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‎README.md

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@@ -13,6 +13,7 @@ A community-maintained easy-to-use Java/Kotlin OpenAI API for ChatGPT, Text Comp
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## Features
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* [Completions](https://platform.openai.com/docs/api-reference/completions)
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* [Chat Completions](https://platform.openai.com/docs/api-reference/chat)
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* [Azure OpenAI](https://learn.microsoft.com/en-us/azure/cognitive-services/openai/reference) support via `AzureOpenAI` class
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## Installation
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For Kotlin DSL (`build.gradle.kts`), add this to your dependencies block:
@@ -85,6 +86,7 @@ public class JavaChatTest {
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}
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}
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```
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To use the Azure OpenAI API, use the `AzureOpenAI` class instead of `OpenAI`.
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> **Note**: OpenAI recommends using environment variables for your API token
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([Read more](https://help.openai.com/en/articles/5112595-best-practices-for-api-key-safety)).
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‎src/main/kotlin/com/cjcrafter/openai/AzureOpenAI.kt

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package com.cjcrafter.openai
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import okhttp3.OkHttpClient
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import okhttp3.Request
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import okhttp3.RequestBody
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import okhttp3.RequestBody.Companion.toRequestBody
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/**
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* The Azure OpenAI API client.
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*
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* See {@link OpenAI} for more information.
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*
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* This class constructs url in the form of: https://<azureBaseUrl>/openai/deployments/<modelName>/<endpoint>?api-version=<apiVersion>
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*
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* @property azureBaseUrl The base URL for the Azure OpenAI API. Usually https://<your_resource_group>.openai.azure.com
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* @property apiVersion The API version to use. Defaults to 2023-03-15-preview.
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* @property modelName The model name to use. This is the name of the model deployed to Azure.
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*/
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class AzureOpenAI @JvmOverloads constructor(
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apiKey: String,
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organization: String? = null,
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client: OkHttpClient = OkHttpClient(),
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private val azureBaseUrl: String = "",
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private val apiVersion: String = "2023-03-15-preview",
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private val modelName: String = ""
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) : OpenAI(apiKey, organization, client) {
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override fun buildRequest(request: Any, endpoint: String): Request {
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val json = gson.toJson(request)
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val body: RequestBody = json.toRequestBody(mediaType)
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return Request.Builder()
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.url("$azureBaseUrl/openai/deployments/$modelName/$endpoint?api-version=$apiVersion")
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.addHeader("Content-Type", "application/json")
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.addHeader("api-key", apiKey)
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.apply { if (organization != null) addHeader("OpenAI-Organization", organization) }
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.post(body).build()
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}
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}

‎src/main/kotlin/com/cjcrafter/openai/OpenAI.kt

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@@ -52,15 +52,15 @@ import java.util.function.Consumer
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* @property client Controls proxies, timeouts, etc.
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* @constructor Create a ChatBot for responding to requests.
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*/
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class OpenAI @JvmOverloads constructor(
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private val apiKey: String,
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private val organization: String? = null,
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open class OpenAI @JvmOverloads constructor(
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protected val apiKey: String,
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protected val organization: String? = null,
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private val client: OkHttpClient = OkHttpClient()
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) {
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private val mediaType = "application/json; charset=utf-8".toMediaType()
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private val gson = createGson()
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protected val mediaType = "application/json; charset=utf-8".toMediaType()
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protected val gson = createGson()
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private fun buildRequest(request: Any, endpoint: String): Request {
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protected open fun buildRequest(request: Any, endpoint: String): Request {
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val json = gson.toJson(request)
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val body: RequestBody = json.toRequestBody(mediaType)
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return Request.Builder()
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val httpRequest = buildRequest(request, COMPLETIONS_ENDPOINT)
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try {
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val httpResponse = client.newCall(httpRequest).execute();
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val httpResponse = client.newCall(httpRequest).execute()
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lateinit var response: CompletionResponse
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OpenAICallback(true, { throw it }) {
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response = gson.fromJson(it, CompletionResponse::class.java)

‎src/test/java/JavaTestAzure.java

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import com.cjcrafter.openai.AzureOpenAI;
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import com.cjcrafter.openai.OpenAI;
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import com.cjcrafter.openai.chat.ChatMessage;
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import com.cjcrafter.openai.chat.ChatRequest;
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import com.cjcrafter.openai.chat.ChatResponse;
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import com.cjcrafter.openai.completions.CompletionRequest;
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import com.cjcrafter.openai.exception.OpenAIError;
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import io.github.cdimascio.dotenv.Dotenv;
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import java.util.ArrayList;
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import java.util.Collections;
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import java.util.List;
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import java.util.Scanner;
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public class JavaTestAzure {
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// Colors for pretty formatting
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public static final String RESET = "\033[0m";
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public static final String BLACK = "\033[0;30m";
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public static final String RED = "\033[0;31m";
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public static final String GREEN = "\033[0;32m";
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public static final String YELLOW = "\033[0;33m";
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public static final String BLUE = "\033[0;34m";
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public static final String PURPLE = "\033[0;35m";
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public static final String CYAN = "\033[0;36m";
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public static final String WHITE = "\033[0;37m";
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public static void main(String[] args) throws OpenAIError {
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Scanner scanner = new Scanner(System.in);
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// Add test cases for AzureOpenAI
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System.out.println(GREEN + " 9. Azure Completion (create, sync)");
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System.out.println(GREEN + " 10. Azure Completion (stream, sync)");
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System.out.println(GREEN + " 11. Azure Completion (create, async)");
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System.out.println(GREEN + " 12. Azure Completion (stream, async)");
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System.out.println(GREEN + " 13. Azure Chat (create, sync)");
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System.out.println(GREEN + " 14. Azure Chat (stream, sync)");
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System.out.println(GREEN + " 15. Azure Chat (create, async)");
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System.out.println(GREEN + " 16. Azure Chat (stream, async)");
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System.out.println();
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// Determine which method to call
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switch (scanner.nextLine()) {
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// ...
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case "9":
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doCompletionAzure(false, false);
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break;
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case "10":
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doCompletionAzure(true, false);
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break;
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case "11":
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doCompletionAzure(false, true);
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break;
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case "12":
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doCompletionAzure(true, true);
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break;
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case "13":
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doChatAzure(false, false);
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break;
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case "14":
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doChatAzure(true, false);
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break;
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case "15":
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doChatAzure(false, true);
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break;
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case "16":
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doChatAzure(true, true);
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break;
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default:
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System.err.println("Invalid option");
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break;
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}
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}
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public static void doCompletionAzure(boolean stream, boolean async) throws OpenAIError {
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Scanner scan = new Scanner(System.in);
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System.out.println(YELLOW + "Enter completion: ");
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String input = scan.nextLine();
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// CompletionRequest contains the data we sent to the OpenAI API. We use
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// 128 tokens, so we have a bit of a delay before the response (for testing).
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CompletionRequest request = CompletionRequest.builder()
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.model("davinci")
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.prompt(input)
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.maxTokens(128).build();
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// Loads the API key from the .env file in the root directory.
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String key = Dotenv.load().get("OPENAI_TOKEN");
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OpenAI openai = new AzureOpenAI(key);
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System.out.println(RESET + "Generating Response" + PURPLE);
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// Generate a print the message
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if (stream) {
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if (async)
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openai.streamCompletionAsync(request, response -> System.out.print(response.get(0).getText()));
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else
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openai.streamCompletion(request, response -> System.out.print(response.get(0).getText()));
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} else {
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if (async)
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openai.createCompletionAsync(request, response -> System.out.println(response.get(0).getText()));
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else
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System.out.println(openai.createCompletion(request).get(0).getText());
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}
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System.out.println(CYAN + " !!! Code has finished executing. Wait for async code to complete." + RESET);
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}
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public static void doChatAzure(boolean stream, boolean async) throws OpenAIError {
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Scanner scan = new Scanner(System.in);
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// This is the prompt that the bot will refer back to for every message.
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ChatMessage prompt = ChatMessage.toSystemMessage("You are a helpful chatbot.");
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// Use a mutable (modifiable) list! Always! You should be reusing the
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// ChatRequest variable, so in order for a conversation to continue
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// you need to be able to modify the list.
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List<ChatMessage> messages = new ArrayList<>(Collections.singletonList(prompt));
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// ChatRequest is the request we send to OpenAI API. You can modify the
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// model, temperature, maxTokens, etc. This should be saved, so you can
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// reuse it for a conversation.
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ChatRequest request = ChatRequest.builder()
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.model("gpt-3.5-turbo")
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.messages(messages).build();
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// Loads the API key from the .env file in the root directory.
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String key = Dotenv.load().get("OPENAI_TOKEN");
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OpenAI openai = new AzureOpenAI(key);
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// The conversation lasts until the user quits the program
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while (true) {
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// Prompt the user to enter a response
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System.out.println(YELLOW + "Enter text below:\n\n");
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String input = scan.nextLine();
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// Add the newest user message to the conversation
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messages.add(ChatMessage.toUserMessage(input));
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System.out.println(RESET + "Generating Response" + PURPLE);
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if (stream) {
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if (async) {
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openai.streamChatCompletionAsync(request, response -> {
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System.out.print(response.get(0).getDelta());
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if (response.get(0).isFinished())
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messages.add(response.get(0).getMessage());
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});
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} else {
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openai.streamChatCompletion(request, response -> {
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System.out.print(response.get(0).getDelta());
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if (response.get(0).isFinished())
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messages.add(response.get(0).getMessage());
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});
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}
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} else {
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if (async) {
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openai.createChatCompletionAsync(request, response -> {
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System.out.println(response.get(0).getMessage().getContent());
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messages.add(response.get(0).getMessage());
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});
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} else {
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ChatResponse response = openai.createChatCompletion(request);
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System.out.println(response.get(0).getMessage().getContent());
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messages.add(response.get(0).getMessage());
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}
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}
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System.out.println(CYAN + " !!! Code has finished executing. Wait for async code to complete.");
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}
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}
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}

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