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| import gradio as gr | |
| from dotenv import load_dotenv | |
| # Load environment variables from the .env file de forma local | |
| load_dotenv() | |
| import base64 | |
| with open("Iso_Logotipo_Ceibal.png", "rb") as image_file: | |
| encoded_image = base64.b64encode(image_file.read()).decode() | |
| import os | |
| import openai | |
| openai.api_key = os.environ["OPENAI_API_KEY"] | |
| def get_image(text: str): | |
| response = openai.Image.create(prompt=text, n=1, size="512x512") #,response_format="b64_json" | |
| print(response['data'][0]['url']) # type: ignore | |
| return response['data'][0]['url']# type: ignore | |
| with gr.Blocks() as demo: | |
| gr.Markdown( | |
| """ | |
| <center> | |
| <h1> | |
| Uso de AI para la generación de imagenes a partir de texto. | |
| </h1> | |
| <img src='data:image/jpg;base64,{}' width=200px> | |
| <h2> | |
| Con este espacio podrás generar imagenes a partir de texto. Utiliza el modelo DALL-E de OpenAI. | |
| </h2> | |
| <h2> | |
| Obtendrás mejores resultados cuanto más larga sea la descripción. | |
| </h2> | |
| </center> | |
| """.format( | |
| encoded_image | |
| ) | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Markdown("Primero debes ingresar el texto para generar la imagen:") | |
| with gr.Row(): | |
| with gr.Column(scale=4): | |
| prompt = gr.Textbox( | |
| label="Texo base para generar la imagen" | |
| ) # Give prompt some real estate | |
| with gr.Column(scale=1, min_width=50): | |
| btn = gr.Button("Generar") # Submit button side by side! | |
| with gr.Column(): | |
| output = gr.Image( | |
| label="Resultado", height=512, width=512 | |
| ) # Move the output up too | |
| # examples = gr.Examples( | |
| # inputs=[prompt] | |
| # examples=[["Un perro en el parque", "low quality"]], | |
| # ) | |
| btn.click( | |
| fn=get_image, | |
| inputs=prompt, | |
| outputs=[output], | |
| ) # steps,guidance,width,height] | |
| demo.launch(debug=True) |