- Added new dependencies including chonkie and markdown-it-py to requirements.txt.
- Refactored the Elasticsearch ingestion script to read and concatenate documents from specified folders.
- Implemented semantic chunking for documents using the chonkie library.
- Removed the old elasticsearch_ingestion_from_docs.py script as its functionality has been integrated into the main ingestion pipeline.
- Updated README.md to reflect new project structure and environment variables.
- Added a new changelog entry for version 1.4.0 detailing recent changes and enhancements.
- Updated `read_files` function to return a list of dictionaries containing 'content' and 'title' keys.
- Added logic to handle concatenation of file contents and improved handling of file prefixes.
- Introduced `get_chunk_docs` function to chunk document contents using `SemanticChunker`.
- Added `convert_chunks_to_document` function to convert chunked content into `Document` objects.
- Integrated logging for chunking process.
- Updated dependencies in `uv.lock` to include `chonkie` and other related packages.
- Implemented a new script `translate_mbpp.py` to generate synthetic datasets using various LLM providers.
- Integrated the `get_prompt_mbpp` function in `prompts.py` to create prompts tailored for AVAP language conversion.
- Implemented `replace_javascript_with_avap` function to handle text replacement.
- Created `read_concat_files` function to read and concatenate files with a specified prefix, replacing JavaScript markers.
- Added functionality to read files from a specified directory and process their contents.
- Implemented `elasticsearch_ingestion` function to handle document ingestion into Elasticsearch.
- Created `build_chunks_from_folder` function to read and clean text files, generating document chunks.
- Added logging for better traceability during the ingestion process.
- Updated `uv.lock` to include `boto3` as a new dependency.