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AI · alternatives · 2026

24 alternatives to Morphik – Open-source RAG that understands PDF images, runs locally

Hey HN, we’re Adi and Arnav. A few months ago, we hit a wall trying to get LLMs to answer questions over research papers and instruction manuals. Everything worked fine, until the answer lived inside an image or diagram embedded in the PDF. Even GPT‑4o flubbed it (we recently tried O3 with the same, and surprisingly it flubbed it too). Naive RAG pipelines just pulled in some text chunks and ignored the rest. We took an invention disclosure PDF (https://drive.google.com/file/d/1ySzQgbNZkC5dPLtE3pnnVL2rW_9...) containing an IRR‑vs‑frequency graph and asked GPT “From…

Morphik is an open-source retrieval-augmented generation system designed to extract and answer questions from PDF documents containing images, diagrams, and embedded visual content. Built for researchers and… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

  1. 1

    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…

    2024 · github.com · its alternatives →

  2. 2

    Advanced visual-text compression technology

    2025 · huggingface.co · its alternatives →

  3. 3

    Hey HN - we built Morphik MCP to solve a common problem: finding specific information across scattered technical docs. We've experimented with GraphRAG, ColPali, contextual embeddings, and more. MCP emerged as the solution that unifies these approaches. Features: - Multimodal search across text, diagrams, and videos - Natural language knowledge base management - Fully open-source with responsive support What sets MCP apart is its ability to return images (including diagrams) directly to the MCP client. Users have applied it to search over data ranging from blood tests to patents, and we use…

    2025 · docs.morphik.ai · its alternatives →

  4. 4

    I've developed a Python API service that uses GPT-4o for OCR on PDFs. It features parallel processing and batch handling for improved performance. Not only does it convert PDF to markdown, but it also describes the images within the PDF using captions like `[Image: This picture shows 4 people waving]`. In testing with NASA's Apollo 17 flight documents, it successfully converted complex, multi-oriented pages into well-structured Markdown. The project is open-source and available on GitHub. Feedback is welcome.

    2024 · github.com · its alternatives →

  5. 5

    I really like using NoteBook LM, especially when I have a bunch of research papers I'm trying to extract insights from. For example, if I'm implementing a new feature (like re-ranking) into Morphik, I like to create a notebook with some papers about it, and then compare those models with each other on different benchmarks. I thought it would be cool to create a free, completely open-source version of it, so that I could use some private docs (like my journal!) and see if a NoteBook LM like system can help with that. I've found it to be insanely helpful, so I added a version of it onto the…

    2025 · github.com · its alternatives →

  6. 6

    Hey there HN! We’re Antonio, Luca, and Yuhang, and we’re excited to introduce Fast GraphRAG, an open-source RAG approach that leverages knowledge graphs and the 25 years old PageRank for better information retrieval and reasoning. Building a good RAG pipeline these days takes a lot of manual optimizations. Most engineers intuitively start from naive RAG: throw everything in a vector database and hope that semantic search is powerful enough. This can work for use cases where accuracy isn’t too important and hallucinations are tolerable, but it doesn’t work for more difficult queries that…

    2024 · github.com · its alternatives →

  7. 7

    I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications. It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically. I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...

    2024 · embedding.io · its alternatives →

  8. 8

    Hi HN! We're building R2R [https://github.com/SciPhi-AI/R2R], an open source RAG answer engine that is built on top of Postgres+Neo4j. The best way to get started is with the docs - https://r2r-docs.sciphi.ai/introduction. This is a major update from our V1 which we have spent the last 3 months intensely building after getting a ton of great feedback from our first Show HN (https://news.ycombinator.com/item?id=39510874). We changed our focus to building a RAG engine instead of a framework, because this is what developers asked for the most.…

    2024 · github.com · its alternatives →

  9. 9

    I've built an advanced RAG (Retrieval-Augmented Generation) pipeline from scratch to demystify the complex mechanics of modern LLM-powered Question Answering systems. This repository features: -- An implementation of a sub-question query engine from scratch to answer complex user questions. -- Illustrative explanations that unveil the inner workings of the system. -- An analysis of the challenges I faced while working with the system, like prompt engineering and cost estimation. -- Qualitative comparison with similar frameworks like LlamaIndex, offering a broader perspective. Key Takeaway:…

    2023 · github.com · its alternatives →

  10. 10

    Hi HackerNews, Lately, I have seen an explosion in posts offering paid APIs/services to get unstructured data into LLMs (i.e. langchain extract, ragflow, unstructured, unstract, just to name a few) and I have been largely disappointed by them, either because they fail to implement multimodal support, fail to give good context for "really tricky" PDFs / Word docs / Powerpoints, or are just plain difficult to use. In light of all these posts I figured I'd share my solution that has been working smoothly for me and my clients. I put it up on GitHub for free so you can check it…

    2024 · github.com · its alternatives →

  11. 11

    Hello HN, I'm Owen from SciPhi (https://www.sciphi.ai/), a startup working on simplifying˛Retrieval-Augmented Generation (RAG). Today we’re excited to share R2R (https://github.com/SciPhi-AI/R2R), an open-source framework that makes it simpler to develop and deploy production-grade RAG systems. Just a quick reminder: RAG helps Large Language Models (LLMs) use current information and specific knowledge. For example, it allows a programming assistant to use your latest documents to answer questions. The idea is to gather all the relevant information…

    2024 · github.com · its alternatives →

  12. 12

    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…

    2024 · github.com · its alternatives →

  13. 13QP

    Hey HN! We've just launched Quilt, a robust RAG (Retrieval-Augmented Generation) UI that revolutionizes how you interact with your documents. Key features: - Multi-user setup with private/public document collections - Advanced hybrid RAG pipeline combining full-text & vector search - Smart citations with in-browser PDF preview and highlights - Fully customizable settings and prompts through the UI Making an account is free, no need to even use a strong password: this is only to ensure your documents are separate from the rest. We're keen to hear your thoughts and feedback. What features…

    2024 · quilt.fly.dev · its alternatives →

  14. 14
    RAGstack▲111

    Deploy a private ChatGPT alternative hosted within your VPC

    2023 · github.com · its alternatives →

  15. 15

    RAGLite is a Python package for building Retrieval-Augmented Generation (RAG) applications. RAG applications can be magical when they work well, but anyone who has built one knows how much the output quality depends on the quality of retrieval and augmentation. With RAGLite, we set out to unhobble RAG by mapping out all of its subproblems and implementing the best solutions to those subproblems. For example, RAGLite solves the chunking problem by partitioning documents in provably optimal level 4 semantic chunks. Another unique contribution is its optimal closed-form linear query adapter…

    2024 · github.com · its alternatives →

  16. 16

    Hi all! This morning, we released a new Apache 2.0 licensed model on HuggingFace for detecting hallucinations in retrieval augmented generation (RAG) systems. What we've found is that even when given a "simple" instruction like "summarize the following news article," every LLM that's available hallucinates to some extent, making up details that never existed in the source article -- and some of them quite a bit. As a RAG provider and proponents of ethical AI, we want to see LLMs get better at this. We've published an open source model, a blog more thoroughly describing our methodology (and…

    2023 · vectara.com · its alternatives →

  17. 17

    While building a Retrieval-Augmented Generation (RAG) system, I was frustrated by my vector database consuming 8GB RAM just to search my own PDFs. After incurring $150 in cloud costs, I had an unconventional idea: what if I encoded my documents into video frames? The concept sounded absurd—storing text in video? But modern video codecs have been optimized for compression over decades. So, I converted text into QR codes, then encoded those as video frames, letting H.264/H.265 handle the compression. The results were surprising. 10,000 PDFs compressed down to a 1.4GB video file. Search…

    2025 · github.com · its alternatives →

  18. 18

    Uses hybrid semantic search (combination of dense embeddings and sparse vectors) to retrieve high quality answers across your documents. Features - Significantly faster than competition (Process a 200 page PDF in <5s) - Much better answer quality - Fast summarization tool - Beta API for end to end extractive document QA ([email protected]) Try it out (no login) - Llama 2 paper https:&#x2F;&#x2F;www.dankgpt.com&#x2F;chat&#x2F;346f444d-e286-4671-b157-540f4cb... - Scott Aaronson Quantum Information Science lectures…

    2023 · dankgpt.com · its alternatives →

  19. 19

    Hey HN, solo dev here. After years of frustration with how LLMs handle complex documents, especially PDFs with tables, I decided to build a solution myself. My approach uses a Markdown conversion step to preserve the table structure, which seems to work surprisingly well for chunking. This little parser is the first public piece of a much larger, privacy-focused AI platform I'm building. I'm pretty much running on fumes financially, so any feedback, critique, or support is massively appreciated. Happy to answer any questions about the approach!

    Nov 2025 · github.com · its alternatives →

  20. 20

    Hey hacker news, We’re the cofounders at Psychic.dev (http:&#x2F;&#x2F;psychic.dev) where we help companies connect LLMs to private data. With the launch of Llama 2, we think it’s finally viable to self-host an internal application that’s on-par with ChatGPT, so we did exactly that and made it an open source project. We also included a vector DB and API server so you can upload files and connect Llama 2 to your own data. The RAG in RAGstack stands for Retrieval Augmented Generation, a technique where the capabilities of a large language model (LLM) are augmented by retrieving information…

    2023 · github.com · its alternatives →

  21. 21DQ

    Hello fellow hackers, we made a site that gets GPT to answer your question using the info on a webpage you specify or document you upload (e.g., a large textbook .pdf file). Background: When ChatGPT came out, I had the idea of having it pull answers from my stereo receiver's annoyingly dense 32 page manual. My weekend project prototype proceeded to surprise with great answers—just like what we've all experienced by now. My co-founder thought we should productize it, and make it easy to use online. So here we are with a very early beta! (Try it on a HN thread...)

    2023 · klavier.ai · its alternatives →

  22. 22

    Hey HN! I built SimplePDF Copilot: an AI assistant that can interact with the PDF editor. It fills fields, answers questions, focuses on a specific field, adds fields, deletes pages, and so on. It's built on top of SimplePDF that I started 7 years ago, pioneering privacy-respecting client-side pdf editing, now used monthly by 200k+ people. As for the privacy model: the PDF itself never leaves the browser. Parsing, rendering, and field detection all run client-side. The text the model needs (and your messages) goes to whatever LLM you point at. By default that's our demo proxy (DeepSeek V4…

    May 2026 · copilot.simplepdf.com · its alternatives →

  23. 23

    RAG pipeline with PDF OCR, vector search and chat UI

    2025 · github.com · its alternatives →

  24. 24

    A Python CLI to test, benchmark, and find the best RAG chunking strategy for your Markdown documents. - messkan/rag-chunk

    Nov 2025 · github.com · its alternatives →

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