* refactor(file_chunker): replace file parser with file chunker component
- Rename file_parser module to file_chunker across codebase
- Update BaseFileParser to BaseFileChunker with corresponding component type
- Rename LinkedFileParser to MarkdownFileChunker for markdown-specific chunking
- Rename ChunkedFileParser to DefaultFileChunker for default byte-based chunking
- Update documentation references from file_parser to file_chunker
- Modify dependency injection in BaseStep to use file_chunker instead of file_parser
- Update configuration and component registration to use new chunker naming
- Rename all related test files and update test assertions accordingly
- Add recursive option to scan_store_changes_step in default configuration
* feat(database): enhance Neo4j connection with environment variable support
- Add support for NEO4J_PASSWORD environment variable as fallback
- Make password parameter optional in constructor with validation
- Update chromadb dependency from 1.3.5 to 1.5.7
- Configure CORS credentials based on origin settings
- Import os module for environment variable access
* feat(config): add timezone support and remove unused dialog directory
- Added timezone field to application config with IANA timezone support
- Removed unused dialog_dir configuration and related directory creation
- Replaced date.today() with timezone-aware now() function across daily operations
- Created evolve module with timezone-aware datetime functionality
- Updated daily_create, daily_list, and daily_reindex steps to use timezone-aware dates
* refactor(steps): update file chunker implementation
- Replace ChunkedFileParser with DefaultFileChunker in background steps
- Add module docstring to evolve steps package
- Update return type annotation to reflect new chunker class usage
* refactor(components): rename embedding and llm components to as_embedding and as_llm
- Rename reme4/components/embedding to reme4/components/as_embedding
- Rename reme4/components/llm to reme4/components/as_llm
- Update all imports and references from embedding to as_embedding
- Update all imports and references from llm to as_llm
- Change BaseEmbedding to BaseAsEmbedding and update inheritance
- Change BaseLLM to BaseAsLLM and update inheritance
- Update component types from LLM/EMBEDDING to AS_LLM/AS_EMBEDDING
- Update configuration keys from embedding/llm to as_embedding/as_llm
- Update all property references from llm to as_llm in step classes
- Update test assertions to use new component enum values
* refactor(embedding_store): rename embedding parameter to as_embedding
- Updated configuration key from 'embedding' to 'as_embedding'
- Renamed class attribute from 'embedding' to 'as_embedding'
- Updated method calls to use 'as_embedding' instead of 'embedding'
- Changed parameter name in constructor from 'embedding' to 'as_embedding'
- Updated documentation to reflect new parameter name
- Modified health check to use 'as_embedding' property
* feat(agent_wrapper): add unified agent wrapper component with multiple backends
- Introduce BaseAgentWrapper abstract base class for agent implementations
- Add AsAgentWrapper implementation using AgentScope framework
- Add CcAgentWrapper implementation using Claude Code SDK
- Register agent_wrapper component type in ComponentEnum
- Configure default agent_wrapper settings in default.yaml
- Implement tool integration for both AgentScope and Claude Code backends
- Support fluent configuration via set_system_prompt() and add_tools() methods
* feat(agent-wrapper): add structured output support for agent wrappers
- Import SystemMsg in AsAgentWrapper for structured output handling
- Add output_schema parameter support in AsAgentWrapper with generate_structured_output
- Implement set_output_schema method in BaseAgentWrapper for chaining configuration
- Add output schema support in CcAgentWrapper with JSON schema format option
- Return structured output when available in CcAgentWrapper response
- Refactor kwargs handling to use default values consistently across wrapper classes
* 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
* refactor(evolve): consolidate auto memory planner and writer into single step
- Removed separate AutoMemoryPlannerStep and AutoMemoryWriterStep classes
- Combined functionality into new AutoMemoryStep class in auto_memory.py
- Migrated prompt templates from separate YAML files to unified auto_memory.yaml
- Updated module imports to reference new consolidated step
- Simplified memory recording process using single ReAct agent instead of two-stage planning/writing
- Maintained same input/output contract with messages, session_id, and memory_hint parameters
- Preserved all original functionality for creating/updating daily notes with conversation facts
* fix(daily): update empty session_id handling to create day-level file
- Changed test to verify empty session_id creates day-level file daily/<date>.md
- Updated assertion to check response success instead of rejection
- Modified metadata verification to include path, session_id and created status
- Added file existence check for the generated daily markdown file
- Updated test name and print statement to reflect new behavior
- Fixed test registration to use updated function name
* fix(bm25_index): 修正BM25索引计算中的文档长度归一化问题
修复了在计算BM25相似度时对文档长度进行不正确归一化的bug，确保所有查询都能得到准确的相关性评分。
* up
* up
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* up
* up
* up
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* refactor(steps): Rename and adjust indexing step logic
- Rename `scan_changes.py` and `reindex.py` to `clear_and_scan.py`
- Update implementation details of `ScanChangesStep` and `ClearAndScanStep`
- Modify the scheduling mechanism in `WatchChangesStep`
- Adjust step registration and parameter configuration in config files
- Update related tests to align with the new interface changes
* up
* feat(daily): replace daily CRUD operations with slug provisioning approach
* refactor(tests): migrate CRUD step tests from HTTP server to direct LocalFileStore
* up
* up
* up
* up
---------
Co-authored-by: huangsen <huangsen.huang@alibaba-inc.com>
* feat(file_store): add FAISS-backed local file store implementation
- Introduce FaissLocalFileStore class with vector search capabilities using FAISS IndexFlatIP
- Implement FAISS index persistence with binary format and JSON id-map sidecar
- Add automatic index rebuilding when sidecar files are missing or corrupted
- Support tombstone mechanism for efficient deletion and compaction
- Register 'faiss' component type in the registry system
- Add faiss-cpu dependency requirement to pyproject.toml
- Update configuration schema to use simplified parameter structure
- Enhance search step to support parameter override from runtime context
- Add comprehensive unit tests for FAISS store functionality
- Implement fallback to parent methods for basic CRUD operations
* refactor(search): simplify parameter retrieval logic
- Removed _param method that checked context and kwargs
- Directly use self.kwargs.get for all parameter retrievals
- Maintained same default values for vector_weight, candidate_multiplier, expand_links, and max_links_per_direction
- Reduced code complexity by eliminating redundant context checking logic
* 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
* refactor(steps): Add job management methods and support registering them as tools
Added methods to the `BaseStep` class for retrieving, running, and registering jobs as tools, enhancing the functionality of the step class.
* fix doc
* chore(pyproject.toml): Update dependency versions and adjust package configuration
Bump agentscope version to 1.0.19 and reorganize the core dependency configuration structure.
* feat: add Neo4j file graph support and markdown parser with wikilink extraction
- Add Neo4jFileGraph implementation for property-graph storage with
virtual/real node handling and link management
- Introduce LinkedFileParser for markdown files with frontmatter,
wikilink graph extraction, and full-skeleton chunking
- Update pyproject.toml to include pyyaml, mistletoe, and neo4j
dependencies
- Modify .gitignore to exclude /vault and structure.md
- Change reme CLI entry point from reme_ai.main to remecli.reme
- Register new neo4j and md components in respective registries
* refactor(file-graph): add chunk_ids support to Neo4jFileGraph
Add chunk_ids field to File node properties in Neo4jFileGraph to
enable better content chunk tracking and management.
BREAKING CHANGE: File node schema now includes chunk_ids property
which may affect existing integrations.
feat(parser): implement wikilink resolution logic
Move path resolution logic from utils/path_resolver to
linked_file_parser module and enhance wikilink resolution with
folder-note rule support and improved error handling.
fix(tests): update test assertions and variable names
Update test cases to reflect changes in data structures and
variable naming conventions across various components.
chore(config): update package entry point reference
Change reme CLI entry point from remecli.reme:main to
reme_ai.reme:main in pyproject.toml.
refactor(utils): remove deprecated path_resolver module
Remove the old path_resolver utility module as its functionality
has been moved to linked_file_parser.
docs(file-graph): update Neo4jFileGraph documentation
Update class docstrings and comments to reflect new chunk_ids
property and other structural changes.
style(formatting): adjust code formatting and line breaks
Minor formatting improvements including line length optimization
and consistent spacing adjustments throughout the codebase.
* fix(pyproject.toml): correct entry point for reme command
Change the entry point from "reme_ai.reme:main" to "reme_ai.main:main"
to fix the module reference for the reme command in project scripts.
* feat(vector_store): add OceanBase as a VectorStore
* refactor(obvec): make it cleaner
* docs: add obvec related info
* refactor: minor update
* refactor: clean code and pass lint
* docs: remove unrelated edit
* docs: minor update
* feat(compactor): add extra instruction support and improve error handling
- Add extra_instruction parameter to compactor for custom guidance during message compaction
- Implement try-catch blocks around AS LLM initialization with detailed error logging
- Add extra_instruction parameter to ReMe.compact method with comprehensive documentation
- Update agentscope dependency from 1.0.17 to 1.0.18 in light installation
- Bump version number from 0.3.1.6 to 0.3.1.7
- Pass extra_instruction parameter through compactor instantiation and execution flow
* fix(core): add error handling for AS LLM formatters and token counters initialization
- Wrapped AS LLM formatters initialization in try-except blocks
- Added specific error logging for failed AS LLM formatter initialization
- Wrapped AS token counters initialization in try-except blocks
- Added specific error logging for failed AS token counter initialization
- Applied same error handling pattern to both initial setup and restart operations
- Maintained existing warning logs for unsupported backends
* refactor(core): replace text truncation utilities with new marker system
- Remove old truncate_text_utils module and its exports
- Replace TRUNCATION_MARKER_START with _TRUNCATION_NOTICE_MARKER constant
- Update as_msg_stat.py to split content using new marker format
- Modify FileIO tool to use TRUNCATION_NOTICE_MARKER for continuation hints
- Change is_truncated function checks to use marker presence detection
- Move transformers dependency from main deps to light extra dependencies
- Update tool result compactor tests to verify marker instead of is_truncated calls
* feat(file_io): enhance file operations with path resolution and append functionality
- Add expanduser() to resolve file paths with ~ symbol
- Implement proper file existence and type validation in update_file
- Add new append_file method to append content to files
- Update truncation notice format for better readability
- Fix typo in error message from "provide" to "provided"
- Update transformers dependency in pyproject.toml
- Remove duplicate transformers dependency from light extras
* refactor(file_io): disable pylint too-many-return-statements warning
* perf(file_watcher): increase default polling delay and optimize watcher configuration
- Increased default poll_delay_ms from 1000ms to 2000ms to reduce CPU usage
- Removed force_polling parameter as it's no longer needed with updated polling strategy
- Simplified async watch configuration by removing conditional force_polling logic
- Reduced overall system resource consumption during file watching operations
* refactor(memory): update conversation log documentation in memory summary
- Changed "Raw conversation logs" to "Earlier conversation logs" for clarity
- Added warning note about potentially large dialog file sizes
- Improved formatting with additional line break for better readability
- Maintained existing compressed summary integration unchanged
* feat(memory): add long-term memory support to file-based memory system
- Initialize _long_term_memory attribute as empty string
- Add memories section to content when long-term memory exists
- Consolidate summary and memories into single user message
- Format memories with markdown header # Memories
- Maintain existing compressed summary functionality
- Join multiple content parts with double newlines
* chore(deps): update version and move litellm to dev dependencies
- Updated package version from 0.3.1.2 to 0.3.1.3
- Removed litellm from main dependencies in pyproject.toml
- Added litellm as fixed version dependency in dev group
- Maintained litellm requirement while reorganizing dependency structure
* chore(deps): move litellm dependency to full extras
- Moved litellm==1.80.0 from main dependencies to full extra
- Kept litellm as optional dependency for users needing full feature set
- Maintains backward compatibility for light installation option
* feat(pyproject): add litellm dependency to project configuration
- Added litellm==1.80.0 as optional dependency in pyproject.toml
- Created new litellm extra group for LiteLLM integration
- Updated full dependency group to include the new litellm option
* update
* refactor(memory): remove unnecessary type check and update error logging
* refactor(core): standardize logger import and update agentscope dependency
* fix(memory): disable console output and add logging for summarizer component
* feat(core): replace OpenAI token counter with custom ReMe token counter
- Replace OpenAITokenCounter with ReMeTokenCounter implementation
- Add support for HuggingFace mirror and configurable tokenizer
- Register ReMeTokenCounter as default token counter in registry
- Update config to use hf backend with Qwen2.5-7B-Instruct model
refactor(memory): convert token counting methods to async in message handlers
- Change count_str_token, stat_message, count_msgs_token to async methods
- Update format_msgs_to_str and context_check to use async token counting
- Modify _format_tool_result_output to support async token counting
- Adjust all dependent methods to await async token counting calls
feat(memory): add dialog persistence to in-memory storage
- Implement _append_messages_to_dialog for saving messages to JSONL files
- Add dialog_path parameter to ReMeInMemoryMemory constructor
- Persist messages to daily JSONL files based on timestamp grouping
- Update mark_messages_compressed to save and remove compressed messages
- Modify clear_content to persist all messages before clearing memory
refactor(ops): update token counter type hints and initialization
- Change BaseOp to use HuggingFaceTokenCounter instead of TokenCounterBase
- Update type annotations for as_token_counter property and parameters
- Remove direct token counter injection from Compactor and ContextChecker
- Pass as_token_counter parameter through service context mechanism
style(logging): improve error logging with exception details
- Replace logger.error with logger.exception in browser control tool
- Change logger.error to logger.exception in memory get tool error handling
- Add proper exception logging with stack trace information
chore(config): add token counter configuration to light YAML
- Add as_token_counters section with default hf backend configuration
- Configure Qwen/Qwen2.5-7B-Instruct model with mirror support enabled
- Set up pretrained_model_name_or_path and use_mirror parameters
test(context): update context check tests to async implementation
- Convert verify_context_check_invariants to async function
- Update context check test methods to use async calls
- Change stat_message calls to await async implementation
- Modify test_empty_messages and test_below_threshold_returns_all to async
* feat(core): implement context checking and memory management features
* refactor(core): replace direct loguru import with logger utility function
* refactor(reme): remove RuntimeContext dependency and simplify context checking
* feat(docs): add raw conversation persistence to ReMe framework
- Add Weikang Zhou as a contributor in pyproject.toml
- Update README.md with new author in software citation
- Add new paper reference for AgentscopeReMe framework
- Include arXiv link and publication details
- Add full author list for the research paper
- Update bibliography with proper formatting
- Added QdrantVectorStore backend with native async operations
- Implemented advanced filtering capabilities for metadata queries
- Added support for Qdrant Cloud and local deployments- Updated vector store comparison table with Qdrant features
- Enhanced documentation with Qdrant setup and usage examples
- Fixed code block formatting in vector store API guide
- Updated embedding model integration for Qdrant compatibility
- Updated __version__ in reme_ai/__init__.py
- Updated project version in pyproject.toml- Changed flowllm dependency to include reme extra
- Fixed typo in README.md query example
- Enhanced tool call result parsing with improved scoring logic (0.0 or 1.0)
- Updated tool memory schema to reflect binary success/failure scoring
- Added deterministic behavior support via seed configuration in mock tools
- Improved evaluation prompts to focus on result quality over success flags
- Extended README with tool memory documentation and usage examples- Added utility functions for generating mock tool call results
- Removed deprecated test file for UseMockSearchOp- Updated default configurations to include use_mock_search operation- Bumped version to0.1.10 and updated flowllm dependency requirement
- Moved deprecation warnings to main init file
- Simplified tool memory summary formatting by removing redundant statistics
- Fixed tool call result processing to handle multiple tool names concurrently
