Update app.py

app.py

@@ -1,4 +1,86 @@
-import streamlit as st
+import streamlit as stimport streamlit as st
+import requests
+import json
+
+# ------------------- CONFIGURATION ------------------- #
+API_URL = "https://api-inference.huggingface.co/models/HuggingFaceTB/SmolVLM-256M-Instruct"
+API_TOKEN = "YOUR_HUGGINGFACE_API_TOKEN"  # Replace with your actual Hugging Face API token
+
+headers = {"Authorization": f"Bearer {API_TOKEN}"}
+
+# ------------------- FUNCTION TO QUERY MODEL ------------------- #
+def query_huggingface_api(prompt):
+    payload = {
+        "inputs": prompt,
+        "parameters": {
+            "max_new_tokens": 200,
+            "temperature": 0.7
+        }
+    }
+    response = requests.post(API_URL, headers=headers, json=payload)
+    if response.status_code != 200:
+        st.error(f"API Error {response.status_code}: {response.text}")
+        return None
+    return response.json()
+
+# ------------------- STREAMLIT APP ------------------- #
+st.set_page_config(page_title="Build Smart Estimator", page_icon="🏗️")
+
+# App title
+st.title("🏗️ Build Smart Estimator")
+st.markdown("""
+Welcome to **Build Smart Estimator** — an intelligent tool to help you estimate construction materials based on your project details!
+""")
+
+# Input Fields
+st.header("Enter Your Project Details")
+
+col1, col2 = st.columns(2)
+
+with col1:
+    total_area = st.number_input("🏠 Total Area (in square meters)", min_value=10.0, step=10.0)
+    num_floors = st.number_input("🏢 Number of Floors", min_value=1, step=1)
+
+with col2:
+    structure_type = st.selectbox("🏗️ Structure Type", options=[
+        "Residential", "Commercial", "Industrial", "Warehouse"
+    ])
+    material_pref = st.multiselect(
+        "🧱 Material Preference (Select one or more)",
+        options=["Cement", "Bricks", "Steel", "Concrete"]
+    )
+
+# Submit button
+if st.button("Estimate Materials 🚀"):
+    if total_area <= 0 or num_floors <= 0:
+        st.warning("Please enter valid Total Area and Number of Floors.")
+    elif not material_pref:
+        st.warning("Please select at least one Material Preference.")
+    else:
+        # Prepare input prompt for the model
+        prompt = (
+            f"Estimate the required quantities of {', '.join(material_pref)} "
+            f"for a {structure_type.lower()} building with a total area of {total_area} square meters "
+            f"and {num_floors} floors. Provide the estimates in a clear and concise manner."
+        )
+
+        st.info("Sending your inputs to the smart estimator...")
+
+        # Call Hugging Face model
+        response = query_huggingface_api(prompt)
+
+        if response:
+            st.subheader("📊 Estimated Material Requirements")
+            # Assuming the model returns a list with a 'generated_text' field
+            if isinstance(response, list) and 'generated_text' in response[0]:
+                st.write(response[0]['generated_text'])
+            else:
+                st.write(response)
+
+# Footer
+st.markdown("---")
+st.caption("© 2025 Build Smart Estimator | Powered by Streamlit & Hugging Face")
+
 import math
 
 st.title("Scientific Calculator")