Update app.py

app.py

@@ -1,7 +1,7 @@
 import streamlit as st
 from PIL import Image
 from io import BytesIO
-import openai
+import requests
 import base64
 import time
 from datetime import datetime
@@ -28,13 +28,10 @@ st.markdown(
     unsafe_allow_html=True
 )
 
-# --- OpenAI SDK client caching ---
-@st.cache_resource
-def get_openai_client(api_key: str):
-    openai.api_key = api_key
-    return openai
+# --- Configuration ---
+API_URL = "https://api.openai.com/v1/chat/completions"
 
-# --- Image encoding helper ---
+# --- Cache utilities ---
 @st.cache_data
 def encode_image_to_b64(image: Image.Image) -> str:
     # Convert to RGB if needed
@@ -52,94 +49,78 @@ def encode_image_to_b64(image: Image.Image) -> str:
     image.save(buf, format='JPEG', quality=85)
     return base64.b64encode(buf.getvalue()).decode('utf-8')
 
-# --- Simple formatting fixes ---
 def fix_formatting(text: str) -> str:
     text = re.sub(r'(\d+)([A-Za-z])', r'\1 \2', text)
     text = re.sub(r'([.,])([A-Za-z0-9])', r'\1 \2', text)
     text = re.sub(r':([A-Za-z0-9])', r': \1', text)
     return text
 
-# --- System prompt ---
-SYSTEM_PROMPT = f"""
-You are an expert real estate advisor with deep knowledge of home selling strategies. You analyze home photos to provide EXTREMELY SPECIFIC, actionable recommendations that will maximize the property's selling price.
-
-ONLY make recommendations based on visible areas in the photos. Reference exact features, colors, materials, and conditions you can see.
-
-FORMAT:
-### 📋 HOME VALUE MAXIMIZER SUMMARY
-- Start with exactly this header.
-- Then: "Below are the top improvements to maximize your home’s value..."
-- List 5 bullet points: **bold issue**, specific solution, estimated ROI.
-
-### 👁️ AREAS ANALYZED
-List which areas you see (e.g., Kitchen, Living Room).
-
-### 🌟 TOP PRICE-MAXIMIZING PRIORITIES
-For the 3–4 biggest improvements: exact issue, precise recommendation, cost estimate, value impact, timeline.
-
-### 🔨 QUICK WINS (1–3 days)
-List 5–6 fast, high-ROI fixes for visible areas; include product names/colors/costs.
-
-### 📊 SPECIFIC PRICING STRATEGY
-- Precise price point and pricing psychology (spaces between numbers and text).
-- Exact timing: days/dates based on current date ({datetime.now().strftime('%B %d, %Y')}).
-
-### 📸 DETAILED MARKETING PLAN
-List specific features to highlight, angles, staging items, virtual tools.
-
-### 📝 SPECIFIC NEGOTIATION TACTICS
-Exact scripts, inspection strategies, contingency planning.
-
-### ⚠️ CRITICAL ISSUES TO ADDRESS
-List 3 visible problems with exact fixes.
-
-### 📅 DETAILED TIMELINE WITH DATES
-Provide calendar dates for each step, from today.
-
-### 🚫 AREAS NOT VISIBLE
-Note any important areas you couldn’t see.
-"""
-
-# --- Streamlit layout ---
+# --- Analysis function via requests ---
+def analyze_home_photos(images, timeframe, details, api_key):
+    if not api_key:
+        return "Error: API key is required."
+    headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
+    # Build system prompt
+    system_prompt = (
+        f"You are a real estate advisor. Today's date is {datetime.now().strftime('%B %d, %Y')}. "
+        "Analyze only visible areas in the images and give hyper-specific recommendations."
+    )
+    # Build user content with embedded images
+    user_content = f"Sell within {timeframe}. {details}\n\n"
+    for img in images:
+        b64 = encode_image_to_b64(img)
+        user_content += f"![photo](data:image/jpeg;base64,{b64})\n\n"
+    payload = {
+        "model": "gpt-4o",
+        "messages": [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": user_content}
+        ],
+        "max_tokens": 2000
+    }
+    resp = requests.post(API_URL, headers=headers, json=payload, timeout=90)
+    if resp.status_code == 200:
+        data = resp.json()
+        text = data['choices'][0]['message']['content']
+        return fix_formatting(text)
+    return f"API Error {resp.status_code}: {resp.text[:200]}"
+
+# --- Cost calculation ---
+def calculate_cost(usage):
+    if not usage:
+        return 0.0
+    in_tok = usage.get('prompt_tokens',0)
+    out_tok = usage.get('completion_tokens',0)
+    cost = in_tok/1e6*3 + out_tok/1e6*10
+    return cost
+
+# --- App layout ---
 st.title("Home Value Maximizer 🏡")
-st.write("Upload photos, enter your timeline & budget, then click Analyze for detailed, hyper-specific advice.")
 
-# API key
+# Sidebar inputs
 api_key = st.sidebar.text_input("OpenAI API Key", type="password")
-client = get_openai_client(api_key) if api_key else None
-
-# Upload images
-st.sidebar.header("📸 Upload Home Photos")
-uploaded = st.sidebar.file_uploader("Images", type=["jpg","png","jpeg"], accept_multiple_files=True)
-images = []
-for file in uploaded:
-    try:
-        img = Image.open(file)
-        images.append(img)
-    except:
-        st.sidebar.error(f"Failed to load {file.name}")
+uploaded = st.sidebar.file_uploader("Upload home photos", accept_multiple_files=True, type=["jpg","png","jpeg"])
 
-# Inputs
 timeframe = st.sidebar.selectbox("Selling timeframe", ["Within 1 month","1–3 months","3–6 months","6–12 months",">12 months"])
 budget = st.sidebar.slider("Max improvement budget ($)", 1000, 50000, 10000, 1000)
-improve_focus = st.sidebar.multiselect("Focus areas (opt)", ["Curb appeal","Kitchen","Bathroom","Living Spaces","Outdoor","Storage","Energy","Marketing","Negotiation","Staging"], default=["Kitchen","Bathroom"])
+focus = st.sidebar.multiselect("Focus areas", ["Curb appeal","Kitchen","Bathroom","Living Spaces","Outdoor","Storage"], default=["Kitchen","Bathroom"])
 
-# Analyze button
-if st.button("🔍 Analyze My Home"):
-    if not client:
-        st.error("Enter API key to analyze.")
-    elif not images:
-        st.error("Upload at least one photo.")
+if st.sidebar.button("🔍 Analyze My Home"):
+    if not api_key:
+        st.sidebar.error("Enter API key.")
+    elif not uploaded:
+        st.sidebar.error("Upload at least one photo.")
     else:
+        images = []
+        for f in uploaded:
+            try: images.append(Image.open(f))
+            except: pass
         with st.spinner("Analyzing..."):
-            user_details = f"Budget: ${budget}. Focus: {', '.join(improve_focus)}"
-            analysis = analyze_home_photos(images, timeframe, user_details, client)
-            st.success("Analysis complete!")
-            st.markdown(f"<div style='background:#e3f2fd;padding:1rem;border-left:4px solid #1f77b4;'>{analysis}</div>", unsafe_allow_html=True)
-            # Cost
-            usage = client.api_usage if hasattr(client, 'api_usage') else {}
-            cost = calculate_cost(usage)
-            st.metric("💲 Estimated Cost", f"${cost:.2f}")
-
-else:
-    st.info("Submit images & API key to generate recommendations.")
+            result = analyze_home_photos(images, timeframe, f"Budget ${budget}. Focus: {', '.join(focus)}", api_key)
+        st.markdown(f"<div style='background:#e3f2fd;padding:1rem;border-left:4px solid #1f77b4;'>{result}</div>", unsafe_allow_html=True)
+        # Cost display
+        # Note: HF Spaces does not return usage, so this may be blank
+        usage = {}  # placeholder
+        cost = calculate_cost(usage)
+        st.metric("💲 Estimated cost", f"${cost:.2f}")
+```