diff --git a/bot/admin/server/src/main/kotlin/BotAdminVerticle.kt b/bot/admin/server/src/main/kotlin/BotAdminVerticle.kt index 901c3e83ac..ca27b061d2 100644 --- a/bot/admin/server/src/main/kotlin/BotAdminVerticle.kt +++ b/bot/admin/server/src/main/kotlin/BotAdminVerticle.kt @@ -57,6 +57,7 @@ import ai.tock.translator.I18nLabel import ai.tock.translator.Translator import ai.tock.translator.Translator.initTranslator import ai.tock.translator.TranslatorEngine +import ch.tutteli.kbox.isNotNullAndNotBlank import com.fasterxml.jackson.module.kotlin.readValue import com.github.salomonbrys.kodein.instance import io.vertx.core.http.HttpMethod.GET @@ -444,9 +445,9 @@ open class BotAdminVerticle : AdminVerticle() { } } - blockingJsonPost("/configuration/bots/:botId/rag", admin) { context, configuration: BotRAGConfigurationDTO -> - if (context.organization == configuration.namespace) { - BotRAGConfigurationDTO(RAGService.saveRag(configuration)) + blockingJsonPost("/configuration/bots/:botId/rag", admin) { context, request: BotRAGConfigurationDTO -> + if (context.organization == request.namespace) { + BotRAGConfigurationDTO(RAGService.saveRag(request)) } else { unauthorized() } @@ -454,9 +455,7 @@ open class BotAdminVerticle : AdminVerticle() { blockingJsonGet("/configuration/bots/:botId/rag", admin) { context -> RAGService.getRAGConfiguration(context.organization, context.path("botId")) - ?.let { - BotRAGConfigurationDTO(it) - } + ?.let { BotRAGConfigurationDTO(it) } } blockingDelete("/configuration/bots/:botId/rag", admin) { context -> diff --git a/bot/admin/server/src/main/kotlin/model/BotObservabilityConfigurationDTO.kt b/bot/admin/server/src/main/kotlin/model/BotObservabilityConfigurationDTO.kt index bf3d5084e6..2b40b98c02 100644 --- a/bot/admin/server/src/main/kotlin/model/BotObservabilityConfigurationDTO.kt +++ b/bot/admin/server/src/main/kotlin/model/BotObservabilityConfigurationDTO.kt @@ -21,6 +21,7 @@ import ai.tock.bot.admin.bot.observability.BotObservabilityConfiguration import ai.tock.genai.orchestratorcore.mappers.ObservabilitySettingMapper import ai.tock.genai.orchestratorcore.models.Constants import ai.tock.genai.orchestratorcore.models.observability.ObservabilitySettingDTO +import ai.tock.genai.orchestratorcore.models.observability.toDTO import ai.tock.genai.orchestratorcore.utils.SecurityUtils import org.litote.kmongo.newId import org.litote.kmongo.toId @@ -33,24 +34,24 @@ data class BotObservabilityConfigurationDTO( val setting: ObservabilitySettingDTO, ) { constructor(configuration: BotObservabilityConfiguration) : this( - configuration._id.toString(), - configuration.namespace, - configuration.botId, - configuration.enabled, - ObservabilitySettingMapper.toDTO(configuration.setting), + id = configuration._id.toString(), + namespace = configuration.namespace, + botId = configuration.botId, + enabled = configuration.enabled, + setting = configuration.setting.toDTO(), ) fun toBotObservabilityConfiguration(): BotObservabilityConfiguration = BotObservabilityConfiguration( - id?.toId() ?: newId(), - namespace, - botId, - enabled, - ObservabilitySettingMapper.toEntity( - namespace, - botId, - Constants.GEN_AI_OBSERVABILITY, - setting + _id = id?.toId() ?: newId(), + namespace = namespace, + botId = botId, + enabled = enabled, + setting = ObservabilitySettingMapper.toEntity( + namespace = namespace, + botId = botId, + feature = Constants.GEN_AI_OBSERVABILITY, + dto = setting ), ) } diff --git a/bot/admin/server/src/main/kotlin/model/BotRAGConfigurationDTO.kt b/bot/admin/server/src/main/kotlin/model/BotRAGConfigurationDTO.kt index 187d035219..6db34f848b 100644 --- a/bot/admin/server/src/main/kotlin/model/BotRAGConfigurationDTO.kt +++ b/bot/admin/server/src/main/kotlin/model/BotRAGConfigurationDTO.kt @@ -17,12 +17,14 @@ package ai.tock.bot.admin.model import ai.tock.bot.admin.bot.rag.BotRAGConfiguration +import ai.tock.bot.admin.service.VectorStoreService import ai.tock.genai.orchestratorcore.mappers.EMSettingMapper import ai.tock.genai.orchestratorcore.mappers.LLMSettingMapper import ai.tock.genai.orchestratorcore.models.Constants import ai.tock.genai.orchestratorcore.models.em.EMSettingDTO +import ai.tock.genai.orchestratorcore.models.em.toDTO import ai.tock.genai.orchestratorcore.models.llm.LLMSettingDTO -import ai.tock.genai.orchestratorcore.utils.SecurityUtils +import ai.tock.genai.orchestratorcore.models.llm.toDTO import org.litote.kmongo.newId import org.litote.kmongo.toId @@ -34,38 +36,40 @@ data class BotRAGConfigurationDTO( val llmSetting: LLMSettingDTO, val emSetting: EMSettingDTO, val indexSessionId: String? = null, + val indexName: String? = null, val noAnswerSentence: String, val noAnswerStoryId: String? = null, ) { constructor(configuration: BotRAGConfiguration) : this( - configuration._id.toString(), - configuration.namespace, - configuration.botId, - configuration.enabled, - LLMSettingMapper.toDTO(configuration.llmSetting), - EMSettingMapper.toDTO(configuration.emSetting), - configuration.indexSessionId, - configuration.noAnswerSentence, - configuration.noAnswerStoryId + id = configuration._id.toString(), + namespace = configuration.namespace, + botId = configuration.botId, + enabled = configuration.enabled, + llmSetting = configuration.llmSetting.toDTO(), + emSetting = configuration.emSetting.toDTO(), + indexSessionId = configuration.indexSessionId, + indexName = configuration.generateIndexName(), + noAnswerSentence = configuration.noAnswerSentence, + noAnswerStoryId = configuration.noAnswerStoryId ) fun toBotRAGConfiguration(): BotRAGConfiguration = BotRAGConfiguration( - id?.toId() ?: newId(), - namespace, - botId, - enabled, - LLMSettingMapper.toEntity( - namespace, - botId, - Constants.GEN_AI_RAG_QUESTION_ANSWERING, - llmSetting + _id = id?.toId() ?: newId(), + namespace = namespace, + botId = botId, + enabled = enabled, + llmSetting = LLMSettingMapper.toEntity( + namespace = namespace, + botId = botId, + feature = Constants.GEN_AI_RAG_QUESTION_ANSWERING, + dto = llmSetting ), - EMSettingMapper.toEntity( - namespace, - botId, - Constants.GEN_AI_RAG_EMBEDDING_QUESTION, - emSetting + emSetting = EMSettingMapper.toEntity( + namespace = namespace, + botId = botId, + feature = Constants.GEN_AI_RAG_EMBEDDING_QUESTION, + dto = emSetting ), indexSessionId = indexSessionId, noAnswerSentence = noAnswerSentence, @@ -73,5 +77,13 @@ data class BotRAGConfigurationDTO( ) } +private fun BotRAGConfiguration.generateIndexName(): String? { + return indexSessionId?.takeIf { it.isNotBlank() }?.let { + VectorStoreService.getVectorStoreConfiguration(namespace, botId, enabled = true) + ?.setting + ?.normalizeDocumentIndexName(namespace, botId, it) + } +} + diff --git a/bot/admin/server/src/main/kotlin/model/BotSentenceGenerationConfigurationDTO.kt b/bot/admin/server/src/main/kotlin/model/BotSentenceGenerationConfigurationDTO.kt index b068bf519b..9e6ea41b91 100644 --- a/bot/admin/server/src/main/kotlin/model/BotSentenceGenerationConfigurationDTO.kt +++ b/bot/admin/server/src/main/kotlin/model/BotSentenceGenerationConfigurationDTO.kt @@ -20,6 +20,7 @@ import ai.tock.bot.admin.bot.sentencegeneration.BotSentenceGenerationConfigurati import ai.tock.genai.orchestratorcore.mappers.LLMSettingMapper import ai.tock.genai.orchestratorcore.models.Constants import ai.tock.genai.orchestratorcore.models.llm.LLMSettingDTO +import ai.tock.genai.orchestratorcore.models.llm.toDTO import ai.tock.genai.orchestratorcore.utils.SecurityUtils import org.litote.kmongo.newId import org.litote.kmongo.toId @@ -33,26 +34,26 @@ data class BotSentenceGenerationConfigurationDTO( val llmSetting: LLMSettingDTO, ) { constructor(configuration: BotSentenceGenerationConfiguration) : this( - configuration._id.toString(), - configuration.namespace, - configuration.botId, - configuration.enabled, - configuration.nbSentences, - LLMSettingMapper.toDTO(configuration.llmSetting), + id = configuration._id.toString(), + namespace = configuration.namespace, + botId = configuration.botId, + enabled = configuration.enabled, + nbSentences = configuration.nbSentences, + llmSetting = configuration.llmSetting.toDTO(), ) fun toSentenceGenerationConfiguration(): BotSentenceGenerationConfiguration = BotSentenceGenerationConfiguration( - id?.toId() ?: newId(), - namespace, - botId, - enabled, - nbSentences, - LLMSettingMapper.toEntity( - namespace, - botId, - Constants.GEN_AI_COMPLETION_SENTENCE_GENERATION, - llmSetting + _id = id?.toId() ?: newId(), + namespace = namespace, + botId = botId, + enabled = enabled, + nbSentences = nbSentences, + llmSetting = LLMSettingMapper.toEntity( + namespace = namespace, + botId = botId, + feature = Constants.GEN_AI_COMPLETION_SENTENCE_GENERATION, + dto = llmSetting ) ) } diff --git a/bot/admin/server/src/main/kotlin/model/BotVectorStoreConfigurationDTO.kt b/bot/admin/server/src/main/kotlin/model/BotVectorStoreConfigurationDTO.kt index 4c4ca9d66a..05751c90c7 100644 --- a/bot/admin/server/src/main/kotlin/model/BotVectorStoreConfigurationDTO.kt +++ b/bot/admin/server/src/main/kotlin/model/BotVectorStoreConfigurationDTO.kt @@ -21,6 +21,7 @@ import ai.tock.genai.orchestratorcore.mappers.LLMSettingMapper import ai.tock.genai.orchestratorcore.mappers.VectorStoreSettingMapper import ai.tock.genai.orchestratorcore.models.Constants import ai.tock.genai.orchestratorcore.models.vectorstore.VectorStoreSettingDTO +import ai.tock.genai.orchestratorcore.models.vectorstore.toDTO import ai.tock.genai.orchestratorcore.utils.SecurityUtils import org.litote.kmongo.newId import org.litote.kmongo.toId @@ -33,24 +34,24 @@ data class BotVectorStoreConfigurationDTO( val setting: VectorStoreSettingDTO, ) { constructor(configuration: BotVectorStoreConfiguration) : this( - configuration._id.toString(), - configuration.namespace, - configuration.botId, - configuration.enabled, - VectorStoreSettingMapper.toDTO(configuration.setting), + id = configuration._id.toString(), + namespace = configuration.namespace, + botId = configuration.botId, + enabled = configuration.enabled, + setting = configuration.setting.toDTO(), ) fun toBotVectorStoreConfiguration(): BotVectorStoreConfiguration = BotVectorStoreConfiguration( - id?.toId() ?: newId(), - namespace, - botId, - enabled, - VectorStoreSettingMapper.toEntity( - namespace, - botId, - Constants.GEN_AI_VECTOR_STORE, - setting + _id = id?.toId() ?: newId(), + namespace = namespace, + botId = botId, + enabled = enabled, + setting = VectorStoreSettingMapper.toEntity( + namespace = namespace, + botId = botId, + feature = Constants.GEN_AI_VECTOR_STORE, + dto = setting ) ) } diff --git a/bot/admin/server/src/main/kotlin/service/ObservabilityService.kt b/bot/admin/server/src/main/kotlin/service/ObservabilityService.kt index baf2477425..38963333a4 100644 --- a/bot/admin/server/src/main/kotlin/service/ObservabilityService.kt +++ b/bot/admin/server/src/main/kotlin/service/ObservabilityService.kt @@ -44,6 +44,16 @@ object ObservabilityService { return observabilityConfigurationDAO.findByNamespaceAndBotId(namespace, botId) } + /** + * Get the Observability configuration + * @param namespace: the namespace + * @param botId: the botId + * @param enabled: the observability activation (enabled or not) + */ + fun getObservabilityConfiguration(namespace: String, botId: String, enabled: Boolean): BotObservabilityConfiguration? { + return observabilityConfigurationDAO.findByNamespaceAndBotIdAndEnabled(namespace, botId, enabled) + } + /** * Deleting the Observability Configuration * @param namespace: the namespace @@ -56,16 +66,6 @@ object ObservabilityService { return observabilityConfigurationDAO.delete(observabilityConfig._id) } - /** - * Get the Observability configuration - * @param namespace: the namespace - * @param botId: the botId - * @param enabled: the observability activation (enabled or not) - */ - fun getObservabilityConfiguration(namespace: String, botId: String, enabled: Boolean): BotObservabilityConfiguration? { - return observabilityConfigurationDAO.findByNamespaceAndBotIdAndEnabled(namespace, botId, enabled) - } - /** * Save Observability configuration and filter errors * @param observabilityConfig : the observability configuration to create or update diff --git a/bot/admin/server/src/main/kotlin/service/RAGValidationService.kt b/bot/admin/server/src/main/kotlin/service/RAGValidationService.kt index bb409e0b56..d2de5a0ab8 100644 --- a/bot/admin/server/src/main/kotlin/service/RAGValidationService.kt +++ b/bot/admin/server/src/main/kotlin/service/RAGValidationService.kt @@ -19,9 +19,12 @@ package ai.tock.bot.admin.service import ai.tock.bot.admin.bot.rag.BotRAGConfiguration import ai.tock.genai.orchestratorclient.requests.EMProviderSettingStatusQuery import ai.tock.genai.orchestratorclient.requests.LLMProviderSettingStatusQuery +import ai.tock.genai.orchestratorclient.requests.VectorStoreProviderSettingStatusQuery import ai.tock.genai.orchestratorclient.responses.ProviderSettingStatusResponse import ai.tock.genai.orchestratorclient.services.EMProviderService import ai.tock.genai.orchestratorclient.services.LLMProviderService +import ai.tock.genai.orchestratorclient.services.VectorStoreProviderService +import ai.tock.genai.orchestratorcore.utils.VectorStoreUtils import ai.tock.shared.exception.error.ErrorMessage import ai.tock.shared.injector import ai.tock.shared.provide @@ -31,29 +34,44 @@ object RAGValidationService { private val llmProviderService: LLMProviderService get() = injector.provide() private val emProviderService: EMProviderService get() = injector.provide() + private val vectorStoreProviderService: VectorStoreProviderService get() = injector.provide() fun validate(ragConfig: BotRAGConfiguration): Set { return mutableSetOf().apply { - addAll( - llmProviderService - .checkSetting( - LLMProviderSettingStatusQuery( - ragConfig.llmSetting, - ObservabilityService.getObservabilityConfiguration( - ragConfig.namespace, - ragConfig.botId, - enabled = true - )?.setting - ) + val llmErrors = llmProviderService.checkSetting( + LLMProviderSettingStatusQuery( + ragConfig.llmSetting, + ObservabilityService.getObservabilityConfiguration( + ragConfig.namespace, ragConfig.botId, enabled = true + )?.setting + ) + ).getErrors("LLM setting check failed") + + val embeddingErrors = emProviderService.checkSetting( + EMProviderSettingStatusQuery(ragConfig.emSetting) + ).getErrors("Embedding Model setting check failed") + + val indexSessionIdErrors = validateIndexSessionId(ragConfig) + + val vectorStoreErrors = (indexSessionIdErrors + embeddingErrors).takeIf { it.isEmpty() }?.let { + val vectorStoreSetting = VectorStoreService.getVectorStoreConfiguration( + ragConfig.namespace, ragConfig.botId, enabled = true + )?.setting + + val (_, indexName) = VectorStoreUtils.getVectorStoreElements( + ragConfig.namespace, ragConfig.botId, ragConfig.indexSessionId!!, vectorStoreSetting + ) + + vectorStoreProviderService.checkSetting( + VectorStoreProviderSettingStatusQuery( + vectorStoreSetting = vectorStoreSetting, + emSetting = ragConfig.emSetting, + documentIndexName = indexName ) - .getErrors("LLM setting check failed") - ) - addAll( - emProviderService - .checkSetting(EMProviderSettingStatusQuery(ragConfig.emSetting)) - .getErrors("Embedding Model setting check failed") - ) - addAll(validateIndexSessionId(ragConfig)) + ).getErrors("Vector store setting check failed") + } ?: emptySet() + + addAll(llmErrors + embeddingErrors + indexSessionIdErrors + vectorStoreErrors) } } diff --git a/bot/admin/server/src/main/kotlin/service/VectorStoreService.kt b/bot/admin/server/src/main/kotlin/service/VectorStoreService.kt index ed9aa75782..3d559f21b3 100644 --- a/bot/admin/server/src/main/kotlin/service/VectorStoreService.kt +++ b/bot/admin/server/src/main/kotlin/service/VectorStoreService.kt @@ -35,13 +35,26 @@ object VectorStoreService { private val logger: KLogger = KotlinLogging.logger {} private val vectorStoreConfigurationDAO: BotVectorStoreConfigurationDAO get() = injector.provide() + /** * Get the Vector Store configuration + * @param namespace: the namespace + * @param botId: the botId */ fun getVectorStoreConfiguration(namespace: String, botId: String): BotVectorStoreConfiguration? { return vectorStoreConfigurationDAO.findByNamespaceAndBotId(namespace, botId) } + /** + * Get the Vector Store configuration + * @param namespace: the namespace + * @param botId: the botId + * @param enabled: the configuration activation (enabled or not) + */ + fun getVectorStoreConfiguration(namespace: String, botId: String, enabled: Boolean): BotVectorStoreConfiguration? { + return vectorStoreConfigurationDAO.findByNamespaceAndBotIdAndEnabled(namespace, botId, enabled) + } + /** * Deleting the Vector Store Configuration * @param namespace: the namespace diff --git a/bot/admin/server/src/main/kotlin/service/VectorStoreValidationService.kt b/bot/admin/server/src/main/kotlin/service/VectorStoreValidationService.kt index aea17b0dda..73a9ba2e52 100644 --- a/bot/admin/server/src/main/kotlin/service/VectorStoreValidationService.kt +++ b/bot/admin/server/src/main/kotlin/service/VectorStoreValidationService.kt @@ -20,7 +20,6 @@ import ai.tock.bot.admin.bot.vectorstore.BotVectorStoreConfiguration import ai.tock.genai.orchestratorclient.requests.VectorStoreProviderSettingStatusQuery import ai.tock.genai.orchestratorclient.responses.ProviderSettingStatusResponse import ai.tock.genai.orchestratorclient.services.VectorStoreProviderService -import ai.tock.genai.orchestratorcore.utils.OpenSearchUtils import ai.tock.shared.exception.error.ErrorMessage import ai.tock.shared.injector import ai.tock.shared.provide @@ -34,16 +33,7 @@ object VectorStoreValidationService { return mutableSetOf().apply { addAll( vectorStoreProviderService - .checkSetting( - VectorStoreProviderSettingStatusQuery( - config.setting, - // TODO : the document index name will be managed for each vector store type - // TODO : See https://github.com/theopenconversationkit/tock/pull/1735 - OpenSearchUtils.normalizeDocumentIndexName( - config.namespace, config.botId - ) - ) - ) + .checkSetting(VectorStoreProviderSettingStatusQuery(vectorStoreSetting = config.setting)) .getErrors("Vector store setting check failed") ) } diff --git a/bot/engine/src/main/kotlin/admin/bot/rag/BotRAGConfiguration.kt b/bot/engine/src/main/kotlin/admin/bot/rag/BotRAGConfiguration.kt index 3a1e647ce3..603eb9d60c 100644 --- a/bot/engine/src/main/kotlin/admin/bot/rag/BotRAGConfiguration.kt +++ b/bot/engine/src/main/kotlin/admin/bot/rag/BotRAGConfiguration.kt @@ -31,5 +31,3 @@ data class BotRAGConfiguration( val noAnswerSentence: String, val noAnswerStoryId: String? = null, ) - -fun BotRAGConfiguration?.isEnabled(): Boolean = this?.enabled ?: false \ No newline at end of file diff --git a/bot/engine/src/main/kotlin/admin/bot/vectorstore/BotVectorStoreConfiguration.kt b/bot/engine/src/main/kotlin/admin/bot/vectorstore/BotVectorStoreConfiguration.kt index e08d41f19f..eea13d2cdf 100644 --- a/bot/engine/src/main/kotlin/admin/bot/vectorstore/BotVectorStoreConfiguration.kt +++ b/bot/engine/src/main/kotlin/admin/bot/vectorstore/BotVectorStoreConfiguration.kt @@ -17,7 +17,6 @@ package ai.tock.bot.admin.bot.vectorstore import ai.tock.genai.orchestratorcore.models.vectorstore.VectorStoreSetting -import io.vertx.ext.web.RoutingContext import org.litote.kmongo.Id data class BotVectorStoreConfiguration( diff --git a/bot/engine/src/main/kotlin/engine/config/RAGAnswerHandler.kt b/bot/engine/src/main/kotlin/engine/config/RAGAnswerHandler.kt index 57343f72fc..39c92fbc26 100644 --- a/bot/engine/src/main/kotlin/engine/config/RAGAnswerHandler.kt +++ b/bot/engine/src/main/kotlin/engine/config/RAGAnswerHandler.kt @@ -17,6 +17,7 @@ package ai.tock.bot.engine.config import ai.tock.bot.admin.bot.rag.BotRAGConfiguration +import ai.tock.bot.admin.bot.vectorstore.BotVectorStoreConfiguration import ai.tock.bot.admin.indicators.IndicatorValues import ai.tock.bot.admin.indicators.Indicators import ai.tock.bot.admin.indicators.metric.MetricType @@ -36,15 +37,14 @@ import ai.tock.genai.orchestratorclient.responses.TextWithFootnotes import ai.tock.genai.orchestratorclient.retrofit.GenAIOrchestratorBusinessError import ai.tock.genai.orchestratorclient.retrofit.GenAIOrchestratorValidationError import ai.tock.genai.orchestratorclient.services.RAGService -import ai.tock.genai.orchestratorcore.models.vectorstore.VectorStoreSetting +import ai.tock.genai.orchestratorcore.models.vectorstore.* import ai.tock.genai.orchestratorcore.utils.OpenSearchUtils +import ai.tock.genai.orchestratorcore.utils.PGVectorUtils +import ai.tock.genai.orchestratorcore.utils.VectorStoreUtils import ai.tock.shared.* import engine.config.AbstractProactiveAnswerHandler import mu.KotlinLogging -private val kNeighborsDocuments = intProperty( - name = "tock_gen_ai_orchestrator_document_number_neighbors", - defaultValue = 1) private val nLastMessages = intProperty( name = "tock_gen_ai_orchestrator_dialog_number_messages", defaultValue = 5) @@ -55,6 +55,7 @@ private val ragDebugEnabled = booleanProperty( name = "tock_gen_ai_orchestrator_rag_debug_enabled", defaultValue = false) + object RAGAnswerHandler : AbstractProactiveAnswerHandler { private val logger = KotlinLogging.logger {} @@ -160,23 +161,21 @@ object RAGAnswerHandler : AbstractProactiveAnswerHandler { private fun rag(botBus: BotBus): RAGResult { logger.info { "Call Generative AI Orchestrator - RAG API" } with(botBus) { - // The RAG Story is only handled when RAG and will use Vector Store settings if defined, otherwise it will not send any vector store setting in the RAG Query which will default to Gen AI Orchestrator environment variable vector settings + // The RAG Story is only handled when RAG and will use Vector Store settings if defined, + // otherwise it will not send any vector store setting in the RAG Query which will default to + // Gen AI Orchestrator environment variable vector settings val ragConfiguration = botDefinition.ragConfiguration!! val vectorStoreConfiguration = botDefinition.vectorStoreConfiguration + val vectorStoreSetting = vectorStoreConfiguration?.takeIf { it.enabled }?.setting - var documentSearchParams = OpenSearchParams( - // The number of neighbors to return for each query_embedding. - k = kNeighborsDocuments, filter = listOf( - Term(term = mapOf("metadata.index_session_id.keyword" to ragConfiguration.indexSessionId!!)) - ) + val (documentSearchParams, indexName) = VectorStoreUtils.getVectorStoreElements( + ragConfiguration.namespace, + ragConfiguration.botId, + // The indexSessionId is mandatory to enable RAG Story + ragConfiguration.indexSessionId!!, + vectorStoreSetting ) - var vectorStoreSetting: VectorStoreSetting? = null - if(vectorStoreConfiguration!= null && vectorStoreConfiguration.enabled) { - vectorStoreSetting = vectorStoreConfiguration.setting - documentSearchParams = documentSearchParams.copy(k = vectorStoreSetting.k) - } - try { val response = ragService.rag( query = RAGQuery( @@ -188,11 +187,7 @@ object RAGAnswerHandler : AbstractProactiveAnswerHandler { "no_answer" to ragConfiguration.noAnswerSentence ), embeddingQuestionEmSetting = ragConfiguration.emSetting, - // TODO : the document index name will be managed for each vector store type - // TODO : See https://github.com/theopenconversationkit/tock/pull/1735 - documentIndexName = OpenSearchUtils.normalizeDocumentIndexName( - ragConfiguration.namespace, ragConfiguration.botId - ), + documentIndexName = indexName, documentSearchParams = documentSearchParams, vectorStoreSetting = vectorStoreSetting, observabilitySetting = botDefinition.observabilityConfiguration?.setting diff --git a/gen-ai/orchestrator-client/src/main/kotlin/ai/tock/genai/orchestratorclient/requests/RAGQuery.kt b/gen-ai/orchestrator-client/src/main/kotlin/ai/tock/genai/orchestratorclient/requests/RAGQuery.kt index a64f975971..458ab163ef 100644 --- a/gen-ai/orchestrator-client/src/main/kotlin/ai/tock/genai/orchestratorclient/requests/RAGQuery.kt +++ b/gen-ai/orchestrator-client/src/main/kotlin/ai/tock/genai/orchestratorclient/requests/RAGQuery.kt @@ -15,11 +15,10 @@ */ package ai.tock.genai.orchestratorclient.requests -import ai.tock.genai.orchestratorcore.models.llm.LLMSetting import ai.tock.genai.orchestratorcore.models.em.EMSetting -import ai.tock.genai.orchestratorcore.models.llm.LLMProvider +import ai.tock.genai.orchestratorcore.models.llm.LLMSetting import ai.tock.genai.orchestratorcore.models.observability.ObservabilitySetting -import ai.tock.genai.orchestratorcore.models.vectorstore.VectorStoreProvider +import ai.tock.genai.orchestratorcore.models.vectorstore.DocumentSearchParamsBase import ai.tock.genai.orchestratorcore.models.vectorstore.VectorStoreSetting data class RAGQuery( @@ -30,7 +29,7 @@ data class RAGQuery( val questionAnsweringPromptInputs: Map, val embeddingQuestionEmSetting: EMSetting, val documentIndexName: String, - val documentSearchParams: DocumentSearchParams, + val documentSearchParams: DocumentSearchParamsBase, val vectorStoreSetting: VectorStoreSetting?, val observabilitySetting: ObservabilitySetting? ) @@ -44,16 +43,3 @@ enum class ChatMessageType{ HUMAN, AI } - -abstract class DocumentSearchParams( - val provider: VectorStoreProvider, -) - -data class OpenSearchParams( - val k: Int, - val filter: List -): DocumentSearchParams(VectorStoreProvider.OpenSearch) - -data class Term( - val term: Map -) diff --git a/gen-ai/orchestrator-client/src/main/kotlin/ai/tock/genai/orchestratorclient/requests/VectorStoreProviderSettingStatusQuery.kt b/gen-ai/orchestrator-client/src/main/kotlin/ai/tock/genai/orchestratorclient/requests/VectorStoreProviderSettingStatusQuery.kt index d89da1e04e..2ec34e229e 100644 --- a/gen-ai/orchestrator-client/src/main/kotlin/ai/tock/genai/orchestratorclient/requests/VectorStoreProviderSettingStatusQuery.kt +++ b/gen-ai/orchestrator-client/src/main/kotlin/ai/tock/genai/orchestratorclient/requests/VectorStoreProviderSettingStatusQuery.kt @@ -16,9 +16,11 @@ package ai.tock.genai.orchestratorclient.requests +import ai.tock.genai.orchestratorcore.models.em.EMSetting import ai.tock.genai.orchestratorcore.models.vectorstore.VectorStoreSetting class VectorStoreProviderSettingStatusQuery( - val setting: VectorStoreSetting, - val indexName: String, + val vectorStoreSetting: VectorStoreSetting? = null, + val emSetting : EMSetting? = null, + val documentIndexName: String? = null ) \ No newline at end of file diff --git a/gen-ai/orchestrator-client/src/main/kotlin/ai/tock/genai/orchestratorclient/services/impl/VectorStoreProviderServiceImpl.kt b/gen-ai/orchestrator-client/src/main/kotlin/ai/tock/genai/orchestratorclient/services/impl/VectorStoreProviderServiceImpl.kt index 2773b1aad3..2e5238e55f 100644 --- a/gen-ai/orchestrator-client/src/main/kotlin/ai/tock/genai/orchestratorclient/services/impl/VectorStoreProviderServiceImpl.kt +++ b/gen-ai/orchestrator-client/src/main/kotlin/ai/tock/genai/orchestratorclient/services/impl/VectorStoreProviderServiceImpl.kt @@ -21,13 +21,17 @@ import ai.tock.genai.orchestratorclient.requests.VectorStoreProviderSettingStatu import ai.tock.genai.orchestratorclient.responses.ProviderSettingStatusResponse import ai.tock.genai.orchestratorclient.retrofit.GenAIOrchestratorClient import ai.tock.genai.orchestratorclient.services.VectorStoreProviderService +import ai.tock.genai.orchestratorcore.models.vectorstore.VectorStoreProvider class VectorStoreProviderServiceImpl: VectorStoreProviderService { private val retrofit = GenAIOrchestratorClient.getClient() private val vectorStoreProviderApi = retrofit.create(VectorStoreProviderApi::class.java) override fun checkSetting(query: VectorStoreProviderSettingStatusQuery): ProviderSettingStatusResponse? { - val response = vectorStoreProviderApi.checkVectorStoreSetting(query, query.setting.provider).execute() + val response = vectorStoreProviderApi.checkVectorStoreSetting( + query, + query.vectorStoreSetting?.provider ?: VectorStoreProvider.Default + ).execute() return response.body() } } \ No newline at end of file diff --git a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/mappers/VectorStoreSettingMapper.kt b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/mappers/VectorStoreSettingMapper.kt index b7e58a5cdd..b3b97e25f8 100644 --- a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/mappers/VectorStoreSettingMapper.kt +++ b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/mappers/VectorStoreSettingMapper.kt @@ -17,6 +17,7 @@ package ai.tock.genai.orchestratorcore.mappers import ai.tock.genai.orchestratorcore.models.vectorstore.OpenSearchVectorStoreSetting +import ai.tock.genai.orchestratorcore.models.vectorstore.PGVectorStoreSetting import ai.tock.genai.orchestratorcore.models.vectorstore.VectorStoreSetting import ai.tock.genai.orchestratorcore.models.vectorstore.VectorStoreSettingDTO import ai.tock.genai.orchestratorcore.utils.SecurityUtils @@ -36,7 +37,11 @@ object VectorStoreSettingMapper { when(this){ is OpenSearchVectorStoreSetting -> { val fetchedPassword = SecurityUtils.fetchSecretKeyValue(password) - return OpenSearchVectorStoreSetting(k, vectorSize, host, port, username, fetchedPassword) + return OpenSearchVectorStoreSetting(host, port, username, fetchedPassword, k) + } + is PGVectorStoreSetting -> { + val fetchedPassword = SecurityUtils.fetchSecretKeyValue(password) + return PGVectorStoreSetting(host, port, username, fetchedPassword, k, database) } else -> throw IllegalArgumentException("Unsupported VectorStore Setting") @@ -56,7 +61,11 @@ object VectorStoreSettingMapper { when(this){ is OpenSearchVectorStoreSetting -> { val secretPassword = SecurityUtils.createSecretKey(namespace, botId, feature, password) - return OpenSearchVectorStoreSetting(k, vectorSize, host, port, username, secretPassword) + return OpenSearchVectorStoreSetting(host, port, username, secretPassword, k) + } + is PGVectorStoreSetting -> { + val secretPassword = SecurityUtils.createSecretKey(namespace, botId, feature, password) + return PGVectorStoreSetting(host, port, username, secretPassword, k, database) } else -> throw IllegalArgumentException("Unsupported VectorStore Setting") diff --git a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/Constants.kt b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/Constants.kt index 76f7d20546..fcb244ffb7 100644 --- a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/Constants.kt +++ b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/Constants.kt @@ -24,6 +24,7 @@ object Constants { const val LANGFUSE = "Langfuse" const val OPEN_SEARCH = "OpenSearch" + const val PG_VECTOR = "PGVector" private const val GEN_AI="GenAI" private const val GEN_AI_RAG="$GEN_AI/RAG" diff --git a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/em/EMSettingBase.kt b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/em/EMSettingBase.kt index 851bcd0c7c..9a94579558 100644 --- a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/em/EMSettingBase.kt +++ b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/em/EMSettingBase.kt @@ -16,6 +16,7 @@ package ai.tock.genai.orchestratorcore.models.em +import ai.tock.genai.orchestratorcore.mappers.EMSettingMapper import ai.tock.genai.orchestratorcore.models.Constants import ai.tock.shared.security.key.SecretKey import com.fasterxml.jackson.annotation.JsonSubTypes @@ -37,4 +38,7 @@ abstract class EMSettingBase( ) typealias EMSettingDTO = EMSettingBase -typealias EMSetting = EMSettingBase \ No newline at end of file +typealias EMSetting = EMSettingBase + +// Extension functions for DTO conversion +fun EMSetting.toDTO(): EMSettingDTO = EMSettingMapper.toDTO(this) \ No newline at end of file diff --git a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/llm/LLMSettingBase.kt b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/llm/LLMSettingBase.kt index 25d46b7c49..d2ca82f105 100644 --- a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/llm/LLMSettingBase.kt +++ b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/llm/LLMSettingBase.kt @@ -17,6 +17,8 @@ package ai.tock.genai.orchestratorcore.models.llm +import ai.tock.genai.orchestratorcore.mappers.EMSettingMapper +import ai.tock.genai.orchestratorcore.mappers.LLMSettingMapper import ai.tock.genai.orchestratorcore.models.Constants import ai.tock.shared.security.key.SecretKey import com.fasterxml.jackson.annotation.JsonSubTypes @@ -43,3 +45,6 @@ abstract class LLMSettingBase( typealias LLMSettingDTO = LLMSettingBase typealias LLMSetting = LLMSettingBase + +// Extension functions for DTO conversion +fun LLMSetting.toDTO(): LLMSettingDTO = LLMSettingMapper.toDTO(this) diff --git a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/observability/ObservabilitySettingBase.kt b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/observability/ObservabilitySettingBase.kt index 194a870177..e1205d38a7 100644 --- a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/observability/ObservabilitySettingBase.kt +++ b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/observability/ObservabilitySettingBase.kt @@ -17,6 +17,7 @@ package ai.tock.genai.orchestratorcore.models.observability +import ai.tock.genai.orchestratorcore.mappers.ObservabilitySettingMapper import ai.tock.genai.orchestratorcore.models.Constants import ai.tock.shared.security.key.SecretKey import com.fasterxml.jackson.annotation.JsonSubTypes @@ -36,3 +37,6 @@ abstract class ObservabilitySettingBase( typealias ObservabilitySettingDTO = ObservabilitySettingBase typealias ObservabilitySetting = ObservabilitySettingBase + +// Extension functions for DTO conversion +fun ObservabilitySetting.toDTO(): ObservabilitySettingDTO = ObservabilitySettingMapper.toDTO(this) diff --git a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/OpenSearchVectorStoreSetting.kt b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/OpenSearchVectorStoreSetting.kt index 4a3943b8e8..4117229cd2 100644 --- a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/OpenSearchVectorStoreSetting.kt +++ b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/OpenSearchVectorStoreSetting.kt @@ -16,15 +16,35 @@ package ai.tock.genai.orchestratorcore.models.vectorstore +import ai.tock.genai.orchestratorcore.utils.OpenSearchUtils + data class OpenSearchVectorStoreSetting( + override val host: String, + override val port: Int, + override val username: String, + override val password: T, override val k: Int, - override val vectorSize: Int, - val host: String, - val port: Int, - val username: String, - val password: T, ) : VectorStoreSettingBase( provider = VectorStoreProvider.OpenSearch, - k = k, - vectorSize = vectorSize -) \ No newline at end of file + host = host, + port = port, + username = username, + password = password, + k = k +) { + + override fun normalizeDocumentIndexName(namespace: String, botId: String, indexSessionId: String): String = + OpenSearchUtils.normalizeDocumentIndexName(namespace, botId, indexSessionId) + + override fun getDocumentSearchParams(): OpenSearchParams = + OpenSearchParams(k = k, filter = null) +} + +data class OpenSearchParams( + val k: Int = 4, + val filter: List? = null +) : DocumentSearchParamsBase(VectorStoreProvider.OpenSearch) + +data class Term( + val term: Map +) diff --git a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/PGVectorStoreSetting.kt b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/PGVectorStoreSetting.kt new file mode 100644 index 0000000000..3b14335b95 --- /dev/null +++ b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/PGVectorStoreSetting.kt @@ -0,0 +1,47 @@ +/* + * Copyright (C) 2017/2021 e-voyageurs technologies + * + * Licensed 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. + */ + +package ai.tock.genai.orchestratorcore.models.vectorstore + +import ai.tock.genai.orchestratorcore.utils.PGVectorUtils + +data class PGVectorStoreSetting( + override val host: String, + override val port: Int, + override val username: String, + override val password: T, + override val k: Int, + val database: String, +) : VectorStoreSettingBase( + provider = VectorStoreProvider.PGVector, + host = host, + port = port, + username = username, + password = password, + k = k +) { + + override fun normalizeDocumentIndexName(namespace: String, botId: String, indexSessionId: String): String = + PGVectorUtils.normalizeDocumentIndexName(namespace, botId, indexSessionId) + + override fun getDocumentSearchParams(): PGVectorParams = + PGVectorParams(k = k, filter = null) +} + +data class PGVectorParams( + val k: Int = 4, + val filter: Map? = null +) : DocumentSearchParamsBase(VectorStoreProvider.PGVector) \ No newline at end of file diff --git a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/VectorStoreProvider.kt b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/VectorStoreProvider.kt index fbca7467b6..df04e091e9 100644 --- a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/VectorStoreProvider.kt +++ b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/VectorStoreProvider.kt @@ -17,7 +17,7 @@ package ai.tock.genai.orchestratorcore.models.vectorstore enum class VectorStoreProvider{ - OpenSearch; + Default, OpenSearch, PGVector; companion object { fun findByName(provider: String): VectorStoreProvider? { diff --git a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/VectorStoreSettingBase.kt b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/VectorStoreSettingBase.kt index c07cb3b1b5..89df4894cb 100644 --- a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/VectorStoreSettingBase.kt +++ b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/models/vectorstore/VectorStoreSettingBase.kt @@ -17,6 +17,8 @@ package ai.tock.genai.orchestratorcore.models.vectorstore +import ai.tock.genai.orchestratorcore.mappers.LLMSettingMapper +import ai.tock.genai.orchestratorcore.mappers.VectorStoreSettingMapper import ai.tock.genai.orchestratorcore.models.Constants import ai.tock.shared.security.key.SecretKey import com.fasterxml.jackson.annotation.JsonSubTypes @@ -28,13 +30,37 @@ import com.fasterxml.jackson.annotation.JsonTypeInfo property = "provider" ) @JsonSubTypes( - JsonSubTypes.Type(value = OpenSearchVectorStoreSetting::class, name = Constants.OPEN_SEARCH) + JsonSubTypes.Type(value = OpenSearchVectorStoreSetting::class, name = Constants.OPEN_SEARCH), + JsonSubTypes.Type(value = PGVectorStoreSetting::class, name = Constants.PG_VECTOR) ) abstract class VectorStoreSettingBase( val provider: VectorStoreProvider, - open val k: Int, // the number of documents (neighbors) to return for each rag query - open val vectorSize: Int, -) + open val host: String, + open val port: Int, + open val username: String, + open val password: T, + // The number of documents (neighbors) to return for each vector search + open val k: Int, +){ + /** + * Normalize the document index name + * @param namespace the namespace + * @param botId the bot ID + */ + abstract fun normalizeDocumentIndexName(namespace: String, botId: String, indexSessionId: String): String + + /** + * Get search params (filter) params + */ + abstract fun getDocumentSearchParams(): DocumentSearchParamsBase +} typealias VectorStoreSettingDTO = VectorStoreSettingBase typealias VectorStoreSetting = VectorStoreSettingBase + +// Extension functions for DTO conversion +fun VectorStoreSetting.toDTO(): VectorStoreSettingDTO = VectorStoreSettingMapper.toDTO(this) + +abstract class DocumentSearchParamsBase( + val provider: VectorStoreProvider, +) diff --git a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/utils/OpenSearchUtils.kt b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/utils/OpenSearchUtils.kt index ac18b21b4a..74f8c8270e 100644 --- a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/utils/OpenSearchUtils.kt +++ b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/utils/OpenSearchUtils.kt @@ -22,11 +22,13 @@ object OpenSearchUtils { * Normalize the document index name * Here, OpenSearch rules are used * See: https://docs.aws.amazon.com/opensearch-service/latest/developerguide/indexing.html#indexing-naming - * @param ragConfig the RAG configuration + * @param namespace the namespace + * @param botId the bot ID + * @param indexSessionId the index session ID */ - fun normalizeDocumentIndexName(namespace: String, botId: String): String { + fun normalizeDocumentIndexName(namespace: String, botId: String, indexSessionId: String): String { // Convert to lowercase - var normalized = "ns-$namespace-bot-$botId".lowercase() + var normalized = "ns-$namespace-bot-$botId-session-$indexSessionId".lowercase() // Replace underscores and space with hyphens normalized = normalized.replace('_', '-').replace(' ', '-') // Remove invalid characters diff --git a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/utils/PGVectorUtils.kt b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/utils/PGVectorUtils.kt new file mode 100644 index 0000000000..03e998d601 --- /dev/null +++ b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/utils/PGVectorUtils.kt @@ -0,0 +1,44 @@ +/* + * Copyright (C) 2017/2021 e-voyageurs technologies + * + * Licensed 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. + */ + +package ai.tock.genai.orchestratorcore.utils + +object PGVectorUtils { + + /** + * Normalize the document index name + * Here, PostgeSQL rules are used + * See: https://www.postgresql.org/docs/7.0/syntax525.htm + * @param namespace the namespace + * @param botId the bot ID + * @param indexSessionId the index session ID + */ + fun normalizeDocumentIndexName(namespace: String, botId: String, indexSessionId: String): String { + // Convert to lowercase + var normalized = "ns-$namespace-bot-$botId-session-$indexSessionId".lowercase() + + // Replace invalid characters with underscores + normalized = normalized.replace(Regex("[^a-z0-9_]"), "_") + + // Ensure the name starts with a letter or underscore + if (!Regex("^[a-z_]").containsMatchIn(normalized)) { + normalized = "_$normalized" + } + + return normalized + } + +} \ No newline at end of file diff --git a/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/utils/VectorStoreUtils.kt b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/utils/VectorStoreUtils.kt new file mode 100644 index 0000000000..5c276daac8 --- /dev/null +++ b/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/utils/VectorStoreUtils.kt @@ -0,0 +1,61 @@ +/* + * Copyright (C) 2017/2021 e-voyageurs technologies + * + * Licensed 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. + */ + +package ai.tock.genai.orchestratorcore.utils + +import ai.tock.genai.orchestratorcore.models.vectorstore.* +import ai.tock.shared.intProperty +import ai.tock.shared.property + +private val vectorStore = property( + name = "tock_gen_ai_orchestrator_vector_store_provider", + defaultValue = VectorStoreProvider.OpenSearch.name) +private val kNeighborsDocuments = intProperty( + name = "tock_gen_ai_orchestrator_document_number_neighbors", + defaultValue = 1) + +typealias DocumentIndexName = String + +object VectorStoreUtils { + + fun getVectorStoreElements( + namespace: String, + botId: String, + indexSessionId: String, + vectorStoreSetting: VectorStoreSetting?, + ): Pair { + + vectorStoreSetting?.let { + val searchParams = it.getDocumentSearchParams() + val indexName = it.normalizeDocumentIndexName(namespace, botId, indexSessionId) + return Pair(searchParams, indexName) + } + + val (documentSearchParams, indexName) = when (vectorStore) { + VectorStoreProvider.OpenSearch.name -> { + OpenSearchParams(k = kNeighborsDocuments) to + OpenSearchUtils.normalizeDocumentIndexName(namespace, botId, indexSessionId) + } + VectorStoreProvider.PGVector.name -> { + PGVectorParams(k = kNeighborsDocuments) to + PGVectorUtils.normalizeDocumentIndexName(namespace, botId, indexSessionId) + } + else -> throw IllegalArgumentException("Unsupported Vector Store Provider [$vectorStore]") + } + + return Pair(documentSearchParams, indexName) + } +} \ No newline at end of file diff --git a/gen-ai/orchestrator-core/src/test/kotlin/ai/tock/genai/orchestratorcore/utils/OpenSearchUtilsTest.kt b/gen-ai/orchestrator-core/src/test/kotlin/ai/tock/genai/orchestratorcore/utils/OpenSearchUtilsTest.kt index 94bb54ee20..321c2013f7 100644 --- a/gen-ai/orchestrator-core/src/test/kotlin/ai/tock/genai/orchestratorcore/utils/OpenSearchUtilsTest.kt +++ b/gen-ai/orchestrator-core/src/test/kotlin/ai/tock/genai/orchestratorcore/utils/OpenSearchUtilsTest.kt @@ -18,7 +18,6 @@ package ai.tock.genai.orchestratorcore.utils import org.junit.jupiter.api.Test import kotlin.test.assertEquals -import kotlin.test.assertTrue class OpenSearchUtilsTest { @Test @@ -27,34 +26,36 @@ class OpenSearchUtilsTest { // GIVEN // "namespace" in uppercase // "botId" in uppercase + // "indexSessionId" in uppercase // WHEN : // Launch of the normalisation val indexName = OpenSearchUtils.normalizeDocumentIndexName( - namespace = "NAMESPACE", botId = "BOTID" + namespace = "NAMESPACE", botId = "BOTID", indexSessionId = "123-ABC-5F" ) // THEN : // Convert to lowercase - assertEquals("ns-namespace-bot-botid", indexName) + assertEquals("ns-namespace-bot-botid-session-123-abc-5f", indexName) } @Test fun `when namespace and botId has a underscore`() { // GIVEN - // "namespace" has a underscore - // "botId" has a underscore + // "namespace" has an underscore + // "botId" has an underscore + // "indexSessionId" in uppercase // WHEN : // Launch of the normalisation val indexName = OpenSearchUtils.normalizeDocumentIndexName( - namespace = "my_private_namespace", botId = "bot_id" + namespace = "my_private_namespace", botId = "bot_id", indexSessionId = "123-ABC-5F" ) // THEN : // Replace underscores with hyphens - assertEquals("ns-my-private-namespace-bot-bot-id", indexName) + assertEquals("ns-my-private-namespace-bot-bot-id-session-123-abc-5f", indexName) } @Test @@ -63,15 +64,16 @@ class OpenSearchUtilsTest { // GIVEN // "namespace" has a "*" // "botId" has a "?" + // "indexSessionId" in uppercase // WHEN : // Launch of the normalisation val indexName = OpenSearchUtils.normalizeDocumentIndexName( - namespace = "my_private*", botId = "bot?id" + namespace = "my_private*", botId = "bot?id", indexSessionId = "123-ABC-5F" ) // THEN : // Remove invalid characters - assertEquals("ns-my-private-bot-botid", indexName) + assertEquals("ns-my-private-bot-botid-session-123-abc-5f", indexName) } } \ No newline at end of file diff --git a/gen-ai/orchestrator-server/src/main/python/server/poetry.lock b/gen-ai/orchestrator-server/src/main/python/server/poetry.lock index 2258cc49df..57644d984c 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/poetry.lock +++ b/gen-ai/orchestrator-server/src/main/python/server/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.7.0 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. 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[tool.poetry.dependencies] -python = "^3.9" -uvicorn = "^0.25.0" -pydantic-settings="^2.1.0" -fastapi = "^0.109.2" -langchain = "^0.1.0" -langchain-openai = "^0.0.2" -tiktoken = "^0.5.2" -opensearch-py = "^2.4.2" -path = "^16.9.0" -colorlog = "^6.8.0" -boto3 = "^1.34.25" -urllib3 = "^1.26" -jinja2 = "^3.1.3" -langfuse = "^2.33.0" +python = "^3.10" +uvicorn = "^0.31.0" +pydantic-settings="^2.5.2" +fastapi = "^0.115.0" +langchain = "^0.3.2" +langchain-openai = "^0.2.2" +tiktoken = "^0.8.0" +opensearch-py = "^2.7.1" +path = "^17.0.0" +colorlog = "^6.8.2" +boto3 = "^1.35.35" +urllib3 = "^2.2.3" +jinja2 = "^3.1.4" +langfuse = "^2.51.4" httpx-auth-awssigv4 = "^0.1.4" +langchain-postgres = "^0.0.12" google-cloud-secret-manager = "^2.20.2" +psycopg = {extras = ["binary"], version = "^3.2.3"} [tool.poetry.group.dev.dependencies] diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/configurations/environment/settings.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/configurations/environment/settings.py index 6dbd261b8a..9e697906cd 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/configurations/environment/settings.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/configurations/environment/settings.py @@ -13,45 +13,26 @@ # limitations under the License. # """ -This module manages the initialization of application settings, based on environment variables -The OpenSearch master user credentials are retrieved from AWS Secrets Manager if -open_search_aws_secret_manager_name is set +This module manages the initialization of application settings, based on environment variables. +The default Vector Store credentials are configured directly on environment, +or retrieved from the Secret Manager Provider if the vector_store_credentials_secret_name is set. """ import logging -from email.policy import default from enum import Enum, unique -from typing import Optional, Tuple +from typing import Optional from path import Path from pydantic import Field -from pydantic_settings import BaseSettings, SettingsConfigDict +from pydantic_settings import SettingsConfigDict, BaseSettings from gen_ai_orchestrator.models.security.proxy_server_type import ProxyServerType from gen_ai_orchestrator.models.vector_stores.vectore_store_provider import VectorStoreProvider -from gen_ai_orchestrator.utils.aws.aws_secrets_manager_client import AWSSecretsManagerClient -from gen_ai_orchestrator.utils.strings import obfuscate +from gen_ai_orchestrator.utils.secret_manager.secret_manager_provider import SecretManagerProvider logger = logging.getLogger(__name__) -def fetch_open_search_credentials() -> Tuple[Optional[str], Optional[str]]: - """Fetch the OpenSearch credentials.""" - if application_settings.open_search_aws_secret_manager_name is not None: - logger.info('Use of AWS Secrets Manager to get OpenSearch credentials...') - credentials = AWSSecretsManagerClient().get_credentials( - secret_name=application_settings.open_search_aws_secret_manager_name - ) - if credentials is not None: - logger.info("The credentials have been successfully retrieved from AWS Secrets Manager.") - return credentials.username, credentials.password - else: - logger.error("No credentials extracted from AWS Secrets Manager.") - return None, None - else: - return application_settings.open_search_user, application_settings.open_search_pwd - - @unique class _Environment(str, Enum): """Enumeration to list environment type""" @@ -76,23 +57,24 @@ class _Settings(BaseSettings): llm_provider_max_retries: int = 0 em_provider_timeout: int = 4 + vector_store_provider: Optional[VectorStoreProvider] = VectorStoreProvider.OPEN_SEARCH + vector_store_host: Optional[str] = 'localhost' + vector_store_port: Optional[str] = '9200' + vector_store_user: Optional[str] = 'admin' + vector_store_pwd: Optional[str] = 'admin' + vector_store_database: Optional[str] = None # Only if necessary. Example: PGVector + vector_store_secret_manager_provider: Optional[SecretManagerProvider] = None + vector_store_credentials_secret_name: Optional[str] = None + """Number of document to retrieve from the Vector Store""" + vector_store_k: int = 4 """Request timeout: set the maximum time (in seconds) for the request to be completed.""" vector_store_timeout: int = 4 - vector_store_provider: Optional[VectorStoreProvider] = VectorStoreProvider.OPEN_SEARCH.value - - """OpenSearch Vector Store Setting""" - open_search_host: str = 'localhost' - open_search_port: str = '9200' - open_search_aws_secret_manager_name: Optional[str] = None - open_search_user: Optional[str] = 'admin' - open_search_pwd: Optional[str] = 'admin' - """Request timeout: set the maximum time (in seconds) for the request to be completed.""" - open_search_timeout: int = 4 + vector_store_test_query: str = 'What knowledge do you have?' + """Observability Setting""" observability_provider_max_retries: int = 0 """Request timeout (in seconds).""" observability_provider_timeout: int = 3 - """ This AWSLambda proxy is used when the architecture implemented for the Langfuse observability tool places it behind an API Gateway which requires its @@ -104,20 +86,9 @@ class _Settings(BaseSettings): observability_proxy_server: Optional[ProxyServerType] = None observability_proxy_server_authorization_header_name: Optional[str] = None - gcp_project_id: Optional[str] = Field(alias='tock_gcp_project_id', default=None) + """GCP""" + gcp_project_id: Optional[str] = Field(alias='tock_gcp_project_id', default=None) # GCP project ID used for GCP Secrets application_settings = _Settings() is_prod_environment = _Environment.PROD == application_settings.application_environment - -if VectorStoreProvider.OPEN_SEARCH == application_settings.vector_store_provider: - open_search_username, open_search_password = fetch_open_search_credentials() - - if open_search_password is not None : - logger.info( - 'OpenSearch user credentials: %s:%s', - open_search_username, - obfuscate(open_search_password), - ) -else: - open_search_username, open_search_password = None, None diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/errors/exceptions/vector_store/vector_store_exceptions.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/errors/exceptions/vector_store/vector_store_exceptions.py index d4ef12e637..c56df8e90a 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/errors/exceptions/vector_store/vector_store_exceptions.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/errors/exceptions/vector_store/vector_store_exceptions.py @@ -37,5 +37,10 @@ class GenAIUnknownVectorStoreProviderSettingException(GenAIOrchestratorException def __init__(self, info: Optional[ErrorInfo] = None): super().__init__(ErrorCode.VECTOR_STORE_UNKNOWN_PROVIDER_SETTING, info) +class GenAIVectorStoreNoDocumentRetrievedException(GenAIOrchestratorException): + """No documents were retrieved from the Vector Store""" + + def __init__(self, info: Optional[ErrorInfo] = None): + super().__init__(ErrorCode.VECTOR_STORE_NO_DOCUMENT_RETRIEVED, info) diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/errors/errors_models.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/errors/errors_models.py index ebcb1cc6d6..8a43d75f82 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/errors/errors_models.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/errors/errors_models.py @@ -49,6 +49,7 @@ class ErrorCode(Enum): # Vector Store Errors VECTOR_STORE_UNKNOWN_PROVIDER = 3000 VECTOR_STORE_UNKNOWN_PROVIDER_SETTING = 3001 + VECTOR_STORE_NO_DOCUMENT_RETRIEVED = 3002 # OpenSearch Errors OPEN_SEARCH_SETTINGS_ERROR = 4000 @@ -167,7 +168,9 @@ class ErrorMessages: detail='Reduce the length of the prompt message.', ), # Vector Store Errors - ErrorCode.VECTOR_STORE_UNKNOWN_PROVIDER: ErrorMessage(message='Unknown vector store.'), + ErrorCode.VECTOR_STORE_UNKNOWN_PROVIDER: ErrorMessage(message='Unknown vector store provider.'), + ErrorCode.VECTOR_STORE_UNKNOWN_PROVIDER_SETTING: ErrorMessage(message='Unknown vector store setting.'), + ErrorCode.VECTOR_STORE_NO_DOCUMENT_RETRIEVED: ErrorMessage(message='No documents were retrieved from the vector store.'), # OpenSearch Errors ErrorCode.OPEN_SEARCH_SETTINGS_ERROR: ErrorMessage( message='The OpenSearch is improperly configured.', diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/security/credentials.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/security/credentials.py index 6581409dfe..af8538643e 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/security/credentials.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/security/credentials.py @@ -27,5 +27,5 @@ class Credentials(BaseModel): password: str = Field( description='The password.', examples=['a12G-3@p!'], - min_length=8 + min_length=4 ) diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/open_search/open_search_params.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/open_search/open_search_params.py index 2cc5b4e73d..82a2411609 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/open_search/open_search_params.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/open_search/open_search_params.py @@ -14,7 +14,7 @@ # """Model for creating OpenSearchParams.""" -from typing import List, Literal +from typing import List, Literal, Optional from pydantic import Field @@ -34,24 +34,18 @@ class OpenSearchParams(BaseVectorStoreSearchParams): examples=[VectorStoreProvider.OPEN_SEARCH], default=VectorStoreProvider.OPEN_SEARCH, ) - k: int = Field( - description='The number of documents (neighbors) to return for each query_embedding.', - examples=[3], - default=4, - ) - filter: List[OpenSearchTermParams] = Field( + filter: Optional[List[OpenSearchTermParams]] = Field( description='The OpenSearch boolean query filter. Logical "and" operator is applied. For more information, ' 'see : https://opensearch.org/docs/latest/query-dsl/compound/bool/', examples=[[{'term': {'key_1': 'value_1'}}, {'term': {'key_2': 'value_2'}}]], + default=None ) def to_dict(self): - return { - 'k': self.k, - 'filter': list( - map( - lambda term_param: {'term': term_param.term}, - self.filter, - ) - ), - } + result = {'k': self.k} + + if self.filter: + result['filter'] = [{'term': term_param.term} for term_param in self.filter] + + return result + diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/pgvector/__init__.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/pgvector/__init__.py new file mode 100644 index 0000000000..9e67ec83d9 --- /dev/null +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/pgvector/__init__.py @@ -0,0 +1,14 @@ +# Copyright (C) 2023-2024 Credit Mutuel Arkea +# +# Licensed 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. +# diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/pgvector/pgvector_params.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/pgvector/pgvector_params.py new file mode 100644 index 0000000000..f4df43df54 --- /dev/null +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/pgvector/pgvector_params.py @@ -0,0 +1,48 @@ +# Copyright (C) 2023-2024 Credit Mutuel Arkea +# +# Licensed 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. +# +"""Model for creating PGVectorParams.""" + +from typing import Literal, Optional + +from pydantic import Field + +from gen_ai_orchestrator.models.vector_stores.vector_store_search_params import BaseVectorStoreSearchParams +from gen_ai_orchestrator.models.vector_stores.vectore_store_provider import ( + VectorStoreProvider, +) + + +class PGVectorParams(BaseVectorStoreSearchParams): + """ + The PGVector params. Used to search with filter. + https://api.python.langchain.com/en/latest/vectorstores/langchain_postgres.vectorstores.PGVector.html + """ + + provider: Literal[VectorStoreProvider.PGVECTOR] = Field( + description='The Vector Store Provider.', + examples=[VectorStoreProvider.PGVECTOR], + default=VectorStoreProvider.PGVECTOR, + ) + filter: Optional[dict] = Field( + description='Filter by metadata.', + examples=[{'tag1': 'vector stores'}], + default=None, + ) + + def to_dict(self): + return { + 'k': self.k, + 'filter': self.filter, + } diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/pgvector/pgvector_setting.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/pgvector/pgvector_setting.py new file mode 100644 index 0000000000..83c7e871ea --- /dev/null +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/pgvector/pgvector_setting.py @@ -0,0 +1,62 @@ +# Copyright (C) 2023-2024 Credit Mutuel Arkea +# +# Licensed 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. +# +"""Model for creating PGVectorStoreSetting.""" + +from typing import Literal + +from pydantic import Field + +from gen_ai_orchestrator.models.security.raw_secret_key.raw_secret_key import ( + RawSecretKey, +) +from gen_ai_orchestrator.models.security.security_types import SecretKey +from gen_ai_orchestrator.models.vector_stores.vector_store_setting import BaseVectorStoreSetting +from gen_ai_orchestrator.models.vector_stores.vectore_store_provider import VectorStoreProvider + + +class PGVectorStoreSetting(BaseVectorStoreSetting): + """ + A class for PGVector Vector Store Setting. + Usage docs: https://github.com/pgvector/pgvector + """ + + provider: Literal[VectorStoreProvider.PGVECTOR] = Field( + description='The Vector Store Provider.', + examples=[VectorStoreProvider.PGVECTOR], + default=VectorStoreProvider.PGVECTOR + ) + host: str = Field( + description='The hostname of postgres server', examples=['localhost'], + default='localhost' + ) + port: int = Field( + description='The postgres server port', examples=['5432'], + default='5432' + ) + username: str = Field( + description='The vector store connection username.', + examples=['postgres'], + ) + password: SecretKey = Field( + description='The vector store connection password.', + examples=[RawSecretKey(value='postgres')], + ) + database: str = Field( + description='The postgres name', examples=['postgres'], + default='postgres' + ) + + + diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vector_store_search_params.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vector_store_search_params.py index 12befbde4a..f693f65aca 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vector_store_search_params.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vector_store_search_params.py @@ -30,6 +30,11 @@ class BaseVectorStoreSearchParams(ABC, BaseModel): description='The Vector Store Provider.', examples=[VectorStoreProvider.OPEN_SEARCH], ) + k: int = Field( + description='The number of Documents to return.', + examples=[3], + default=4, + ) @abstractmethod def to_dict(self) -> dict: diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vector_store_setting.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vector_store_setting.py index 6017ad9798..6646fb0292 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vector_store_setting.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vector_store_setting.py @@ -13,7 +13,6 @@ # limitations under the License. # """Model for creating BaseVectorStoreSetting.""" -from typing import Optional from pydantic import BaseModel, Field @@ -24,8 +23,4 @@ class BaseVectorStoreSetting(BaseModel): """A base class for Vector Store Setting.""" provider: VectorStoreProvider = Field(description='The Vector Store Provider.') - vector_size: int = Field( - description='The size of the embedding vector.', examples=[1536], default=1536, - ge=1 - ) diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vector_store_types.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vector_store_types.py index bf2c773ad9..66989bcffd 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vector_store_types.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vector_store_types.py @@ -20,11 +20,13 @@ from gen_ai_orchestrator.models.vector_stores.open_search.open_search_params import OpenSearchParams from gen_ai_orchestrator.models.vector_stores.open_search.open_search_setting import OpenSearchVectorStoreSetting +from gen_ai_orchestrator.models.vector_stores.pgvector.pgvector_params import PGVectorParams +from gen_ai_orchestrator.models.vector_stores.pgvector.pgvector_setting import PGVectorStoreSetting DocumentSearchParams = Annotated[ - Union[OpenSearchParams], Body(discriminator='provider') + Union[OpenSearchParams, PGVectorParams], Body(discriminator='provider') ] VectorStoreSetting = Annotated[ - Union[OpenSearchVectorStoreSetting], Body(discriminator='provider') + Union[OpenSearchVectorStoreSetting, PGVectorStoreSetting], Body(discriminator='provider') ] diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vectore_store_provider.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vectore_store_provider.py index 3e99febafa..749172a473 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vectore_store_provider.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/models/vector_stores/vectore_store_provider.py @@ -22,6 +22,7 @@ class VectorStoreProvider(str, Enum): """Enumeration to list Vector Store Provider types""" OPEN_SEARCH = 'OpenSearch' + PGVECTOR = 'PGVector' @classmethod def has_value(cls, value): diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/routers/rag_router.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/routers/rag_router.py index c7d004764a..ec2746ce98 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/routers/rag_router.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/routers/rag_router.py @@ -13,20 +13,63 @@ # limitations under the License. # """RAG Router Module""" +import logging from fastapi import APIRouter +from fastapi import Request +from gen_ai_orchestrator.configurations.environment.settings import application_settings +from gen_ai_orchestrator.errors.exceptions.ai_provider.ai_provider_exceptions import AIProviderBadQueryException +from gen_ai_orchestrator.errors.handlers.fastapi.fastapi_handler import create_error_info_bad_request +from gen_ai_orchestrator.models.vector_stores.vector_store_types import VectorStoreSetting, DocumentSearchParams from gen_ai_orchestrator.routers.requests.requests import RagQuery from gen_ai_orchestrator.routers.responses.responses import RagResponse from gen_ai_orchestrator.services.rag.rag_service import rag +logger = logging.getLogger(__name__) + rag_router = APIRouter(prefix='/rag', tags=['Retrieval Augmented Generation']) @rag_router.post('') -async def ask_rag(query: RagQuery, debug: bool = False) -> RagResponse: +async def ask_rag(request: Request, query: RagQuery, debug: bool = False) -> RagResponse: """ ## Ask a RAG System Ask question to a RAG System, and return answer by using a knowledge base (documents) """ + # Check the consistency of the Vector Store Provider with the request body + validate_vector_store_rag_query(request, query.vector_store_setting, query.document_search_params) + + # execute RAG return await rag(query, debug) + +def validate_vector_store_rag_query( + request: Request, + vector_store_setting: VectorStoreSetting, + vector_store_search_params: DocumentSearchParams): + """ + Check the consistency of the Vector Store Provider with the request body + Args: + request: The http request + vector_store_setting: The Vector Store Provider Setting + vector_store_search_params: the vector store search params + + Raises: + AIProviderBadQueryException: if the search parameters are not compatible with the vector store + """ + + logger.debug('RAG - Query validation') + + vector_store_provider = application_settings.vector_store_provider + if vector_store_setting is not None: + vector_store_provider = vector_store_setting.provider + + if vector_store_provider != vector_store_search_params.provider: + logger.error('Inconsistency between vector store provider and document search parameters (%s Vs %s)', + vector_store_provider.value, vector_store_search_params.provider.value) + raise AIProviderBadQueryException( + create_error_info_bad_request( + request=request, + provider=vector_store_search_params.provider, + cause='Inconsistency between vector store provider and document search parameters') + ) diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/routers/requests/requests.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/routers/requests/requests.py index c271895dcf..ca27181d2d 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/routers/requests/requests.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/routers/requests/requests.py @@ -111,9 +111,17 @@ class QAQuery(BaseQuery): class VectorStoreProviderSettingStatusQuery(BaseModel): """The query for the Vector Store Provider Setting Status""" - setting: VectorStoreSetting = Field(description='The Vector Store Provider setting to be checked.') - index_name: str = Field( - description='Index name corresponding to a document collection in the vector database.' + vector_store_setting: Optional[VectorStoreSetting] = Field( + description='The Vector Store Provider setting to be checked.', + default=None + ) + em_setting: Optional[EMSetting] = Field( + description="Embedding model setting, used to calculate the user's question vector.", + default=None + ) + document_index_name: Optional[str] = Field( + description='Index name corresponding to a document collection in the vector database.', + default=None ) diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/routers/vector_store_providers_router.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/routers/vector_store_providers_router.py index 200c8a3b94..8190f31902 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/routers/vector_store_providers_router.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/routers/vector_store_providers_router.py @@ -137,11 +137,12 @@ async def check_vector_store_provider_setting( logger.info('Start Vector Store setting check for provider %s', provider_id) # Query validation - validate_query(request, provider_id, query.setting) + if query.vector_store_setting is not None: + validate_query(request, provider_id, query.vector_store_setting) try: # Vector Store setting check - await check_vector_store_setting(query.setting, query.index_name) + await check_vector_store_setting(query.vector_store_setting, query.em_setting, query.document_index_name) logger.info('The Vector Store setting is valid') return ProviderSettingStatusResponse(valid=True) diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/langchain_factory.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/langchain_factory.py index 8cb589c41c..eda1615e57 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/langchain_factory.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/langchain_factory.py @@ -26,8 +26,7 @@ from langchain_core.embeddings import Embeddings from langfuse.callback import CallbackHandler as LangfuseCallbackHandler -from gen_ai_orchestrator.configurations.environment.settings import open_search_password, open_search_username, \ - application_settings +from gen_ai_orchestrator.configurations.environment.settings import application_settings from gen_ai_orchestrator.errors.exceptions.exceptions import ( GenAIUnknownProviderSettingException, ) @@ -56,7 +55,9 @@ from gen_ai_orchestrator.models.observability.observability_type import ObservabilitySetting from gen_ai_orchestrator.models.security.raw_secret_key.raw_secret_key import RawSecretKey from gen_ai_orchestrator.models.vector_stores.open_search.open_search_setting import OpenSearchVectorStoreSetting +from gen_ai_orchestrator.models.vector_stores.pgvector.pgvector_setting import PGVectorStoreSetting from gen_ai_orchestrator.models.vector_stores.vector_store_types import VectorStoreSetting +from gen_ai_orchestrator.models.vector_stores.vectore_store_provider import VectorStoreProvider from gen_ai_orchestrator.routers.requests.requests import RagQuery from gen_ai_orchestrator.services.langchain.factories.callback_handlers.callback_handlers_factory import \ LangChainCallbackHandlerFactory @@ -86,9 +87,11 @@ from gen_ai_orchestrator.services.langchain.factories.vector_stores.open_search_factory import ( OpenSearchFactory, ) +from gen_ai_orchestrator.services.langchain.factories.vector_stores.pgvector_factory import PGVectorFactory from gen_ai_orchestrator.services.langchain.factories.vector_stores.vector_store_factory import ( LangChainVectorStoreFactory, ) +from gen_ai_orchestrator.utils.secret_manager.secret_manager_service import vector_store_credentials logger = logging.getLogger(__name__) @@ -159,30 +162,70 @@ def get_vector_store_factory( Returns: The LangChain Vector Store Factory, or raise an exception otherwise """ + logger.info('Get Vector Store Factory for the given setting') - logger.info('Get Vector Store Factory for the given provider') - if setting is None: - logger.debug('Vector Store Factory (based on env variables) - OpenSearchFactory') + # Helper function to create OpenSearchFactory + def create_opensearch_factory(vs_setting: Optional[OpenSearchVectorStoreSetting]) -> OpenSearchFactory: return OpenSearchFactory( - setting=OpenSearchVectorStoreSetting( - host=application_settings.open_search_host, - port=application_settings.open_search_port, - username=open_search_username, - password=RawSecretKey(value=open_search_password), + setting=vs_setting or OpenSearchVectorStoreSetting( + host=application_settings.vector_store_host, + port=application_settings.vector_store_port, + username=vector_store_credentials.username, + password=RawSecretKey(value=vector_store_credentials.password), ), index_name=index_name, embedding_function=embedding_function ) - elif isinstance(setting, OpenSearchVectorStoreSetting): - logger.debug('Vector Store Factory (based on RAG query) - OpenSearchFactory') - return OpenSearchFactory( - setting=setting, + + # Helper function to create PGVectorFactory + def create_pgvector_factory(vs_setting: Optional[PGVectorStoreSetting]) -> PGVectorFactory: + return PGVectorFactory( + setting=vs_setting or PGVectorStoreSetting( + host=application_settings.vector_store_host, + port=application_settings.vector_store_port, + username=vector_store_credentials.username, + password=RawSecretKey(value=vector_store_credentials.password), + database=application_settings.vector_store_database + ), index_name=index_name, embedding_function=embedding_function ) - else: + + # If no setting is provided, use defaults from environment variables + if setting is None: + logger.info('No Vector Store setting was given.') + + # Validate required default settings + if application_settings.vector_store_provider is None or vector_store_credentials is None: + logger.error('No default Vector Store defined!') + raise GenAIUnknownVectorStoreProviderSettingException() + + # Dictionary dispatch for factory creation based on provider type + factory_dispatch = { + VectorStoreProvider.OPEN_SEARCH: create_opensearch_factory, + VectorStoreProvider.PGVECTOR: create_pgvector_factory, + } + + # Create factory based on the provider type + provider = application_settings.vector_store_provider + if provider in factory_dispatch: + logger.debug(f'Creating Vector Store Factory from environment - {provider}') + return factory_dispatch[provider](None) + + logger.error('Unknown Vector Store provider in environment!') raise GenAIUnknownVectorStoreProviderSettingException() + # Use the provided setting to determine the factory type + if isinstance(setting, OpenSearchVectorStoreSetting): + logger.debug('Creating Vector Store Factory based on RAG query - OpenSearchFactory') + return create_opensearch_factory(setting) + elif isinstance(setting, PGVectorStoreSetting): + logger.debug('Creating Vector Store Factory based on RAG query - PGVectorFactory') + return create_pgvector_factory(setting) + + logger.error('Unknown Vector Store provider setting in RAG query!') + raise GenAIUnknownVectorStoreProviderSettingException() + def get_callback_handler_factory(setting: BaseObservabilitySetting) -> LangChainCallbackHandlerFactory: """ diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/vector_stores/open_search_factory.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/vector_stores/open_search_factory.py index 93aa55d2f7..4a5dba5da9 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/vector_stores/open_search_factory.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/vector_stores/open_search_factory.py @@ -14,7 +14,6 @@ # """Model for creating OpenSearchFactory""" import logging -from typing import Optional, Any from langchain_community.vectorstores.opensearch_vector_search import OpenSearchVectorSearch from langchain_core.vectorstores import VectorStoreRetriever @@ -23,6 +22,7 @@ application_settings, is_prod_environment ) +from gen_ai_orchestrator.errors.handlers.opensearch.opensearch_exception_handler import opensearch_exception_handler from gen_ai_orchestrator.models.vector_stores.open_search.open_search_setting import OpenSearchVectorStoreSetting from gen_ai_orchestrator.services.langchain.factories.vector_stores.vector_store_factory import ( LangChainVectorStoreFactory, @@ -40,9 +40,8 @@ class OpenSearchFactory(LangChainVectorStoreFactory): """ setting: OpenSearchVectorStoreSetting - index_name: str - def get_vector_store(self): + def get_vector_store(self) -> OpenSearchVectorSearch: password = fetch_secret_key_value(self.setting.password) logger.info( 'OpenSearch user credentials: %s:%s', @@ -70,3 +69,9 @@ def get_vector_store_retriever(self, search_kwargs: dict) -> VectorStoreRetrieve return self.get_vector_store().as_retriever( search_kwargs=search_kwargs ) + + @opensearch_exception_handler + async def check_vector_store_connection(self) -> bool: + """To check the connection information, we ask for basic information about the cluster.""" + self.get_vector_store().client.info() + return True diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/vector_stores/pgvector_factory.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/vector_stores/pgvector_factory.py new file mode 100644 index 0000000000..1c36a0261c --- /dev/null +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/vector_stores/pgvector_factory.py @@ -0,0 +1,69 @@ +# Copyright (C) 2023-2024 Credit Mutuel Arkea +# +# Licensed 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. +# +"""Model for creating PGVectorFactory""" +import logging + +from langchain_core.vectorstores import VectorStoreRetriever +from langchain_postgres import PGVector + +from gen_ai_orchestrator.configurations.environment.settings import application_settings +from gen_ai_orchestrator.models.vector_stores.pgvector.pgvector_setting import PGVectorStoreSetting +from gen_ai_orchestrator.services.langchain.factories.vector_stores.vector_store_factory import ( + LangChainVectorStoreFactory, +) +from gen_ai_orchestrator.services.security.security_service import fetch_secret_key_value +from gen_ai_orchestrator.utils.strings import obfuscate + +logger = logging.getLogger(__name__) + + +class PGVectorFactory(LangChainVectorStoreFactory): + """ + A class for LangChain PGVector Factory + https://api.python.langchain.com/en/latest/vectorstores/langchain_postgres.vectorstores.PGVector.html + """ + + setting: PGVectorStoreSetting + + def get_vector_store(self) -> PGVector: + password = fetch_secret_key_value(self.setting.password) + logger.info( + 'PostgreSQL user credentials: %s:%s', + self.setting.username, + obfuscate(password), + ) + + return PGVector( + embeddings=self.embedding_function, + collection_name=self.index_name, + connection=f'postgresql+psycopg://{self.setting.username}:{password}@{self.setting.host}:{self.setting.port}/{self.setting.database}', + use_jsonb=True, + async_mode=True + ) + + def get_vector_store_retriever(self, search_kwargs: dict) -> VectorStoreRetriever: + return self.get_vector_store().as_retriever( + search_kwargs=search_kwargs + ) + + async def check_vector_store_connection(self) -> bool: + """ + To check the connection information, we perform a vector search :The objective is not the search result itself. + We do this because the langchain implementation doesn't provide us with a method on the + VectorStore to check the connection independently. + """ + await self.get_vector_store().asimilarity_search( + query=application_settings.vector_store_test_query, k=application_settings.vector_store_k) + return True diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/vector_stores/vector_store_factory.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/vector_stores/vector_store_factory.py index 68133b78cf..5d886d81a9 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/vector_stores/vector_store_factory.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/factories/vector_stores/vector_store_factory.py @@ -16,13 +16,18 @@ import logging from abc import ABC, abstractmethod -from typing import Optional +from typing import List +from langchain_core.documents import Document from langchain_core.embeddings import Embeddings from langchain_core.vectorstores import VectorStore, VectorStoreRetriever from pydantic import BaseModel, ConfigDict +from gen_ai_orchestrator.configurations.environment.settings import application_settings +from gen_ai_orchestrator.errors.exceptions.vector_store.vector_store_exceptions import \ + GenAIVectorStoreNoDocumentRetrievedException from gen_ai_orchestrator.errors.handlers.opensearch.opensearch_exception_handler import opensearch_exception_handler +from gen_ai_orchestrator.models.errors.errors_models import ErrorInfo from gen_ai_orchestrator.models.vector_stores.vector_store_setting import BaseVectorStoreSetting logger = logging.getLogger(__name__) @@ -33,6 +38,7 @@ class LangChainVectorStoreFactory(ABC, BaseModel): setting: BaseVectorStoreSetting embedding_function: Embeddings + index_name: str model_config = ConfigDict(arbitrary_types_allowed=True) @abstractmethod @@ -65,11 +71,22 @@ async def check_vector_store_setting(self) -> bool: BusinessException: For incorrect setting """ logger.info('Invoke vector store provider to check setting') - query = 'what is a vector store ?' - response = await self.get_vector_store().asimilarity_search( - query=query, - k=1 + documents: List[Document] = await self.get_vector_store().asimilarity_search( + query=application_settings.vector_store_test_query, k=application_settings.vector_store_k ) - logger.info('Invocation successful') - logger.debug('[query: %s], [response: %s]', query, response) - return True + logger.debug('Invocation successful') + logger.debug('[index: %s], [query: %s], [document count: %s]', self.index_name, application_settings.vector_store_test_query, len(documents)) + if len(documents) > 0 : + return True + else: + logger.warning('No documents retrieved from the Vector Store') + raise GenAIVectorStoreNoDocumentRetrievedException(ErrorInfo( + provider=self.setting.provider.value, + error='No documents retrieved', + cause='Index not found or data not ingested' + )) + + @abstractmethod + async def check_vector_store_connection(self) -> bool: + """Check vector store connection and authentication""" + pass diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/rag_chain.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/rag_chain.py index 44b32dcc05..0cef58558e 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/rag_chain.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/langchain/rag_chain.py @@ -180,11 +180,11 @@ def create_rag_chain(query: RagQuery) -> ConversationalRetrievalChain: index_name=query.document_index_name, embedding_function=em_factory.get_embedding_model()) + logger.debug('RAG chain - Document index name: %s', query.document_index_name) logger.debug('RAG chain - Create a ConversationalRetrievalChain from LLM') return ConversationalRetrievalChain.from_llm( llm=llm_factory.get_language_model(), - retriever=vector_store_factory.get_vector_store_retriever( - None if query.document_search_params is None else query.document_search_params.to_dict()), + retriever=vector_store_factory.get_vector_store_retriever(query.document_search_params.to_dict()), return_source_documents=True, return_generated_question=True, combine_docs_chain_kwargs={ diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/vector_store/vector_store_service.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/vector_store/vector_store_service.py index 80f1874037..5584d050c5 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/vector_store/vector_store_service.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/services/vector_store/vector_store_service.py @@ -15,21 +15,27 @@ """Module for the Vector Store Service""" import logging +from typing import Optional from langchain_community.embeddings import FakeEmbeddings +from gen_ai_orchestrator.models.em.em_types import EMSetting from gen_ai_orchestrator.models.vector_stores.vector_store_types import VectorStoreSetting -from gen_ai_orchestrator.services.langchain.factories.langchain_factory import get_vector_store_factory +from gen_ai_orchestrator.services.langchain.factories.langchain_factory import get_vector_store_factory, get_em_factory logger = logging.getLogger(__name__) -async def check_vector_store_setting(setting: VectorStoreSetting, index_name: str) -> bool: +async def check_vector_store_setting( + vector_store_setting: Optional[VectorStoreSetting], + em_setting: Optional[EMSetting], + index_name: Optional[str]) -> bool: """ Run a check for a given Vector Store setting. Args: - setting: The Vector Store setting to check + vector_store_setting: The Vector Store setting to check + em_setting: The Embeddings setting to use with the Vector Store index_name: the index name Returns: @@ -37,7 +43,17 @@ async def check_vector_store_setting(setting: VectorStoreSetting, index_name: st """ logger.info('Get the Callback handler Factory, then check the Vector Store setting.') - return await get_vector_store_factory(setting=setting, - index_name=index_name, - embedding_function=FakeEmbeddings(size=setting.vector_size) - ).check_vector_store_setting() + + if em_setting is None or index_name is None: + return await get_vector_store_factory( + setting=vector_store_setting, + index_name="fake_index_name", + embedding_function=FakeEmbeddings(size=1536) + ).check_vector_store_connection() + else: + return await get_vector_store_factory( + setting=vector_store_setting, + index_name=index_name, + embedding_function=get_em_factory(em_setting).get_embedding_model() + ).check_vector_store_setting() + diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/aws/aws_secrets_manager_client.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/aws/aws_secrets_manager_client.py index 6f79ffac61..fe218890e0 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/aws/aws_secrets_manager_client.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/aws/aws_secrets_manager_client.py @@ -20,7 +20,7 @@ import boto3 from botocore.exceptions import ClientError -from gen_ai_orchestrator.utils.secret_manager.secrets_manager_client import SecretManagerClient +from gen_ai_orchestrator.utils.secret_manager.secret_manager_client import SecretManagerClient logger = logging.getLogger(__name__) T = TypeVar('T') diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/gcp/gcp_secret_manager_client.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/gcp/gcp_secret_manager_client.py index 058fa699f8..687c23bf58 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/gcp/gcp_secret_manager_client.py +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/gcp/gcp_secret_manager_client.py @@ -22,7 +22,7 @@ from google.cloud import secretmanager from gen_ai_orchestrator.configurations.environment.settings import application_settings -from gen_ai_orchestrator.utils.secret_manager.secrets_manager_client import SecretManagerClient +from gen_ai_orchestrator.utils.secret_manager.secret_manager_client import SecretManagerClient logger = logging.getLogger(__name__) T = TypeVar('T') diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/secret_manager/secrets_manager_client.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/secret_manager/secret_manager_client.py similarity index 100% rename from gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/secret_manager/secrets_manager_client.py rename to gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/secret_manager/secret_manager_client.py diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/secret_manager/secret_manager_provider.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/secret_manager/secret_manager_provider.py new file mode 100644 index 0000000000..9c3bcd554f --- /dev/null +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/secret_manager/secret_manager_provider.py @@ -0,0 +1,29 @@ +# Copyright (C) 2023-2024 Credit Mutuel Arkea +# +# Licensed 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. +# +"""SecretManagerProvider Enumeration.""" + +from enum import Enum, unique + + +@unique +class SecretManagerProvider(str, Enum): + """Enumeration to list Secret Manager Provider types""" + + AWS = 'AWS_SECRETS_MANAGER' + GCP = 'GCP_SECRET_MANAGER' + + @classmethod + def has_value(cls, value): + return value in cls._value2member_map_ diff --git a/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/secret_manager/secret_manager_service.py b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/secret_manager/secret_manager_service.py new file mode 100644 index 0000000000..5c013091e7 --- /dev/null +++ b/gen-ai/orchestrator-server/src/main/python/server/src/gen_ai_orchestrator/utils/secret_manager/secret_manager_service.py @@ -0,0 +1,66 @@ +import logging +from typing import Optional + +from gen_ai_orchestrator.configurations.environment.settings import application_settings +from gen_ai_orchestrator.models.security.credentials import Credentials +from gen_ai_orchestrator.utils.aws.aws_secrets_manager_client import AWSSecretsManagerClient +from gen_ai_orchestrator.utils.gcp.gcp_secret_manager_client import GCPSecretManagerClient +from gen_ai_orchestrator.utils.secret_manager.secret_manager_provider import SecretManagerProvider +from gen_ai_orchestrator.utils.strings import obfuscate + +logger = logging.getLogger(__name__) + +# Define a mapping of secret manager providers to their corresponding client classes +secret_manager_provider_map = { + SecretManagerProvider.AWS.value: AWSSecretsManagerClient, + SecretManagerProvider.GCP.value: GCPSecretManagerClient +} + + +def fetch_default_vector_store_credentials() -> Optional[Credentials]: + """Fetch the Vector Store credentials.""" + if not application_settings.vector_store_credentials_secret_name: + return _get_credentials_from_env() + + secret_name = application_settings.vector_store_credentials_secret_name + secret_manager_provider = application_settings.vector_store_secret_manager_provider + + # Fetch the corresponding client based on the provider + secret_manager_client_class = secret_manager_provider_map.get(secret_manager_provider) + + if secret_manager_client_class: + logger.info(f'Using {secret_manager_provider} to get vector store credentials...') + secret_manager_client = secret_manager_client_class() + credentials = secret_manager_client.get_credentials(secret_name) + else: + credentials = _get_credentials_from_env() + + # Log whether credentials were successfully retrieved + if credentials: + logger.info("Credentials successfully retrieved.") + else: + logger.info("No credentials were found.") + + return credentials + +def _get_credentials_from_env() -> Optional[Credentials]: + """Fetch credentials from environment variables.""" + if application_settings.vector_store_user or application_settings.vector_store_pwd: + return Credentials( + username=application_settings.vector_store_user, + password=application_settings.vector_store_pwd + ) + return None + + +vector_store_credentials: Optional[Credentials] = fetch_default_vector_store_credentials() + +if vector_store_credentials is not None: + logger.info( + 'A default Vector Store is defined : [Provider=%s][Credentials=(user:%s, password:%s)]', + application_settings.vector_store_provider.value, + vector_store_credentials.username, + obfuscate(vector_store_credentials.password), + ) +else: + logger.warning('No default Vector Store is defined !') \ No newline at end of file diff --git a/gen-ai/orchestrator-server/src/main/python/server/tests/configurations/test_configurations.py b/gen-ai/orchestrator-server/src/main/python/server/tests/configurations/test_configurations.py index 164fc823fe..c6608ceda2 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/tests/configurations/test_configurations.py +++ b/gen-ai/orchestrator-server/src/main/python/server/tests/configurations/test_configurations.py @@ -12,11 +12,17 @@ # See the License for the specific language governing permissions and # limitations under the License. # -from gen_ai_orchestrator.configurations.environment.settings import fetch_open_search_credentials, _Settings +import os + +from gen_ai_orchestrator.configurations.environment.settings import _Settings, application_settings from gen_ai_orchestrator.configurations.logging.logger import setup_logging from gen_ai_orchestrator.models.security.credentials import Credentials from unittest.mock import patch +from gen_ai_orchestrator.models.vector_stores.vectore_store_provider import VectorStoreProvider +from gen_ai_orchestrator.utils.secret_manager.secret_manager_provider import SecretManagerProvider +from gen_ai_orchestrator.utils.secret_manager.secret_manager_service import fetch_default_vector_store_credentials + def test_environment(): """Test settings are read successfully""" @@ -30,32 +36,105 @@ def test_logging(): @patch('boto3.client') @patch('gen_ai_orchestrator.utils.aws.aws_secrets_manager_client.AWSSecretsManagerClient.get_credentials') -@patch('gen_ai_orchestrator.configurations.environment.settings.application_settings', - _Settings(open_search_aws_secret_manager_name='my_secret_key')) -def test_fetch_open_search_credentials(mock_get_credentials, mock_boto3_client): +@patch('gen_ai_orchestrator.utils.secret_manager.secret_manager_service.application_settings', + _Settings( + vector_store_provider = VectorStoreProvider.OPEN_SEARCH, + vector_store_host = None, + vector_store_port = None, + vector_store_user = None, + vector_store_pwd = None, + vector_store_database = None, + vector_store_secret_manager_provider = SecretManagerProvider.AWS, + vector_store_credentials_secret_name = 'my_secret_key' + ) +) +def test_fetch_aws_secret_credentials(mock_get_credentials, mock_boto3_client): # Test data - open_search_credentials = Credentials(username="user", password="pwd123456") + my_credentials = Credentials(username="user", password="pwd123456") # Configure the mocks to return specific values mock_boto3_client.return_value = None - mock_get_credentials.return_value = open_search_credentials + mock_get_credentials.return_value = my_credentials - - # Call the function to fetch aws secret key - username, password = fetch_open_search_credentials() + # Call the function to fetch the credentials of the default vector store + credentials = fetch_default_vector_store_credentials() # Check test results mock_boto3_client.assert_called_once_with(service_name='secretsmanager') - mock_get_credentials.assert_called_once_with(secret_name='my_secret_key') - assert username == open_search_credentials.username - assert password == open_search_credentials.password + mock_get_credentials.assert_called_once_with('my_secret_key') + assert credentials.username == my_credentials.username + assert credentials.password == my_credentials.password + +@patch('google.cloud.secretmanager.SecretManagerServiceClient') +@patch('gen_ai_orchestrator.utils.gcp.gcp_secret_manager_client.GCPSecretManagerClient.get_credentials') +@patch('gen_ai_orchestrator.utils.secret_manager.secret_manager_service.application_settings', + _Settings( + vector_store_provider = VectorStoreProvider.OPEN_SEARCH, + vector_store_host = None, + vector_store_port = None, + vector_store_user = None, + vector_store_pwd = None, + vector_store_database = None, + vector_store_secret_manager_provider = SecretManagerProvider.GCP, + vector_store_credentials_secret_name = 'my_secret_key' + ) +) +def test_fetch_gcp_secret_credentials(mock_get_credentials, mock_gcp_secretmanager_client): + # Test data + my_credentials = Credentials(username="user", password="pwd123456") + + # Configure the mocks to return specific values + mock_gcp_secretmanager_client.return_value = None + mock_get_credentials.return_value = my_credentials + + # Call the function to fetch the credentials of the default vector store + credentials = fetch_default_vector_store_credentials() + + # Check test results + mock_gcp_secretmanager_client.assert_called_once() + mock_get_credentials.assert_called_once_with('my_secret_key') + assert credentials.username == my_credentials.username + assert credentials.password == my_credentials.password + +@patch('boto3.client') +@patch('gen_ai_orchestrator.utils.aws.aws_secrets_manager_client.AWSSecretsManagerClient.get_credentials') +@patch('gen_ai_orchestrator.utils.secret_manager.secret_manager_service.application_settings', + _Settings( + vector_store_provider=None, + vector_store_host=None, + vector_store_port=None, + vector_store_user='default_user', + vector_store_pwd='default_pwd', + vector_store_database=None, + vector_store_secret_manager_provider=None, + vector_store_credentials_secret_name=None + )) +def test_fetch_default_credentials(mock_get_credentials, mock_boto3_client): + # Call the function to fetch the credentials of the default vector store + credentials = fetch_default_vector_store_credentials() + + # Check test results + assert not mock_boto3_client.called + assert not mock_get_credentials.called + assert credentials.username == 'default_user' + assert credentials.password == 'default_pwd' @patch('boto3.client') @patch('gen_ai_orchestrator.utils.aws.aws_secrets_manager_client.AWSSecretsManagerClient.get_credentials') -@patch('gen_ai_orchestrator.configurations.environment.settings.application_settings', - _Settings(open_search_aws_secret_manager_name='my_secret_key')) -def test_fetch_bad_open_search_credentials(mock_get_credentials, mock_boto3_client): +@patch('gen_ai_orchestrator.utils.secret_manager.secret_manager_service.application_settings', + _Settings( + vector_store_provider=VectorStoreProvider.OPEN_SEARCH, + vector_store_host=None, + vector_store_port=None, + vector_store_user=None, + vector_store_pwd=None, + vector_store_database=None, + vector_store_secret_manager_provider=SecretManagerProvider.AWS, + vector_store_credentials_secret_name='my_secret_key' + ) + ) +def test_fetch_bad_credentials(mock_get_credentials, mock_boto3_client): # Test data open_search_credentials = None @@ -63,27 +142,10 @@ def test_fetch_bad_open_search_credentials(mock_get_credentials, mock_boto3_clie mock_boto3_client.return_value = None mock_get_credentials.return_value = open_search_credentials - # Call the function to fetch aws secret key - username, password = fetch_open_search_credentials() + # Call the function to fetch the credentials of the default vector store + credentials = fetch_default_vector_store_credentials() # Check test results mock_boto3_client.assert_called_once_with(service_name='secretsmanager') - mock_get_credentials.assert_called_once_with(secret_name='my_secret_key') - assert username is None - assert password is None - - -@patch('boto3.client') -@patch('gen_ai_orchestrator.utils.aws.aws_secrets_manager_client.AWSSecretsManagerClient.get_credentials') -@patch('gen_ai_orchestrator.configurations.environment.settings.application_settings', - _Settings(open_search_user='default_user', open_search_pwd='default_pwd')) -def test_fetch_default_open_search_credentials(mock_get_credentials, mock_boto3_client): - # Call the function to fetch aws secret key - username, password = fetch_open_search_credentials() - - # Check test results - assert not mock_boto3_client.called - assert not mock_get_credentials.called - assert username == 'default_user' - assert password == 'default_pwd' - + mock_get_credentials.assert_called_once_with('my_secret_key') + assert credentials is None diff --git a/gen-ai/orchestrator-server/src/main/python/server/tests/services/test_langchain_factory.py b/gen-ai/orchestrator-server/src/main/python/server/tests/services/test_langchain_factory.py index 5b499df470..c269e2228f 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/tests/services/test_langchain_factory.py +++ b/gen-ai/orchestrator-server/src/main/python/server/tests/services/test_langchain_factory.py @@ -14,7 +14,6 @@ # import pytest -from langchain_community.embeddings import FakeEmbeddings from gen_ai_orchestrator.errors.exceptions.exceptions import ( GenAIUnknownProviderSettingException, @@ -22,7 +21,7 @@ from gen_ai_orchestrator.errors.exceptions.observability.observability_exceptions import \ GenAIUnknownObservabilityProviderSettingException from gen_ai_orchestrator.errors.exceptions.vector_store.vector_store_exceptions import \ - GenAIUnknownVectorStoreProviderException, GenAIUnknownVectorStoreProviderSettingException + GenAIUnknownVectorStoreProviderSettingException from gen_ai_orchestrator.models.em.azureopenai.azure_openai_em_setting import ( AzureOpenAIEMSetting, ) @@ -42,7 +41,8 @@ ) from gen_ai_orchestrator.models.observability.observability_provider import ObservabilityProvider from gen_ai_orchestrator.models.observability.observability_type import ObservabilitySetting -from gen_ai_orchestrator.models.vector_stores.vector_store_types import VectorStoreSetting +from gen_ai_orchestrator.models.vector_stores.open_search.open_search_setting import OpenSearchVectorStoreSetting +from gen_ai_orchestrator.models.vector_stores.pgvector.pgvector_setting import PGVectorStoreSetting from gen_ai_orchestrator.services.langchain.factories.callback_handlers.langfuse_callback_handler_factory import \ LangfuseCallbackHandlerFactory from gen_ai_orchestrator.services.langchain.factories.em.azure_openai_em_factory import ( @@ -68,6 +68,7 @@ from gen_ai_orchestrator.services.langchain.factories.vector_stores.open_search_factory import ( OpenSearchFactory, ) +from gen_ai_orchestrator.services.langchain.factories.vector_stores.pgvector_factory import PGVectorFactory def test_get_unknown_llm_factory(): @@ -192,7 +193,7 @@ def test_get_open_search_vector_store_factory(): ) ) open_search = get_vector_store_factory( - setting=VectorStoreSetting( + setting=OpenSearchVectorStoreSetting( **{ 'provider': 'OpenSearch', 'host': 'localhost', @@ -207,7 +208,25 @@ def test_get_open_search_vector_store_factory(): index_name='my-index-name', embedding_function=em_factory.get_embedding_model() ) + pgvector = get_vector_store_factory( + setting=PGVectorStoreSetting( + **{ + 'provider': 'PGVector', + 'host': 'localhost', + 'port': 5432, + 'password': { + 'type': 'Raw', + 'value': 'ab7***************************A1IV4B', + }, + 'username': 'postgres', + 'database': 'postgres' + } + ), + index_name='my-index-name', + embedding_function=em_factory.get_embedding_model() + ) assert isinstance(open_search, OpenSearchFactory) + assert isinstance(pgvector, PGVectorFactory) def test_get_unknown_vector_store_factory(): diff --git a/gen-ai/orchestrator-server/src/main/python/server/tests/utils/test_aws_secrets_manager_client.py b/gen-ai/orchestrator-server/src/main/python/server/tests/utils/test_aws_secrets_manager_client.py index 4fb9d14dc0..ecc68868a9 100644 --- a/gen-ai/orchestrator-server/src/main/python/server/tests/utils/test_aws_secrets_manager_client.py +++ b/gen-ai/orchestrator-server/src/main/python/server/tests/utils/test_aws_secrets_manager_client.py @@ -21,8 +21,8 @@ from gen_ai_orchestrator.models.security.credentials import Credentials from gen_ai_orchestrator.utils.aws.aws_secrets_manager_client import ( AWSSecretsManagerClient, - parse_secret_data, ) +from gen_ai_orchestrator.utils.secret_manager.secret_manager_client import parse_secret_data @patch('boto3.client') diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/README.md b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/README.md index d109c2b438..67e4483b4c 100644 --- a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/README.md +++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/README.md @@ -123,24 +123,29 @@ Recursively browse web URLs (follow links from these base URLs), then scrape lin #### index_documents.py -Index a ready-to-index CSV file ('title'|'url'|'text' lines) file contents into an OpenSearch vector database. +Index a ready-to-index CSV ('title'|'url'|'text' lines) file contents into a given vector database. ``` Usage: - index_documents.py [-v] [] + index_documents.py [-v] [] index_documents.py -h | --help index_documents.py --version Arguments: input_csv path to the ready-to-index file - index_name name of the OpenSearch index (shall follow indexes naming rules) - embeddings_cfg path to an embeddings configuration file (JSON format) (shall describe settings for one of OpenAI or AzureOpenAI embeddings model) + namespace the namespace + bot_id the bot ID + embeddings_json_config path to an embeddings configuration file (JSON format) + (shall describe settings for one of OpenAI or AzureOpenAI + embeddings model) + vector_store_json_config path to a vector store configuration file (JSON format) + (shall describe settings for one of OpenSearch or PGVector store) chunks_size size of the embedded chunks of documents Options: -h --help Show this screen --version Show version - -v Verbose output for debugging (without this option, script will be silent but for errors and the unique indexing session id) + -v Verbose output for debugging ``` Index a ready-to-index CSV file contents into an OpenSearch vector database. @@ -159,20 +164,39 @@ Documents will be indexed in OpenSearch DB under index_name index (index_name sh | title | the 'title' column from original input CSV | | url | the 'url' column from original input CSV | -A unique indexing session id is produced and printed to the console (will be the last line printed if the '-v' option is used). - -## OpenSearch Configuration - -To configure the OpenSearch vector store, you can use the following environment variables: - -| Variables | Description | Default | -|--------------------------------------------------------------|-------------------------------------------------------------------------------------|-------------| -| tock_gen_ai_orchestrator_open_search_host | The OpenSearch host | 'localhost' | -| tock_gen_ai_orchestrator_open_search_port | The OpenSearch port | '9200' | -| tock_gen_ai_orchestrator_open_search_aws_secret_manager_name | The optional AWS secret name that store the OpenSearch user credentials | None | -| chtock_gen_ai_orchestrator_open_search_user | The OpenSearch user (Raw value) | 'admin' | -| tock_gen_ai_orchestrator_open_search_pwd | The OpenSearch password (Raw value) | 'admin' | -| tock_gen_ai_orchestrator_open_search_timeout | Request timeout: set the maximum time (in seconds) for the request to be completed. | '4' | +#### Sample result: +
+------------------- Indexing details ----------------------------------------------------------
+                 Index name : ns-03-bot-cmso-session-b2bbb74a-1439-499d-a621-0f4b6bff0491
+           Index session ID : b2bbb74a-1439-499d-a621-0f4b6bff0491
+        Documents extracted : 391 (Docs)
+          Documents chunked : 391 (Chunks)
+                 Chunk size : 20000 (Characters)
+                  Input csv : cmso_full_06062024.csv
+   Embeddings configuration : embeddings_azure_openai_settings.json
+ Vector Store configuration : vector_store_opensearch_settings.json
+                   Duration : 39.34 seconds
+                       Date : 2024-09-10 16:29:54
+-----------------------------------------------------------------------------------------------
+
+ +## Default Vector Store Configuration + +To configure the default vector store, you can use the following environment variables: + +| Variables | Description | Default | List of values | +|------------------------------------------------------------------|-------------------------------------------------------------------|-------------------------------|---------------------------------------------| +| `tock_gen_ai_orchestrator_application_environment` | Application environment | `DEV` | `DEV`, `PROD` | +| `tock_gen_ai_orchestrator_em_provider_timeout` | Embeddings request timeout (in seconds) | 120 | Integer | +| `tock_gen_ai_orchestrator_vector_store_provider` | Vector Store Provider | `OpenSearch` | `OpenSearch`, `PGVector` | +| `tock_gen_ai_orchestrator_vector_store_host` | Vector Store host | 'localhost' | String | +| `tock_gen_ai_orchestrator_vector_store_port` | Vector Store port | '9200' | Integer | +| `tock_gen_ai_orchestrator_vector_store_user` | Vector Store user | 'admin' | String | +| `tock_gen_ai_orchestrator_vector_store_pwd` | Vector Store password | 'admin' | String | +| `tock_gen_ai_orchestrator_vector_store_database` | Vector Store database name (Only if necessary. Example: PGVector) | Null | String | +| `tock_gen_ai_orchestrator_vector_store_test_query` | Query used to test the Vector Store | 'What knowledge do you have?' | String | +| `tock_gen_ai_orchestrator_vector_store_secret_manager_provider` | Secret Manager Provider | `AWS_SECRETS_MANAGER` | `AWS_SECRETS_MANAGER`, `GCP_SECRET_MANAGER` | +| `tock_gen_ai_orchestrator_vector_store_credentials_secret_name` | Secret name storing credentials | Null | String | ## Testing RAG settings on dataset diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/embeddings_azure_openai_settings.example.json b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/examples/embeddings_azure_openai_settings.example.json similarity index 100% rename from gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/embeddings_azure_openai_settings.example.json rename to gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/examples/embeddings_azure_openai_settings.example.json diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/embeddings_openai_settings.example.json b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/examples/embeddings_openai_settings.example.json similarity index 100% rename from gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/embeddings_openai_settings.example.json rename to gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/examples/embeddings_openai_settings.example.json diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/examples/vector_store_opensearch_settings.example.json b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/examples/vector_store_opensearch_settings.example.json new file mode 100644 index 0000000000..fb327d9894 --- /dev/null +++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/examples/vector_store_opensearch_settings.example.json @@ -0,0 +1,10 @@ +{ + "provider": "OpenSearch", + "host": "localhost", + "port": 9200, + "username": "admin", + "password": { + "type": "Raw", + "value": "admin" + } +} \ No newline at end of file diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/examples/vector_store_pgvector_settings.example.json b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/examples/vector_store_pgvector_settings.example.json new file mode 100644 index 0000000000..0ae3506b4e --- /dev/null +++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/examples/vector_store_pgvector_settings.example.json @@ -0,0 +1,11 @@ +{ + "provider": "PGVector", + "host": "127.0.0.1", + "port": 5432, + "username": "postgres", + "password": { + "type": "Raw", + "value": "postgres" + }, + "database": "postgres" +} \ No newline at end of file diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/index_documents.py b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/index_documents.py index fea4d34d36..d0b7acf45a 100644 --- a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/index_documents.py +++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/index_documents.py @@ -12,75 +12,73 @@ # See the License for the specific language governing permissions and # limitations under the License. # -"""Index a ready-to-index CSV file ('title'|'url'|'text' lines) file contents -into an OpenSearch vector database. +"""Index a ready-to-index CSV ('title'|'url'|'text' lines) file contents into a given vector database. Usage: - index_documents.py [-v] [] + index_documents.py [-v] [] index_documents.py -h | --help index_documents.py --version Arguments: input_csv path to the ready-to-index file - index_name name of the OpenSearch index (shall follow indexes - naming rules) - embeddings_cfg path to an embeddings configuration file (JSON format) + namespace the namespace + bot_id the bot ID + embeddings_json_config path to an embeddings configuration file (JSON format) (shall describe settings for one of OpenAI or AzureOpenAI embeddings model) + vector_store_json_config path to a vector store configuration file (JSON format) + (shall describe settings for one of OpenSearch or PGVector store) chunks_size size of the embedded chunks of documents Options: -h --help Show this screen --version Show version - -v Verbose output for debugging (without this option, script will - be silent but for errors and the unique indexing session id) + -v Verbose output for debugging Index a ready-to-index CSV file contents into an OpenSearch vector database. CSV columns are 'title'|'url'|'text'. 'text' will be chunked according to -chunks_size, and embedded using configuration described in embeddings_cfg (it +chunks_size, and embedded using configuration described in embeddings_json_config (it uses the embeddings constructor from the orchestrator module, so JSON file -shall follow corresponding format). Documents will be indexed in OpenSearch DB -under index_name index (index_name shall follow OpenSearch naming restrictions). -A unique indexing session id is produced and printed to the console (will be -the last line printed if the '-v' option is used). +shall follow corresponding format). Documents will be indexed in a vector store (vector_store_json_config) +under index_name index (index_name is generated following the naming restrictions of the vector store, +example for OpenSearch : ns-{namespace}-bot-{bot_id}-session-{uuid4}) +This The index_name is unique and will be printed to the console at the end of successful execution """ +import asyncio import csv import json import logging +import re import sys from datetime import datetime from pathlib import Path -from typing import Iterable +from typing import List from uuid import uuid4 +import humanize import pandas as pd from docopt import docopt -from gen_ai_orchestrator.models.em.ollama.ollama_em_setting import OllamaEMSetting -from langchain.embeddings.base import Embeddings -from langchain.text_splitter import RecursiveCharacterTextSplitter -from langchain_community.document_loaders.dataframe import DataFrameLoader -from langchain_core.documents import Document - -from gen_ai_orchestrator.models.em.azureopenai.azure_openai_em_setting import ( - AzureOpenAIEMSetting, -) +from gen_ai_orchestrator.models.em.azureopenai.azure_openai_em_setting import AzureOpenAIEMSetting from gen_ai_orchestrator.models.em.em_provider import EMProvider from gen_ai_orchestrator.models.em.em_setting import BaseEMSetting -from gen_ai_orchestrator.models.em.openai.openai_em_setting import ( - OpenAIEMSetting, -) -from gen_ai_orchestrator.models.vector_stores.vectore_store_provider import ( - VectorStoreProvider, -) +from gen_ai_orchestrator.models.em.openai.openai_em_setting import OpenAIEMSetting +from gen_ai_orchestrator.models.vector_stores.open_search.open_search_setting import OpenSearchVectorStoreSetting +from gen_ai_orchestrator.models.vector_stores.pgvector.pgvector_setting import PGVectorStoreSetting +from gen_ai_orchestrator.models.vector_stores.vector_store_setting import BaseVectorStoreSetting +from gen_ai_orchestrator.models.vector_stores.vectore_store_provider import VectorStoreProvider from gen_ai_orchestrator.services.langchain.factories.langchain_factory import ( get_em_factory, get_vector_store_factory, ) +from langchain.text_splitter import RecursiveCharacterTextSplitter +from langchain_community.document_loaders.dataframe import DataFrameLoader +from langchain_core.documents import Document # Define the size of the csv field -> Set to maximum to process large csvs csv.field_size_limit(sys.maxsize) -def index_documents(args): + +async def index_documents(args): """ Read a ready-to-index CSV file, then index its contents to an OpenSearch DB. @@ -88,30 +86,33 @@ def index_documents(args): args (dict): A dictionary containing command-line arguments. Expecting keys: '' - '' - '' + '' + '' + '' + '' '' Returns: The indexing session unique id. """ # unique date / uuid for each indexing session (stored as metadata) - start_time = datetime.now() - formatted_datetime = start_time.strftime('%Y-%m-%d %H:%M:%S') - session_uuid = uuid4() + session_uuid = str(uuid4()) logging.debug( f"Beginning indexation session {session_uuid} at '{formatted_datetime}'" ) logging.debug(f"Read input CSV file {args['']}") df = pd.read_csv(args[''], delimiter='|', quotechar='"', names=['title', 'source', 'text']) + # Prevent NaN value in the 'source' column with a default value 'UNKNOWN', then replace it with None + df['source'] = df['source'].fillna('UNKNOWN') + df['source'] = df['source'].replace('UNKNOWN', None) loader = DataFrameLoader(df, page_content_column='text') docs = loader.load() for doc in docs: doc.metadata['index_session_id'] = session_uuid doc.metadata['index_datetime'] = formatted_datetime - doc.metadata['id'] = uuid4() # A uuid for the doc (will be used by TOCK) + doc.metadata['id'] = str(uuid4()) # An uuid for the doc (will be used by TOCK) logging.debug(f"Split texts in {args['']} characters-sized chunks") # recursive splitter is used to preserve sentences & paragraphs @@ -124,34 +125,77 @@ def index_documents(args): # Add title to text (for better semantic search) splitted_docs = add_title_to_text(splitted_docs=splitted_docs) - logging.debug(f"Get embeddings model from {args['']} config file") - with open(args[''], 'r') as file: - config_dict = json.load(file) - em_settings = em_settings_from_config(config_dict) + logging.debug(f"Get embeddings model from {args['']} config file") + with open(Path(args['']), 'r') as json_file: + config_dict = json.load(json_file) + em_settings = load_setting( + data=config_dict, + provider_mapping={ + EMProvider.OPEN_AI: OpenAIEMSetting, + EMProvider.AZURE_OPEN_AI_SERVICE: AzureOpenAIEMSetting + }, + base_class=BaseEMSetting + ) + + logging.debug(f"Get vector store from {args['']} config file") + with open(Path(args['']), 'r') as json_file: + config_dict = json.load(json_file) + vector_store_settings = load_setting( + data=config_dict, + provider_mapping={ + VectorStoreProvider.OPEN_SEARCH: OpenSearchVectorStoreSetting, + VectorStoreProvider.PGVECTOR: PGVectorStoreSetting + }, + base_class=BaseVectorStoreSetting + ) # Use embeddings factory from orchestrator em_factory = get_em_factory(em_settings) - + await em_factory.check_embedding_model_setting() embeddings = em_factory.get_embedding_model() - # Index all chunks in vector DB - embed_and_store_docs( - splitted_docs, embeddings=embeddings, index_name=args[''] - ) + # generating index name + index_name = normalize_index_name(vector_store_settings.provider, args[''], args[''], session_uuid) - # Print statistics - duration = datetime.now() - start_time - logging.debug( - f"Indexed {len(splitted_docs)} chunks in '{args['']}' from {len(docs)} lines in '{args['']}' (duration: {duration})" + vector_store_factory = get_vector_store_factory( + setting=vector_store_settings, + index_name=index_name, + embedding_function=embeddings ) + await vector_store_factory.check_vector_store_connection() + vector_store = vector_store_factory.get_vector_store() - # Return session index uuid to main script - return session_uuid + await embedding_and_indexing(splitted_docs, vector_store) + + # Return indexing details + return index_name, session_uuid, len(docs), len(splitted_docs) + + +async def embedding_and_indexing(splitted_docs: List[Document], vector_store): + # Index all chunks in vector DB + logging.debug('Index chunks in DB') + # Index respecting bulk_size (500 is from_documents current default: it is described for clarity only) + bulk_size = 500 + for i in range(0, len(splitted_docs), bulk_size): + logging.debug(f'i={i}, splitted_docs={len(splitted_docs)}') + await vector_store.aadd_documents(documents=splitted_docs[i: i + bulk_size], bulk_size=bulk_size) + + +def load_setting(data: dict, provider_mapping: dict, base_class): + """Function to load and instantiate the right class according to the provider""" + base_setting = base_class(**data) + provider = base_setting.provider + setting_class = provider_mapping.get(provider) + + if setting_class: + return setting_class(**data) + else: + raise ValueError(f"Unknown Provider {provider}.") def generate_ids_for_each_chunks( - splitted_docs: Iterable[Document], -) -> Iterable[Document]: + splitted_docs: List[Document], +) -> List[Document]: """Add chunk id ('n/N') to the documents' metadata using Pandas.""" metadata = [doc.metadata for doc in splitted_docs] df_metadata = pd.DataFrame(metadata) @@ -168,8 +212,8 @@ def generate_ids_for_each_chunks( def add_title_to_text( - splitted_docs: Iterable[Document], -) -> Iterable[Document]: + splitted_docs: List[Document], +) -> List[Document]: """ Add 'title' from metadata to Document's page_content for better semantic search. @@ -184,65 +228,55 @@ def add_title_to_text( return splitted_docs -def em_settings_from_config(setting_dict: dict) -> BaseEMSetting: - """Get embeddings settings from config dict.""" - # Create settings class according to embeddings provider from config file - em_settings = None - if config_dict['provider'] == EMProvider.OPEN_AI: - em_settings = OpenAIEMSetting(**setting_dict) - elif config_dict['provider'] == EMProvider.AZURE_OPEN_AI_SERVICE: - em_settings = AzureOpenAIEMSetting(**setting_dict) - elif config_dict['provider'] == EMProvider.OLLAMA: - em_settings = OllamaEMSetting(**setting_dict) +def normalize_index_name(provider: VectorStoreProvider, namespace: str, bot_id: str, index_session_id: str) -> str: + if VectorStoreProvider.OPEN_SEARCH == provider : + return normalize_opensearch_index_name(namespace, bot_id, index_session_id) - return em_settings + if VectorStoreProvider.PGVECTOR == provider: + return normalize_pgvector_index_name(namespace, bot_id, index_session_id) + raise ValueError(f"Unknown Provider {provider}.") -def embed_and_store_docs( - documents: Iterable[Document], embeddings: Embeddings, index_name: str -) -> None: - """ Embed all chunks in vector database.""" - logging.debug('Index chunks in DB') - # Use vector store factory from orchestrator - vectorstore_factory = get_vector_store_factory( - None, # Default vector store is OpenSearch and created base on environment variables, see tooling README.md - embedding_function=embeddings, - index_name=index_name, - ) - opensearch_db = vectorstore_factory.get_vector_store() - # Index respecting bulk_size (500 is from_documents current default: it is described for clarity only) - bulk_size = 500 - for i in range(0, len(documents), bulk_size): - logging.debug(f'i={i}, splitted_docs={len(documents)}') - opensearch_db.add_documents( - documents=documents[i : i + bulk_size], bulk_size=bulk_size - ) +def normalize_pgvector_index_name(namespace: str, bot_id: str, index_session_id: str) -> str: + """ + Normalize the document index name, base on PGVector rules. + Same treatment as tock/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/utils/PGVectorUtils.kt#normalizeDocumentIndexName() + """ + + # Convert to lowercase + normalized = f"ns-{namespace}-bot-{bot_id}-session-{index_session_id}".lower() + + # Replace invalid characters with underscores + normalized = re.sub(r'[^a-z0-9_]', '_', normalized) + + # Ensure the name starts with a letter or underscore + if not re.match(r'^[a-z_]', normalized): + normalized = f"_{normalized}" + return normalized -def index_name_is_valid(index_name: str) -> bool: +def normalize_opensearch_index_name(namespace: str, bot_id: str, index_session_id: str) -> str: """ - Check if index_name is a valid OpenSearch index name. - (https://opensearch.org/docs/latest/api-reference/index-apis/create-index) + Normalize the document index name, base on OpenSearch rules. + Same treatment as tock/gen-ai/orchestrator-core/src/main/kotlin/ai/tock/genai/orchestratorcore/utils/OpenSearchUtils.kt#normalizeDocumentIndexName() """ - if not index_name.islower(): - logging.error('Index name must be all lowercase') - return False - if index_name.startswith('_') or index_name.startswith('-'): - logging.error('Index names can’t begin with underscores (_) or hyphens (-)') - return False + # Convert to lowercase + normalized = f"ns-{namespace}-bot-{bot_id}-session-{index_session_id}".lower() - # List of invalid characters - invalid_chars = [':', '"', '*', '+', '/', '\\', '|', '?', '#', '>', '<', ',', ' '] - for char in invalid_chars: - if char in index_name: - logging.error(f'Index name contains invalid character: {char}') - return False + # Replace underscores and spaces with hyphens + normalized = normalized.replace('_', '-').replace(' ', '-') - return True + # Remove invalid characters + invalid_characters = {' ', ',', ':', '"', '*', '+', '/', '\\', '|', '?', '#', '>', '<'} + normalized = ''.join(c for c in normalized if c not in invalid_characters) + return normalized if __name__ == '__main__': + start_time = datetime.now() + formatted_datetime = start_time.strftime('%Y-%m-%d %H:%M:%S') + cli_args = docopt(__doc__, version='Webscraper 0.1.0') # Set logging level @@ -252,44 +286,21 @@ def index_name_is_valid(index_name: str) -> bool: ) # Check args: - # - input file path - inputfile_path = Path(cli_args['']) - if not inputfile_path.exists(): - logging.error( - f"Cannot proceed: input CSV file '{cli_args['']}' does not exist" - ) - sys.exit(1) + for file_path in ['input_csv', 'embeddings_json_config', 'vector_store_json_config']: + if not Path(cli_args[f'<{file_path}>']).exists(): + logging.error(f"Cannot proceed: this file {cli_args[f'<{file_path}>']} does not exist") + sys.exit(1) + + for json_file_path in ['embeddings_json_config', 'vector_store_json_config']: + try: + with open(Path(cli_args[f'<{json_file_path}>'])) as file: + json.load(file) + except json.JSONDecodeError: + logging.error( + f"Cannot proceed: this file '{cli_args[f'<{json_file_path}>']}' is not a valid JSON file" + ) + sys.exit(1) - # - index name - # could be checked via factory in a future version - if not index_name_is_valid(cli_args['']): - logging.error( - f"Cannot proceed: index name {cli_args['']} is not a valid OpenSearch index name" - ) - sys.exit(1) - - # - embeddings config JSON file - cfg_file_path = Path(cli_args['']) - if not cfg_file_path.exists(): - logging.error( - f"Cannot proceed: embeddings config file '{cli_args['']}' does not exist" - ) - sys.exit(1) - try: - with open(cfg_file_path, 'r') as file: - config_dict = json.load(file) - except json.JSONDecodeError: - logging.error( - f"Cannot proceed: embeddings config file '{cli_args['']}' is not a valid JSON file" - ) - sys.exit(1) - if not EMProvider.has_value(config_dict['provider']): - logging.error( - f"Cannot proceed: embeddings config file references an unknown embedding model : '{config_dict['provider']}'" - ) - sys.exit(1) - - # - chunks size try: int(cli_args['']) except ValueError: @@ -299,7 +310,27 @@ def index_name_is_valid(index_name: str) -> bool: sys.exit(1) # Main func - indexing_session_uuid = index_documents(cli_args) + index_name, indexing_session_uuid, documents_count, chunks_count = asyncio.run(index_documents(cli_args)) + + # Print statistics + duration = datetime.now() - start_time + logging.debug( + f"Indexed {chunks_count} chunks in '{index_name}' from {documents_count} documents (csv line) in '{cli_args['']}' (duration: {duration})" + ) # Print indexation session's unique id - print(indexing_session_uuid) + logging.info( + f""" +------------------- Indexing details ---------------------- + Index name : {index_name} + Index session ID : {indexing_session_uuid} + Documents extracted : {documents_count} (Docs) + Documents chunked : {chunks_count} (Chunks) + Chunk size : {cli_args['']} (Characters) + Input csv : {cli_args['']} + Embeddings configuration : {cli_args['']} + Vector Store configuration : {cli_args['']} + Duration : {humanize.precisedelta(duration)} + Date : {datetime.now().strftime("%Y-%m-%d %H:%M:%S")} +------------------------------------------------------------ + """) \ No newline at end of file diff --git a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/poetry.lock b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/poetry.lock index 5278125fce..7ed9201147 100644 --- a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/poetry.lock +++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/poetry.lock @@ -13,102 +13,102 @@ files = [ [[package]] name = "aiohttp" -version = "3.10.8" +version = "3.10.9" description = "Async http client/server framework (asyncio)" optional = false python-versions = ">=3.8" files = [ - {file = "aiohttp-3.10.8-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:a1ba7bc139592339ddeb62c06486d0fa0f4ca61216e14137a40d626c81faf10c"}, - {file = "aiohttp-3.10.8-cp310-cp310-macosx_10_9_x86_64.whl", hash = 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b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/pyproject.toml index 707d0cc992..c5dddb3892 100644 --- a/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/pyproject.toml +++ b/gen-ai/orchestrator-server/src/main/python/tock-llm-indexing-tools/pyproject.toml @@ -5,23 +5,26 @@ description = "Tools to index data from different sources to TOCK RAG vector DB" authors = ["Pierre Guirriec "] license = "Apache 2.0" readme = "README.md" +package-mode = false [tool.poetry.dependencies] -python = "^3.9" +python = "^3.10" docopt-ng = "^0.9.0" pandas = "^2.2.1" openpyxl = "^3.1.2" beautifulsoup4 = "^4.12.2" -langchain = "^0.1.0" -langsmith = "^0.1.41" +langchain = "^0.3.2" +langsmith = "^0.1.132" python-dotenv = "^1.0.0" opensearch-py = "^2.4.2" gen_ai_orchestrator = {path = "../server"} -langchain-community = "^0.0.29" +langchain-community = "^0.3.1" pre-commit = "^3.7.1" aiometer = "^0.5.0" -aiohttp = "^3.9.5" -aiohttp-socks = "^0.8.4" +aiohttp = "^3.10.9" 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