Update app.py

app.py

@@ -4,11 +4,12 @@ import streamlit as st
 from PIL import Image
 from openai import OpenAI
 from pathlib import Path
-import io
+
 
 # ✅ 1. Page Configuration — MUST be first Streamlit command
 st.set_page_config(page_title="AI Architecture Assistant", layout="centered")
 
+
 # ✅ 2. Inline custom CSS with Poppins font and olive green theme
 st.markdown("""
 <style>
@@ -169,6 +170,324 @@ if st.button("Get Material Recommendations"):
             st.markdown(result)
     else:
         st.warning("Please enter a prompt first.")
+st.markdown("### 💰 Cost Estimate by Region")
+
+region = st.selectbox("Select a region in Canada:", [
+    "Alberta", "British Columbia", "Ontario", "Quebec", "Atlantic Canada", "Prairies"
+])
+
+if st.button("Get Cost Estimate"):
+    if st.session_state.prompt.strip():
+        with st.spinner("Calculating cost estimate..."):
+            def generate_cost_estimate(prompt, region):
+                system_instruction = (
+                    "You are a residential construction cost estimator for Canadian regions. "
+                    "Based on the given architectural prompt and selected region, estimate a typical low-to-high cost range "
+                    "for building the described design. Mention 4–5 key cost categories. Use Canadian dollars. "
+                    "Adjust prices to be realistic for the selected region, and keep your response brief and clear."
+                )
+
+                user_input = f"Region: {region}\n\nPrompt:\n{prompt}"
+
+                response = client.chat.completions.create(
+                    model="gpt-4",
+                    messages=[
+                        {"role": "system", "content": system_instruction},
+                        {"role": "user", "content": user_input}
+                    ],
+                    temperature=0.7
+                )
+                return response.choices[0].message.content.strip()
+
+            estimate = generate_cost_estimate(st.session_state.prompt, region)
+            st.markdown(estimate)
+    else:
+        st.warning("Please enter a prompt first.")
+        st.markdown("### 🏗️ Building Code Comparison")
+
+st.markdown("---")
+st.markdown("### 🧾 Building Code Comparison Between Provinces")
+
+province_1 = st.selectbox("Select first province:", [
+    "British Columbia", "Alberta", "Ontario", "Quebec", "Atlantic Canada", "Prairies"
+], key="prov1")
+
+province_2 = st.selectbox("Select second province:", [
+    "British Columbia", "Alberta", "Ontario", "Quebec", "Atlantic Canada", "Prairies"
+], key="prov2")
+
+if st.button("Compare Building Codes"):
+    if province_1 != province_2:
+        with st.spinner("Comparing codes across provinces..."):
+            def compare_building_codes(p1, p2, prompt):
+                system_instruction = (
+                    "You are a Canadian building code expert. Compare the key differences in building code requirements "
+                    f"between {p1} and {p2} for residential construction, especially related to small or modern homes like the one described below. "
+                    "Focus on differences in energy efficiency, foundations, insulation, accessibility, and design limitations. "
+                    "Keep your response clear and under 10 bullet points."
+                )
+
+                response = client.chat.completions.create(
+                    model="gpt-4",
+                    messages=[
+                        {"role": "system", "content": system_instruction},
+                        {"role": "user", "content": prompt}
+                    ],
+                    temperature=0.7
+                )
+                return response.choices[0].message.content.strip()
+
+            comparison = compare_building_codes(province_1, province_2, st.session_state.prompt)
+            st.markdown(f"### 🏛️ {province_1} vs. {province_2}")
+            st.markdown(comparison)
+    else:
+        st.warning("Please select two different provinces.")
+        st.markdown("### ➡️ What would you like to do next?")
+
+# === DESIGN IDEAS SECTION ===
+
+st.markdown("### ➡️ What would you like to do next?")
+
+next_step = st.selectbox(
+    "Now that you have some information and a layout in mind, would you like help with...",
+    [
+        "Select an option",
+        "🎨 Explore design ideas (color palettes, materials for your climate)",
+        "🔍 Continue researching (codes, build types, regulations)"
+    ]
+)
+
+if next_step == "🎨 Explore design ideas (color palettes, materials for your climate)":
+    st.markdown("#### 🎨 Design Recommendations")
+    st.markdown("We'll give you smart and stylish ideas based on your region and layout.")
+
+    # Select region
+    design_region = st.selectbox("Where will your home be built?", [
+        "British Columbia", "Alberta", "Ontario", "Quebec", "Atlantic Canada", "Prairies"
+    ], key="design_region")
+
+    # Select style
+    design_style = st.selectbox("What style do you like?", [
+        "Scandinavian", "Modern Minimalist", "Rustic Cabin", "Japandi", "West Coast Contemporary"
+    ], key="design_style")
+
+    # Select design advice categories
+    selected_categories = st.multiselect(
+        "What kind of design advice would you like?",
+        [
+            "Climate-Responsive Material Suggestions",
+            "Interior Color Palette",
+            "Lighting & Window Placement Tips",
+            "Space-Saving Built-ins"
+        ],
+        default=["Climate-Responsive Material Suggestions", "Interior Color Palette"]
+    )
+
+# Generate design ideas with GPT
+if st.button("Generate Design Ideas"):
+        with st.spinner("Designing your dream space..."):
+
+            def generate_design_ideas(prompt, region, style, categories):
+                system_instruction = (
+                    "You are a residential design assistant. Based on the home description, region, and preferred design style, "
+                    "give tailored recommendations for the selected categories. Keep it concise, stylish, and easy to implement for a small-scale home."
+                )
+
+                user_input = (
+                    f"Prompt:\n{prompt}\n\n"
+                    f"Region: {region}\n"
+                    f"Style: {style}\n"
+                    f"Categories: {', '.join(categories)}"
+                )
+
+                response = client.chat.completions.create(
+                    model="gpt-4",
+                    messages=[
+                        {"role": "system", "content": system_instruction},
+                        {"role": "user", "content": user_input}
+                    ],
+                    temperature=0.7
+                )
+                return response.choices[0].message.content.strip()
+
+            design_results = generate_design_ideas(
+                st.session_state.prompt,
+                design_region,
+                design_style,
+                selected_categories
+            )
+
+            st.markdown("### 💡 Design Suggestions")
+            st.markdown(design_results)
+
+            # Store summary in session state
+            st.session_state.design_summary = {
+                "Prompt": st.session_state.prompt,
+                "Region": design_region,
+                "Style": design_style,
+                "Categories": selected_categories,
+                "Design Suggestions": design_results,
+                "Materials": st.session_state.get("material_recommendations", "Not generated"),
+                "Image URL": st.session_state.get("generated_image_url", "Not generated")
+            }
+
+# === Download Summary ===
+import io
+
+st.markdown("---")
+st.markdown("### 📥 Download Your Concept Summary")
+
+if st.button("Download Summary as Text"):
+    summary = st.session_state.design_summary
+    content = f"""🏠 AI Architecture Design Summary
+Prompt:
+{summary['Prompt']}
+Region: {summary['Region']}
+Style: {summary['Style']}
+Selected Categories: {', '.join(summary['Categories'])}
+🎨 Design Suggestions:
+{summary['Design Suggestions']}
+🧱 Recommended Materials:
+{summary['Materials']}
+🖼️ Floor Plan Image:
+{summary['Image URL']}
+"""
+
+    st.download_button(
+        label="Download Summary",
+        data=io.StringIO(content),
+        file_name="design_summary.txt",
+        mime="text/plain"
+    )
+
+# === Concept Image Generation ===
+st.markdown("### 🖼️ Visualizing Your Design Concept")
+
+if st.button("Generate Concept Image from Design Summary"):
+    with st.spinner("Creating a personalized visual..."):
+        refined_prompt = (
+    f"Based on the following tiny home project details:\n\n"
+    f"Region: {design_region}\n"
+    f"Style: {design_style}\n"
+    f"Categories: {', '.join(selected_categories)}\n"
+    f"Design Suggestions: {st.session_state.design_summary['Design Suggestions']}\n\n"
+    "Create a professional architectural rendering that visually reflects this concept.\n"
+    "Focus on realistic materials, lighting, and color palette. Use a 3D rendering style with natural surroundings."
+)
+
+
+        try:
+            response = client.images.generate(
+                model="dall-e-3",
+                prompt=refined_prompt,
+                size="1024x1024",
+                quality="standard",
+                n=1
+            )
+            concept_image_url = response.data[0].url
+            st.image(concept_image_url, caption="Generated Concept Image", use_column_width=True)
+            st.markdown(f"[Download Image]({concept_image_url})", unsafe_allow_html=True)
+
+            st.session_state.generated_concept_image_url = concept_image_url
+
+        except Exception as e:
+            st.error(f"Image generation failed: {e}")
+            
+if next_step == "🔍 Continue researching (codes, build types, regulations)":
+    st.markdown("#### 🔍 Research Hub")
+    st.info("Here are some useful topics and tools to help you dig deeper before you build.")
+
+    st.markdown("##### 🧠 Suggested Topics to Explore")
+    research_topics = {
+        "Prefab vs. Traditional Construction": "Compare pros and cons of prefabricated (modular) vs. traditional stick-built homes.",
+        "Land Use & Zoning": "Understand how land use bylaws and zoning affect what and where you can build.",
+        "Permit & Code Requirements": "Find out what permits are typically needed for a small home project in Canada.",
+        "Sustainable Building Materials": "Explore environmentally-friendly materials that are affordable and effective.",
+        "Off-Grid Living Regulations": "Learn the legal considerations if you want to live off-grid.",
+        "Energy Efficiency Standards": "Understand how to meet or exceed Canadian energy code requirements."
+    }
+
+    selected_topic = st.selectbox("Choose a topic to learn more:", ["Select a topic"] + list(research_topics.keys()))
+    if selected_topic != "Select a topic":
+        with st.spinner("Researching..."):
+            response = client.chat.completions.create(
+                model="gpt-4",
+                messages=[
+                    {"role": "system", "content": "You are a Canadian construction research assistant."},
+                    {"role": "user", "content": research_topics[selected_topic]}
+                ],
+                temperature=0.7
+            )
+            st.markdown(f"### 📖 {selected_topic}")
+            st.markdown(response.choices[0].message.content.strip())
+
+    st.markdown("##### 💬 Ask Your Own Research Question")
+user_question = st.text_input("What else would you like to learn about?")
+
+if st.button("Ask"):
+    if user_question:
+        with st.spinner("Getting the answer..."):
+            response = client.chat.completions.create(
+                model="gpt-4",
+                messages=[
+                    {"role": "system", "content": "You're a helpful Canadian homebuilding advisor. Keep answers clear and based on current standards."},
+                    {"role": "user", "content": user_question}
+                ],
+                temperature=0.7
+            )
+            st.markdown("### 💡 Answer")
+            st.markdown(response.choices[0].message.content.strip())
+    else:
+        st.warning("Please type a question first.")
+
+# === Helpful Resource Links (shown no matter what) ===
+st.markdown("##### 🔗 Helpful Resources")
+st.markdown("""
+- [National Building Code of Canada (2020)](https://nrc.canada.ca/en/certifications-evaluations-standards/codes-canada/codes-canada-publications/national-building-code-canada-2020)
+- [BC Building Code](https://www.bccodes.ca/)
+- [Alberta Building Codes & Standards](https://www.alberta.ca/building-codes-and-standards.aspx)
+- [Ontario Building Code](https://www.ontario.ca/page/building-code)
+- [Quebec Construction Code](https://www.rbq.gouv.qc.ca/en/technical-buildings/buildings/construction-code.html)
+- [Tiny Home Legal Info (Canada)](https://tinyhousecanada.ca/)
+""")
+# === 9. Eco-Friendly Upgrades Agent ===
+
+st.markdown("---")
+st.markdown("### 🌱 Suggest Eco-Friendly Upgrades")
+
+if st.button("Get Eco-Friendly Suggestions"):
+    if st.session_state.prompt.strip():
+        with st.spinner("Analyzing your layout for green upgrades..."):
+
+            def suggest_eco_upgrades(prompt):
+                system_instruction = (
+                    "You are a sustainability expert in residential architecture. "
+                    "Based on the following home design prompt, suggest 5 to 7 eco-friendly upgrades. "
+                    "Be specific and include options like energy efficiency, water conservation, material choices, and renewable energy use. "
+                    "Avoid general advice—tailor suggestions to the design and layout described."
+                )
+
+                response = client.chat.completions.create(
+                    model="gpt-4",
+                    messages=[
+                        {"role": "system", "content": system_instruction},
+                        {"role": "user", "content": prompt}
+                    ],
+                    temperature=0.7
+                )
+
+                return response.choices[0].message.content.strip()
+
+            eco_suggestions = suggest_eco_upgrades(st.session_state.prompt)
+
+            st.markdown("### ✅ Recommended Eco-Friendly Features")
+            st.markdown(eco_suggestions)
+
+            # Save to session for summary
+            st.session_state.eco_suggestions = eco_suggestions
+
+    else:
+        st.warning("Please enter a prompt first.")