app.py

import requests
import gradio as gr
import openai
from io import BytesIO
from pydub import AudioSegment

# Set up OpenAI API
openai.api_key = "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"

# Set up FPT API
tts = "IsZh7u8eHrjHgALqn0XS3M4vvouN331F"
tts_api_url = "https://api.fpt.ai/hmi/tts/v5"


def generate_presentation(topic):
    prompt = f"Please explain {topic} in the most easy and attractive way possible."

    # Set up OpenAI API parameters
    model_engine = "text-davinci-002"
    max_tokens = 1048
    temperature = 0.7

    # Generate the presentation content using OpenAI's GPT-3 API
    response = openai.Completion.create(
        engine=model_engine,
        prompt=prompt,
        max_tokens=max_tokens,
        temperature=temperature
    )

    return response.choices[0].text


def generate_audio(text):
    # Set up text-to-speech API parameters
    voice = "banmai"
    speed = "0"

    # Send a request to the text-to-speech API
    headers = {
        "api-key": tts,
        "voice": voice,
        "speed": speed
    }
    data = {"text": text}
    response = requests.post(tts_api_url, headers=headers, json=data)

    # Convert the response audio to a playable format
    audio_bytes = BytesIO(response.content)
    audio_segment = AudioSegment.from_file(audio_bytes.getvalue(), format="mp3")
    audio_segment.export("presentation_audio.mp3", format="mp3")

    return audio_bytes


def generate_presentation_and_audio(topic):
    presentation = generate_presentation(topic)
    audio = generate_audio(presentation)
    return presentation, audio


def main():
    title = "AICademy"
    description = "Generate a presentation on any topic using GPT-3 and convert it to audio using FPT's text-to-speech API."
    inputs = gr.inputs.Textbox(label="Enter the topic for your presentation:")
    outputs = [
        gr.outputs.Audio(label="Presentation Audio", type="numpy"),
        gr.outputs.Textbox(label="Presentation Text")
    ]
    examples = [
        ["What is artificial intelligence?"],
        ["How do black holes form?"],
        ["Explain the concept of quantum computing."],
    ]
    iface = gr.Interface(fn=generate_presentation_and_audio, inputs=inputs, outputs=outputs, title=title, description=description, examples=examples)

    iface.launch()


if __name__ == "__main__":
    main()