refs #708: benchmark Llama game scope profile

database/adb/112_sgmp_select_ai_oci_llama4scout_profile.sql

@@ -0,0 +1,81 @@
+-- Creates a non-operational comparison profile for Smilegate game-scope chat.
+-- The active GPT profile remains unchanged. Provider credentials and profile
+-- metadata are copied from it so the only comparison variable is the model.
+
+DECLARE
+  v_exists PLS_INTEGER;
+  v_credential_name VARCHAR2(128);
+  v_region VARCHAR2(128);
+  v_compartment_id VARCHAR2(4000);
+  v_attributes CLOB;
+  v_attribute_json JSON_OBJECT_T := JSON_OBJECT_T();
+BEGIN
+  SELECT COUNT(*)
+    INTO v_exists
+    FROM user_cloud_ai_profiles
+   WHERE profile_name = 'SGMP_POC_OCI_LLAMA4SCOUT';
+
+  IF v_exists > 0 THEN
+    DBMS_CLOUD_AI.DROP_PROFILE(
+      profile_name => 'SGMP_POC_OCI_LLAMA4SCOUT',
+      force        => TRUE
+    );
+  END IF;
+
+  SELECT DBMS_LOB.SUBSTR(attribute_value, 128, 1)
+    INTO v_credential_name
+    FROM user_cloud_ai_profile_attributes
+   WHERE profile_name = 'SGMP_POC_OCI_GPT54MINI'
+     AND attribute_name = 'credential_name';
+
+  SELECT DBMS_LOB.SUBSTR(attribute_value, 128, 1)
+    INTO v_region
+    FROM user_cloud_ai_profile_attributes
+   WHERE profile_name = 'SGMP_POC_OCI_GPT54MINI'
+     AND attribute_name = 'region';
+
+  SELECT DBMS_LOB.SUBSTR(attribute_value, 4000, 1)
+    INTO v_compartment_id
+    FROM user_cloud_ai_profile_attributes
+   WHERE profile_name = 'SGMP_POC_OCI_GPT54MINI'
+     AND attribute_name = 'oci_compartment_id';
+
+  v_attribute_json.put('provider', 'oci');
+  v_attribute_json.put('credential_name', v_credential_name);
+  v_attribute_json.put('model', 'meta.llama-4-scout-17b-16e-instruct');
+  v_attribute_json.put('region', v_region);
+  v_attribute_json.put('oci_compartment_id', v_compartment_id);
+  v_attributes := v_attribute_json.to_clob;
+
+  DBMS_CLOUD_AI.CREATE_PROFILE(
+    profile_name => 'SGMP_POC_OCI_LLAMA4SCOUT',
+    attributes   => v_attributes,
+    description  => 'Non-operational Smilegate game-scope latency comparison'
+  );
+
+  FOR source_attribute IN (
+    SELECT attribute_name, attribute_value
+      FROM user_cloud_ai_profile_attributes
+     WHERE profile_name = 'SGMP_POC_OCI_GPT54MINI'
+       AND attribute_name NOT IN (
+         'credential_name', 'model', 'provider', 'provider_endpoint',
+         'region', 'oci_compartment_id', 'oci_endpoint_id',
+         'oci_apiformat', 'oci_runtimetype'
+       )
+  ) LOOP
+    DBMS_CLOUD_AI.SET_ATTRIBUTE(
+      profile_name    => 'SGMP_POC_OCI_LLAMA4SCOUT',
+      attribute_name  => source_attribute.attribute_name,
+      attribute_value => source_attribute.attribute_value
+    );
+  END LOOP;
+END;
+/
+
+SELECT attribute_name, attribute_value
+  FROM user_cloud_ai_profile_attributes
+ WHERE profile_name = 'SGMP_POC_OCI_LLAMA4SCOUT'
+   AND attribute_name IN (
+     'provider', 'model', 'credential_name', 'region', 'oci_compartment_id'
+   )
+ ORDER BY attribute_name;

database/adb/113_sgmp_game_scope_chat_profile_benchmark.sql

@@ -0,0 +1,60 @@
+-- Read-only latency and JSON-shape comparison for the game-mention extraction
+-- stage. Korean input is reconstructed from UTF-8 base64 for SQLcl safety.
+
+set serveroutput on size unlimited
+
+DECLARE
+  v_question CLOB := utl_i18n.raw_to_char(
+    utl_encode.base64_decode(utl_raw.cast_to_raw(
+      '66Gc65Oc64KY7J247J20656RIOy5tOygnOuCmOydmCAyMDI264WEIDfsm5QgMTXsnbwgQVXrpbwg6rCB6rCBIOyVjOugpOykmC4='
+    )),
+    'AL32UTF8'
+  );
+  v_prompt CLOB;
+  v_result CLOB;
+  v_json JSON_OBJECT_T;
+  v_started PLS_INTEGER;
+  v_elapsed_seconds NUMBER;
+
+  PROCEDURE run_profile(p_profile_name IN VARCHAR2) IS
+  BEGIN
+    v_started := DBMS_UTILITY.GET_TIME;
+    v_result := DBMS_CLOUD_AI.GENERATE(
+      prompt => v_prompt,
+      profile_name => p_profile_name,
+      action => 'chat'
+    );
+    v_elapsed_seconds := (DBMS_UTILITY.GET_TIME - v_started) / 100;
+    v_json := JSON_OBJECT_T.parse(v_result);
+    DBMS_OUTPUT.PUT_LINE(
+      p_profile_name
+      || '|elapsed_seconds=' || TO_CHAR(v_elapsed_seconds, 'FM9990D00')
+      || '|scope_hint=' || NVL(v_json.get_string('scope_hint'), 'NULL')
+      || '|mention_count=' || v_json.get_array('game_mentions').get_size
+    );
+  EXCEPTION
+    WHEN OTHERS THEN
+      DBMS_OUTPUT.PUT_LINE(
+        p_profile_name || '|elapsed_seconds='
+        || TO_CHAR(v_elapsed_seconds, 'FM9990D00')
+        || '|ERROR|' || SQLCODE || '|' || SUBSTR(SQLERRM, 1, 300)
+      );
+      DBMS_OUTPUT.PUT_LINE(
+        p_profile_name || '|raw_response=' || DBMS_LOB.SUBSTR(v_result, 1000, 1)
+      );
+  END;
+BEGIN
+  v_prompt := 'Extract only game-name mentions from the user question. '
+    || 'Metrics, acronyms, dates, filters, and database object or column names are not game names unless they are themselves an explicit game title. '
+    || 'When a title-like noun directly qualifies a game data request such as user master, character, sales, AU, NRU, server, or game log, preserve that noun as a game-name mention even when it is not in a catalog. '
+    || 'Do not discard an unknown title merely because it cannot be resolved. General scope words such as common, overall, all, total, or every are not game-name mentions unless they are part of an explicit title. '
+    || 'Return exactly one JSON object with keys game_mentions (array of strings) '
+    || 'and scope_hint (GLOBAL, SINGLE_GAME, MULTI_GAME, ALL_GAMES, UNKNOWN). '
+    || 'Do not resolve names to IDs and do not generate SQL. '
+    || 'Return raw JSON only: no prose, no Markdown, and no code fence. Question: '
+    || v_question;
+
+  run_profile('SGMP_POC_OCI_GPT54MINI');
+  run_profile('SGMP_POC_OCI_LLAMA4SCOUT');
+END;
+/

docs/design/708-smilegate-select-ai-oci-genai/README.md

@@ -46,3 +46,24 @@ Smilegate DATA & AI PoC는 Autonomous Database의 게임 데이터에서 Select
 - `DBMS_CLOUD_AI.GENERATE(..., 'showsql')`이 읽기 전용 `SELECT` 또는 `WITH` SQL을 생성한다.
 - 해당 SQL을 읽기 전용 트랜잭션에서 실행해 결과를 반환한다.
 - 운영 MCP 응답의 `profile`이 `SGMP_POC_OCI_GPT54MINI`이다.
+
+## Llama 4 Scout 범위 판정 성능 비교
+
+게임 범위 판정은 Text2SQL 실행 전 OCI Chat을 사용한다. 이 단계의 응답시간을
+비교하기 위해 운영 프로파일을 교체하지 않고 별도 테스트 프로파일
+`SGMP_POC_OCI_LLAMA4SCOUT`을 만든다.
+
+| 구분 | 운영 | 비교 대상 |
+| --- | --- | --- |
+| 프로파일 | `SGMP_POC_OCI_GPT54MINI` | `SGMP_POC_OCI_LLAMA4SCOUT` |
+| 모델 | `openai.gpt-5.4-mini` | `meta.llama-4-scout-17b-16e-instruct` |
+| 인증·리전 | 기존 OCI credential·inference region 유지 | 동일 |
+| object list·metadata | 운영 값 | 운영 값 복제 |
+| 운영 트래픽 | 사용 | 사용하지 않음 |
+
+`sql/adb/112_sgmp_select_ai_oci_llama4scout_profile.sql`은 기존 OCI 프로파일의
+credential, region, compartment, object list와 metadata instructions를 복제하고
+모델만 교체한다. 같은 질문을 두 프로파일에 각각 Chat 호출해 경과시간과 반환 JSON
+형식을 기록한다. 품질·지연시간 결과를 검토하기 전에는
+`sg_game_extract_mentions`와 `sg_game_match_candidate`의 운영 프로파일을 바꾸지
+않는다.