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Currently, table information is gathered through SQLAlchemy as complete table DDL and a user-selected number of sample rows from each table. This PR adds the option to use user-defined table information instead of automatically collecting it. This will use the provided table information and fall back to the automatic gathering for tables that the user didn't provide information for. Off the top of my head, there are a few cases where this can be quite useful: - The first n rows of a table are uninformative, or very similar to one another. In this case, hand-crafting example rows for a table such that they provide the good, diverse information can be very helpful. Another approach we can think about later is getting a random sample of n rows instead of the first n rows, but there are some performance considerations that need to be taken there. Even so, hand-crafting the sample rows is useful and can guarantee the model sees informative data. - The user doesn't want every column to be available to the model. This is not an elegant way to fulfill this specific need since the user would have to provide the table definition instead of a simple list of columns to include or ignore, but it does work for this purpose. - For the developers, this makes it a lot easier to compare/benchmark the performance of different prompting structures for providing table information in the prompt. These are cases I've run into myself (particularly cases 1 and 3) and I've found these changes useful. Personally, I keep custom table info for a few tables in a yaml file for versioning and easy loading. Definitely open to other opinions/approaches though! |
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| .. | ||
| examples | ||
| generic | ||
| async_chain.ipynb | ||
| generic_how_to.rst | ||
| getting_started.ipynb | ||
| how_to_guides.rst | ||
| key_concepts.md | ||
| utility_how_to.rst | ||