Show HN : Low code cloud document database https://ift.tt/HoS8iZh

Show HN : Low code cloud document database Low code cloud document database https://slyce-io.co.uk/ August 17, 2023 at 03:43PM

Show HN: I resurrected one of the top dead Show HNs https://ift.tt/GZ43IbA

Show HN: I resurrected one of the top dead Show HNs OneView was first posted to HN in 2017, but died sometime around late 2019. Using the web archive I cobbled together something that works. According to this[0], oneview is the #5 top dead show hn. [0] https://ift.tt/UYnOdqc... https://ift.tt/7O6Igxq August 17, 2023 at 08:26PM

Show HN: Create your own Discover Weekly https://ift.tt/6GSIuR9

Show HN: Create your own Discover Weekly Choose a few playlists to get new tracks from, and they'll be filtered out every Monday to a new playlist. Kind of like Discover Weekly, but you get to choose the music sources. Hope you enjoy, and I would love feedback! https://ift.tt/mkxWUKG August 17, 2023 at 08:17PM

Show HN: Interactive exercises for GNU grep, sed and awk https://ift.tt/fDlRrnK

Show HN: Interactive exercises for GNU grep, sed and awk Hello! For the past few months, I've been using a Python framework called Textual to create TUI apps for interactive exercises. Released the app for GNU awk earlier today, so thought I'd create a post here. If you already know how to manage Python packages, you can use the following command to get all the three apps: pip install grepexercises sedexercises awkexercises `pipx` should also work, but I haven't tested it. The GitHub repo has the source code as well as more detailed installation instructions. You can use alternative CLI tools to solve these exercises as well. For example, Perl instead of GNU awk or ripgrep instead of GNU grep and so on. Hope you find these TUI apps useful. I'd highly appreciate your feedback. Happy learning :) https://ift.tt/PoVJZf4 August 17, 2023 at 03:43PM

Show HN: Strich – Barcode scanning for web apps https://ift.tt/CqFHBjE

Show HN: Strich – Barcode scanning for web apps Hi, I'm Alex - the creator of STRICH ( https://strich.io ), a barcode scanning library for web apps. Barcode scanning in web apps is nothing new. In my previous work experience, I've had the opportunity to use both high-end commercial offerings (e.g. Scandit) and OSS libraries like QuaggaJS or ZXing-JS in a wide range of customer projects, mainly in logistics. I became dissatisfied with both. The established commercial offerings had five- to six-figure license fees and the developer experience was not always optimal. The web browser as a platform also seemed not to be the main priority for these players. The open source libraries are essentially unmaintained and not suitable for commercial use due to the lack of support. Also the recognition performance is not enough for some cases - for a detailed comparison see https://ift.tt/HnqVzW4 Having dabbled a bit in Computer Vision topics before, and armed with an understanding of the market situation, I set out to build an alternative to fill the gap between the two worlds. After almost two years of on-and-off development and 6 months of piloting with a key customer, STRICH launched at beginning of this year. STRICH is built exclusively for web browsers running on smartphones. I believe the vast majority of barcode scanning apps are in-house line of business apps that benefit from distribution outside of app stores and a single codebase with abundant developer resources. Barcode scanning in web apps is efficient and avoids platform risk and unnecessary costs associated with developing and publishing native apps. https://strich.io August 17, 2023 at 06:54PM

Show HN: Rules – Shortcuts Automation Based on Calendar Events https://ift.tt/oqgZW52

Show HN: Rules – Shortcuts Automation Based on Calendar Events Read and thought once too often that "This would be trivial if Calendar Events were triggers for Personal Shortcuts Automations". So decided to create a Mac app for it. The app works similar to Rules in Mail: - Specify some conditions (e.g. Calendar is "Work", Location contains "zoom") - Choose shortcuts to run on events that meet the conditions - you can have multiple actions, each with a different offset and custom input Good to know: - The app can only trigger automations while your Mac is awake (missed actions can be triggered on wake up) - The free version offers full functionality, but is limited to a max of 2 rules. Pro is a one-time purchase - All your data stays on device + no ads or data collection I would appreciate any feedback, especially what automations you might use the app for https://ift.tt/HawRKIs August 17, 2023 at 02:23PM

Show HN: Marqo – Vectorless Vector Search https://ift.tt/UiY0oFs

Show HN: Marqo – Vectorless Vector Search Marqo is an end-to-end vector search engine. It contains everything required to integrate vector search into an application in a single API. Here is a code snippet for a minimal example of vector search with Marqo: mq = marqo.Client() mq.create_index("my-first-index") mq.index("my-first-index").add_documents([{"title": "The Travels of Marco Polo"}]) results = mq.index("my-first-index").search(q="Marqo Polo") Why Marqo? Vector similarity alone is not enough for vector search. Vector search requires more than a vector database - it also requires machine learning (ML) deployment and management, preprocessing and transformations of inputs as well as the ability to modify search behavior without retraining a model. Marqo contains all these pieces, enabling developers to build vector search into their application with minimal effort. Why not X, Y, Z vector database? Vector databases are specialized components for vector similarity. They are “vectors in - vectors out”. They still require the production of vectors, management of the ML models, associated orchestration and processing of the inputs. Marqo makes this easy by being “documents in, documents out”. Preprocessing of text and images, embedding the content, storing meta-data and deployment of inference and storage is all taken care of by Marqo. We have been running Marqo for production workloads with both low-latency and large index requirements. Marqo features: - Low-latency (10’s ms - configuration dependent), large scale (10’s - 100’s M vectors). - Easily integrates with LLM’s and other generative AI - augmented generation using a knowledge base. - Pre-configured open source embedding models - SBERT, Huggingface, CLIP/OpenCLIP. - Pre-filtering and lexical search. - Multimodal model support - search text and/or images. - Custom models - load models fine tuned from your own data. - Ranking with document meta data - bias the similarity with properties like popularity. - Multi-term multi-modal queries - allows per query personalization and topic avoidance. - Multi-modal representations - search over documents that have both text and images. - GPU/CPU/ONNX/PyTorch inference support. See some examples here: Multimodal search: [1] https://ift.tt/ljhqbU3... Refining image quality and identifying unwanted content: [2] https://ift.tt/G6aMV2f... Question answering over transcripts of speech: [3] https://ift.tt/GTgv6cH Question and answering over technical documents and augmenting NPC's with a backstory: [4] https://ift.tt/YNmJCaE... https://ift.tt/hNIDgFK August 16, 2023 at 07:31PM