- Enhance E2E testing and LLM analysis report and:
- Add --analyze-log flag to run_e2e.sh to re-run LLM analysis on existing logs.
- Add test:e2e and analyze-log scripts to package.json for easier execution.
- Correct display errors and dependency validation output:
- Update chalk usage in add-task.js to use bracket notation (chalk[color]) compatible with v5, resolving 'chalk.keyword is not a function' error.
- Modify fix-dependencies command output to show red failure box with issue count instead of green success box when validation fails.
- Refactor interactive model setup:
- Verify inclusion of 'No change' option during interactive model setup flow (task-master models --setup).
- Update model definitions:
- Add max_tokens field for gpt-4o in supported-models.json.
- Remove unused scripts:
- Delete prepare-package.js and rule-transformer.test.js.
Release candidate
Integrates the OpenRouter AI provider using the Vercel AI SDK adapter (@openrouter/ai-sdk-provider). This allows users to configure and utilize models available through the OpenRouter platform.
- Added src/ai-providers/openrouter.js with standard Vercel AI SDK wrapper functions (generateText, streamText, generateObject).
- Updated ai-services-unified.js to include the OpenRouter provider in the PROVIDER_FUNCTIONS map and API key resolution logic.
- Verified config-manager.js handles OpenRouter API key checks correctly.
- Users can configure OpenRouter models via .taskmasterconfig using the task-master models command or MCP models tool. Requires OPENROUTER_API_KEY.
- Enhanced error handling in ai-services-unified.js to provide clearer messages when generateObjectService fails due to lack of underlying tool support in the selected model/provider endpoint.
Adds the ability for users to specify custom model IDs for Ollama and OpenRouter providers, bypassing the internal supported model list.
- Introduces --ollama and --openrouter flags for the 'task-master models --set-<role>' command.
- Updates the interactive 'task-master models --setup' to include options for entering custom Ollama/OpenRouter IDs.
- Implements live validation against the OpenRouter API when a custom OpenRouter ID is provided.
- Refines the model setting logic to prioritize explicit provider flags/choices.
- Adds warnings when custom models are set.
- Updates the changeset file.
Integrates the xAI provider into the unified AI service layer, allowing the use of Grok models (e.g., grok-3, grok-3-mini).
Changes include:
- Added dependency.
- Created with implementations for generateText, streamText, and generateObject (stubbed).
- Updated to include the xAI provider in the function map.
- Updated to recognize the 'xai' provider and the environment variable.
- Updated to include known Grok models and their capabilities (object generation marked as likely unsupported).
- Add OpenAI provider implementation using @ai-sdk/openai.\n- Update `models` command/tool to display API key status for configured providers.\n- Implement model-specific `maxTokens` override logic in `config-manager.js` using `supported-models.json`.\n- Improve AI error message parsing in `ai-services-unified.js` for better clarity.
This commit updates all relevant documentation (READMEs, docs/*, .cursor/rules) to accurately reflect the finalized unified AI service architecture and the new configuration system (.taskmasterconfig + .env/mcp.json). It also includes the final code cleanup steps related to the refactoring.
Key Changes:
1. **Documentation Updates:**
* Revised `README.md`, `README-task-master.md`, `assets/scripts_README.md`, `docs/configuration.md`, and `docs/tutorial.md` to explain the new configuration split (.taskmasterconfig vs .env/mcp.json).
* Updated MCP configuration examples in READMEs and tutorials to only include API keys in the `env` block.
* Added/updated examples for using the `--research` flag in `docs/command-reference.md`, `docs/examples.md`, and `docs/tutorial.md`.
* Updated `.cursor/rules/ai_services.mdc`, `.cursor/rules/architecture.mdc`, `.cursor/rules/dev_workflow.mdc`, `.cursor/rules/mcp.mdc`, `.cursor/rules/taskmaster.mdc`, `.cursor/rules/utilities.mdc`, and `.cursor/rules/new_features.mdc` to align with the new architecture, removing references to old patterns/files.
* Removed internal rule links from user-facing rules (`taskmaster.mdc`, `dev_workflow.mdc`, `self_improve.mdc`).
* Deleted outdated example file `docs/ai-client-utils-example.md`.
2. **Final Code Refactor & Cleanup:**
* Corrected `update-task-by-id.js` by removing the last import from the old `ai-services.js`.
* Refactored `update-subtask-by-id.js` to correctly use the unified service and logger patterns.
* Removed the obsolete export block from `mcp-server/src/core/task-master-core.js`.
* Corrected logger implementation in `update-tasks.js` for CLI context.
* Updated API key mapping in `config-manager.js` and `ai-services-unified.js`.
3. **Configuration Files:**
* Updated API keys in `.cursor/mcp.json`, replacing `GROK_API_KEY` with `XAI_API_KEY`.
* Updated `.env.example` with current API key names.
* Added `azureOpenaiBaseUrl` to `.taskmasterconfig` example.
4. **Task Management:**
* Marked documentation subtask 61.10 as 'done'.
* Includes various other task content/status updates from the diff summary.
5. **Changeset:**
* Added `.changeset/cuddly-zebras-matter.md` for user-facing `expand`/`expand-all` improvements.
This commit concludes the major architectural refactoring (Task 61) and ensures the documentation accurately reflects the current system.
Resolves persistent 404 'Not Found' errors when calling Anthropic models via the Vercel AI SDK. The primary issue was likely related to incorrect or missing API headers.
- Refactors Anthropic provider (src/ai-providers/anthropic.js) to use the standard 'anthropic-version' header instead of potentially outdated/incorrect beta headers when creating the client instance.
- Updates the default fallback model ID in .taskmasterconfig to 'claude-3-5-sonnet-20241022'.
- Fixes the interactive model setup (task-master models --setup) in scripts/modules/commands.js to correctly filter and default the main model selection.
- Improves the cost display in the 'task-master models' command output to explicitly show 'Free' for models with zero cost.
- Updates description for the 'id' parameter in the 'set_task_status' MCP tool definition for clarity.
- Updates list of models and costs
This commit implements several related improvements to the models command and configuration system:
- Added MCP support for the models command:
- Created new direct function implementation in models.js
- Registered modelsDirect in task-master-core.js for proper export
- Added models tool registration in tools/index.js
- Ensured project name replacement when copying .taskmasterconfig in init.js
- Improved .taskmasterconfig copying during project initialization:
- Added copyTemplateFile() call in createProjectStructure()
- Ensured project name is properly replaced in the config
- Restructured tool registration in logical workflow groups:
- Organized registration into 6 functional categories
- Improved command ordering to follow typical workflow
- Added clear group comments for maintainability
- Enhanced documentation in cursor rules:
- Updated dev_workflow.mdc with clearer config management instructions
- Added comprehensive models command reference to taskmaster.mdc
- Clarified CLI vs MCP usage patterns and options
- Added warning against manual .taskmasterconfig editing
The interactive model setup triggered by `task-master models --setup` was previously attempting to call non-existent setter functions (`setMainModel`, etc.) in `config-manager.js`, leading to errors and preventing configuration updates.
This commit refactors the `--setup` logic within the `models` command handler in `scripts/modules/commands.js`. It now correctly:
- Loads the current configuration using `getConfig()`." -m "- Updates the appropriate sections of the loaded configuration object based on user selections from `inquirer`." -m "- Saves the modified configuration using the existing `writeConfig()` function from `config-manager.js`." -m "- Handles disabling the fallback model correctly."
Introduces a configurable fallback model and adds support for additional AI provider API keys in the environment setup.
- **Add Fallback Model Configuration (.taskmasterconfig):**
- Implemented a new section in .
- Configured as the default fallback model, enhancing resilience if the primary model fails.
- **Update Default Model Configuration (.taskmasterconfig):**
- Changed the default model to .
- Changed the default model to .
- **Add API Key Examples (assets/env.example):**
- Added example environment variables for:
- (for OpenAI/OpenRouter)
- (for Google Gemini)
- (for XAI Grok)
- Included format comments for clarity.
Refactored `config-manager.js` to handle different execution contexts (CLI vs. MCP) and fixed related Jest tests.
- Modified `readConfig` and `writeConfig` to accept an optional `explicitRoot` parameter, allowing explicit path specification (e.g., from MCP) while retaining automatic project root finding for CLI usage.
- Updated getter/setter functions (`getMainProvider`, `setMainModel`, etc.) to accept and propagate the `explicitRoot`.
- Resolved Jest testing issues for dynamic imports by using `jest.unstable_mockModule` for `fs` and `chalk` dependencies *before* the dynamic `import()`.
- Corrected console error assertions in tests to match exact logged messages.
- Updated `.cursor/rules/tests.mdc` with guidelines for `jest.unstable_mockModule` and precise console assertions.
