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app.py

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+import gradio as gr
+import google.generativeai as genai
+from PIL import Image
+import io
+import numpy as np
+
+def generate_content(api_key, prompt, image_data):
+
+    genai.configure(api_key=api_key)  
+
+    # Convert uploaded binary data into a PIL image.
+    # image = Image.open(io.BytesIO(image_data))
+    image = Image.fromarray(np.uint8(image_data)).convert('RGB')
+
+    model = genai.GenerativeModel('gemini-pro-vision')
+
+    response = model.generate_content([prompt, image])
+    response.resolve()
+    return response.text
+
+
+
+with gr.Blocks() as app:
+    gr.Markdown("# Morshen micro is demo")
+    gr.Markdown("https://ai.google.dev/")
+    api_key_input = gr.Textbox(label="API Key", type="password", value="AIzaSyBx6NCOCoNTpvock5As8_IYctd_zGqom4U", placeholder="Enter your API Key", lines=1)
+
+    # image_input = gr.File(label="Upload an image", type="binary")
+    image_input = gr.Image(label="Загрузить изображение ")
+    prompt_input = gr.Textbox(label="Функция", placeholder="Enter your Prompt", value="Идентификация вируса/бактерии и назначение по лечению ",lines=3)
+    generate_button = gr.Button("Пуск")
+    output = gr.Markdown()
+    
+    generate_button.click(
+        generate_content, 
+        inputs=[api_key_input, prompt_input, image_input],
+        outputs=output
+    )
+
+app.launch()

requirements.txt

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+google-generativeai==0.3.1
+gradio