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app.py

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+import streamlit as st
+import pandas as pd
+import joblib
+
+# Sayfa ayarları / Page Settings
+st.set_page_config(page_title="Fraud Guard Pro", page_icon="🛡️", layout="wide")
+
+# Modelleri yükle / Load Assets
+@st.cache_resource
+def load_assets():
+    model = joblib.load("fraud_model.pkl")
+    cols = joblib.load("columns.pkl")
+    return model, cols
+
+model, cols = load_assets()
+
+# --- BAŞLIK KISMI / HEADER SECTION ---
+st.markdown("<h1 style='text-align: center;'>🛡️ Fraud Guard Pro</h1>", unsafe_allow_html=True)
+st.markdown("<h3 style='text-align: center;'>Finansal Dolandırıcılık Analiz Sistemi | Financial Fraud Analysis System</h3>", unsafe_allow_html=True)
+st.markdown("---")
+
+# --- ÖRNEK SENARYOLAR / QUICK SCENARIOS ---
+st.subheader("🚀 Hızlı Test Senaryoları / Quick Test Scenarios")
+col_s1, col_s2 = st.columns(2)
+
+with col_s1:
+    if st.button("🚨 Şüpheli İşlem Örneği / Load Fraud Example"):
+        st.session_state.step = 1
+        st.session_state.type = "TRANSFER"
+        st.session_state.amount = 50000.0
+        st.session_state.oldorg = 50000.0
+        st.session_state.neworg = 0.0
+        st.warning("Şüpheli senaryo yüklendi! / Fraud scenario loaded!")
+
+with col_s2:
+    if st.button("✅ Güvenli İşlem Örneği / Load Safe Example"):
+        st.session_state.step = 1
+        st.session_state.type = "PAYMENT"
+        st.session_state.amount = 150.0
+        st.session_state.oldorg = 2500.0
+        st.session_state.neworg = 2350.0
+        st.success("Güvenli senaryo yüklendi! / Safe scenario loaded!")
+
+# --- SOL MENÜ: VERİ GİRİŞİ / SIDEBAR: DATA INPUT ---
+st.sidebar.header("📥 İşlem Detayları / Transaction Details")
+
+step = st.sidebar.number_input("Adım / Step", value=st.session_state.get('step', 1))
+type_options = ["CASH_OUT", "TRANSFER", "PAYMENT", "DEBIT"]
+type_input = st.sidebar.selectbox("Tür / Type", type_options, 
+                                 index=type_options.index(st.session_state.get('type', 'CASH_OUT')))
+amount = st.sidebar.number_input("Tutar / Amount", value=st.session_state.get('amount', 0.0))
+oldbalanceOrg = st.sidebar.number_input("Gönderen Eski Bakiye / Sender Old Bal.", value=st.session_state.get('oldorg', 0.0))
+newbalanceOrig = st.sidebar.number_input("Gönderen Yeni Bakiye / Sender New Bal.", value=st.session_state.get('neworg', 0.0))
+oldbalanceDest = st.sidebar.number_input("Alıcı Eski Bakiye / Receiver Old Bal.", value=0.0)
+newbalanceDest = st.sidebar.number_input("Alıcı Yeni Bakiye / Receiver New Bal.", value=0.0)
+
+# Veriyi hazırlama / Data Preparation
+input_df = pd.DataFrame([[step, amount, oldbalanceOrg, newbalanceOrig, oldbalanceDest, newbalanceDest]],
+                        columns=["step", "amount", "oldbalanceOrg", "newbalanceOrig", "oldbalanceDest", "newbalanceDest"])
+
+for t in type_options:
+    input_df["type_" + t] = 1 if type_input == t else 0
+
+input_df = input_df.reindex(columns=cols, fill_value=0)
+
+# --- ANALİZ VE SONUÇ / ANALYSIS AND RESULT ---
+st.divider()
+if st.button("🔍 ANALİZ ET / ANALYZE NOW", use_container_width=True):
+    prediction = model.predict(input_df)
+    
+    res_col1, res_col2 = st.columns([1, 2])
+    
+    with res_col1:
+        if prediction[0] == 1:
+            st.error("🚨 SONUÇ / RESULT: ŞÜPHELİ / FRAUD")
+            st.metric(label="Risk", value="HIGH / YÜKSEK")
+        else:
+            st.success("✅ SONUÇ / RESULT: GÜVENLİ / SAFE")
+            st.metric(label="Risk", value="LOW / DÜŞÜK")
+
+    with res_col2:
+        st.subheader("📝 Karar Analizi / Decision Analysis")
+        if prediction[0] == 1:
+            st.write("🚩 **Neden Şüpheli? / Why Fraud?**")
+            st.write("- Tr: İşlem türü yüksek riskli grupta. / En: High-risk transaction type.")
+            if amount >= oldbalanceOrg and amount > 0:
+                st.write("- Tr: Hesap bakiyesi tamamen boşaltılıyor. / En: Account is being emptied.")
+        else:
+            st.write("🛡️ **Neden Güvenli? / Why Safe?**")
+            st.write("- Tr: Şüpheli bir bakiye hareketi saptanmadı. / En: No suspicious balance movement detected.")
+            if type_input in ["PAYMENT", "DEBIT"]:
+                st.write("- Tr: Düşük riskli işlem kategorisi. / En: Low-risk category.")
+
+st.sidebar.markdown("---")
+st.sidebar.caption("Dev: Esma | Model: Random Forest")

columns.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b0ee326e0fcf79a2c94bcecdd855e006c102ecd03b3f2dba03eb31fefb4b2871
+size 599

fraud_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c37db75a1db2a709964b4d7ea3ee24948dbc49f5a1d1d104aa9a01a5762711a4
+size 3147609