An index to use with Large Language Models (LLMs) to answer questions about Bytewax documentation and Python API.
Make a new virtual env. Then install the requirements
pip install -r requirements.txtAn index-file must exist before you can ask questions. You can run the file
query_bytewax.py to create an index, or you can download one
here
Note that the preloaded index file above only contains a subset of the Bytewax repository. You can edit the python-file to not exclude any folders. By default, Rust source files are not included.
Usage requires at least an OpenAI API key in your environment variables. If you want to recreate the index, a Github API key is needed as well. With the current configuration, creating an index uses free HuggingFace models, but asking queries requires OpenAI quota.
To get more relevant answers, increase the n_sources parameter (default is 2)
python query_bytewax.py -n 3
Enter query: How can I emit a state after each change or update for a given key
INFO:root:> [query] Total LLM token usage: 1453 tokens
INFO:root:> [query] Total embedding token usage: 15 tokens
To emit a state after each change or update for a given key, you can use a
stateful map function. This function will take in the key and the new state,
and then emit the updated state for that key. For example, in the code
snippet provided, the stateful map function "order_book" is used to update
the OrderBook object with the new state and then emit the updated state for
that key. Additionally, the code will check if the order should be removed
and if not it will update the order. If the order was removed, it will check
to make sure the bid and ask prices are modified if required. Finally, the
`capture` operator is used to use the output builder function that was
defined earlier and print out the output to the terminal.