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Working implementation. Using ray, tested end to end locally
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KastanDay committed Dec 14, 2023
1 parent 2b52177 commit 00834df
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import os
import supabase
import pandas as pd
import time
from concurrent.futures import ProcessPoolExecutor
from functools import partial
from multiprocessing import Manager

import supabase

DOCUMENTS_TABLE = os.environ['NEW_NEW_NEWNEW_MATERIALS_SUPABASE_TABLE']
SUPABASE_CLIENT = supabase.create_client(supabase_url=os.environ['SUPABASE_URL'], supabase_key=os.environ['SUPABASE_API_KEY'])
SUPABASE_CLIENT = supabase.create_client(supabase_url=os.environ['SUPABASE_URL'], supabase_key=os.environ['SUPABASE_API_KEY']) # type: ignore


def context_processing(found_docs, search_query, course_name):
def context_parent_doc_padding(found_docs, search_query, course_name):
"""
Takes top N contexts acquired from QRANT similarity search and pads them
"""
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