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MarkItDown
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i like reddit very much
Based on our record, Reddit seems to be a lot more popular than MarkItDown. While we know about 3301 links to Reddit, we've tracked only 15 mentions of MarkItDown. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
You don't need to use an online service to do this; you get to avoid spending money on tokens doing it offline. Gemma 4 works perfectly well offline on limited hardware (I have an 8GB video card) and can handle extracting text from image-based PDFs just fine. Take a PDF -> run it through MarkItDown [1], using the OCR plugin if you need (point it to Gemma 4) -> now you can ask Gemma 4 questions about the document.... - Source: Hacker News / 28 days ago
Related: https://github.com/microsoft/markitdown. - Source: Hacker News / about 1 month ago
I have a standing instruction for any documents that can't natively be read by a given AI to first be converted into .md using https://github.com/microsoft/markitdown which I've found to work really well. - Source: Hacker News / about 1 month ago
Native support: https://techcommunity.microsoft.com/blog/onedriveblog/introducing-markdown-support-in-sharepoint-and-onedrive/4512174 Microsoft OSS python: https://github.com/microsoft/markitdown. - Source: Hacker News / about 1 month ago
Microsoft's open-source MarkItDown is a Python library and CLI that converts PDFs (plus Office files, images, audio and more) into Markdown aimed squarely at language models. It's fast, free, and trivial to drop into a script. - Source: dev.to / about 2 months ago
From urllib.parse import urlparse Def normalize_gh(r): return { "title": r["name"], "url": r["url"], "source": "github", "score": r["stars_this_period"], "desc": r.get("description", ""), "date": r["trending_date"], "lang": r.get("language"), } Def normalize_hn(p): return { "title": p["title"].replace("Show HN: ", ""), "url":... - Source: dev.to / 3 months ago
@tool Def search_reddit(keywords: str, max_results: int = 20) -> list[dict]: """Fallback: search Reddit directly via PRAW.""" reddit = praw.Reddit( client_id=os.environ["REDDIT_CLIENT_ID"], client_secret=os.environ["REDDIT_CLIENT_SECRET"], user_agent="doug-agent/1.0", ) candidates = [] for submission in reddit.subreddit("all").search(keywords, sort="new",... - Source: dev.to / 3 months ago
Import requests Import time Def fetch_subreddit_posts(subreddit, sort="hot", limit=25): url = f"https://www.reddit.com/r/{subreddit}/{sort}.json" params = { "limit": limit, "raw_json": 1, # Prevents HTML encoding in responses } headers = { "User-Agent": "PythonScraper/1.0 (research project)" } response = requests.get(url, params=params, headers=headers) if... - Source: dev.to / 4 months ago
From sessionkeeper import SessionKeeper Async with SessionKeeper("reddit") as sk: page = await sk.get_authenticated_page("https://reddit.com") # You're logged in. Do your automation. await page.goto("https://reddit.com/r/blender/submit"). - Source: dev.to / 5 months ago
It's completely free, and takes just moments to set up - you just need to create an account, and set up keywords for the service to track. When your keywords are mentioned on Reddit, Hackernews, or Lobste.rs, you'll get a tidy little email in your inbox. - Source: dev.to / over 1 year ago
Doc2Markdown - Convert PDF, Word, PowerPoint, Excel and more to clean Markdown
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Markdown to PDF - Super simple way to get your markdown files to PDF
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Mark2PDF - Convert your markdown to beautiful PDF in seconds
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