* feat: enhance token limits with dynamic discovery + AST metadata
Improves upon upstream PR #154 with two major enhancements:
1. **Hybrid Token Limit Discovery**
- Dynamic: Query Ollama /api/show for context limits
- Fallback: Registry for LM Studio/OpenAI
- Zero maintenance for Ollama users
- Respects custom num_ctx settings
2. **AST Metadata Preservation**
- create_ast_chunks() returns dict format with metadata
- Preserves file_path, file_name, timestamps
- Includes astchunk metadata (line numbers, node counts)
- Fixes content extraction bug (checks "content" key)
- Enables --show-metadata flag
3. **Better Token Limits**
- nomic-embed-text: 2048 tokens (vs 512)
- nomic-embed-text-v1.5: 2048 tokens
- Added OpenAI models: 8192 tokens
4. **Comprehensive Tests**
- 11 tests for token truncation
- 545 new lines in test_astchunk_integration.py
- All metadata preservation tests passing
* fix: merge EMBEDDING_MODEL_LIMITS and remove redundant validation
- Merged upstream's model list with our corrected token limits
- Kept our corrected nomic-embed-text: 2048 (not 512)
- Removed post-chunking validation (redundant with embedding-time truncation)
- All tests passing except 2 pre-existing integration test failures
* style: apply ruff formatting and restore PR #154 version handling
- Remove duplicate truncate_to_token_limit and get_model_token_limit functions
- Restore version handling logic (model:latest -> model) from PR #154
- Restore partial matching fallback for model name variations
- Apply ruff formatting to all modified files
- All 11 token truncation tests passing
* style: sort imports alphabetically (pre-commit auto-fix)
* fix: show AST token limit warning only once per session
- Add module-level flag to track if warning shown
- Prevents spam when processing multiple files
- Add clarifying note that auto-truncation happens at embedding time
- Addresses issue where warning appeared for every code file
* enhance: add detailed logging for token truncation
- Track and report truncation statistics (count, tokens removed, max length)
- Show first 3 individual truncations with exact token counts
- Provide comprehensive summary when truncation occurs
- Use WARNING level for data loss visibility
- Silent (DEBUG level only) when no truncation needed
Replaces misleading "truncated where necessary" message that appeared
even when nothing was truncated.
* feat: add metadata output to search results
- Add --show-metadata flag to display file paths in search results
- Preserve document metadata (file_path, file_name, timestamps) during chunking
- Update MCP tool schema to support show_metadata parameter
- Enhance CLI search output to display metadata when requested
- Fix pre-existing bug: args.backend -> args.backend_name
Resolves yichuan-w/LEANN#144
* fix: resolve ZMQ linking issues in Python extension
- Use pkg_check_modules IMPORTED_TARGET to create PkgConfig::ZMQ
- Set PKG_CONFIG_PATH to prioritize ARM64 Homebrew on Apple Silicon
- Override macOS -undefined dynamic_lookup to force proper symbol resolution
- Use PUBLIC linkage for ZMQ in faiss library for transitive linking
- Mark cppzmq includes as SYSTEM to suppress warnings
Fixes editable install ZMQ symbol errors while maintaining compatibility
across Linux, macOS Intel, and macOS ARM64 platforms.
* style: apply ruff formatting
* chore: update faiss submodule to use ww2283 fork
Use ww2283/faiss fork with fix/zmq-linking branch to resolve CI checkout
failures. The ZMQ linking fixes are not yet merged upstream.
* feat: implement true batch processing for Ollama embeddings
Migrate from deprecated /api/embeddings to modern /api/embed endpoint
which supports batch inputs. This reduces HTTP overhead by sending
32 texts per request instead of making individual API calls.
Changes:
- Update endpoint from /api/embeddings to /api/embed
- Change parameter from 'prompt' (single) to 'input' (array)
- Update response parsing for batch embeddings array
- Increase timeout to 60s for batch processing
- Improve error handling for batch requests
Performance:
- Reduces API calls by 32x (batch size)
- Eliminates HTTP connection overhead per text
- Note: Ollama still processes batch items sequentially internally
Related: #151
* fall back to original faiss as i merge the PR
---------
Co-authored-by: yichuan520030910320 <yichuan_wang@berkeley.edu>
* Printing querying time
* Adding source name to chunks
Adding source name as metadata to chunks, then printing the sources when searching
* Printing the context provided to LLM
To check the data transmitted to the LLMs : display the relevance, ID, content, and source of each sent chunk.
* Correcting source as metadata for chunks
* Applying ruff format
* Applying Ruff formatting
* Ruff formatting
BREAKING CHANGE: trust_remote_code now defaults to False for security
- Set trust_remote_code=False by default in HFChat class
- Add explicit trust_remote_code parameter to HFChat.__init__()
- Add security warning when trust_remote_code=True is used
- Update get_llm() function to support trust_remote_code parameter
- Update benchmark utilities (load_hf_model, load_vllm_model, load_qwen_vl_model)
- Add comprehensive documentation for security implications
Security Benefits:
- Prevents arbitrary code execution from compromised model repositories
- Requires explicit opt-in for models that need remote code execution
- Shows clear warnings when security is reduced
- Follows security-by-default principle
Migration Guide:
- Most users: No changes needed (more secure by default)
- Users with models requiring remote code: Add trust_remote_code=True explicitly
- Config users: Add 'trust_remote_code': true to LLM config if needed
Fixes#136
* feat: Add MCP integration support for Slack and Twitter
- Implement SlackMCPReader for connecting to Slack MCP servers
- Implement TwitterMCPReader for connecting to Twitter MCP servers
- Add SlackRAG and TwitterRAG applications with full CLI support
- Support live data fetching via Model Context Protocol (MCP)
- Add comprehensive documentation and usage examples
- Include connection testing capabilities with --test-connection flag
- Add standalone tests for core functionality
- Update README with detailed MCP integration guide
- Add Aakash Suresh to Active Contributors
Resolves#36
* fix: Resolve linting issues in MCP integration
- Replace deprecated typing.Dict/List with built-in dict/list
- Fix boolean comparisons (== True/False) to direct checks
- Remove unused variables in demo script
- Update type annotations to use modern Python syntax
All pre-commit hooks should now pass.
* fix: Apply final formatting fixes for pre-commit hooks
- Remove unused imports (asyncio, pathlib.Path)
- Remove unused class imports in demo script
- Ensure all files pass ruff format and pre-commit checks
This should resolve all remaining CI linting issues.
* fix: Apply pre-commit formatting changes
- Fix trailing whitespace in all files
- Apply ruff formatting to match project standards
- Ensure consistent code style across all MCP integration files
This commit applies the exact changes that pre-commit hooks expect.
* fix: Apply pre-commit hooks formatting fixes
- Remove trailing whitespace from all files
- Fix ruff formatting issues (2 errors resolved)
- Apply consistent code formatting across 3 files
- Ensure all files pass pre-commit validation
This resolves all CI formatting failures.
* fix: Update MCP RAG classes to match BaseRAGExample signature
- Fix SlackMCPRAG and TwitterMCPRAG __init__ methods to provide required parameters
- Add name, description, and default_index_name to super().__init__ calls
- Resolves test failures: test_slack_rag_initialization and test_twitter_rag_initialization
This fixes the TypeError caused by BaseRAGExample requiring additional parameters.
* style: Apply ruff formatting - add trailing commas
- Add trailing commas to super().__init__ calls in SlackMCPRAG and TwitterMCPRAG
- Fixes ruff format pre-commit hook requirements
* fix: Resolve SentenceTransformer model_kwargs parameter conflict
- Fix local_files_only parameter conflict in embedding_compute.py
- Create separate copies of model_kwargs and tokenizer_kwargs for local vs network loading
- Prevents parameter conflicts when falling back from local to network loading
- Resolves TypeError in test_readme_examples.py tests
This addresses the SentenceTransformer initialization issues in CI tests.
* fix: Add comprehensive SentenceTransformer version compatibility
- Handle both old and new sentence-transformers versions
- Gracefully fallback from advanced parameters to basic initialization
- Catch TypeError for model_kwargs/tokenizer_kwargs and use basic SentenceTransformer init
- Ensures compatibility across different CI environments and local setups
- Maintains optimization benefits where supported while ensuring broad compatibility
This resolves test failures in CI environments with older sentence-transformers versions.
* style: Apply ruff formatting to embedding_compute.py
- Break long logger.warning lines for better readability
- Fixes pre-commit hook formatting requirements
* docs: Comprehensive documentation improvements for better user experience
- Add clear step-by-step Getting Started Guide for new users
- Add comprehensive CLI Reference with all commands and options
- Improve installation instructions with clear steps and verification
- Add detailed troubleshooting section for common issues (Ollama, OpenAI, etc.)
- Clarify difference between CLI commands and specialized apps
- Add environment variables documentation
- Improve MCP integration documentation with CLI integration examples
- Address user feedback about confusing installation and setup process
This resolves documentation gaps that made LEANN difficult for non-specialists to use.
* style: Remove trailing whitespace from README.md
- Fix trailing whitespace issues found by pre-commit hooks
- Ensures consistent formatting across documentation
* docs: Simplify README by removing excessive documentation
- Remove overly complex CLI reference and getting started sections (lines 61-334)
- Remove emojis from section headers for cleaner appearance
- Keep README simple and focused as requested
- Maintain essential MCP integration documentation
This addresses feedback to keep documentation minimal and avoid auto-generated content.
* docs: Address maintainer feedback on README improvements
- Restore emojis in section headers (Prerequisites and Quick Install)
- Add MCP live data feature mention in line 23 with links to Slack and Twitter
- Add detailed API credential setup instructions for Slack:
- Step-by-step Slack App creation process
- Required OAuth scopes and permissions
- Clear token identification (xoxb- vs xapp-)
- Add detailed API credential setup instructions for Twitter:
- Twitter Developer Account application process
- API v2 requirements for bookmarks access
- Required permissions and scopes
This addresses maintainer feedback to make API setup more user-friendly.
* Add readline support to interactive command line interfaces
- Implement readline history, navigation, and editing for CLI, API, and RAG chat modes
- Create shared InteractiveSession class to consolidate readline functionality
- Add command history persistence across sessions with separate files per context
- Support built-in commands: help, clear, history, quit/exit
- Enable arrow key navigation and command editing in all interactive modes
* Improvements based on feedback
* feat: finance bench
* docs: results
* chore: ignroe data README
* feat: fix financebench
* feat: laion, also required idmaps support
* style: format
* style: format
* fix: resolve ruff linting errors
- Remove unused variables in benchmark scripts
- Rename unused loop variables to follow convention
* feat: enron email bench
* experiments for running DiskANN & BM25 on Arch 4090
* style: format
* chore(ci): remove paru-bin submodule and config to fix checkout --recurse-submodules
* docs: data
* docs: data updated
* fix: as package
* fix(ci): only run pre-commit
* chore: use http url of astchunk; use group for some dev deps
* fix(ci): should checkout modules as well since `uv sync` checks
* fix(ci): run with lint only
* fix: find links to install wheels available
* CI: force local wheels in uv install step
* CI: install local wheels via file paths
* CI: pick wheels matching current Python tag
* CI: handle python tag mismatches for local wheels
* CI: use matrix python venv and set macOS deployment target
* CI: revert install step to match main
* CI: use uv group install with local wheel selection
* CI: rely on setup-uv for Python and tighten group install
* CI: install build deps with uv python interpreter
* CI: use temporary uv venv for build deps
* CI: add build venv scripts path for wheel repair
* feat: Add GitHub PR and issue templates for better contributor experience
* simplify: Make templates more concise and user-friendly
* fix: enable is_compact=False, is_recompute=True
* feat: update when recompute
* test
* fix: real recompute
* refactor
* fix: compare with no-recompute
* fix: test
* feat: Add ARM64 Linux wheel support for leann-backend-hnsw
* fix: Use OpenBLAS for ARM64 Linux builds instead of Intel MKL
* fix: Configure Faiss with SVE optimization for ARM64 builds
- Set FAISS_OPT_LEVEL to "sve" for ARM64 architecture
- Disable x86-specific SIMD instructions (AVX2, AVX512, SSE4.1)
- Use ARM64-native SVE optimization as per Faiss conda build scripts
- Add architecture detection and proper configuration messages
Fixes compilation error: "xmmintrin.h: No such file or directory"
on ubuntu-24.04-arm runners.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: Apply ARM64 compatibility fix directly to Faiss submodule
- Modify faiss/impl/pq.cpp to use x86-specific preprocessor conditions
- Remove patch file approach in favor of direct submodule modification
- Update CMakeLists.txt to reflect the submodule changes
- Fixes ARM64 Linux compilation by preventing x86 SIMD header inclusion
This resolves the "xmmintrin.h: No such file or directory" error
when building ARM64 Linux wheels for Docker compatibility.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* chore: Update Faiss submodule to include ARM64 compatibility fix
- Points to commit ed96ff7d with x86-specific preprocessor conditions
- Enables successful ARM64 Linux wheel builds
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* retrigger ci
* fix: Use different optimization levels for ARM64 based on platform
- Use SVE optimization only for ARM64 Linux
- Use generic optimization for ARM64 macOS to avoid clang SVE issues
- Fixes macOS ARM64 compilation errors with SVE instructions
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* feat: Update DiskANN submodule with OpenBLAS fallback support
- Points to commit 5c396c4 with ARM64 Linux OpenBLAS support
- Enables DiskANN to build on ARM64 Linux using standard BLAS libraries
- Resolves Intel MKL dependency issues for Docker ARM64 deployments
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: Update DiskANN submodule with ZeroMQ polling configuration
- Points to commit 3a1016e with explicit polling method setup
- Resolves ZeroMQ autodetection issues on ARM64 Linux
- Ensures stable cross-platform ZeroMQ builds
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* retrigger ci
* fix: Update DiskANN submodule with ARM64 compiler flags fix
- Points to commit a0dc600 with architecture-specific compiler flags
- Removes x86 SIMD flags on ARM64 Linux to fix compilation errors
- Enables successful ARM64 Linux wheel builds
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: Update DiskANN submodule with ARM64 compiler flags fix
- Points to commit 0921664 with architecture-specific compiler flags
- Removes x86 SIMD flags on ARM64 Linux to fix compilation errors
- Enables successful ARM64 Linux wheel builds
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* retrigger ci
* fix: Update DiskANN submodule with cross-platform prefetch support
- Points to commit 39192d6 with unified prefetch macros
- Replaces all Intel-specific _mm_prefetch calls with cross-platform macros
- Enables ARM64 Linux compatibility while maintaining x86 performance
- Resolves all remaining compilation errors for ARM64 builds
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: Update DiskANN submodule with corrected ARM64 compatibility fixes
- Points to commit 3cb87a8 with proper x86 platform detection
- Includes ARM64 fallback for AVXDistanceInnerProductFloat function
- Resolves all remaining '__m256 was not declared' compilation errors
- Enables successful ARM64 Linux wheel builds for Docker compatibility
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: Update DiskANN submodule with template type handling fix
- Points to commit d396bc3 with corrected template type handling
- Fixes DistanceInnerProduct template instantiation for int8_t/uint8_t types
- Resolves 'cannot convert const signed char* to const float*' error
- Completes ARM64 Linux compilation compatibility
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: Update DiskANN submodule with DistanceFastL2::norm template fix
- Points to commit 69d9a99 with corrected template type handling
- Fixes DistanceFastL2::norm template instantiation for int8_t/uint8_t types
- Resolves another 'cannot convert const signed char* to const float*' error
- Continues ARM64 Linux compilation compatibility improvements
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: Update DiskANN submodule with LAPACKE header detection
- Points to commit 64a9e01 with LAPACKE header path configuration
- Adds pkg-config based detection for LAPACKE include directories
- Resolves 'lapacke.h: No such file or directory' compilation error
- Completes OpenBLAS integration for ARM64 Linux builds
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: Update DiskANN submodule with enhanced LAPACKE header detection
- Points to commit 18d0721 with fallback LAPACKE header search paths
- Checks multiple standard locations for lapacke.h on various systems
- Improves ARM64 Linux compatibility for OpenBLAS builds
- Should resolve 'lapacke.h: No such file or directory' errors
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: Add liblapacke-dev package for ARM64 Linux builds
- Add liblapacke-dev to ARM64 dependencies alongside libopenblas-dev
- Provides lapacke.h header file needed for LAPACK C interface
- Fixes 'lapacke.h: No such file or directory' compilation error
- Enables complete OpenBLAS + LAPACKE support for ARM64 wheel builds
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: Update DiskANN submodule with cosine_similarity.h x86 intrinsics fix
- Points to commit dbb17eb with corrected conditional compilation
- Fixes immintrin.h inclusion for ARM64 compatibility in cosine_similarity.h
- Resolves 'immintrin.h: No such file or directory' error
- Continues systematic ARM64 Linux compilation fixes
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: Update DiskANN submodule with LAPACKE library linking fix
- Points to commit 19f9603 with explicit LAPACKE library discovery and linking
- Resolves 'undefined symbol: LAPACKE_sgesdd' runtime error on ARM64 Linux
- Completes ARM64 Linux wheel build compatibility for Docker deployments
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
---------
Co-authored-by: Claude <noreply@anthropic.com>
* Metadata filtering initial version
* Metadata filtering initial version
* Fixes linter issues
* Cleanup code
* Clean up and readme
* Fix after review
* Use UV in example
* Merge main into feature/metadata-filtering
* feat(core): Add AST-aware code chunking with astchunk integration
This PR introduces intelligent code chunking that preserves semantic boundaries
(functions, classes, methods) for better code understanding in RAG applications.
Key Features:
- AST-aware chunking for Python, Java, C#, TypeScript files
- Graceful fallback to traditional chunking for unsupported languages
- New specialized code RAG application for repositories
- Enhanced CLI with --use-ast-chunking flag
- Comprehensive test suite with integration tests
Technical Implementation:
- New chunking_utils.py module with enhanced chunking logic
- Extended base RAG framework with AST chunking arguments
- Updated document RAG with --enable-code-chunking flag
- CLI integration with proper error handling and fallback
Benefits:
- Better semantic understanding of code structure
- Improved search quality for code-related queries
- Maintains backward compatibility with existing workflows
- Supports mixed content (code + documentation) seamlessly
Dependencies:
- Added astchunk and tree-sitter parsers to pyproject.toml
- All dependencies are optional - fallback works without them
Testing:
- Comprehensive test suite in test_astchunk_integration.py
- Integration tests with document RAG
- Error handling and edge case coverage
Documentation:
- Updated README.md with AST chunking highlights
- Added ASTCHUNK_INTEGRATION.md with complete guide
- Updated features.md with new capabilities
* Refactored chunk utils
* Remove useless import
* Update README.md
* Update apps/chunking/utils.py
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Update apps/code_rag.py
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Fix issue
* apply suggestion from @Copilot
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Fixes after pr review
* Fix tests not passing
* Fix linter error for documentation files
* Update .gitignore with unwanted files
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Andy Lee <andylizf@outlook.com>
* feat: Enhance CLI with improved list and smart remove commands
## ✨ New Features
### 🏠 Enhanced `leann list` command
- **Better UX**: Current project shown first with clear separation
- **Visual improvements**: Icons (🏠/📂), better formatting, size info
- **Smart guidance**: Context-aware usage examples and getting started tips
### 🛡️ Smart `leann remove` command
- **Safety first**: Always shows ALL matching indexes across projects
- **Intelligent handling**:
- Single match: Clear location display with cross-project warnings
- Multiple matches: Interactive selection with final confirmation
- **Prevents accidents**: No more deleting wrong indexes due to name conflicts
- **User-friendly**: 'c' to cancel, clear visual hierarchy, detailed info
### 🔧 Technical improvements
- **Clean logging**: Hide debug messages for better CLI experience
- **Comprehensive search**: Always scan all projects for transparency
- **Error handling**: Graceful handling of edge cases and user input
## 🎯 Impact
- **Safer**: Eliminates risk of accidental index deletion
- **Clearer**: Users always know what they're operating on
- **Smarter**: Automatic detection and handling of common scenarios
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* chore: vscode ruff, and format
* fix: Update DiskANN submodule with MKL linking improvements
Updates DiskANN submodule to include fix for MKL linking issues:
- Replaces global link_libraries() with target-specific linking
- Uses dynamic MKL linking (mkl_rt) for better cross-platform compatibility
- Prevents MKL contamination of unrelated targets (like zlib tests)
- Resolves build failures on strict linkers (Arch Linux) while maintaining Ubuntu compatibility
DiskANN commit: c593831 - fix: Replace global MKL linking with target-specific approach
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Co-Authored-By: Claude <noreply@anthropic.com>
* chore: all linux deps
* fix: Update Intel MKL download link to avoid 403 error
- Replace problematic Intel download URL that returns 403 Forbidden
- Use general Intel oneAPI MKL page instead of specific download parameters
- This fixes the lychee link checker CI failure
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: Configure lychee to use browser User-Agent for Intel links
- Replace domain exclusion with browser User-Agent to properly check Intel links
- Intel website blocks automated tools but allows browser-like requests
- This enables proper link validation while avoiding 403 Forbidden errors
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
* fix: Use curl User-Agent for lychee link checking
Intel website has specific anti-bot logic:
- Blocks browser User-Agents (returns 403)
- Blocks lychee default User-Agent (returns 403)
- Allows curl User-Agent (returns 200)
This enables proper link validation for Intel documentation.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
---------
Co-authored-by: Claude <noreply@anthropic.com>