refs #737: move game query planning into ADB MCP tool
This commit is contained in:
devmrko
@@ -50,10 +50,13 @@ Smilegate view는 전체 게임 마스터와 alias를 기준으로 하고, 현
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- ADB Chat이 반환한 `game_mentions`의 각 항목은 서로 독립적으로 판정한다. 벡터 검색 결과를
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하나의 목록으로 합쳐 모든 후보를 지원 게임으로 취급하지 않는다.
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- 벡터 검색은 후보를 찾는 단계다. 후보의 카탈로그 명칭, 별칭, `GAME_ID`, `GAME_PREFIX` 중
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추출 명칭과 정규화 매칭되는 항목만 `supportedGames`에 넣는다.
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- 추출 명칭과 매칭되는 카탈로그 항목이 없으면 해당 원문 명칭을 `unmatchedGames`에 남긴다.
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유사도 순위가 높다는 이유만으로 다른 게임에 대입하지 않는다.
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- 벡터 검색은 후보를 찾는 단계다. ADB OCI GenAI가 추출 명칭과 후보의 카탈로그 명칭,
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별칭, `GAME_ID`, `GAME_PREFIX`를 비교해 후보 중 하나를 선택하거나 전체를 거절한다.
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- 애플리케이션은 모델이 반환한 `gameKey`가 실제 후보 목록에 있을 때만
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`supportedGames`에 넣는다. 후보 목록에 없는 식별자는 거절한다.
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- 모델이 모든 후보를 거절하면 해당 원문 명칭을 `unmatchedGames`에 남긴다. 유사도 순위가
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높다는 이유만으로 다른 게임에 대입하지 않는다.
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- 게임 판정에 정규식, 부분문자열 매칭, 유사도 임계값을 사용하지 않는다.
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- 동일 게임이 여러 명칭으로 검색되더라도 `supportedGames`는 `gameKey` 기준으로 중복을
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제거한다. `matchedGames`와 `unmatchedGames`에는 mention별 판정 근거를 유지한다.
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- 일부만 지원되는 복수 게임 질문은 `status=PARTIAL`로 반환하고, 지원 게임의 worker 실행과
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194
sql/adb/81_sg_game_query_plan.sql
Normal file
194
sql/adb/81_sg_game_query_plan.sql
Normal file
@@ -0,0 +1,194 @@
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-- OCI GenAI candidate selection. Vector distance only orders candidates; the
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-- model may select one supplied game_key or explicitly reject all candidates.
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CREATE OR REPLACE FUNCTION sg_game_match_candidate(
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p_mention IN CLOB,
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p_candidates_json IN CLOB
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) RETURN CLOB AUTHID DEFINER
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IS
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v_prompt CLOB;
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v_result CLOB;
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BEGIN
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v_prompt := 'Decide whether the extracted game-name mention refers to exactly '
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|| 'one game in the supplied candidate array. Candidate vector distance is '
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|| 'retrieval evidence only and must not establish identity. Compare the '
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|| 'mention with candidate gameName, aliases, gameId, and gamePrefix. '
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|| 'If one candidate clearly identifies the same game, return exactly '
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|| '{"status":"MATCHED","game_key":"candidate key","reason":"short reason"}. '
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|| 'If none clearly identifies the same game, return exactly '
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|| '{"status":"UNMATCHED","game_key":null,"reason":"short reason"}. '
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|| 'Never invent a game_key and never return a key absent from the supplied '
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|| 'candidate array. Mention: '
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|| DBMS_LOB.SUBSTR(p_mention, 1000, 1)
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|| ' Candidates: '
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|| DBMS_LOB.SUBSTR(p_candidates_json, 12000, 1);
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v_result := DBMS_CLOUD_AI.GENERATE(
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prompt => v_prompt,
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profile_name => 'SGMP_POC_OCI_GPT54MINI',
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action => 'chat'
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);
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RETURN v_result;
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END;
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/
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-- Complete game query planning inside ADB. The MCP server only invokes this
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-- function and returns its structured result.
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CREATE OR REPLACE FUNCTION sg_game_query_plan(
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p_question IN CLOB,
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p_top_k IN PLS_INTEGER DEFAULT 5
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) RETURN CLOB AUTHID DEFINER
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IS
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TYPE t_seen_game_keys IS TABLE OF BOOLEAN INDEX BY VARCHAR2(128);
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v_extract_raw CLOB;
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v_extract JSON_OBJECT_T;
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v_mentions JSON_ARRAY_T;
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v_scope_type VARCHAR2(30);
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v_supported JSON_ARRAY_T := JSON_ARRAY_T();
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v_unmatched JSON_ARRAY_T := JSON_ARRAY_T();
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v_mention_results JSON_ARRAY_T := JSON_ARRAY_T();
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v_seen_game_keys t_seen_game_keys;
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v_result JSON_OBJECT_T := JSON_OBJECT_T();
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v_mention VARCHAR2(1000);
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v_candidates JSON_ARRAY_T;
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v_candidate JSON_OBJECT_T;
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v_decision_raw CLOB;
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v_decision JSON_OBJECT_T;
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v_decision_status VARCHAR2(30);
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v_selected_key VARCHAR2(128);
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v_reason VARCHAR2(4000);
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v_matched_candidate JSON_OBJECT_T;
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v_mention_result JSON_OBJECT_T;
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v_unmatched_item JSON_OBJECT_T;
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v_cursor SYS_REFCURSOR;
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v_game_key VARCHAR2(128);
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v_game_id VARCHAR2(128);
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v_game_prefix VARCHAR2(128);
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v_game_nm VARCHAR2(512);
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v_game_alias_nm VARCHAR2(512);
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v_cosine_distance NUMBER;
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BEGIN
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v_extract_raw := sg_game_extract_mentions(p_question);
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v_extract := JSON_OBJECT_T.parse(v_extract_raw);
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v_mentions := v_extract.get_array('game_mentions');
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v_scope_type := NVL(v_extract.get_string('scope_hint'), 'UNKNOWN');
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FOR i IN 0 .. v_mentions.get_size - 1 LOOP
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v_mention := v_mentions.get_string(i);
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v_candidates := JSON_ARRAY_T();
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v_cursor := sg_game_catalog_search(
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v_mention,
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LEAST(GREATEST(NVL(p_top_k, 5), 1), 20)
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);
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LOOP
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FETCH v_cursor INTO
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v_game_key,
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v_game_id,
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v_game_prefix,
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v_game_nm,
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v_game_alias_nm,
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v_cosine_distance;
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EXIT WHEN v_cursor%NOTFOUND;
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v_candidate := JSON_OBJECT_T();
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v_candidate.put('gameKey', v_game_key);
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v_candidate.put('gameId', v_game_id);
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v_candidate.put('gamePrefix', v_game_prefix);
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v_candidate.put('gameName', v_game_nm);
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v_candidate.put('aliases', v_game_alias_nm);
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v_candidate.put('cosineDistance', v_cosine_distance);
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v_candidates.append(v_candidate);
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END LOOP;
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CLOSE v_cursor;
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v_decision_raw := sg_game_match_candidate(
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v_mention,
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v_candidates.to_clob
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);
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v_decision := JSON_OBJECT_T.parse(v_decision_raw);
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v_decision_status := UPPER(
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NVL(v_decision.get_string('status'), 'UNMATCHED')
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);
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v_selected_key := v_decision.get_string('game_key');
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v_reason := v_decision.get_string('reason');
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v_matched_candidate := NULL;
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IF v_decision_status = 'MATCHED' AND v_selected_key IS NOT NULL THEN
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FOR j IN 0 .. v_candidates.get_size - 1 LOOP
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v_candidate := TREAT(v_candidates.get(j) AS JSON_OBJECT_T);
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IF v_candidate.get_string('gameKey') = v_selected_key THEN
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v_matched_candidate := v_candidate;
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EXIT;
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END IF;
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END LOOP;
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END IF;
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v_mention_result := JSON_OBJECT_T();
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v_mention_result.put('mention', v_mention);
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v_mention_result.put('candidateGames', v_candidates);
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v_mention_result.put('reason', v_reason);
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IF v_matched_candidate IS NOT NULL THEN
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v_mention_result.put('status', 'MATCHED');
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v_mention_result.put('reasonCode', 'LLM_CANDIDATE_MATCH');
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v_mention_result.put('matchedGameKey', v_selected_key);
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IF NOT v_seen_game_keys.EXISTS(v_selected_key) THEN
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v_supported.append(v_matched_candidate);
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v_seen_game_keys(v_selected_key) := TRUE;
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END IF;
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ELSE
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v_mention_result.put('status', 'UNMATCHED');
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IF v_decision_status = 'MATCHED' THEN
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v_mention_result.put(
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'reasonCode',
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'LLM_SELECTED_UNKNOWN_CANDIDATE'
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);
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ELSE
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v_mention_result.put('reasonCode', 'LLM_NO_CANDIDATE_MATCH');
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END IF;
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v_unmatched_item := JSON_OBJECT_T();
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v_unmatched_item.put('mention', v_mention);
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v_unmatched_item.put(
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'reasonCode',
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v_mention_result.get_string('reasonCode')
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);
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v_unmatched_item.put('reason', v_reason);
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v_unmatched.append(v_unmatched_item);
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END IF;
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v_mention_results.append(v_mention_result);
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END LOOP;
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v_result.put('scopeType', v_scope_type);
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IF v_supported.get_size = 0 THEN
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v_result.put('status', 'NO_MATCH');
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ELSIF v_unmatched.get_size > 0 THEN
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v_result.put('status', 'PARTIAL');
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ELSE
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v_result.put('status', 'SUPPORTED');
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END IF;
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v_result.put('matchedGames', v_supported);
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v_result.put('mentionResults', v_mention_results);
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v_result.put('supportedGames', v_supported);
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v_result.put('unmatchedGames', v_unmatched);
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IF v_supported.get_size = 0 THEN
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v_result.put('nextAction', 'STOP_NO_MATCH');
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ELSIF v_scope_type = 'MULTI_GAME' THEN
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v_result.put('nextAction', 'CALL_FEWSHOT_PER_GAME');
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ELSE
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v_result.put('nextAction', 'CALL_FEWSHOT');
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END IF;
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CASE v_scope_type
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WHEN 'SINGLE_GAME' THEN v_result.put('executionMode', 'SINGLE');
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WHEN 'MULTI_GAME' THEN v_result.put('executionMode', 'FAN_OUT');
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WHEN 'ALL_GAMES' THEN v_result.put('executionMode', 'GROUPED');
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ELSE v_result.put('executionMode', 'BLOCKED');
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END CASE;
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RETURN v_result.to_clob;
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END;
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/
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@@ -3,6 +3,7 @@ package com.cloudhandson.vpdbackoffice.service;
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import com.cloudhandson.vpdbackoffice.config.BackofficeProperties;
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import com.fasterxml.jackson.databind.JsonNode;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import com.fasterxml.jackson.databind.node.ObjectNode;
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import java.sql.CallableStatement;
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import java.sql.Clob;
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import java.sql.Connection;
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@@ -11,15 +12,17 @@ import java.sql.ResultSet;
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import java.sql.SQLException;
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import java.sql.Types;
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import java.util.ArrayList;
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import java.util.Comparator;
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import java.util.LinkedHashMap;
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import java.util.List;
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import java.util.Locale;
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import java.util.Map;
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import java.util.Optional;
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import java.util.stream.Stream;
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import org.springframework.stereotype.Service;
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/**
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* MCP database gateway for the ADB-owned game query planning functions.
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*
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* <p>Game mention extraction, vector candidate retrieval, and OCI GenAI
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* candidate selection run inside {@code SG_GAME_QUERY_PLAN}. Java validates
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* authentication and transports the structured JSON result without applying
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* game-name matching rules.</p>
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*/
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@Service
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public class GameCatalogVectorService {
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@@ -37,76 +40,38 @@ public class GameCatalogVectorService {
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this.objectMapper = objectMapper;
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}
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/**
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* Resolves each extracted game mention independently.
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*
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* <p>Vector search supplies candidates. A candidate becomes executable only
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* when the extracted mention also matches catalog identity text. This keeps
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* an unknown mention from inheriting the nearest unrelated game while
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* retaining the original mention for partial-result reporting.</p>
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*/
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public Resolution resolve(String token, String question, int topK) {
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public ObjectNode queryPlan(
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String token, String question, int topK
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) {
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requireActiveToken(token);
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JsonNode extracted;
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try {
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extracted = objectMapper.readTree(extractMentions(question));
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} catch (Exception exception) {
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throw new AppException(
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"게임명 추출 결과 JSON 파싱 실패: " + exception.getMessage());
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}
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String scopeType = extracted.path("scope_hint").asText("UNKNOWN");
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Map<String, MentionResolution> mentionsByNormalizedText =
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new LinkedHashMap<>();
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Map<String, GameCandidate> supportedByGameKey = new LinkedHashMap<>();
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for (JsonNode item : extracted.path("game_mentions")) {
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String mention = item.asText("").trim();
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String normalizedMention = normalizeIdentity(mention);
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if (normalizedMention.isEmpty()
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|| mentionsByNormalizedText.containsKey(normalizedMention)) {
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continue;
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}
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List<GameCandidate> candidates = search(token, mention, topK);
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Optional<GameCandidate> matched =
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selectMatchedCandidate(mention, candidates);
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MentionResolution resolution;
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if (matched.isPresent()) {
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GameCandidate game = matched.get();
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supportedByGameKey.putIfAbsent(game.gameKey(), game);
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resolution = new MentionResolution(
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mention, "MATCHED", game, candidates);
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} else {
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resolution = new MentionResolution(
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mention, "UNMATCHED", null, candidates);
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}
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mentionsByNormalizedText.put(normalizedMention, resolution);
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}
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return new Resolution(
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scopeType,
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List.copyOf(supportedByGameKey.values()),
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List.copyOf(mentionsByNormalizedText.values())
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);
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}
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private String extractMentions(String question) {
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BackofficeProperties.SelectAi database = requiredDatabase();
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try (Connection connection = DriverManager.getConnection(
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database.dbUrl(), database.dbUsername(), database.dbPassword());
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CallableStatement statement = connection.prepareCall(
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"{ ? = call sg_game_extract_mentions(?) }")) {
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"{ ? = call sg_game_query_plan(?, ?) }")) {
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statement.registerOutParameter(1, Types.CLOB);
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statement.setString(2, question);
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statement.setInt(3, boundedTopK(topK));
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statement.execute();
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Clob value = (Clob) statement.getObject(1);
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return value == null
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? "{\"game_mentions\":[],\"scope_hint\":\"UNKNOWN\"}"
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: value.getSubString(1, (int) value.length());
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String raw = value == null ? "" :
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value.getSubString(1, (int) value.length());
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JsonNode parsed = objectMapper.readTree(raw);
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if (!(parsed instanceof ObjectNode plan)
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|| !plan.hasNonNull("status")
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|| !plan.path("supportedGames").isArray()
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|| !plan.path("unmatchedGames").isArray()) {
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throw new AppException("ADB 게임 질의 계획 응답 형식이 올바르지 않습니다.");
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}
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return plan;
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} catch (SQLException exception) {
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throw new AppException(
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"ADB 게임명 추출 실패: " + exception.getMessage());
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"ADB 게임 질의 계획 실패: " + exception.getMessage());
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} catch (AppException exception) {
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throw exception;
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} catch (Exception exception) {
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throw new AppException(
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"ADB 게임 질의 계획 JSON 파싱 실패: " + exception.getMessage());
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}
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}
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@@ -122,7 +87,7 @@ public class GameCatalogVectorService {
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"{ ? = call sg_game_catalog_search(?, ?) }")) {
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statement.registerOutParameter(1, Types.REF_CURSOR);
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statement.setString(2, question);
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statement.setInt(3, Math.min(Math.max(topK, 1), 20));
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statement.setInt(3, boundedTopK(topK));
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statement.execute();
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try (ResultSet rows = (ResultSet) statement.getObject(1)) {
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while (rows.next()) {
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@@ -143,40 +108,8 @@ public class GameCatalogVectorService {
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}
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}
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static Optional<GameCandidate> selectMatchedCandidate(
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String mention, List<GameCandidate> candidates
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) {
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String normalizedMention = normalizeIdentity(mention);
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if (normalizedMention.isEmpty()) {
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return Optional.empty();
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}
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return candidates.stream()
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.filter(candidate -> identityFields(candidate)
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.map(GameCatalogVectorService::normalizeIdentity)
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.anyMatch(field -> field.contains(normalizedMention)))
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.min(Comparator.comparingDouble(GameCandidate::similarity));
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}
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private static Stream<String> identityFields(GameCandidate candidate) {
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return Stream.of(
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nullToEmpty(candidate.gameKey()),
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nullToEmpty(candidate.gameId()),
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nullToEmpty(candidate.gamePrefix()),
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nullToEmpty(candidate.gameName()),
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nullToEmpty(candidate.aliases())
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);
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}
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private static String normalizeIdentity(String value) {
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if (value == null) {
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return "";
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}
|
||||
return value.toUpperCase(Locale.ROOT)
|
||||
.replaceAll("[\\s\\p{Punct}]", "");
|
||||
}
|
||||
|
||||
private static String nullToEmpty(String value) {
|
||||
return value == null ? "" : value;
|
||||
static int boundedTopK(int topK) {
|
||||
return Math.min(Math.max(topK, 1), 20);
|
||||
}
|
||||
|
||||
private BackofficeProperties.SelectAi requiredDatabase() {
|
||||
@@ -204,23 +137,4 @@ public class GameCatalogVectorService {
|
||||
String aliases,
|
||||
double similarity
|
||||
) {}
|
||||
|
||||
public record MentionResolution(
|
||||
String mention,
|
||||
String status,
|
||||
GameCandidate matchedGame,
|
||||
List<GameCandidate> candidates
|
||||
) {}
|
||||
|
||||
public record Resolution(
|
||||
String scopeType,
|
||||
List<GameCandidate> candidates,
|
||||
List<MentionResolution> mentions
|
||||
) {
|
||||
public Resolution(
|
||||
String scopeType, List<GameCandidate> candidates
|
||||
) {
|
||||
this(scopeType, candidates, List.of());
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -200,12 +200,12 @@ public class McpSseService {
|
||||
} else if (gameScopeTool) {
|
||||
response = gameScopeResponse(gameScopeService.resolve(
|
||||
token, arguments.path("question").asText("")));
|
||||
} else if (gameCatalogTool) {
|
||||
response = gameCatalogVectorResponse(gameCatalogVectorService.resolve(
|
||||
token, arguments.path("question").asText(""), arguments.path("topK").asInt(5)));
|
||||
} else if (gameQueryPlanTool) {
|
||||
response = gameQueryPlanResponse(gameCatalogVectorService.resolve(
|
||||
token, arguments.path("question").asText(""), arguments.path("topK").asInt(5)));
|
||||
} else if (gameCatalogTool || gameQueryPlanTool) {
|
||||
response = gameCatalogVectorService.queryPlan(
|
||||
token,
|
||||
arguments.path("question").asText(""),
|
||||
arguments.path("topK").asInt(5)
|
||||
);
|
||||
} else {
|
||||
String prompt = arguments.path("prompt").asText("");
|
||||
response = queryTool
|
||||
@@ -258,50 +258,6 @@ public class McpSseService {
|
||||
return response;
|
||||
}
|
||||
|
||||
private ObjectNode gameCatalogVectorResponse(GameCatalogVectorService.Resolution resolution) {
|
||||
ObjectNode response = objectMapper.createObjectNode();
|
||||
response.put("scopeType", resolution.scopeType());
|
||||
boolean hasUnmatched = resolution.mentions().stream()
|
||||
.anyMatch(mention -> "UNMATCHED".equals(mention.status()));
|
||||
response.put("status", resolution.candidates().isEmpty()
|
||||
? "NO_MATCH" : hasUnmatched ? "PARTIAL" : "CANDIDATES");
|
||||
ArrayNode items = response.putArray("matchedGames");
|
||||
for (GameCatalogVectorService.GameCandidate c : resolution.candidates()) {
|
||||
addGameCandidate(items.addObject(), c, true);
|
||||
}
|
||||
ArrayNode mentionResults = response.putArray("mentionResults");
|
||||
for (GameCatalogVectorService.MentionResolution mention
|
||||
: resolution.mentions()) {
|
||||
ObjectNode item = mentionResults.addObject();
|
||||
item.put("mention", mention.mention());
|
||||
item.put("status", mention.status());
|
||||
if (mention.matchedGame() != null) {
|
||||
item.put("matchedGameKey", mention.matchedGame().gameKey());
|
||||
}
|
||||
ArrayNode candidates = item.putArray("candidateGames");
|
||||
for (GameCatalogVectorService.GameCandidate candidate
|
||||
: mention.candidates()) {
|
||||
addGameCandidate(candidates.addObject(), candidate, false);
|
||||
}
|
||||
}
|
||||
return response;
|
||||
}
|
||||
|
||||
private void addGameCandidate(
|
||||
ObjectNode item,
|
||||
GameCatalogVectorService.GameCandidate candidate,
|
||||
boolean includeAliases
|
||||
) {
|
||||
item.put("gameKey", candidate.gameKey());
|
||||
item.put("gameId", candidate.gameId());
|
||||
item.put("gamePrefix", candidate.gamePrefix());
|
||||
item.put("gameName", candidate.gameName());
|
||||
if (includeAliases) {
|
||||
item.put("aliases", candidate.aliases());
|
||||
}
|
||||
item.put("cosineDistance", candidate.similarity());
|
||||
}
|
||||
|
||||
private ObjectNode qaVectorStoreResponse(QaVectorService.VectorStoreResult stored) {
|
||||
ObjectNode response = objectMapper.createObjectNode();
|
||||
response.put("status", "QA_VECTOR_STORED");
|
||||
@@ -409,44 +365,6 @@ public class McpSseService {
|
||||
-1L, "게임 질의 계획", SELECT_AI_TOOL_PATH);
|
||||
}
|
||||
|
||||
private ObjectNode gameQueryPlanResponse(GameCatalogVectorService.Resolution resolution) {
|
||||
ObjectNode response = gameCatalogVectorResponse(resolution);
|
||||
List<GameCatalogVectorService.MentionResolution> unmatchedMentions =
|
||||
resolution.mentions().stream()
|
||||
.filter(mention -> "UNMATCHED".equals(mention.status()))
|
||||
.toList();
|
||||
response.put("status", resolution.candidates().isEmpty()
|
||||
? "NO_MATCH" : unmatchedMentions.isEmpty() ? "SUPPORTED" : "PARTIAL");
|
||||
ArrayNode supported = response.putArray("supportedGames");
|
||||
for (GameCatalogVectorService.GameCandidate c : resolution.candidates()) {
|
||||
ObjectNode item = supported.addObject();
|
||||
item.put("gameKey", c.gameKey());
|
||||
item.put("gameId", c.gameId());
|
||||
item.put("gameName", c.gameName());
|
||||
item.put("gamePrefix", c.gamePrefix());
|
||||
item.put("cosineDistance", c.similarity());
|
||||
}
|
||||
ArrayNode unmatched = response.putArray("unmatchedGames");
|
||||
for (GameCatalogVectorService.MentionResolution mention
|
||||
: unmatchedMentions) {
|
||||
ObjectNode item = unmatched.addObject();
|
||||
item.put("mention", mention.mention());
|
||||
item.put("reasonCode", "NO_CATALOG_IDENTITY_MATCH");
|
||||
}
|
||||
response.put("nextAction", resolution.candidates().isEmpty()
|
||||
? "STOP_NO_MATCH"
|
||||
: ("MULTI_GAME".equals(resolution.scopeType())
|
||||
? "CALL_FEWSHOT_PER_GAME" : "CALL_FEWSHOT"));
|
||||
String mode = switch (resolution.scopeType()) {
|
||||
case "SINGLE_GAME" -> "SINGLE";
|
||||
case "MULTI_GAME" -> "FAN_OUT";
|
||||
case "ALL_GAMES" -> "GROUPED";
|
||||
default -> "BLOCKED";
|
||||
};
|
||||
response.put("executionMode", mode);
|
||||
return response;
|
||||
}
|
||||
|
||||
private String selectAiProfile() {
|
||||
BackofficeProperties.SelectAi selectAi = properties == null ? null : properties.selectAi();
|
||||
if (selectAi == null || selectAi.profile() == null || selectAi.profile().isBlank()) {
|
||||
|
||||
@@ -2,51 +2,14 @@ package com.cloudhandson.vpdbackoffice.service;
|
||||
|
||||
import static org.assertj.core.api.Assertions.assertThat;
|
||||
|
||||
import java.util.List;
|
||||
import org.junit.jupiter.api.Test;
|
||||
|
||||
class GameCatalogVectorServiceTest {
|
||||
|
||||
private static final GameCatalogVectorService.GameCandidate CATALOG_GAME =
|
||||
new GameCatalogVectorService.GameCandidate(
|
||||
"GAME_KEY",
|
||||
"GAME_ID",
|
||||
"GME",
|
||||
"Catalog Game",
|
||||
"GME Catalog Game 카탈로그게임",
|
||||
0.31
|
||||
);
|
||||
|
||||
@Test
|
||||
void acceptsCandidateWhoseCatalogIdentityContainsTheExtractedMention() {
|
||||
var match = GameCatalogVectorService.selectMatchedCandidate(
|
||||
"카탈로그 게임", List.of(CATALOG_GAME));
|
||||
|
||||
assertThat(match).contains(CATALOG_GAME);
|
||||
}
|
||||
|
||||
@Test
|
||||
void rejectsNearestVectorCandidateWithoutCatalogIdentityMatch() {
|
||||
var match = GameCatalogVectorService.selectMatchedCandidate(
|
||||
"Unknown title", List.of(CATALOG_GAME));
|
||||
|
||||
assertThat(match).isEmpty();
|
||||
}
|
||||
|
||||
@Test
|
||||
void choosesClosestCandidateAmongIdentityMatches() {
|
||||
var farther = new GameCatalogVectorService.GameCandidate(
|
||||
"GAME_KEY_2",
|
||||
"GAME_ID_2",
|
||||
"GM2",
|
||||
"Catalog Game Plus",
|
||||
"Catalog Game Plus",
|
||||
0.44
|
||||
);
|
||||
|
||||
var match = GameCatalogVectorService.selectMatchedCandidate(
|
||||
"Catalog Game", List.of(farther, CATALOG_GAME));
|
||||
|
||||
assertThat(match).contains(CATALOG_GAME);
|
||||
void boundsCandidateCountPassedToTheAdbPlanningTool() {
|
||||
assertThat(GameCatalogVectorService.boundedTopK(0)).isEqualTo(1);
|
||||
assertThat(GameCatalogVectorService.boundedTopK(3)).isEqualTo(3);
|
||||
assertThat(GameCatalogVectorService.boundedTopK(100)).isEqualTo(20);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -262,7 +262,7 @@ class McpSseServiceTest {
|
||||
.contains("\"status\" : \"PARTIAL\"")
|
||||
.contains("\"gameKey\" : \"SUPPORTED_GAME\"")
|
||||
.contains("\"mention\" : \"Unknown game\"")
|
||||
.contains("\"reasonCode\" : \"NO_CATALOG_IDENTITY_MATCH\"");
|
||||
.contains("\"reasonCode\" : \"LLM_NO_CANDIDATE_MATCH\"");
|
||||
}
|
||||
|
||||
private ObjectNode request(int id, String method) {
|
||||
@@ -370,41 +370,24 @@ class McpSseServiceTest {
|
||||
}
|
||||
|
||||
@Override
|
||||
public Resolution resolve(String token, String question, int topK) {
|
||||
GameCandidate supported = new GameCandidate(
|
||||
"SUPPORTED_GAME",
|
||||
"SUPPORTED_GAME_ID",
|
||||
"SUPPORTED_PREFIX",
|
||||
"Supported game",
|
||||
"Supported",
|
||||
0.1
|
||||
);
|
||||
GameCandidate nearestUnknownCandidate = new GameCandidate(
|
||||
"OTHER_GAME",
|
||||
"OTHER_GAME_ID",
|
||||
"OTHER_PREFIX",
|
||||
"Other game",
|
||||
"Other",
|
||||
0.6
|
||||
);
|
||||
return new Resolution(
|
||||
"MULTI_GAME",
|
||||
java.util.List.of(supported),
|
||||
java.util.List.of(
|
||||
new MentionResolution(
|
||||
"Supported game",
|
||||
"MATCHED",
|
||||
supported,
|
||||
java.util.List.of(supported)
|
||||
),
|
||||
new MentionResolution(
|
||||
"Unknown game",
|
||||
"UNMATCHED",
|
||||
null,
|
||||
java.util.List.of(nearestUnknownCandidate)
|
||||
)
|
||||
)
|
||||
);
|
||||
public ObjectNode queryPlan(String token, String question, int topK) {
|
||||
ObjectNode plan = new ObjectMapper().createObjectNode();
|
||||
plan.put("scopeType", "MULTI_GAME");
|
||||
plan.put("status", "PARTIAL");
|
||||
plan.putArray("matchedGames")
|
||||
.addObject()
|
||||
.put("gameKey", "SUPPORTED_GAME");
|
||||
plan.putArray("mentionResults");
|
||||
plan.putArray("supportedGames")
|
||||
.addObject()
|
||||
.put("gameKey", "SUPPORTED_GAME");
|
||||
plan.putArray("unmatchedGames")
|
||||
.addObject()
|
||||
.put("mention", "Unknown game")
|
||||
.put("reasonCode", "LLM_NO_CANDIDATE_MATCH");
|
||||
plan.put("nextAction", "CALL_FEWSHOT_PER_GAME");
|
||||
plan.put("executionMode", "FAN_OUT");
|
||||
return plan;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user