Format entire codebase with ruff and add type hints across all modules:
- Apply ruff formatting to all Python files (121 files, 17K insertions)
- Add type hints to function signatures throughout lightrag core and API
- Update test suite with improved type annotations and docstrings
- Add pyrightconfig.json for static type checking configuration
- Create prompt_optimized.py and test_extraction_prompt_ab.py test files
- Update ruff.toml and .gitignore for improved linting configuration
- Standardize code style across examples, reproduce scripts, and utilities
Added support for structured output (JSON mode) from the OpenAI API in `openai.py` and `azure_openai.py`.
When `response_format` is used to request structured data, the new logic checks for the `message.parsed` attribute. If it exists, it's serialized into a JSON string as the final content. If not, the code falls back to the existing `message.content` handling, ensuring backward compatibility.
- Add enable_cot parameter to all LLM APIs
- Implement CoT for OpenAI with <think> tags
- Log warnings for unsupported providers
- Enable CoT in query operations
- Handle streaming and non-streaming CoT
• Remove global temperature parameter
• Add provider-specific temp configs
• Update env example with new settings
• Fix Bedrock temperature handling
• Clean up splash screen display
Replace regex-based JSON extraction with json-repair for better handling of malformed LLM responses. Remove deprecated JSON parsing utilities and clean up keyword_extraction parameter across LLM providers.
- Remove locate_json_string_body_from_string() and convert_response_to_json()
- Use json-repair.loads() in extract_keywords_only() for robust parsing
- Clean up LLM interfaces and remove unused parameters
- Add json-repair dependency
This parameter is no longer used. Its removal simplifies the API and clarifies that token length management is handled by upstream text chunking logic rather than the embedding wrapper.
