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This package contains all Java interfaces and annotations to interact with Microsoft Azure functions java runtime.

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/**
 * Copyright (c) Microsoft Corporation. All rights reserved.
 * Licensed under the MIT License. See License.txt in the project root for
 * license information.
 */

package com.microsoft.azure.functions.openai.annotation.textcompletion;

import com.microsoft.azure.functions.annotation.CustomBinding;

import java.lang.annotation.ElementType;
import java.lang.annotation.Retention;
import java.lang.annotation.RetentionPolicy;
import java.lang.annotation.Target;
 
/**
 * 
 * Assistant query input attribute which is used query the Assistant to get current state.
 * 
 * 
 * @since 1.0.0
 */
@Retention(RetentionPolicy.RUNTIME)
@Target(ElementType.PARAMETER)
@CustomBinding(direction = "in", name = "", type = "textCompletion")
public @interface TextCompletion {

    /**
     * The variable name used in function.json.
     * 
     * @return The variable name used in function.json.
     */
    String name();

    /**
     * The prompt to generate completions for, encoded as a string.
     *
     * @return The prompt string.
     */
    String prompt();

    /**
     * The ID of the model to use.
     *
     * @return The model ID.
     */
    String model() default "gpt-3.5-turbo";

    /**
     * The sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output
     * more random, while lower values like 0.2 will make it more focused and deterministic.
     * It's generally recommended to use this or {@link #topP()} but not both.
     *
     * @return The sampling temperature value.
     */
    String temperature() default "0.5";

    /**
     * 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.
     * It's generally recommended to use this or {@link #temperature()} but not both.
     *
     * @return The topP value.
     */
    String topP() default "";

    /**
     * The maximum number of tokens to generate in the completion.
     * The token count of your prompt plus max_tokens cannot exceed the model's context length.
     * Most models have a context length of 2048 tokens (except for the newest models, which support 4096).
     *
     * @return The maxTokens value.
     */
    String maxTokens() default "100";
 
 }