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856f57c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 | import gradio as gr
import openai
import base64
from PIL import Image
import os
# 🔑 Get OpenAI key from Hugging Face Secrets
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
if not OPENAI_API_KEY:
raise ValueError("Please set OPENAI_API_KEY in Hugging Face Secrets")
openai.api_key = OPENAI_API_KEY
def encode_image(image_path):
"""Convert uploaded image to base64 string"""
with open(image_path, "rb") as img_file:
return base64.b64encode(img_file.read()).decode("utf-8")
def classify_medicine(image_path):
try:
image_b64 = encode_image(image_path)
response = openai.chat.completions.create(
model="gpt-4o-mini",
messages=[
{"role": "system", "content": "You are an assistant that classifies medicine packaging."},
{
"role": "user",
"content": [
{"type": "text", "text": "Classify the uploaded medicine image as 'Generic' or 'Ethical (Branded)'. Only respond with one of these two labels."},
{"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{image_b64}"}}
]
}
],
)
result = response.choices[0].message.content.strip()
return image_path, f"✅ Prediction: {result}"
except Exception as e:
return None, f"⚠️ Error: {str(e)}"
# 🎨 Custom UI
custom_css = """
.gradio-container {
background-color: #f9fdfb !important;
font-family: 'Segoe UI', sans-serif;
color: #003333 !important;
padding: 20px;
}
h1 {
color: #006666 !important;
text-align: center;
font-weight: 700;
margin-bottom: 10px;
}
p {
text-align: center;
color: #004d4d !important;
font-size: 16px;
}
.card {
background: white;
border-radius: 16px;
padding: 20px;
box-shadow: 0px 4px 15px rgba(0,0,0,0.08);
}
button {
background-color: #f9fdfb !important;
color: black !important;
border-radius: 8px !important;
font-weight: bold;
font-size: 15px;
padding: 10px 20px;
}
button:hover {
background-color: #f9fdfb !important;
}
"""
with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
gr.Markdown("<h1>💊 Pharma Medicine Classifier</h1><p>Upload a medicine image to check if it is <b>Generic</b> or <b>Ethical (Branded)</b>.</p>")
with gr.Row(elem_classes="card"):
with gr.Column():
input_img = gr.Image(type="filepath", label="📷 Upload Medicine Image", height=250)
classify_btn = gr.Button("🔍 Classify Medicine", variant="primary")
with gr.Column():
preview_img = gr.Image(label="Uploaded Image", interactive=False, height=250)
output_label = gr.Textbox(label="Result", interactive=False)
classify_btn.click(fn=classify_medicine, inputs=input_img, outputs=[preview_img, output_label])
demo.launch()
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