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Refactoring of ChatClient to add fluent API and introduce Model as dependent object

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* Rename the ModelClient class hierarchy into Model:
  - Rename ModelClient into Model. Update all code and doc references.
  - Rename ChatClient to ChatModel. Update all ChatClient suffixes and chatClient fields and variables in code and doc.
  - Rename EmbeddingClient into EmbeddingModel. Update the XxxEmbeddingClient class and variable suffixes and embeddingClient variables and fields in code and docs.
  - Rename ImageClient into ImageModel.
  - Rename SpeechClient into SpeechModel.
  - Rename TranscriptionClient into TranscriptionModel.
  - Update all javadocs and antora pages. Update the related diagrams.

* Create fluent API in ChatClient interface that now includes streaming support
* Add OpenAI FunctionCallbackWrapper2IT auto-config tests.
* Add ChatClientTest mockito testing.
* Add ChatModel#getDefaultOptions(), and remove @FunctionalInterface

* ChatModel enums extend the new ModelDescription interface.
* Implement fromOptions copy method in every ChatOptions implementation.
* Extend ChatClient to use the model default options if not provided explicitly.

* Update readme to provide guidance on how to adapt to breaking changes.

Co-authored-by: Christian Tzolov <ctzolov@vmware.com>
Co-authored-by: Mark Pollack <mpollack@vmware.com>
This commit is contained in:
Josh Long
2024-05-18 21:30:51 +02:00
committed by Mark Pollack
parent bce45c2d2f
commit fbfc87e814
426 changed files with 4815 additions and 2912 deletions
Download Patch File Download Diff File Expand all files Collapse all files

18
models/spring-ai-postgresml/src/main/java/org/springframework/ai/postgresml/PostgresMlEmbeddingClient.java → models/spring-ai-postgresml/src/main/java/org/springframework/ai/postgresml/PostgresMlEmbeddingModel.java
View File

@@ -24,7 +24,7 @@ import java.util.Map;
import org.springframework.ai.document.Document;
import org.springframework.ai.document.MetadataMode;
import org.springframework.ai.embedding.AbstractEmbeddingClient;
import org.springframework.ai.embedding.AbstractEmbeddingModel;
import org.springframework.ai.embedding.Embedding;
import org.springframework.ai.embedding.EmbeddingOptions;
import org.springframework.ai.embedding.EmbeddingRequest;
@@ -39,12 +39,12 @@ import org.springframework.util.CollectionUtils;
import org.springframework.util.StringUtils;
/**
* <a href="https://postgresml.org">PostgresML</a> EmbeddingClient
* <a href="https://postgresml.org">PostgresML</a> EmbeddingModel
*
* @author Toshiaki Maki
* @author Christian Tzolov
*/
public class PostgresMlEmbeddingClient extends AbstractEmbeddingClient implements InitializingBean {
public class PostgresMlEmbeddingModel extends AbstractEmbeddingModel implements InitializingBean {
public static final String DEFAULT_TRANSFORMER_MODEL = "distilbert-base-uncased";
@@ -83,16 +83,16 @@ public class PostgresMlEmbeddingClient extends AbstractEmbeddingClient implement
* a constructor
* @param jdbcTemplate JdbcTemplate
*/
public PostgresMlEmbeddingClient(JdbcTemplate jdbcTemplate) {
public PostgresMlEmbeddingModel(JdbcTemplate jdbcTemplate) {
this(jdbcTemplate, PostgresMlEmbeddingOptions.builder().build());
}
/**
* a PostgresMlEmbeddingClient constructor
* a PostgresMlEmbeddingModel constructor
* @param jdbcTemplate JdbcTemplate to use to interact with the database.
* @param options PostgresMlEmbeddingOptions to configure the client.
*/
public PostgresMlEmbeddingClient(JdbcTemplate jdbcTemplate, PostgresMlEmbeddingOptions options) {
public PostgresMlEmbeddingModel(JdbcTemplate jdbcTemplate, PostgresMlEmbeddingOptions options) {
Assert.notNull(jdbcTemplate, "jdbc template must not be null.");
Assert.notNull(options, "options must not be null.");
Assert.notNull(options.getTransformer(), "transformer must not be null.");
@@ -110,7 +110,7 @@ public class PostgresMlEmbeddingClient extends AbstractEmbeddingClient implement
* @param transformer huggingface sentence-transformer name
*/
@Deprecated(since = "0.8.0", forRemoval = true)
public PostgresMlEmbeddingClient(JdbcTemplate jdbcTemplate, String transformer) {
public PostgresMlEmbeddingModel(JdbcTemplate jdbcTemplate, String transformer) {
this(jdbcTemplate, transformer, VectorType.PG_ARRAY);
}
@@ -122,7 +122,7 @@ public class PostgresMlEmbeddingClient extends AbstractEmbeddingClient implement
* @param vectorType vector type in PostgreSQL
*/
@Deprecated(since = "0.8.0", forRemoval = true)
public PostgresMlEmbeddingClient(JdbcTemplate jdbcTemplate, String transformer, VectorType vectorType) {
public PostgresMlEmbeddingModel(JdbcTemplate jdbcTemplate, String transformer, VectorType vectorType) {
this(jdbcTemplate, transformer, vectorType, Map.of(), MetadataMode.EMBED);
}
@@ -135,7 +135,7 @@ public class PostgresMlEmbeddingClient extends AbstractEmbeddingClient implement
* @param kwargs optional arguments
*/
@Deprecated(since = "0.8.0", forRemoval = true)
public PostgresMlEmbeddingClient(JdbcTemplate jdbcTemplate, String transformer, VectorType vectorType,
public PostgresMlEmbeddingModel(JdbcTemplate jdbcTemplate, String transformer, VectorType vectorType,
Map<String, Object> kwargs, MetadataMode metadataMode) {
Assert.notNull(jdbcTemplate, "jdbc template must not be null.");
Assert.notNull(transformer, "transformer must not be null.");

4
models/spring-ai-postgresml/src/main/java/org/springframework/ai/postgresml/PostgresMlEmbeddingOptions.java
View File

@@ -24,7 +24,7 @@ import com.fasterxml.jackson.annotation.JsonProperty;
import org.springframework.ai.document.MetadataMode;
import org.springframework.ai.embedding.EmbeddingOptions;
import org.springframework.ai.model.ModelOptionsUtils;
import org.springframework.ai.postgresml.PostgresMlEmbeddingClient.VectorType;
import org.springframework.ai.postgresml.PostgresMlEmbeddingModel.VectorType;
/**
* @author Christian Tzolov
@@ -36,7 +36,7 @@ public class PostgresMlEmbeddingOptions implements EmbeddingOptions {
/**
* The Huggingface transformer model to use for the embedding.
*/
private @JsonProperty("transformer") String transformer = PostgresMlEmbeddingClient.DEFAULT_TRANSFORMER_MODEL;
private @JsonProperty("transformer") String transformer = PostgresMlEmbeddingModel.DEFAULT_TRANSFORMER_MODEL;
/**
* PostgresML vector type to use for the embedding.

54
models/spring-ai-postgresml/src/test/java/org/springframework/ai/postgresml/PostgresMlEmbeddingClientIT.java → models/spring-ai-postgresml/src/test/java/org/springframework/ai/postgresml/PostgresMlEmbeddingModelIT.java
View File

@@ -30,7 +30,7 @@ import org.junit.jupiter.params.provider.ValueSource;
import org.springframework.ai.embedding.EmbeddingOptions;
import org.springframework.ai.embedding.EmbeddingRequest;
import org.springframework.ai.embedding.EmbeddingResponse;
import org.springframework.ai.postgresml.PostgresMlEmbeddingClient.VectorType;
import org.springframework.ai.postgresml.PostgresMlEmbeddingModel.VectorType;
import org.testcontainers.containers.PostgreSQLContainer;
import org.testcontainers.containers.wait.strategy.LogMessageWaitStrategy;
@@ -56,7 +56,7 @@ import static org.assertj.core.api.Assertions.assertThat;
@AutoConfigureTestDatabase(replace = AutoConfigureTestDatabase.Replace.NONE)
@Testcontainers
@Disabled("Disabled from automatic execution, as it requires an excessive amount of memory (over 9GB)!")
class PostgresMlEmbeddingClientIT {
class PostgresMlEmbeddingModelIT {
@Container
@ServiceConnection
@@ -80,51 +80,51 @@ class PostgresMlEmbeddingClientIT {
@Test
void embed() {
PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate);
embeddingClient.afterPropertiesSet();
PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate);
embeddingModel.afterPropertiesSet();
List<Double> embed = embeddingClient.embed("Hello World!");
List<Double> embed = embeddingModel.embed("Hello World!");
assertThat(embed).hasSize(768);
}
@Test
void embedWithPgVector() {
PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate,
PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate,
PostgresMlEmbeddingOptions.builder()
.withTransformer("distilbert-base-uncased")
.withVectorType(PostgresMlEmbeddingClient.VectorType.PG_VECTOR)
.withVectorType(PostgresMlEmbeddingModel.VectorType.PG_VECTOR)
.build());
embeddingClient.afterPropertiesSet();
embeddingModel.afterPropertiesSet();
List<Double> embed = embeddingClient.embed(new Document("Hello World!"));
List<Double> embed = embeddingModel.embed(new Document("Hello World!"));
assertThat(embed).hasSize(768);
}
@Test
void embedWithDifferentModel() {
PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate,
PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate,
PostgresMlEmbeddingOptions.builder().withTransformer("intfloat/e5-small").build());
embeddingClient.afterPropertiesSet();
embeddingModel.afterPropertiesSet();
List<Double> embed = embeddingClient.embed(new Document("Hello World!"));
List<Double> embed = embeddingModel.embed(new Document("Hello World!"));
assertThat(embed).hasSize(384);
}
@Test
void embedWithKwargs() {
PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate,
PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate,
PostgresMlEmbeddingOptions.builder()
.withTransformer("distilbert-base-uncased")
.withVectorType(PostgresMlEmbeddingClient.VectorType.PG_ARRAY)
.withVectorType(PostgresMlEmbeddingModel.VectorType.PG_ARRAY)
.withKwargs(Map.of("device", "cpu"))
.withMetadataMode(MetadataMode.EMBED)
.build());
embeddingClient.afterPropertiesSet();
embeddingModel.afterPropertiesSet();
List<Double> embed = embeddingClient.embed(new Document("Hello World!"));
List<Double> embed = embeddingModel.embed(new Document("Hello World!"));
assertThat(embed).hasSize(768);
}
@@ -132,14 +132,14 @@ class PostgresMlEmbeddingClientIT {
@ParameterizedTest
@ValueSource(strings = { "PG_ARRAY", "PG_VECTOR" })
void embedForResponse(String vectorType) {
PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate,
PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate,
PostgresMlEmbeddingOptions.builder()
.withTransformer("distilbert-base-uncased")
.withVectorType(VectorType.valueOf(vectorType))
.build());
embeddingClient.afterPropertiesSet();
embeddingModel.afterPropertiesSet();
EmbeddingResponse embeddingResponse = embeddingClient
EmbeddingResponse embeddingResponse = embeddingModel
.embedForResponse(List.of("Hello World!", "Spring AI!", "LLM!"));
assertThat(embeddingResponse).isNotNull();
@@ -157,16 +157,16 @@ class PostgresMlEmbeddingClientIT {
@Test
void embedCallWithRequestOptionsOverride() {
PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate,
PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate,
PostgresMlEmbeddingOptions.builder()
.withTransformer("distilbert-base-uncased")
.withVectorType(VectorType.PG_VECTOR)
.build());
embeddingClient.afterPropertiesSet();
embeddingModel.afterPropertiesSet();
var request1 = new EmbeddingRequest(List.of("Hello World!", "Spring AI!", "LLM!"), EmbeddingOptions.EMPTY);
EmbeddingResponse embeddingResponse = embeddingClient.call(request1);
EmbeddingResponse embeddingResponse = embeddingModel.call(request1);
assertThat(embeddingResponse).isNotNull();
assertThat(embeddingResponse.getResults()).hasSize(3);
@@ -188,7 +188,7 @@ class PostgresMlEmbeddingClientIT {
.withKwargs(Map.of("device", "cpu"))
.build());
embeddingResponse = embeddingClient.call(request2);
embeddingResponse = embeddingModel.call(request2);
assertThat(embeddingResponse).isNotNull();
assertThat(embeddingResponse.getResults()).hasSize(3);
@@ -205,11 +205,11 @@ class PostgresMlEmbeddingClientIT {
@Test
void dimensions() {
PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate);
embeddingClient.afterPropertiesSet();
Assertions.assertThat(embeddingClient.dimensions()).isEqualTo(768);
PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate);
embeddingModel.afterPropertiesSet();
Assertions.assertThat(embeddingModel.dimensions()).isEqualTo(768);
// cached
Assertions.assertThat(embeddingClient.dimensions()).isEqualTo(768);
Assertions.assertThat(embeddingModel.dimensions()).isEqualTo(768);
}
@SpringBootApplication

26
models/spring-ai-postgresml/src/test/java/org/springframework/ai/postgresml/PostgresMlEmbeddingOptionsTests.java
View File

@@ -34,8 +34,8 @@ public class PostgresMlEmbeddingOptionsTests {
public void defaultOptions() {
PostgresMlEmbeddingOptions options = PostgresMlEmbeddingOptions.builder().build();
assertThat(options.getTransformer()).isEqualTo(PostgresMlEmbeddingClient.DEFAULT_TRANSFORMER_MODEL);
assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingClient.VectorType.PG_ARRAY);
assertThat(options.getTransformer()).isEqualTo(PostgresMlEmbeddingModel.DEFAULT_TRANSFORMER_MODEL);
assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingModel.VectorType.PG_ARRAY);
assertThat(options.getKwargs()).isEqualTo(Map.of());
assertThat(options.getMetadataMode()).isEqualTo(org.springframework.ai.document.MetadataMode.EMBED);
}
@@ -44,13 +44,13 @@ public class PostgresMlEmbeddingOptionsTests {
public void newOptions() {
PostgresMlEmbeddingOptions options = PostgresMlEmbeddingOptions.builder()
.withTransformer("intfloat/e5-small")
.withVectorType(PostgresMlEmbeddingClient.VectorType.PG_VECTOR)
.withVectorType(PostgresMlEmbeddingModel.VectorType.PG_VECTOR)
.withMetadataMode(org.springframework.ai.document.MetadataMode.ALL)
.withKwargs(Map.of("device", "cpu"))
.build();
assertThat(options.getTransformer()).isEqualTo("intfloat/e5-small");
assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingClient.VectorType.PG_VECTOR);
assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingModel.VectorType.PG_VECTOR);
assertThat(options.getKwargs()).isEqualTo(Map.of("device", "cpu"));
assertThat(options.getMetadataMode()).isEqualTo(org.springframework.ai.document.MetadataMode.ALL);
}
@@ -59,37 +59,37 @@ public class PostgresMlEmbeddingOptionsTests {
public void mergeOptions() {
var jdbcTemplate = Mockito.mock(JdbcTemplate.class);
PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(jdbcTemplate);
PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(jdbcTemplate);
PostgresMlEmbeddingOptions options = embeddingClient.mergeOptions(EmbeddingOptions.EMPTY);
PostgresMlEmbeddingOptions options = embeddingModel.mergeOptions(EmbeddingOptions.EMPTY);
// Default options
assertThat(options.getTransformer()).isEqualTo(PostgresMlEmbeddingClient.DEFAULT_TRANSFORMER_MODEL);
assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingClient.VectorType.PG_ARRAY);
assertThat(options.getTransformer()).isEqualTo(PostgresMlEmbeddingModel.DEFAULT_TRANSFORMER_MODEL);
assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingModel.VectorType.PG_ARRAY);
assertThat(options.getKwargs()).isEqualTo(Map.of());
assertThat(options.getMetadataMode()).isEqualTo(org.springframework.ai.document.MetadataMode.EMBED);
// Partial override
options = embeddingClient.mergeOptions(PostgresMlEmbeddingOptions.builder()
options = embeddingModel.mergeOptions(PostgresMlEmbeddingOptions.builder()
.withTransformer("intfloat/e5-small")
.withKwargs(Map.of("device", "cpu"))
.build());
assertThat(options.getTransformer()).isEqualTo("intfloat/e5-small");
assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingClient.VectorType.PG_ARRAY); // Default
assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingModel.VectorType.PG_ARRAY); // Default
assertThat(options.getKwargs()).isEqualTo(Map.of("device", "cpu"));
assertThat(options.getMetadataMode()).isEqualTo(org.springframework.ai.document.MetadataMode.EMBED); // Default
// Complete override
options = embeddingClient.mergeOptions(PostgresMlEmbeddingOptions.builder()
options = embeddingModel.mergeOptions(PostgresMlEmbeddingOptions.builder()
.withTransformer("intfloat/e5-small")
.withVectorType(PostgresMlEmbeddingClient.VectorType.PG_VECTOR)
.withVectorType(PostgresMlEmbeddingModel.VectorType.PG_VECTOR)
.withMetadataMode(org.springframework.ai.document.MetadataMode.ALL)
.withKwargs(Map.of("device", "cpu"))
.build());
assertThat(options.getTransformer()).isEqualTo("intfloat/e5-small");
assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingClient.VectorType.PG_VECTOR);
assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingModel.VectorType.PG_VECTOR);
assertThat(options.getKwargs()).isEqualTo(Map.of("device", "cpu"));
assertThat(options.getMetadataMode()).isEqualTo(org.springframework.ai.document.MetadataMode.ALL);
}