refs #708 #739: use Cohere command and vector game scope

database/adb/81_sg_game_query_plan.sql

@@ -1,32 +1,57 @@
--- OCI GenAI candidate selection. Vector distance only orders candidates; the
--- model may select one supplied game_key or explicitly reject all candidates.
+-- Vector-score candidate selection. The closest catalog vector is accepted
+-- only when it is within the customer-managed policy threshold.
 CREATE OR REPLACE FUNCTION sg_game_match_candidate(
   p_mention IN CLOB,
   p_candidates_json IN CLOB
 ) RETURN CLOB AUTHID DEFINER
 IS
-  v_prompt CLOB;
-  v_result CLOB;
+  v_candidates JSON_ARRAY_T;
+  v_candidate JSON_OBJECT_T;
+  v_result JSON_OBJECT_T := JSON_OBJECT_T();
+  v_threshold NUMBER;
+  v_distance NUMBER;
+  v_game_key VARCHAR2(128);
 BEGIN
-  v_prompt := 'Decide whether the extracted game-name mention refers to exactly '
-    || 'one game in the supplied candidate array. Candidate vector distance is '
-    || 'retrieval evidence only and must not establish identity. Compare the '
-    || 'mention with candidate gameName, aliases, gameId, and gamePrefix. '
-    || 'If one candidate clearly identifies the same game, return exactly '
-    || '{"status":"MATCHED","game_key":"candidate key","reason":"short reason"}. '
-    || 'If none clearly identifies the same game, return exactly '
-    || '{"status":"UNMATCHED","game_key":null,"reason":"short reason"}. '
-    || 'Never invent a game_key and never return a key absent from the supplied '
-    || 'candidate array. Mention: '
-    || DBMS_LOB.SUBSTR(p_mention, 1000, 1)
-    || ' Candidates: '
-    || DBMS_LOB.SUBSTR(p_candidates_json, 12000, 1);
-  v_result := DBMS_CLOUD_AI.GENERATE(
-    prompt => v_prompt,
-    profile_name => 'SGMP_POC_OCI_GPT54MINI',
-    action => 'chat'
-  );
-  RETURN v_result;
+  SELECT number_value
+    INTO v_threshold
+    FROM sg_game_scope_policy
+   WHERE policy_key = 'GAME_ALIAS_MAX_COSINE_DISTANCE'
+     AND active_yn = 'Y';
+
+  v_candidates := JSON_ARRAY_T.parse(p_candidates_json);
+  IF v_candidates.get_size = 0 THEN
+    v_result.put('status', 'UNMATCHED');
+    v_result.put_null('game_key');
+    v_result.put('reason', 'No active game catalog vector candidate was returned.');
+    RETURN v_result.to_clob;
+  END IF;
+
+  v_candidate := TREAT(v_candidates.get(0) AS JSON_OBJECT_T);
+  v_distance := v_candidate.get_number('cosineDistance');
+  v_game_key := v_candidate.get_string('gameKey');
+
+  IF v_distance <= v_threshold THEN
+    v_result.put('status', 'MATCHED');
+    v_result.put('game_key', v_game_key);
+    v_result.put(
+      'reason',
+      'Closest catalog vector distance '
+      || TO_CHAR(v_distance, 'FM0D000000')
+      || ' is within configured maximum '
+      || TO_CHAR(v_threshold, 'FM0D000000') || '.'
+    );
+  ELSE
+    v_result.put('status', 'UNMATCHED');
+    v_result.put_null('game_key');
+    v_result.put(
+      'reason',
+      'Closest catalog vector distance '
+      || TO_CHAR(v_distance, 'FM0D000000')
+      || ' exceeds configured maximum '
+      || TO_CHAR(v_threshold, 'FM0D000000') || '.'
+    );
+  END IF;
+  RETURN v_result.to_clob;
 END;
 /
 
@@ -255,14 +280,14 @@ BEGIN
 
       IF v_matched_candidate IS NOT NULL THEN
         v_mention_result.put('status', 'MATCHED');
-        v_mention_result.put('reasonCode', 'LLM_CANDIDATE_MATCH');
+        v_mention_result.put('reasonCode', 'VECTOR_SCORE_MATCH');
         v_mention_result.put('matchedGameKey', v_selected_key);
 
         v_target := JSON_OBJECT_T.parse(v_matched_candidate.to_clob);
         v_target.put('mention', v_mention);
         v_target.put('status', 'MATCHED');
         v_target.put('matchStatus', 'MATCHED');
-        v_target.put('reasonCode', 'LLM_CANDIDATE_MATCH');
+        v_target.put('reasonCode', 'VECTOR_SCORE_MATCH');
         v_target.put('reason', v_reason);
         v_matched_count := v_matched_count + 1;
 
@@ -282,14 +307,7 @@ BEGIN
         END IF;
       ELSE
         v_mention_result.put('status', 'UNMATCHED');
-        IF v_decision_status = 'MATCHED' THEN
-          v_mention_result.put(
-            'reasonCode',
-            'LLM_SELECTED_UNKNOWN_CANDIDATE'
-          );
-        ELSE
-          v_mention_result.put('reasonCode', 'LLM_NO_CANDIDATE_MATCH');
-        END IF;
+        v_mention_result.put('reasonCode', 'VECTOR_SCORE_OVER_THRESHOLD');
 
         v_target := JSON_OBJECT_T();
         v_target.put('mention', v_mention);