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NEWS.md
In mLLMCelltype: Cell Type Annotation Using Large Language Models
mLLMCelltype Changelog
2.0.5 (2026-05-11)
Bug Fixes
- Unified discussion cell-type extraction across consensus checking and early discussion fallback paths.
- Scoped Qwen endpoint detection cache by API key to avoid cross-credential endpoint reuse.
- Forwarded registered custom model configuration to custom providers that accept
model_config or ....
Documentation
- Updated caching guidance, model examples, and Python integration examples for current package behavior.
2.0.4 (2026-05-10)
Bug Fixes
- Aligned R documentation with the actual
annotate_cell_types() return contract.
- Hardened discussion error-response filtering so failed model responses are excluded consistently.
- Kept default tests offline by gating real API integration tests behind explicit environment variables.
Documentation
- Updated examples and integration guidance for the current cross-language API surface.
2.0.0 (2026-02-08)
Breaking Changes
- Version bump to 2.0.0: Major release reflecting substantial architectural improvements since 1.2.9
- Logger defaults changed:
UnifiedLogger console output is now disabled by default (enable_console = FALSE). Use configure_logger(console_output = TRUE) to enable console logging.
New Model Support
- Added support for latest LLM models across all providers:
- OpenAI: GPT-5.2, GPT-5.1, GPT-5, o3-pro, o4-mini
- Anthropic: Claude Opus 4.6, Claude Opus 4.5, Claude Sonnet 4.5
- Google: Gemini 3 Pro, Gemini 3 Flash, Gemini 2.5 Pro/Flash
- X.AI: Grok 4, Grok 4.1, Grok 4 Heavy
- DeepSeek: DeepSeek R1
- Alibaba: Qwen 3 Max
- Zhipu: GLM-4.7
- MiniMax: MiniMax M2.1
Architecture Improvements
- Unified logging system: Consolidated dual debug mechanisms (
debug parameter + LLMCELLTYPE_DEBUG_CACHE env var) into single log_debug() approach; debug = TRUE temporarily enables console + DEBUG level via on.exit()
- Complete audit trail: All
warning() calls now paired with log_warn() for file-based audit; LLM consensus decisions logged to audit trail
- NAMESPACE fix:
QwenProcessor now correctly exported; internal .qwen_endpoint_cache no longer exposed in public API
- Cluster ID preservation: Cluster IDs from input are preserved as-is throughout the annotation pipeline
Bug Fixes
- Fixed
@export misplacement in qwen_processor.R that exported internal state instead of the processor class
- Fixed missing
tissue_name parameter in real API test calls
- Fixed
print() bypassing logging system in compare_model_predictions.R
- Fixed trailing newlines causing double-spaced console output in
compare_model_predictions.R
- Fixed
message() format inconsistencies across consensus and comparison functions
- Improved NA handling in API key validation and print functions
Code Quality
- Removed marketing language from documentation
- Consistent
message() + log_info() pairing across entire codebase
- Removed dead
TaskState.TESTING from state machine (web component)
1.3.6 (2026-02-07)
Documentation Clarification
- Clarified current cluster ID contract in tutorials and examples: input cluster IDs are preserved as-is
- Updated mapping examples to use annotation names directly (instead of assuming sequential
0:(n-1) IDs)
- Kept historical release notes unchanged; this entry documents the current behavior explicitly
1.3.5 (2025-10-12)
Updated Models
- Updated Anthropic Claude model support to include latest releases:
- Added Claude Sonnet 4.5 (
claude-sonnet-4-5-20250929) - Newest Sonnet model, same price as earlier Sonnets
- Added Claude Opus 4.1 (
claude-opus-4-1-20250805) - Updated Opus model
- Added Claude 4 series models (
claude-sonnet-4-20250514, claude-opus-4-20250514)
- Added support for both date-versioned and alias formats (e.g.,
claude-sonnet-4.5, claude-opus-4.1)
- Updated all documentation, vignettes, and examples to recommend latest models
- All Sonnet models (4.5, 4, 3.5, 3.7) have identical pricing - Claude Sonnet 4.5 is now supported at identical pricing
Documentation Updates
- Updated model recommendations in usage tutorials and vignettes
- Updated get_provider() documentation with comprehensive model lists
- Added clarification that dated model versions are identical across all platforms
Notes
- OpenRouter now supports
anthropic/claude-sonnet-4.5 and anthropic/claude-opus-4.1
- All dated model versions (e.g.,
20250929) remain stable and do not change over time
1.3.4 (2025-09-09)
Bug Fixes
- Fixed critical NA handling issue in base_api_processor.R that caused "missing value where TRUE/FALSE needed" errors
- Fixed similar NA handling issues in print_consensus_summary.R
- Improved robustness of API key validation to handle NA, NULL, and empty string cases correctly
Improvements
- Enhanced error handling for invalid API keys
- Better support for OpenRouter API integration
- Improved stability when processing consensus annotations
1.3.2 (2025-09-02) - CRAN Release
Official CRAN Release
- mLLMCelltype is now available on CRAN:
install.packages("mLLMCelltype")
- CRAN page: https://CRAN.R-project.org/package=mLLMCelltype
- DOI: 10.32614/CRAN.package.mLLMCelltype
Installation
- Standard R package installation from CRAN repository
- Package has passed CRAN checks for reliability and compatibility
- Tested across R versions and platforms (Windows, macOS, Linux)
Features
- Automated cell type annotation using consensus from multiple LLMs
- Support for OpenAI, Anthropic, Google, and other providers through OpenRouter
- Integration with Seurat workflows
- Uncertainty quantification for annotations
- Caching system for API cost reduction
- Interactive consensus building with multi-model discussion
1.3.1 (2025-07-16)
New Features: Enhanced Cluster Analysis Control
Selective Cluster Analysis
- New parameter
clusters_to_analyze: Allows users to specify exactly which clusters to analyze
- No need to manually filter input data
- Maintains original cluster numbering
- Reduces API calls and costs by focusing on relevant clusters
- Perfect for iterative refinement and subtyping workflows
Cache Control for Re-analysis
- New parameter
force_rerun: Forces fresh analysis of controversial clusters
- Bypasses cache when you need new analysis with different context
- Essential for subtype identification with tissue-specific context
- Non-controversial clusters still benefit from cache performance
- Combines perfectly with
clusters_to_analyze for targeted workflows
Use Cases
- Iterative Subtyping: Analyze broad cell types first, then focus on specific populations
- Cost-Effective Re-analysis: Only re-analyze controversial or specific clusters
- Context-Specific Analysis: Re-run with different tissue contexts without cache interference
- Targeted Refinement: Focus computational resources on clusters of interest
Implementation
- Full backward compatibility maintained
- Comprehensive input validation and error handling
- Extensive testing with real API keys across multiple scenarios
- Updated documentation with detailed examples
1.2.9 (2025-06-24)
Consensus check optimization
Performance Optimization
- Two-Stage Consensus Strategy: Implemented optimized consensus checking that reduces redundant API calls through early consensus detection
- Stage 1 - Simple Consensus: First performs fast local calculation based on normalized annotations
- Stage 2 - LLM Verification: Only calls LLM for clusters that don't meet consensus thresholds
- Smart Resource Usage: LLM only used for genuinely ambiguous cases
Cost Reduction
- API cost optimization:
- Clear consensus cases (majority of clusters) now processed without LLM calls
- Reduces costs proportionally to API call reduction
- Maintains same accuracy while being much more economical
Implementation Details
- New Functions:
normalize_annotation(): Handles annotation variations (e.g., "T cells" vs "T lymphocytes")calculate_simple_consensus(): Fast local consensus calculation with CP and entropy metrics- Improved Fallback: If LLM fails, falls back to simple consensus results instead of default values
- Enhanced Logging: Clear indication of which strategy was used for each cluster
1.2.7 (2025-06-17)
Major Enhancements: Code Deduplication and Enhanced Logging
Code Architecture Refactoring
- BaseAPIProcessor: Introduced abstract base class for API processing with unified error handling and logging
- Reduced code duplication across API processors
- Standardized interface: All processors now inherit from
BaseAPIProcessor with consistent make_api_call() and extract_response_content() methods
- Unified error handling: Centralized exception handling and retry logic across all API providers
Enhanced Discussion Logging
- Fixed Discussion Format Issues: Resolved fragmented discussion logs where multi-line model responses were split into multiple entries
- Improved readability: Multi-line model predictions now properly consolidated into single coherent text blocks
- Better structure: Clean Markdown format with proper headers and code block formatting
- Complete conversations: Full model reasoning (grounds, warrant, backing, qualifier, rebuttal) preserved in readable format
Complete API Request/Response Logging
- New Feature: Full API audit trail with complete request and response content
- Dual format logging: Both JSON (machine-readable) and Markdown (human-readable) formats
- Complete transparency: Every API call now logged with full prompt content and response
- Debugging support: Detailed metadata including chunk information, timing, and response characteristics
- Session organization: API logs organized in dedicated
api_logs/ subdirectories within each session
Improved Log Organization
- Enhanced directory structure:
logs/
├── mllm_YYYYMMDD_HHMMSS.log # Main session log
├── YYYYMMDD_HHMMSS/ # Session directory
│ ├── cluster_X_discussion.md # Discussion logs (fixed format)
│ └── api_logs/ # Complete API call logs (NEW)
│ ├── provider_model_timestamp.json
│ └── provider_model_timestamp.md
Performance Improvements
- Reduced codebase size: Consolidated API processor code
- Maintainability: Single source of truth for API processing logic
- Consistency: Standardized error messages and logging across all providers
Quality Assurance
- Comprehensive testing: All changes verified with real API calls using OpenRouter
- Backward compatibility: Existing functionality preserved while enhancing logging capabilities
- Zero breaking changes: All public APIs remain unchanged
1.2.6 (2025-06-14)
Major Logging System Overhaul
- Unified Logging System: Replaced fragmented logging infrastructure with comprehensive unified logging
- Removed: Old
DiscussionLogger class and scattered write_log calls
- Added: New
UnifiedLogger R6 class with structured JSON output, multi-level logging, and performance monitoring
- New functions:
configure_logger(), get_logger(), log_info(), log_warn(), log_error(), log_debug()
- Features: Session tracking, API call monitoring, cache operation logging, automatic log rotation
Performance Improvements
- Performance Monitoring: Integrated performance tracking with session duration, API call counting, and error statistics
- Log Rotation: Automatic log file rotation with configurable size limits and file retention
- Structured Logging: JSON-formatted logs with context metadata for better analysis and debugging
API Enhancements
- Function Signature Updates: Removed logger parameters from all consensus annotation functions
- Code Cleanup: Eliminated 20+ scattered logger parameter dependencies across the codebase
- Cache Integration: Enhanced cache operations with detailed logging and performance tracking
Documentation Updates
- Updated Vignettes: Revised advanced features tutorial with new unified logging examples
- Roxygen Documentation: Updated all function documentation to reflect new logging system
- NAMESPACE Updates: Added exports for new logging functions and UnifiedLogger class
Breaking Changes
- Logger Parameters: Removed
logger parameters from interactive_consensus_annotation() and related functions
- DiscussionLogger: Deprecated
DiscussionLogger class (still exported for backward compatibility but not recommended)
1.2.5 (2025-06-02)
Model Updates
- Updated Gemini model support: Added support for new Gemini models and removed discontinued ones
- Added
gemini-2.0-flash-lite to supported models list
- Updated documentation to reflect Google's model migration recommendations
- Removed references to discontinued Gemini 1.5 Pro 001 and Gemini 1.5 Flash 001 models
Important Notes
- Google Gemini Model Migration: Google has discontinued several Gemini 1.5 models:
- Already discontinued: Gemini 1.5 Pro 001, Gemini 1.5 Flash 001
- Will be discontinued on Sept 24, 2025: Gemini 1.5 Pro 002, Gemini 1.5 Flash 002, Gemini 1.5 Flash-8B -001
- Recommended migration: Use
gemini-2.0-flash or gemini-2.0-flash-lite for better performance and continued support
- The aliases
gemini-1.5-pro and gemini-1.5-flash will continue to work until September 24, 2025
Documentation Updates
- Updated all README files (English and international versions) with new Gemini model information
- Updated R documentation and vignettes to reflect model changes
- Added migration guidance in main documentation
1.2.4 (2025-05-25)
Critical Bug Fixes
- Fixed major
as.logical(from) error: Resolved critical error that occurred when processing large numbers of clusters (60+ clusters), which was caused by non-character data being passed to strsplit() functions
- Enhanced error handling for API responses: Added comprehensive
tryCatch() blocks around all strsplit() operations in API processing functions
- Improved response validation: Added robust type checking for API responses to prevent function/closure types from being processed as character strings
Improvements
- Enhanced API processing robustness: All API processing functions (
process_openrouter.R, process_anthropic.R, process_openai.R, process_deepseek.R, process_qwen.R, process_stepfun.R, process_minimax.R, process_zhipu.R, process_gemini.R, process_grok.R) now include improved error handling
- Better NULL value handling: Improved
unlist() operations to filter out NULL values and handle errors gracefully
- Enhanced logging: Added more detailed error logging for debugging API response issues
- Improved consensus checking: Enhanced
check_consensus.R to handle edge cases with malformed responses
Technical Details
- Fixed issue where large cluster datasets could cause type coercion errors in response parsing
- Added validation for function/closure types in API responses to prevent downstream errors
- Improved error messages to provide better diagnostics for API response issues
1.2.3 (2025-05-10)
Bug Fixes
- Fixed error handling in consensus checking when API responses are NULL or invalid
- Improved error logging for OpenRouter API error responses
- Added robust NULL and type checking in check_consensus function
Improvements
- Enhanced error diagnostics for OpenRouter API errors
- Added detailed logging of API error messages and response structures
- Improved robustness when handling unexpected API response formats
1.2.2 (2025-05-09)
Bug Fixes
- Fixed the 'non-character argument' error that occurred when processing API responses
- Added robust type checking for API responses across all model providers
- Improved error handling for unexpected API response formats
Improvements
- Added detailed error logging for API response issues
- Implemented consistent error handling patterns across all API processing functions
- Enhanced response validation to ensure proper structure before processing
1.2.1 (2025-05-01)
Improvements
- Added support for OpenRouter API
- Added support for free models through OpenRouter
- Updated documentation with examples for using OpenRouter models
1.2.0 (2025-04-30)
Features
- Added visualization functions for cell type annotation results
- Added support for uncertainty metrics visualization
- Implemented improved consensus building algorithm
1.1.5 (2025-04-27)
Bug Fixes
- Fixed an issue with cluster index validation that caused errors when processing certain CSV input files
- Improved error handling for negative indices with clearer error messages
Improvements
- Added example script for CSV-based annotation workflow (cat_heart_annotation.R)
- Enhanced input validation with more detailed diagnostics
- Updated documentation to clarify CSV input format requirements
1.1.4 (2025-04-24)
Bug Fixes
- Fixed a critical issue with cluster index handling, now the package strictly accepts only 0-based indices (compatible with Seurat)
- Fixed negative index (-1) issues that could occur when processing CSV input files
- Added strict validation for input cluster indices to ensure they start from 0
Improvements
- Removed automatic conversion logic from 1-based to 0-based indices in
prompt_templates.R
- Added input validation in
consensus_annotation.R to ensure cluster indices start from 0
- Updated code comments to clearly indicate that the package only accepts 0-based indices
1.1.3 (2025-04-15)
- Added support for X.AI's Grok models
- Updated the list of supported models, including Gemini 2.5 Pro
- Improved error handling and logging
1.1.2 (2025-03-30)
- Added support for Gemini 2.0 models
- Improved model response parsing
- Fixed cache management issues
1.1.1 (2025-03-15)
- Added support for Claude 3.7 and Claude 3.5 models
- Improved consensus building algorithm
- Fixed multiple minor bugs
1.1.0 (2025-03-01)
- Added interactive consensus annotation functionality
- Added multi-model discussion capability
- Improved cell type standardization
1.0.0 (2025-02-15)
- Initial release
- Support for cell type annotation using LLMs
- Support for models from OpenAI, Anthropic, and Google
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mLLMCelltype Changelog
2.0.5 (2026-05-11)
Bug Fixes
- Unified discussion cell-type extraction across consensus checking and early discussion fallback paths.
- Scoped Qwen endpoint detection cache by API key to avoid cross-credential endpoint reuse.
- Forwarded registered custom model configuration to custom providers that accept
model_configor....
Documentation
- Updated caching guidance, model examples, and Python integration examples for current package behavior.
2.0.4 (2026-05-10)
Bug Fixes
- Aligned R documentation with the actual
annotate_cell_types()return contract. - Hardened discussion error-response filtering so failed model responses are excluded consistently.
- Kept default tests offline by gating real API integration tests behind explicit environment variables.
Documentation
- Updated examples and integration guidance for the current cross-language API surface.
2.0.0 (2026-02-08)
Breaking Changes
- Version bump to 2.0.0: Major release reflecting substantial architectural improvements since 1.2.9
- Logger defaults changed:
UnifiedLoggerconsole output is now disabled by default (enable_console = FALSE). Useconfigure_logger(console_output = TRUE)to enable console logging.
New Model Support
- Added support for latest LLM models across all providers:
- OpenAI: GPT-5.2, GPT-5.1, GPT-5, o3-pro, o4-mini
- Anthropic: Claude Opus 4.6, Claude Opus 4.5, Claude Sonnet 4.5
- Google: Gemini 3 Pro, Gemini 3 Flash, Gemini 2.5 Pro/Flash
- X.AI: Grok 4, Grok 4.1, Grok 4 Heavy
- DeepSeek: DeepSeek R1
- Alibaba: Qwen 3 Max
- Zhipu: GLM-4.7
- MiniMax: MiniMax M2.1
Architecture Improvements
- Unified logging system: Consolidated dual debug mechanisms (
debugparameter +LLMCELLTYPE_DEBUG_CACHEenv var) into singlelog_debug()approach;debug = TRUEtemporarily enables console + DEBUG level viaon.exit() - Complete audit trail: All
warning()calls now paired withlog_warn()for file-based audit; LLM consensus decisions logged to audit trail - NAMESPACE fix:
QwenProcessornow correctly exported; internal.qwen_endpoint_cacheno longer exposed in public API - Cluster ID preservation: Cluster IDs from input are preserved as-is throughout the annotation pipeline
Bug Fixes
- Fixed
@exportmisplacement inqwen_processor.Rthat exported internal state instead of the processor class - Fixed missing
tissue_nameparameter in real API test calls - Fixed
print()bypassing logging system incompare_model_predictions.R - Fixed trailing newlines causing double-spaced console output in
compare_model_predictions.R - Fixed
message()format inconsistencies across consensus and comparison functions - Improved NA handling in API key validation and print functions
Code Quality
- Removed marketing language from documentation
- Consistent
message()+log_info()pairing across entire codebase - Removed dead
TaskState.TESTINGfrom state machine (web component)
1.3.6 (2026-02-07)
Documentation Clarification
- Clarified current cluster ID contract in tutorials and examples: input cluster IDs are preserved as-is
- Updated mapping examples to use annotation names directly (instead of assuming sequential
0:(n-1)IDs) - Kept historical release notes unchanged; this entry documents the current behavior explicitly
1.3.5 (2025-10-12)
Updated Models
- Updated Anthropic Claude model support to include latest releases:
- Added Claude Sonnet 4.5 (
claude-sonnet-4-5-20250929) - Newest Sonnet model, same price as earlier Sonnets - Added Claude Opus 4.1 (
claude-opus-4-1-20250805) - Updated Opus model - Added Claude 4 series models (
claude-sonnet-4-20250514,claude-opus-4-20250514) - Added support for both date-versioned and alias formats (e.g.,
claude-sonnet-4.5,claude-opus-4.1) - Updated all documentation, vignettes, and examples to recommend latest models
- All Sonnet models (4.5, 4, 3.5, 3.7) have identical pricing - Claude Sonnet 4.5 is now supported at identical pricing
Documentation Updates
- Updated model recommendations in usage tutorials and vignettes
- Updated get_provider() documentation with comprehensive model lists
- Added clarification that dated model versions are identical across all platforms
Notes
- OpenRouter now supports
anthropic/claude-sonnet-4.5andanthropic/claude-opus-4.1 - All dated model versions (e.g.,
20250929) remain stable and do not change over time
1.3.4 (2025-09-09)
Bug Fixes
- Fixed critical NA handling issue in base_api_processor.R that caused "missing value where TRUE/FALSE needed" errors
- Fixed similar NA handling issues in print_consensus_summary.R
- Improved robustness of API key validation to handle NA, NULL, and empty string cases correctly
Improvements
- Enhanced error handling for invalid API keys
- Better support for OpenRouter API integration
- Improved stability when processing consensus annotations
1.3.2 (2025-09-02) - CRAN Release
Official CRAN Release
- mLLMCelltype is now available on CRAN:
install.packages("mLLMCelltype") - CRAN page: https://CRAN.R-project.org/package=mLLMCelltype
- DOI: 10.32614/CRAN.package.mLLMCelltype
Installation
- Standard R package installation from CRAN repository
- Package has passed CRAN checks for reliability and compatibility
- Tested across R versions and platforms (Windows, macOS, Linux)
Features
- Automated cell type annotation using consensus from multiple LLMs
- Support for OpenAI, Anthropic, Google, and other providers through OpenRouter
- Integration with Seurat workflows
- Uncertainty quantification for annotations
- Caching system for API cost reduction
- Interactive consensus building with multi-model discussion
1.3.1 (2025-07-16)
New Features: Enhanced Cluster Analysis Control
Selective Cluster Analysis
- New parameter
clusters_to_analyze: Allows users to specify exactly which clusters to analyze - No need to manually filter input data
- Maintains original cluster numbering
- Reduces API calls and costs by focusing on relevant clusters
- Perfect for iterative refinement and subtyping workflows
Cache Control for Re-analysis
- New parameter
force_rerun: Forces fresh analysis of controversial clusters - Bypasses cache when you need new analysis with different context
- Essential for subtype identification with tissue-specific context
- Non-controversial clusters still benefit from cache performance
- Combines perfectly with
clusters_to_analyzefor targeted workflows
Use Cases
- Iterative Subtyping: Analyze broad cell types first, then focus on specific populations
- Cost-Effective Re-analysis: Only re-analyze controversial or specific clusters
- Context-Specific Analysis: Re-run with different tissue contexts without cache interference
- Targeted Refinement: Focus computational resources on clusters of interest
Implementation
- Full backward compatibility maintained
- Comprehensive input validation and error handling
- Extensive testing with real API keys across multiple scenarios
- Updated documentation with detailed examples
1.2.9 (2025-06-24)
Consensus check optimization
Performance Optimization
- Two-Stage Consensus Strategy: Implemented optimized consensus checking that reduces redundant API calls through early consensus detection
- Stage 1 - Simple Consensus: First performs fast local calculation based on normalized annotations
- Stage 2 - LLM Verification: Only calls LLM for clusters that don't meet consensus thresholds
- Smart Resource Usage: LLM only used for genuinely ambiguous cases
Cost Reduction
- API cost optimization:
- Clear consensus cases (majority of clusters) now processed without LLM calls
- Reduces costs proportionally to API call reduction
- Maintains same accuracy while being much more economical
Implementation Details
- New Functions:
normalize_annotation(): Handles annotation variations (e.g., "T cells" vs "T lymphocytes")calculate_simple_consensus(): Fast local consensus calculation with CP and entropy metrics- Improved Fallback: If LLM fails, falls back to simple consensus results instead of default values
- Enhanced Logging: Clear indication of which strategy was used for each cluster
1.2.7 (2025-06-17)
Major Enhancements: Code Deduplication and Enhanced Logging
Code Architecture Refactoring
- BaseAPIProcessor: Introduced abstract base class for API processing with unified error handling and logging
- Reduced code duplication across API processors
- Standardized interface: All processors now inherit from
BaseAPIProcessorwith consistentmake_api_call()andextract_response_content()methods - Unified error handling: Centralized exception handling and retry logic across all API providers
Enhanced Discussion Logging
- Fixed Discussion Format Issues: Resolved fragmented discussion logs where multi-line model responses were split into multiple entries
- Improved readability: Multi-line model predictions now properly consolidated into single coherent text blocks
- Better structure: Clean Markdown format with proper headers and code block formatting
- Complete conversations: Full model reasoning (grounds, warrant, backing, qualifier, rebuttal) preserved in readable format
Complete API Request/Response Logging
- New Feature: Full API audit trail with complete request and response content
- Dual format logging: Both JSON (machine-readable) and Markdown (human-readable) formats
- Complete transparency: Every API call now logged with full prompt content and response
- Debugging support: Detailed metadata including chunk information, timing, and response characteristics
- Session organization: API logs organized in dedicated
api_logs/subdirectories within each session
Improved Log Organization
- Enhanced directory structure:
logs/ ├── mllm_YYYYMMDD_HHMMSS.log # Main session log ├── YYYYMMDD_HHMMSS/ # Session directory │ ├── cluster_X_discussion.md # Discussion logs (fixed format) │ └── api_logs/ # Complete API call logs (NEW) │ ├── provider_model_timestamp.json │ └── provider_model_timestamp.md
Performance Improvements
- Reduced codebase size: Consolidated API processor code
- Maintainability: Single source of truth for API processing logic
- Consistency: Standardized error messages and logging across all providers
Quality Assurance
- Comprehensive testing: All changes verified with real API calls using OpenRouter
- Backward compatibility: Existing functionality preserved while enhancing logging capabilities
- Zero breaking changes: All public APIs remain unchanged
1.2.6 (2025-06-14)
Major Logging System Overhaul
- Unified Logging System: Replaced fragmented logging infrastructure with comprehensive unified logging
- Removed: Old
DiscussionLoggerclass and scatteredwrite_logcalls - Added: New
UnifiedLoggerR6 class with structured JSON output, multi-level logging, and performance monitoring - New functions:
configure_logger(),get_logger(),log_info(),log_warn(),log_error(),log_debug() - Features: Session tracking, API call monitoring, cache operation logging, automatic log rotation
Performance Improvements
- Performance Monitoring: Integrated performance tracking with session duration, API call counting, and error statistics
- Log Rotation: Automatic log file rotation with configurable size limits and file retention
- Structured Logging: JSON-formatted logs with context metadata for better analysis and debugging
API Enhancements
- Function Signature Updates: Removed logger parameters from all consensus annotation functions
- Code Cleanup: Eliminated 20+ scattered logger parameter dependencies across the codebase
- Cache Integration: Enhanced cache operations with detailed logging and performance tracking
Documentation Updates
- Updated Vignettes: Revised advanced features tutorial with new unified logging examples
- Roxygen Documentation: Updated all function documentation to reflect new logging system
- NAMESPACE Updates: Added exports for new logging functions and UnifiedLogger class
Breaking Changes
- Logger Parameters: Removed
loggerparameters frominteractive_consensus_annotation()and related functions - DiscussionLogger: Deprecated
DiscussionLoggerclass (still exported for backward compatibility but not recommended)
1.2.5 (2025-06-02)
Model Updates
- Updated Gemini model support: Added support for new Gemini models and removed discontinued ones
- Added
gemini-2.0-flash-liteto supported models list - Updated documentation to reflect Google's model migration recommendations
- Removed references to discontinued Gemini 1.5 Pro 001 and Gemini 1.5 Flash 001 models
Important Notes
- Google Gemini Model Migration: Google has discontinued several Gemini 1.5 models:
- Already discontinued: Gemini 1.5 Pro 001, Gemini 1.5 Flash 001
- Will be discontinued on Sept 24, 2025: Gemini 1.5 Pro 002, Gemini 1.5 Flash 002, Gemini 1.5 Flash-8B -001
- Recommended migration: Use
gemini-2.0-flashorgemini-2.0-flash-litefor better performance and continued support - The aliases
gemini-1.5-proandgemini-1.5-flashwill continue to work until September 24, 2025
Documentation Updates
- Updated all README files (English and international versions) with new Gemini model information
- Updated R documentation and vignettes to reflect model changes
- Added migration guidance in main documentation
1.2.4 (2025-05-25)
Critical Bug Fixes
- Fixed major
as.logical(from)error: Resolved critical error that occurred when processing large numbers of clusters (60+ clusters), which was caused by non-character data being passed tostrsplit()functions - Enhanced error handling for API responses: Added comprehensive
tryCatch()blocks around allstrsplit()operations in API processing functions - Improved response validation: Added robust type checking for API responses to prevent function/closure types from being processed as character strings
Improvements
- Enhanced API processing robustness: All API processing functions (
process_openrouter.R,process_anthropic.R,process_openai.R,process_deepseek.R,process_qwen.R,process_stepfun.R,process_minimax.R,process_zhipu.R,process_gemini.R,process_grok.R) now include improved error handling - Better NULL value handling: Improved
unlist()operations to filter out NULL values and handle errors gracefully - Enhanced logging: Added more detailed error logging for debugging API response issues
- Improved consensus checking: Enhanced
check_consensus.Rto handle edge cases with malformed responses
Technical Details
- Fixed issue where large cluster datasets could cause type coercion errors in response parsing
- Added validation for function/closure types in API responses to prevent downstream errors
- Improved error messages to provide better diagnostics for API response issues
1.2.3 (2025-05-10)
Bug Fixes
- Fixed error handling in consensus checking when API responses are NULL or invalid
- Improved error logging for OpenRouter API error responses
- Added robust NULL and type checking in check_consensus function
Improvements
- Enhanced error diagnostics for OpenRouter API errors
- Added detailed logging of API error messages and response structures
- Improved robustness when handling unexpected API response formats
1.2.2 (2025-05-09)
Bug Fixes
- Fixed the 'non-character argument' error that occurred when processing API responses
- Added robust type checking for API responses across all model providers
- Improved error handling for unexpected API response formats
Improvements
- Added detailed error logging for API response issues
- Implemented consistent error handling patterns across all API processing functions
- Enhanced response validation to ensure proper structure before processing
1.2.1 (2025-05-01)
Improvements
- Added support for OpenRouter API
- Added support for free models through OpenRouter
- Updated documentation with examples for using OpenRouter models
1.2.0 (2025-04-30)
Features
- Added visualization functions for cell type annotation results
- Added support for uncertainty metrics visualization
- Implemented improved consensus building algorithm
1.1.5 (2025-04-27)
Bug Fixes
- Fixed an issue with cluster index validation that caused errors when processing certain CSV input files
- Improved error handling for negative indices with clearer error messages
Improvements
- Added example script for CSV-based annotation workflow (cat_heart_annotation.R)
- Enhanced input validation with more detailed diagnostics
- Updated documentation to clarify CSV input format requirements
1.1.4 (2025-04-24)
Bug Fixes
- Fixed a critical issue with cluster index handling, now the package strictly accepts only 0-based indices (compatible with Seurat)
- Fixed negative index (-1) issues that could occur when processing CSV input files
- Added strict validation for input cluster indices to ensure they start from 0
Improvements
- Removed automatic conversion logic from 1-based to 0-based indices in
prompt_templates.R - Added input validation in
consensus_annotation.Rto ensure cluster indices start from 0 - Updated code comments to clearly indicate that the package only accepts 0-based indices
1.1.3 (2025-04-15)
- Added support for X.AI's Grok models
- Updated the list of supported models, including Gemini 2.5 Pro
- Improved error handling and logging
1.1.2 (2025-03-30)
- Added support for Gemini 2.0 models
- Improved model response parsing
- Fixed cache management issues
1.1.1 (2025-03-15)
- Added support for Claude 3.7 and Claude 3.5 models
- Improved consensus building algorithm
- Fixed multiple minor bugs
1.1.0 (2025-03-01)
- Added interactive consensus annotation functionality
- Added multi-model discussion capability
- Improved cell type standardization
1.0.0 (2025-02-15)
- Initial release
- Support for cell type annotation using LLMs
- Support for models from OpenAI, Anthropic, and Google
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