RAGCheck

What it does

Most PDF-to-text tools just extract text. But when you feed that into an LLM or vector DB, tables break, scans become unreadable, and headers repeat in every chunk. RAGCheck doesn't just convert — it diagnoses. Get a RAG Readiness Score (0-100) with actionable recommendations. Download clean Markdown, structured JSON, and pre-chunked text optimized for embeddings. Free tier: 3 conversions/day. No signup required.

• OS
  Open-source Rule-based PDF parser for RAG2024 · github.com · ▲293

  The PDF parser is a rule based parser which uses text co-ordinates (boundary box), graphics and font data. The PDF parser works off text layer and also offers a OCR option to automatically use OCR if there are scanned pages in your PDFs. The OCR feature is based off a modified version of tika which uses tesseract underneath. The PDF Parser offers the following features: * Sections and subsections along with their levels. * Paragraphs - combines lines. * Links between sections and paragraphs. * Tables along with the section the tables are found in. * Lists and nested lists. * Join content…

• RO
  Ragas – Open-source library for evaluating RAG pipelines2024 · github.com · ▲121

  Ragas is an open-source library for evaluating and testing RAG and other LLM applications. Github: https://docs.ragas.io/en/stable/, docs: https://docs.ragas.io/. Ragas provides you with different sets of metrics and methods like synthetic test data generation to help you evaluate your RAG applications. Ragas started off by scratching our own itch for evaluating our RAG chatbots last year. Problems Ragas can solve - How do you choose the best components for your RAG, such as the retriever, reranker, and LLM? - How do you formulate a test dataset…

• 
  RagifyMay 2026 · ragify.it · ▲3

  Make your PDFs RAG-ready

• 
  Document Parser by Contextual AI2025 · ▲118

  Multimodal document parser designed for RAG systems

• 
  Dabarqus2024 · ▲92

  Add PDF chat to your LLM app in less than 9 lines of code

• OS
  Open-Source Colab Notebooks to Implement Advanced RAG Techniques2024 · github.com · ▲98

  Hey HN fam, We’ve seen developers spend a lot of time implementing advanced RAG techniques from scratch. While these techniques are essential for improving performance, their implementation requires a lot of effort and testing! To help with this process, our team (Athina AI) has released Open-Source Advanced RAG Cookbooks. This is a collection of ready-to-run Google Colab notebooks featuring the most commonly implemented techniques. Please show us some love by starring the repo if you find this useful!

• 
  I trained a 125M model to autocomplete piano on-device▲598

  I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.

  AI · 17d ago · simedw.com

• 
  Astute▲585

  Automate your B2B brand going viral, with new media creators

  AI · 19d ago · company-app.joinastute.com

• 
  Grok Bot▲547

  AI teammates that you can give real work to

  AI · 26d ago · x.ai

• 
  Needle2: 14MB agentic LLM for phones, wearables, smart home and robots▲537

  Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…

  AI · 27d ago · cactuscompute.com

• 
  Monid▲475

  One wallet, every paid tool your agent needs

  AI · 7d ago · monid.ai

• 
  Clara AI SDR▲460

  Turn website visitors into qualified pipeline

  AI · 20d ago · clarasdr.ai

• 
  Brew ▲905

  Like Claude design for email marketing

  AI · May 2026 · brew.new

• 
  Kilo Code for VS Code▲897

  Parallel agents, diff reviewer, and multi-model comparisons

  Dev tools · May 2026 · kilo.ai

• 
  StoreClaw▲805

  Grow your store profits with agents that know how to sell

  AI · May 2026 · storeclaw.ai

• 
  PollyReach▲796

  Give your agent a real number and voice to make calls.

  AI · May 2026 · pollyreach.ai

• NW
  Needle: We Distilled Gemini Tool Calling into a 26M Model▲776

  Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…

  Life & fun · May 2026 · github.com

• FM
  Files.md – Open-source alternative to Obsidian▲730

  Dev tools · May 2026 · github.com