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Java: Add GeminiTextGenerationService and usage data to chat completi…
…on (#6583) ### Motivation and Context <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, providing the following information: 1. Why is this change required? 2. What problem does it solve? 3. What scenario does it contribute to? 4. If it fixes an open issue, please link to the issue here. --> ### Description Fixes #6580 <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> ### 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 😄
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...icrosoft/semantickernel/aiservices/google/textcompletion/GeminiTextGenerationService.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,142 @@ | ||
| // Copyright (c) Microsoft. All rights reserved. | ||
| package com.microsoft.semantickernel.aiservices.google.textcompletion; | ||
|
|
||
| import com.google.cloud.vertexai.VertexAI; | ||
| import com.google.cloud.vertexai.api.GenerateContentResponse; | ||
| import com.google.cloud.vertexai.api.GenerationConfig; | ||
| import com.google.cloud.vertexai.generativeai.GenerativeModel; | ||
| import com.microsoft.semantickernel.Kernel; | ||
| import com.microsoft.semantickernel.aiservices.google.GeminiService; | ||
| import com.microsoft.semantickernel.aiservices.google.implementation.MonoConverter; | ||
| import com.microsoft.semantickernel.exceptions.AIException; | ||
| import com.microsoft.semantickernel.exceptions.SKCheckedException; | ||
| import com.microsoft.semantickernel.exceptions.SKException; | ||
| import com.microsoft.semantickernel.orchestration.FunctionResultMetadata; | ||
| import com.microsoft.semantickernel.orchestration.PromptExecutionSettings; | ||
| import com.microsoft.semantickernel.services.gemini.GeminiServiceBuilder; | ||
| import com.microsoft.semantickernel.services.textcompletion.StreamingTextContent; | ||
| import com.microsoft.semantickernel.services.textcompletion.TextContent; | ||
| import com.microsoft.semantickernel.services.textcompletion.TextGenerationService; | ||
| import reactor.core.publisher.Flux; | ||
| import reactor.core.publisher.Mono; | ||
|
|
||
| import org.slf4j.Logger; | ||
| import org.slf4j.LoggerFactory; | ||
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|
||
| import javax.annotation.Nullable; | ||
| import java.io.IOException; | ||
| import java.time.OffsetDateTime; | ||
| import java.util.ArrayList; | ||
| import java.util.List; | ||
| import java.util.UUID; | ||
|
|
||
| public class GeminiTextGenerationService extends GeminiService implements TextGenerationService { | ||
| private static final Logger LOGGER = LoggerFactory.getLogger(GeminiTextGenerationService.class); | ||
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|
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| public GeminiTextGenerationService(VertexAI client, String modelId) { | ||
| super(client, modelId); | ||
| } | ||
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| public static Builder builder() { | ||
| return new Builder(); | ||
| } | ||
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| @Override | ||
| public Mono<List<TextContent>> getTextContentsAsync( | ||
| String prompt, | ||
| @Nullable PromptExecutionSettings executionSettings, | ||
| @Nullable Kernel kernel) { | ||
| return this.internalGetTextAsync(prompt, executionSettings); | ||
| } | ||
|
|
||
| @Override | ||
| public Flux<StreamingTextContent> getStreamingTextContentsAsync( | ||
| String prompt, | ||
| @Nullable PromptExecutionSettings executionSettings, | ||
| @Nullable Kernel kernel) { | ||
| return this | ||
| .internalGetTextAsync(prompt, executionSettings) | ||
| .flatMapMany(it -> Flux.fromStream(it.stream()) | ||
| .map(StreamingTextContent::new)); | ||
| } | ||
|
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| private Mono<List<TextContent>> internalGetTextAsync(String prompt, | ||
| @Nullable PromptExecutionSettings executionSettings) { | ||
|
|
||
| try { | ||
| GenerativeModel model = getGenerativeModel(executionSettings); | ||
| return MonoConverter.fromApiFuture(model.generateContentAsync(prompt)) | ||
| .doOnError(e -> LOGGER.error("Error generating text", e)) | ||
| .flatMap(result -> { | ||
| List<TextContent> textContents = new ArrayList<>(); | ||
|
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||
| FunctionResultMetadata<GenerateContentResponse.UsageMetadata> metadata = FunctionResultMetadata | ||
| .build( | ||
| UUID.randomUUID().toString(), | ||
| result.getUsageMetadata(), | ||
| OffsetDateTime.now()); | ||
|
|
||
| result.getCandidatesList().forEach( | ||
| candidate -> { | ||
| candidate.getContent().getPartsList().forEach(part -> { | ||
| if (!part.getText().isEmpty()) { | ||
| textContents.add( | ||
| new TextContent(part.getText(), getModelId(), metadata)); | ||
| } | ||
| }); | ||
| }); | ||
|
|
||
| return Mono.just(textContents); | ||
| }); | ||
| } catch (SKCheckedException | IOException e) { | ||
| return Mono.error(new SKException("Error generating text", e)); | ||
| } | ||
| } | ||
|
|
||
| private GenerativeModel getGenerativeModel( | ||
| @Nullable PromptExecutionSettings executionSettings) throws SKCheckedException { | ||
| GenerativeModel.Builder modelBuilder = new GenerativeModel.Builder() | ||
| .setModelName(getModelId()) | ||
| .setVertexAi(getClient()); | ||
|
|
||
| if (executionSettings != null) { | ||
| if (executionSettings.getResultsPerPrompt() < 1 | ||
| || executionSettings.getResultsPerPrompt() > MAX_RESULTS_PER_PROMPT) { | ||
| throw SKCheckedException.build("Error building generative model.", | ||
| new AIException(AIException.ErrorCodes.INVALID_REQUEST, | ||
| String.format( | ||
| "Results per prompt must be in range between 1 and %d, inclusive.", | ||
| MAX_RESULTS_PER_PROMPT))); | ||
| } | ||
|
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| GenerationConfig config = GenerationConfig.newBuilder() | ||
| .setMaxOutputTokens(executionSettings.getMaxTokens()) | ||
| .setTemperature((float) executionSettings.getTemperature()) | ||
| .setTopP((float) executionSettings.getTopP()) | ||
| .setCandidateCount(executionSettings.getResultsPerPrompt()) | ||
| .build(); | ||
|
|
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| modelBuilder.setGenerationConfig(config); | ||
| } | ||
|
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| return modelBuilder.build(); | ||
| } | ||
|
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| public static class Builder extends | ||
| GeminiServiceBuilder<GeminiTextGenerationService, GeminiTextGenerationService.Builder> { | ||
| @Override | ||
| public GeminiTextGenerationService build() { | ||
| if (this.client == null) { | ||
| throw new AIException(AIException.ErrorCodes.INVALID_REQUEST, | ||
| "VertexAI client must be provided"); | ||
| } | ||
|
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| if (this.modelId == null || modelId.isEmpty()) { | ||
| throw new AIException(AIException.ErrorCodes.INVALID_REQUEST, | ||
| "Gemini model id must be provided"); | ||
| } | ||
|
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||
| return new GeminiTextGenerationService(client, modelId); | ||
| } | ||
| } | ||
| } |
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