Implements a more robust bundling strategy for Mermaid diagrams to prevent
dynamic chunk loading at runtime, which was causing CSP violations.
Key changes:
- Added manualChunks function in vite.config.ts to consolidate all Mermaid
code and dependencies into a single bundle
- Added mermaid and dagre to optimizeDeps.include for pre-bundling
- Customized chunkFileNames to ensure predictable output
- Removed incorrect static imports in MermaidBlock.tsx
This resolves the CSP errors where Mermaid was attempting to dynamically
load chunks like chunk-RZ5BOZE2.js and channel.js from the webview origin.
Fixes: #3680
Signed-off-by: Eric Wheeler <roo-code@z.ewheeler.org>
Co-authored-by: Eric Wheeler <roo-code@z.ewheeler.org>
Co-authored-by: Daniel <57051444+daniel-lxs@users.noreply.github.com>
* feat(prompts): enforce codebase_search as primary code understanding tool
- Add conditional codebase_search enforcement in tool use guidelines
- Modify objective section to prioritize codebase_search when available
- Update rules section with critical codebase_search-first rule
- Pass CodeIndexManager to prompt sections for availability checks
- Ensure graceful degradation when codebase_search is unavailable
* chore(docs): remove codebase search enforcement documentation
* fix: update snapshot and reorder capabilities section
- Update system.test.ts snapshot to reflect architect mode without codebase_search enforcement
- Reorder capabilities section to place search_files description after codebase_search
- Ensures logical flow: codebase_search (semantic) → search_files (regex) → other tools
* refactor: improve tool-use-guidelines numbering logic
- Replace subsequentNumbers object with array-based approach
- Use automatic incrementing with itemNumber++ for sequential numbering
- Build guidelines as an array and join at the end
- Fix potential numbering issues with conditional logic
- Update tests and snapshots to match new format
As suggested by daniel-lxs in PR #4340
* feat: Add OpenAI Compatible embedder for codebase indexing
- Implement OpenAiCompatibleEmbedder with batching and retry logic
- Add configuration support for base URL and API key
- Update UI with provider selection and input fields
- Add comprehensive test coverage
- Support for all OpenAI-compatible endpoints (LiteLLM, LMStudio, Ollama, etc.)
- Add internationalization for 17 languages
* fix: Update CodeIndexSettings tests for OpenAI Compatible provider
- Fix field count expectations (4 fields including Qdrant)
- Use specific test IDs for button selection
- Fix input handling with clear() before type()
- Use toHaveBeenLastCalledWith for better assertions
- Fix status text matching with regex pattern
* fix: resolve UI test failures and ESLint errors
- Remove unused waitFor import to fix ESLint error
- Fix test expectations to match actual component behavior for input fields
- Simplify provider selection test by removing complex mock interactions
- All CodeIndexSettings tests now pass (20/20)
* feat: add custom model infrastructure for OpenAI-compatible embedder
- Add manual model ID and embedding dimension configuration
- Enable custom model input via text field in settings UI
- Add modelDimension parameter to OpenAiCompatibleEmbedder
- Update configuration management to persist dimension setting
- Prioritize manual dimension over hardcoded model profiles
- Add comprehensive test coverage for new functionality
This allows users to specify any custom embedding model and its
dimension for OpenAI-compatible providers, removing dependency
on hardcoded model profiles.
* Add missing translations for OpenAI-compatible model dimension settings in all locales
* refactor: remove unused modelDimension parameter from OpenAiCompatibleEmbedder
- Remove modelDimension property and constructor parameter from OpenAiCompatibleEmbedder class
- Update ServiceFactory to not pass dimension to embedder constructor
- Update tests to match new constructor signature
- The dimension is still used for QdrantVectorStore configuration
* chore: bot suggestion
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* chore: bot suggestion
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* refactor: rename OpenAiCompatibleEmbedder to OpenAICompatibleEmbedder for consistency
* feat: add model dimension validation for OpenAI-compatible settings
* refactor: improve default model ID retrieval logic for embedding providers
* feat: add default model ID retrieval for openai-compatible provider
* refactor: update default model ID retrieval to use shared utility function
* fix: Remove unnecessary type assertion in OpenAICompatibleEmbedder
* feat: add model dimension input for openai-compatible provider
---------
Co-authored-by: Daniel Riccio <ricciodaniel98@gmail.com>
Co-authored-by: Daniel <57051444+daniel-lxs@users.noreply.github.com>
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
- Replace manual PATH and HOME env var handling with getDefaultEnvironment()
- Improves consistency and reliability of MCP client environment setup
- Leverages SDK's built-in environment configuration
- Allow specific binary formats (.pdf, .docx, .ipynb) to be processed by extractTextFromFile
- Block unsupported binary files with existing "Binary file" notice
- Update tests to cover both supported and unsupported binary file scenarios
- Refactor test mocks for better maintainability and coverage
