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import java.net.HttpURLConnection;
import java.net.URL;
import java.io.BufferedReader;
import java.io.InputStreamReader;
import java.io.DataOutputStream;
import java.io.InputStreamReader;
import java.nio.charset.StandardCharsets;
import java.util.HashMap;
import java.util.Map;
import java.util.Scanner;


public class HttpRequestMultipleHeadersExample {

    public static void main(String[] args) throws Exception {
        while (true){
            chatWithGPT();
        }
    }

    public static void chatWithGPT() throws Exception{
        String url = "https://api.openai.com/v1/chat/completions";
        URL obj = new URL(url);
        HttpURLConnection con = (HttpURLConnection) obj.openConnection();

        // set request method
        con.setRequestMethod("POST");

        // set custom headers
        con.setRequestProperty("Content-Type", "application/json");
        con.setRequestProperty("Authorization", "Bearer sk-......");


         // create a Scanner object to read input from the console
         Scanner scanner = new Scanner(System.in);

         // prompt the user to enter a string
         System.out.print("😋: ");
 
         // read the user's input as a string
         String question = scanner.nextLine();

        // set request body
        String requestBody = "{\"model\": \"gpt-3.5-turbo\", \"messages\": [{\"role\": \"user\", \"content\": \"" + question + "\"}]}";
        con.setDoOutput(true);
        DataOutputStream out = new DataOutputStream(con.getOutputStream());
        out.writeBytes(requestBody);
        out.flush();
        out.close();

        int responseCode = con.getResponseCode();
        // System.out.println("Response Code : " + responseCode);

        BufferedReader in = new BufferedReader(new InputStreamReader(con.getInputStream()));
        String inputLine;
        StringBuffer response = new StringBuffer();
        while ((inputLine = in.readLine()) != null) {
            response.append(inputLine);
        }
        in.close();

        // System.out.println("Response Body : " + response.toString());


        // parse response body as a JSON object
        String jsonString = response.toString();
        int contentIndex = jsonString.indexOf("\"content\":");
        String contentValue = jsonString.substring(contentIndex + "\"content\":".length() + 1, jsonString.indexOf("\"", contentIndex + "\"content\":".length() + 2));
        System.out.print("🤖: " + contentValue);
        System.out.println("\n");
    }
   
}

#include <CkUpload.h>

void ChilkatSample(void)
    {
    CkUpload upload;

    // Specify the page (ASP, ASP.NET, Perl, Python, Ruby, CGI, etc)
    // that will receive and process the HTTP Upload.
    upload.put_Hostname("www.mywebserver.com");
    upload.put_Path("/receiveUpload.aspx");

    // Add one or more files to be uploaded.
    upload.AddFileReference("file1","dude.gif");
    upload.AddFileReference("file2","swordfish.xml");
    upload.AddFileReference("file3","sample.doc");

    // Do the upload.  The method returns when the upload
    // is completed.
    // This component also includes asynchronous upload capability,
    // which is demonstrated in another example.
    bool success = upload.BlockingUpload();
    if (success != true) {
        std::cout << upload.lastErrorText() << "\r\n";
    }
    else {
        std::cout << "Files uploaded!" << "\r\n";
    }
    }

import openai


# Use your openai api key (https://platform.openai.com/account/api-keys)
openai.api_key = "sk-..."

MODEL = "gpt-3.5-turbo"

# see https://platform.openai.com/account/usage for the free api trial usage remaining

# Set up the basic role for ChatGPT
messages=[{"role": "system", "content": "You are a helpful assistant, and you will correctly answer all my questions."}]


# Ask ChatGPT question and get reply
def chat_with_ChatGPT():

    # Input the question
    my_question = input("😄 : ") 

    # It will append to the messages list as a user role (your question)
    messages.append({"role": "user", "content": my_question})

    # Ask ChatGPT and get reply
    response = openai.ChatCompletion.create(model=MODEL, messages= messages)

    # It will return as a key, value pair and now just get the reply
    reply_message = response['choices'][0]['message']['content']
    total_tokens = response['usage']['total_tokens']
    messages.append({"role": "assistant", "content": reply_message})

    # print("total token:", total_tokens)
    print("🤖 :", reply_message)
    print('')
    

while True:
   chat_with_ChatGPT()

import openai


# Use your openai api key (https://platform.openai.com/account/api-keys)
openai.api_key = "sk-..."

MODEL = "gpt-3.5-turbo"

# see https://platform.openai.com/account/usage for the free api trial usage remaining

# Set up the basic role for ChatGPT
messages=[{"role": "system", "content": "You are a helpful assistant, and you will correctly answer all my questions."}]


# Ask ChatGPT question and get reply
def chat_with_ChatGPT():

    # Input the question
    my_question = input("😄 : ") 

    # It will append to the messages list as a user role (your question)
    messages.append({"role": "user", "content": my_question})

    # Ask ChatGPT and get reply
    response = openai.ChatCompletion.create(model=MODEL, messages= messages)

    # It will return as a key, value pair and now just get the reply
    reply_message = response['choices'][0]['message']['content']
    total_tokens = response['usage']['total_tokens']
    messages.append({"role": "assistant", "content": reply_message})

    # print("total token:", total_tokens)
    print("🤖 :", reply_message)
    print('')
    

while True:
   chat_with_ChatGPT()