Update app.py

app.py

@@ -4,80 +4,76 @@ import csv
 import io
 
 # -------------------------------
-# BuildSmart Estimator: Streamlit Web App
+# BuildSmart Estimator using Groq
 # -------------------------------
 
-# Set page config
 st.set_page_config(page_title="BuildSmart Estimator", page_icon="🏗️")
-
-# App title
 st.title("🏗️ BuildSmart Estimator")
 st.subheader("Estimate construction materials based on project details")
 
-# Input form for user
+# Securely fetch Groq API key from Streamlit secrets
+GROQ_API_KEY = st.secrets["GROQ_API_KEY"]
+GROQ_MODEL = "llama3-70b-8192"  # Recommended and supported
+
+# Form inputs
 with st.form("estimator_form"):
     total_area = st.number_input("Total Area (in square feet)", min_value=100, step=50)
     floors = st.number_input("Number of Floors", min_value=1, step=1)
     structure_type = st.selectbox("Structure Type", ["Residential", "Commercial", "Industrial"])
     material_pref = st.selectbox("Material Preference", ["Cement & Bricks", "Steel & Concrete"])
     location = st.text_input("Location", placeholder="e.g., Lahore, Karachi, etc.")
-    
-    # Submit button
     submitted = st.form_submit_button("Estimate Materials")
 
-# Function to build the prompt
+# Prompt constructor
 def build_prompt(area, floors, structure, material, loc):
-    return (
-        f"Estimate the construction material required for a {structure} building "
-        f"with {floors} floor(s), total area of {area} square feet, located in {loc}, "
-        f"using {material}. Return quantities for: Cement (bags), Sand (cubic feet), Bricks (units), "
-        f"Steel (kg), Crush (cubic feet), and Rori (cubic feet)."
-    )
+    return f"""
+You are a construction cost estimator bot. Based on the following user inputs, estimate the quantity of construction materials needed.
+
+Project Details:
+- Total Area: {area} sq ft
+- Number of Floors: {floors}
+- Structure Type: {structure}
+- Material Preference: {material}
+- Location: {loc}
+
+Return only the estimated material quantities in this format:
+
+Cement (bags): 
+Sand (cubic feet): 
+Bricks (units): 
+Steel (kg): 
+Crush (cubic feet): 
+Rori (cubic feet):
+"""
 
-# Function to call Hugging Face Inference API
-def query_huggingface_api(prompt):
-    API_URL = "https://api-inference.huggingface.co/models/your-username/your-model-name"  # 🔁 Replace this
+# Groq API function
+def call_groq_api(prompt):
     headers = {
-        "Authorization": "Bearer YOUR_HUGGINGFACE_API_TOKEN"  # 🔁 Replace this
+        "Authorization": f"Bearer {GROQ_API_KEY}",
+        "Content-Type": "application/json"
     }
     payload = {
-        "inputs": prompt
+        "model": GROQ_MODEL,
+        "messages": [
+            {"role": "user", "content": prompt}
+        ]
     }
-    response = requests.post(API_URL, headers=headers, json=payload)
+    response = requests.post("https://api.groq.com/openai/v1/chat/completions", headers=headers, json=payload)
+
     if response.status_code == 200:
-        return response.json()[0]['generated_text']
+        return response.json()["choices"][0]["message"]["content"]
     else:
-        return f"❌ API Error: {response.status_code} - {response.text}"
+        return f"❌ Error: {response.status_code} - {response.text}"
 
-# Process form submission
+# Run on form submission
 if submitted:
     prompt = build_prompt(total_area, floors, structure_type, material_pref, location)
     with st.spinner("Estimating materials..."):
-        response_text = query_huggingface_api(prompt)
-    
-    # Display results
-    st.markdown("### 📦 Estimated Material Requirements")
-    st.text(response_text)
-
-    # Optional: Convert response into CSV format
-    csv_buffer = io.StringIO()
-    writer = csv.writer(csv_buffer)
-    writer.writerow(["Material", "Quantity"])
+        result = call_groq_api(prompt)
 
-    # Parse simple line-based format (adjust if your model returns structured JSON)
-    for line in response_text.splitlines():
-        if ":" in line:
-            parts = line.split(":", 1)
-            writer.writerow([parts[0].strip(), parts[1].strip()])
-
-    # Download button
-    st.download_button(
-        label="📥 Download Estimate",
-        data=csv_buffer.getvalue(),
-        file_name="material_estimate.csv",
-        mime="text/csv"
-    )
+    # Display result
+    st.markdown("### 📦 Estimated Material Requirements")
+    st.text(result)
 
-# Footer
-st.markdown("---")
-st.caption("Developed for educational purposes. Replace placeholder API values before deployment.")
+    # CSV export
+    csv_buffer = io.String_