ZhiPu AI

ZhiPu AI is a platform to provide model service including text generation, text embedding, image generation and so on. You can refer to ZhiPu AI Open Platform for more details. LangChain4j integrates with ZhiPu AI by using HTTP endpoint. We are consider migrating it from HTTP endpoint to official SDK and are appreciated of any help!

Maven Dependency

You can use ZhiPu AI with LangChain4j in plain Java or Spring Boot applications.

Plain Java

note

Since 1.0.0-alpha1, langchain4j-zhipu-ai has migrated to langchain4j-community and is renamed to langchain4j-community-zhipu-ai

Before 1.0.0-alpha1:

<dependency>
    <groupId>dev.langchain4j</groupId>
    <artifactId>langchain4j-zhipu-ai</artifactId>
    <version>${previous version here}</version>
</dependency>

1.0.0-alpha1 and later:

<dependency>
    <groupId>dev.langchain4j</groupId>
    <artifactId>langchain4j-community-zhipu-ai</artifactId>
    <version>1.0.0-beta1</version>
</dependency>

Or, you can use BOM to manage dependencies consistently:

<dependencyManagement>
    <dependency>
        <groupId>dev.langchain4j</groupId>
        <artifactId>langchain4j-community-bom</artifactId>
        <version>1.0.0-beta1</version>
        <typ>pom</typ>
        <scope>import</scope>
    </dependency>
</dependencyManagement>

Configurable parameters

ZhipuAiChatModel

ZhipuAiChatModel has following parameters to configure when you initialize it:

Property	Description	Default Value
baseUrl	The URL to connect to. You can use HTTP or websocket to connect to DashScope	https://open.bigmodel.cn/
apiKey	The API Key
model	The model to use.	glm-4-flash
topP	The probability threshold for kernel sampling controls the diversity of texts generated by the model. the higher the top_p, the more diverse the generated texts, and vice versa. Value range: (0, 1.0]. We generally recommend altering this or temperature but not both.
maxRetries	The maximum retry times to request	3
temperature	Sampling temperature that controls the diversity of the text generated by the model. the higher the temperature, the more diverse the generated text, and vice versa. Value range: [0, 2)	0.7
stops	With the stop parameter, the model will automatically stop generating text when it is about to contain the specified string or token_id.
maxToken	The maximum number of tokens returned by this request.	512
listeners	Listeners that listen for request, response and errors.
callTimeout	OKHttp timeout config for request
connectTimeout	OKHttp timeout config for request
writeTimeout	OKHttp timeout config for request
readTimeout	OKHttp timeout config for request
logRequests	Whether to log request or not	false
logResponses	Whether to log response or not	false

ZhipuAiStreamingChatModel

Same as ZhipuAiChatModel, except maxRetries.

Examples

Plain Java

You can initialize ZhipuAiChatModel by using following code:

ChatLanguageModel qwenModel = ZhipuAiChatModel.builder()
                    .apiKey("You API key here")
                    .callTimeout(Duration.ofSeconds(60))
                    .connectTimeout(Duration.ofSeconds(60))
                    .writeTimeout(Duration.ofSeconds(60))
                    .readTimeout(Duration.ofSeconds(60))
                    .build();

Or more custom for other parameters:

ChatLanguageModel qwenModel = ZhipuAiChatModel.builder()
                    .apiKey("You API key here")
                    .model("glm-4")
                    .temperature(0.6)
                    .maxToken(1024)
                    .maxRetries(1)
                    .callTimeout(Duration.ofSeconds(60))
                    .connectTimeout(Duration.ofSeconds(60))
                    .writeTimeout(Duration.ofSeconds(60))
                    .readTimeout(Duration.ofSeconds(60))
                    .build();

More Examples

You can check more examples in:

• ZhipuAiChatModelIT
• ZhipuAiStreamingChatModelIT