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Update ZhiPuAi model support

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- Added additional support for ZhiPuAi models including vision model GLM-4V
- Default model changed to GLM_4_Air and update documentation
- Added additional unit and integration tests
- Add documentation for vision model
This commit is contained in:
GR
2024-06-13 08:44:13 +08:00
committed by Mark Pollack
parent 172c7f1a1a
commit f989dfe06e
13 changed files with 409 additions and 23 deletions
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4
models/spring-ai-minimax/src/test/java/org/springframework/ai/minimax/api/MiniMaxApiIT.java
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@@ -43,7 +43,7 @@ public class MiniMaxApiIT {
void chatCompletionEntity() {
ChatCompletionMessage chatCompletionMessage = new ChatCompletionMessage("Hello world", Role.USER);
ResponseEntity<ChatCompletion> response = miniMaxApi
.chatCompletionEntity(new ChatCompletionRequest(List.of(chatCompletionMessage), "abab6.5g", 0.7f, false));
.chatCompletionEntity(new ChatCompletionRequest(List.of(chatCompletionMessage), "glm-4-air", 0.7f, false));
assertThat(response).isNotNull();
assertThat(response.getBody()).isNotNull();
@@ -53,7 +53,7 @@ public class MiniMaxApiIT {
void chatCompletionStream() {
ChatCompletionMessage chatCompletionMessage = new ChatCompletionMessage("Hello world", Role.USER);
Flux<ChatCompletionChunk> response = miniMaxApi
.chatCompletionStream(new ChatCompletionRequest(List.of(chatCompletionMessage), "abab6.5g", 0.7f, true));
.chatCompletionStream(new ChatCompletionRequest(List.of(chatCompletionMessage), "glm-4-air", 0.7f, true));
assertThat(response).isNotNull();
assertThat(response.collectList().block()).isNotNull();

5
models/spring-ai-zhipuai/src/main/java/org/springframework/ai/zhipuai/ZhiPuAiChatModel.java
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@@ -17,12 +17,11 @@ package org.springframework.ai.zhipuai;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.chat.model.Generation;
import org.springframework.ai.chat.model.StreamingChatModel;
import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
import org.springframework.ai.chat.prompt.ChatOptions;
import org.springframework.ai.chat.prompt.Prompt;
import org.springframework.ai.model.ModelOptionsUtils;
@@ -287,7 +286,7 @@ public class ZhiPuAiChatModel extends
if (mediaContentData instanceof byte[] bytes) {
// Assume the bytes are an image. So, convert the bytes to a base64 encoded
// following the prefix pattern.
return String.format("data:%s;base64,%s", mimeType.toString(), Base64.getEncoder().encodeToString(bytes));
return Base64.getEncoder().encodeToString(bytes);
}
else if (mediaContentData instanceof String text) {
// Assume the text is a URLs or a base64 encoded image prefixed by the user.

10
models/spring-ai-zhipuai/src/main/java/org/springframework/ai/zhipuai/ZhiPuAiChatOptions.java
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@@ -15,11 +15,6 @@
*/
package org.springframework.ai.zhipuai;
import java.util.ArrayList;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
import com.fasterxml.jackson.annotation.JsonIgnore;
import com.fasterxml.jackson.annotation.JsonInclude;
import com.fasterxml.jackson.annotation.JsonInclude.Include;
@@ -33,6 +28,11 @@ import org.springframework.ai.zhipuai.api.ZhiPuAiApi.FunctionTool;
import org.springframework.boot.context.properties.NestedConfigurationProperty;
import org.springframework.util.Assert;
import java.util.ArrayList;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
/**
* ZhiPuAiChatOptions represents the options for the ZhiPuAiChat model.
*

3
models/spring-ai-zhipuai/src/main/java/org/springframework/ai/zhipuai/ZhiPuAiImageModel.java
View File

@@ -17,10 +17,9 @@ package org.springframework.ai.zhipuai;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.ai.image.Image;
import org.springframework.ai.image.ImageModel;
import org.springframework.ai.image.ImageGeneration;
import org.springframework.ai.image.ImageModel;
import org.springframework.ai.image.ImageOptions;
import org.springframework.ai.image.ImagePrompt;
import org.springframework.ai.image.ImageResponse;

7
models/spring-ai-zhipuai/src/main/java/org/springframework/ai/zhipuai/api/ZhiPuAiApi.java
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@@ -18,7 +18,6 @@ package org.springframework.ai.zhipuai.api;
import com.fasterxml.jackson.annotation.JsonInclude;
import com.fasterxml.jackson.annotation.JsonInclude.Include;
import com.fasterxml.jackson.annotation.JsonProperty;
import org.springframework.ai.model.ModelDescription;
import org.springframework.ai.model.ModelOptionsUtils;
import org.springframework.ai.retry.RetryUtils;
@@ -49,7 +48,7 @@ import java.util.function.Predicate;
*/
public class ZhiPuAiApi {
public static final String DEFAULT_CHAT_MODEL = ChatModel.GLM_3_Turbo.getValue();
public static final String DEFAULT_CHAT_MODEL = ChatModel.GLM_4_Air.getValue();
public static final String DEFAULT_EMBEDDING_MODEL = EmbeddingModel.Embedding_2.getValue();
private static final Predicate<String> SSE_DONE_PREDICATE = "[DONE]"::equals;
@@ -115,6 +114,10 @@ public class ZhiPuAiApi {
*/
public enum ChatModel implements ModelDescription {
GLM_4("GLM-4"),
GLM_4V("glm-4v"),
GLM_4_Air("glm-4-air"),
GLM_4_AirX("glm-4-airx"),
GLM_4_Flash("glm-4-flash"),
GLM_3_Turbo("GLM-3-Turbo");
public final String value;

7
models/spring-ai-zhipuai/src/test/java/org/springframework/ai/zhipuai/api/ZhiPuAiApiIT.java
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@@ -17,7 +17,6 @@ package org.springframework.ai.zhipuai.api;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
import org.springframework.ai.zhipuai.api.ZhiPuAiApi.ChatCompletion;
import org.springframework.ai.zhipuai.api.ZhiPuAiApi.ChatCompletionChunk;
import org.springframework.ai.zhipuai.api.ZhiPuAiApi.ChatCompletionMessage;
@@ -44,8 +43,8 @@ public class ZhiPuAiApiIT {
@Test
void chatCompletionEntity() {
ChatCompletionMessage chatCompletionMessage = new ChatCompletionMessage("Hello world", Role.USER);
ResponseEntity<ChatCompletion> response = zhiPuAiApi.chatCompletionEntity(
new ChatCompletionRequest(List.of(chatCompletionMessage), "glm-3-turbo", 0.7f, false));
ResponseEntity<ChatCompletion> response = zhiPuAiApi
.chatCompletionEntity(new ChatCompletionRequest(List.of(chatCompletionMessage), "glm-4-air", 0.7f, false));
assertThat(response).isNotNull();
assertThat(response.getBody()).isNotNull();
@@ -55,7 +54,7 @@ public class ZhiPuAiApiIT {
void chatCompletionStream() {
ChatCompletionMessage chatCompletionMessage = new ChatCompletionMessage("Hello world", Role.USER);
Flux<ChatCompletionChunk> response = zhiPuAiApi
.chatCompletionStream(new ChatCompletionRequest(List.of(chatCompletionMessage), "glm-3-turbo", 0.7f, true));
.chatCompletionStream(new ChatCompletionRequest(List.of(chatCompletionMessage), "glm-4-air", 0.7f, true));
assertThat(response).isNotNull();
assertThat(response.collectList().block()).isNotNull();

53
models/spring-ai-zhipuai/src/test/java/org/springframework/ai/zhipuai/chat/ActorsFilms.java Normal file
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@@ -0,0 +1,53 @@
/*
* Copyright 2023 - 2024 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.zhipuai.chat;
import java.util.List;
/**
* @author Geng Rong
*/
public class ActorsFilms {
private String actor;
private List<String> movies;
public ActorsFilms() {
}
public String getActor() {
return actor;
}
public void setActor(String actor) {
this.actor = actor;
}
public List<String> getMovies() {
return movies;
}
public void setMovies(List<String> movies) {
this.movies = movies;
}
@Override
public String toString() {
return "ActorsFilms{" + "actor='" + actor + '\'' + ", movies=" + movies + '}';
}
}

335
models/spring-ai-zhipuai/src/test/java/org/springframework/ai/zhipuai/chat/ZhiPuAiChatModelIT.java Normal file
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@@ -0,0 +1,335 @@
/*
* Copyright 2023 - 2024 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.zhipuai.chat;
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 org.springframework.ai.chat.messages.AssistantMessage;
import org.springframework.ai.chat.messages.Media;
import org.springframework.ai.chat.messages.Message;
import org.springframework.ai.chat.messages.UserMessage;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.chat.model.Generation;
import org.springframework.ai.chat.model.StreamingChatModel;
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.FunctionCallbackWrapper;
import org.springframework.ai.zhipuai.ZhiPuAiChatOptions;
import org.springframework.ai.zhipuai.ZhiPuAiTestConfiguration;
import org.springframework.ai.zhipuai.api.MockWeatherService;
import org.springframework.ai.zhipuai.api.ZhiPuAiApi;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.core.convert.support.DefaultConversionService;
import org.springframework.core.io.ClassPathResource;
import org.springframework.core.io.Resource;
import org.springframework.util.MimeTypeUtils;
import reactor.core.publisher.Flux;
import java.io.IOException;
import java.net.URL;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Map;
import java.util.Objects;
import java.util.stream.Collectors;
import static org.assertj.core.api.Assertions.assertThat;
/**
* @author Geng Rong
*/
@SpringBootTest(classes = ZhiPuAiTestConfiguration.class)
@EnabledIfEnvironmentVariable(named = "ZHIPU_AI_API_KEY", matches = ".+")
class ZhiPuAiChatModelIT {
@Autowired
protected ChatModel chatModel;
@Autowired
protected StreamingChatModel streamingChatModel;
private static final Logger logger = LoggerFactory.getLogger(ZhiPuAiChatModelIT.class);
@Value("classpath:/prompts/system-message.st")
private Resource systemResource;
@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(systemResource);
Message systemMessage = systemPromptTemplate.createMessage(Map.of("name", "Bob", "voice", "pirate"));
Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
ChatResponse response = chatModel.call(prompt);
assertThat(response.getResults()).hasSize(1);
assertThat(response.getResults().get(0).getOutput().getContent()).contains("Blackbeard");
// needs fine tuning... evaluateQuestionAndAnswer(request, response, false);
}
@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(systemResource);
Message systemMessage = systemPromptTemplate.createMessage(Map.of("name", "Bob", "voice", "pirate"));
Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
Flux<ChatResponse> flux = streamingChatModel.stream(prompt);
List<ChatResponse> responses = flux.collectList().block();
assertThat(responses.size()).isGreaterThan(1);
String stitchedResponseContent = responses.stream()
.map(ChatResponse::getResults)
.flatMap(List::stream)
.map(Generation::getOutput)
.map(AssistantMessage::getContent)
.collect(Collectors.joining());
assertThat(stitchedResponseContent).contains("Blackbeard");
}
@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<String> list = outputConverter.convert(generation.getOutput().getContent());
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", "an array of numbers from 1 to 9 under they key name 'numbers'", "format", format));
Prompt prompt = new Prompt(promptTemplate.createMessage());
Generation generation = chatModel.call(prompt).getResult();
Map<String, Object> result = outputConverter.convert(generation.getOutput().getContent());
assertThat(result.get("numbers")).isEqualTo(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9));
}
@Test
void beanOutputConverter() {
BeanOutputConverter<ActorsFilms> 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 = chatModel.call(prompt).getResult();
ActorsFilms actorsFilms = outputConverter.convert(generation.getOutput().getContent());
}
record ActorsFilmsRecord(String actor, List<String> movies) {
}
@Test
void beanOutputConverterRecords() {
BeanOutputConverter<ActorsFilmsRecord> outputConverter = new BeanOutputConverter<>(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 = chatModel.call(prompt).getResult();
ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
logger.info("" + actorsFilms);
assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");
assertThat(actorsFilms.movies()).hasSize(5);
}
@Test
void beanStreamOutputConverterRecords() {
BeanOutputConverter<ActorsFilmsRecord> outputConverter = new BeanOutputConverter<>(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 = Objects
.requireNonNull(streamingChatModel.stream(prompt).collectList().block())
.stream()
.map(ChatResponse::getResults)
.flatMap(List::stream)
.map(Generation::getOutput)
.map(AssistantMessage::getContent)
.collect(Collectors.joining());
ActorsFilmsRecord actorsFilms = outputConverter.convert(generationTextFromStream);
logger.info("" + actorsFilms);
assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");
assertThat(actorsFilms.movies()).hasSize(5);
}
@Test
void functionCallTest() {
UserMessage userMessage = new UserMessage("What's the weather like in San Francisco, Tokyo, and Paris?");
List<Message> messages = new ArrayList<>(List.of(userMessage));
var promptOptions = ZhiPuAiChatOptions.builder()
.withModel(ZhiPuAiApi.ChatModel.GLM_4.getValue())
.withFunctionCallbacks(List.of(FunctionCallbackWrapper.builder(new MockWeatherService())
.withName("getCurrentWeather")
.withDescription("Get the weather in location")
.withResponseConverter((response) -> "" + response.temp() + response.unit())
.build()))
.build();
ChatResponse response = chatModel.call(new Prompt(messages, promptOptions));
logger.info("Response: {}", response);
assertThat(response.getResult().getOutput().getContent()).containsAnyOf("30.0", "30");
assertThat(response.getResult().getOutput().getContent()).containsAnyOf("10.0", "10");
assertThat(response.getResult().getOutput().getContent()).containsAnyOf("15.0", "15");
}
@Test
void streamFunctionCallTest() {
UserMessage userMessage = new UserMessage("What's the weather like in San Francisco, Tokyo, and Paris?");
List<Message> messages = new ArrayList<>(List.of(userMessage));
var promptOptions = ZhiPuAiChatOptions.builder()
.withFunctionCallbacks(List.of(FunctionCallbackWrapper.builder(new MockWeatherService())
.withName("getCurrentWeather")
.withDescription("Get the weather in location")
.withResponseConverter((response) -> "" + response.temp() + response.unit())
.build()))
.build();
Flux<ChatResponse> response = streamingChatModel.stream(new Prompt(messages, promptOptions));
String content = Objects.requireNonNull(response.collectList().block())
.stream()
.map(ChatResponse::getResults)
.flatMap(List::stream)
.map(Generation::getOutput)
.map(AssistantMessage::getContent)
.collect(Collectors.joining());
logger.info("Response: {}", content);
assertThat(content).containsAnyOf("30.0", "30");
assertThat(content).containsAnyOf("10.0", "10");
assertThat(content).containsAnyOf("15.0", "15");
}
@ParameterizedTest(name = "{0} : {displayName} ")
@ValueSource(strings = { "glm-4v" })
void multiModalityEmbeddedImage(String modelName) throws IOException {
var imageData = new ClassPathResource("/test.png");
var userMessage = new UserMessage("Explain what do you see on this picture?",
List.of(new Media(MimeTypeUtils.IMAGE_PNG, imageData)));
var response = chatModel
.call(new Prompt(List.of(userMessage), ZhiPuAiChatOptions.builder().withModel(modelName).build()));
logger.info(response.getResult().getOutput().getContent());
assertThat(response.getResult().getOutput().getContent()).contains("bananas", "apple");
assertThat(response.getResult().getOutput().getContent()).containsAnyOf("bowl", "basket");
}
@ParameterizedTest(name = "{0} : {displayName} ")
@ValueSource(strings = { "glm-4v" })
void multiModalityImageUrl(String modelName) throws IOException {
var userMessage = new UserMessage("Explain what do you see on this picture?", List
.of(new Media(MimeTypeUtils.IMAGE_PNG,
new URL("https://docs.spring.io/spring-ai/reference/1.0-SNAPSHOT/_images/multimodal.test.png"))));
ChatResponse response = chatModel
.call(new Prompt(List.of(userMessage), ZhiPuAiChatOptions.builder().withModel(modelName).build()));
logger.info(response.getResult().getOutput().getContent());
assertThat(response.getResult().getOutput().getContent()).contains("bananas", "apple");
assertThat(response.getResult().getOutput().getContent()).containsAnyOf("bowl", "basket");
}
@Test
void streamingMultiModalityImageUrl() throws IOException {
var userMessage = new UserMessage("Explain what do you see on this picture?", List
.of(new Media(MimeTypeUtils.IMAGE_PNG,
new URL("https://docs.spring.io/spring-ai/reference/1.0-SNAPSHOT/_images/multimodal.test.png"))));
Flux<ChatResponse> response = streamingChatModel.stream(new Prompt(List.of(userMessage),
ZhiPuAiChatOptions.builder().withModel(ZhiPuAiApi.ChatModel.GLM_4V.getValue()).build()));
String content = Objects.requireNonNull(response.collectList().block())
.stream()
.map(ChatResponse::getResults)
.flatMap(List::stream)
.map(Generation::getOutput)
.map(AssistantMessage::getContent)
.collect(Collectors.joining());
logger.info("Response: {}", content);
assertThat(content).contains("bananas", "apple");
assertThat(content).containsAnyOf("bowl", "basket");
}
}

1
models/spring-ai-zhipuai/src/test/java/org/springframework/ai/zhipuai/embedding/EmbeddingIT.java
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@@ -17,7 +17,6 @@ package org.springframework.ai.zhipuai.embedding;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
import org.springframework.ai.embedding.EmbeddingResponse;
import org.springframework.ai.zhipuai.ZhiPuAiEmbeddingModel;
import org.springframework.beans.factory.annotation.Autowired;

1
models/spring-ai-zhipuai/src/test/java/org/springframework/ai/zhipuai/image/ZhiPuAiImageModelIT.java
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@@ -17,7 +17,6 @@ package org.springframework.ai.zhipuai.image;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
import org.springframework.ai.image.Image;
import org.springframework.ai.image.ImageModel;
import org.springframework.ai.image.ImageOptionsBuilder;

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4
spring-ai-docs/src/main/antora/modules/ROOT/pages/api/chat/zhipuai-chat.adoc
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@@ -90,7 +90,7 @@ The prefix `spring.ai.zhipuai.chat` is the property prefix that lets you configu
| spring.ai.zhipuai.chat.enabled | Enable ZhiPuAI chat model. | true
| spring.ai.zhipuai.chat.base-url | Optional overrides the spring.ai.zhipuai.base-url to provide chat specific url | https://open.bigmodel.cn/api/paas
| spring.ai.zhipuai.chat.api-key | Optional overrides the spring.ai.zhipuai.api-key to provide chat specific api-key | -
| spring.ai.zhipuai.chat.options.model | This is the ZhiPuAI Chat model to use | `GLM-3-Turbo` (the `GLM-3-Turbo`, `GLM-4`, and `GLM-4V` point to the latest model versions)
| spring.ai.zhipuai.chat.options.model | This is the ZhiPuAI Chat model to use | `GLM-3-Turbo` (the `GLM-3-Turbo`, `GLM-4`, `GLM-4-Air`, `GLM-4-AirX`, `GLM-4-Flash`, and `GLM-4V` point to the latest model versions)
| spring.ai.zhipuai.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.zhipuai.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. | 0.7
| spring.ai.zhipuai.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. | 1.0
@@ -139,7 +139,7 @@ Add a `application.properties` file, under the `src/main/resources` directory, t
[source,application.properties]
----
spring.ai.zhipuai.api-key=YOUR_API_KEY
spring.ai.zhipuai.chat.options.model=glm-3-turbo
spring.ai.zhipuai.chat.options.model=glm-4-air
spring.ai.zhipuai.chat.options.temperature=0.7
----

2
spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/zhipuai/ZhiPuAiChatProperties.java
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@@ -28,7 +28,7 @@ public class ZhiPuAiChatProperties extends ZhiPuAiParentProperties {
public static final String CONFIG_PREFIX = "spring.ai.zhipuai.chat";
public static final String DEFAULT_CHAT_MODEL = ZhiPuAiApi.ChatModel.GLM_3_Turbo.value;
public static final String DEFAULT_CHAT_MODEL = ZhiPuAiApi.ChatModel.GLM_4_Air.value;
private static final Double DEFAULT_TEMPERATURE = 0.7;