Files
Aakash Suresh b4bb8dec75 feat: Add MCP integration support for Slack and Twitter (#134)
* 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.
2025-10-07 02:18:32 -07:00
..
2025-09-24 11:19:04 -07:00

LEANN Tests

This directory contains automated tests for the LEANN project using pytest.

Test Files

test_readme_examples.py

Tests the examples shown in README.md:

  • The basic example code that users see first (parametrized for both HNSW and DiskANN backends)
  • Import statements work correctly
  • Different backend options (HNSW, DiskANN)
  • Different LLM configuration options (parametrized for both backends)
  • All main README examples are tested with both HNSW and DiskANN backends using pytest parametrization

test_basic.py

Basic functionality tests that verify:

  • All packages can be imported correctly
  • C++ extensions (FAISS, DiskANN) load properly
  • Basic index building and searching works for both HNSW and DiskANN backends
  • Uses parametrized tests to test both backends

test_document_rag.py

Tests the document RAG example functionality:

  • Tests with facebook/contriever embeddings
  • Tests with OpenAI embeddings (if API key is available)
  • Tests error handling with invalid parameters
  • Verifies that normalized embeddings are detected and cosine distance is used

test_diskann_partition.py

Tests DiskANN graph partitioning functionality:

  • Tests DiskANN index building without partitioning (baseline)
  • Tests automatic graph partitioning with is_recompute=True
  • Verifies that partition files are created and large files are cleaned up for storage saving
  • Tests search functionality with partitioned indices
  • Validates medoid and max_base_norm file generation and usage
  • Includes performance comparison between DiskANN (with partition) and HNSW
  • Note: These tests are skipped in CI due to hardware requirements and computation time

Running Tests

Install test dependencies:

# Using uv dependency groups (tools only)
uv sync --only-group test

Run all tests:

pytest tests/

# Or with coverage
pytest tests/ --cov=leann --cov-report=html

# Run in parallel (faster)
pytest tests/ -n auto

Run specific tests:

# Only basic tests
pytest tests/test_basic.py

# Only tests that don't require OpenAI
pytest tests/ -m "not openai"

# Skip slow tests
pytest tests/ -m "not slow"

# Run DiskANN partition tests (requires local machine, not CI)
pytest tests/test_diskann_partition.py

Run with specific backend:

# Test only HNSW backend
pytest tests/test_basic.py::test_backend_basic[hnsw]
pytest tests/test_readme_examples.py::test_readme_basic_example[hnsw]

# Test only DiskANN backend
pytest tests/test_basic.py::test_backend_basic[diskann]
pytest tests/test_readme_examples.py::test_readme_basic_example[diskann]

# All DiskANN tests (parametrized + specialized partition tests)
pytest tests/ -k diskann

CI/CD Integration

Tests are automatically run in GitHub Actions:

  1. After building wheel packages
  2. On multiple Python versions (3.9 - 3.13)
  3. On both Ubuntu and macOS
  4. Using pytest with appropriate markers and flags

pytest.ini Configuration

The pytest.ini file configures:

  • Test discovery paths
  • Default timeout (600 seconds)
  • Environment variables (HF_HUB_DISABLE_SYMLINKS, TOKENIZERS_PARALLELISM)
  • Custom markers for slow and OpenAI tests
  • Verbose output with short tracebacks

Known Issues

  • OpenAI tests are automatically skipped if no API key is provided