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Java: Allow Semantic Kernel to obtain credentials via Managed identity and azure cli. Fix some tests (#3298)

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### Motivation and Context

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### Description

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### Contribution Checklist

<!-- Before submitting this PR, please make sure: -->

- [ ] The code builds clean without any errors or warnings
- [ ] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [ ] All unit tests pass, and I have added new tests where possible
- [ ] I didn't break anyone 😄
This commit is contained in:
John Oliver
2023-11-07 12:00:42 +00:00
committed by GitHub
parent a69702917d
commit 3f894eada1
17 changed files with 355 additions and 152 deletions
Download Patch File Download Diff File Expand all files Collapse all files
java/connectors/semantickernel-connectors-ai-openai/pom.xml
+5
View File
@@ -20,6 +20,11 @@
<groupId>com.microsoft.semantic-kernel</groupId>
<artifactId>semantickernel-api</artifactId>
</dependency>
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-identity</artifactId>
<optional>true</optional>
</dependency>
<dependency>
<groupId>jakarta.inject</groupId>
<artifactId>jakarta.inject-api</artifactId>
java/connectors/semantickernel-connectors-memory-azurecognitivesearch/pom.xml
+12 -1
View File
@@ -1,6 +1,7 @@
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
@@ -28,6 +29,16 @@
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-search-documents</artifactId>
<exclusions>
<!--
TODO: Remove pending a fix for:
https://github.com/Azure/azure-sdk-for-java/issues/36054
-->
<exclusion>
<groupId>com.azure</groupId>
<artifactId>azure-core-serializer-json-jackson</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.mockito</groupId>
java/extensions/semantickernel-settings-loader/pom.xml
+5
View File
@@ -28,5 +28,10 @@
<groupId>org.junit.jupiter</groupId>
<artifactId>junit-jupiter</artifactId>
</dependency>
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-identity</artifactId>
<optional>true</optional>
</dependency>
</dependencies>
</project>
java/extensions/semantickernel-settings-loader/src/main/java/com/microsoft/semantickernel/connectors/ai/openai/util/AzureCredentialType.java
+97
View File
@@ -0,0 +1,97 @@
// Copyright (c) Microsoft. All rights reserved.
package com.microsoft.semantickernel.connectors.ai.openai.util;
import com.azure.core.credential.TokenCredential;
import com.microsoft.semantickernel.exceptions.ConfigurationException;
import java.io.File;
import java.util.List;
import java.util.Map;
import javax.annotation.Nullable;
import org.slf4j.Logger;
/** Defines the type of azure credential used for authenticating to this resource */
public enum AzureCredentialType {
KEY {
@Nullable
@Override
public TokenCredential getTokenCredential() {
return null;
}
},
MANAGED_IDENTITY {
@Nullable
@Override
public TokenCredential getTokenCredential() {
if (classIsPresent("com.azure.identity.ManagedIdentityCredentialBuilder")) {
return new com.azure.identity.ManagedIdentityCredentialBuilder().build();
}
return null;
}
},
AZURE_CLI {
@Nullable
@Override
public TokenCredential getTokenCredential() {
if (classIsPresent("com.azure.identity.AzureCliCredentialBuilder")) {
return new com.azure.identity.AzureCliCredentialBuilder().build();
}
return null;
}
};
private static final Logger LOGGER =
org.slf4j.LoggerFactory.getLogger(AzureCredentialType.class);
/**
* Create a TokenCredential instance.
*
* @return TokenCredential instance or null if not found
*/
@Nullable
public abstract TokenCredential getTokenCredential();
/**
* Create a TokenCredential instance, uses the default settings locations (see {@link
* SettingsMap} for details).
*
* <p>Set the 'client.azureopenai.credentialtype' environment variable within settings to
* determine the token type. {@link AzureCredentialType}
*
* @return TokenCredential instance or null if not found
*/
@Nullable
public static TokenCredential getCredential() throws ConfigurationException {
return getCredential((List<File>) null);
}
/**
* Create a TokenCredential instance, uses the provided settings locations (see {@link
* SettingsMap} for details).
*
* <p>Set the 'client.azureopenai.credentialtype' environment variable within settings to
* determine the token type. {@link AzureCredentialType}
*
* @return TokenCredential instance or null if not found
*/
@Nullable
public static TokenCredential getCredential(@Nullable List<File> propertyFileLocations)
throws ConfigurationException {
Map<String, String> settings = OpenAIClientProvider.getSettings(propertyFileLocations);
return new AzureOpenAISettings(settings)
.getAzureOpenAiCredentialsType()
.getTokenCredential();
}
private static boolean classIsPresent(String className) {
try {
Class.forName(className, false, Thread.currentThread().getContextClassLoader());
return true;
} catch (ClassNotFoundException e) {
LOGGER.warn(
"Requested Managed Identity or Azure CLI authentication, however the"
+ " azure-identity library is not available on the classpath");
return false;
}
}
}
java/extensions/semantickernel-settings-loader/src/main/java/com/microsoft/semantickernel/connectors/ai/openai/util/AzureOpenAISettings.java
+13
View File
@@ -7,15 +7,18 @@ import javax.annotation.Nullable;
/** Settings for Azure OpenAI client */
public class AzureOpenAISettings extends AbstractOpenAIClientSettings {
private static final String DEFAULT_SETTINGS_PREFIX = "client.azureopenai";
private static final String AZURE_OPEN_AI_ENDPOINT_SUFFIX = "endpoint";
private static final String AZURE_OPEN_AI_DEPLOYMENT_NAME_SUFFIX = "deploymentname";
private static final String AZURE_OPEN_AI_CREDENTIALS_TYPE = "credentialtype";
@Nullable private final String key;
@Nullable private final String endpoint;
@Nullable private final String deploymentName;
@Nullable private final AzureCredentialType credentialType;
private final String settingsPrefix;
public AzureOpenAISettings(Map<String, String> settings) {
@@ -27,6 +30,12 @@ public class AzureOpenAISettings extends AbstractOpenAIClientSettings {
key = settings.get(settingsPrefix + "." + KEY_SUFFIX);
endpoint = settings.get(settingsPrefix + "." + AZURE_OPEN_AI_ENDPOINT_SUFFIX);
deploymentName = settings.get(settingsPrefix + "." + AZURE_OPEN_AI_DEPLOYMENT_NAME_SUFFIX);
String credType =
settings.getOrDefault(settingsPrefix + "." + AZURE_OPEN_AI_CREDENTIALS_TYPE, "key")
.toUpperCase();
credentialType = AzureCredentialType.valueOf(credType);
}
/**
@@ -65,6 +74,10 @@ public class AzureOpenAISettings extends AbstractOpenAIClientSettings {
return key;
}
public AzureCredentialType getAzureOpenAiCredentialsType() {
return credentialType;
}
@Override
public boolean assertIsValid() throws ConfigurationException {
if (key == null) {
java/extensions/semantickernel-settings-loader/src/main/java/com/microsoft/semantickernel/connectors/ai/openai/util/OpenAIClientProvider.java
+21 -12
View File
@@ -7,6 +7,7 @@ import com.azure.ai.openai.OpenAIAsyncClient;
import com.azure.ai.openai.OpenAIClientBuilder;
import com.azure.core.credential.AzureKeyCredential;
import com.azure.core.credential.KeyCredential;
import com.azure.core.credential.TokenCredential;
import com.azure.core.util.ClientOptions;
import com.microsoft.semantickernel.SemanticKernelHttpSettings;
import com.microsoft.semantickernel.exceptions.ConfigurationException;
@@ -79,7 +80,7 @@ public class OpenAIClientProvider {
return new OpenAIClientProvider(settings, clientType);
}
private static Map<String, String> getSettings(@Nullable List<File> propertyFileLocations)
static Map<String, String> getSettings(@Nullable List<File> propertyFileLocations)
throws ConfigurationException {
Map<String, String> settings;
@@ -235,19 +236,27 @@ public class OpenAIClientProvider {
private OpenAIAsyncClient buildAzureOpenAIClient() throws ConfigurationException {
AzureOpenAISettings settings = new AzureOpenAISettings(configuredSettings);
try {
settings.assertIsValid();
} catch (ConfigurationException e) {
LOGGER.warn("Could not instantiate Azure OpenAI client");
LOGGER.warn(e.getMessage());
throw e;
OpenAIClientBuilder builder = new OpenAIClientBuilder().endpoint(settings.getEndpoint());
TokenCredential tokenCredential = null;
if (settings.getAzureOpenAiCredentialsType() != null) {
tokenCredential = settings.getAzureOpenAiCredentialsType().getTokenCredential();
}
OpenAIClientBuilder builder =
new OpenAIClientBuilder()
.endpoint(settings.getEndpoint())
.clientOptions(clientOptions)
.credential(new AzureKeyCredential(settings.getKey()));
if (tokenCredential != null) {
builder.credential(tokenCredential);
} else {
try {
settings.assertIsValid();
} catch (ConfigurationException e) {
LOGGER.warn("Could not instantiate Azure OpenAI client");
LOGGER.warn(e.getMessage());
throw e;
}
builder.credential(new AzureKeyCredential(settings.getKey()));
}
return builder.buildAsyncClient();
}
java/samples/sample-code/README.md
+19 -4
View File
@@ -34,10 +34,14 @@ They can then be run by:
# Configuration
You can define the provider of Open AI by setting the `OPENAI_CLIENT_TYPE`
By default, the samples will use the Open AI client, but you can also use the Azure Open AI client.
## Open AI client type
You can define the provider of Open AI (openai.com or Azure), this can be done by setting the `OPENAI_CLIENT_TYPE`
property or environment variable to either [`OPENAI`](https://openai.com/api/)
or [`AZURE_OPEN_AI`](https://learn.microsoft.com/azure/cognitive-services/openai/).
By default, the samples will use the Open AI client.
or [`AZURE_OPEN_AI`](https://learn.microsoft.com/azure/cognitive-services/openai/). By default, the samples will use the
Open AI client.
```shell
OPENAI_CLIENT_TYPE=OPEN_AI ../../mvnw exec:java -Dsample=Example04_CombineLLMPromptsAndNativeCode
@@ -55,7 +59,6 @@ The samples search for the client settings in the following order:
1. Properties file at `java/samples/conf.properties`.
1. Properties file at `~/.sk/conf.properties`.
## Properties File
You can set the location of a properties file, by setting the `CONF_PROPERTIES` property or environment variable, ie:
@@ -123,3 +126,15 @@ OPEN_AI_KEY="my-key" \
OPEN_AI_ORGANIZATION_ID="organisation id" \
../../mvnw clean package exec:java -Dsample=Example04_CombineLLMPromptsAndNativeCode
```
## Managed Identity and Azure CLI Credentials (Azure only)
The `credentialtype` setting (i.e `client.openai.credentialtype`):
- `managed_identity`: will attempt to obtain credentials via Azure's managed identity.
- `azure_cli`: will attempt to obtain credentials via Azure's CLI, to use this you must have logged in to the az client
for instance by running `az login`.
To use either of these settings, the `azure-identity` dependency must be available to the application. Additionally, you
must have the "Cognitive Services User" role assigned to your identity.
java/samples/sample-code/pom.xml
+4
View File
@@ -76,6 +76,10 @@
<groupId>com.microsoft.semantic-kernel</groupId>
<artifactId>semantickernel-settings-loader</artifactId>
</dependency>
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-identity</artifactId>
</dependency>
</dependencies>
<build>
java/samples/sample-code/src/main/java/com/microsoft/semantickernel/samples/syntaxexamples/Example04_CombineLLMPromptsAndNativeCode.java
+3 -7
View File
@@ -34,24 +34,20 @@ public class Example04_CombineLLMPromptsAndNativeCode {
public static void main(String[] args) throws ConfigurationException {
OpenAIAsyncClient client = SamplesConfig.getClient();
TextCompletion textCompletion = SKBuilders.textCompletion()
.withModelId("text-davinci-003")
TextCompletion textCompletion = SKBuilders.chatCompletion()
.withModelId("gpt-35-turbo-2")
.withOpenAIClient(client)
.build();
Kernel kernel = SKBuilders.kernel().withDefaultAIService(textCompletion).build();
Kernel kernel = SKBuilders.kernel().withDefaultAIService(textCompletion).build();
kernel.importSkill(new SearchEngineSkill(), null);
kernel.importSkillFromDirectory("SummarizeSkill", SampleSkillsUtil.detectSkillDirLocation(),
"SummarizeSkill");
// Run
String ask = "What's the tallest building in South America?";
Mono<SKContext> result =
kernel.runAsync(ask, kernel.getSkills().getFunction("Search", null));
result =
kernel.runAsync(
ask,
kernel.getSkills().getFunction("Search", null),
java/samples/sample-code/src/main/java/com/microsoft/semantickernel/samples/syntaxexamples/Example12_SequentialPlanner.java
+3 -3
View File
@@ -183,16 +183,16 @@ public class Example12_SequentialPlanner {
private static Kernel initializeKernel() throws ConfigurationException {
OpenAIAsyncClient client = SamplesConfig.getClient();
var kernel = SKBuilders.kernel()
.withDefaultAIService(SKBuilders.chatCompletion()
.withDefaultAIService(SKBuilders.textCompletion()
.withOpenAIClient(client)
.withModelId("gpt-35-turbo")
.withModelId("gpt-35-turbo-instruct")
.build())
.withMemory(SKBuilders
.semanticTextMemory()
.withEmbeddingGenerator(
SKBuilders.textEmbeddingGeneration()
.withOpenAIClient(client)
.withModelId("gpt-35-turbo")
.withModelId("text-embedding-ada-002")
.build()
)
.withStorage(new VolatileMemoryStore())
java/samples/sample-code/src/main/java/com/microsoft/semantickernel/samples/syntaxexamples/Example14_SemanticMemory.java
+146 -108
View File
@@ -1,17 +1,20 @@
// Copyright (c) Microsoft. All rights reserved.
package com.microsoft.semantickernel.samples.syntaxexamples;
import com.azure.core.credential.TokenCredential;
import com.microsoft.semantickernel.Kernel;
import com.microsoft.semantickernel.SKBuilders;
import com.microsoft.semantickernel.SamplesConfig;
import com.microsoft.semantickernel.connectors.ai.openai.util.AzureCredentialType;
import com.microsoft.semantickernel.connectors.memory.azurecognitivesearch.AzureCognitiveSearchMemoryStore;
import com.microsoft.semantickernel.exceptions.ConfigurationException;
import com.microsoft.semantickernel.memory.VolatileMemoryStore;
import reactor.core.publisher.Flux;
import reactor.core.publisher.Mono;
import com.microsoft.semantickernel.settings.SettingsMap;
import java.util.Arrays;
import java.util.Map;
import java.util.stream.Collectors;
import reactor.core.publisher.Flux;
import reactor.core.publisher.Mono;
/**
@@ -32,75 +35,102 @@ import java.util.stream.Collectors;
* README</a> for configuring your environment to run the examples.
*/
public class Example14_SemanticMemory {
private static final String MEMORY_COLLECTION_NAME = "SKGitHub";
public static void main(String[] args) throws Exception {
System.out.println("==============================================================");
System.out.println("======== Semantic Memory using Azure Cognitive Search ========");
System.out.println("==============================================================");
private static final String MEMORY_COLLECTION_NAME = "SKGitHub";
var openAIAsyncClient = SamplesConfig.getClient();
public static void main(String[] args) throws Exception {
System.out.println("==============================================================");
System.out.println("======== Semantic Memory using Azure Cognitive Search ========");
System.out.println("==============================================================");
/* This example leverages Azure Cognitive Search to provide SK with Semantic Memory.
*
* Azure Cognitive Search automatically indexes your data semantically, so you don't
* need to worry about embedding generation.
*/
var kernelWithACS = SKBuilders.kernel()
.withMemoryStorage(
new AzureCognitiveSearchMemoryStore(System.getenv("ACS_ENDPOINT"), System.getenv("ACS_API_KEY")))
.withDefaultAIService(SKBuilders.textEmbeddingGeneration()
.withOpenAIClient(openAIAsyncClient)
.withModelId("text-embedding-ada-002")
.build())
.build();
var openAIAsyncClient = SamplesConfig.getClient();
runExampleAsync(kernelWithACS).block();
AzureCognitiveSearchMemoryStore memoryStore = buildAzureCognitiveSearchMemoryStore();
/* This example leverages Azure Cognitive Search to provide SK with Semantic Memory.
*
* Azure Cognitive Search automatically indexes your data semantically, so you don't
* need to worry about embedding generation.
*/
var kernelWithACS = SKBuilders.kernel()
.withMemoryStorage(memoryStore)
.withDefaultAIService(SKBuilders.textEmbeddingGeneration()
.withOpenAIClient(openAIAsyncClient)
.withModelId("text-embedding-ada-002")
.build())
.build();
System.out.println("====================================================");
System.out.println("======== Semantic Memory (volatile, in RAM) ========");
System.out.println("====================================================");
runExampleAsync(kernelWithACS).block();
/* You can build your own semantic memory combining an Embedding Generator
* with a Memory storage that supports search by similarity (ie semantic search).
*
* In this example we use a volatile memory, a local simulation of a vector DB.
*
* You can replace VolatileMemoryStore with Qdrant (see QdrantMemoryStore connector)
* or implement your connectors for Pinecone, Vespa, Postgres + pgvector, SQLite VSS, etc.
*/
System.out.println("====================================================");
System.out.println("======== Semantic Memory (volatile, in RAM) ========");
System.out.println("====================================================");
var kernelWithCustomDb = SKBuilders.kernel()
.withDefaultAIService(SKBuilders.textEmbeddingGeneration()
.withOpenAIClient(openAIAsyncClient)
.withModelId("text-embedding-ada-002")
.build())
.withMemoryStorage(new VolatileMemoryStore.Builder().build())
.build();
/* You can build your own semantic memory combining an Embedding Generator
* with a Memory storage that supports search by similarity (ie semantic search).
*
* In this example we use a volatile memory, a local simulation of a vector DB.
*
* You can replace VolatileMemoryStore with Qdrant (see QdrantMemoryStore connector)
* or implement your connectors for Pinecone, Vespa, Postgres + pgvector, SQLite VSS, etc.
*/
runExampleAsync(kernelWithCustomDb).block();
var kernelWithCustomDb = SKBuilders.kernel()
.withDefaultAIService(SKBuilders.textEmbeddingGeneration()
.withOpenAIClient(openAIAsyncClient)
.withModelId("text-embedding-ada-002")
.build())
.withMemoryStorage(new VolatileMemoryStore.Builder().build())
.build();
runExampleAsync(kernelWithCustomDb).block();
}
private static AzureCognitiveSearchMemoryStore buildAzureCognitiveSearchMemoryStore()
throws ConfigurationException {
Map<String, String> settings = SettingsMap.getDefault();
AzureCognitiveSearchMemoryStore memoryStore;
if (settings.get("cognativesearch.token") == null) {
// Attempt to obtain token via
TokenCredential token = AzureCredentialType.getCredential();
if (token == null) {
throw new IllegalStateException(
"Unable to obtain token credentials. Please provide a key for Azure Cognitive Search, or log in to az.");
}
memoryStore = new AzureCognitiveSearchMemoryStore(
settings.get("cognativesearch.endpoint"),
token
);
} else {
memoryStore = new AzureCognitiveSearchMemoryStore(
settings.get("cognativesearch.endpoint"),
settings.get("cognativesearch.token")
);
}
return memoryStore;
}
public static Mono<Void> runExampleAsync(Kernel kernel) {
return storeMemoryAsync(kernel)
.then(searchMemoryAsync(kernel, "How do I get started?"))
public static Mono<Void> runExampleAsync(Kernel kernel) {
return storeMemoryAsync(kernel)
.then(searchMemoryAsync(kernel, "How do I get started?"))
/*
Output:
/*
Output:
Query: How do I get started?
Query: How do I get started?
Result 1:
URL: : https://github.com/microsoft/semantic-kernel/blob/main/README.md
Title : README: Installation, getting started, and how to contribute
Result 1:
URL: : https://github.com/microsoft/semantic-kernel/blob/main/README.md
Title : README: Installation, getting started, and how to contribute
Result 2:
URL: : https://github.com/microsoft/semantic-kernel/blob/main/samples/dotnet-jupyter-notebooks/00-getting-started.ipynb
Title : Jupyter notebook describing how to get started with the Semantic Kernel
Result 2:
URL: : https://github.com/microsoft/semantic-kernel/blob/main/samples/dotnet-jupyter-notebooks/00-getting-started.ipynb
Title : Jupyter notebook describing how to get started with the Semantic Kernel
*/
*/
.then(searchMemoryAsync(kernel, "Can I build a chat with SK?"));
.then(searchMemoryAsync(kernel, "Can I build a chat with SK?"));
/*
Output:
@@ -116,60 +146,68 @@ public class Example14_SemanticMemory {
Title : README: README associated with a sample chat summary react-based webapp
*/
}
}
private static Mono<Void> searchMemoryAsync(Kernel kernel, String query) {
return kernel.getMemory().searchAsync(MEMORY_COLLECTION_NAME, query, 2, 0.5f, false)
.mapNotNull(memories -> {
System.out.println("\nQuery: " + query + "\n");
for (int n = 0; n < memories.size(); n++) {
var memory = memories.get(n);
System.out.println("Result " + (n + 1) + ":");
System.out.println(" URL: : " + memory.getMetadata().getId());
System.out.println(" Title : " + memory.getMetadata().getDescription());
System.out.println();
}
System.out.println("----------------------");
return null;
});
}
private static Mono<Void> searchMemoryAsync(Kernel kernel, String query) {
return kernel.getMemory().searchAsync(MEMORY_COLLECTION_NAME, query, 2, 0.5f, false)
.mapNotNull(memories -> {
System.out.println("\nQuery: " + query + "\n");
for (int n = 0; n < memories.size(); n++) {
var memory = memories.get(n);
System.out.println("Result " + (n + 1) + ":");
System.out.println(" URL: : " + memory.getMetadata().getId());
System.out.println(" Title : " + memory.getMetadata().getDescription());
System.out.println();
}
System.out.println("----------------------");
return null;
});
}
private static Mono<Void> storeMemoryAsync(Kernel kernel) {
/* Store some data in the semantic memory.
*
* When using Azure Cognitive Search the data is automatically indexed on write.
*
* When using the combination of VolatileStore and Embedding generation, SK takes
* care of creating and storing the index
*/
private static Mono<Void> storeMemoryAsync(Kernel kernel) {
/* Store some data in the semantic memory.
*
* When using Azure Cognitive Search the data is automatically indexed on write.
*
* When using the combination of VolatileStore and Embedding generation, SK takes
* care of creating and storing the index
*/
return Flux.fromIterable(sampleData().entrySet())
.doFirst(() -> System.out.println("\nAdding some GitHub file URLs and their descriptions to the semantic memory."))
.map(entry -> {
System.out.println("Save '" + entry.getKey() + "' to memory.");
return kernel.getMemory().saveReferenceAsync(
MEMORY_COLLECTION_NAME,
entry.getValue(),
entry.getKey(),
"GitHub",
entry.getValue(),
null);
}
)
.mapNotNull(Mono::block)
.doFinally(signalType -> System.out.println("\n----------------------"))
.then();
}
return Flux.fromIterable(sampleData().entrySet())
.doFirst(() -> System.out.println(
"\nAdding some GitHub file URLs and their descriptions to the semantic memory."))
.map(entry -> {
System.out.println("Save '" + entry.getKey() + "' to memory.");
return kernel.getMemory().saveReferenceAsync(
MEMORY_COLLECTION_NAME,
entry.getValue(),
entry.getKey(),
"GitHub",
entry.getValue(),
null);
}
)
.mapNotNull(Mono::block)
.doFinally(signalType -> System.out.println("\n----------------------"))
.then();
}
private static Map<String, String> sampleData() {
return Arrays.stream(new String[][]{
{"https://github.com/microsoft/semantic-kernel/blob/main/README.md", "README: Installation, getting started, and how to contribute"},
{"https://github.com/microsoft/semantic-kernel/blob/main/samples/notebooks/dotnet/02-running-prompts-from-file.ipynb", "Jupyter notebook describing how to pass prompts from a file to a semantic skill or function"},
{"https://github.com/microsoft/semantic-kernel/blob/main/samples/notebooks/dotnet/00-getting-started.ipynb", "Jupyter notebook describing how to get started with the Semantic Kernel"},
{"https://github.com/microsoft/semantic-kernel/tree/main/samples/skills/ChatSkill/ChatGPT", "Sample demonstrating how to create a chat skill interfacing with ChatGPT"},
{"https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/SemanticKernel/Memory/VolatileMemoryStore.cs", "C# class that defines a volatile embedding store"},
{"https://github.com/microsoft/semantic-kernel/blob/main/samples/dotnet/KernelHttpServer/README.md", "README: How to set up a Semantic Kernel Service API using Azure Function Runtime v4"},
{"https://github.com/microsoft/semantic-kernel/blob/main/samples/apps/chat-summary-webapp-react/README.md", "README: README associated with a sample chat summary react-based webapp"},
}).collect(Collectors.toMap(element -> element[0], element -> element[1]));
}
private static Map<String, String> sampleData() {
return Arrays.stream(new String[][]{
{"https://github.com/microsoft/semantic-kernel/blob/main/README.md",
"README: Installation, getting started, and how to contribute"},
{"https://github.com/microsoft/semantic-kernel/blob/main/samples/notebooks/dotnet/02-running-prompts-from-file.ipynb",
"Jupyter notebook describing how to pass prompts from a file to a semantic skill or function"},
{"https://github.com/microsoft/semantic-kernel/blob/main/samples/notebooks/dotnet/00-getting-started.ipynb",
"Jupyter notebook describing how to get started with the Semantic Kernel"},
{"https://github.com/microsoft/semantic-kernel/tree/main/samples/skills/ChatSkill/ChatGPT",
"Sample demonstrating how to create a chat skill interfacing with ChatGPT"},
{"https://github.com/microsoft/semantic-kernel/blob/main/dotnet/src/SemanticKernel/Memory/VolatileMemoryStore.cs",
"C# class that defines a volatile embedding store"},
{"https://github.com/microsoft/semantic-kernel/blob/main/samples/dotnet/KernelHttpServer/README.md",
"README: How to set up a Semantic Kernel Service API using Azure Function Runtime v4"},
{"https://github.com/microsoft/semantic-kernel/blob/main/samples/apps/chat-summary-webapp-react/README.md",
"README: README associated with a sample chat summary react-based webapp"},
}).collect(Collectors.toMap(element -> element[0], element -> element[1]));
}
}
java/samples/sample-code/src/main/java/com/microsoft/semantickernel/samples/syntaxexamples/Example17_ChatGPT.java
+2 -2
View File
@@ -24,10 +24,10 @@ public class Example17_ChatGPT {
Kernel kernel = SKBuilders.kernel()
.withAIService(
"chat-test",
"gpt-35-turbo",
SKBuilders.chatCompletion()
.withOpenAIClient(client)
.withModelId("chat-test")
.withModelId("gpt-35-turbo")
.build(),
true,
ChatCompletion.class
java/samples/sample-code/src/main/java/com/microsoft/semantickernel/samples/syntaxexamples/Example28_ActionPlanner.java
+1 -1
View File
@@ -25,7 +25,7 @@ public class Example28_ActionPlanner {
var kernel = SKBuilders.kernel()
.withDefaultAIService(SKBuilders.textCompletion()
.withModelId("text-davinci-002")
.withModelId("text-davinci-003")
.withOpenAIClient(client)
.build())
.build();
java/semantickernel-api/src/main/java/com/microsoft/semantickernel/SkillExecutor.java
+2 -1
View File
@@ -75,7 +75,8 @@ public interface SkillExecutor {
* @throws KernelException if it is not possible to correctly load the skill
*/
ReadOnlyFunctionCollection importSkillFromResources(
String pluginDirectory, String skillName, String functionName, @Nullable Class clazz) throws KernelException;
String pluginDirectory, String skillName, String functionName, @Nullable Class clazz)
throws KernelException;
/**
* Imports the native functions annotated on the given object as a skill.
java/semantickernel-api/src/main/java/com/microsoft/semantickernel/extensions/KernelExtensions.java
+15 -12
View File
@@ -97,7 +97,8 @@ public class KernelExtensions {
String pluginName,
String functionName,
@Nullable Class clazz,
PromptTemplateEngine promptTemplateEngine) throws KernelException {
PromptTemplateEngine promptTemplateEngine)
throws KernelException {
PromptTemplateConfig config =
getPromptTemplateConfig(pluginDirectory, pluginName, functionName, clazz);
@@ -150,7 +151,8 @@ public class KernelExtensions {
}
private static PromptTemplateConfig getPromptTemplateConfig(
String pluginDirectory, String pluginName, String functionName, @Nullable Class clazz) throws KernelException {
String pluginDirectory, String pluginName, String functionName, @Nullable Class clazz)
throws KernelException {
String configFileName =
pluginDirectory
+ File.separator
@@ -169,18 +171,19 @@ public class KernelExtensions {
ResourceLocation.CLASSPATH,
ResourceLocation.FILESYSTEM);
return new ObjectMapper().readValue(config, PromptTemplateConfig.class);
return new ObjectMapper().readValue(config, PromptTemplateConfig.class);
} catch (IOException e) {
if (e instanceof JsonMappingException) {
LOGGER.error("Failed to parse config file " + configFileName, e);
if (e instanceof JsonMappingException) {
LOGGER.error("Failed to parse config file " + configFileName, e);
throw new KernelException(
ErrorCodes.FUNCTION_CONFIGURATION_ERROR,
"Failed to parse config file " + configFileName, e);
} else {
LOGGER.debug("No config for " + functionName + " in " + pluginName);
}
return null;
throw new KernelException(
ErrorCodes.FUNCTION_CONFIGURATION_ERROR,
"Failed to parse config file " + configFileName,
e);
} else {
LOGGER.debug("No config for " + functionName + " in " + pluginName);
}
return null;
}
}
}
java/semantickernel-bom/pom.xml
+5
View File
@@ -106,6 +106,11 @@
<artifactId>azure-ai-openai</artifactId>
<version>1.0.0-beta.5</version>
</dependency>
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-identity</artifactId>
<version>1.10.4</version>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
java/semantickernel-core/src/main/java/com/microsoft/semantickernel/DefaultKernel.java
+2 -1
View File
@@ -235,7 +235,8 @@ public class DefaultKernel implements Kernel {
@Override
public ReadOnlyFunctionCollection importSkillFromResources(
String pluginDirectory, String skillName, String functionName, @Nullable Class clazz) throws KernelException {
String pluginDirectory, String skillName, String functionName, @Nullable Class clazz)
throws KernelException {
Map<String, SemanticFunctionConfig> skills =
KernelExtensions.importSemanticSkillFromResourcesDirectory(
pluginDirectory, skillName, functionName, clazz, promptTemplateEngine);