- 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.
- Changed execution counts for several code cells to maintain proper order.
- Updated system message to specify the role of the agent in responding to AVAP-related queries.
- Modified user input example to inquire about reserved words in AVAP.
- Enhanced AI response to include detailed information about AVAP reserved words and provided a code example demonstrating their usage.
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