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This commit adds code changes to generate a QA dataset and evaluate the performance of the retriever. The `eval/dataset.py` file includes the generation of the QA dataset using the `generate_qa_embedding_pairs` function. The resulting dataset is saved as `pg_eval_dataset.json`. The `eval/run.py` file performs the evaluation using the `RetrieverEvaluator` class and saves the evaluation results as `retriever_eval_results.csv`. Additionally, the `ingestion/apply_ingestion.py` file is modified to import from the `ingestion.dataloader` module. Note: Please remove any meta information like issue references, tags, or author names from the commit message.
This commit adds an async method `arun` to the `HyDE` class in `preretrieve/hyde.py`. The `arun` method allows for invoking the HyDE chain asynchronously using the `await` keyword. This improves the efficiency and responsiveness of the code. Note: Please remove any meta information like issue references, tags, or author names from the commit message.
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