...

src/main/kotlin/network/RagService.kt

@@ -1,5 +1,7 @@
 package network// src/main/kotlin/network/RagService.kt
 
+import Defines.EMBEDDING_PORT
+import Defines.LLM_PORT
 import TradingLogStore
 import dev.langchain4j.community.rag.content.retriever.lucene.LuceneEmbeddingStore
 import dev.langchain4j.data.document.Metadata
@@ -56,12 +58,12 @@ object RagService {
 
     // 임베딩 모델 (8081) 및 채팅 모델 (8080) 설정
     private val embeddingModel = OpenAiEmbeddingModel.builder()
-        .baseUrl("http://127.0.0.1:${AutoTradingManager.EMBEDDING_PORT}/v1")
+        .baseUrl("http://127.0.0.1:${EMBEDDING_PORT}/v1")
         .apiKey("unused")
         .build()
 
     private val chatModel = OpenAiChatModel.builder()
-        .baseUrl("http://127.0.0.1:${AutoTradingManager.LLM_PORT}/v1")
+        .baseUrl("http://127.0.0.1:${LLM_PORT}/v1")
         .apiKey("unused")
         .temperature(0.0) // [중요] 0.0으로 설정하여 결정론적 응답 유도
         .timeout(Duration.ofSeconds(60))