* feat(codex): add authentication mode support with thread-safe logging
- Implement _CodexAuthConfig dataclass for resolved auth settings
- Add auth_mode parameter with auto/api_key/oauth options
- Separate API key and OAuth authentication flows
- Force specific login method based on auth mode
- Add explicit API key validation requirement
- Serialize concurrent logger initialization in thread lock
- Close logging handlers properly during cleanup
- Update default config with auth_mode presets for codex and codex_oauth
- Add comprehensive tests for authentication modes and concurrent logging
* feat(file_store): implement background embedding backfill and keyword index repair
- Add _after_embedding_backfill hook in FAISS local file store
- Schedule startup embedding repair without delaying component readiness
- Cancel and collect embedding backfill task during component shutdown
- Log progress at fixed percentage boundaries for long-running operations
- Process embedding backfill in configurable batch sizes with progress reporting
- Rebuild keyword index in bounded batches with detailed mismatch diagnostics
- Format stdlib logs consistently with QwenPaw console output using relative paths
- Run embedding backfill as background task that doesn't block component startup
- Add comprehensive tests for background embedding and keyword index repair scenarios
* fix(file-store): repair graph-chunk consistency on load
- Add _repair_graph_chunk_consistency method to detect and fix mismatched graph/chunk states
- Clear torn graph/chunk state when missing or orphaned chunks are detected
- Ensure keyword index sync handles empty chunks properly
- Add comprehensive tests for graph-chunk consistency scenarios
- Update test utilities to properly seed graph/chunk snapshots
- Increment version to 0.4.1.2
* feat(file_io): enhance list step response format and add comprehensive logging
- Format list output with bullet points for better readability
- Add explicit "No files found" message when directory is empty
- Include detailed timing information for file store startup phases
- Add logging for chunk loading, graph consistency checks, and keyword indexing
- Provide detailed metrics for embedding backfill operations
- Add comprehensive test coverage for empty directory scenarios
- Include batch processing statistics for embedding operations
* feat(logger): add QwenPaw logging integration with forwarding mechanism
- Introduce _ForwardToLoggerHandler to forward log records to target logger
- Add qwenpaw logger integration that forwards ReMe logs to QwenPaw handlers
- Maintain ReMe logger stability for modules that cache it at import time
- Enable QwenPaw handlers to take effect without ReMe reconfiguration
- Add comprehensive tests for stdlib forwarding to QwenPaw sinks
- Support explicit REME_DISABLE_LOGURU=false to keep original Loguru backend
- Preserve existing logging behavior when QwenPaw is not configured
* fix(file_store): serialize concurrent FAISS dump operations to prevent corruption
- Add asyncio lock to ensure only one FAISS dump operation runs at a time
- Generate unique temporary filenames using UUID tokens for atomic replacement
- Implement proper cleanup of temporary files in finally block
- Add comprehensive test to verify concurrent dumps are serialized
- Ensure atomic writes by replacing both index and idmap files together
- Prevent partial state writes during concurrent access scenarios
- Removed max_file_bytes configuration from index_update_loop, resource_watch_loop, digest_watch_loop, and reindex jobs
- Updated default.yaml to reflect simplified job configurations without file size limits
- Removed corresponding test case that validated the 20 MiB limit behavior
- Simplified watch directories and suffixes to basic configurations
- Cleaned up unnecessary commented configurations in the YAML file
* feat(benchmark): add final answer review step for evaluation
- Introduce FinalAnswerReviewStep to handle answer validation
- Add final_answer_review.jsonl dataset with 24 evaluation cases
- Include detailed reasoning and golden check results for each case
- Support various question types including temporal reasoning and preferences
- Implement time consistency checks for session references
- Add comprehensive test coverage for different evaluation scenarios
* chore(benchmark): remove longmemeval final answer review file
- Removed final_answer_review.jsonl containing 23 evaluation records
- Deleted question_id mappings with detailed reasoning for golden answers
- Removed answer correctness assessments and session time validation checks
- Cleaned up benchmark dataset used for memory evaluation testing
- Eliminated JSONL format evaluation results for temporal reasoning tasks
- Removed references to various session IDs and time-based validations
* config(default): disable shell step configuration by commenting out
- Commented out the shell step configuration in default.yaml
- Disabled asynchronous shell command execution capability
- Removed shell step from available backend operations
- Preserved traverse backend configuration unchanged
* refactor(tests): remove unused shell job test from config parser tests
- Removed test_default_config_registers_shell_job function that was no longer needed
- Kept existing test for frontmatter chunk metadata configuration
- Cleaned up test suite by removing obsolete test case
* feat(index): add file size limits and oversized file handling
- Implement max_file_bytes configuration option for content processing jobs
- Add default 20MB file size limit for background processing in default config
- Skip oversized files during auto_resource step with appropriate metadata
- Clear stale index entries when oversized files are modified
- Add size-based filtering logic to update_changes step with skip reporting
- Include file size validation in UpdateIndexStep with proper response handling
- Add comprehensive tests for oversized file scenarios in auto_resource and update_index
- Document file size limits in constants with appropriate thresholds
* chore(version): bump version to 0.4.1.1
- Update __version__ from 0.4.1.0 to 0.4.1.1 in __init__.py
* fix(index): isolate batch metadata and handle file races
- Changed dimensions property to avoid forcing provider construction
- Added _ensure_model method to construct provider on demand
- Modified __call__ to ensure model exists before use
- Updated _start to defer provider initialization
- Removed eager health check during startup
- Added compact embedding serialization with base64 encoding
- Implemented batch processing for vector search with heap-based ranking
- Added document_ids property to keyword index interface
- Updated chunk persistence to handle legacy JSON embeddings
- Optimized memory usage by avoiding materialization of metadata in document_ids
* feat(core): add shell command execution and memory status reporting
- Introduce ShellStep for executing shell commands with timeout support
- Add StatusStep to report memory estimates for stateful data components
- Register shell and status commands in default configuration
- Update documentation with new reme status and shell command capabilities
- Implement comprehensive unit tests for both new step types
- Add support for asynchronous command execution with proper error handling
* feat(config): add log_config option to suppress config loading logs
- Add log_config parameter to resolve_app_config function with default True
- Conditionally log config loading messages based on log_config flag
- Update reme.py and service_utils.py to use log_config=False for client calls
- Suppress config logging in user-facing contexts to avoid output pollution
refactor(shell): rename command parameter to cmd for clarity
- Change 'command' to 'cmd' in default.yaml configuration schema
- Rename 'timeout' to 'shell_timeout' to avoid parameter name collisions
- Update ShellStep to accept both legacy and new parameter names
- Maintain backward compatibility with existing command/timeout usage
test(shell): add comprehensive tests for shell step parameter handling
- Add test cases for new cmd and shell_timeout parameter names
- Verify legacy command and timeout parameters still work
- Test blank command rejection message updated to use cmd
- Create integration test for shell parameter payload passing
* fix(shell): ensure proper environment loading and process timeout handling
- Move load_env() call to execute before parse_args() in main function
- Add proper process group killing for timeout scenarios on POSIX systems
- Implement recursive child process termination on Windows for proper cleanup
- Change parameter name from 'timeout' to 'shell_timeout' in shell execution
- Remove support for legacy 'command' and 'timeout' parameter names
- Update test cases to verify new timeout behavior and parameter requirements
- Add comments explaining component size tracking implementation details
* feat(benchmark): add golden answer validation and session review for LongMemEval
- Introduce GoldenCheckStep to validate LongMemEval golden answers using structured verdicts
- Add SessionReviewStep to extract query/answer-relevant evidence from all sessions
- Implement concurrent session processing with configurable concurrency limits
- Create check_golden job configuration with lme_review and lme_judge agent wrappers
- Add Qwen3.7-plus model configuration for enhanced processing capabilities
- Include python_execute tool integration for agent-based reasoning and date validation
- Generate comprehensive JSON output with session summaries and validation verdicts
- Add run_check_golden.py script for batch processing across all LongMemEval samples
- Configure proper logging initialization with console and file output options
- Update component registry and file I/O modules to support new benchmark features
* feat(scripts): add script to summarize LongMemEval check_golden verdicts
- Parse check_golden.json files across all LongMemEval samples
- Calculate accuracy metrics for golden answers and session IDs
- Provide breakdown by question type with percentage calculations
- Add command line options for listing bad samples and JSON output
- Include progress tracking showing completed vs pending samples
- Display confidence scores and date sanity checks statistics
* refactor(benchmark): move golden check scripts to longmemeval directory
- Moved run_check_golden.py from scripts/ to benchmark/longmemeval/
- Moved stats_check_golden.py from scripts/ to benchmark/longmemeval/
- Updated path resolution to use parents[2] instead of parent.parent
- Added new --list-run-failed option to stats script
- Added logging directory constant and functions for tracking launched samples
- Enhanced stats output with launched count and run failure information
- Improved error reporting with run failure details and log file paths
* feat(benchmark): add LongMemEval agentic answer workflow with session extraction
- Add LmeAgenticAnswerStep, LmeAutoMemoryStep, and LmeExtractSessionStep to __init__.py
- Create shared helper render_with_source for displaying search results with session_id
- Implement agentic_answer step with vector_search, bm25_search, and extract_session_by_id tools
- Add auto_memory step to convert each session into search-friendly daily notes
- Create extract_session step to retrieve and analyze raw session content by session_id
- Update jinli_lme.yaml with auto_memory, vector_search, bm25_search, and agentic_answer jobs
- Configure lme_memory, lme_extract, and lme_agentic_answer agent wrappers
- Enhance search steps with include_source option to show session_id metadata
- Add proper session_id tracking and collision handling in daily note generation
* feat(benchmark): add LongMemEval agentic answer evaluation pipeline
- Add session_id tracking to agentic_answer.py result metadata
- Introduce run_agentic_answer.py driver for complete pipeline execution
- Implement auto_memory, update_index, and agentic_answer job orchestration
- Add concurrent execution with configurable limits and staggering
- Create aggregation script for collecting tool-call trails and results
- Add stats_agentic_answer.py for comprehensive result analysis
- Implement resume capability with existing output detection
- Generate aggregate.json with per-sample breakdown and tool call summaries
* feat(steps): add ClearPathsStep for cleaning workspace outputs before rebuild
- Introduce ClearPathsStep to remove stale workspace files/directories
- Add support for specifying paths and config_keys as targets to clear
- Implement safety checks to prevent deletion of files outside workspace
- Add logging for cleared paths and warnings for invalid paths
- Configure clear_paths_step in jinli_lme.yaml to clean daily_dir
- Add clear_paths_step to clean mem_answer.json before rebuilds
* feat(benchmark): add resume functionality to agentic answer runner
- Replace --force flag with --resume flag for controlling job execution
- By default every job reruns with clean rebuild behavior using config clear steps
- Add --resume option to skip samples whose output already exists and continue interrupted batches
- Update documentation to reflect new default clean rebuild behavior
- Modify job skipping logic to honor resume flag instead of force flag
- Update dry-run output to show correct todo jobs based on resume status
- Change default example command to use --resume for continuing interrupted runs
* feat(benchmark): generate JSONL output for check golden records
- Add write_check_golden_list function to create JSONL file
- Write all readable check_golden records as JSONL format
- Include check_golden_list path in stats output
- Display generated JSONL file path in summary report
- Maintain UTF-8 encoding with non-ASCII character support
* refactor(benchmark): rename answer judge step and integrate LME LLM judge
- Rename AnswerJudgeStep to LmeLlmJudgeStep and update imports
- Add new llm_judge configuration in jinli_lme.yaml
- Update run_agentic_answer.py to include llm_judge in pipeline
- Modify LmeLlmJudgeStep to read from query.json and answer.json
- Write LLM judgement results back to mem_answer.json
- Add command line options for start/end sample range selection
- Update aggregate.json generation to include LLM judgement data
- Add resume capability for llm_judge job based on judgement presence
* refactor(benchmark): rename answer judge step and integrate LME LLM judge
- Rename AnswerJudgeStep to LmeLlmJudgeStep and update imports
- Add new llm_judge configuration in jinli_lme.yaml
- Update run_agentic_answer.py to include llm_judge in pipeline
- Modify LmeLlmJudgeStep to read from query.json and answer.json
- Write LLM judgement results back to mem_answer.json
- Add command line options for start/end sample range selection
- Update aggregate.json generation to include LLM judgement data
- Add resume capability for llm_judge job based on judgement presence
* feat(steps): add wait_for_paths_step to block until workspace files exist
- Introduce WaitForPathsStep class that polls for required workspace-relative paths
- Add step registration with 'wait_for_paths_step' backend identifier
- Implement path validation to ensure targets are within workspace boundaries
- Add polling mechanism with configurable intervals via poll_seconds parameter
- Include logging functionality with log_every_seconds parameter for status updates
- Add metadata tracking of waited paths and duration in response object
- Register step in index module and expose in public API
- Configure step in jinli_lme.yaml to wait for session_review.json before golden check
- Add script rename from run_check_golden.py to run_golden_check.py with enhanced options
* feat(benchmark): enhance longmemeval benchmarking with concurrency and progress tracking
- Add benchmark extra dependency group with portalocker requirement
- Introduce concurrent execution support for golden_check and session_review workflows
- Add progress reporting interval option with real-time status updates
- Implement global throttling mechanism for session review requests using file locks
- Enhance golden check validation with current schema verification
- Add active task tracking and graceful shutdown handling
- Rename check_golden scripts to golden_check for consistency
- Update statistics reporting with correct/incorrect terminology instead of reasonable
- Add stale format detection and compatibility handling for verdict fields
- Include both_correct rate calculation in accuracy metrics
- Add concurrency and staggering options for better resource management
* ci(workflow): add Windows smoke test workflow
- Create new workflow file .github/workflows/windows-smoke.yml
- Configure workflow to trigger on push and pull request events
- Set up Python environment with version 3.11
- Install package dependencies using pip
- Run version job as smoke test for CLI functionality
- Enable concurrency control to prevent duplicate runs
- Use matrix strategy for Python version testing
* feat(benchmark): add retry mechanism and health check for session review
- Added retry configuration options (retry_initial_seconds, retry_max_seconds, retry_max_attempts) to jinli_lme.yaml
- Implemented exponential backoff retry logic with configurable parameters in session_review step
- Added output_is_healthy function to verify session_review.json integrity and absence of failed reviews
- Updated resume functionality to skip only healthy outputs instead of all existing files
- Integrated JSON parsing and validation to check for failed reviews in output files
- Enhanced error handling and logging for retry attempts and recovery scenarios
* feat(benchmark): add LongMemEval session review statistics script
- Create stats_session_review.py to summarize session_review.json artifacts
- Add command line options for listing failed, missing, and run failed samples
- Implement JSON output mode for programmatic consumption
- Calculate and display health statistics including total samples, healthy outputs, failed sessions
- Provide detailed failure information with session IDs and error messages
- Generate re-run commands for samples with failed reviews
- Add percentage calculations for better statistical overview
- Include support for multiple output formats and detailed logging
* feat(benchmark): add LongMemEval output cleanup script and enhance golden check retry logic
- Added clean_sample_outputs.py script to remove generated LongMemEval files while preserving source inputs
- Implemented configurable retry mechanism in golden_check.py with exponential backoff strategy
- Added retry parameters (initial/max seconds and max attempts) to control failure recovery behavior
- Integrated asyncio support for asynchronous sleep during retry intervals
- Configured default retry settings in jinli_lme.yaml with 5s initial and 300s maximum intervals
- Preserved core files (query.json, answer.json, session/) while cleaning generated artifacts
* feat(benchmark): add AppleDouble file cleanup to sample output cleaner
- Remove AppleDouble files starting with '._' recursively including under session/
- Add is_under helper function to check if path is inside parent directory
- Track targets in set to avoid duplicate processing
- Include AppleDouble files in cleanup targets when not already covered by existing targets
- Maintain dry-run mode as default behavior with --apply flag for actual deletion
* refactor(benchmark): update LongMemEval sample output cleaning script
- Add time and Iterator imports for enhanced functionality
- Add --progress-every argument to control progress reporting frequency
- Replace is_under function with iter_sample_targets generator
- Implement detailed progress tracking with timing measurements
- Add sample-by-sample processing with elapsed time reporting
- Include AppleDouble file detection within session directory
- Update target counting and deletion statistics display
- Add conditional progress updates based on progress-every setting
- Improve dry-run mode with would-delete indication
* chore(benchmark): increase initial interval for session review step
- Changed START_INTERVAL_SECONDS from 1.0 to 3.0 seconds
- Adjusted timing parameters for better benchmark stability
* refactor(benchmark): implement coordinated retry mechanism for session reviews
- Add retry gate condition to coordinate concurrent review attempts
- Implement wait_for_healthy_start_slot to handle sequential retries
- Create mark_retrying and mark_recovered functions to track retry states
- Update reply_with_retry to accept index parameter for coordination
- Add has_prior_retry logic to prevent race conditions during recovery
- Ensure proper cleanup of retry state on success or failure
- Maintain backward compatibility while adding coordination features
* chore(benchmark): adjust session review start interval timeout
- Changed START_INTERVAL_SECONDS from 3.0 to 5.0 seconds
- Increased initial delay for session review benchmark step
- Updated timeout configuration for improved stability
* refactor(benchmark): update session review concurrency and throttling mechanism
- Replace global throttle with per-process concurrency control
- Add concurrency parameter with default value of 30 in config
- Add start_interval_seconds parameter with default value of 2 seconds
- Change default concurrency from 3 to 1 in command line interface
- Update documentation to reflect new throttling behavior
- Implement semaphore-based concurrency limiting for review tasks
- Modify retry mechanism to use local locking instead of global files
- Remove portalocker dependency for cross-process throttling
* refactor(config): update session review configuration and concurrency settings
- Removed deprecated retry configuration parameters from jinli_lme.yaml
- Increased MAX_CONCURRENCY from 30 to 60 in session_review.py
- Reduced START_INTERVAL_SECONDS from 2.0 to 1.0 in session_review.py
- Cleaned up redundant backend specifications in configuration file
- Simplified agent wrapper configurations by removing obsolete retry settings
* feat(benchmark): enhance LME auto memory step with advanced scheduling and error handling
- Add datetime parsing functionality for LongMemEval timestamps with regex pattern
- Implement configurable concurrency limits with MAX_CONCURRENCY of 60
- Introduce retry mechanism with exponential backoff for agent interactions
- Add session filtering based on date comparison with question_date validation
- Create rate limiting with start interval control between requests
- Implement sophisticated retry coordination using asyncio conditions
- Add comprehensive error tracking for failed and filtered session extracts
- Remove deprecated concurrency parameter from jinli_lme.yaml configuration
- Add structured output validation in session review step
- Include detailed metadata reporting with session statistics and errors
* fix(benchmark): adjust default concurrency for auto_memory job
- Changed default concurrency from 3 to 1 for auto_memory job to prevent API overload
- Updated help text to reflect new default value of 1 for concurrency parameter
- Modified documentation to clarify concurrency behavior varies by job type
* refactor(search): replace hardcoded candidate multiplier with constant
- Introduced _CANDIDATE_MULTIPLIER constant set to 10
- Replaced hardcoded factor of 5 with _CANDIDATE_MULTIPLIER in BM25 search
- Replaced hardcoded factor of 5 with _CANDIDATE_MULTIPLIER in vector search
- Updated test to verify both search steps use ten times limit for candidates
- Imported VectorSearchStep and Bm25SearchStep in test module
- Added comprehensive test case for candidate count calculation logic
* feat(lme): add data inspection error handling with fallback mechanism
- Implemented non-retryable data inspection error markers detection
- Added _is_data_inspection_error method to identify inspection failures
- Created fallback handling for data inspection errors in auto memory extraction
- Added fallback handling for data inspection errors in session review
- Extended failed extracts tracking with non-retryable and fallback flags
- Separated fallback extracts from regular failed extracts in reporting
- Enhanced error logging with specific data inspection failure messages
- Updated metrics to track fallback extractions and reviews separately
- Maintained existing retry logic for other exception types
* feat(benchmark): enhance session review statistics with fallback tracking
- Add support for identifying and listing non-retryable fallback reviews
- Introduce --list-fallback argument to display fallback review details
- Separate retryable failures from non-retryable fallbacks in reporting
- Track fallback samples and sessions separately from failed ones
- Update console output to show both retryable and non-retryable categories
- Include fallback details in JSON output with reasons and session info
- Modify failure counting logic to distinguish between retryable and fallback reviews
* feat(benchmark): add question_id tracking and enhanced fallback reporting
- Add question_id function to extract query.question_id from data
- Initialize question_id_by_id dictionary to store question IDs by index
- Store question_id for each sample during data processing
- Enhance fallback output to include question IDs and session information
- Format sample labels with question IDs when available
- Display session IDs associated with each fallback case
* feat(benchmark): add question_id support and improve bad sample reporting
- Add question_id_for function to extract question_id from multiple sources
- Add sample_label function to format samples as idx(question_id) when available
- Store question_id in data dictionary during processing
- Change bad_golden and bad_sessions to store full records instead of just indices
- Update list_bad output to show formatted labels with question_id information
- Improve error reporting with more detailed sample identification
* feat(benchmark): enhance golden check stats with structured output
- Add related_session_ids function to extract session IDs from verdict records
- Create grouped_records function to group records by question type
- Replace flat list output with JSON-formatted grouped records in list_bad option
- Replace flat list output with JSON-formatted grouped records in list_bad_sessions option
- Maintain Chinese labels while adding structured data presentation
- Improve readability of bad verdict record display with hierarchical grouping
* feat(benchmark): update data structure for question indexing
- Replace sample_label with _idx field for index tracking
- Add question_id field to store _question_id values
- Maintain backward compatibility with empty string defaults
- Preserve existing session_id functionality
- Update data mapping to include new fields in grouped results
* refactor(benchmark): streamline golden answer verification process
- Replace relevance filtering with comprehensive information extraction
- Remove is_relevant field and simplify session summary structure
- Change relevant_info to extracted_info for clarity
- Update golden check logic to work with full extractions instead of filtered summaries
- Simplify prompt instructions to focus on complete information extraction
- Remove redundant schema validation and structured output requirements
- Adjust statistics calculation to match new extraction approach
- Update metadata field names to reflect extraction rather than relevance checking
* feat(benchmark): add selective file deletion option to clean_sample_outputs
- Add --filename argument to delete only specific root-level files
- Modify iter_sample_targets function to accept optional filenames filter
- Implement validation for root-level filename constraints
- Update function calls to pass filenames parameter
- Add example usage for selective file deletion in documentation
* feat(benchmark): add error count metrics to golden check statistics
- Added golden_bad, session_bad, and both_bad calculation fields
- Updated console output format to include error counts per question type
- Modified table display to show both accuracy rates and error numbers
- Enhanced statistical summary with additional error breakdown metrics
* test(search): update search step tests with include_source parameter
- Added include_source=False parameter to VectorSearchStep initialization
- Added include_source=False parameter to Bm25SearchStep initialization
- Maintained existing RuntimeContext parameters for both search steps
- Updated test calls to match new constructor signature with include_source option
- Set default version to 0.4.1.0
- Comment out embedding configuration in default.yaml
- Update README and README_ZH to clarify embedding components are disabled by default
- Add note explaining how to enable embedding-based semantic retrieval
- Adjust table formatting and descriptions in documentation
- Modify search command description to reflect vector search availability when enabled
* feat(service): add CLI service for local job execution
- Introduce CliService to execute single jobs locally without serving ports
- Add prepare_start_config and should_precheck_start functions for CLI job setup
- Update reme start command to use CLI service when job argument is provided
- Change default service backend from http to cli in jinli_lme config
- Modify SearchStep to use constants and rename configuration parameters
- Add unit tests for CLI service functionality and configuration handling
- Update file extension support to include json format in addition to md and jsonl
* feat(search): add BM25 and vector search steps with configuration updates
- Add Bm25SearchStep and VectorSearchStep classes with tool context deduplication
- Register new search step components in index module
- Update configuration to use separate vector_search and bm25_search endpoints
- Modify LLM models from qwen3.7-plus/glm-5.1 to glm-5.2 variants
- Adjust search parameters and remove hybrid search implementation
- Configure embedding store as default in storage settings
- Remove auto-memory and file catalog configurations
- Update watch directories from multiple paths to session_dir only
* feat(agent): add tool result offloading and workspace management
- Add tool_results_dir configuration option for offloaded tool results storage
- Implement ToolResultOffloadMiddleware to persist large tool results to files
- Create WorkspaceBackend to standardize file operations across tools
- Add configurable builtin tools selection with sequential execution option
- Integrate middleware support for agent wrapper with offloading capability
- Update application initialization to create tool results directory
- Add safety mechanisms for filesystem operations with sanitized filenames
- Enhance agent wrapper with configurable working directory handling
- Upgrade agentscope dependency to version 2.0.4 for improved features
# Conflicts:
# reme/application.py
* feat(benchmark): add LongMemEval agentic search and result management
- Introduce AgenticAnswerStep for agent-based history search
- Add LmePrepareJudgeStep and LmeSaveResultStep for evaluation pipeline
- Implement AddDraftStep and ReadAllDraftStep for evidence accumulation
- Update configuration with new agent wrapper and search parameters
- Add comparison script for analyzing agent run differences
- Include documentation for LongMemEval failure analysis
- Enhance tool result offloading with skip options
- Modify search defaults and indexing behavior
* feat(agent): implement tool result offloading with system reminders
- Added tool_result_offload_message parameter to agent wrapper reply method
- Implemented configurable reminder template for offloaded tool results
- Created system reminder messages when tool results are offloaded to files
- Added Chinese user message template for agentic answer step
- Updated tool result offloading middleware to use custom reminder templates
- Enhanced agentic answer instructions to handle long tool results via draft storage
* feat(scripts): add LongMemEval results summarization tool
- Create summarize_lme_results.py script to analyze result JSON files
- Implement command line interface with answer id and dataset root options
- Add support for specifying index range with start and end parameters
- Include option to show failure details and non-successful completions
- Calculate completion statistics and accuracy metrics
- Display detailed breakdown of yes/no/other judgements
- Handle missing and unreadable result files gracefully
- Format output with percentages and comprehensive summary statistics
* feat(summarize_lme_results): add question type breakdown to result summary
- Import defaultdict from collections module
- Add by_type dictionary to track statistics by question type
- Count completed, yes, no, and other responses for each question type
- Display detailed breakdown table showing accuracy by question type
- Include question type column when processing judgements
- Print comprehensive summary with question type distribution
- Calculate and display accuracy percentage for each question type category
* feat(lme): switch to qwen3.7-max model and add shuffle functionality
- Changed default LLM model from glm-5.1 to qwen3.7-max in jinli_lme.yaml
- Added random module import for shuffle functionality
- Implemented --shuffle argument with BooleanOptionalAction for dataset shuffling
- Added --seed argument to control random seed for reproducible shuffling
- Applied random shuffle to dataset indices when shuffle is enabled
- Added console output showing shuffle operation and seed information
* fix(cli): set default random seed for shuffle functionality
- Changed default seed value from None to 42 for consistent shuffling behavior
- Ensures reproducible results when using shuffle option without explicit seed
- Maintains backward compatibility while providing deterministic defaults
* refactor(benchmark): update agentic answer guidelines for grounding
- Updated English instruction to emphasize strict grounding in retrieved context
- Modified Chinese instruction to stress evidence-based responses without inference
- Removed redundant conciseness requirement in both language versions
- Enhanced clarity on proper use of draft saving and retrieval mechanisms
- Strengthened emphasis against hallucination of unsupported facts
* refactor(benchmark): update agentic search instructions and configuration
- Replace separate vector_search and bm25_search with unified search tool
- Update agent instructions to use single search tool with multiple strategies
- Simplify Chinese instructions for search methodology
- Add comprehensive search tool configuration with hybrid vector/BM25 capabilities
- Increase model retry attempts from 1 to 3 for better reliability
- Remove redundant tool references from job_tools list
* feat(search): add configurable search limit with environment variable support
- Remove hardcoded limit and min_score parameters from config schema
- Increase LLM context size from 200000 to 1000000
- Add REME_SEARCH_LIMIT environment variable support for search configuration
- Implement command line argument --search-limit to override default search limit
- Add input validation to ensure search limit is positive
- Modify subprocess execution to pass environment variables
- Update search step to use dynamic default limit from environment or fallback to 5
* refactor(benchmark): remove agentic answer step and related configurations
- Removed AgenticAnswerStep class and its registration
- Deleted agentic_answer.yaml prompt configuration file
- Removed agentic answer related job definitions from jinli_lme.yaml
- Cleaned up tool result offloading middleware implementation
- Removed tool_results_dir configuration field from application config
- Deleted comparison and analysis scripts for agent runs
- Removed agentic answer step from LME init module exports
- Updated agent wrapper to remove tool result offloading functionality
- Removed unused imports and dependencies in agent wrapper module
* refactor(benchmark): remove unused LME result processing components
- Removed LmePrepareJudgeStep and LmeSaveResultStep classes from benchmark module
- Cleaned up imports and exports in lme module initialization
- Removed unused middleware configuration from agent wrapper
- Deleted obsolete result.py file containing deprecated result processing logic
- Simplified agent instantiation by removing middleware parameter
- Updated import statements to reflect removed dependencies
* refactor(index): remove unused search steps and update imports
- Remove Bm25SearchStep and VectorSearchStep from index steps module
- Remove unused prepare_start_config and should_precheck_start exports
- Move import statements to proper location in reme.py
- Update test module to use direct import path for CliService
- Remove vector_search and bm25_search configurations from jinli_lme.yaml
- Add workspace directory environment variable configuration
- Add docstring to getcwd method in agent wrapper
- Remove empty middleware list from agent wrapper initialization
* feat(index): add BM25 and vector search steps with tool context deduplication
- Add Bm25SearchStep for plain BM25 keyword search with tool_context deduplication
- Add VectorSearchStep for plain vector search with tool_context deduplication
- Implement tool context state management with TTL-based deduplication
- Add support for chunk deduplication across tool contexts within TTL window
- Update index steps module to include new search step classes
- Add test coverage for CLI metadata output functionality
- Refactor CLI service to remove unused show_status parameter
- Update documentation comments to reflect internal service configuration
* feat(steps): add Python code execution capability
- Introduce PythonExecuteStep to run Python code in subprocess
- Add configuration for python_execute step in jinli_lme.yaml
- Register python_execute in available tools list
- Implement timeout handling with default 60 second limit
- Capture stdout/stderr output and return code metadata
- Add comprehensive unit tests for execution scenarios
- Support workspace directory context for code execution
- Handle timeout errors and runtime exceptions gracefully
* refactor(python_execute): replace subprocess with asyncio for Python code execution
- Replace subprocess.run with asyncio.create_subprocess_exec for non-blocking execution
- Add _PythonResult dataclass to encapsulate execution results and timeout status
- Implement proper timeout handling with asyncio.wait_for and process.kill()
- Update metadata to include returncode and stderr when timeout occurs
- Convert synchronous _run_python method to asynchronous implementation
- Maintain backward compatibility while improving execution reliability
* refactor(python_execute): replace subprocess with asyncio for Python code execution
- Replace subprocess.run with asyncio.create_subprocess_exec for non-blocking execution
- Add _PythonResult dataclass to encapsulate execution results and timeout status
- Implement proper timeout handling with asyncio.wait_for and process.kill()
- Update metadata to include returncode and stderr when timeout occurs
- Convert synchronous _run_python method to asynchronous implementation
- Maintain backward compatibility while improving execution reliability
* fix(embedding): enforce strict dimension matching for embeddings
- Add _embedding_dim_matches method to validate embedding dimensions
- Reject embeddings with mismatched dimensions instead of padding/truncating
- Drop stale embeddings with wrong dimensions during loading and upsert operations
- Disable embedding store when query dimensions don't match configured dimensions
- Fail health checks when embedding dimensions don't match expected values
- Skip chunks with wrong dimensions during FAISS index rebuild
- Add comprehensive tests for dimension validation behavior
* refactor(file_store): simplify conditional checks in vector search and test assertions
- Combine multiple conditionals into single check for empty FAISS index
- Replace explicit empty list comparison with boolean check for node embedding calls
- Maintain same functional behavior while improving code readability
* fix(embedding): harden dimension validation helpers
* refactor(embedding): update embedding model initialization and session storage paths
- Remove unused inspect import from as_embedding module
- Pass dimensions directly to embedding model constructor instead of using parameters
- Update session state file paths to use mem_session directory instead of resource
- Add mem_session_dir configuration option to application config schema
- Update workspace directory creation to include new mem_session directory
- Change AgentScope and Claude Code session paths to use mem_session directory
- Move embedding dimensions from parameters to top-level configuration
- Update AgentScope dependency version from 2.0.3 to 2.0.4
- Update integration tests to reflect new session file location paths
* chore(version): bump version to 0.4.0.8
- Update __version__ from 0.4.0.7 to 0.4.0.8 in __init__.py
* refactor(search): replace time module with datetime for timestamp generation
- Removed unused time import
- Added static method _now_ts using datetime.timestamp
- Updated clock parameter to use _now_ts method instead of time.time
- Maintained same timestamp precision and functionality
* test(http): add tests for HTTP client display formatting
- Add test for default metadata hiding behavior in CLI output
- Add test for metadata display when show_metadata is enabled
- Verify _format_for_display method correctly formats response text
- Test both success case and metadata inclusion scenarios
* chore(build): remove longmemeval from gitignore
- Removed longmemeval directory from gitignore list
- Kept evaluation and datasets directories in ignore list
- Updated gitignore configuration for proper version control
2.0.3 promoted `dimensions` to a required first-class constructor
argument while keeping a backfill from `parameters.dimensions`; 2.0.2
has no such argument and reads `dimensions` from `Parameters`. Keep
`dimensions` in `Parameters` for both versions and, when the model
constructor accepts `dimensions`, pass `dimensions=None` so 2.0.3's
backfill promotes it out of `parameters`.
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
* feat(search): add tool context deduplication and improve search configuration
- Modify _make_tool methods to accept and inject tool_context_id parameter
- Add tool_context_id handling in AS and CC agent wrappers
- Increase search candidate multiplier from 3.0 to 5.0 in default config
- Extend HTTP client timeout from 30s to 3600s
- Add tool context deduplication logic to prevent duplicate search results
- Implement TTL-based expiration for seen chunks in tool contexts
- Add comprehensive unit tests for tool context deduplication behavior
- Update .gitignore to exclude longmemeval directory
- Add time import for timestamp functionality in search step
* refactor(search): replace time module with datetime for timestamp generation
- Removed unused time import
- Added static method _now_ts using datetime.timestamp
- Updated clock parameter to use _now_ts method instead of time.time
- Maintained same timestamp precision and functionality
* feat: add start_date/end_date time filter support for search job
- Add _extract_date_from_path to extract validated YYYY-MM-DD from chunk paths
- Add start_date/end_date filtering in _matches_search_filter
- Implement progressive recall in FaissLocalFileStore.vector_search
- Promote start_date/end_date from context to search_filter in SearchStep
- Add start_date/end_date parameters to search job in default.yaml
- Add unit tests for date filter functionality
* fix: validate/normalize date filters and harden _extract_date_from_path
Address three code-review comments on the time_filter search feature:
1. Validate/normalize start_date and end_date before string comparison.
_matches_search_filter does lexicographic comparison against path_date
(always canonical YYYY-MM-DD). Raw caller values like '2026-2-28' or
'abc' would produce silently wrong results. Now SearchStep normalizes
valid dates via extract_daily_date (with strptime fallback for
non-zero-padded input) and silently ignores invalid dates with a
logger.warning, removing them from the filter.
2. Clarify behavior for paths without embedded dates.
Added optional strict_date_filter parameter (default False). When True
and at least one date bound is active, chunks whose path yields no date
(e.g. digest/personal/topic.md) are excluded. When False (default),
the existing behavior is preserved — dateless paths pass through.
3. Harden _extract_date_from_path against non-standard suffixes.
Previously parts[1].split('.')[0] accepted '2026-05-18.anything' as a
valid date. Now only exact 'YYYY-MM-DD' (dir) and 'YYYY-MM-DD.md'
(day-index) forms are accepted.
call_server now resolves the client backend/transport/host/port from the
live `reme start` process (replaying its start args through
resolve_app_config) so a bare `reme <action>` reaches the server however
it was actually launched, falling back to local config when none runs.
Explicit backend=/transport=/host=/port= still win.
Also fix as_embedding to pass `dimensions` explicitly for agentscope
>=2.0.2, and add Claude Code auto-memory/auto-dream demos to the READMEs.
* fix(auto-memory): preserve message timestamps
* fix(auto-memory): infer daily date from messages
* feat(file_io): add strict date parsing and improve daily date handling
- Add new parse_daily_date function for strict YYYY-MM-DD validation
- Replace extract_daily_date with parse_daily_date for explicit date validation
- Change _messages_day to use max date instead of min for historical imports
- Reorder imports to maintain consistent module ordering
- Move session message saving after date validation in auto_memory
- Add comprehensive tests for invalid date rejection before saving
- Add tests for strict YYYY-MM-DD date format validation
- Update test names to reflect latest date behavior
---------
Co-authored-by: Ziyang Guo <121015044+RunMarshal@users.noreply.github.com>
Co-authored-by: jinli.yl <jinli.yl@alibaba-inc.com>
* refactor(transfer): drop orphaned ingest step, make service discovery cross-platform
- Remove ingest step: superseded by auto_resource (drop files under
resource/ → watcher interprets them); its meta.json/<date>.md outputs
had no consumers and tripped the auto_resource watcher.
- Replace lsof/pgrep shell-outs in service_utils with psutil (per-process
enumeration, no root needed on macOS) for Windows/macOS/Linux support.
- Add cross-platform test coverage for _pid_on_port / _scan_reme_procs.
- Deps: +psutil, -filelock (only used by the removed ingest lock).
* chore(release): bump version to 0.4.0.5
* fix(mcp): resolve circular import issues and update dependencies
- Moved fastmcp imports inside functions to prevent circular dependencies
- Replaced _TRANSPORT_MAP with _VALID_TRANSPORTS set for transport validation
- Updated version number from 0.4.0.3 to 0.4.0.4
- Added claude-agent-sdk dependency to core optional dependencies
- Used TYPE_CHECKING imports for FastMCP related types
- Restructured transport mapping logic within function scope
- Fixed string annotation for CallToolResult type hints
* refactor(tests): update date handling in daily steps tests
- Replace _date.today() with timezone-aware now function
- Use Asia/Shanghai timezone for date formatting
- Change return format to use strftime instead of isoformat
- Import now function from reme.steps.evolve module
* refactor(tests): clean up unused imports in daily steps test
- Removed unused date import from datetime module
- Removed redundant pathlib Path import that was already imported later
- Kept necessary imports for asyncio, os, tempfile, warnings, and frontmatter modules
* test(daily_steps): update test to include application context for daily list step
- Add ApplicationContext initialization with temporary workspace directory
- Register file store component in application context
- Pass application context to DailyListStep constructor
- Maintain existing test assertion behavior for date metadata verification
* feat(file_io): add daily_write step for creating daily notes with conversation metadata
- Add DailyWriteStep class that delegates to write job for creating daily notes
- Register daily_write job in default configuration with proper parameters
- Include validation for name and session_id path components
- Add test coverage for daily_write functionality including metadata handling
- Preserve existing job execution method in application.py after repositioning
- Update base_step.py to use positional-only parameter syntax for job methods
- Import and expose DailyWriteStep in file_io module initialization
- Override reserved metadata keys (name, description, session_id, source_conversation) with fixed values
- Refresh daily index after successful write operation
- Generate proper source conversation links in markdown format
* feat(daily): refactor daily note system with enhanced metadata handling
- Introduce validate_filename_component function and export it
- Add _INDEX_HIDDEN_METADATA_KEYS to hide conversation metadata from index
- Update scan_notes to exclude hidden metadata keys from index rendering
- Modify auto_memory to use daily_write tool and manage session frontmatter
- Implement session note lookup and renaming based on frontmatter name
- Update daily_list to return flattened note metadata including session info
- Change daily_write to dispatch write step instead of running job
- Add test cases for updated daily note functionality and metadata handling
- Update version from 0.4.0.2 to 0.4.0.3
* fix(evolve): correct metadata update in auto memory response
- Fixed trailing comma issue in metadata dictionary update
- Ensured proper formatting of response metadata structure
- Maintained existing functionality while fixing syntax error
* refactor(auto_resource): replace daily_create with dynamic note management
- Remove DailyCreateStep and related exports from file_io module
- Replace static daily note creation with dynamic resource-linked card system
- Implement LLM-suggested naming with frontmatter-driven file management
- Add source_resource linking for tracking original files
- Introduce collision handling with hash-based suffixes
- Update documentation to reflect new resource card workflow
- Modify auto_resource prompts to use write/edit tools instead of daily_create
- Adjust test fixture comments to match new agent behavior
- Update framework diagrams and quick start examples accordingly
* feat(app): add version info to app initialization and update auto-memory logic
- Include version number in application startup logging
- Remove tool result truncation logic from auto-memory step
- Update auto-memory to exclude tool_result blocks from saved history
- Add test case to verify tool results are filtered out from message saving
- Update YAML prompts to clarify filename naming rules without dates
- Modify configuration to support new dispatch steps format with persistence control
* feat(auto_memory): add note modification tracking and optimize frontmatter updates
- Add _note_bytes and _note_modified methods to track actual file changes
- Optimize frontmatter updates by checking existing metadata before update
- Add modified flag to response metadata indicating actual note changes
- Update logging to include modified status in various operations
- Add comprehensive tests for modified/unmodified detection scenarios
- Enhance result hook logic to skip when no actual changes occur
- Refactor metadata handling to properly track creation vs modification status
* feat(evolve): enhance agent reply processing and logging capabilities
- Add agent_reply_result_text function to extract final user-visible text from agent replies
- Implement comprehensive logging throughout auto_memory, auto_resource, and dream modules
- Add max_units configuration option to limit extracted memory units
- Improve error handling and validation in auto_resource step
- Refactor dream extract step to respect max_units limit during processing
- Enhance summary rendering in dream finish step with detailed breakdown
- Add result hook functionality for embedding hosts integration
- Implement loose resource filename handling for root-level resources
- Update test cases to reflect new functionality and improved error messages
* test(background-steps): update fake upsert function to include created parameter
- Modified fake_upsert function to accept 'created' parameter instead of '_created'
- Added 'created' field to captured dictionary in fake_upsert function
- Included 'created': True in the expected response dictionary for test case
- Updated test assertion to match new parameter structure
- Implement _backfill_missing_embeddings method to handle chunks without embeddings
- Add logic to identify and process chunks that predate embedding feature
- Integrate backfill process into store loading sequence
- Add proper error handling and logging for backfill operations
- Create unit test for embedding backfill functionality
- Ensure backfilled embeddings are properly persisted to storage
* chore(logging): change info logs to debug level for data loading operations
- Changed stopwords loading log from info to debug level
- Changed file catalog nodes loading log from info to debug level
- Changed file graph nodes loading log from info to debug level
* feat(dream): add dream schema definitions and enum for auto-dream functionality
- Add DreamBucketEnum with procedure, personal, and wiki values
- Create comprehensive dream-related Pydantic models including DreamUnit,
DreamTopic, DreamExtractOutput, IntegrateOutcome, TopicSelectionOutput,
ProactiveResult, and DreamState
- Move schema definitions from local step module to shared schema package
- Update dream extraction and integration steps to use new enum-based
bucket validation
- Initialize digest directories for each dream bucket type
- Enhance embedding store health check with workspace directory logging
* refactor(tests): update DreamState import path in test_auto_dream.py
- Move DreamState import from reme.steps.evolve.dream.schema to reme.schema
- Maintain same functionality with updated module reference
- Align import with new schema location in project structure
* fix(core): update version number to 0.4.0.1
- Incremented version from 0.4.0.0 to 0.4.0.1 in __init__.py
* fix(index): remove stopwords path from tokenizer config and add keyword index repair
- Remove stopwords_path from tokenizer config to prevent index forking by install path
- Add _sync_keyword_index_from_chunks method to repair keyword index when persisted state mismatches
- Implement test for keyword index repair from persisted chunks when missing
- Add test to verify tokenizer fingerprint ignores stopwords absolute path
- Update version from 0.4.0.1 to 0.4.0.2
* feat(dream): add scan_days parameter to dream extraction process
- Add scan_days configuration option to default.yaml with default value of 2
- Implement recent_dates utility function to calculate date ranges for scanning
- Modify DreamExtractStep to scan multiple days based on scan_days parameter
- Update dream extraction to process files across multiple dates instead of single day
- Extend DreamState schema to include dates and scan_days fields
- Update DreamTopicsStep to handle multi-day topic processing
- Modify finish step to checkpoint files from all scanned dates
- Add comprehensive tests for multi-day scanning functionality
- Update prompt templates to include scan dates information
- Refactor topics writing logic to target specific date rather than current date
* docs: rename vault_dir to workspace_dir in documentation and examples
* refactor(extract): format long method call across multiple lines
* refactor(extract): format system prompt parameters for better readability
* refactor(vector_store): make obvec and zvec vector stores optional dependencies
- Removed direct imports of ObVecVectorStore and ZvecVectorStore from init file
- Added try-except blocks for conditional importing of optional vector stores
- Updated error handling to check for both pyobvector and sqlalchemy in ObVecVectorStore
- Renamed _OBVECTOR_IMPORT_ERROR to _OBVEC_IMPORT_ERROR for consistency
- Moved pyobvector and related dependencies to optional 'obvec' extra
- Added separate 'zvec' optional dependency group
- Updated package configuration to exclude reme4 module patterns
- Removed reme4 entry point from console scripts
- Bumped version from 0.3.1.9 to 0.3.1.10
* refactor(dependencies): reorganize project dependencies and add optional seekdb support
- Move sqlite-vec, prompt_toolkit, and rich to earlier in dependencies list
- Remove pyseekdb from main dependencies and create separate seekdb optional dependency group
- Reorder pyyaml to later in the dependencies list
- Maintain all existing dependency versions while improving organization
* chore(deps): remove faiss-cpu dependency from pyproject.toml
- Removed faiss-cpu>=1.7.4 from the faiss dependency group
- Cleaned up unused faiss dependency configuration
- Updated project dependencies to exclude faiss-cpu package
* feat(seekdb): add Seekdb file and vector stores with pyseekdb>=1.2.0
* refactor(seekdb): add pyseekdb_conn and remote-only host/port config
* refactor(embedding): remove env fallbacks from BaseEmbeddingModel; pass credentials in tests
* refactor(seekdb): drop tenant from client kwargs; default database test and empty password
* fix(deps): gate pyseekdb to Python >=3.11 for CI 3.10 compatibility
* fix(seekdb): satisfy pre-commit pylint and formatting for seekdb stores
- Changed directory name from 'tool_result' to 'tool_results' in documentation
- Updated path variable assignment to use correct plural form 'tool_results'
- Ensured consistent directory naming throughout initialization logic
* fix(reme_light): dedupe default watch paths on case-insensitive filesystems
On Windows NTFS and macOS HFS+, ``MEMORY.md`` and ``memory.md`` resolve to
the same physical file. ``ReMeLight.__init__`` hardcoded both spellings in
the default ``watch_paths`` list, so the memory markdown file was indexed
twice on those filesystems, wasting embedding calls and producing duplicate
search hits.
Dedupe the default candidate list using ``os.path.normcase`` as the
comparison key. On case-sensitive filesystems normcase is the identity
function, so both spellings continue to be watched there. The original
path strings are preserved, the caller-supplied ``watch_paths`` path is
untouched, and only the built-in fallback is affected.
Fixes#228
* refactor(reme_light): simplify watch path dedup via existence check
Replace the os.path.normcase-based dedup loop with a direct exists()
check that picks one of MEMORY.md / memory.md. On case-insensitive
filesystems both spellings resolve to the same file so exists() returns
true for both, naturally avoiding a duplicate watch — including on
macOS where os.path.normcase is the identity function and the previous
approach silently did nothing.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
---------
Co-authored-by: jinli.yl <jinli.yl@alibaba-inc.com>
Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
