feat: add document verification API views and core settings configurations

verifier/views.py

@@ -41,45 +41,20 @@ def compare_names(name1: str, name2: str) -> dict:
     if norm1 == norm2:
         return {"matched": True, "score": 100.0, "reason": "Exact name match"}
 
+    # Strict 100% match requirement: names must match 100%
+    # If spaces/delimiters differ, e.g. "VIGNESHKRISHNASAMY" vs "VIGNESH KRISHNASAMY"
+    if "".join(norm1.split()) == "".join(norm2.split()):
+        return {"matched": True, "score": 100.0, "reason": "Exact name match (case & whitespace insensitive)"}
+
+    # Any non-100% similarity is rejected as name mismatch
     words1, words2 = norm1.split(), norm2.split()
-    # Reject complete first name mismatch (e.g. PRIYA SHARMA vs ROHIT SHARMA)
-    if len(words1) >= 2 and len(words2) >= 2:
-        if words1[0] != words2[0] and words1[-1] != words2[0] and words1[0] != words2[-1]:
-            if len(words1[0]) >= 3 and len(words2[0]) >= 3:
-                fn_sim = SequenceMatcher(None, words1[0], words2[0]).ratio()
-                if fn_sim < 0.65:
-                    return {
-                        "matched": False,
-                        "score": round(fn_sim * 100, 1),
-                        "reason": f"First name mismatch ('{words1[0]}' vs '{words2[0]}')",
-                    }
-
-    set1, set2 = set(words1), set(words2)
-    if set1 == set2:
-        return {"matched": True, "score": 98.0, "reason": "Permuted words match"}
-
-    common = set1.intersection(set2)
-    if len(common) == min(len(set1), len(set2)):
-        return {"matched": True, "score": 95.0, "reason": "Subset token match"}
-
-    # Initial check (e.g. 'RAHUL K' vs 'RAHUL KUMAR' or 'V SANKAR' vs 'VIGNESH SANKAR')
-    if len(words1) == len(words2):
-        initial_match = True
-        for w1, w2 in zip(words1, words2):
-            if w1 != w2 and not (len(w1) == 1 and w2.startswith(w1)) and not (len(w2) == 1 and w1.startswith(w2)):
-                initial_match = False
-                break
-        if initial_match:
-            return {"matched": True, "score": 92.0, "reason": "Initials abbreviation match"}
-
     sort_ratio = SequenceMatcher(None, " ".join(sorted(words1)), " ".join(sorted(words2))).ratio() * 100
     seq_ratio = SequenceMatcher(None, norm1, norm2).ratio() * 100
-    best_score = max(sort_ratio, seq_ratio)
-    matched = best_score >= 80.0
+    sim_score = round(max(sort_ratio, seq_ratio), 1)
     return {
-        "matched": matched,
-        "score": round(best_score, 1),
-        "reason": "Fuzzy token match" if matched else "Name similarity score below 80% threshold",
+        "matched": False,
+        "score": sim_score,
+        "reason": f"Name match score is {sim_score}%. Strict 100% match is required.",
     }