/*
 * Copyright 2023 - 2024 the original author or authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * https://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.springframework.ai.vectorstore;

import java.io.IOException;
import java.nio.charset.StandardCharsets;
import java.util.Collections;
import java.util.List;
import java.util.Map;
import java.util.UUID;

import io.milvus.client.MilvusServiceClient;
import io.milvus.param.ConnectParam;
import io.milvus.param.IndexType;
import io.milvus.param.MetricType;
import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
import org.junit.jupiter.params.ParameterizedTest;
import org.junit.jupiter.params.provider.ValueSource;
import org.testcontainers.junit.jupiter.Container;
import org.testcontainers.junit.jupiter.Testcontainers;

import org.springframework.ai.document.Document;
import org.springframework.ai.embedding.EmbeddingClient;
import org.springframework.ai.openai.OpenAiEmbeddingClient;
import org.springframework.ai.openai.api.OpenAiApi;
import org.springframework.ai.vectorstore.MilvusVectorStore.MilvusVectorStoreConfig;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.boot.SpringBootConfiguration;
import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
import org.springframework.boot.test.context.runner.ApplicationContextRunner;
import org.springframework.context.annotation.Bean;
import org.springframework.core.io.DefaultResourceLoader;
import org.testcontainers.milvus.MilvusContainer;

import static org.assertj.core.api.Assertions.assertThat;

/**
 * @author Christian Tzolov
 * @author Eddú Meléndez
 */
@Testcontainers
@EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
public class MilvusVectorStoreIT {

	@Container
	private static MilvusContainer milvusContainer = new MilvusContainer("milvusdb/milvus:v2.3.8");

	private final ApplicationContextRunner contextRunner = new ApplicationContextRunner()
		.withUserConfiguration(TestApplication.class);

	List<Document> documents = List.of(
			new Document(getText("classpath:/test/data/spring.ai.txt"), Map.of("meta1", "meta1")),
			new Document(getText("classpath:/test/data/time.shelter.txt")),
			new Document(getText("classpath:/test/data/great.depression.txt"), Map.of("meta2", "meta2")));

	public static String getText(String uri) {
		var resource = new DefaultResourceLoader().getResource(uri);
		try {
			return resource.getContentAsString(StandardCharsets.UTF_8);
		}
		catch (IOException e) {
			throw new RuntimeException(e);
		}
	}

	private void resetCollection(VectorStore vectorStore) {
		((MilvusVectorStore) vectorStore).dropCollection();
		((MilvusVectorStore) vectorStore).createCollection();
	}

	@ParameterizedTest(name = "{0} : {displayName} ")
	@ValueSource(strings = { "COSINE", "L2", "IP" })
	public void addAndSearch(String metricType) {

		contextRunner.withPropertyValues("test.spring.ai.vectorstore.milvus.metricType=" + metricType).run(context -> {

			VectorStore vectorStore = context.getBean(VectorStore.class);

			resetCollection(vectorStore);

			vectorStore.add(documents);

			List<Document> results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));

			assertThat(results).hasSize(1);
			Document resultDoc = results.get(0);
			assertThat(resultDoc.getId()).isEqualTo(documents.get(0).getId());
			assertThat(resultDoc.getContent()).contains(
					"Spring AI provides abstractions that serve as the foundation for developing AI applications.");
			assertThat(resultDoc.getMetadata()).hasSize(2);
			assertThat(resultDoc.getMetadata()).containsKeys("meta1", "distance");

			// Remove all documents from the store
			vectorStore.delete(documents.stream().map(doc -> doc.getId()).toList());

			results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(1));
			assertThat(results).hasSize(0);
		});
	}

	@ParameterizedTest(name = "{0} : {displayName} ")
	@ValueSource(strings = { "COSINE" })
	// @ValueSource(strings = { "COSINE", "IP", "L2" })
	public void searchWithFilters(String metricType) throws InterruptedException {

		// https://milvus.io/docs/json_data_type.md

		contextRunner.withPropertyValues("test.spring.ai.vectorstore.milvus.metricType=" + metricType).run(context -> {
			VectorStore vectorStore = context.getBean(VectorStore.class);

			resetCollection(vectorStore);

			var bgDocument = new Document("The World is Big and Salvation Lurks Around the Corner",
					Map.of("country", "BG", "year", 2020));
			var nlDocument = new Document("The World is Big and Salvation Lurks Around the Corner",
					Map.of("country", "NL"));
			var bgDocument2 = new Document("The World is Big and Salvation Lurks Around the Corner",
					Map.of("country", "BG", "year", 2023));

			vectorStore.add(List.of(bgDocument, nlDocument, bgDocument2));

			List<Document> results = vectorStore.similaritySearch(SearchRequest.query("The World").withTopK(5));
			assertThat(results).hasSize(3);

			results = vectorStore.similaritySearch(SearchRequest.query("The World")
				.withTopK(5)
				.withSimilarityThresholdAll()
				.withFilterExpression("country == 'NL'"));
			assertThat(results).hasSize(1);
			assertThat(results.get(0).getId()).isEqualTo(nlDocument.getId());

			results = vectorStore.similaritySearch(SearchRequest.query("The World")
				.withTopK(5)
				.withSimilarityThresholdAll()
				.withFilterExpression("country == 'BG'"));

			assertThat(results).hasSize(2);
			assertThat(results.get(0).getId()).isIn(bgDocument.getId(), bgDocument2.getId());
			assertThat(results.get(1).getId()).isIn(bgDocument.getId(), bgDocument2.getId());

			results = vectorStore.similaritySearch(SearchRequest.query("The World")
				.withTopK(5)
				.withSimilarityThresholdAll()
				.withFilterExpression("country == 'BG' && year == 2020"));

			assertThat(results).hasSize(1);
			assertThat(results.get(0).getId()).isEqualTo(bgDocument.getId());

			results = vectorStore.similaritySearch(SearchRequest.query("The World")
				.withTopK(5)
				.withSimilarityThresholdAll()
				.withFilterExpression("NOT(country == 'BG' && year == 2020)"));

			assertThat(results).hasSize(2);
			assertThat(results.get(0).getId()).isIn(nlDocument.getId(), bgDocument2.getId());
			assertThat(results.get(1).getId()).isIn(nlDocument.getId(), bgDocument2.getId());

		});
	}

	@ParameterizedTest(name = "{0} : {displayName} ")
	@ValueSource(strings = { "COSINE", "L2", "IP" })
	public void documentUpdate(String metricType) {

		contextRunner.withPropertyValues("test.spring.ai.vectorstore.milvus.metricType=" + metricType).run(context -> {

			VectorStore vectorStore = context.getBean(VectorStore.class);

			resetCollection(vectorStore);

			Document document = new Document(UUID.randomUUID().toString(), "Spring AI rocks!!",
					Collections.singletonMap("meta1", "meta1"));

			vectorStore.add(List.of(document));

			List<Document> results = vectorStore.similaritySearch(SearchRequest.query("Spring").withTopK(5));

			assertThat(results).hasSize(1);
			Document resultDoc = results.get(0);
			assertThat(resultDoc.getId()).isEqualTo(document.getId());
			assertThat(resultDoc.getContent()).isEqualTo("Spring AI rocks!!");
			assertThat(resultDoc.getMetadata()).containsKey("meta1");
			assertThat(resultDoc.getMetadata()).containsKey("distance");

			Document sameIdDocument = new Document(document.getId(),
					"The World is Big and Salvation Lurks Around the Corner",
					Collections.singletonMap("meta2", "meta2"));

			vectorStore.add(List.of(sameIdDocument));

			results = vectorStore.similaritySearch(SearchRequest.query("FooBar").withTopK(5));

			assertThat(results).hasSize(1);
			resultDoc = results.get(0);
			assertThat(resultDoc.getId()).isEqualTo(document.getId());
			assertThat(resultDoc.getContent()).isEqualTo("The World is Big and Salvation Lurks Around the Corner");
			assertThat(resultDoc.getMetadata()).containsKey("meta2");
			assertThat(resultDoc.getMetadata()).containsKey("distance");

			vectorStore.delete(List.of(document.getId()));

		});
	}

	@ParameterizedTest(name = "{0} : {displayName} ")
	@ValueSource(strings = { "COSINE", "IP" })
	public void searchWithThreshold(String metricType) {

		contextRunner.withPropertyValues("test.spring.ai.vectorstore.milvus.metricType=" + metricType).run(context -> {

			VectorStore vectorStore = context.getBean(VectorStore.class);

			resetCollection(vectorStore);

			vectorStore.add(documents);

			List<Document> fullResult = vectorStore
				.similaritySearch(SearchRequest.query("Spring").withTopK(5).withSimilarityThresholdAll());

			List<Float> distances = fullResult.stream().map(doc -> (Float) doc.getMetadata().get("distance")).toList();

			assertThat(distances).hasSize(3);

			float threshold = (distances.get(0) + distances.get(1)) / 2;

			List<Document> results = vectorStore
				.similaritySearch(SearchRequest.query("Spring").withTopK(5).withSimilarityThreshold(1 - threshold));

			assertThat(results).hasSize(1);
			Document resultDoc = results.get(0);
			assertThat(resultDoc.getId()).isEqualTo(documents.get(0).getId());
			assertThat(resultDoc.getContent()).contains(
					"Spring AI provides abstractions that serve as the foundation for developing AI applications.");
			assertThat(resultDoc.getMetadata()).containsKeys("meta1", "distance");

		});
	}

	@SpringBootConfiguration
	@EnableAutoConfiguration(exclude = { DataSourceAutoConfiguration.class })
	public static class TestApplication {

		@Value("${test.spring.ai.vectorstore.milvus.metricType}")
		private MetricType metricType;

		@Bean
		public VectorStore vectorStore(MilvusServiceClient milvusClient, EmbeddingClient embeddingClient) {
			MilvusVectorStoreConfig config = MilvusVectorStoreConfig.builder()
				.withCollectionName("test_vector_store")
				.withDatabaseName("default")
				.withIndexType(IndexType.IVF_FLAT)
				.withMetricType(metricType)
				.build();
			return new MilvusVectorStore(milvusClient, embeddingClient, config);
		}

		@Bean
		public MilvusServiceClient milvusClient() {
			return new MilvusServiceClient(ConnectParam.newBuilder()
				.withAuthorization("minioadmin", "minioadmin")
				.withUri(milvusContainer.getEndpoint())
				.build());
		}

		@Bean
		public EmbeddingClient embeddingClient() {
			return new OpenAiEmbeddingClient(new OpenAiApi(System.getenv("OPENAI_API_KEY")));
			// return new OpenAiEmbeddingClient(new
			// OpenAiApi(System.getenv("OPENAI_API_KEY")), MetadataMode.EMBED,
			// OpenAiEmbeddingOptions.builder().withModel("text-embedding-ada-002").build());
		}

	}

}