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index_docs.py
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121 lines (92 loc) · 2.38 KB
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import sys
import time
import requests
from bs4 import BeautifulSoup
import nltk
from lib.database import weaviate_schema, weaviate_update
from lib.ai import ai
nltk.download('punkt')
tokenizer = nltk.data.load('tokenizers/punkt/english.pickle')
# weavaite schema
schema = weaviate_schema("docs")
# get the sitemap and load it
sitemap = "https://docs.featurebase.com/sitemap.xml"
result = requests.get(sitemap).text
# parse with BS
soup = BeautifulSoup(result, features="xml")
urls = soup.find_all("loc")
# build list of URLs
_urls = []
for url in urls:
_urls.append(url.text)
# overwrite the list
urls = _urls
for url in urls:
if "404" in url:
continue
res = requests.get(url)
html_page = res.content
soup = BeautifulSoup(html_page, 'html.parser')
title = soup.find('title').text
print("Indexing: %s" % title)
text = soup.find("div", {"id": "main-content"})
words = ""
previous_words = ""
for i, entry in enumerate(tokenizer.tokenize(text.text)):
print(i)
words = words + " " + entry.replace("\n", " ")
if (i % 3) == 0:
# ai_doc = ai("mirror", {"words": words})
document = {
"sentence": words,
"url": url,
"title": title
}
print("==================")
print(document)
for x in range(10):
try:
print(weaviate_update(document, "Docs"))
break
except Exception as ex:
print("%s - sleeping 10 seconds for retry" % ex)
time.sleep(10)
print("==================")
words = ""
if words != "":
# ai_doc = ai("mirror", {"words": words})
document = {
"sentence": words,
"url": url,
"title": title
}
print("==================")
print(document)
for x in range(10):
try:
print(weaviate_update(document, "Docs"))
break
except Exception as ex:
print("%s - sleeping 10 seconds for retry" % ex)
time.sleep(10)
print("==================")
sys.exit()
"""
splits = text.text.split(" ") # split on spaces
fulltexts = []
_fulltext = ""
for split in splits:
_fulltext = _fulltext + split + " "
# if we have a long string and a stop character
if len(_fulltext) > 208 and (split.endswith(".") or split.endswith('."') or split.endswith("?") or split.endswith("!")):
fulltexts.append(_fulltext)
_fulltext = ""
fulltexts.append(_fulltext)
for fulltext in fulltexts:
document = {
"url": url,
"title": title,
"sentence": fulltext.strip(" ")
}
weaviate_update(document, "Docs")
"""