Welcome to neuroqrs’s documentation!#
NeuroQRS (Neuro Query Recommendation System) is Faiss + LLM based query recommender with auto-improvement using closed feedback loop!
It works by first using faiss to check for any similar previous search, if not then it builds one using genai! XD
Installation#
[Coming Soon] Install the neuroqrs
package with pip:
$ pip install neuroqrs
Or install the latest package directly from github
$ pip install git+https://github.com/searchX/neuroqrs
Example Usage#
from neuroqrs.main import NeuroQRS
neuroqrs = NeuroQRS()
async def main():
... statements
import asyncio
asyncio.run(main())
Force fetch documents from chatgpt api (index + search mode)
print(await neuroqrs.query_and_index("nike casual ", "nike", {}, {}))
# Output: ['nike casual black', 'nike casual men', 'nike casual white', 'nike casual wear', 'nike casual shoes']
Only do quick query without reindexing/genai
print(await neuroqrs.quick_query("nike casual ", "nike"))
# Output: ['nike casual black', 'nike casual men', 'nike casual white', 'nike casual wear', 'nike casual shoes']
Try quick query, if data not avaliable then index and get results (combines above two)
print(await neuroqrs.query_maybe_index("nike casual ", "nike", {}, {}))
# Output: ['nike casual black', 'nike casual men', 'nike casual white', 'nike casual wear', 'nike casual shoes']