Bump package version to 0.1.27 (#994)
Co-authored-by: Deven Patel <deven298@yahoo.com>
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@@ -536,13 +536,10 @@ class EmbedChain(JSONSerializable):
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or the dry run result
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:rtype: str, if citations is False, otherwise Tuple[str,List[Tuple[str,str,str]]]
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"""
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if "citations" in kwargs:
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citations = kwargs.pop("citations")
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else:
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citations = False
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citations = kwargs.get("citations", False)
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db_kwargs = {key: value for key, value in kwargs.items() if key != "citations"}
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contexts = self._retrieve_from_database(
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input_query=input_query, config=config, where=where, citations=citations, **kwargs
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input_query=input_query, config=config, where=where, citations=citations, **db_kwargs
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)
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if citations and len(contexts) > 0 and isinstance(contexts[0], tuple):
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contexts_data_for_llm_query = list(map(lambda x: x[0], contexts))
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@@ -1,10 +1,10 @@
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import concurrent.futures
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import hashlib
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import logging
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from urllib.parse import urlparse
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import requests
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from tqdm import tqdm
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from urllib.parse import urlparse
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try:
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from bs4 import BeautifulSoup
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@@ -38,7 +38,7 @@ class SitemapLoader(BaseLoader):
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response = requests.get(sitemap_url)
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response.raise_for_status()
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else:
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with open(sitemap_url, "r") as file:
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with open(sitemap_url, "r") as file:
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soup = BeautifulSoup(file, "xml")
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links = [link.text for link in soup.find_all("loc") if link.parent.name == "url"]
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if len(links) == 0:
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@@ -1,6 +1,6 @@
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[tool.poetry]
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name = "embedchain"
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version = "0.1.26"
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version = "0.1.27"
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description = "Data platform for LLMs - Load, index, retrieve and sync any unstructured data"
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authors = [
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"Taranjeet Singh <taranjeet@embedchain.ai>",
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