- 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.
- 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.
- Set execution counts to null for initial cells in langgraph_agent_simple.ipynb
- Update execution counts for subsequent cells to maintain order
- Change output stream name from stdout to stderr for error handling
- Capture and log detailed error messages for failed Langfuse client authentication
Update uv.lock to manage accelerate dependency
- Remove accelerate from main dependencies
- Add accelerate to dev dependencies with version specification
- Adjust requires-dist section to reflect changes in dependency management
- 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.
pseco
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