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| import google.generativeai as genai | |
| import gradio as gr | |
| import numpy as np | |
| import PIL.Image | |
| genai.configure(api_key="AIzaSyA7tPavobVN5_3-BJ0qhFT5HVjO4V19QWk") | |
| def ImageChat(image, prompt): | |
| # load model | |
| model = genai.GenerativeModel("gemini-1.5-flash") | |
| # check image file and convert to a Numpy array | |
| if isinstance(image, np.ndarray): | |
| img = PIL.Image.fromarray(image) | |
| else: | |
| img = PIL.Image.open(image) | |
| response = model.generate_content([prompt, img]) | |
| return response.text | |
| app = gr.Interface(ImageChat, | |
| inputs = [gr.Image(label = "Image"), gr.Text(label = "Prompt")], | |
| outputs = gr.Text(label = "Response"), | |
| title = "Image Chat", | |
| theme = "Taithrah/Minimal") | |
| app.launch() | |