- Implemented parser for executing AVAP files within a Docker container (parser v1.py).
- Created a script to send AVAP code to a local server and handle responses (parser v2.py).
- Introduced a mock MBAP test harness to validate AVAP code against expected outputs (mbap_tester.py).
- Added transformation logic to convert AVAP code into Python-like syntax for testing purposes.
- Enhanced error handling and output formatting in the testing harness.
- Implemented code to utilize OllamaEmbeddings for embedding documents.
- Included example usage with sample text inputs.
- Demonstrated response handling from the Ollama LLM.
- Noted deprecation warning for the Ollama class in LangChain.
- 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.
- Created a new Jupyter notebook for analyzing BEIR dataset with CosQA using Ollama embeddings.
- Implemented a custom embedding class to integrate LangChain's OllamaEmbeddings with BEIR.
- Added data loading and evaluation logic for the CosQA dataset.
- Updated `uv.lock` to remove unnecessary dependencies (`mteb` and `polars`) and incremented revision number.
pseco
acano