File size: 3,139 Bytes
baee0d1 78e66ed baee0d1 78e66ed baee0d1 78e66ed baee0d1 78e66ed 487cdc9 78e66ed a7e0859 78e66ed 4052fe3 78e66ed d70fb92 78e66ed d70fb92 baee0d1 78e66ed 487cdc9 baee0d1 78e66ed baee0d1 78e66ed 487cdc9 |
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 |
import os
import gradio as gr
import requests
import base64
from PIL import Image
from io import BytesIO
# Set your Groq API key
GROQ_API_KEY = os.getenv("GROQ_API_KEY") or "PASTE_YOUR_GROQ_API_KEY_HERE"
GROQ_URL = "https://api.groq.com/openai/v1/chat/completions"
GROQ_MODEL = "llama3-70b-8192"
def analyze_damage(image, user_prompt):
if image is None or not user_prompt.strip():
return "⚠️ Please upload an image and enter a question or description."
# Convert image to base64 for potential future use
buffered = BytesIO()
image.save(buffered, format="JPEG")
img_base64 = base64.b64encode(buffered.getvalue()).decode()
system_prompt = (
"You are a helpful construction engineer. The user has uploaded an image of some construction damage "
"and has asked a question. Based on the image and their description or question, identify:\n"
"- Type of damage\n"
"- Possible causes\n"
"- Recommended repair materials/tools\n"
"- Estimated repair time"
)
messages = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": f"Image uploaded.\nQuestion: {user_prompt}"}
]
headers = {
"Authorization": f"Bearer {GROQ_API_KEY}",
"Content-Type": "application/json"
}
payload = {
"model": GROQ_MODEL,
"messages": messages,
"temperature": 0.7
}
try:
response = requests.post(GROQ_URL, headers=headers, json=payload)
response.raise_for_status()
reply = response.json()["choices"][0]["message"]["content"]
return reply
except Exception as e:
return f"❌ Error: {str(e)}"
# Gradio UI
with gr.Blocks(theme=gr.themes.Soft(primary_hue="orange")) as demo:
gr.Markdown("# 🏗️ Construction Damage Assistant")
gr.Markdown("""
Upload an image of the damage and ask a question like:<br>
🔹 *What type of crack is this?*<br>
🔹 *What material should I use to fix it?*<br><br>
The assistant will analyze your question and give expert suggestions.
""", elem_classes="description-box")
with gr.Row():
with gr.Column(scale=1):
image_input = gr.Image(label="📸 Upload Damage Photo", type="pil", height=280)
question_input = gr.Textbox(
label="🧾 Ask a Question or Describe the Problem",
placeholder="e.g., What caused this crack? How do I fix it?",
lines=3
)
submit_btn = gr.Button("🔍 Analyze", variant="primary")
clear_btn = gr.Button("🧹 Clear Inputs")
with gr.Column(scale=1.5):
output = gr.Textbox(
label="💡 AI Response",
lines=18,
show_copy_button=True
)
submit_btn.click(fn=analyze_damage, inputs=[image_input, question_input], outputs=output)
clear_btn.click(lambda: (None, "", ""), outputs=[image_input, question_input, output])
gr.Markdown("___")
gr.Markdown("🔧 Powered by **Groq LLaMA3** | Built with ❤️ using **Gradio**")
demo.launch()
|