....

build.gradle.kts

@@ -64,7 +64,8 @@ dependencies {
 //	implementation("org.springframework.ai:spring-ai-ollama-spring-boot-starter:1.0.0-SNAPSHOT")
 	implementation(platform("org.springframework.ai:spring-ai-bom:1.0.0-M6"))
 	implementation("org.springframework.ai:spring-ai-ollama-spring-boot-starter:1.0.0-M6")
-	implementation("org.springframework.ai:spring-ai-redis-store")
+	implementation ("org.springframework.ai:spring-ai-qdrant-store-spring-boot-starter")
+//	implementation ("io.qdrant:client:1.13.0")
 
 	implementation ("org.slf4j:slf4j-simple:1.7.25")
 

src/main/kotlin/kr/lunaticbum/back/lun/configs/AppConfig.kt

@@ -1,7 +1,7 @@
 package kr.lunaticbum.back.lun.configs
 
+import io.qdrant.client.QdrantClient
 import org.springframework.ai.ollama.api.OllamaApi
-import org.springframework.ai.ollama.api.OllamaOptions
 import org.springframework.beans.factory.annotation.Value
 import org.springframework.context.annotation.Bean
 import org.springframework.context.annotation.Configuration
@@ -30,6 +30,12 @@ class AppConfig : WebMvcConfigurer {
         super.addInterceptors(registry)
     }
 
+
+//    @Bean
+//    fun qdrantClient(): QdrantClient {
+//        return QdrantClient("https://ollama.lunaticbum.kr:6334")
+//    }
+
     @Bean
     fun chatClient(): OllamaApi {
         return OllamaApi("https://lama.lunaticbum.kr")

src/main/kotlin/kr/lunaticbum/back/lun/controllers/Telegram.kt

@@ -12,6 +12,7 @@ import com.google.maps.model.RankBy
 import jakarta.servlet.http.HttpServletRequest
 import kotlinx.coroutines.CoroutineScope
 import kotlinx.coroutines.Dispatchers
+import kotlinx.coroutines.async
 import kotlinx.coroutines.launch
 import kr.lunaticbum.back.lun.configs.GlobalEnvironment
 import kr.lunaticbum.back.lun.model.*
@@ -437,26 +438,40 @@ class Telegram {
     @Autowired
     lateinit var lama : Lama
 
+
     @ResponseBody
     @GetMapping("query/{path}")
     fun googleQueryTest(@PathVariable path: String): String {
         var originalQuery = path
-        val gSearch = "https://psn.lunaticbum.kr/search?q=${originalQuery?.replace("오늘", SimpleDateFormat("yyyMMdd").format(Date()))}&language=auto&time_range=month&safesearch=0&categories=general&format=json"
+//        POST /collections
-        println("gSearch >>> ${gSearch}")
+//
-        var additionalInfo = StringBuffer()
+//        Content-Type: application/json
-        additionalInfo.append("참고자료")
+//
-        var idx = 0
+//        {
-        WebClient.create().get()
+//            "name": "movies",
-            .uri(gSearch)
+//            "vector_size": 3072,
-            .retrieve()
+//            "distance": "Cosine"
-            .bodyToMono(SearXng::class.java).timeout(Duration.ofMinutes(20L)).block()?.let { gsResult ->
+//        }
-                gsResult.results?.filter { it.score > 0.5}?.forEach {
-                    additionalInfo.append(idx).append(":").append(Gson().toJson(it))
-                    idx += 1
-                }
-            }
 
-        lama.generateResponse(query = originalQuery)
+//        println(lama.makeCollection())
+
+//        val gSearch = "https://psn.lunaticbum.kr/search?q=${originalQuery?.replace("오늘", SimpleDateFormat("yyyMMdd").format(Date()))}&language=auto&time_range=month&safesearch=0&categories=general&format=json"
+//        println("gSearch >>> ${gSearch}")
+//        var additionalInfo = StringBuffer()
+//        additionalInfo.append("참고자료")
+//        var idx = 0
+//        WebClient.create().get()
+//            .uri(gSearch)
+//            .retrieve()
+//            .bodyToMono(SearXng::class.java).timeout(Duration.ofMinutes(20L)).block()?.let { gsResult ->
+//                gsResult.results?.filter { it.score > 0.5}?.forEach {
+//                    additionalInfo.append(idx).append(":").append(Gson().toJson(it))
+//                    idx += 1
+//                }
+//            }
+        CoroutineScope(Dispatchers.IO).async {
+            lama.generateResponse(query = originalQuery)
+        }
         return "TEST"
     }
 

src/main/kotlin/kr/lunaticbum/back/lun/model/QCollection.kt

@@ -0,0 +1,115 @@
+package kr.lunaticbum.back.lun.model
+
+
+class QCollection {
+    var result: QResult? = null
+    var status: String? = null
+    var time: Double = 0.0
+}
+class QConfig {
+    var params: QParams? = null
+    var hnsw_config: QHnswConfig? = null
+    var optimizer_config: QOptimizerConfig? = null
+    var wal_config: QWalConfig? = null
+    var quantization_config: Any? = null
+    var strict_mode_config: QStrictModeConfig? = null
+}
+
+class QHnswConfig {
+    var m: Int = 0
+    var ef_construct: Int = 0
+    var full_scan_threshold: Int = 0
+    var max_indexing_threads: Int = 0
+    var on_disk: Boolean = false
+}
+
+class QOptimizerConfig {
+    var deleted_threshold: Double = 0.0
+    var vacuum_min_vector_number: Int = 0
+    var default_segment_number: Int = 0
+    var max_segment_size: Any? = null
+    var memmap_threshold: Any? = null
+    var indexing_threshold: Int = 0
+    var flush_interval_sec: Int = 0
+    var max_optimization_threads: Any? = null
+}
+
+class QParams {
+    var vectors: QVectors? = null
+    var shard_number: Int = 0
+    var replication_factor: Int = 0
+    var write_consistency_factor: Int = 0
+    var on_disk_payload: Boolean = false
+}
+
+class QPayloadSchema
+
+class QResult {
+    var status: String? = null
+    var optimizer_status: String? = null
+    var indexed_vectors_count: Int = 0
+    var points_count: Long = 0
+    var segments_count: Int = 0
+    var config: QConfig? = null
+    var payload_schema: QPayloadSchema? = null
+}
+
+
+
+class QStrictModeConfig {
+    var enabled: Boolean = false
+}
+
+class QVectors {
+    var size: Int = 0
+    var distance: String? = null
+}
+
+class QWalConfig {
+    var wal_capacity_mb: Int = 0
+    var wal_segments_ahead: Int = 0
+}
+
+class QSearchResult {
+    var id: Int = 0
+    var version: Int = 0
+    var score: Double = 0.0
+}
+
+class QSearch {
+    var result: ArrayList<QSearchResult>? = null
+    var status: String? = null
+    var time: Double = 0.0
+}
+
+
+// import com.fasterxml.jackson.databind.ObjectMapper; // version 2.11.1
+// import com.fasterxml.jackson.annotation.JsonProperty; // version 2.11.1
+/* ObjectMapper om = new ObjectMapper();
+Root root = om.readValue(myJsonString, Root.class); */
+class QContentsPayload {
+    var url: String? = null
+    var title: String? = null
+    var content: String? = null
+    var engine: String? = null
+    var template: String? = null
+    var parsed_url: ArrayList<String>? = null
+    var engines: ArrayList<String>? = null
+    var positions: ArrayList<Int>? = null
+    var score: Double = 0.0
+    var category: String? = null
+    var originQuery: String? = null
+    var pageData: String? = null
+}
+
+class QContentsResult {
+    var id: Int = 0
+    var payload: QContentsPayload? = null
+}
+
+class QContents {
+    var result: ArrayList<QContentsResult>? = null
+    var status: String? = null
+    var time: Double = 0.0
+}
+

src/main/kotlin/kr/lunaticbum/back/lun/model/SearXng.kt

@@ -12,6 +12,7 @@ class SearXng {
     var unresponsive_engines: ArrayList<ArrayList<String>>? = null
 }
 class SearXngResult {
+    var originQuery : String? = null
     var url: String? = null
     var title: String? = null
     var content: String? = null
@@ -23,4 +24,5 @@ class SearXngResult {
     var positions: ArrayList<Int>? = null
     var score: Double = 0.0
     var category: String? = null
+    var pageData : String? = null
 }

src/main/kotlin/kr/lunaticbum/back/lun/service/Lama.kt

@@ -1,61 +1,222 @@
 package kr.lunaticbum.back.lun.service
 
 
-import org.springframework.ai.chat.messages.UserMessage
+
-import org.springframework.ai.chat.prompt.Prompt
+import com.google.gson.Gson
-import org.springframework.ai.document.Document
+import com.knuddels.jtokkit.api.IntArrayList
-import org.springframework.ai.ollama.OllamaChatModel
+import io.micrometer.observation.ObservationRegistry
+import kr.lunaticbum.back.lun.configs.GlobalEnvironment
+import kr.lunaticbum.back.lun.model.*
+import org.jsoup.Jsoup
+import org.springframework.ai.embedding.EmbeddingRequest
+import org.springframework.ai.ollama.OllamaEmbeddingModel
 import org.springframework.ai.ollama.api.OllamaApi
-import org.springframework.ai.vectorstore.SearchRequest
+import org.springframework.ai.ollama.api.OllamaOptions
-import org.springframework.ai.vectorstore.VectorStore
+import org.springframework.ai.ollama.management.ModelManagementOptions
 import org.springframework.beans.factory.annotation.Autowired
 import org.springframework.beans.factory.annotation.Qualifier
 import org.springframework.stereotype.Service
-import java.util.stream.Collectors
+import org.springframework.web.reactive.function.BodyInserters
+import org.springframework.web.reactive.function.client.WebClient
+import java.net.URLEncoder
+import java.text.SimpleDateFormat
+import java.time.Duration
+import java.util.*
+import kotlin.collections.ArrayList
 
 
 @Service
 class Lama {
+
+
     @Qualifier("chatClient")
     @Autowired
     private lateinit var chatClient: OllamaApi
 
-    @Autowired
+    //, val date : String = SimpleDateFormat("yyyyMMddHHmmss").format(Date())
-    private lateinit var vectorStore: VectorStore
+//    data class QSearchData(val query : FloatArray,val limit : Int)
 
-    fun generateResponse(query: String?): String {
+    data class QSearchData(val vector : FloatArray,val limit : Int)
-        println("On generateResponse :: find something")
+    data class QPut(val points : ArrayList<QData>)
-        // 1. 유사 문서 검색
+    data class QData(val id : Long, val vector : FloatArray, val payload : SearXngResult)
 
-        val relevantDocs = vectorStore.similaritySearch(
+    data class QContentsList(var ids : ArrayList<Int> = ArrayList(), var with_payload : Boolean = true, var with_vector : Boolean = false)
-            SearchRequest.builder().query(query!!).topK(3).build()
+    //    fun makeCollection() : String{
+//
+//        class CollectionPut {
+//            val name = "blama_vectors"
+//            val vector_size = 3072
+//            val distance = "Cosine"
+//        }
+//        val qUrl = "https://ollama.lunaticbum.kr/collections"
+//        val client = WebClient.create()
+//        return client.post()
+//            .uri(qUrl)
+//            .header("api-key","blama-admin-key-gb")
+//            .body(BodyInserters.fromValue(Gson().toJson(CollectionPut())))
+//            .retrieve()
+//            .bodyToMono(String::class.java).timeout(Duration.ofMinutes(20L)).block() ?: ""
+//    }
+    var qPointsCount : Long = 0
+    private fun checkCollection() : Long {
+        val qUrl = "https://ollama.lunaticbum.kr/collections/blama_vectors"
+        val client = WebClient.create()
+        return client.get()
+            .uri(qUrl)
+            .header("api-key", "blama-admin-key-gb")
+            .retrieve()
+            .bodyToMono(QCollection::class.java).timeout(Duration.ofMinutes(20L)).block()?.result?.points_count ?: 0L
+    }
+    private fun addDocuments(query : String) {
+
+        val embeddingModel = OllamaEmbeddingModel(
+            chatClient,
+            OllamaOptions.builder().build(),
+            ObservationRegistry.create(),
+            ModelManagementOptions.defaults()
         )
+        val gSearch = "https://psn.lunaticbum.kr/search?q=${query?.replace("오늘", SimpleDateFormat("yyyMMdd").format(Date()))}&language=auto&time_range=month&safesearch=0&categories=general&format=json"
+        println("gSearch >>> ${gSearch}")
+        val sdss = QPut(arrayListOf())
+        WebClient.create().get()
+            .uri(gSearch)
+            .retrieve()
+            .bodyToMono(SearXng::class.java).timeout(Duration.ofMinutes(20L)).block()?.let { gsResult ->
+                gsResult.results?.filter { it.score > 0.5}?.forEach {
+                    qPointsCount += 1
+                    println("in filter")
+                    it.originQuery = query
+                    val data = Gson().toJson(it)
+                    println(it.title)
+                    Jsoup.connect(it.url).get().body().text()?.let { text ->
+                        try {
+                            println("text >>>>> $text")
+                            it.pageData = chatClient.chat(OllamaApi.ChatRequest.Builder("phi4:14b").stream(false).format("json").messages(
+                                listOf(OllamaApi.Message.Builder(OllamaApi.Message.Role.USER).content("'${text}' 웹 페이지 모든 내욜을 복사 한건데 본문 내용만 정리해줘").build())
+                            ).build()).message.content
+                            println("summary result >>>>>  ${it.pageData}")
+                            val embeddingResponse = embeddingModel.call(
+                                EmbeddingRequest(
+                                    listOf(data),
+                                    OllamaOptions.builder()
+                                        .model("nomic-embed-text")
+                                        .truncate(false)
+                                        .build()
+                                )
+                            )
+                            sdss.points.add(QData(id = qPointsCount,embeddingResponse.result.output,it))
+                        }catch (e : Exception) {
 
-        // 2. 프롬프트 구성
+                        }
-        val context = relevantDocs?.map { it.text }?.joinToString(separator = "\n")
+                    }
-        val prompt = """
+                }
-            Context information is below.
+            }
-            ----
+        println("out filter")
-            $context
+        if (sdss.points.size > 0) {
-            ----
+            println("sdss.points.size ${sdss.points.size} ${Gson().toJson(sdss)}")
-            Given the context information and not prior knowledge, answer the query: $query
+            val qUrl = "https://ollama.lunaticbum.kr/collections/blama_vectors".plus("/points")
-            \n한국어로 대답해줘
+            val client = WebClient.create()
-        """.trimIndent()
+            client.put()
+                .uri(qUrl)
+                .header("api-key", "blama-admin-key-gb")
+                .body(BodyInserters.fromValue(Gson().toJson(sdss)))
+                .retrieve()
+                .bodyToMono(String::class.java).timeout(Duration.ofMinutes(20L)).block() ?: ""
 
-        // 3. Ollama를 사용하여 응답 생성
-        val response: OllamaApi.ChatResponse = chatClient.chat(OllamaApi.ChatRequest.Builder("phi4:14b").stream(false).format("json").messages(
-            listOf(OllamaApi.Message.Builder(OllamaApi.Message.Role.USER).content(prompt).build())
-        ).build())
-        println(response.message.content)
-        println("On generateResponse :: END OF Answer")
-        return response.message.content
-    }
-
-    // 문서 추가 메소드
-    fun addDocuments(documents: List<Document?>?) {
-        documents?.let {
-            vectorStore.add(it)
         }
-//        vectorStore!!.add(documents)
+        println("end of search")
     }
+
+    private fun embedQuery(embedFlots : FloatArray) : QContents?{
+        val qUrl = "https://ollama.lunaticbum.kr/collections/blama_vectors".plus("/points/search")
+        val client = WebClient.create()
+        var lists = client.post()
+            .uri(qUrl)
+            .header("api-key","blama-admin-key-gb")
+            .body(BodyInserters.fromValue(Gson().toJson(QSearchData(embedFlots,5))))
+            .retrieve()
+            .bodyToMono(QSearch::class.java).timeout(Duration.ofMinutes(20L)).block()
+        return if (lists?.result?.size ?: 0 > 0) {
+            val qContents = QContentsList()
+
+            lists?.result?.forEach {
+                qContents.ids.add(it.id)
+            }
+            val qCUrl = "https://ollama.lunaticbum.kr/collections/blama_vectors".plus("/points")
+            val client2 = WebClient.create()
+            client.post()
+                .uri(qCUrl)
+                .header("api-key", "blama-admin-key-gb")
+                .body(BodyInserters.fromValue(Gson().toJson(qContents)))
+                .retrieve()
+                .bodyToMono(QContents::class.java).timeout(Duration.ofMinutes(20L)).block()
+        } else {
+            null
+        }
+    }
+
+    @Autowired
+    lateinit var globalEvv : GlobalEnvironment
+
+    suspend fun generateResponse(query: String?, targetId: String? = globalEvv.telegramMyId) {
+        val embeddingModel = OllamaEmbeddingModel(
+            chatClient,
+            OllamaOptions.builder().build(),
+            ObservationRegistry.create(),
+            ModelManagementOptions.defaults()
+        )
+        println("On generateResponse :: find something ${query}")
+        query?.let {
+            var embeddingResponse = embeddingModel.call(
+                EmbeddingRequest(
+                    listOf(query),
+                    OllamaOptions.builder()
+                        .model("nomic-embed-text")
+                        .truncate(false)
+                        .build()
+                )
+            )
+            println("points size  ${embeddingResponse.result.output.size}")
+            qPointsCount = checkCollection()
+            addDocuments(it)
+            embeddingResponse = embeddingModel.call(
+                EmbeddingRequest(
+                    listOf(query),
+                    OllamaOptions.builder()
+                        .model("nomic-embed-text")
+                        .truncate(false)
+                        .build()
+                )
+            )
+            println(embeddingResponse.result.output)
+            var context : String? = ""
+            try {
+                embedQuery(embeddingResponse.result.output)?.result?.forEach { result ->
+                    context += "참고자료:".plus(if (result.payload?.pageData?.length ?: 0 > 10) {
+                        result.payload?.pageData
+                    } else {
+                        result.payload?.content
+                    })
+                    context +="\n"
+                }
+
+            }catch (e:Exception){
+                e.printStackTrace()
+            }
+            val response: OllamaApi.ChatResponse =  if (context?.length ?: 0 > 10) {
+                val prompt = "Context information is below.\n$context\nGiven the context information and not prior knowledge, answer the query: $query\n한국어로 대답해줘".trimIndent()
+                chatClient.chat(OllamaApi.ChatRequest.Builder("phi4:14b").stream(false).format("json").messages(
+                    listOf(OllamaApi.Message.Builder(OllamaApi.Message.Role.USER).content(prompt).build())
+                ).build())
+            } else {
+                chatClient.chat(OllamaApi.ChatRequest.Builder("phi4:14b").stream(false).format("json").messages(
+                    listOf(OllamaApi.Message.Builder(OllamaApi.Message.Role.USER).content(query).build())
+                ).build())
+            }
+            println(response.message.content)
+            println("On generateResponse :: END OF Answer")
+        }
+    }
+
+
 }

src/main/resources/application.properties

@@ -65,10 +65,25 @@ spring.data.mongodb.option.local-threshold=15
 spring.ai.ollama.base-url=https://lama.lunaticbum.kr
 spring.ai.ollama.chat.options.model=phi4:14b
 
-spring.data.redis.host=ollama.lunaticbum.kr
+##spring.data.redis.url=ollama.lunaticbum.kr
-spring.ai.vectorstore.redis.initialize-schema=true
+#spring.data.redis.host=lunaticbum.kr
-spring.ai.vectorstore.redis.index=spring-ai-redis-index
+#spring.data.redis.port=6379
-spring.ai.vectorstore.redis.prefix=spring-ai-redis-embedding
+#
+##spring.ai.vectorstore.redis.uri="redis://lunaticbum.kr:6379"
+#
+#
+#spring.ai.vectorstore.redis.initialize-schema=true
+#spring.ai.vectorstore.redis.index=spring-ai-redis-index
+#spring.ai.vectorstore.redis.prefix=spring-ai-redis-embedding
+#https://ollama.lunaticbum.kr/collections/blama_vectors
+spring.ai.vectorstore.qdrant.host=ollama.lunaticbum.kr
+spring.ai.vectorstore.qdrant.port=443
+#spring.ai.vectorstore.qdrant.initialize-schema=true
+spring.ai.vectorstore.qdrant.api-key=blama-admin-key-gb
+spring.ai.vectorstore.qdrant.collection-name=blama_vectors
+spring.ai.ollama.embedding.model=nomic-embed-text
+
+spring.ai.ollama.embedding.enabled=true
 
 
 #>>>>>>> ab915d0a416c69708f1df1ad76d7a14c779c1f59