2. Streaming ChatGPT API with Python

Streaming ChatGPT API responses in Python can be achieved by using the OpenAI API. Here is an example:

import openai

response = openai.StreamingCompletion.create(
  model="chatgpt",
  messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Who won the world series in 2023?"},
        {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2023."},
        {"role": "user", "content": "Where was it played?"}
    ],
  stop={"condition":[{"role": "assistant", "content": "The World Series in 2023 was played in Arlington, Texas."}]}
)

for message in response.iterator():
    print(message['message']['content'])

In this example, we create a streaming completion with a list of messages exchanged between the user and assistant. The assistant’s responses are streamed in real-time using the response.iterator() method.

3. Streaming ChatGPT API with JavaScript

Streaming ChatGPT API responses in JavaScript can be achieved using the streaming-ai module. Here is an example:

const { StreamChatGPT } = require('streamed-chatgpt-api');

const chat = new StreamChatGPT({
    apiKey: 'YOUR_API_KEY',
    model: 'gpt⑷.0-turbo',
});

chat.on('message', (message) => {
    console.log(message['content']);
});

chat.start([
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'Who won the world series in 2023?' },
    { role: 'assistant', content: 'The Los Angeles Dodgers won the World Series in 2023.' },
    { role: 'user', content: 'Where was it played?' }
]);

In this example, we create a new instance of the StreamChatGPT class, passing the API key and the desired model. We listen for the message event to receive the assistant’s responses in real-time. The conversation messages are sent to the start method to initiate the streaming process.

4. Advantages of Streaming ChatGPT API

The advantage of streaming ChatGPT API responses is that it improves the user experience by serving responses in real-time. Instead of waiting for the entire completion to finish, the user can see immediate responses, making the conversation feel more natural and interactive.

5. Use Cases for Streaming ChatGPT API

Streaming ChatGPT API has various use cases:

• Real-time chat applications: Streaming responses can be used in chat applications to provide instant AI-generated replies to users.
• Customer support systems: Streaming responses can enhance customer support systems by providing immediate assistance to users.
• Interactive storytelling: Streaming responses can be used in interactive storytelling platforms to create dynamic and engaging stories.

6. Conclusion

Streamed ChatGPT API allows users to stream AI-generated responses in real-time, improving the user experience and enabling a variety of applications. By leveraging Python or JavaScript, developers can easily implement the streaming functionality and explore its potential in their projects.