Create app.py

app.py

@@ -0,0 +1,75 @@
+# main.py
+import os
+import gradio as gr
+from PIL import Image
+import io
+import base64
+from groq import Groq
+
+# Initialize Groq client with API key (set this as a secret in HF Spaces)
+client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
+
+# Helper: Convert PIL Image to base64
+def image_to_base64(image):
+    buffered = io.BytesIO()
+    image.save(buffered, format="JPEG")
+    return base64.b64encode(buffered.getvalue()).decode()
+
+# Prompt for model
+SYSTEM_PROMPT = """
+You are a helpful civil engineering assistant. The user uploads an image showing some construction damage such as cracks, water leakage, or pipe failure. Based on the image, give:
+
+1. Likely issue  
+2. Possible solution  
+3. Tools or materials needed  
+4. Estimated time to fix
+
+Use simple, helpful, practical language.
+"""
+
+# Chatbot logic
+def analyze_image(image, history):
+    if image is None:
+        return history + [("User", "No image uploaded."), ("Bot", "Please upload a damage photo.")]
+
+    base64_img = image_to_base64(image)
+    image_url = f"data:image/jpeg;base64,{base64_img}"
+
+    try:
+        response = client.chat.completions.create(
+            model="meta-llama/llama-4-scout-17b-16e-instruct",
+            messages=[
+                {"role": "system", "content": SYSTEM_PROMPT},
+                {"role": "user", "content": [
+                    {"type": "text", "text": "Please analyze this image and give advice on the damage."},
+                    {"type": "image_url", "image_url": {"url": image_url}}
+                ]}
+            ],
+            temperature=0.7,
+            max_tokens=512
+        )
+
+        reply = response.choices[0].message.content
+        history.append(("User", "Uploaded image"))
+        history.append(("Bot", reply))
+        return history
+    except Exception as e:
+        return history + [("Bot", f"❌ Error: {str(e)}")]
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("## 🛠️ Construction Damage Assistant\nUpload a photo of damage to get repair advice.")
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            image_input = gr.Image(type="pil", label="Upload Damage Image")
+
+        with gr.Column(scale=2):
+            chatbot = gr.Chatbot(label="Repair Suggestions", height=450)
+
+    state = gr.State([])
+    submit_btn = gr.Button("Analyze")
+
+    submit_btn.click(fn=analyze_image, inputs=[image_input, state], outputs=chatbot)
+
+demo.launch()