f9b89dc25c
- Fixed logic in moveTaskToNewId function that was incorrectly treating task-to-task moves as subtask creation instead of task replacement - Updated moveTaskToNewId to properly handle replacing existing destination tasks instead of just placeholders - The move command now correctly replaces destination tasks and cleans up properly without leaving duplicates - Task Management: Moved task 93 (Google Vertex AI Provider) to position 88, Moved task 94 (Azure OpenAI Provider) to position 89, Updated task dependencies and regenerated task files, Cleaned up orphaned task files automatically - All important validations remain in place: Prevents moving tasks to themselves, Prevents moving parent tasks to their own subtasks, Prevents circular dependencies - Resolves the issue where moving tasks would leave both source and destination tasks in tasks.json and file system
56 lines
4.5 KiB
Plaintext
56 lines
4.5 KiB
Plaintext
# Task ID: 88
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# Title: Implement Google Vertex AI Provider Integration
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# Status: pending
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# Dependencies: 19, 89
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# Priority: medium
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# Description: Develop a dedicated Google Vertex AI provider in the codebase, enabling users to leverage Vertex AI models with enterprise-grade configuration and authentication.
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# Details:
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1. Create a new provider class in `src/ai-providers/google-vertex.js` that extends the existing BaseAIProvider, following the established structure used by other providers (e.g., google.js, openai.js).
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2. Integrate the Vercel AI SDK's `@ai-sdk/google-vertex` package. Use the default `vertex` provider for standard usage, and allow for custom configuration via `createVertex` for advanced scenarios (e.g., specifying project ID, location, and credentials).
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3. Implement all required interface methods (such as `getClient`, `generateText`, etc.) to ensure compatibility with the provider system. Reference the implementation patterns from other providers for consistency.
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4. Handle Vertex AI-specific configuration, including project ID, location, and Google Cloud authentication. Support both environment-based authentication and explicit service account credentials via `googleAuthOptions`.
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5. Implement robust error handling for Vertex-specific issues, including authentication failures and API errors, leveraging the system-wide error handling patterns.
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6. Update `src/ai-providers/index.js` to export the new provider, and add the 'vertex' entry to the PROVIDERS object in `scripts/modules/ai-services-unified.js`.
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7. Update documentation to provide clear setup instructions for Google Vertex AI, including required environment variables, service account setup, and configuration examples.
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8. Ensure the implementation is modular and maintainable, supporting future expansion for additional Vertex AI features or models.
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# Test Strategy:
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- Write unit tests for the new provider class, covering all interface methods and configuration scenarios (default, custom, error cases).
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- Verify that the provider can successfully authenticate using both environment-based and explicit service account credentials.
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- Test integration with the provider system by selecting 'vertex' as the provider and generating text using supported Vertex AI models (e.g., Gemini).
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- Simulate authentication and API errors to confirm robust error handling and user feedback.
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- Confirm that the provider is correctly exported and available in the PROVIDERS object.
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- Review and validate the updated documentation for accuracy and completeness.
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# Subtasks:
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## 1. Create Google Vertex AI Provider Class [pending]
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### Dependencies: None
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### Description: Develop a new provider class in `src/ai-providers/google-vertex.js` that extends the BaseAIProvider, following the structure of existing providers.
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### Details:
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Ensure the new class is consistent with the architecture of other providers such as google.js and openai.js, and is ready to integrate with the AI SDK.
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## 2. Integrate Vercel AI SDK Google Vertex Package [pending]
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### Dependencies: 88.1
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### Description: Integrate the `@ai-sdk/google-vertex` package, supporting both the default provider and custom configuration via `createVertex`.
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### Details:
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Allow for standard usage with the default `vertex` provider and advanced scenarios using `createVertex` for custom project ID, location, and credentials as per SDK documentation.
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## 3. Implement Provider Interface Methods [pending]
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### Dependencies: 88.2
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### Description: Implement all required interface methods (e.g., `getClient`, `generateText`) to ensure compatibility with the provider system.
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### Details:
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Reference implementation patterns from other providers to maintain consistency and ensure all required methods are present and functional.
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## 4. Handle Vertex AI Configuration and Authentication [pending]
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### Dependencies: 88.3
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### Description: Implement support for Vertex AI-specific configuration, including project ID, location, and authentication via environment variables or explicit service account credentials.
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### Details:
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Support both environment-based authentication and explicit credentials using `googleAuthOptions`, following Google Cloud and Vertex AI setup best practices.
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## 5. Update Exports, Documentation, and Error Handling [pending]
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### Dependencies: 88.4
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### Description: Export the new provider, update the PROVIDERS object, and document setup instructions, including robust error handling for Vertex-specific issues.
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### Details:
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Update `src/ai-providers/index.js` and `scripts/modules/ai-services-unified.js`, and provide clear documentation for setup, configuration, and error handling patterns.
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