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Knowledge folders are a workaround to work with very large amounts of text that are larger than the limit of what models can process at once. A semantic search identifies relevant sections and only these sections are then used to generate the response (here is a detailed explanation). Excel and CSV files need a different workaround to be processed. We use the data analyst functionality, which generates Python code that is then executed to extract relevant information (here explained in depth). In summary, these functionalities are used to process specific formats of data. Unfortunately, they cannot be combined, since the knowledge folder functionality would only extract parts of the attached file and this information would be missing to work with the data analyst effectively.