dd96f51179
* feat: Add gemini-cli provider integration for Task Master This commit adds comprehensive support for the Gemini CLI provider, enabling users to leverage Google's Gemini models through OAuth authentication via the gemini CLI tool. This integration provides a seamless experience for users who prefer using their existing Google account authentication rather than managing API keys. ## Implementation Details ### Provider Class (`src/ai-providers/gemini-cli.js`) - Created GeminiCliProvider extending BaseAIProvider - Implements dual authentication support: - Primary: OAuth authentication via `gemini auth login` (authType: 'oauth-personal') - Secondary: API key authentication for compatibility (authType: 'api-key') - Uses the npm package `ai-sdk-provider-gemini-cli` (v0.0.3) for SDK integration - Properly handles authentication validation without console output ### Model Configuration (`scripts/modules/supported-models.json`) - Added two Gemini models with accurate specifications: - gemini-2.5-pro: 72% SWE score, 65,536 max output tokens - gemini-2.5-flash: 71% SWE score, 65,536 max output tokens - Both models support main, fallback, and research roles - Configured with zero cost (free tier) ### System Integration - Registered provider in PROVIDERS map (`scripts/modules/ai-services-unified.js`) - Added to OPTIONAL_AUTH_PROVIDERS set for flexible authentication - Added GEMINI_CLI constant to provider constants (`src/constants/providers.js`) - Exported GeminiCliProvider from index (`src/ai-providers/index.js`) ### Command Line Support (`scripts/modules/commands.js`) - Added --gemini-cli flag to models command for provider hint - Integrated into model selection logic (setModel function) - Updated error messages to include gemini-cli in provider list - Removed unrelated azure/vertex changes to maintain PR focus ### Documentation (`docs/providers/gemini-cli.md`) - Comprehensive provider documentation emphasizing OAuth-first approach - Clear explanation of why users would choose gemini-cli over standard google provider - Detailed installation, authentication, and configuration instructions - Troubleshooting section with common issues and solutions ### Testing (`tests/unit/ai-providers/gemini-cli.test.js`) - Complete test suite with 12 tests covering all functionality - Tests for both OAuth and API key authentication paths - Error handling and edge case coverage - Updated mocks in ai-services-unified.test.js for integration testing ## Key Design Decisions 1. **OAuth-First Design**: The provider assumes users want to leverage their existing `gemini auth login` credentials, making this the default authentication method. 2. **Authentication Type Mapping**: Discovered through testing that the SDK expects: - 'oauth-personal' for OAuth/CLI authentication (not 'gemini-cli' or 'oauth') - 'api-key' for API key authentication (not 'gemini-api-key') 3. **Silent Operation**: Removed console.log statements from validateAuth to match the pattern used by other providers like claude-code. 4. **Limited Model Support**: Only gemini-2.5-pro and gemini-2.5-flash are available through the CLI, as confirmed by the package author. ## Usage ```bash # Install gemini CLI globally npm install -g @google/gemini-cli # Authenticate with Google account gemini auth login # Configure Task Master to use gemini-cli task-master models --set-main gemini-2.5-pro --gemini-cli # Use Task Master normally task-master new "Create a REST API endpoint" ``` ## Dependencies - Added `ai-sdk-provider-gemini-cli@^0.0.3` to package.json - This package wraps the Google Gemini CLI Core functionality for Vercel AI SDK ## Testing All tests pass (613 total), including the new gemini-cli provider tests. Code has been formatted with biome to maintain consistency. This implementation provides a clean, well-tested integration that follows Task Master's existing patterns while offering users a convenient way to use Gemini models with their existing Google authentication. * feat: implement lazy loading for gemini-cli provider - Move ai-sdk-provider-gemini-cli to optionalDependencies - Implement dynamic import with loadGeminiCliModule() function - Make getClient() async to support lazy loading - Update base-provider to handle async getClient() calls - Update tests to handle async getClient() method This allows the application to start without the gemini-cli package installed, only loading it when actually needed. * feat(gemini-cli): replace regex-based JSON extraction with jsonc-parser - Add jsonc-parser dependency for robust JSON parsing - Replace simple regex approach with progressive parsing strategy: 1. Direct parsing after cleanup 2. Smart boundary detection with single-pass analysis 3. Limited fallback for edge cases - Optimize performance with early termination and strategic sampling - Add comprehensive tests for variable declarations, trailing commas, escaped quotes, nested objects, and performance edge cases - Improve reliability for complex JSON structures that Gemini commonly produces - Fix code formatting with biome This addresses JSON parsing failures in generateObject operations while maintaining backward compatibility and significantly improving performance for large responses. * fix: update package-lock.json and fix formatting for CI/CD - Add jsonc-parser to package-lock.json for proper npm ci compatibility - Fix biome formatting issues in gemini-cli provider and tests - Ensure all CI/CD checks pass * feat(gemini-cli): implement comprehensive JSON output reliability system - Add automatic JSON request detection via content analysis patterns - Implement task-specific prompt simplification for improved AI compliance - Add strict JSON enforcement through enhanced system prompts - Implement response interception with intelligent JSON extraction fallback - Add comprehensive test coverage for all new JSON handling methods - Move debug logging to appropriate level for clean user experience This multi-layered approach addresses gemini-cli's conversational response tendencies, ensuring reliable structured JSON output for task expansion operations. Achieves 100% success rate in end-to-end testing while maintaining full backward compatibility with existing functionality. Technical implementation includes: • JSON detection via user message content analysis • Expand-task prompt simplification with cleaner instructions • System prompt enhancement with strict JSON enforcement • Response processing with jsonc-parser-based extraction • Comprehensive unit test coverage for edge cases • Debug-level logging to prevent user interface clutter Resolves: gemini-cli JSON formatting inconsistencies Tested: All 46 test suites pass, formatting verified * chore: add changeset for gemini-cli provider implementation Adds minor version bump for comprehensive gemini-cli provider with: - Lazy loading and optional dependency management - Advanced JSON parsing with jsonc-parser - Multi-layer reliability system for structured output - Complete test coverage and CI/CD compliance * refactor: consolidate optional auth provider logic - Add gemini-cli to existing providersWithoutApiKeys array in config-manager - Export providersWithoutApiKeys for reuse across modules - Remove duplicate OPTIONAL_AUTH_PROVIDERS Set from ai-services-unified - Update ai-services-unified to import and use centralized array - Fix Jest mock to include new providersWithoutApiKeys export This eliminates code duplication and provides a single source of truth for which providers support optional authentication, addressing PR reviewer feedback about existing similar functionality in src/constants.
Changesets
This folder has been automatically generated by @changesets/cli, a build tool that works with multi-package repos or single-package repos to help version and publish code. Full documentation is available in the Changesets repository.
What are Changesets?
Changesets are a way to track changes to packages in your repository. Each changeset:
- Describes the changes you've made
- Specifies the type of version bump needed (patch, minor, or major)
- Connects these changes with release notes
- Automates the versioning and publishing process
How to Use Changesets in Task Master
2. Making Changes
- Create a new branch for your changes
- Make your code changes
- Write tests and ensure all tests pass
3. Creating a Changeset
After making changes, create a changeset by running:
npx changeset
This will:
- Walk you through a CLI to describe your changes
- Ask you to select impact level (patch, minor, major)
- Create a markdown file in the
.changesetdirectory
4. Impact Level Guidelines
When choosing the impact level for your changes:
- Patch: Bug fixes and minor changes that don't affect how users interact with the system
- Example: Fixing a typo in output text, optimizing code without changing behavior
- Minor: New features or enhancements that don't break existing functionality
- Example: Adding a new flag to an existing command, adding new task metadata fields
- Major: Breaking changes that require users to update their usage
- Example: Renaming a command, changing the format of the tasks.json file
5. Writing Good Changeset Descriptions
Your changeset description should:
- Be written for end-users, not developers
- Clearly explain what changed and why
- Include any migration steps or backward compatibility notes
- Reference related issues or pull requests with
#issue-number
Examples:
# Good
Added new `--research` flag to the `expand` command that uses Perplexity AI
to provide research-backed task expansions. Requires PERPLEXITY_API_KEY
environment variable.
# Not Good
Fixed stuff and added new flag
6. Committing Your Changes
Commit both your code changes and the generated changeset file:
git add .
git commit -m "Add feature X with changeset"
git push
7. Pull Request Process
- Open a pull request
- Ensure CI passes
- Await code review
- Once approved and merged, your changeset will be used during the next release
Release Process (for Maintainers)
When it's time to make a release:
- Ensure all desired changesets are merged
- Run
npx changeset versionto update package versions and changelog - Review and commit the changes
- Run
npm publishto publish to npm
This can be automated through Github Actions
Common Issues and Solutions
- Merge Conflicts in Changeset Files: Resolve just like any other merge conflict
- Multiple Changes in One PR: Create multiple changesets if changes affect different areas
- Accidentally Committed Without Changeset: Create the changeset after the fact and commit it separately