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feat: add Azure OpenAi LLM module (#134)
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‎dat-cli/pom.xml‎

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<artifactId>dat-llm-xinference</artifactId>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>cn.datask</groupId>
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<artifactId>dat-llm-azure-openai</artifactId>
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<version>${project.version}</version>
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</dependency>
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<!-- DAT Database Adapter -->
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<dependency>

‎dat-llms/dat-llm-azure-openai/pom.xml‎

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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
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xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
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<modelVersion>4.0.0</modelVersion>
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<parent>
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<groupId>cn.datask</groupId>
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<artifactId>dat-llms</artifactId>
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<version>${revision}</version>
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</parent>
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<artifactId>dat-llm-azure-openai</artifactId>
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<name>DAT : LLMs : Azure OpenAi</name>
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<dependencies>
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<dependency>
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<groupId>cn.datask</groupId>
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<artifactId>dat-core</artifactId>
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<version>${project.version}</version>
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</dependency>
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<dependency>
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<groupId>dev.langchain4j</groupId>
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<artifactId>langchain4j-azure-open-ai</artifactId>
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<version>${langchain4j.vserion}</version>
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</dependency>
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</dependencies>
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</project>

‎dat-llms/dat-llm-azure-openai/src/main/java/ai/dat/llm/azure/AzureOpenAiChatModelFactory.java‎

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package ai.dat.llm.azure;
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import ai.dat.core.configuration.ConfigOption;
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import ai.dat.core.configuration.ConfigOptions;
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import ai.dat.core.configuration.ReadableConfig;
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import ai.dat.core.factories.ChatModelFactory;
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import ai.dat.core.utils.FactoryUtil;
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import com.google.common.base.Preconditions;
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import dev.langchain4j.model.azure.AzureOpenAiChatModel;
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import dev.langchain4j.model.azure.AzureOpenAiStreamingChatModel;
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import dev.langchain4j.model.chat.ChatModel;
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import dev.langchain4j.model.chat.StreamingChatModel;
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import dev.langchain4j.model.chat.request.ResponseFormat;
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import java.time.Duration;
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import java.util.LinkedHashSet;
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import java.util.List;
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import java.util.Map;
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import java.util.Set;
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/**
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*
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*/
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public class AzureOpenAiChatModelFactory implements ChatModelFactory {
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public static final String IDENTIFIER = "azure-openai";
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public static final ConfigOption<String> ENDPOINT =
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ConfigOptions.key("endpoint")
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.stringType()
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.noDefaultValue()
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.withDescription("""
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Supported Azure OpenAI endpoints
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(protocol and hostname, for example: https://aoairesource.openai.azure.com. \
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Replace "aoairesource" with your Azure OpenAI resource name).
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https://{your-resource-name}.openai.azure.com
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""");
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public static final ConfigOption<String> DEPLOYMENT_ID =
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ConfigOptions.key("deployment-id")
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.stringType()
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.noDefaultValue()
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.withDescription("Deployment ID of the model which was deployed.");
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public static final ConfigOption<String> API_VERSION =
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ConfigOptions.key("api-version")
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.stringType()
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.noDefaultValue()
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.withDescription("The API version of Azure OpenAI.");
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public static final ConfigOption<String> API_KEY =
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ConfigOptions.key("api-key")
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.stringType()
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.noDefaultValue()
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.withDescription("Provide Azure OpenAI API key here.");
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public static final ConfigOption<Double> TEMPERATURE =
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ConfigOptions.key("temperature")
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.doubleType()
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.noDefaultValue()
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.withDescription("Controls the randomness of the generated responses. " +
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"Higher values (e.g., 1.0) result in more diverse output, " +
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"while lower values (e.g., 0.2) produce more deterministic responses.");
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public static final ConfigOption<Double> TOP_P =
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ConfigOptions.key("top-p")
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.doubleType()
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.noDefaultValue()
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.withDescription("Controls the diversity of the generated responses by setting a threshold " +
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"for the cumulative probability of top tokens.");
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public static final ConfigOption<Duration> TIMEOUT =
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ConfigOptions.key("timeout")
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.durationType()
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.noDefaultValue()
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.withDescription("The maximum time allowed for the API call to complete.");
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public static final ConfigOption<Integer> MAX_RETRIES =
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ConfigOptions.key("max-retries")
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.intType()
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.defaultValue(2)
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.withDescription("The maximum number of retries in case of API call failure.");
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public static final ConfigOption<Integer> MAX_TOKENS =
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ConfigOptions.key("max-tokens")
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.intType()
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.defaultValue(4096)
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.withDescription("Azure OpenAI LLM model maximum tokens");
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public static final ConfigOption<Long> SEED =
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ConfigOptions.key("seed")
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.longType()
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.noDefaultValue()
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.withDescription("Azure OpenAI LLM model seed");
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public static final ConfigOption<String> USER =
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ConfigOptions.key("user")
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.stringType()
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.noDefaultValue()
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.withDescription("Azure OpenAI user");
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public static final ConfigOption<List<String>> STOP =
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ConfigOptions.key("stop")
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.stringType()
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.asList()
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.noDefaultValue()
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.withDescription("A list of strings that, if generated, will mark the end of the response.");
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public static final ConfigOption<Boolean> LOG_REQUESTS_AND_RESPONSES =
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ConfigOptions.key("log-requests-and-responses")
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.booleanType()
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.defaultValue(false)
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.withDescription("Whether to print the LLM requests and responses log");
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public static final ConfigOption<String> RESPONSE_FORMAT =
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ConfigOptions.key("response-format")
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.stringType()
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.noDefaultValue()
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.withDescription("OpenAI LLM response format. Supported: text, json");
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public static final ConfigOption<Boolean> STRICT_JSON_SCHEMA =
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ConfigOptions.key("strict-json-schema")
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.booleanType()
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.defaultValue(false)
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.withDescription("Whether to output strict json schema");
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public static final ConfigOption<Map<String, String>> CUSTOM_HEADERS =
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ConfigOptions.key("custom-headers")
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.mapType()
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.noDefaultValue()
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.withDescription("Custom HTTP headers. " +
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"For example: {\"content-type\": \"application/json\", " +
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"\"accept\": \"application/json, text/event-stream\"}");
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@Override
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public String factoryIdentifier() {
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return IDENTIFIER;
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}
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@Override
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public Set<ConfigOption<?>> requiredOptions() {
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return new LinkedHashSet<>(List.of(ENDPOINT, DEPLOYMENT_ID, API_VERSION, API_KEY));
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}
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@Override
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public Set<ConfigOption<?>> optionalOptions() {
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return new LinkedHashSet<>(List.of(TEMPERATURE, TOP_P, TIMEOUT,
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MAX_RETRIES, MAX_TOKENS, LOG_REQUESTS_AND_RESPONSES,
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RESPONSE_FORMAT, STRICT_JSON_SCHEMA, STOP, SEED, USER, CUSTOM_HEADERS));
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}
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@Override
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public ChatModel create(ReadableConfig config) {
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FactoryUtil.validateFactoryOptions(this, config);
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validateConfigOptions(config);
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String endpoint = config.get(ENDPOINT);
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String deploymentId = config.get(DEPLOYMENT_ID);
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String apiVersion = config.get(API_VERSION);
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String apiKey = config.get(API_KEY);
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AzureOpenAiChatModel.Builder builder = AzureOpenAiChatModel.builder()
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.endpoint(endpoint)
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.deploymentName(deploymentId)
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.serviceVersion(apiVersion)
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.apiKey(apiKey);
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config.getOptional(TEMPERATURE).ifPresent(builder::temperature);
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config.getOptional(TOP_P).ifPresent(builder::topP);
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config.getOptional(TIMEOUT).ifPresent(builder::timeout);
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config.getOptional(MAX_RETRIES).ifPresent(builder::maxRetries);
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config.getOptional(MAX_TOKENS).ifPresent(builder::maxTokens);
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config.getOptional(RESPONSE_FORMAT).ifPresent(format -> {
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ResponseFormat responseFormat = format.equalsIgnoreCase("JSON")
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? ResponseFormat.JSON : ResponseFormat.TEXT;
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builder.responseFormat(responseFormat);
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});
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config.getOptional(LOG_REQUESTS_AND_RESPONSES).ifPresent(builder::logRequestsAndResponses);
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config.getOptional(STRICT_JSON_SCHEMA).ifPresent(builder::strictJsonSchema);
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config.getOptional(STOP).ifPresent(builder::stop);
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config.getOptional(SEED).ifPresent(builder::seed);
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config.getOptional(USER).ifPresent(builder::user);
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config.getOptional(CUSTOM_HEADERS).ifPresent(builder::customHeaders);
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return builder.build();
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}
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@Override
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public StreamingChatModel createStream(ReadableConfig config) {
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FactoryUtil.validateFactoryOptions(this, config);
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validateConfigOptions(config);
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String endpoint = config.get(ENDPOINT);
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String deploymentId = config.get(DEPLOYMENT_ID);
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String apiVersion = config.get(API_VERSION);
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String apiKey = config.get(API_KEY);
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AzureOpenAiStreamingChatModel.Builder builder = AzureOpenAiStreamingChatModel.builder()
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.endpoint(endpoint)
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.deploymentName(deploymentId)
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.serviceVersion(apiVersion)
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.apiKey(apiKey);
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config.getOptional(TEMPERATURE).ifPresent(builder::temperature);
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config.getOptional(TOP_P).ifPresent(builder::topP);
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config.getOptional(TIMEOUT).ifPresent(builder::timeout);
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config.getOptional(MAX_RETRIES).ifPresent(builder::maxRetries);
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config.getOptional(MAX_TOKENS).ifPresent(builder::maxTokens);
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config.getOptional(RESPONSE_FORMAT).ifPresent(format -> {
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ResponseFormat responseFormat = format.equalsIgnoreCase("JSON")
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? ResponseFormat.JSON : ResponseFormat.TEXT;
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builder.responseFormat(responseFormat);
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});
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config.getOptional(LOG_REQUESTS_AND_RESPONSES).ifPresent(builder::logRequestsAndResponses);
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config.getOptional(STRICT_JSON_SCHEMA).ifPresent(builder::strictJsonSchema);
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config.getOptional(STOP).ifPresent(builder::stop);
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config.getOptional(SEED).ifPresent(builder::seed);
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config.getOptional(USER).ifPresent(builder::user);
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config.getOptional(CUSTOM_HEADERS).ifPresent(builder::customHeaders);
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return builder.build();
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}
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private void validateConfigOptions(ReadableConfig config) {
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config.getOptional(TEMPERATURE)
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.ifPresent(t -> Preconditions.checkArgument(t >= 0.0 && t <= 2.0,
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"'" + TEMPERATURE.key() + "' value must be between 0.0 and 2.0"));
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config.getOptional(TOP_P)
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.ifPresent(v -> Preconditions.checkArgument(v > 0.0 && v <= 1.0,
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"'" + TOP_P.key() + "' value must > 0.0 and <= 1.0"));
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Integer maxRetries = config.get(MAX_RETRIES);
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Preconditions.checkArgument(maxRetries >= 0,
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"'" + MAX_RETRIES.key() + "' value must be greater than or equal to 0");
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Integer maxTokens = config.get(MAX_TOKENS);
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Preconditions.checkArgument(maxTokens > 0,
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"'" + MAX_TOKENS.key() + "' value must be greater than 0");
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}
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}

‎dat-llms/dat-llm-azure-openai/src/main/resources/META-INF/services/ai.dat.core.factories.ChatModelFactory‎

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ai.dat.llm.azure.AzureOpenAiChatModelFactory

‎dat-llms/pom.xml‎

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<module>dat-llm-ollama</module>
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<module>dat-llm-gemini</module>
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<module>dat-llm-xinference</module>
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<module>dat-llm-azure-openai</module>
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</modules>
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</project>

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