<label for='answer'>Answer:</label>		<input type='text' id='answer' name='answer' readonly><br>

	<input type='submit' value='Submit'>	</form></body></html>

This HTML code defines a form with two textboxes: one for the user's prompt and another to display the AI-generated answer. The 'required' attribute ensures a prompt is provided, while 'readonly' makes the answer textbox non-editable.

Python Flask Integrationpythonfrom flask import Flask, render_template, requestimport openai

app = Flask(name)

Set up OpenAI API credentialsopenai.api_key = 'YOUR_API_KEY'

Define the route for the home page@app.route('/')def home(): return render_template('index.html')

Define the route for processing the form data@app.route('/', methods=['POST'])def process_form(): prompt = request.form['prompt'] answer = generate_answer(prompt) return render_template('index.html', answer=answer)

Define a function to generate the answer using OpenAI APIdef generate_answer(prompt): response = openai.Completion.create( engine='davinci', prompt=prompt, max_tokens=100 ) return response.choices[0].text

if name == 'main': app.run(debug=True)

This Python code, using Flask framework, connects the HTML form with OpenAI's API. The code defines routes for the homepage and form submission, retrieves the prompt from the form, and uses the generate_answer function to send a request to OpenAI's API. Finally, the generated answer is sent back to the HTML template for display.

Key Points

• Replace 'YOUR_API_KEY' with your actual OpenAI API key.- You may adjust the 'max_tokens' parameter in the generate_answer function to control the length of the generated response.- This example uses the 'davinci' engine; feel free to experiment with other OpenAI engines for different text generation styles.

This tutorial provides a starting point for building your own prompt-answering application using OpenAI and web technologies. Feel free to extend and adapt it to meet your specific requirements.