Fixes#6432 - Windows debugging issue where VSCode debug configuration
failed because the root turbo.json was missing the bundle and watch:bundle
task definitions that are required by the debug tasks.
The issue occurred because:
- VSCode debug configuration runs the default build task (watch)
- The watch task depends on watch:bundle via turbo
- Root turbo.json was missing bundle and watch:bundle task definitions
- This caused "Cannot find module extension.js" error on Windows
Changes:
- Added bundle task with outputs configuration
- Added watch:bundle task with cache disabled
- Both tasks now properly delegate to workspace-specific implementations
feat: remove "(prev Roo Cline)" from extension title in all languages
- Updated all package.nls.*.json files to remove "(prev Roo Cline)" references from extension display names
- Updated all localized README.md files to remove "(prev Roo Cline)" references from titles
- Updated main README.md to remove "(prev Roo Cline)" reference from title
- Affects 18 language files and 18 README files across all supported locales
Co-authored-by: Roo Code <roomote@roocode.com>
feat: increase Claude Code default max output tokens from 8k to 16k
- Changed CLAUDE_CODE_DEFAULT_MAX_OUTPUT_TOKENS from 8000 to 16000
- Users can still lower it to 8k via environment variable if needed
- Addresses issue #6125 regarding output token limits
Co-authored-by: Roo Code <roomote@roocode.com>
- Add todo list initialization and tracking throughout the review workflow
- Replace all MCP GitHub server calls with gh CLI commands
- Fix duplicate step numbering issue
- Update best practices and common mistakes documentation
- Add notes about GitHub CLI limitations for inline comments
* feat: add prompt caching support for LiteLLM (#5791)
- Add litellmUsePromptCache configuration option to provider settings
- Implement cache control headers in LiteLLM handler when enabled
- Add UI checkbox for enabling prompt caching (only shown for supported models)
- Track cache read/write tokens in usage data
- Add comprehensive test for prompt caching functionality
- Reuse existing translation keys for consistency across languages
This allows LiteLLM users to benefit from prompt caching with supported models
like Claude 3.7, reducing costs and improving response times.
* fix: improve LiteLLM prompt caching to work for multi-turn conversations
- Convert system message to structured format with cache_control
- Handle both string and array content types for user messages
- Apply cache_control to content items, not just message level
- Update tests to match new message structure
This ensures prompt caching works correctly for all messages in a conversation,
not just the initial system prompt and first user message.
* fix: resolve TypeScript linter error for cache_control property
Use type assertion to handle cache_control property that's not in OpenAI types
