444 lines
20 KiB
Java
444 lines
20 KiB
Java
package com.cloudhandson.vpdbackoffice.service;
|
|
|
|
import com.cloudhandson.vpdbackoffice.config.BackofficeProperties;
|
|
import com.cloudhandson.vpdbackoffice.domain.token.BearerTokenRecord;
|
|
import com.fasterxml.jackson.databind.JsonNode;
|
|
import com.fasterxml.jackson.databind.ObjectMapper;
|
|
import com.fasterxml.jackson.databind.node.ArrayNode;
|
|
import com.fasterxml.jackson.databind.node.ObjectNode;
|
|
import java.math.BigDecimal;
|
|
import java.math.BigInteger;
|
|
import java.sql.Connection;
|
|
import java.sql.DriverManager;
|
|
import java.sql.PreparedStatement;
|
|
import java.sql.ResultSet;
|
|
import java.sql.ResultSetMetaData;
|
|
import java.sql.Statement;
|
|
import java.time.Clock;
|
|
import java.time.LocalDateTime;
|
|
import java.time.ZoneId;
|
|
import java.util.List;
|
|
import java.util.regex.Pattern;
|
|
import org.springframework.stereotype.Service;
|
|
|
|
/**
|
|
* Generates and executes bounded read-only SQL through the configured schema-owned Select AI profile.
|
|
*/
|
|
@Service
|
|
public class SelectAiService {
|
|
|
|
private static final int MAX_PROMPT_LENGTH = 4_000;
|
|
private static final int MAX_RESULT_ROWS = 100;
|
|
private static final int QUERY_TIMEOUT_SECONDS = 30;
|
|
private static final int MAX_FEW_SHOT_EXAMPLES = 3;
|
|
private static final int MAX_FEW_SHOT_SQL_CHARS = 4_000;
|
|
private static final int MAX_ENRICHED_PROMPT_LENGTH = 16_000;
|
|
private static final String POLICY_PREFIX =
|
|
"Answer the original user question using the current approved object list and policy. "
|
|
+ "If no game identifier resolves through game-alias metadata, do not select a prefix-specific object "
|
|
+ "and do not infer a default game. State that the required game identifier is missing instead.\n\n";
|
|
private static final Pattern UNSAFE_SQL = Pattern.compile(
|
|
"(?is)\\b(?:insert|update|delete|merge|alter|drop|create|truncate|grant|revoke|"
|
|
+ "commit|rollback|savepoint|lock|call|exec(?:ute)?|begin|declare|for\\s+update|"
|
|
+ "dbms_[a-z0-9_]*|utl_[a-z0-9_]*|sys\\s*\\.)\\b"
|
|
);
|
|
|
|
private final BackofficeProperties properties;
|
|
private final BearerTokenService bearerTokenService;
|
|
private final Clock clock;
|
|
private final ObjectMapper objectMapper;
|
|
private final QaVectorService qaVectorService;
|
|
private final GameScopeService gameScopeService;
|
|
private final GameCatalogVectorService gameCatalogVectorService;
|
|
|
|
public SelectAiService(
|
|
BackofficeProperties properties,
|
|
BearerTokenService bearerTokenService,
|
|
Clock clock,
|
|
ObjectMapper objectMapper,
|
|
QaVectorService qaVectorService,
|
|
GameScopeService gameScopeService,
|
|
GameCatalogVectorService gameCatalogVectorService
|
|
) {
|
|
this.properties = properties;
|
|
this.bearerTokenService = bearerTokenService;
|
|
this.clock = clock;
|
|
this.objectMapper = objectMapper;
|
|
this.qaVectorService = qaVectorService;
|
|
this.gameScopeService = gameScopeService;
|
|
this.gameCatalogVectorService = gameCatalogVectorService;
|
|
}
|
|
|
|
public JsonNode generateAndExecute(String bearerToken, String prompt) {
|
|
return generateAndExecute(bearerToken, prompt, null);
|
|
}
|
|
|
|
/**
|
|
* Executes one DB-resolved game scope. The optional key is revalidated for
|
|
* the original question; it is never a caller-provided table or prefix.
|
|
*/
|
|
public JsonNode generateAndExecute(String bearerToken, String prompt, String scopeGameKey) {
|
|
requireActiveToken(bearerToken);
|
|
String normalizedPrompt = requiredPrompt(prompt);
|
|
BackofficeProperties.SelectAi selectAi = requiredSelectAi();
|
|
ResolvedExecutionScope scope = resolveExecutionScope(bearerToken, normalizedPrompt, scopeGameKey);
|
|
|
|
GameContext gameContext = resolveGameContext(bearerToken, normalizedPrompt);
|
|
EnrichedPrompt enrichedPrompt = enrichWithFewShot(
|
|
bearerToken, selectAi, gameContext.prompt(scope.prompt()));
|
|
String generatedSql = generate(selectAi, enrichedPrompt.prompt(), "showsql");
|
|
String normalizedSql = validateReadOnlySql(generatedSql);
|
|
QueryExecution execution = executeReadOnly(selectAi, normalizedSql);
|
|
ObjectNode response = objectMapper.createObjectNode();
|
|
response.put("status", "SHOWSQL_AND_EXECUTED");
|
|
response.put("profile", selectAi.profile());
|
|
response.put("originalPrompt", normalizedPrompt);
|
|
response.put("gameScopeType", gameContext.scopeType());
|
|
response.put("gameScopeStatus", gameContext.status());
|
|
response.put("gameCandidateCount", gameContext.candidates().size());
|
|
if (scope.gameKey() != null) {
|
|
response.put("scopeGameKey", scope.gameKey());
|
|
response.put("scopeDisplayName", scope.displayName());
|
|
response.put("scopeStatus", "DB_REVALIDATED");
|
|
}
|
|
response.put("fewShotStatus", enrichedPrompt.status());
|
|
response.put("fewShotExampleCount", enrichedPrompt.exampleCount());
|
|
addFewShotExamples(response, enrichedPrompt.examples());
|
|
response.put("generatedSql", normalizedSql);
|
|
response.put("execution", "READ_ONLY_EXECUTED");
|
|
response.put("rowCount", execution.items().size());
|
|
response.put("truncated", execution.truncated());
|
|
response.set("items", execution.items());
|
|
response.put("nextStep", execution.truncated()
|
|
? "최초 " + MAX_RESULT_ROWS + "건만 반환했습니다. 생성 SQL로 전체 결과를 확인할 수 있습니다."
|
|
: "생성 SQL을 읽기 전용으로 실행한 결과입니다.");
|
|
return response;
|
|
}
|
|
|
|
private GameContext resolveGameContext(String bearerToken, String question) {
|
|
try {
|
|
List<GameCatalogVectorService.GameCandidate> candidates =
|
|
gameCatalogVectorService.search(bearerToken, question, 5);
|
|
String status = candidates.isEmpty() ? "NO_MATCH" : "RESOLVED";
|
|
String scopeType = candidates.isEmpty() ? "UNKNOWN" : "SINGLE_GAME";
|
|
return new GameContext(scopeType, status, candidates);
|
|
} catch (Exception ignored) {
|
|
return new GameContext("UNKNOWN", "UNAVAILABLE", List.of());
|
|
}
|
|
}
|
|
|
|
private ResolvedExecutionScope resolveExecutionScope(
|
|
String bearerToken, String originalPrompt, String scopeGameKey
|
|
) {
|
|
String requestedKey = scopeGameKey == null ? "" : scopeGameKey.trim();
|
|
if (requestedKey.isEmpty()) {
|
|
return new ResolvedExecutionScope(originalPrompt, null, null);
|
|
}
|
|
if (gameScopeService == null) {
|
|
throw new AppException("게임 범위 검증 서비스를 사용할 수 없습니다.");
|
|
}
|
|
GameScopeService.GameScope scope = gameScopeService.resolve(bearerToken, originalPrompt).scopes().stream()
|
|
.filter(item -> requestedKey.equals(item.gameKey()))
|
|
.findFirst()
|
|
.orElseThrow(() -> new AppException("요청한 게임 범위가 DB 조회 결과에 없습니다."));
|
|
if (!"SUPPORTED".equals(scope.status())) {
|
|
throw new AppException("DB 게임 범위가 조회 실행을 허용하지 않습니다: " + scope.reasonCode());
|
|
}
|
|
String scopedPrompt = "Use only the DB-resolved game scope below. Do not generate SQL for any other "
|
|
+ "game mentioned in the original question. The scope was validated through current game alias "
|
|
+ "metadata and approved object availability.\n"
|
|
+ "Resolved game key: " + scope.gameKey() + "\n"
|
|
+ "Resolved display name: " + scope.displayName() + "\n"
|
|
+ "Matched alias: " + scope.matchedAlias() + "\n\n"
|
|
+ "Original user question:\n" + originalPrompt;
|
|
return new ResolvedExecutionScope(scopedPrompt, scope.gameKey(), scope.displayName());
|
|
}
|
|
|
|
private void addFewShotExamples(ObjectNode response, List<QaVectorService.VectorExample> examples) {
|
|
ArrayNode items = response.putArray("fewShotExamples");
|
|
for (QaVectorService.VectorExample example : examples) {
|
|
ObjectNode item = items.addObject();
|
|
item.put("exampleId", example.exampleId());
|
|
item.put("question", example.question());
|
|
item.put("answerSql", example.answerSql());
|
|
if (example.answer() != null) {
|
|
item.put("answer", example.answer());
|
|
}
|
|
item.put("embeddingModel", example.embeddingModel());
|
|
item.put("cosineDistance", example.cosineDistance());
|
|
}
|
|
}
|
|
|
|
/** Returns the prompt Select AI assembled for SQL generation without executing generated SQL. */
|
|
public JsonNode generatePrompt(String bearerToken, String prompt) {
|
|
requireActiveToken(bearerToken);
|
|
String normalizedPrompt = requiredPrompt(prompt);
|
|
BackofficeProperties.SelectAi selectAi = requiredSelectAi();
|
|
EnrichedPrompt enrichedPrompt = enrichWithFewShot(bearerToken, selectAi, normalizedPrompt);
|
|
String selectAiPrompt = generate(selectAi, enrichedPrompt.prompt(), "showprompt");
|
|
|
|
ObjectNode response = objectMapper.createObjectNode();
|
|
response.put("status", "SHOWPROMPT");
|
|
response.put("profile", selectAi.profile());
|
|
response.put("originalPrompt", normalizedPrompt);
|
|
response.put("fewShotStatus", enrichedPrompt.status());
|
|
response.put("fewShotExampleCount", enrichedPrompt.exampleCount());
|
|
response.put("selectAiPrompt", selectAiPrompt);
|
|
return response;
|
|
}
|
|
|
|
private BackofficeProperties.SelectAi requiredSelectAi() {
|
|
BackofficeProperties.SelectAi selectAi = properties == null ? null : properties.selectAi();
|
|
if (selectAi == null || !selectAi.configured()) {
|
|
throw new AppException("Select AI 연결 설정이 필요합니다. "
|
|
+ "BACKOFFICE_SELECT_AI_DB_URL, BACKOFFICE_SELECT_AI_DB_USERNAME, "
|
|
+ "BACKOFFICE_SELECT_AI_DB_PASSWORD를 확인하세요.");
|
|
}
|
|
return selectAi;
|
|
}
|
|
|
|
private void requireActiveToken(String bearerToken) {
|
|
if (bearerToken == null || bearerToken.isBlank()) {
|
|
throw new VpdTokenAccessDeniedException();
|
|
}
|
|
BearerTokenRecord token = bearerTokenService.findByPlainToken(bearerToken.trim());
|
|
LocalDateTime now = LocalDateTime.now(clock.withZone(ZoneId.systemDefault()));
|
|
if (token == null || !token.active(now)) {
|
|
throw new VpdTokenAccessDeniedException();
|
|
}
|
|
}
|
|
|
|
private String requiredPrompt(String prompt) {
|
|
String normalized = prompt == null ? "" : prompt.trim();
|
|
if (normalized.isEmpty()) {
|
|
throw new AppException("prompt는 필수입니다.");
|
|
}
|
|
if (normalized.length() > MAX_PROMPT_LENGTH) {
|
|
throw new AppException("prompt는 " + MAX_PROMPT_LENGTH + "자 이하여야 합니다.");
|
|
}
|
|
return normalized;
|
|
}
|
|
|
|
private String generate(
|
|
BackofficeProperties.SelectAi selectAi,
|
|
String prompt,
|
|
String action
|
|
) {
|
|
String sql = "SELECT DBMS_CLOUD_AI.GENERATE(?, ?, ?) FROM dual";
|
|
try (Connection connection = DriverManager.getConnection(
|
|
selectAi.dbUrl(), selectAi.dbUsername(), selectAi.dbPassword());
|
|
PreparedStatement statement = connection.prepareStatement(sql)) {
|
|
statement.setString(1, prompt);
|
|
statement.setString(2, selectAi.profile());
|
|
statement.setString(3, action);
|
|
try (ResultSet resultSet = statement.executeQuery()) {
|
|
if (!resultSet.next() || resultSet.getString(1) == null) {
|
|
throw new AppException("Select AI가 " + action.toUpperCase() + " 결과를 반환하지 않았습니다.");
|
|
}
|
|
return resultSet.getString(1);
|
|
}
|
|
} catch (AppException exception) {
|
|
throw exception;
|
|
} catch (Exception exception) {
|
|
throw new AppException("Select AI " + action.toUpperCase() + " 생성 실패: "
|
|
+ exception.getMessage());
|
|
}
|
|
}
|
|
|
|
private EnrichedPrompt enrichWithFewShot(
|
|
String bearerToken,
|
|
BackofficeProperties.SelectAi selectAi,
|
|
String prompt
|
|
) {
|
|
if (!fewShotEnabled(selectAi) || qaVectorService == null) {
|
|
return new EnrichedPrompt(prompt, "DISABLED", 0, List.of());
|
|
}
|
|
try {
|
|
List<QaVectorService.VectorExample> examples = qaVectorService
|
|
.search(bearerToken, prompt, fewShotTopK(selectAi))
|
|
.examples();
|
|
if (examples.isEmpty()) {
|
|
return new EnrichedPrompt(composePolicyPrompt(prompt), "NO_MATCH", 0, List.of());
|
|
}
|
|
return new EnrichedPrompt(
|
|
composeFewShotPrompt(prompt, examples), "APPLIED", Math.min(examples.size(), MAX_FEW_SHOT_EXAMPLES),
|
|
examples.subList(0, Math.min(examples.size(), MAX_FEW_SHOT_EXAMPLES)));
|
|
} catch (Exception ignored) {
|
|
// Vector retrieval is an optional prompt aid; preserve the normal Text2SQL path on failure.
|
|
return new EnrichedPrompt(composePolicyPrompt(prompt), "UNAVAILABLE", 0, List.of());
|
|
}
|
|
}
|
|
|
|
static String composePolicyPrompt(String prompt) {
|
|
return POLICY_PREFIX
|
|
+ "Resolve business terms and game names from the approved game-alias metadata before selecting a "
|
|
+ "game-scoped object. A generic term such as common user means no particular game. If no game alias "
|
|
+ "is resolved, do not substitute an arbitrary game-scoped object. Return a read-only no-match result "
|
|
+ "and preserve the resolver status for the answer layer; do not invent a user-facing explanation.\n"
|
|
+ "Original user question:\n" + prompt;
|
|
}
|
|
|
|
static String composeFewShotPrompt(String prompt, List<QaVectorService.VectorExample> examples) {
|
|
StringBuilder enriched = new StringBuilder(POLICY_PREFIX
|
|
+ "The verified examples below are guidance only: use only relevant SQL patterns, do not invent "
|
|
+ "identifiers, and do not override current metadata or game-alias resolution policy. "
|
|
+ "When examples use a game-specific object, reuse that pattern only after the current question "
|
|
+ "resolves the same game alias; otherwise keep the query unscoped or request clarification.\n\n"
|
|
+ "Verified few-shot examples:\n");
|
|
int included = 0;
|
|
for (QaVectorService.VectorExample example : examples) {
|
|
if (included >= MAX_FEW_SHOT_EXAMPLES) {
|
|
break;
|
|
}
|
|
String answerSql = truncate(example.answerSql(), MAX_FEW_SHOT_SQL_CHARS);
|
|
if (answerSql.isBlank()) {
|
|
continue;
|
|
}
|
|
String candidate = "Example " + (included + 1) + " question:\n" + example.question()
|
|
+ "\nExample " + (included + 1) + " verified SQL:\n" + answerSql + "\n\n";
|
|
if (enriched.length() + candidate.length() + prompt.length() > MAX_ENRICHED_PROMPT_LENGTH) {
|
|
break;
|
|
}
|
|
enriched.append(candidate);
|
|
included++;
|
|
}
|
|
if (included == 0) {
|
|
return composePolicyPrompt(prompt);
|
|
}
|
|
return enriched.append("Original user question:\n").append(prompt).toString();
|
|
}
|
|
|
|
private static String truncate(String value, int maxLength) {
|
|
String normalized = value == null ? "" : value.trim();
|
|
return normalized.length() <= maxLength ? normalized : normalized.substring(0, maxLength);
|
|
}
|
|
|
|
private boolean fewShotEnabled(BackofficeProperties.SelectAi selectAi) {
|
|
return selectAi.fewShotEnabled() == null || selectAi.fewShotEnabled();
|
|
}
|
|
|
|
private int fewShotTopK(BackofficeProperties.SelectAi selectAi) {
|
|
Integer configured = selectAi.fewShotTopK();
|
|
if (configured == null) {
|
|
return MAX_FEW_SHOT_EXAMPLES;
|
|
}
|
|
return Math.max(1, Math.min(configured, MAX_FEW_SHOT_EXAMPLES));
|
|
}
|
|
|
|
private QueryExecution executeReadOnly(BackofficeProperties.SelectAi selectAi, String generatedSql) {
|
|
ArrayNode items = objectMapper.createArrayNode();
|
|
boolean truncated = false;
|
|
try (Connection connection = DriverManager.getConnection(
|
|
selectAi.dbUrl(), selectAi.dbUsername(), selectAi.dbPassword());
|
|
Statement transaction = connection.createStatement()) {
|
|
connection.setAutoCommit(false);
|
|
connection.setReadOnly(true);
|
|
transaction.execute("SET TRANSACTION READ ONLY");
|
|
try (PreparedStatement statement = connection.prepareStatement(generatedSql)) {
|
|
statement.setQueryTimeout(QUERY_TIMEOUT_SECONDS);
|
|
statement.setFetchSize(MAX_RESULT_ROWS + 1);
|
|
statement.setMaxRows(MAX_RESULT_ROWS + 1);
|
|
try (ResultSet resultSet = statement.executeQuery()) {
|
|
ResultSetMetaData metadata = resultSet.getMetaData();
|
|
while (resultSet.next()) {
|
|
if (items.size() >= MAX_RESULT_ROWS) {
|
|
truncated = true;
|
|
break;
|
|
}
|
|
ObjectNode row = items.addObject();
|
|
for (int columnIndex = 1; columnIndex <= metadata.getColumnCount(); columnIndex++) {
|
|
String column = metadata.getColumnLabel(columnIndex);
|
|
if (column == null || column.isBlank()) {
|
|
column = metadata.getColumnName(columnIndex);
|
|
}
|
|
putResultValue(row, column, resultSet.getObject(columnIndex));
|
|
}
|
|
}
|
|
}
|
|
} finally {
|
|
connection.rollback();
|
|
}
|
|
} catch (Exception exception) {
|
|
throw new AppException("Select AI 생성 SQL 실행 실패: " + exception.getMessage());
|
|
}
|
|
return new QueryExecution(items, truncated);
|
|
}
|
|
|
|
private void putResultValue(ObjectNode row, String column, Object value) {
|
|
if (value == null) {
|
|
row.putNull(column);
|
|
} else if (value instanceof BigDecimal number) {
|
|
row.put(column, number);
|
|
} else if (value instanceof BigInteger number) {
|
|
row.put(column, number);
|
|
} else if (value instanceof Integer number) {
|
|
row.put(column, number);
|
|
} else if (value instanceof Long number) {
|
|
row.put(column, number);
|
|
} else if (value instanceof Short number) {
|
|
row.put(column, number);
|
|
} else if (value instanceof Float number) {
|
|
row.put(column, number);
|
|
} else if (value instanceof Double number) {
|
|
row.put(column, number);
|
|
} else if (value instanceof Boolean bool) {
|
|
row.put(column, bool);
|
|
} else {
|
|
row.put(column, String.valueOf(value));
|
|
}
|
|
}
|
|
|
|
private String validateReadOnlySql(String generatedSql) {
|
|
String normalized = generatedSql == null ? "" : generatedSql.trim();
|
|
if (normalized.startsWith("```")) {
|
|
int firstLineEnd = normalized.indexOf('\n');
|
|
int closingFence = normalized.lastIndexOf("```");
|
|
if (firstLineEnd >= 0 && closingFence > firstLineEnd) {
|
|
normalized = normalized.substring(firstLineEnd + 1, closingFence).trim();
|
|
}
|
|
}
|
|
normalized = normalized.replaceFirst(";\\s*$", "").trim();
|
|
if (!normalized.matches("(?is)^(select|with)\\b.*")) {
|
|
throw new AppException("Select AI가 읽기 전용 SELECT/WITH SQL을 반환하지 않았습니다.");
|
|
}
|
|
if (normalized.contains(";")) {
|
|
throw new AppException("Select AI 결과에 여러 SQL 문장이 포함되어 있어 반환하지 않습니다.");
|
|
}
|
|
if (normalized.contains("--") || normalized.contains("/*") || normalized.contains("*/")
|
|
|| UNSAFE_SQL.matcher(normalized).find()) {
|
|
throw new AppException("Select AI 결과에 실행이 허용되지 않는 SQL 구문이 포함되어 있습니다.");
|
|
}
|
|
return normalized;
|
|
}
|
|
|
|
private record QueryExecution(ArrayNode items, boolean truncated) {}
|
|
|
|
private record EnrichedPrompt(
|
|
String prompt, String status, int exampleCount, List<QaVectorService.VectorExample> examples) {}
|
|
|
|
private record ResolvedExecutionScope(String prompt, String gameKey, String displayName) {}
|
|
|
|
private record GameContext(
|
|
String scopeType, String status, List<GameCatalogVectorService.GameCandidate> candidates) {
|
|
String prompt(String original) {
|
|
StringBuilder context = new StringBuilder();
|
|
context.append("[GAME CATALOG MATCH]\n")
|
|
.append("scope_type: ").append(scopeType).append('\n')
|
|
.append("status: ").append(status).append('\n');
|
|
for (GameCatalogVectorService.GameCandidate candidate : candidates) {
|
|
context.append("game_key: ").append(candidate.gameKey()).append('\n')
|
|
.append("game_id: ").append(candidate.gameId()).append('\n')
|
|
.append("game_prefix: ").append(candidate.gamePrefix()).append('\n')
|
|
.append("game_name: ").append(candidate.gameName()).append('\n')
|
|
.append("matched_aliases: ").append(candidate.aliases()).append('\n')
|
|
.append("cosine_distance: ").append(candidate.similarity()).append('\n');
|
|
}
|
|
context.append("[GAME SCOPE POLICY]\n")
|
|
.append("Use only DB-approved game scope when status is RESOLVED. ")
|
|
.append("When status is NO_MATCH or UNKNOWN, do not infer a game-specific object.\n\n")
|
|
.append(original);
|
|
return context.toString();
|
|
}
|
|
}
|
|
}
|