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| import gradio as gr | |
| import requests | |
| from PIL import Image | |
| from io import BytesIO | |
| import os | |
| import torch | |
| from transformers import BlipProcessor, BlipForConditionalGeneration | |
| # ✅ Load Groq API key from environment (add this in Hugging Face Secrets) | |
| GROQ_API_KEY = os.getenv("GROQ_API_KEY") | |
| GROQ_MODEL = "llama3-70b-8192" | |
| # ✅ Load BLIP model for image captioning | |
| processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base") | |
| blip_model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base") | |
| # 📸 Generate caption from image | |
| def get_caption(image): | |
| inputs = processor(images=image, return_tensors="pt") | |
| out = blip_model.generate(**inputs) | |
| caption = processor.decode(out[0], skip_special_tokens=True) | |
| return caption | |
| # 💬 Communicate with Groq API | |
| def generate_response(image, user_query=""): | |
| if GROQ_API_KEY is None: | |
| return "❌ API key not set. Please set GROQ_API_KEY using Hugging Face Secrets." | |
| caption = get_caption(image) | |
| headers = { | |
| "Authorization": f"Bearer {GROQ_API_KEY}", | |
| "Content-Type": "application/json" | |
| } | |
| data = { | |
| "model": GROQ_MODEL, | |
| "messages": [ | |
| {"role": "system", "content": "You are a helpful assistant that analyzes construction damage from image captions and gives expert repair advice."}, | |
| {"role": "user", "content": f"Image caption: {caption}"}, | |
| {"role": "user", "content": f"My question is: {user_query or 'No follow-up question.'}"}, | |
| {"role": "user", "content": "Please provide:\n1. Type of damage\n2. Likely cause\n3. Suggested repair solutions\n4. Required tools\n5. Estimated time and cost"} | |
| ] | |
| } | |
| try: | |
| response = requests.post("https://api.groq.com/openai/v1/chat/completions", headers=headers, json=data, timeout=30) | |
| if response.status_code == 200: | |
| content = response.json()['choices'][0]['message']['content'] | |
| return content if content.strip() else "⚠️ No response received. Please try again." | |
| else: | |
| return f"❌ Error {response.status_code}: {response.text}" | |
| except Exception as e: | |
| return f"❌ Exception: {str(e)}" | |
| # ============================ | |
| # 🌟 Gradio Modern UI | |
| # ============================ | |
| with gr.Blocks(css=""" | |
| .gradio-container { | |
| background-color: #f8f9fa; | |
| font-family: 'Segoe UI', sans-serif; | |
| } | |
| #title { | |
| text-align: center; | |
| font-size: 32px; | |
| font-weight: bold; | |
| padding: 20px 0; | |
| color: #333; | |
| } | |
| #subtitle { | |
| text-align: center; | |
| font-size: 16px; | |
| color: #666; | |
| margin-bottom: 20px; | |
| } | |
| .card { | |
| border: 1px solid #ddd; | |
| border-radius: 16px; | |
| background-color: white; | |
| padding: 20px; | |
| box-shadow: 0 4px 8px rgba(0,0,0,0.03); | |
| } | |
| """) as demo: | |
| gr.Markdown("<div id='title'>\ud83c\udfd7\ufe0f BuildFix AI — Construction Damage Inspector</div>") | |
| gr.Markdown("<div id='subtitle'>Upload a construction damage image and get expert analysis with repair suggestions instantly.</div>") | |
| with gr.Row(): | |
| with gr.Column(scale=1, elem_classes="card"): | |
| image_input = gr.Image(type="pil", label="\ud83d\udcf8 Upload Image of Damage") | |
| user_query = gr.Textbox(label="\ud83d\udcac Ask a follow-up question (optional)", placeholder="e.g., How expensive is this repair?", lines=2) | |
| submit_btn = gr.Button("\ud83d\udd0d Analyze", variant="primary") | |
| with gr.Column(scale=1, elem_classes="card"): | |
| result_output = gr.Textbox(label="\ud83e\uddd0 AI Report", lines=20) | |
| submit_btn.click(fn=generate_response, inputs=[image_input, user_query], outputs=result_output) | |
| demo.launch() | |