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| import openai | |
| import requests | |
| from io import BytesIO | |
| import gradio as gr | |
| openai.api_key = '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' | |
| def generate_image(prompt): | |
| # Use GPT-3 to generate a description of the image | |
| model_engine = "text-davinci-002" | |
| description = openai.Completion.create( | |
| engine=model_engine, | |
| prompt=f"Generate an image of {prompt}", | |
| max_tokens=256, | |
| n=1, | |
| stop=None, | |
| temperature=0.5 | |
| ).choices[0].text.strip() | |
| # Use DALL-E to generate an image based on the description | |
| response = requests.post( | |
| "https://api.openai.com/v1/images/generations", | |
| headers={ | |
| "Content-Type": "application/json", | |
| "Authorization": f"Bearer {openai.api_key}" | |
| }, | |
| json={ | |
| "model": "image-alpha-001", | |
| "prompt": description, | |
| "num_images": 1, | |
| "size": "1024x1024", | |
| "response_format": "url" | |
| } | |
| ) | |
| # Parse the image URL from the API response and return the image | |
| image_url = response.json()["data"][0]["url"] | |
| response = requests.get(image_url) | |
| image = BytesIO(response.content) | |
| return image | |
| iface = gr.Interface( | |
| fn=generate_image, | |
| inputs="text", | |
| outputs="image", | |
| title="Text to Image Generator", | |
| description="Enter a prompt to generate an image", | |
| examples=[ | |
| ["a red apple on a white background"], | |
| ["a yellow sun setting over a mountain range"], | |
| ["a futuristic cityscape at night"] | |
| ] | |
| ) | |
| iface.launch() | |