mirror of
https://github.com/Mintplex-Labs/anything-llm.git
synced 2024-11-09 00:10:10 +01:00
86 lines
2.8 KiB
Python
86 lines
2.8 KiB
Python
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import os, json, requests, tempfile
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from requests_html import HTMLSession
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from langchain.document_loaders import UnstructuredHTMLLoader
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def fetch_all_publications(subdomain):
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file_path = f"./outputs/substack-logs/substack-{subdomain}.json"
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if os.path.isdir("./outputs/substack-logs") == False:
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os.makedirs("./outputs/substack-logs")
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if os.path.exists(file_path):
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with open(file_path, "r") as file:
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print(f"Returning cached data for substack {subdomain}.substack.com. If you do not wish to use stored data then delete the file for this newsletter to allow refetching.")
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return json.load(file)
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collecting = True
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offset = 0
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publications = []
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while collecting is True:
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url = f"https://{subdomain}.substack.com/api/v1/archive?sort=new&offset={offset}"
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response = requests.get(url)
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if(response.ok == False):
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print("Bad response - exiting collection")
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collecting = False
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continue
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data = response.json()
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if(len(data) ==0 ):
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collecting = False
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continue
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for publication in data:
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publications.append(publication)
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offset = len(publications)
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with open(file_path, 'w+', encoding='utf-8') as json_file:
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json.dump(publications, json_file, ensure_ascii=True, indent=2)
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print(f"{len(publications)} publications found for author {subdomain}.substack.com. Saved to substack-logs/channel-{subdomain}.json")
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return publications
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def only_valid_publications(publications= []):
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valid_publications = []
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for publication in publications:
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is_paid = publication.get('audience') != 'everyone'
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if (is_paid and publication.get('should_send_free_preview') != True) or publication.get('type') != 'newsletter': continue
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valid_publications.append(publication)
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return valid_publications
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def get_content(article_link):
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print(f"Fetching {article_link}")
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if(len(article_link) == 0):
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print("Invalid URL!")
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return None
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session = HTMLSession()
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req = session.get(article_link)
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if(req.ok == False):
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print("Could not reach this url!")
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return None
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req.html.render()
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full_text = None
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with tempfile.NamedTemporaryFile(mode = "w") as tmp:
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tmp.write(req.html.html)
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tmp.seek(0)
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loader = UnstructuredHTMLLoader(tmp.name)
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data = loader.load()[0]
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full_text = data.page_content
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tmp.close()
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return full_text
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def append_meta(publication, text):
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meta = {
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'url': publication.get('canonical_url'),
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'thumbnail': publication.get('cover_image'),
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'title': publication.get('title'),
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'subtitle': publication.get('subtitle'),
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'description': publication.get('description'),
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'createdAt': publication.get('post_date'),
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'wordCount': publication.get('wordcount')
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}
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return "Newsletter Metadata:\n"+json.dumps(meta)+"\n\nArticle Content:\n" + text
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