Update app.py

app.py

@@ -28,18 +28,78 @@ OPENROUTER_BASE_URL = "https://openrouter.ai/api/v1"
 def initialize_ocr():
     """Inisialisasi model PaddleOCR tanpa parameter GPU."""
     try:
-        # Hanya tentukan language dan angle classifier
         return PaddleOCR(lang='en', use_angle_cls=True)
     except Exception as e:
         st.error(f"Gagal inisialisasi OCR: {e}")
         return None
 
+
+def parse_numeric_value(text: str) -> float:
+    """Parse string menjadi float dengan menghapus karakter non-numerik."""
+    cleaned = re.sub(r"[^\d\.\-]", "", str(text))
+    if cleaned in ['', '.', '-']:
+        return 0.0
+    try:
+        return float(cleaned)
+    except:
+        return 0.0
+
+
+def get_nutrition_advice(serving_size, sugar_norm, fat_norm, sugar_grade, fat_grade, final_grade):
+    """Memanggil API OpenRouter untuk mendapatkan saran nutrisi."""
+    prompt = f"""
+    Anda adalah ahli gizi dari Indonesia yang ramah.
+    - Takaran Saji: {serving_size} g/ml
+    - Gula (per 100): {sugar_norm:.2f} g (Grade {sugar_grade.replace('Grade ', '')})
+    - Lemak Jenuh (per 100): {fat_norm:.2f} g (Grade {fat_grade.replace('Grade ', '')})
+    - Grade Akhir: {final_grade.replace('Grade ', '')}
+
+    Berikan saran nutrisi singkat 50-80 kata, fokus pada dampak kesehatan dan tips praktis.
+    """
+    headers = {"Authorization": f"Bearer {OPENROUTER_API_KEY}", "Content-Type": "application/json"}
+    payload = {
+        "model": "mistralai/mistral-7b-instruct:free",
+        "messages": [{"role": "user", "content": prompt}],
+        "max_tokens": 250,
+        "temperature": 0.7
+    }
+    try:
+        r = requests.post(f"{OPENROUTER_BASE_URL}/chat/completions", headers=headers, json=payload, timeout=30)
+        r.raise_for_status()
+        data = r.json()
+        return data["choices"][0]["message"]["content"].strip()
+    except Exception as e:
+        return f"Error: {e}"
+
+
+def get_grade_from_value(value, thresholds):
+    if value <= thresholds["A"]:
+        return "Grade A"
+    if value <= thresholds["B"]:
+        return "Grade B"
+    if value <= thresholds["C"]:
+        return "Grade C"
+    return "Grade D"
+
+
+def get_grade_color(grade):
+    colors = {
+        "Grade A": ("#2ecc71", "white"),
+        "Grade B": ("#f1c40f", "black"),
+        "Grade C": ("#e67e22", "white"),
+        "Grade D": ("#e74c3c", "white")
+    }
+    return colors.get(grade, ("#bdc3c7", "black"))
+
+
 def reset_state():
-    for k in ['ocr_done','data','calculated']:
-        st.session_state.pop(k, None)
+    for k in ['ocr_done', 'data', 'calculated', 'calc']:
+        if k in st.session_state:
+            del st.session_state[k]
 
 # --- UI APLIKASI ---
 
+# Inisialisasi OCR
 cr = initialize_ocr()
 if cr is None:
     st.error("Model OCR tidak tersedia.")
@@ -59,7 +119,7 @@ with st.expander("📋 Petunjuk Penggunaan"):
 
 # Langkah 1: Upload
 st.header("1. Upload Gambar")
-file = st.file_uploader("Pilih gambar tabel gizi", type=["jpg","jpeg","png"], on_change=reset_state)
+file = st.file_uploader("Pilih gambar tabel gizi", type=["jpg", "jpeg", "png"], on_change=reset_state)
 
 if file:
     arr = np.frombuffer(file.read(), np.uint8)
@@ -68,7 +128,7 @@ if file:
 
     if st.button("Analisis OCR"):
         with st.spinner("Mendeteksi teks..."):
-            res = cr.ocr(img, cls=True)
+            res = cr.ocr(img)
         texts = [ln[1][0] for ln in (res[0] if res else [])]
         full = " ".join(texts).lower()
         patterns = {
@@ -77,7 +137,7 @@ if file:
             'fat': r"(lemak jenuh|saturated fat)[^\d]*(\d+\.?\d*)"
         }
         data = {}
-        for k,p in patterns.items():
+        for k, p in patterns.items():
             m = re.search(p, full)
             if m:
                 data[k] = m.group(2)
@@ -91,38 +151,43 @@ if st.session_state.get('ocr_done'):
     st.header("2. Koreksi & Hitung Grade")
     d = st.session_state.data
     with st.form("form2"):
-        serving = st.text_input("Takaran Saji (g/ml)", value=d.get('serving','100'))
-        sugar = st.text_input("Gula (g)", value=d.get('sugar','0'))
-        fat = st.text_input("Lemak Jenuh (g)", value=d.get('fat','0'))
+        serving = st.text_input("Takaran Saji (g/ml)", value=d.get('serving', '100'))
+        sugar = st.text_input("Gula (g)", value=d.get('sugar', '0'))
+        fat = st.text_input("Lemak Jenuh (g)", value=d.get('fat', '0'))
         ok = st.form_submit_button("Hitung Grade")
     if ok:
         sv = parse_numeric_value(serving)
         sg = parse_numeric_value(sugar)
         fg = parse_numeric_value(fat)
-        sp = sg/sv*100 if sv>0 else 0
-        fp = fg/sv*100 if sv>0 else 0
-        st.session_state.calc = {'sv':sv,'sp':sp,'fp':fp}
+        sp = (sg / sv) * 100 if sv > 0 else 0
+        fp = (fg / sv) * 100 if sv > 0 else 0
+        st.session_state.calc = {'sv': sv, 'sp': sp, 'fp': fp}
         st.session_state.calculated = True
 
 # Langkah 3: Tampilkan Hasil
 if st.session_state.get('calculated'):
     c = st.session_state.calc
-    gs = get_grade_from_value(c['sp'],{"A":1.0,"B":5.0,"C":10.0})
-    gf = get_grade_from_value(c['fp'],{"A":0.7,"B":1.2,"C":2.8})
-    gf_final = max(gs,gf, key=lambda x: ['Grade A','Grade B','Grade C','Grade D'].index(x))
+    gs = get_grade_from_value(c['sp'], {"A": 1.0, "B": 5.0, "C": 10.0})
+    gf = get_grade_from_value(c['fp'], {"A": 0.7, "B": 1.2, "C": 2.8})
+    final_grade = max(gs, gf, key=lambda x: ['Grade A', 'Grade B', 'Grade C', 'Grade D'].index(x))
+
     st.header("3. Hasil Grading")
     cols = st.columns(3)
-    def show(col,title,val,unit,gr):
-        bc,tc = get_grade_color(gr)
-        col.markdown(f"<div style='background:{bc};padding:10px;border-radius:8px;text-align:center;color:{tc};'>"
-                     f"<strong>{title}</strong><p>{val:.2f} {unit}</p><h4>{gr}</h4></div>",unsafe_allow_html=True)
-    show(cols[0],"Gula",c['sp'],"g/100ml",gs)
-    show(cols[1],"Lemak Jenuh",c['fp'],"g/100ml",gf)
-    show(cols[2],"Grade Akhir",0,"",gf_final)
+    def show(col, title, value, unit, grade):
+        bg, textc = get_grade_color(grade)
+        col.markdown(
+            f"<div style='background:{bg};padding:10px;border-radius:8px;text-align:center;color:{textc};'>"
+            f"<strong>{title}</strong><p>{value:.2f} {unit}</p><h4>{grade}</h4></div>",
+            unsafe_allow_html=True
+        )
+    show(cols[0], "Gula", c['sp'], "g/100ml", gs)
+    show(cols[1], "Lemak Jenuh", c['fp'], "g/100ml", gf)
+    show(cols[2], "Grade Akhir", 0, "", final_grade)
+
     st.divider()
     st.header("4. Saran Nutrisi AI")
     with st.spinner("Meminta AI..."):
-        advice = get_nutrition_advice(c['sv'],c['sp'],c['fp'],gs,gf,gf_final)
+        advice = get_nutrition_advice(c['sv'], c['sp'], c['fp'], gs, gf, final_grade)
     st.info(advice)
 
 # Footer