chore: changed log statements from info to debug. (#189)

Author: sbussweiler

lmos-classifier-core/src/main/kotlin/org/eclipse/lmos/classifier/core/AgentClassifier.kt

@@ -63,10 +63,12 @@ data class SystemContext(
  * @property candidateAgents The agents considered during classification, depending on the classification strategy:
  * - **Embedding-based classifier**; candidates originate from semantic search.
  * - **LLM-based classifier**; candidates derived from [AgentProvider]s.
+ * @property reason A concise explanation of the classification decision, present only for LLM-based classifications.
  */
 open class ClassificationResult(
     var classifiedAgents: List<ClassifiedAgent>,
     val candidateAgents: List<Agent> = emptyList(),
+    val reason: String = "",
 )
 
 /**

lmos-classifier-hybrid/src/main/kotlin/org/eclipse/lmos/classifier/hybrid/FastTrackAgentClassifier.kt

@@ -67,7 +67,7 @@ class FastTrackAgentClassifier(
     ) {
         val classifiedAgentId = result.classifiedAgents.firstOrNull()?.id ?: "none"
         this
-            .atInfo()
+            .atDebug()
             .addKeyValue("classifier-type", "Hybrid-Fasttrack")
             .addKeyValue("classifier-user-message", request.inputContext.userMessage)
             .addKeyValue("classifier-is-fasttrack", isFastTrack)

lmos-classifier-llm/src/main/kotlin/org/eclipse/lmos/classifier/llm/ChatModelPrompts.kt

@@ -30,13 +30,13 @@ fun defaultSystemPrompt(): String =
 
     Format your answer as a single JSON object, for example:
     Example question: "Mobile"
-    Example answer: {"agentId": null, "reason": "It is unclear what the customer means by 'Mobile'."}
+    Example answer: {"reason": "It is unclear what the customer means by 'Mobile'.", "agentId": null}
 
     Example question: "Order status"
-    Example answer: {"agentId": "order-agent-service", "reason": "Customer wants to know the status of their order."}
+    Example answer: {"reason": "Customer wants to know the status of their order.", "agentId": "order-agent-service"}
 
     Example question: "Hello"
-    Example answer: {"agentId": null, "reason": "The request is a greeting and there is no agent for that."}
+    Example answer: {"reason": "The request is a greeting and there is no agent for that.", "agentId": null}
     """.trimIndent()
 
 fun defaultGermanSystemPrompt(): String =
@@ -65,11 +65,11 @@ fun defaultGermanSystemPrompt(): String =
 
     Antworte in einem einzelnen JSON-Format wie im Beispiel.
     Beispielanfrage: "Mobilfunk"
-    Beispielantwort: {"agentId": null, "reason": "Es ist nicht klar was der Kunde mit \"Mobilfunk\" meint."}
+    Beispielantwort: {"reason": "Es ist nicht klar was der Kunde mit \"Mobilfunk\" meint.", agentId": null}
 
     Beispielanfrage: "Auftragsstatus"
-    Beispielantwort: {"agentId": "order-agent-service", "reason": "Der Kunde will den Status eines Auftrags erfahren"}
+    Beispielantwort: {"reason": "Der Kunde will den Status eines Auftrags erfahren", "agentId": "order-agent-service"}
 
     Beispielanfrage: "Guten Tag"
-    Beispielantwort: {"agentId": null, "reason": "Die Anfrage eine Begrüßung und ist nicht Telekom-spezifisch"}
+    Beispielantwort: {"reason": "Die Anfrage eine Begrüßung und ist nicht Telekom-spezifisch", agentId": null}
     """.trimIndent()

lmos-classifier-llm/src/main/kotlin/org/eclipse/lmos/classifier/llm/DefaultModelAgentClassifier.kt

@@ -104,7 +104,7 @@ class DefaultModelAgentClassifier(
         return if (agent == null) {
             ClassificationResult(emptyList(), agents)
         } else {
-            ClassificationResult(listOf(ClassifiedAgent(agent.id, agent.name, agent.address)), agents)
+            ClassificationResult(listOf(ClassifiedAgent(agent.id, agent.name, agent.address)), agents, response.reason)
         }
     }
 
@@ -118,7 +118,7 @@ class DefaultModelAgentClassifier(
             }
         val classifiedAgentId = result.classifiedAgents.firstOrNull()?.id ?: "none"
         this
-            .atInfo()
+            .atDebug()
             .addKeyValue("classifier-type", "LLM")
             .addKeyValue("classifier-user-message", request.inputContext.userMessage)
             .addKeyValue("classifier-candidate-agents", candidateAgents)
@@ -137,8 +137,8 @@ class DefaultModelAgentClassifier(
 }
 
 data class ClassifiedAgentResult(
-    val agentId: String?,
     val reason: String,
+    val agentId: String?,
 )
 
 data class LlmCandidateAgent(

lmos-classifier-llm/src/test/kotlin/org/eclipse/lmos/classifier/llm/DefaultModelAgentClassifierTest.kt

@@ -58,7 +58,7 @@ internal class DefaultModelAgentClassifierTest {
         // given
         val request = modelClassificationRequest()
 
-        val expectedAgentId = jacksonObjectMapper().writeValueAsString(ClassifiedAgentResult("weather-bot", "customer wants weather info"))
+        val expectedAgentId = jacksonObjectMapper().writeValueAsString(ClassifiedAgentResult("customer wants weather info", "weather-bot"))
         val expectedClassifiedAgent = ClassifiedAgent("weather-bot", "weather-bot-name", "weather-bot-address")
         val expectedCandidateAgents = agentProvider.provide(request)
         val chatResponse = ChatResponse.builder().aiMessage(AiMessage((expectedAgentId))).build()
@@ -71,6 +71,7 @@ internal class DefaultModelAgentClassifierTest {
         // then
         assertThat(classification.classifiedAgents).isEqualTo(listOf(expectedClassifiedAgent))
         assertThat(classification.candidateAgents).isEqualTo(expectedCandidateAgents)
+        assertThat(classification.reason).isEqualTo("customer wants weather info")
         assertThat(messagesSlot.captured.messages()).hasSize(4)
 
         assertThat(messagesSlot.captured.messages()[0]).isInstanceOf(SystemMessage::class.java)
@@ -91,7 +92,7 @@ internal class DefaultModelAgentClassifierTest {
         // given
         val request = modelClassificationRequest()
 
-        val expectedAgentId = jacksonObjectMapper().writeValueAsString(ClassifiedAgentResult(null, "no suitable agent found"))
+        val expectedAgentId = jacksonObjectMapper().writeValueAsString(ClassifiedAgentResult("no suitable agent found", null))
         val expectedCandidateAgents = agentProvider.provide(request)
         val chatResponse = ChatResponse.builder().aiMessage(AiMessage((expectedAgentId))).build()
         val messagesSlot = slot<ChatRequest>()

lmos-classifier-vector/src/main/kotlin/org/eclipse/lmos/classifier/vector/DefaultEmbeddingAgentClassifier.kt

@@ -47,7 +47,7 @@ class DefaultEmbeddingAgentClassifier(
     ) {
         val classifiedAgentId = result.classifiedAgents.firstOrNull()?.id ?: "none"
         this
-            .atInfo()
+            .atDebug()
             .addKeyValue("classifier-type", "Vector")
             .addKeyValue("classifier-user-message", request.inputContext.userMessage)
             .addKeyValue("classifier-embedding-search-queries", searchQueries)

lmos-classifier-vector/src/main/kotlin/org/eclipse/lmos/classifier/vector/ranker/SingleAgentEmbeddingRanker.kt

@@ -84,7 +84,7 @@ class SingleAgentEmbeddingRanker(
         rankingMatch: Boolean,
     ) {
         this
-            .atInfo()
+            .atDebug()
             .addKeyValue("classifier-embedding-ranking-thresholds", thresholds)
             .addKeyValue("classifier-embedding-ranking-evaluation", embeddingRankingEvaluation)
             .addKeyValue("classifier-embedding-ranking-top-agent", topAgent)