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| from google import genai | |
| from google.genai import types | |
| from PIL import Image | |
| from io import BytesIO | |
| import gradio as gr | |
| import base64 | |
| import os | |
| api_key = os.getenv("GEMINI_API_KEY") | |
| def generate_image(prompt): | |
| """ | |
| Transforms text into an image. | |
| Args: | |
| prompt: A natural language instruction that is used to generate an image. | |
| Returns: | |
| An image. | |
| """ | |
| client = genai.Client(api_key=api_key) | |
| prompt = tuple(prompt) | |
| response = client.models.generate_content( | |
| model="gemini-2.0-flash-preview-image-generation", | |
| contents=prompt, | |
| config=types | |
| .GenerateContentConfig( | |
| response_modalities=['TEXT', 'IMAGE'] | |
| ) | |
| ) | |
| for part in response.candidates[0].content.parts: | |
| if part.text is not None: | |
| pass | |
| elif part.inline_data is not None: | |
| image = Image.open(BytesIO((part.inline_data.data))) | |
| # image.save('gemini-native-image.png') | |
| # display(image) | |
| return image | |
| # build gradio interface | |
| app = gr.Interface(fn = generate_image, | |
| inputs = gr.Text(label="Prompt",placeholder="Type your prompt here. . ."), | |
| outputs = gr.Image(label="Generated Image"), | |
| title="Gemini Image Generator", | |
| examples=["A 3D rendering of a little black girl wearing a colorful dress and smiling broadly at the camera", | |
| "Disney and Pixar-style playful bunny skipping about in a garden full of carrots and lettuce", | |
| "A strong black female superhero with braided hair flying in the bright blue sky", | |
| "A jazz musician playing his saxophone and surrounded by colorful musical notes."]) | |
| # launch application | |
| if __name__ == "__main__": | |
| app.launch(mcp_server = True) |