* fix(docs): publish OpenClaw and Hermes integration figures
The generated /en/integrations/openclaw, /zh/integrations/openclaw and
/en/integrations/hermes pages are built from the plugin READMEs, which
reference local figures/. Only the dsh and Studio READMEs had their
./figures/ links rewritten to site paths and their figure directories
copied into the build, so every screenshot on those three pages resolved
to /<language>/integrations/figures/*.png and 404'd. verify-build.mjs
only checks <a> links, never <img> sources, so the build stayed green.
Mirror the dsh pattern: rewrite the figure links to /figures/openclaw/
and /figures/hermes/, copy both figure directories into public/figures/,
add the missing language-cross link for the Hermes page, and cover all of
it in the generated-content tests.
* ci(docs): watch the new integration figure directories
The figures this PR adds under integrations/hermes_agent/figures/ and
integrations/openclaw/figures/ were not in either docs workflow's path
filter, so a follow-up commit that only touches a PNG would skip the docs
build and the broken-reference tests. Add both globs to the pull_request
filter in ci-docs.yml and the push filter in deploy-docs.yml, matching how
integrations/dsh/figures/** and reme_studio/figures/** are already listed.
Requested in review on #586.
* test(docs): validate all integration screenshot references
---------
Co-authored-by: jinli.yl <jinli.yl@alibaba-inc.com>
* feat(docker): add container deployment and multi-platform release workflow
* fix(llm): initialize providers on model access and preserve runtime injection
* test(llm): keep rejected model updates independent of credentials
* chore(ci): harden and split workflows
* fix(ci): support token-based npm publishing
* test: make disappearing resource check portable
* fix(ci): make Studio releases recoverable
* fix(ci): stop Studio publishing on cancellation
* feat(plugins): auto-tag generated reports
* fix(logging): forward host records on Python 3.13
* refactor(tags): decouple auto tagging from index updates
* fix(tags): bind auto tagging to configured index
* fix(tags): preserve standalone default index
* fix(tags): make auto tagging best effort
* refractor(proactive): upgrade proactive feature with disentangled job and steps
* refactor(proactive): apply audit fixes
- rename read-side job 'proactive' -> 'proactive_read' (less confusing vs the refresh pipeline)
- drop dedicated agent_wrapper.proactive; extraction reuses the default wrapper
- simplify schema: remove unused ProactiveExtractOutput/TopicUpdate, drop resource_paths
- extract no longer scans resource/ directly (daily notes already carry resource content)
- update tests and docs accordingly
* feat(proactive): strict extract-output gate and prompt total budget
- parse_extract_reply now requires a contract section (follow_ups/extends/updates
as a list); non-empty replies with misspelled section names trigger the
existing one-shot retry instead of silently checkpointing changed files
- pack_paths gains max_total_chars; extract packs newest daily material first,
keeps the first file on overflow, and records omitted files in a trailer
(default budget 300000 chars, configurable via max_total_chars)
- tests: schema gate unit, schema-error retry e2e, budget unit + e2e
* feat(proactive): add scenario-card plan step and generative agenda step
* feat(proactive): digest-personal profile personalization and leaner LLM contract
- extract/plan/agenda now draw a user profile block from <digest_dir>/personal/*.md
(frontmatter description + body excerpt, per-file budget, profile.md fallback)
- all daily access honours the configured daily_dir (prompt paths parameterized,
config-driven fallbacks) so workspaces using e.g. memory/ work unchanged
- schema trim: drop dead fields errors/material_paths, carry_forward_all -> count
- shrink LLM output contract: new topics emit title/reason/confidence/paths only;
keywords removed end-to-end, evidence derived from paths[0] (updates keep it)
* fix(proactive): skip checkpoint when extract reply stays unusable after retry
Two consecutive unparseable replies now short-circuit the round without
checkpointing, so the same material is retried next round instead of being
silently consumed (closes the residual audit #1 gap: the structural gate
detected schema-wrong output but a double failure still checkpointed).
* fix(proactive): replace running bool with reference-counted job activity tracker for the idle gate
* refactor(proactive): remove job activity tracking and idle gate, restore job tree to upstream
* fix(proactive): address second audit round (readonly reader, mtime checkpoint, wider fallbacks, profile containment, horizon content, expiry boundary)
* refactor(dream): strip interests.yaml ownership from dream, proactive is now the sole writer
* refactor(dream): separate proactive topic generation
* ci: update renamed auto dream smoke test
* fix(proactive): complete refresh migration and docs
---------
Co-authored-by: jinli.yl <jinli.yl@alibaba-inc.com>
* chore(release): prepare ReMe 0.4.1.9
* refactor(config): remove daily_cookbook and streamline plugin configs
- Delete the entire daily_cookbook.yaml standalone application config
- Remove qwenpaw dependencies verification and related CI workflow steps
- Simplify release workflows by removing qwenpaw verification and enforcing reme-ai >=0.4.1.9
- Update plugin start commands and examples to use 'default' or 'demo' configs instead of daily_cookbook
- Adjust imports and tests related to daily_cookbook removal and injected_job_kwargs enhancements
- Refactor agent wrapper to support injected_job_kwargs for job parameter injection in auto-fin and daily-paper
- Improve daily_paper digest prompt to include configured daily directory and correct historical search constraints
- Update dependency versions in pyproject.toml files to require reme-ai >=0.4.1.9 and remove qwenpaw optional dependencies
- Clean up unused environment variables and obsolete test cases related to daily_cookbook and verification steps
* fix(local_embedding_store): retry batch computation on vector space changes
- Add up to 3 attempts to recompute embedding batch if vector space changes during processing
- Log warnings when maximum retries reached and discard stale results
- Prevent caching results from outdated vector spaces to maintain consistency
- Add tests to verify retry behavior and abort after continuous vector space churn
fix(daily_paper): update digest search logic and tests
- Change search to query existing memory, not only previous articles in daily_dir
- Allow multiple searches outside daily_dir but limit links to dated markdown in daily_dir before today
- Update test assertions to reflect revised search and linking rules
* fix(embedding): retry vector space changes per request
* refactor(packaging): reorganize published packages
* fix(packaging): install AgentScope extra in wheel smoke
* docs: align package guides and documentation site
* ci(workflow): add core dependency verification step in Python package build
- Add a workflow step to verify released core dependencies by installing the wheel with core extras
- Assert the presence of the static index.html file to ensure proper package contents
- Create and use a temporary virtual environment for isolation during verification
- Keep existing artifacts upload step intact and conditional on inputs.upload_artifacts flag
* fix(ci): update package installation dependencies in Windows workflow
- Change pip install from editable reme_studio and core to only dev and as extras
- Remove installation of reme_studio and core to streamline dependency setup
- Ensure Windows CI uses the correct extras for testing environment
* fix(tests): add missing commas in toml file reads in package version tests
- Added trailing commas in the tomllib.loads calls for auto-fin and daily_paper configs
- Ensured consistent syntax to prevent potential tuple misinterpretation
- Improved readability and correctness of the test setup code
* fix(packaging): protect qwenpaw releases and test Studio health
* fix: recover embedding after transient health failure
* refactor(embedding_store): remove provider_success_count and simplify health recovery logic
- Deleted provider_success_count attribute and related methods across embedding and file stores
- Updated _recover_after_real_request to rely solely on is_healthy flag for recovery decisions
- Removed redundant counting logic for provider successes during embedding operations
- Cleaned up health status management to streamline provider recovery detection
- Adjusted unit tests to align with removal of provider_success_count and maintain health checks consistency
* refactor(embedding_store): use default health check timeout
* fix(embedding_store): ensure is_healthy remains unchanged on cache hits
- Updated get_embeddings docstring to clarify cache hits must not alter is_healthy state
- Improved code comment for embedding dimension matching method
* fix(file_store): make embedding recovery race-safe
* ci: use default CodeQL query suite
* fix(file_store): preserve queued embedding rebuilds
* fix(file_store): preserve verified recovery without chunks
* feat: add entry-point plugin system
* fix: harden plugin config and client loading
* docs(workflow): add detailed manual for publishing reme-auto-fin to PyPI
- Provide step-by-step instructions for updating project.version and merging branches
- Explain dependency verification for reme-ai on PyPI during build
- Specify requirements for GitHub Actions secret configuration and version uniqueness
- Describe manual workflow triggering and input of version number
- Recommend publishing order for related projects
- Clarify that only manual dispatch triggers publishing, no automatic triggers on push or tag
* feat: support plugin-defined component types
* refactor: simplify plugin configuration
* fix: isolate plugin loading and defer client fallback
* refactor: freeze built-in component registry
* fix: isolate config entry point loading
* fix: complete auto-fin package metadata
* fix(packaging): harden the Studio release workflow
* chore(daily-paper): tune scheduled discovery defaults
* fix(docs): link the ReMe blog to GitHub Pages
* fix(docs): increase Chinese hero title spacing
* refactor(docs): share hero title line spacing
* fix(docs): keep desktop hero copy on two lines
* fix(docs): widen the home hero description
* style(docs): loosen hero title line height
* fix(docs): hide Markdown frontmatter in rendered pages
* docs(readme): simplify installation and remove standalone ReMe Studio instructions
- Remove references to separate ReMe Studio package and static build steps
- Clarify that `core` extra includes common integrations including Studio
- Update installation instructions to use `pip install -e ".[core]"`
- Remove detailed Studio usage and frontend development instructions
- Note that Studio is included with `core` and optional via `web` extra
- Simplify Quick Start guide by removing Studio usage step
- Remove mentions of serving Studio with HTTP service when using extras
- Update both English and Chinese README files accordingly
* docs(readme): streamline and clarify memory design and operations
- Remove redundant explanations about core extra installation
- Simplify memory processing flow description for clarity
- Clarify memory workspace directory default and customization
- Condense automatic memory flow to emphasize rebuildable metadata
- Refine search functionality explanation with RRF fusion details
- Shorten and clarify agent integration description, removing redundancy
- Update and simplify the operations command list, removing less common commands
- Revise community and support section for conciseness and clarity
- Maintain parallel updates in both English and Chinese README files
* test(bump_version): add tests for version bumping and consistency checks
- Add dynamic loading of bump_version and package_studio scripts for testing
- Test that studio package and dependencies have matching versions
- Implement fixtures to write temporary version files for testing
- Add test ensuring bump_version updates all relevant files and dependencies
- Add test to reject inconsistent version sources before writing
- Refactor tests to use common REPOSITORY path variable
- Include imports and setup for pytest in test file
feat(bump_version): create script to update ReMe and Studio versions
- Implement version reading from __init__.py and pyproject.toml files
- Validate current versions are consistent across files before updating
- Update version strings atomically to avoid partial writes
- Ensure exact pinning of studio dependency in main package extras
- Validate new version format against a safe pattern
- Provide CLI interface to bump versions from command line
- Raise errors if expected version declarations or pins are missing or duplicated
* fix(release): validate split package publishing
* fix(release): improve validation diagnostics
* fix(release): sync docs and workflow inputs
* fix(release): split PyPI publish jobs
* feat: simplify local links and support line anchors
* fix: align line anchor tests with CI lint
* fix: preserve local links across file moves
* fix: encode markdown paths when rewriting links
* refactor(read): keep explicit line range parameters
* fix: simplify legacy link predicate compatibility
* docs: align local link behavior with implementation
* fix: skip unsupported markdown destination escapes
* fix: normalize workspace link paths across platforms
* fix: bound markdown link scanning
* fix: keep local link processing linear
* docs: clarify permissive markdown link parsing
* fix: handle local link processing failures
* refactor: limit file links to wikilink syntax
* docs: align wikilink contract with implementation
* fix: normalize dream and neighbor paths on Windows
* fix: resolve workspace path for neighbor expansion
* test(background_steps): add comprehensive tests for batch processing and memory management
- Add test for catalog upserts in batches of at most 100 files
- Add test for catalog deletes in batches of at most 100 paths
- Add test for index memory budget reducing batches to one file
- Add test for memory target limiting cumulative batch size
- Add test for invalid batch memory settings rejection
- Add test for continuing after one batch fails
- Add test for yielding to event loop while building batch
- Add test for modified file reusing unchanged embedding
- Add test for reporting memory estimation failure without aborting
feat(update_changes): implement bounded batch processing with memory management
- Add configurable batch parameters with default values
- Implement memory budget calculation based on available system memory
- Add file inspection and memory estimation before processing
- Implement batch flushing when limits are reached
- Add proper error handling for batch operations
- Support async yielding during batch building
- Add comprehensive validation for batch configuration parameters
- Implement memory estimation for indexing operations
- Add batch size limiting for delete operations
* test(steps): add tests for memory estimation failure handling
- Add test case for isolated file processing when memory estimation fails
- Add test case for proper release of flushed items before building next file
- Implement weak reference tracking to verify payload lifetime management
- Create parametrized tests for both source and item memory estimation methods
- Add assertions to verify single-item batch behavior on estimation failures
- Include comprehensive error handling verification for memory budget calculations
* chore(version): bump version to 0.4.1.3
- Update __version__ from 0.4.1.2 to 0.4.1.3 in __init__.py
* feat(index): support batch settings from environment
* refactor(index): use direct batch defaults
* refactor(index): configure memory estimates through step args
* ci: simplify Windows smoke dependencies
* 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
* chore(workflow): update package installation to include core extra dependencies
- Modified pre-commit workflow to install with [dev,core] extras
- Updated python-publish workflow to install wheel with core extra dependency
- Changed from direct dist/*.whl install to variable assignment for wheel path
- Ensured core dependencies are included during test installation phase
* chore(workflow): remove docs deployment workflow
- Delete the entire docs.yml workflow file that was used for deploying documentation
- Remove all related configuration including build and deploy jobs
- Stop automatic deployment of docs on pushes to main branch
- Remove GitHub Actions workflow for docs/ directory changes
* 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
