forked from opensearch-project/ml-commons
-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Signed-off-by: zane-neo <[email protected]>
- Loading branch information
Showing
7 changed files
with
294 additions
and
1 deletion.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
108 changes: 108 additions & 0 deletions
108
plugin/src/test/java/org/opensearch/ml/rest/RestBedRockV2PostProcessFunctionInferenceIT.java
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,108 @@ | ||
| /* | ||
| * Copyright OpenSearch Contributors | ||
| * SPDX-License-Identifier: Apache-2.0 | ||
| */ | ||
|
|
||
| package org.opensearch.ml.rest; | ||
|
|
||
| import lombok.SneakyThrows; | ||
| import lombok.extern.log4j.Log4j2; | ||
| import org.apache.commons.lang3.StringUtils; | ||
| import org.junit.Before; | ||
| import org.opensearch.ml.common.FunctionName; | ||
| import org.opensearch.ml.common.dataset.TextDocsInputDataSet; | ||
| import org.opensearch.ml.common.input.MLInput; | ||
|
|
||
| import java.io.IOException; | ||
| import java.nio.file.Files; | ||
| import java.nio.file.Path; | ||
| import java.util.ArrayList; | ||
| import java.util.List; | ||
| import java.util.Locale; | ||
| import java.util.Map; | ||
|
|
||
| @Log4j2 | ||
| public class RestBedRockV2PostProcessFunctionInferenceIT extends MLCommonsRestTestCase { | ||
| private static final String AWS_ACCESS_KEY_ID = System.getenv("AWS_ACCESS_KEY_ID"); | ||
| private static final String AWS_SECRET_ACCESS_KEY = System.getenv("AWS_SECRET_ACCESS_KEY"); | ||
| private static final String AWS_SESSION_TOKEN = System.getenv("AWS_SESSION_TOKEN"); | ||
| private static final String GITHUB_CI_AWS_REGION = "us-west-2"; | ||
| private static final List<String> POST_PROCESS_FUNCTIONS = List.of( | ||
| "connector.post_process.bedrock_v2.embedding.float", | ||
| "connector.post_process.bedrock_v2.embedding.binary" | ||
| ); | ||
| private static final Map<String, String> DATA_TYPE = Map.of( | ||
| "connector.post_process.bedrock_v2.embedding.float", "FLOAT32", | ||
| "connector.post_process.bedrock_v2.embedding.binary", "BINARY" | ||
| ); | ||
|
|
||
| @SneakyThrows | ||
| @Before | ||
| public void setup() throws IOException, InterruptedException { | ||
| RestMLRemoteInferenceIT.disableClusterConnectorAccessControl(); | ||
| Thread.sleep(20000); | ||
| } | ||
|
|
||
| public void test_bedrock_embedding_model() throws Exception { | ||
| // Skip test if key is null | ||
| if (tokenNotSet()) { | ||
| return; | ||
| } | ||
| String templates = Files | ||
| .readString( | ||
| Path | ||
| .of( | ||
| RestMLPredictionAction.class | ||
| .getClassLoader() | ||
| .getResource("org/opensearch/ml/rest/templates/BedRockV2ConnectorBodies.json") | ||
| .toURI() | ||
| ) | ||
| ); | ||
| for (String postProcessFunction : POST_PROCESS_FUNCTIONS) { | ||
| String bedrockEmbeddingModelName = "bedrock embedding model: " + postProcessFunction; | ||
| String modelId = registerRemoteModel( | ||
| String | ||
| .format( | ||
| templates, | ||
| GITHUB_CI_AWS_REGION, | ||
| AWS_ACCESS_KEY_ID, | ||
| AWS_SECRET_ACCESS_KEY, | ||
| AWS_SESSION_TOKEN, | ||
| StringUtils.substringAfterLast(postProcessFunction, "."), | ||
| postProcessFunction | ||
| ), | ||
| bedrockEmbeddingModelName, | ||
| true | ||
| ); | ||
| String errorMsg = String.format("failed to test: %s", postProcessFunction); | ||
| TextDocsInputDataSet inputDataSet = TextDocsInputDataSet.builder().docs(List.of("hello", "world")).build(); | ||
| MLInput mlInput = MLInput.builder().inputDataset(inputDataSet).algorithm(FunctionName.TEXT_EMBEDDING).build(); | ||
| Map inferenceResult = predictTextEmbeddingModel(modelId, mlInput); | ||
| assertTrue(errorMsg, inferenceResult.containsKey("inference_results")); | ||
| List output = (List) inferenceResult.get("inference_results"); | ||
| assertEquals(errorMsg, 2, output.size()); | ||
| assertTrue(errorMsg, output.get(0) instanceof Map); | ||
| assertTrue(errorMsg, output.get(1) instanceof Map); | ||
| validateOutput(errorMsg, (Map) output.get(0), DATA_TYPE.get(postProcessFunction)); | ||
| validateOutput(errorMsg, (Map) output.get(1), DATA_TYPE.get(postProcessFunction)); | ||
| } | ||
| } | ||
|
|
||
| private void validateOutput(String errorMsg, Map<String, Object> output, String dataType) { | ||
| assertTrue(errorMsg, output.containsKey("output")); | ||
| assertTrue(errorMsg, output.get("output") instanceof List); | ||
| List outputList = (List) output.get("output"); | ||
| assertEquals(errorMsg, 1, outputList.size()); | ||
| assertTrue(errorMsg, outputList.get(0) instanceof Map); | ||
| assertTrue(errorMsg, ((Map<?, ?>) outputList.get(0)).get("data") instanceof List); | ||
| assertEquals(errorMsg, ((Map<?, ?>) outputList.get(0)).get("data_type"), dataType); | ||
| } | ||
|
|
||
| private boolean tokenNotSet() { | ||
| if (AWS_ACCESS_KEY_ID == null || AWS_SECRET_ACCESS_KEY == null || AWS_SESSION_TOKEN == null) { | ||
| log.info("#### The AWS credentials are not set. Skipping test. ####"); | ||
| return true; | ||
| } | ||
| return false; | ||
| } | ||
| } |
76 changes: 76 additions & 0 deletions
76
plugin/src/test/java/org/opensearch/ml/rest/RestCohereInferenceIT.java
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,76 @@ | ||
| package org.opensearch.ml.rest; | ||
|
|
||
| import org.apache.commons.lang3.StringUtils; | ||
| import org.junit.Before; | ||
| import org.opensearch.ml.common.FunctionName; | ||
| import org.opensearch.ml.common.dataset.TextDocsInputDataSet; | ||
| import org.opensearch.ml.common.input.MLInput; | ||
|
|
||
| import java.io.IOException; | ||
| import java.net.URISyntaxException; | ||
| import java.nio.file.Files; | ||
| import java.nio.file.Path; | ||
| import java.util.List; | ||
| import java.util.Map; | ||
| import java.util.Optional; | ||
|
|
||
| public class RestCohereInferenceIT extends MLCommonsRestTestCase { | ||
| private final String COHERE_KEY = Optional.ofNullable(System.getenv("COHERE_KEY")).orElse("UzRF34a6gj0OKkvHOO6FZxLItv8CNpK5dFdCaUDW"); | ||
| private final Map<String, String> DATA_TYPE = Map.of( | ||
| "connector.post_process.cohere_v2.embedding.float", "FLOAT32", | ||
| "connector.post_process.cohere_v2.embedding.int8", "INT8", | ||
| "connector.post_process.cohere_v2.embedding.uint8", "UINT8", | ||
| "connector.post_process.cohere_v2.embedding.binary", "BINARY", | ||
| "connector.post_process.cohere_v2.embedding.ubinary", "UBINARY" | ||
| ); | ||
| private final List<String> POST_PROCESS_FUNCTIONS = List.of( | ||
| "connector.post_process.cohere_v2.embedding.float", | ||
| "connector.post_process.cohere_v2.embedding.int8", | ||
| "connector.post_process.cohere_v2.embedding.uint8", | ||
| "connector.post_process.cohere_v2.embedding.binary", | ||
| "connector.post_process.cohere_v2.embedding.ubinary"); | ||
|
|
||
| @Before | ||
| public void setup() throws IOException { | ||
| updateClusterSettings("plugins.ml_commons.trusted_connector_endpoints_regex", List.of("^.*$")); | ||
| } | ||
|
|
||
|
|
||
| public void test_cohereInference_withDifferent_postProcessFunction() throws URISyntaxException, IOException, InterruptedException { | ||
| String templates = Files | ||
| .readString( | ||
| Path | ||
| .of( | ||
| RestMLPredictionAction.class | ||
| .getClassLoader() | ||
| .getResource("org/opensearch/ml/rest/templates/CohereConnectorBodies.json") | ||
| .toURI() | ||
| ) | ||
| ); | ||
| for (String postProcessFunction : POST_PROCESS_FUNCTIONS) { | ||
| String connectorRequestBody = String.format(templates, COHERE_KEY, StringUtils.substringAfterLast(postProcessFunction, "."), postProcessFunction); | ||
| String testCaseName = postProcessFunction + "_test"; | ||
| String modelId = registerRemoteModel(connectorRequestBody, testCaseName, true); | ||
| String errorMsg = String.format("failed to run test with test name: %s", testCaseName); | ||
| TextDocsInputDataSet inputDataSet = TextDocsInputDataSet.builder().docs(List.of("hello", "world")).build(); | ||
| MLInput mlInput = MLInput.builder().inputDataset(inputDataSet).algorithm(FunctionName.TEXT_EMBEDDING).build(); | ||
| Map inferenceResult = predictTextEmbeddingModel(modelId, mlInput); | ||
| assertTrue(errorMsg, inferenceResult.containsKey("inference_results")); | ||
| List output = (List) inferenceResult.get("inference_results"); | ||
| assertEquals(errorMsg, 1, output.size()); | ||
| assertTrue(errorMsg, output.get(0) instanceof Map); | ||
| validateOutput(errorMsg, (Map) output.get(0), DATA_TYPE.get(postProcessFunction)); | ||
| } | ||
| } | ||
|
|
||
| private void validateOutput(String errorMsg, Map<String, Object> output, String dataType) { | ||
| assertTrue(errorMsg, output.containsKey("output")); | ||
| assertTrue(errorMsg, output.get("output") instanceof List); | ||
| List outputList = (List) output.get("output"); | ||
| assertEquals(errorMsg, 2, outputList.size()); | ||
| assertTrue(errorMsg, outputList.get(0) instanceof Map); | ||
| assertTrue(errorMsg, ((Map<?, ?>) outputList.get(0)).get("data") instanceof List); | ||
| assertTrue(errorMsg, ((Map<?, ?>) outputList.get(0)).get("data_type").equals(dataType)); | ||
| } | ||
|
|
||
| } |
30 changes: 30 additions & 0 deletions
30
plugin/src/test/resources/org/opensearch/ml/rest/templates/BedRockV2ConnectorBodies.json
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,30 @@ | ||
| { | ||
| "name": "Amazon Bedrock Connector: embedding", | ||
| "description": "The connector to bedrock Titan embedding model", | ||
| "version": 1, | ||
| "protocol": "aws_sigv4", | ||
| "parameters": { | ||
| "region": "%s", | ||
| "service_name": "bedrock", | ||
| "model_name": "amazon.titan-embed-text-v2:0" | ||
| }, | ||
| "credential": { | ||
| "access_key": "%s", | ||
| "secret_key": "%s", | ||
| "session_token": "%s" | ||
| }, | ||
| "actions": [ | ||
| { | ||
| "action_type": "predict", | ||
| "method": "POST", | ||
| "url": "https://bedrock-runtime.${parameters.region}.amazonaws.com/model/${parameters.model_name}/invoke", | ||
| "headers": { | ||
| "content-type": "application/json", | ||
| "x-amz-content-sha256": "required" | ||
| }, | ||
| "request_body": "{ \"inputText\": \"${parameters.inputText}\", \"embeddingTypes\": [\"%s\"] }", | ||
| "pre_process_function": "connector.pre_process.bedrock.embedding", | ||
| "post_process_function": "%s" | ||
| } | ||
| ] | ||
| } |
26 changes: 26 additions & 0 deletions
26
plugin/src/test/resources/org/opensearch/ml/rest/templates/CohereConnectorBodies.json
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,26 @@ | ||
| { | ||
| "name": "Cohere Connector: embedding", | ||
| "description": "The connector to cohere embedding model", | ||
| "version": 1, | ||
| "protocol": "http", | ||
| "parameters": { | ||
| "model_name": "embed-english-v3.0" | ||
| }, | ||
| "credential": { | ||
| "cohere_key": "%s" | ||
| }, | ||
| "actions": [ | ||
| { | ||
| "action_type": "predict", | ||
| "method": "POST", | ||
| "url": "https://api.cohere.com/v2/embed", | ||
| "headers": { | ||
| "content-type": "application/json", | ||
| "Authorization": "Bearer ${credential.cohere_key}" | ||
| }, | ||
| "request_body": "{ \"texts\": ${parameters.texts}, \"truncate\": \"END\", \"model\": \"${parameters.model_name}\", \"embedding_types\": [\"%s\"], \"input_type\": \"classification\"}", | ||
| "pre_process_function": "connector.pre_process.cohere.embedding", | ||
| "post_process_function": "%s" | ||
| } | ||
| ] | ||
| } |