Bagels is a terminal-based expense tracker written in Python. It provides a simple text-based user interface (TUI) for recording and viewing expenses, allowing users to add transactions with descriptions, amounts, and categories. Bagels emphasizes ease of use and speed, offering features like auto-completion and quick keyboard navigation. It also supports exporting data to CSV for further analysis or use in other tools.
The author announced the acquisition of their bootstrapped SaaS startup, Refind, by Readwise. After five years of profitable growth and serving thousands of paying users, they decided to join forces with Readwise to accelerate development and reach a wider audience. They expressed gratitude to the Hacker News community for their support and feedback throughout Refind's journey, highlighting how the platform played a crucial role in their initial user acquisition and growth. The author is excited about the future and the opportunity to continue building valuable tools for learners with the Readwise team.
The Hacker News comments on the "Thank HN" acquisition post are overwhelmingly positive and congratulatory. Several commenters inquire about the startup's niche and journey, expressing genuine curiosity and admiration for the bootstrapped success. Some offer advice for navigating the acquisition process, while others share their own experiences with acquisitions, both positive and negative. A few highlight the importance of celebrating such wins within the startup community, offering encouragement to other founders. The most compelling comments offer practical advice stemming from personal experience, like negotiating earn-outs and retaining key employees. There's a general sense of shared excitement and goodwill throughout the thread.
Libmodulor is a TypeScript library designed for building cross-platform applications with a strong focus on developer experience and maintainability. It leverages a modular architecture, promoting code reuse and separation of concerns through features like dependency injection, a unified event bus, and lifecycle management. The library aims to simplify complex application logic by providing built-in solutions for common tasks such as state management, routing, and API interactions, allowing developers to focus on building features rather than boilerplate. While opinionated in its structure, libmodulor offers flexibility in choosing UI frameworks and targets web, desktop, and mobile platforms.
HN commenters generally express skepticism about the value proposition of libmodulor, particularly regarding its use of TypeScript and perceived over-engineering. Several question the necessity of such a library for simple projects, arguing that vanilla HTML, CSS, and JavaScript are sufficient. Some doubt the touted "multi-platform" capabilities, suggesting it's merely a web framework repackaged. Others criticize the project's apparent complexity and lack of clear advantages over established solutions like React Native or Flutter. The focus on server components and the use of RPC are also questioned, with commenters pointing to potential performance drawbacks. A few express interest in specific aspects, such as the server-driven UI approach and the developer experience, but overall sentiment leans towards cautious skepticism.
The author created a system using the open-source large language model, Ollama, to automatically respond to SMS spam messages. Instead of simply blocking the spam, the system engages the spammers in extended, nonsensical, and often humorous conversations generated by the LLM, wasting their time and resources. The goal is to make SMS spam less profitable by increasing the cost of sending messages, ultimately discouraging spammers. The author details the setup process, which involves running Ollama locally, forwarding SMS messages to a server, and using a Python script to interface with the LLM and send replies.
HN users generally praised the project for its creativity and humor. Several commenters shared their own experiences with SMS spam, expressing frustration and a desire for effective countermeasures. Some discussed the ethical implications of engaging with spammers, even with an LLM, and the potential for abuse or unintended consequences. Technical discussion centered around the cost-effectiveness of running such a system, with some suggesting optimizations or alternative approaches like using a less resource-intensive LLM. Others expressed interest in expanding the project to handle different types of spam or integrating it with existing spam-filtering tools. A few users also pointed out potential legal issues, like violating telephone consumer protection laws, depending on the nature of the responses generated by the LLM.
The Hacker News post asks if anyone is working on interesting projects using small language models (LLMs). The author is curious about applications beyond the typical large language model use cases, specifically focusing on smaller, more resource-efficient models that could run on personal devices. They are interested in exploring the potential of these compact LLMs for tasks like personal assistants, offline use, and embedded systems, highlighting the benefits of reduced latency, increased privacy, and lower operational costs.
HN users discuss various applications of small language models (SLMs). Several highlight the benefits of SLMs for on-device processing, citing improved privacy, reduced latency, and offline functionality. Specific use cases mentioned include grammar and style checking, code generation within specialized domains, personalized chatbots, and information retrieval from personal documents. Some users point to quantized models and efficient architectures like llama.cpp as enabling technologies. Others caution that while promising, SLMs still face limitations in performance compared to larger models, particularly in tasks requiring complex reasoning or broad knowledge. There's a general sense of optimism about the potential of SLMs, with several users expressing interest in exploring and contributing to this field.
The author trained a YOLOv5 model to detect office chairs in a dataset of 40 million hotel room photos, aiming to identify properties suitable for "bleisure" (business + leisure) travelers. They achieved reasonable accuracy and performance despite the challenges of diverse chair styles and image quality. The model's output is a percentage indicating the likelihood of an office chair's presence, offering a quick way to filter a vast image database for hotels catering to digital nomads and business travelers. This project demonstrates a practical application of object detection for a specific niche market within the hospitality industry.
Hacker News users discussed the practical applications and limitations of using YOLO to detect office chairs in hotel photos. Some questioned the business value, wondering how chair detection translates to actionable insights for hotels. Others pointed out potential issues with YOLO's accuracy, particularly with diverse chair designs and varying image quality. The computational cost and resource intensity of processing such a large dataset were also highlighted. A few commenters suggested alternative approaches, like crowdsourcing or using pre-trained models specifically designed for furniture detection. There was also a brief discussion about the ethical implications of analyzing hotel photos without explicit consent.
The original poster is exploring alternative company structures, specifically cooperatives (co-ops), for a SaaS business and seeking others' experiences with this model. They're interested in understanding the practicalities, benefits, and drawbacks of running a SaaS as a co-op, particularly concerning attracting investment, distributing profits, and maintaining developer motivation. They wonder if the inherent democratic nature of co-ops might hinder rapid decision-making, a crucial aspect of the competitive SaaS landscape. Essentially, they're questioning whether the co-op model is compatible with the demands of building and scaling a successful SaaS company.
Several commenters on the Hacker News thread discuss their experiences with or thoughts on alternative company models for SaaS, particularly co-ops. Some express skepticism about the scalability of co-ops for SaaS due to the capital-intensive nature of the business and the potential difficulty in attracting and retaining top talent without competitive salaries and equity. Others share examples of successful co-ops, highlighting the benefits of shared ownership, democratic decision-making, and profit-sharing. A few commenters suggest hybrid models, combining aspects of co-ops with traditional structures to balance the need for both stability and shared benefits. Some also point out the importance of clearly defining roles and responsibilities within a co-op to avoid common pitfalls. Finally, several comments emphasize the crucial role of shared values and a strong commitment to the co-op model for long-term success.
Artemis is a web reader designed for a calmer online reading experience. It transforms cluttered web pages into clean, focused text, stripping away ads, sidebars, and other distractions. The tool offers customizable fonts, spacing, and color themes, prioritizing readability and a distraction-free environment. It aims to reclaim the simple pleasure of reading online by presenting content in a clean, book-like format directly in your browser.
Hacker News users generally praised Artemis, calling it "clean," "nice," and "pleasant." Several appreciated its minimalist design and focus on readability. Some suggested improvements, including options for custom fonts, adjustable line height, and a dark mode. One commenter noted its similarity to existing reader-mode browser extensions, while others highlighted its benefit as a standalone tool for a distraction-free reading experience. The discussion also touched on technical aspects, with users inquiring about the framework used (SolidJS) and suggesting potential features like Pocket integration and an API for self-hosting. A few users expressed skepticism about the project's longevity and the practicality of a dedicated reader app.
Summary of Comments ( 60 )
https://news.ycombinator.com/item?id=42828833
HN users generally praised Bagels for its simplicity and use of a text-based interface. Several commenters appreciated the developer's focus on a straightforward, easy-to-use tool that avoids unnecessary complexity. Some suggested potential improvements, like adding support for budgeting or different currencies. One user highlighted the benefit of plain text data storage for easy backups and portability. The project's reliance on Python and the
textualTUI framework also drew positive remarks. A few questioned the long-term viability of the project and suggested exploring alternatives like Ledger.The Hacker News post titled "Show HN: Bagels – TUI expense tracker" linking to the GitHub repository for Bagels, a terminal-based expense tracker, has generated a modest number of comments, primarily focused on its functionality and potential alternatives.
Several commenters express appreciation for the simplicity and clean interface of Bagels. One user highlights the appeal of text-based interfaces for their speed and efficiency, contrasting them favorably with browser-based or graphical applications. Another commenter echoes this sentiment, praising the speed and ease of use, particularly for those comfortable with command-line tools.
A significant portion of the discussion revolves around comparisons with other expense tracking tools. Ledger, a command-line accounting tool, is mentioned multiple times, with users discussing its power and flexibility. One commenter suggests integrating Bagels with Ledger, potentially leveraging Bagels for quick data entry and Ledger for more comprehensive reporting and analysis. Another user mentions Beancount, another text-based accounting system, as a potential alternative.
The conversation also touches on the desired features and potential improvements for Bagels. One commenter requests the ability to categorize expenses, a common feature in many expense trackers. Another user suggests the possibility of using a more structured data format, potentially enabling easier data import and export. The discussion also includes brief mentions of other tools like fzf (a command-line fuzzy finder) and the potential benefits of cloud synchronization for data backup and accessibility across devices.
While generally positive, some comments express reservations or suggest alternative approaches. One user questions the long-term viability of using a TUI for expense tracking, suggesting that graphical interfaces might be more suitable for complex financial management. Another commenter points out the existing abundance of expense tracking applications, implicitly questioning the need for another tool.
Overall, the comments reflect a mix of interest and skepticism towards Bagels. While many appreciate its minimalist approach and speed, others question its long-term practicality and compare it to existing solutions. The discussion highlights the ongoing debate between the simplicity of text-based interfaces and the richness of graphical applications, particularly in the context of financial management.