diff --git a/models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/proxy/DeepSeekWithOpenAiChatModelIT.java b/models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/proxy/DeepSeekWithOpenAiChatModelIT.java new file mode 100644 index 00000000000..fe00a6a69d0 --- /dev/null +++ b/models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/proxy/DeepSeekWithOpenAiChatModelIT.java @@ -0,0 +1,343 @@ +/* + * Copyright 2024-2025 the original author or authors. + * + * 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 + * + * https://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 org.springframework.ai.openai.chat.proxy; + +import java.util.ArrayList; +import java.util.Arrays; +import java.util.List; +import java.util.Map; +import java.util.stream.Collectors; + +import org.junit.jupiter.api.Disabled; +import org.junit.jupiter.api.Test; +import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable; +import org.junit.jupiter.params.ParameterizedTest; +import org.junit.jupiter.params.provider.ValueSource; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; +import reactor.core.publisher.Flux; + +import org.springframework.ai.chat.client.ChatClient; +import org.springframework.ai.chat.messages.AssistantMessage; +import org.springframework.ai.chat.messages.Message; +import org.springframework.ai.chat.messages.UserMessage; +import org.springframework.ai.chat.model.ChatResponse; +import org.springframework.ai.chat.model.Generation; +import org.springframework.ai.chat.prompt.Prompt; +import org.springframework.ai.chat.prompt.PromptTemplate; +import org.springframework.ai.chat.prompt.SystemPromptTemplate; +import org.springframework.ai.converter.BeanOutputConverter; +import org.springframework.ai.converter.ListOutputConverter; +import org.springframework.ai.converter.MapOutputConverter; +import org.springframework.ai.model.function.FunctionCallback; +import org.springframework.ai.openai.OpenAiChatModel; +import org.springframework.ai.openai.OpenAiChatOptions; +import org.springframework.ai.openai.api.OpenAiApi; +import org.springframework.ai.openai.api.tool.MockWeatherService; +import org.springframework.ai.openai.chat.ActorsFilms; +import org.springframework.beans.factory.annotation.Autowired; +import org.springframework.beans.factory.annotation.Value; +import org.springframework.boot.SpringBootConfiguration; +import org.springframework.boot.test.context.SpringBootTest; +import org.springframework.context.annotation.Bean; +import org.springframework.core.convert.support.DefaultConversionService; +import org.springframework.core.io.Resource; + +import static org.assertj.core.api.Assertions.assertThat; + +/** + * @author Alexandros Pappas + * + * The DeepSeek API uses an API format compatible with OpenAI, allowing developers to + * easily integrate it into existing systems that use the OpenAI SDK5. + * + * For more information on DeepSeek behavior, refer to its API documentation: + * DeepSeek API + */ +@SpringBootTest(classes = DeepSeekWithOpenAiChatModelIT.Config.class) +@EnabledIfEnvironmentVariable(named = "DEEPSEEK_API_KEY", matches = ".+") +@Disabled("Requires DeepSeek credits") +class DeepSeekWithOpenAiChatModelIT { + + private static final Logger logger = LoggerFactory.getLogger(DeepSeekWithOpenAiChatModelIT.class); + + private static final String DEEPSEEK_BASE_URL = "https://api.deepseek.com"; + + private static final String DEFAULT_DEEPSEEK_MODEL = "deepseek-chat"; + + @Value("classpath:/prompts/system-message.st") + private Resource systemResource; + + @Autowired + private OpenAiChatModel chatModel; + + @Test + void roleTest() { + UserMessage userMessage = new UserMessage( + "Tell me about 3 famous pirates from the Golden Age of Piracy and what they did."); + SystemPromptTemplate systemPromptTemplate = new SystemPromptTemplate(this.systemResource); + Message systemMessage = systemPromptTemplate.createMessage(Map.of("name", "Bob", "voice", "pirate")); + Prompt prompt = new Prompt(List.of(userMessage, systemMessage)); + ChatResponse response = this.chatModel.call(prompt); + assertThat(response.getResults()).hasSize(1); + assertThat(response.getResults().get(0).getOutput().getText()).contains("Blackbeard"); + } + + @Test + void streamRoleTest() { + UserMessage userMessage = new UserMessage( + "Tell me about 3 famous pirates from the Golden Age of Piracy and what they did."); + SystemPromptTemplate systemPromptTemplate = new SystemPromptTemplate(this.systemResource); + Message systemMessage = systemPromptTemplate.createMessage(Map.of("name", "Bob", "voice", "pirate")); + Prompt prompt = new Prompt(List.of(userMessage, systemMessage)); + Flux flux = this.chatModel.stream(prompt); + + List responses = flux.collectList().block(); + assertThat(responses.size()).isGreaterThan(1); + + String stitchedResponseContent = responses.stream() + .map(ChatResponse::getResults) + .flatMap(List::stream) + .map(Generation::getOutput) + .map(AssistantMessage::getText) + .collect(Collectors.joining()); + + assertThat(stitchedResponseContent).contains("Blackbeard"); + } + + @Test + void streamingWithTokenUsage() { + var promptOptions = OpenAiChatOptions.builder().streamUsage(true).seed(1).build(); + + var prompt = new Prompt("List two colors of the Polish flag. Be brief.", promptOptions); + + var streamingTokenUsage = this.chatModel.stream(prompt).blockLast().getMetadata().getUsage(); + var referenceTokenUsage = this.chatModel.call(prompt).getMetadata().getUsage(); + + assertThat(streamingTokenUsage.getPromptTokens()).isGreaterThan(0); + assertThat(streamingTokenUsage.getGenerationTokens()).isGreaterThan(0); + assertThat(streamingTokenUsage.getTotalTokens()).isGreaterThan(0); + + assertThat(streamingTokenUsage.getPromptTokens()).isEqualTo(referenceTokenUsage.getPromptTokens()); + assertThat(streamingTokenUsage.getGenerationTokens()).isEqualTo(referenceTokenUsage.getGenerationTokens()); + assertThat(streamingTokenUsage.getTotalTokens()).isEqualTo(referenceTokenUsage.getTotalTokens()); + + } + + @Test + void listOutputConverter() { + DefaultConversionService conversionService = new DefaultConversionService(); + ListOutputConverter outputConverter = new ListOutputConverter(conversionService); + + String format = outputConverter.getFormat(); + String template = """ + List five {subject} + {format} + """; + PromptTemplate promptTemplate = new PromptTemplate(template, + Map.of("subject", "ice cream flavors", "format", format)); + Prompt prompt = new Prompt(promptTemplate.createMessage()); + Generation generation = this.chatModel.call(prompt).getResult(); + + List list = outputConverter.convert(generation.getOutput().getText()); + assertThat(list).hasSize(5); + + } + + @Test + void mapOutputConverter() { + MapOutputConverter outputConverter = new MapOutputConverter(); + + String format = outputConverter.getFormat(); + String template = """ + Provide me a List of {subject} + {format} + """; + PromptTemplate promptTemplate = new PromptTemplate(template, + Map.of("subject", "numbers from 1 to 9 under they key name 'numbers'", "format", format)); + Prompt prompt = new Prompt(promptTemplate.createMessage()); + Generation generation = this.chatModel.call(prompt).getResult(); + + Map result = outputConverter.convert(generation.getOutput().getText()); + assertThat(result.get("numbers")).isEqualTo(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9)); + + } + + @Test + void beanOutputConverter() { + + BeanOutputConverter outputConverter = new BeanOutputConverter<>(ActorsFilms.class); + + String format = outputConverter.getFormat(); + String template = """ + Generate the filmography for a random actor. + {format} + """; + PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format)); + Prompt prompt = new Prompt(promptTemplate.createMessage()); + Generation generation = this.chatModel.call(prompt).getResult(); + + ActorsFilms actorsFilms = outputConverter.convert(generation.getOutput().getText()); + assertThat(actorsFilms.getActor()).isNotEmpty(); + } + + @Test + void beanOutputConverterRecords() { + + BeanOutputConverter outputConverter = new BeanOutputConverter<>( + DeepSeekWithOpenAiChatModelIT.ActorsFilmsRecord.class); + + String format = outputConverter.getFormat(); + String template = """ + Generate the filmography of 5 movies for Tom Hanks. + {format} + """; + PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format)); + Prompt prompt = new Prompt(promptTemplate.createMessage()); + Generation generation = this.chatModel.call(prompt).getResult(); + + DeepSeekWithOpenAiChatModelIT.ActorsFilmsRecord actorsFilms = outputConverter + .convert(generation.getOutput().getText()); + logger.info("" + actorsFilms); + assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks"); + assertThat(actorsFilms.movies()).hasSize(5); + } + + @Test + void beanStreamOutputConverterRecords() { + + BeanOutputConverter outputConverter = new BeanOutputConverter<>( + DeepSeekWithOpenAiChatModelIT.ActorsFilmsRecord.class); + + String format = outputConverter.getFormat(); + String template = """ + Generate the filmography of 5 movies for Tom Hanks. + {format} + """; + PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format)); + Prompt prompt = new Prompt(promptTemplate.createMessage()); + + String generationTextFromStream = this.chatModel.stream(prompt) + .collectList() + .block() + .stream() + .map(ChatResponse::getResults) + .flatMap(List::stream) + .map(Generation::getOutput) + .map(AssistantMessage::getText) + .collect(Collectors.joining()); + + DeepSeekWithOpenAiChatModelIT.ActorsFilmsRecord actorsFilms = outputConverter.convert(generationTextFromStream); + logger.info("" + actorsFilms); + assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks"); + assertThat(actorsFilms.movies()).hasSize(5); + } + + @Test + @Disabled("The current version of the deepseek-chat model's Function Calling capability is unstable, which may result in looped calls or empty responses.") + void functionCallTest() { + + UserMessage userMessage = new UserMessage("What's the weather like in San Francisco, Tokyo, and Paris?"); + + List messages = new ArrayList<>(List.of(userMessage)); + + var promptOptions = OpenAiChatOptions.builder() + .functionCallbacks(List.of(FunctionCallback.builder() + .function("getCurrentWeather", new MockWeatherService()) + .description("Get the weather in location") + .inputType(MockWeatherService.Request.class) + .build())) + .build(); + + ChatResponse response = this.chatModel.call(new Prompt(messages, promptOptions)); + + logger.info("Response: {}", response); + + assertThat(response.getResult().getOutput().getText()).contains("30", "10", "15"); + } + + @Test + @Disabled("The current version of the deepseek-chat model's Function Calling capability is unstable, which may result in looped calls or empty responses.") + void streamFunctionCallTest() { + + UserMessage userMessage = new UserMessage( + "What's the weather like in San Francisco, Tokyo, and Paris? Return the temperature in Celsius."); + + List messages = new ArrayList<>(List.of(userMessage)); + + var promptOptions = OpenAiChatOptions.builder() + .functionCallbacks(List.of(FunctionCallback.builder() + .function("getCurrentWeather", new MockWeatherService()) + .description("Get the weather in location") + .inputType(MockWeatherService.Request.class) + .build())) + .build(); + + Flux response = this.chatModel.stream(new Prompt(messages, promptOptions)); + + String content = response.collectList() + .block() + .stream() + .map(ChatResponse::getResults) + .flatMap(List::stream) + .map(Generation::getOutput) + .map(AssistantMessage::getText) + .collect(Collectors.joining()); + logger.info("Response: {}", content); + + assertThat(content).contains("30", "10", "15"); + } + + @ParameterizedTest(name = "{0} : {displayName} ") + @ValueSource(strings = { "deepseek-chat", "deepseek-reasoner" }) + void validateCallResponseMetadata(String model) { + // @formatter:off + ChatResponse response = ChatClient.create(this.chatModel).prompt() + .options(OpenAiChatOptions.builder().model(model).build()) + .user("Tell me about 3 famous pirates from the Golden Age of Piracy and what they did") + .call() + .chatResponse(); + // @formatter:on + + logger.info(response.toString()); + assertThat(response.getMetadata().getId()).isNotEmpty(); + assertThat(response.getMetadata().getModel()).containsIgnoringCase(model); + assertThat(response.getMetadata().getUsage().getPromptTokens()).isPositive(); + assertThat(response.getMetadata().getUsage().getGenerationTokens()).isPositive(); + assertThat(response.getMetadata().getUsage().getTotalTokens()).isPositive(); + } + + record ActorsFilmsRecord(String actor, List movies) { + + } + + @SpringBootConfiguration + static class Config { + + @Bean + public OpenAiApi chatCompletionApi() { + return new OpenAiApi(DEEPSEEK_BASE_URL, System.getenv("DEEPSEEK_API_KEY")); + } + + @Bean + public OpenAiChatModel openAiClient(OpenAiApi openAiApi) { + return new OpenAiChatModel(openAiApi, OpenAiChatOptions.builder().model(DEFAULT_DEEPSEEK_MODEL).build()); + } + + } + +} diff --git a/spring-ai-docs/src/main/antora/modules/ROOT/images/spring-ai-deepseek-integration.jpg b/spring-ai-docs/src/main/antora/modules/ROOT/images/spring-ai-deepseek-integration.jpg new file mode 100644 index 00000000000..444e92fb379 Binary files /dev/null and b/spring-ai-docs/src/main/antora/modules/ROOT/images/spring-ai-deepseek-integration.jpg differ diff --git a/spring-ai-docs/src/main/antora/modules/ROOT/nav.adoc b/spring-ai-docs/src/main/antora/modules/ROOT/nav.adoc index d4234afe76e..71242652d57 100644 --- a/spring-ai-docs/src/main/antora/modules/ROOT/nav.adoc +++ b/spring-ai-docs/src/main/antora/modules/ROOT/nav.adoc @@ -18,6 +18,7 @@ **** xref:api/chat/functions/anthropic-chat-functions.adoc[Anthropic Function Calling] *** xref:api/chat/azure-openai-chat.adoc[Azure OpenAI] **** xref:api/chat/functions/azure-open-ai-chat-functions.adoc[Azure OpenAI Function Calling] +*** xref:api/chat/deepseek-chat.adoc[DeepSeek AI] *** xref:api/chat/google-vertexai.adoc[Google VertexAI] **** xref:api/chat/vertexai-gemini-chat.adoc[VertexAI Gemini] ***** xref:api/chat/functions/vertexai-gemini-chat-functions.adoc[Gemini Function Calling] diff --git a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chat/comparison.adoc b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chat/comparison.adoc index 50deeb06ae0..e74d0f2bf96 100644 --- a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chat/comparison.adoc +++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chat/comparison.adoc @@ -21,6 +21,7 @@ This table compares various Chat Models supported by Spring AI, detailing their | xref::api/chat/anthropic-chat.adoc[Anthropic Claude] | text, pdf, image ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::no.svg[width=12] ^a| image::no.svg[width=12] ^a| image::no.svg[width=12] | xref::api/chat/azure-openai-chat.adoc[Azure OpenAI] | text, image ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::no.svg[width=12] ^a| image::yes.svg[width=16] +| xref::api/chat/deepseek-chat.adoc[DeepSeek (OpenAI-proxy)] | text ^a| image::no.svg[width=12] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] | xref::api/chat/vertexai-gemini-chat.adoc[Google VertexAI Gemini] | text, pdf, image, audio, video ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::no.svg[width=12] ^a| image::yes.svg[width=16] | xref::api/chat/groq-chat.adoc[Groq (OpenAI-proxy)] | text, image ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::yes.svg[width=16] ^a| image::no.svg[width=12] ^a| image::no.svg[width=12] ^a| image::yes.svg[width=16] | xref::api/chat/huggingface.adoc[HuggingFace] | text ^a| image::no.svg[width=12] ^a| image::no.svg[width=12] ^a| image::no.svg[width=12] ^a| image::no.svg[width=12] ^a| image::no.svg[width=12] ^a| image::no.svg[width=12] ^a| image::no.svg[width=12] diff --git a/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chat/deepseek-chat.adoc b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chat/deepseek-chat.adoc new file mode 100644 index 00000000000..d0628daacdf --- /dev/null +++ b/spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chat/deepseek-chat.adoc @@ -0,0 +1,215 @@ += DeepSeek Chat + +https://www.deepseek.com/[DeepSeek AI] provides the open-source DeepSeek R3 model, renowned for its cutting-edge reasoning and problem-solving capabilities. + +Spring AI integrates with DeepSeek AI by reusing the existing xref::api/chat/openai-chat.adoc[OpenAI] client. To get started, you'll need to obtain a https://api-docs.deepseek.com/[DeepSeek API Key], configure the base URL, and select one of the supported models. + +image::spring-ai-deepseek-integration.jpg[w=800,align="center"] + +NOTE: The current version of the deepseek-chat model's Function Calling capability is unstable, which may result in looped calls or empty responses. + +Check the https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/proxy/DeepSeekWithOpenAiChatModelIT.java[DeepSeekWithOpenAiChatModelIT.java] tests for examples of using DeepSeek with Spring AI. + + +== Prerequisites + +* **Create an API Key**: +Visit https://api-docs.deepseek.com/[here] to create an API Key. Configure it using the `spring.ai.openai.api-key` property in your Spring AI project. + +* **Set the DeepSeek Base URL**: +Set the `spring.ai.openai.base-url` property to `https://api.deepseek.com`. + +* **Select a DeepSeek Model**: +Use the `spring.ai.openai.chat.model=` property to specify the model. Refer to https://api-docs.deepseek.com/quick_start/pricing[Supported Models] for available options. + +Example environment variables configuration: + +[source,shell] +---- +export SPRING_AI_OPENAI_API_KEY= +export SPRING_AI_OPENAI_BASE_URL=https://api.deepseek.com +export SPRING_AI_OPENAI_CHAT_MODEL=deepseek-chat +---- + +=== Add Repositories and BOM + +Spring AI artifacts are published in Spring Milestone and Snapshot repositories. +Refer to the xref:getting-started.adoc#repositories[Repositories] section to add these repositories to your build system. + +To help with dependency management, Spring AI provides a BOM (bill of materials) to ensure that a consistent version of Spring AI is used throughout the entire project. Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build system. + + +== Auto-configuration + +Spring AI provides Spring Boot auto-configuration for the OpenAI Chat Client. +To enable it add the following dependency to your project's Maven `pom.xml` or Gradle `build.gradle` build files: + +[tabs] +====== +Maven:: ++ +[source, xml] +---- + + org.springframework.ai + spring-ai-openai-spring-boot-starter + +---- + +Gradle:: ++ +[source,groovy] +---- +dependencies { + implementation 'org.springframework.ai:spring-ai-openai-spring-boot-starter' +} +---- +====== + +TIP: Refer to the xref:getting-started.adoc#dependency-management[Dependency Management] section to add the Spring AI BOM to your build file. + +=== Chat Properties + +==== Retry Properties + +The prefix `spring.ai.retry` is used as the property prefix that lets you configure the retry mechanism for the OpenAI chat model. + +[cols="3,5,1", stripes=even] +|==== +| Property | Description | Default + +| spring.ai.retry.max-attempts | Maximum number of retry attempts. | 10 +| spring.ai.retry.backoff.initial-interval | Initial sleep duration for the exponential backoff policy. | 2 sec. +| spring.ai.retry.backoff.multiplier | Backoff interval multiplier. | 5 +| spring.ai.retry.backoff.max-interval | Maximum backoff duration. | 3 min. +| spring.ai.retry.on-client-errors | If false, throw a NonTransientAiException, and do not attempt retry for `4xx` client error codes | false +| spring.ai.retry.exclude-on-http-codes | List of HTTP status codes that should not trigger a retry (e.g. to throw NonTransientAiException). | empty +| spring.ai.retry.on-http-codes | List of HTTP status codes that should trigger a retry (e.g. to throw TransientAiException). | empty +|==== + +==== Connection Properties + +The prefix `spring.ai.openai` is used as the property prefix that lets you connect to OpenAI. + +[cols="3,5,1", stripes=even] +|==== +| Property | Description | Default + +| spring.ai.openai.base-url | The URL to connect to. Must be set to `https://api.deepseek.com` | - +| spring.ai.openai.chat.api-key | Your DeepSeek API Key | - +|==== + + +==== Configuration Properties + +The prefix `spring.ai.openai.chat` is the property prefix that lets you configure the chat model implementation for OpenAI. +[cols="3,5,1", stripes=even] +|==== +| Property | Description | Default + +| spring.ai.openai.chat.enabled | Enable OpenAI chat model. | true +| spring.ai.openai.chat.base-url | Optional overrides the spring.ai.openai.base-url to provide chat specific url. Must be set to `https://api.deepseek.com` | - +| spring.ai.openai.chat.api-key | Optional overrides the spring.ai.openai.api-key to provide chat specific api-key | - +| spring.ai.openai.chat.options.model | The link:https://api-docs.deepseek.com/quick_start/pricing[DeepSeek LLM model] to use | - +| spring.ai.openai.chat.options.temperature | The sampling temperature to use that controls the apparent creativity of generated completions. Higher values will make output more random while lower values will make results more focused and deterministic. It is not recommended to modify temperature and top_p for the same completions request as the interaction of these two settings is difficult to predict. | 0.8 +| spring.ai.openai.chat.options.frequencyPenalty | Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. | 0.0f +| spring.ai.openai.chat.options.maxTokens | The maximum number of tokens to generate in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length. | - +| spring.ai.openai.chat.options.n | How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs. | 1 +| spring.ai.openai.chat.options.presencePenalty | Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. | - +| spring.ai.openai.chat.options.responseFormat | An object specifying the format that the model must output. Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the message the model generates is valid JSON.| - +| spring.ai.openai.chat.options.seed | This feature is in Beta. If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. | - +| spring.ai.openai.chat.options.stop | Up to 4 sequences where the API will stop generating further tokens. | - +| spring.ai.openai.chat.options.topP | An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both. | - +| spring.ai.openai.chat.options.tools | A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. | - +| spring.ai.openai.chat.options.toolChoice | Controls which (if any) function is called by the model. none means the model will not call a function and instead generates a message. auto means the model can pick between generating a message or calling a function. Specifying a particular function via {"type: "function", "function": {"name": "my_function"}} forces the model to call that function. none is the default when no functions are present. auto is the default if functions are present. | - +| spring.ai.openai.chat.options.user | A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. | - +| spring.ai.openai.chat.options.functions | List of functions, identified by their names, to enable for function calling in a single prompt requests. Functions with those names must exist in the functionCallbacks registry. | - +| spring.ai.openai.chat.options.stream-usage | (For streaming only) Set to add an additional chunk with token usage statistics for the entire request. The `choices` field for this chunk is an empty array and all other chunks will also include a usage field, but with a null value. | false +| spring.ai.openai.chat.options.proxy-tool-calls | If true, the Spring AI will not handle the function calls internally, but will proxy them to the client. Then is the client's responsibility to handle the function calls, dispatch them to the appropriate function, and return the results. If false (the default), the Spring AI will handle the function calls internally. Applicable only for chat models with function calling support | false +|==== + +TIP: All properties prefixed with `spring.ai.openai.chat.options` can be overridden at runtime by adding a request specific <> to the `Prompt` call. + +== Runtime Options [[chat-options]] + +The https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-openai/src/main/java/org/springframework/ai/openai/OpenAiChatOptions.java[OpenAiChatOptions.java] provides model configurations, such as the model to use, the temperature, the frequency penalty, etc. + +On start-up, the default options can be configured with the `OpenAiChatModel(api, options)` constructor or the `spring.ai.openai.chat.options.*` properties. + +At run-time you can override the default options by adding new, request specific, options to the `Prompt` call. +For example to override the default model and temperature for a specific request: + +[source,java] +---- +ChatResponse response = chatModel.call( + new Prompt( + "Generate the names of 5 famous pirates.", + OpenAiChatOptions.builder() + .withModel("deepseek-chat") + .withTemperature(0.4) + .build() + )); +---- + +TIP: In addition to the model specific https://github.com/spring-projects/spring-ai/blob/main/models/spring-ai-openai/src/main/java/org/springframework/ai/openai/OpenAiChatOptions.java[OpenAiChatOptions] you can use a portable https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/prompt/ChatOptions.java[ChatOptions] instance, created with the https://github.com/spring-projects/spring-ai/blob/main/spring-ai-core/src/main/java/org/springframework/ai/chat/prompt/ChatOptionsBuilder.java[ChatOptionsBuilder#builder()]. + +== Function Calling + +NOTE: The current version of the deepseek-chat model's Function Calling capabilitity is unstable, which may result in looped calls or empty responses. + +== Multimodal + +NOTE: Currently, the DeepSeek API doesn't support media content. + +== Sample Controller + +https://start.spring.io/[Create] a new Spring Boot project and add the `spring-ai-openai-spring-boot-starter` to your pom (or gradle) dependencies. + +Add a `application.properties` file, under the `src/main/resources` directory, to enable and configure the OpenAi chat model: + +[source,application.properties] +---- +spring.ai.openai.api-key= +spring.ai.openai.base-url=https://api.deepseek.com +spring.ai.openai.chat.options.model=deepseek-chat +spring.ai.openai.chat.options.temperature=0.7 + +# The DeepSeek API doesn't support embeddings, so we need to disable it. +spring.ai.openai.embedding.enabled=false +---- + +TIP: replace the `api-key` with your DeepSeek Api key. + +This will create a `OpenAiChatModel` implementation that you can inject into your class. +Here is an example of a simple `@Controller` class that uses the chat model for text generations. + +[source,java] +---- +@RestController +public class ChatController { + + private final OpenAiChatModel chatModel; + + @Autowired + public ChatController(OpenAiChatModel chatModel) { + this.chatModel = chatModel; + } + + @GetMapping("/ai/generate") + public Map generate(@RequestParam(value = "message", defaultValue = "Tell me a joke") String message) { + return Map.of("generation", this.chatModel.call(message)); + } + + @GetMapping("/ai/generateStream") + public Flux generateStream(@RequestParam(value = "message", defaultValue = "Tell me a joke") String message) { + Prompt prompt = new Prompt(new UserMessage(message)); + return this.chatModel.stream(prompt); + } +} +---- + +== References + +* https://api-docs.deepseek.com/[Documentation Home] +* https://api-docs.deepseek.com/quick_start/error_codes[Error Codes] +* https://api-docs.deepseek.com/quick_start/rate_limit[Rate Limits]