Deprecated API

Contents

• Terminally Deprecated
• Packages
• Interfaces
• Classes
• Enum Classes
• Annotation Interfaces
• Methods
• Constructors
• Enum Constants

Terminally Deprecated Elements

Element	Description
dev.langchain4j.data.document.parser.apache.tika.ApacheTikaDocumentParser(Supplier<Parser>, Supplier<ContentHandler>, Supplier<Metadata>, Supplier<ParseContext>)	Use the constructor with suppliers for Tika components if you intend to use this parser for multiple files and specify whether to include metadata or not.
dev.langchain4j.data.document.parser.apache.tika.ApacheTikaDocumentParser(Parser, ContentHandler, Metadata, ParseContext)	Use the constructor with suppliers for Tika components if you intend to use this parser for multiple files.
dev.langchain4j.guardrail.JsonExtractorOutputGuardrail	This class has been moved to the `langchain4j-guardrails` module and will be removed in a future release. * Add a dependency on `dev.langchain4j:langchain4j-guardrails` and use the class from that module instead.
dev.langchain4j.internal.InternalStreamingChatResponseHandlerUtils.onPartialResponse(StreamingChatResponseHandler, String)	Use InternalStreamingChatResponseHandlerUtils.onPartialResponse(StreamingChatResponseHandler, String, StreamingHandle) instead.
dev.langchain4j.internal.InternalStreamingChatResponseHandlerUtils.onPartialThinking(StreamingChatResponseHandler, String)	Use InternalStreamingChatResponseHandlerUtils.onPartialThinking(StreamingChatResponseHandler, String, StreamingHandle) instead.
dev.langchain4j.internal.InternalStreamingChatResponseHandlerUtils.onPartialToolCall(StreamingChatResponseHandler, PartialToolCall)	Use InternalStreamingChatResponseHandlerUtils.onPartialToolCall(StreamingChatResponseHandler, PartialToolCall, StreamingHandle) instead.
dev.langchain4j.mcp.client.transport.http.HttpMcpTransport
dev.langchain4j.mcp.registryclient.McpRegistryClient.getServerDetails(String)	This method is not supported on the official MCP registry anymore.
dev.langchain4j.mcp.registryclient.model.McpOfficialMeta.getServerId()	This field was removed in the 2025-09-29 version of the schema.
dev.langchain4j.mcp.registryclient.model.McpServer.getStatus()	This field was moved to the McpOfficialMeta object in schema version 2025-09-29
dev.langchain4j.model.anthropic.internal.api.AnthropicCreateMessageRequest(String, List<AnthropicMessage>, List<AnthropicTextContent>, int, List<String>, boolean, Double, Double, Integer, List<AnthropicTool>, AnthropicToolChoice, AnthropicThinking, AnthropicMetadata)
dev.langchain4j.model.anthropic.internal.api.AnthropicTool(String, String, AnthropicToolSchema, AnthropicCacheControl)	please use AnthropicTool(Builder) instead
dev.langchain4j.model.cohere.CohereEmbeddingModel(String, String, String, String, Duration, Boolean, Boolean, Integer)
dev.langchain4j.model.cohere.CohereEmbeddingModel.withApiKey(String)	Please use builder() instead, and explicitly set the model name and, if necessary, other parameters.
dev.langchain4j.model.cohere.CohereScoringModel(String, String, String, Duration, Integer, Proxy, Boolean, Boolean)
dev.langchain4j.model.cohere.CohereScoringModel.withApiKey(String)	Please use builder() instead, and explicitly set the model name and, if necessary, other parameters.
dev.langchain4j.model.github	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.github.GitHubModelsChatModel	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.github.GitHubModelsChatModelName	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.github.GitHubModelsEmbeddingModel	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.github.GitHubModelsEmbeddingModelName	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.github.GitHubModelsStreamingChatModel	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.github.spi.GitHubModelsChatModelBuilderFactory	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.github.spi.GitHubModelsEmbeddingModelBuilderFactory	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.github.spi.GitHubModelsStreamingChatModelBuilderFactory	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.huggingface.client.HuggingFaceClient.chat(TextGenerationRequest)
dev.langchain4j.model.huggingface.client.HuggingFaceClient.generate(TextGenerationRequest)
dev.langchain4j.model.huggingface.client.Parameters
dev.langchain4j.model.huggingface.client.TextGenerationRequest
dev.langchain4j.model.huggingface.client.TextGenerationResponse
dev.langchain4j.model.huggingface.HuggingFaceChatModel	Please use OpenAiChatModel from the langchain4j-open-ai module instead: ChatModel model = OpenAiChatModel.builder() .apiKey(System.getenv("HF_API_KEY")) .baseUrl("https://router.huggingface.co/v1") .modelName("HuggingFaceTB/SmolLM3-3B:hf-inference") .build();
dev.langchain4j.model.huggingface.HuggingFaceLanguageModel	Please use OpenAiChatModel from the langchain4j-open-ai module instead: ChatModel model = OpenAiChatModel.builder() .apiKey(System.getenv("HF_API_KEY")) .baseUrl("https://router.huggingface.co/v1") .modelName("HuggingFaceTB/SmolLM3-3B:hf-inference") .build();
dev.langchain4j.model.huggingface.HuggingFaceModelName
dev.langchain4j.model.huggingface.spi.HuggingFaceChatModelBuilderFactory
dev.langchain4j.model.huggingface.spi.HuggingFaceLanguageModelBuilderFactory
dev.langchain4j.model.jina.JinaEmbeddingModel(String, String, String, Duration, Integer, Boolean, Boolean, Boolean)
dev.langchain4j.model.jina.JinaScoringModel(String, String, String, Duration, Integer, Boolean, Boolean)
dev.langchain4j.model.localai.LocalAiChatModel(String, String, Double, Double, Integer, Duration, Integer, Boolean, Boolean)
dev.langchain4j.model.localai.LocalAiEmbeddingModel(String, String, Duration, Integer, Boolean, Boolean)
dev.langchain4j.model.localai.LocalAiLanguageModel(String, String, Double, Double, Integer, Duration, Integer, Boolean, Boolean)
dev.langchain4j.model.localai.LocalAiStreamingChatModel(String, String, Double, Double, Integer, Duration, Boolean, Boolean)
dev.langchain4j.model.localai.LocalAiStreamingLanguageModel(String, String, Double, Double, Integer, Duration, Boolean, Boolean)
dev.langchain4j.model.nomic.NomicEmbeddingModel(String, String, String, String, Integer, Duration, Integer, Boolean, Boolean)
dev.langchain4j.model.ovhai.internal.api.EmbeddingRequest	use EmbeddingRequest from langchain4j-open-ai module instead
dev.langchain4j.model.ovhai.internal.api.EmbeddingResponse	use EmbeddingResponse from langchain4j-open-ai module instead
dev.langchain4j.model.ovhai.internal.client.DefaultOvhAiClient	Do not use anymore, use langchain4j-open-ai module instead
dev.langchain4j.model.ovhai.internal.client.OvhAiClient	Do not use anymore, use langchain4j-open-ai module instead
dev.langchain4j.model.ovhai.internal.client.OvhAiClientBuilderFactory	Do not use anymore, use langchain4j-open-ai module instead
dev.langchain4j.model.ovhai.OvhAiEmbeddingModel	use OpenAiEmbeddingModel from langchain4j-open-ai module instead
dev.langchain4j.model.ovhai.OvhAiEmbeddingModel.withApiKey(String)	Please use builder() instead, and explicitly set the baseUrl and, if necessary, other parameters. The default value for baseUrl will be removed in future releases!
dev.langchain4j.model.vertexai.gemini.VertexAiGeminiChatModel(String, String, String, Float, Integer, Integer, Float, Integer, Integer, String, Schema, Map<HarmCategory, SafetyThreshold>, Boolean, String, ToolCallingMode, List<String>, Boolean, Boolean, List<ChatModelListener>, Set<Capability>)	please use VertexAiGeminiChatModel(VertexAiGeminiChatModelBuilder) instead
dev.langchain4j.model.vertexai.gemini.VertexAiGeminiStreamingChatModel(String, String, String, Float, Integer, Integer, Float, String, Schema, Map<HarmCategory, SafetyThreshold>, Boolean, String, ToolCallingMode, List<String>, Boolean, Boolean, List<ChatModelListener>, Map<String, String>, Executor)	please use VertexAiGeminiStreamingChatModel(VertexAiGeminiStreamingChatModelBuilder) instead
dev.langchain4j.model.vertexai.VertexAiChatModel(String, String, String, String, String, Double, Integer, Integer, Double, Integer)	Please use VertexAiChatModel(Builder) instead
dev.langchain4j.model.vertexai.VertexAiEmbeddingModel(String, String, String, String, String, Integer, Integer, Integer, VertexAiEmbeddingModel.TaskType, String, Integer, Boolean)	Please use VertexAiEmbeddingModel(Builder) instead
dev.langchain4j.model.voyageai.VoyageAiEmbeddingModel(HttpClientBuilder, Map<String, String>, String, Duration, Integer, String, String, String, Boolean, String, Boolean, Boolean, Integer)
dev.langchain4j.model.voyageai.VoyageAiScoringModel(HttpClientBuilder, Map<String, String>, String, Duration, Integer, String, String, Integer, Boolean, Boolean, Boolean)
dev.langchain4j.rag.content.retriever.azure.cosmos.nosql.AzureCosmosDBNoSqlContentRetriever(String, AzureKeyCredential, TokenCredential, EmbeddingModel, String, String, String, IndexingPolicy, CosmosVectorEmbeddingPolicy, CosmosFullTextPolicy, Integer, AzureCosmosDBSearchQueryType, Integer, Double, Filter)
dev.langchain4j.rag.content.retriever.elasticsearch.ElasticsearchContentRetriever(ElasticsearchConfiguration, RestClient, String, EmbeddingModel, int, double, Filter)	Use ElasticsearchContentRetriever(ElasticsearchConfiguration, ElasticsearchClient, String, EmbeddingModel, int, double, Filter) instead.
dev.langchain4j.rag.content.retriever.elasticsearch.ElasticsearchContentRetriever.Builder.restClient(RestClient)	Use ElasticsearchContentRetriever.Builder.client(ElasticsearchClient) instead.
dev.langchain4j.store.embedding.chroma.ChromaEmbeddingStore(String, String, Duration, boolean, boolean)	Only works with the V1 API, use the ChromaEmbeddingStore(Builder) constructor instead.
dev.langchain4j.store.embedding.elasticsearch.AbstractElasticsearchEmbeddingStore.initialize(ElasticsearchConfiguration, RestClient, String)	Use now AbstractElasticsearchEmbeddingStore.initialize(ElasticsearchConfiguration, ElasticsearchClient, String)
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore(ElasticsearchConfiguration, String, String, String, String, String)	by ElasticsearchEmbeddingStore(ElasticsearchConfiguration, ElasticsearchClient, String)
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore(ElasticsearchConfiguration, String, String, String, String, String, Integer)	by ElasticsearchEmbeddingStore(ElasticsearchConfiguration, RestClient, String)
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore(ElasticsearchConfiguration, RestClient, String)	by ElasticsearchEmbeddingStore(ElasticsearchConfiguration, ElasticsearchClient, String)
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore.Builder.apiKey(String)	call ElasticsearchEmbeddingStore.Builder.restClient(RestClient) instead
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore.Builder.dimension(Integer)	dimension is not used anymore.
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore.Builder.password(String)	call ElasticsearchEmbeddingStore.Builder.restClient(RestClient) instead
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore.Builder.restClient(RestClient)	Use ElasticsearchEmbeddingStore.Builder.client(ElasticsearchClient) instead.
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore.Builder.serverUrl(String)	call ElasticsearchEmbeddingStore.Builder.restClient(RestClient) instead
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore.Builder.userName(String)	call ElasticsearchEmbeddingStore.Builder.restClient(RestClient) instead
dev.langchain4j.store.embedding.hibernate.Embedding	In favor of EmbeddingVector to avoid naming collisions
dev.langchain4j.store.embedding.pinecone.PineconeEmbeddingStore.Builder.environment(String)	Please use PineconeEmbeddingStore.Builder.createIndex(PineconeIndexConfig)
dev.langchain4j.store.embedding.pinecone.PineconeEmbeddingStore.Builder.projectId(String)	Please use PineconeEmbeddingStore.Builder.createIndex(PineconeIndexConfig)

Deprecated Packages

Package	Description
dev.langchain4j.model.github	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.

Deprecated Interfaces

Interface	Description
dev.langchain4j.model.github.spi.GitHubModelsChatModelBuilderFactory	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.github.spi.GitHubModelsEmbeddingModelBuilderFactory	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.github.spi.GitHubModelsStreamingChatModelBuilderFactory	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.huggingface.spi.HuggingFaceChatModelBuilderFactory
dev.langchain4j.model.huggingface.spi.HuggingFaceLanguageModelBuilderFactory
dev.langchain4j.model.ovhai.internal.client.OvhAiClientBuilderFactory	Do not use anymore, use langchain4j-open-ai module instead

Deprecated Classes

Class	Description
dev.langchain4j.guardrail.JsonExtractorOutputGuardrail	This class has been moved to the `langchain4j-guardrails` module and will be removed in a future release. * Add a dependency on `dev.langchain4j:langchain4j-guardrails` and use the class from that module instead.
dev.langchain4j.mcp.client.transport.http.HttpMcpTransport
dev.langchain4j.model.github.GitHubModelsChatModel	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.github.GitHubModelsEmbeddingModel	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.github.GitHubModelsStreamingChatModel	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.huggingface.client.Parameters
dev.langchain4j.model.huggingface.client.TextGenerationRequest
dev.langchain4j.model.huggingface.client.TextGenerationResponse
dev.langchain4j.model.huggingface.HuggingFaceChatModel	Please use OpenAiChatModel from the langchain4j-open-ai module instead: ChatModel model = OpenAiChatModel.builder() .apiKey(System.getenv("HF_API_KEY")) .baseUrl("https://router.huggingface.co/v1") .modelName("HuggingFaceTB/SmolLM3-3B:hf-inference") .build();
dev.langchain4j.model.huggingface.HuggingFaceLanguageModel	Please use OpenAiChatModel from the langchain4j-open-ai module instead: ChatModel model = OpenAiChatModel.builder() .apiKey(System.getenv("HF_API_KEY")) .baseUrl("https://router.huggingface.co/v1") .modelName("HuggingFaceTB/SmolLM3-3B:hf-inference") .build();
dev.langchain4j.model.huggingface.HuggingFaceModelName
dev.langchain4j.model.openai.internal.chat.FunctionMessage
dev.langchain4j.model.ovhai.internal.api.EmbeddingRequest	use EmbeddingRequest from langchain4j-open-ai module instead
dev.langchain4j.model.ovhai.internal.api.EmbeddingResponse	use EmbeddingResponse from langchain4j-open-ai module instead
dev.langchain4j.model.ovhai.internal.client.DefaultOvhAiClient	Do not use anymore, use langchain4j-open-ai module instead
dev.langchain4j.model.ovhai.internal.client.OvhAiClient	Do not use anymore, use langchain4j-open-ai module instead
dev.langchain4j.model.ovhai.OvhAiEmbeddingModel	use OpenAiEmbeddingModel from langchain4j-open-ai module instead

Deprecated Enum Classes

Enum Class	Description
dev.langchain4j.model.github.GitHubModelsChatModelName	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.
dev.langchain4j.model.github.GitHubModelsEmbeddingModelName	This module is deprecated and will be removed in a future release. Please use the langchain4j-openai-official module instead.

Deprecated Annotation Interfaces

Annotation Interface	Description
dev.langchain4j.store.embedding.hibernate.Embedding	In favor of EmbeddingVector to avoid naming collisions

Deprecated Methods

Method	Description
dev.langchain4j.agentic.agent.AgentBuilder.maxSequentialToolsInvocations(int)	Use AgentBuilder.maxToolCallingRoundTrips(int) instead.
dev.langchain4j.internal.InternalStreamingChatResponseHandlerUtils.onPartialResponse(StreamingChatResponseHandler, String)	Use InternalStreamingChatResponseHandlerUtils.onPartialResponse(StreamingChatResponseHandler, String, StreamingHandle) instead.
dev.langchain4j.internal.InternalStreamingChatResponseHandlerUtils.onPartialThinking(StreamingChatResponseHandler, String)	Use InternalStreamingChatResponseHandlerUtils.onPartialThinking(StreamingChatResponseHandler, String, StreamingHandle) instead.
dev.langchain4j.internal.InternalStreamingChatResponseHandlerUtils.onPartialToolCall(StreamingChatResponseHandler, PartialToolCall)	Use InternalStreamingChatResponseHandlerUtils.onPartialToolCall(StreamingChatResponseHandler, PartialToolCall, StreamingHandle) instead.
dev.langchain4j.mcp.client.DefaultMcpClient.Builder.listener(McpClientListener)	Use DefaultMcpClient.Builder.addListener(McpClientListener) instead.
dev.langchain4j.mcp.client.transport.docker.DockerMcpTransport.Builder.dockerTslVerify(Boolean)	misspelled method name, use DockerMcpTransport.Builder.dockerTlsVerify(Boolean) instead.
dev.langchain4j.mcp.registryclient.McpRegistryClient.getServerDetails(String)	This method is not supported on the official MCP registry anymore.
dev.langchain4j.mcp.registryclient.model.McpOfficialMeta.getServerId()	This field was removed in the 2025-09-29 version of the schema.
dev.langchain4j.mcp.registryclient.model.McpServer.getStatus()	This field was moved to the McpOfficialMeta object in schema version 2025-09-29
dev.langchain4j.model.bedrock.GuardrailAssessmentSummary.Builder.ouputAssessments(List<GuardrailAssessment>)
dev.langchain4j.model.bedrock.GuardrailAssessmentSummary.ouputAssessments()
dev.langchain4j.model.cohere.CohereEmbeddingModel.withApiKey(String)	Please use builder() instead, and explicitly set the model name and, if necessary, other parameters.
dev.langchain4j.model.cohere.CohereScoringModel.CohereScoringModelBuilder.proxy(Proxy)	Proxy configuration via proxy(...) is no longer supported since the migration to the langchain4j HttpClient abstraction. Passing a non-null proxy will cause an UnsupportedOperationException when the model is built. To configure a proxy, supply a custom HttpClientBuilder via CohereScoringModel.CohereScoringModelBuilder.httpClientBuilder(HttpClientBuilder) instead.
dev.langchain4j.model.cohere.CohereScoringModel.withApiKey(String)	Please use builder() instead, and explicitly set the model name and, if necessary, other parameters.
dev.langchain4j.model.huggingface.client.HuggingFaceClient.chat(TextGenerationRequest)
dev.langchain4j.model.huggingface.client.HuggingFaceClient.generate(TextGenerationRequest)
dev.langchain4j.model.openai.internal.chat.AssistantMessage.Builder.functionCall(FunctionCall)
dev.langchain4j.model.openai.internal.chat.AssistantMessage.functionCall()
dev.langchain4j.model.openai.internal.chat.ChatCompletionRequest.Builder.functionCall(FunctionCall)
dev.langchain4j.model.openai.internal.chat.ChatCompletionRequest.Builder.functionCall(String)
dev.langchain4j.model.openai.internal.chat.ChatCompletionRequest.Builder.functions(Function...)
dev.langchain4j.model.openai.internal.chat.ChatCompletionRequest.Builder.functions(List<Function>)
dev.langchain4j.model.openai.internal.chat.ChatCompletionRequest.functionCall()
dev.langchain4j.model.openai.internal.chat.ChatCompletionRequest.functions()
dev.langchain4j.model.openai.internal.chat.Delta.Builder.functionCall(FunctionCall)
dev.langchain4j.model.openai.internal.chat.Delta.functionCall()
dev.langchain4j.model.openai.internal.chat.FunctionMessage.builder()
dev.langchain4j.model.openai.internal.chat.FunctionMessage.from(String, String)
dev.langchain4j.model.openai.internal.OpenAiUtils.toFunctions(Collection<ToolSpecification>)	Functions are deprecated by OpenAI, use OpenAiUtils.toTools(Collection, boolean) instead
dev.langchain4j.model.openai.OpenAiResponsesStreamingChatModel.Builder.strict(Boolean)	use OpenAiResponsesStreamingChatModel.Builder.strictTools(Boolean) and OpenAiResponsesStreamingChatModel.Builder.strictJsonSchema(Boolean) instead
dev.langchain4j.model.openaiofficial.OpenAiOfficialChatModel.Builder.azureDeploymentName(String)	Use OpenAiOfficialChatModel.Builder.microsoftFoundryDeploymentName(String) instead
dev.langchain4j.model.openaiofficial.OpenAiOfficialChatModel.Builder.isAzure(boolean)	Use OpenAiOfficialChatModel.Builder.isMicrosoftFoundry(boolean) instead
dev.langchain4j.model.openaiofficial.OpenAiOfficialEmbeddingModel.Builder.azureDeploymentName(String)	Use OpenAiOfficialEmbeddingModel.Builder.microsoftFoundryDeploymentName(String) instead
dev.langchain4j.model.openaiofficial.OpenAiOfficialEmbeddingModel.Builder.isAzure(boolean)	Use OpenAiOfficialEmbeddingModel.Builder.isMicrosoftFoundry(boolean) instead
dev.langchain4j.model.openaiofficial.OpenAiOfficialImageModel.Builder.azureDeploymentName(String)	Use OpenAiOfficialImageModel.Builder.microsoftFoundryDeploymentName(String) instead
dev.langchain4j.model.openaiofficial.OpenAiOfficialImageModel.Builder.isAzure(boolean)	Use OpenAiOfficialImageModel.Builder.isMicrosoftFoundry(boolean) instead
dev.langchain4j.model.openaiofficial.OpenAiOfficialResponsesStreamingChatModel.Builder.azureDeploymentName(String)	Use OpenAiOfficialResponsesStreamingChatModel.Builder.microsoftFoundryDeploymentName(String) instead
dev.langchain4j.model.openaiofficial.OpenAiOfficialResponsesStreamingChatModel.Builder.isAzure(boolean)	Use OpenAiOfficialResponsesStreamingChatModel.Builder.isMicrosoftFoundry(boolean) instead
dev.langchain4j.model.openaiofficial.OpenAiOfficialResponsesStreamingChatModel.Builder.reasoningEffort(String)	use OpenAiOfficialResponsesStreamingChatModel.Builder.reasoningEffort(ReasoningEffort) instead
dev.langchain4j.model.openaiofficial.OpenAiOfficialResponsesStreamingChatModel.Builder.strict(Boolean)	use OpenAiOfficialResponsesStreamingChatModel.Builder.strictTools(Boolean) and OpenAiOfficialResponsesStreamingChatModel.Builder.strictJsonSchema(Boolean) instead
dev.langchain4j.model.openaiofficial.OpenAiOfficialStreamingChatModel.Builder.azureDeploymentName(String)	Use OpenAiOfficialStreamingChatModel.Builder.microsoftFoundryDeploymentName(String) instead
dev.langchain4j.model.openaiofficial.OpenAiOfficialStreamingChatModel.Builder.isAzure(boolean)	Use OpenAiOfficialStreamingChatModel.Builder.isMicrosoftFoundry(boolean) instead
dev.langchain4j.model.ovhai.OvhAiEmbeddingModel.withApiKey(String)	Please use builder() instead, and explicitly set the baseUrl and, if necessary, other parameters. The default value for baseUrl will be removed in future releases!
dev.langchain4j.rag.content.retriever.elasticsearch.ElasticsearchContentRetriever.Builder.restClient(RestClient)	Use ElasticsearchContentRetriever.Builder.client(ElasticsearchClient) instead.
dev.langchain4j.service.AiServices.maxSequentialToolsInvocations(int)	Use AiServices.maxToolCallingRoundTrips(int) instead.
dev.langchain4j.service.AiServices.tools(Map<ToolSpecification, ToolExecutor>, Set<String>)	use AiServices.tools(List) instead in order to specify ReturnBehavior
dev.langchain4j.service.AiServiceTokenStreamParameters.availableTools()	use AiServiceTokenStreamParameters.toolServiceContext() instead
dev.langchain4j.service.AiServiceTokenStreamParameters.Builder.availableTools(List<ToolSpecification>)	use AiServiceTokenStreamParameters.Builder.toolServiceContext(ToolServiceContext) instead
dev.langchain4j.service.AiServiceTokenStreamParameters.Builder.effectiveTools(List<ToolSpecification>)	use AiServiceTokenStreamParameters.Builder.toolServiceContext(ToolServiceContext) instead
dev.langchain4j.service.AiServiceTokenStreamParameters.Builder.toolExecutors(Map<String, ToolExecutor>)	use AiServiceTokenStreamParameters.Builder.toolServiceContext(ToolServiceContext) instead
dev.langchain4j.service.AiServiceTokenStreamParameters.Builder.toolSpecifications(List<ToolSpecification>)	use AiServiceTokenStreamParameters.Builder.toolServiceContext(ToolServiceContext) instead
dev.langchain4j.service.AiServiceTokenStreamParameters.effectiveTools()	use AiServiceTokenStreamParameters.toolServiceContext() instead
dev.langchain4j.service.AiServiceTokenStreamParameters.toolExecutors()	use AiServiceTokenStreamParameters.toolServiceContext() instead
dev.langchain4j.service.AiServiceTokenStreamParameters.toolSpecifications()	use AiServiceTokenStreamParameters.toolServiceContext() instead
dev.langchain4j.service.tool.AiServiceTool.Builder.immediateReturn(boolean)	use AiServiceTool.Builder.returnBehavior(ReturnBehavior) instead
dev.langchain4j.service.tool.AiServiceTool.immediateReturn()	use AiServiceTool.returnBehavior() instead
dev.langchain4j.service.tool.ToolErrorContext.Builder.memoryId(Object)	Please set ToolErrorContext.Builder.invocationContext(InvocationContext) instead
dev.langchain4j.service.tool.ToolExecution.Builder.result(String)	Please use ToolExecution.Builder.result(ToolExecutionResult) instead
dev.langchain4j.service.tool.ToolProviderResult.Builder.immediateReturnToolNames(Set<String>)	use ToolProviderResult.Builder.add(AiServiceTool) or ToolProviderResult.Builder.add(ToolSpecification, ToolExecutor, ReturnBehavior) to specify tool's ReturnBehavior
dev.langchain4j.service.tool.ToolProviderResult.immediateReturnToolNames()	use ToolProviderResult.aiServiceTools() to get tool's ReturnBehavior
dev.langchain4j.service.tool.ToolProviderResult.toolExecutorByName(String)
dev.langchain4j.service.tool.ToolProviderResult.tools()	use ToolProviderResult.aiServiceTools() instead
dev.langchain4j.service.tool.ToolProviderResult.toolSpecificationByName(String)
dev.langchain4j.service.tool.ToolService.isImmediateTool(String)	use ToolService.returnBehavior(String) instead
dev.langchain4j.service.tool.ToolService.maxSequentialToolsInvocations()	Use ToolService.maxToolCallingRoundTrips() instead.
dev.langchain4j.service.tool.ToolService.maxSequentialToolsInvocations(int)	Use ToolService.maxToolCallingRoundTrips(int) instead.
dev.langchain4j.service.tool.ToolService.toolProvider()	use ToolService.toolProviders() instead
dev.langchain4j.service.tool.ToolServiceContext.Builder.immediateReturnTools(Set<String>)	use ToolServiceContext.Builder.returnBehaviors(Map) instead
dev.langchain4j.service.tool.ToolServiceContext.Builder.toolSpecifications(List<ToolSpecification>)	use ToolServiceContext.Builder.effectiveTools(List) instead
dev.langchain4j.service.tool.ToolServiceContext.immediateReturnTools()	use ToolServiceContext.returnBehavior(String) instead
dev.langchain4j.service.tool.ToolServiceContext.toolSpecifications()	use ToolServiceContext.effectiveTools() instead
dev.langchain4j.service.tool.ToolServiceResult.chatResponse()	Please use ToolServiceResult.aggregateResponse() instead for clarity
dev.langchain4j.store.embedding.elasticsearch.AbstractElasticsearchEmbeddingStore.initialize(ElasticsearchConfiguration, RestClient, String)	Use now AbstractElasticsearchEmbeddingStore.initialize(ElasticsearchConfiguration, ElasticsearchClient, String)
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore.Builder.apiKey(String)	call ElasticsearchEmbeddingStore.Builder.restClient(RestClient) instead
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore.Builder.dimension(Integer)	dimension is not used anymore.
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore.Builder.password(String)	call ElasticsearchEmbeddingStore.Builder.restClient(RestClient) instead
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore.Builder.restClient(RestClient)	Use ElasticsearchEmbeddingStore.Builder.client(ElasticsearchClient) instead.
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore.Builder.serverUrl(String)	call ElasticsearchEmbeddingStore.Builder.restClient(RestClient) instead
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore.Builder.userName(String)	call ElasticsearchEmbeddingStore.Builder.restClient(RestClient) instead
dev.langchain4j.store.embedding.pinecone.PineconeEmbeddingStore.Builder.environment(String)	Please use PineconeEmbeddingStore.Builder.createIndex(PineconeIndexConfig)
dev.langchain4j.store.embedding.pinecone.PineconeEmbeddingStore.Builder.projectId(String)	Please use PineconeEmbeddingStore.Builder.createIndex(PineconeIndexConfig)

Deprecated Constructors

Constructor	Description
dev.langchain4j.data.document.parser.apache.tika.ApacheTikaDocumentParser(Supplier<Parser>, Supplier<ContentHandler>, Supplier<Metadata>, Supplier<ParseContext>)	Use the constructor with suppliers for Tika components if you intend to use this parser for multiple files and specify whether to include metadata or not.
dev.langchain4j.data.document.parser.apache.tika.ApacheTikaDocumentParser(Parser, ContentHandler, Metadata, ParseContext)	Use the constructor with suppliers for Tika components if you intend to use this parser for multiple files.
dev.langchain4j.model.anthropic.internal.api.AnthropicCreateMessageRequest(String, List<AnthropicMessage>, List<AnthropicTextContent>, int, List<String>, boolean, Double, Double, Integer, List<AnthropicTool>, AnthropicToolChoice, AnthropicThinking, AnthropicMetadata)
dev.langchain4j.model.anthropic.internal.api.AnthropicTool(String, String, AnthropicToolSchema, AnthropicCacheControl)	please use AnthropicTool(Builder) instead
dev.langchain4j.model.anthropic.internal.api.AnthropicToolSchema(String, Map<String, Map<String, Object>>, List<String>)	please use AnthropicToolSchema(Builder) instead
dev.langchain4j.model.cohere.CohereEmbeddingModel(String, String, String, String, Duration, Boolean, Boolean, Integer)
dev.langchain4j.model.cohere.CohereScoringModel(String, String, String, Duration, Integer, Proxy, Boolean, Boolean)
dev.langchain4j.model.jina.JinaEmbeddingModel(String, String, String, Duration, Integer, Boolean, Boolean, Boolean)
dev.langchain4j.model.jina.JinaScoringModel(String, String, String, Duration, Integer, Boolean, Boolean)
dev.langchain4j.model.localai.LocalAiChatModel(String, String, Double, Double, Integer, Duration, Integer, Boolean, Boolean)
dev.langchain4j.model.localai.LocalAiEmbeddingModel(String, String, Duration, Integer, Boolean, Boolean)
dev.langchain4j.model.localai.LocalAiLanguageModel(String, String, Double, Double, Integer, Duration, Integer, Boolean, Boolean)
dev.langchain4j.model.localai.LocalAiStreamingChatModel(String, String, Double, Double, Integer, Duration, Boolean, Boolean)
dev.langchain4j.model.localai.LocalAiStreamingLanguageModel(String, String, Double, Double, Integer, Duration, Boolean, Boolean)
dev.langchain4j.model.nomic.NomicEmbeddingModel(String, String, String, String, Integer, Duration, Integer, Boolean, Boolean)
dev.langchain4j.model.vertexai.gemini.VertexAiGeminiChatModel(String, String, String, Float, Integer, Integer, Float, Integer, Integer, String, Schema, Map<HarmCategory, SafetyThreshold>, Boolean, String, ToolCallingMode, List<String>, Boolean, Boolean, List<ChatModelListener>, Set<Capability>)	please use VertexAiGeminiChatModel(VertexAiGeminiChatModelBuilder) instead
dev.langchain4j.model.vertexai.gemini.VertexAiGeminiStreamingChatModel(String, String, String, Float, Integer, Integer, Float, String, Schema, Map<HarmCategory, SafetyThreshold>, Boolean, String, ToolCallingMode, List<String>, Boolean, Boolean, List<ChatModelListener>, Map<String, String>, Executor)	please use VertexAiGeminiStreamingChatModel(VertexAiGeminiStreamingChatModelBuilder) instead
dev.langchain4j.model.vertexai.VertexAiChatModel(String, String, String, String, String, Double, Integer, Integer, Double, Integer)	Please use VertexAiChatModel(Builder) instead
dev.langchain4j.model.vertexai.VertexAiEmbeddingModel(String, String, String, String, String, Integer, Integer, Integer, VertexAiEmbeddingModel.TaskType, String, Integer, Boolean)	Please use VertexAiEmbeddingModel(Builder) instead
dev.langchain4j.model.voyageai.VoyageAiEmbeddingModel(HttpClientBuilder, Map<String, String>, String, Duration, Integer, String, String, String, Boolean, String, Boolean, Boolean, Integer)
dev.langchain4j.model.voyageai.VoyageAiScoringModel(HttpClientBuilder, Map<String, String>, String, Duration, Integer, String, String, Integer, Boolean, Boolean, Boolean)
dev.langchain4j.rag.content.retriever.azure.cosmos.nosql.AzureCosmosDBNoSqlContentRetriever(String, AzureKeyCredential, TokenCredential, EmbeddingModel, String, String, String, IndexingPolicy, CosmosVectorEmbeddingPolicy, CosmosFullTextPolicy, Integer, AzureCosmosDBSearchQueryType, Integer, Double, Filter)
dev.langchain4j.rag.content.retriever.elasticsearch.ElasticsearchContentRetriever(ElasticsearchConfiguration, RestClient, String, EmbeddingModel, int, double, Filter)	Use ElasticsearchContentRetriever(ElasticsearchConfiguration, ElasticsearchClient, String, EmbeddingModel, int, double, Filter) instead.
dev.langchain4j.service.tool.ToolServiceContext(List<ToolSpecification>, Map<String, ToolExecutor>)	use ToolServiceContext(Builder) instead
dev.langchain4j.service.tool.ToolServiceResult(ChatResponse, List<ToolExecution>)	Please use ToolServiceResult(Builder) instead
dev.langchain4j.store.embedding.chroma.ChromaEmbeddingStore(String, String, Duration, boolean, boolean)	Only works with the V1 API, use the ChromaEmbeddingStore(Builder) constructor instead.
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore(ElasticsearchConfiguration, String, String, String, String, String)	by ElasticsearchEmbeddingStore(ElasticsearchConfiguration, ElasticsearchClient, String)
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore(ElasticsearchConfiguration, String, String, String, String, String, Integer)	by ElasticsearchEmbeddingStore(ElasticsearchConfiguration, RestClient, String)
dev.langchain4j.store.embedding.elasticsearch.ElasticsearchEmbeddingStore(ElasticsearchConfiguration, RestClient, String)	by ElasticsearchEmbeddingStore(ElasticsearchConfiguration, ElasticsearchClient, String)
dev.langchain4j.store.embedding.milvus.MilvusEmbeddingStore(MilvusServiceClient, String, Integer, IndexType, MetricType, ConsistencyLevelEnum, Boolean, Boolean, String, String, String, String)
dev.langchain4j.store.embedding.milvus.MilvusEmbeddingStore(String, Integer, String, Integer, IndexType, MetricType, String, String, String, String, ConsistencyLevelEnum, Boolean, Boolean, String, String, String, String, String)

Deprecated Enum Constants

Enum Constant	Description
dev.langchain4j.micrometer.metrics.conventions.OTelGenAiProviderName.AZURE_OPEN_AI
dev.langchain4j.model.anthropic.AnthropicChatModelName.CLAUDE_OPUS_4_1_20250805
dev.langchain4j.model.ModelProvider.AZURE_OPEN_AI
dev.langchain4j.model.openai.internal.chat.Role.FUNCTION
dev.langchain4j.model.openai.OpenAiImageModelName.DALL_E_2	DALL-E models have been deprecated by OpenAI. Use OpenAiImageModelName.GPT_IMAGE_1 or other GPT image models instead.
dev.langchain4j.model.openai.OpenAiImageModelName.DALL_E_3	DALL-E models have been deprecated by OpenAI. Use OpenAiImageModelName.GPT_IMAGE_1 or other GPT image models instead.