.0030514142, 0.052354246, 0.0039023056, 0.0147734955, 0.005988253, 0.0069351853, -0.026878055, -0.016525825, -0.004960444, 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//
// Float [] vector = new Float[qvector.length];
// for(int dblIndex = 0;dblIndex < qvector.length;dblIndex++)
// vector[dblIndex] = new Double(qvector[dblIndex]).floatValue();
//
// Field content = Field.builder().name("content").build();
// Field source = Field.builder().name("source").build();
// Field divider = Field.builder().name("divider").build();
// Field part = Field.builder().name("part").build();
// Field cert = Field.builder().name("certainty").build();
//
// Field _additional = Field.builder()
// .name("_additional")
// .fields(new Field[]{
// Field.builder().name("certainty").build(), // only supported if distance==cosine
// Field.builder().name("distance").build() // always supported
// }).build();
// NearVectorArgument nearVector = NearVectorArgument.builder().vector(vector).build();
// GraphQLResponse response = w.client.graphQL().get().withClassName("Vector_Table").withFields(content, source, divider, part, _additional).withNearVector(nearVector).withAutocut(1).withLimit(3).run().getResult();
//
// ArrayList outputs = ((ArrayList)(((LinkedTreeMap)((LinkedTreeMap)response.getData()).get("Get")).get("Vector_Table")));
// // each of the output is another treemap with each of the fields.. yay
// LinkedTreeMap additional = (LinkedTreeMap)outputs.get(0);
//
// System.err.println("response " + outputs);
//
// // deletes it
//
// //w.client.schema().classDeleter()
// // .withClassName("Vector_Table")
// // .run();
//
// GraphQLResponse resp = w.client.graphQL().get().withClassName("Vector_Table").withFields(content).run().getResult();
//
// System.err.println("Response.. from query " + resp);
// }
}
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