Update modules/proverbs.py

modules/proverbs.py

@@ -1,23 +1,176 @@
-from rapidfuzz import process
+import os
+import pandas as pd
+from rapidfuzz import process, fuzz
 
-def search_proverb(text, df):
+# ============================================================
+# DATA LOCATION
+# ============================================================
 
-    choices = df["Kiembu"].astype(str).tolist()
+BASE_DIR = os.path.dirname(
+    os.path.dirname(
+        os.path.abspath(__file__)
+    )
+)
+
+PROVERB_FILE = os.path.join(
+    BASE_DIR,
+    "data",
+    "proverbs.csv"
+)
+
+# ============================================================
+# LOAD PROVERBS
+# ============================================================
+
+def load_proverbs():
+
+    try:
+
+        df = pd.read_csv(
+            PROVERB_FILE,
+            encoding="utf-8"
+        )
+
+        df.columns = (
+            df.columns
+            .str.strip()
+        )
+
+        df.fillna("", inplace=True)
+
+        print("Proverbs loaded successfully")
+        print("Columns:", df.columns.tolist())
+        print("Records:", len(df))
+
+        return df
+
+    except Exception as e:
+
+        print(
+            f"Proverb loading error: {e}"
+        )
+
+        return pd.DataFrame()
+
+# ============================================================
+# GLOBAL DATAFRAME
+# ============================================================
+
+proverb_df = load_proverbs()
+
+# ============================================================
+# SEARCH PROVERB
+# ============================================================
+
+def search_proverb(text, df=None):
+
+    if df is None:
+        df = proverb_df
+
+    if df.empty:
+        return "Proverb database unavailable."
+
+    if not text:
+        return "Please enter a proverb or keyword."
+
+    query = text.strip()
+
+    if not query:
+        return "Please enter a proverb or keyword."
+
+    # ========================================================
+    # VERIFY REQUIRED COLUMNS
+    # ========================================================
 
-    match = process.extractOne(
-        text,
-        choices
+    required_columns = ["Kiembu", "English"]
+
+    for col in required_columns:
+
+        if col not in df.columns:
+
+            return (
+                f"Missing column '{col}' "
+                f"in proverbs.csv"
+            )
+
+    # ========================================================
+    # EXACT MATCH
+    # ========================================================
+
+    exact_match = df[
+        df["Kiembu"]
+        .astype(str)
+        .str.lower()
+        .str.strip()
+        == query.lower()
+    ]
+
+    if not exact_match.empty:
+
+        proverb = exact_match.iloc[0]["Kiembu"]
+        meaning = exact_match.iloc[0]["English"]
+
+        return f"""
+### Proverb Found
+
+**Kiembu**
+
+{proverb}
+
+**English Meaning**
+
+{meaning}
+"""
+
+    # ========================================================
+    # FUZZY SEARCH
+    # ========================================================
+
+    choices = (
+        df["Kiembu"]
+        .astype(str)
+        .tolist()
+    )
+
+    best_match = process.extractOne(
+        query,
+        choices,
+        scorer=fuzz.WRatio
     )
 
-    if match:
+    if not best_match:
 
-        row = df[
-            df["Kiembu"] == match[0]
-        ]
+        return "No proverb found."
+
+    proverb = best_match[0]
+    score = best_match[1]
+
+    if score < 70:
 
         return (
-            f"Kiembu: {row.iloc[0]['Kiembu']}\n\n"
-            f"English: {row.iloc[0]['English']}"
+            "No close proverb found.\n\n"
+            f"Best similarity score: {score}"
         )
 
-    return "No proverb found"
+    row = df[
+        df["Kiembu"]
+        .astype(str)
+        == proverb
+    ]
+
+    if row.empty:
+        return "No proverb found."
+
+    meaning = row.iloc[0]["English"]
+
+    return f"""
+### Suggested Proverb
+
+**Kiembu**
+
+{proverb}
+
+**English Meaning**
+
+{meaning}
+"""