app.py

import gradio as gr
import openai

# Set up your OpenAI API key
openai.api_key = "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"

# Define the function to handle the user's inputs and generate the output
def process_quote(quote, action, target_language):
    if action == "find author":
        # Call OpenAI API to find the author of the quote
        response = openai.Completion.create(
            engine="text-davinci-003",
            prompt=f"Find the author of the quote: '{quote}'",
            max_tokens=30,
            n=1,
            stop=None,
            temperature=0.7
        )
        author = response.choices[0].text.strip()
        return f"The author of the quote '{quote}' is {author}."
    elif action == "explain quote":
        # Call OpenAI API to explain the quote
        response = openai.Completion.create(
            engine="text-davinci-003",
            prompt=f"Explain the quote: '{quote}'",
            max_tokens=100,
            n=1,
            stop=None,
            temperature=0.7
        )
        explanation = response.choices[0].text.strip()
        return f"Explanation of the quote '{quote}': {explanation}."
    elif action == "generate similar quote":
        # Call OpenAI API to generate a similar quote with fewer tokens
        response = openai.Completion.create(
            engine="text-davinci-003",
            prompt=f"This is similar quote that I have generated:",
            max_tokens=30,
            n=1,
            stop=None,
            temperature=0.7
        )
        similar_quote = response.choices[0].text.strip()
        return f"A similar quote to '{quote}': {similar_quote}."
    elif action == "translate quote":
        response = openai.Completion.create(
            engine="text-davinci-003",
            prompt=f"The translation of the following quote in English is: '{quote}'",
            max_tokens=100,
            n=1,
            stop=None,
            temperature=0.7
        )
        translation = response.choices[0].text.strip()
        return f"Translation of the quote '{quote}': {translation}."

quote_input = gr.inputs.Textbox(label="Enter a quote")
action_input = gr.inputs.Dropdown(["find author", "explain quote", "generate similar quote", "translate quote"], label="Select an action")
language_input = gr.inputs.Dropdown(["en", "fr", "es", "de"], label="Select target language (for translation)")
output_text = gr.outputs.Textbox(label="Output")

interface = gr.Interface(fn=process_quote, inputs=[quote_input, action_input, language_input], outputs=[output_text])

# Run the interface
interface.launch()