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Quill: Open Source Writing Assistant with Prompt Control

Quill is a streamlined open-source background writing assistant designed for users who want more control over prompt engineering. Inspired by Writing Tools, Quill removes certain features like screen capture and a separate chat window to focus on selected text processing, making it compatible with local language models. It allows users to configure parameters and inference settings, and supports any OpenAI-compatible API, such as Ollama and llama.cpp. The user interface is kept simple and readable, though some features from Writing Tools are omitted, which might be missed by some users. Currently, Quill is available only for Windows, and feedback is encouraged to improve its functionality. This matters as it provides writers with a customizable tool that enhances their writing process by integrating local language models and offering greater control over how prompts are managed.

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Posted on

Jan 8, 2026

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TheTweakedGeek

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Commentary, Tools

Topics: open source, local LLMs, customization

Project Showcase Day: Share Your Creations

Project Showcase Day is a weekly event that invites community members to present and discuss their personal projects, regardless of size or complexity. Participants are encouraged to share their creations, explain the technologies and concepts used, discuss challenges faced, and seek feedback or suggestions. This initiative fosters a supportive environment where individuals can celebrate their work, learn from each other, and gain insights to improve their projects, whether they are in progress or completed. Such community engagement is crucial for personal growth and innovation in technology and creative fields.

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Posted on

Dec 28, 2025

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TweakedGeekTech

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Commentary, Learning

Topics: Innovation, collaboration, technology

Imflow: Minimal Image Annotation Tool Launch

Imflow is a newly launched minimal web tool designed to streamline the image annotation process, which can often be tedious and slow. It allows users to create projects, batch upload images, and manually draw bounding boxes and polygons. The tool features a one-shot auto-annotation capability that uses OWL-ViT-Large to suggest bounding boxes across batches based on a single reference image per class. Users can review and filter these proposals by confidence, with options to export annotations in various formats like YOLO, COCO, and Pascal VOC XML. While still in its early stages with some limitations, such as no instance segmentation or video support, Imflow is currently free to use and invites feedback to improve its functionality. This matters because efficient image annotation is crucial for training accurate machine learning models, and tools like Imflow can significantly reduce the time and effort required.

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Topics: machine learning, computer vision, batch processing

PixelBank: ML Coding Practice Platform

PixelBank is a new hands-on coding practice platform tailored for Machine Learning and AI, addressing the gap left by platforms like LeetCode which focus on data structures and algorithms but not on ML-specific coding skills. It allows users to practice writing PyTorch models, perform NumPy operations, and work on computer vision algorithms with instant feedback. The platform offers a variety of features including daily challenges, beautifully rendered math equations, hints, solutions, and progress tracking, with a free-to-use model and optional premium features for additional problems. PixelBank aims to help users build consistency and proficiency in ML coding through an organized, interactive learning experience. Why this matters: PixelBank provides a much-needed resource for aspiring ML engineers to practice and refine their skills in a practical, feedback-driven environment, bridging the gap between theoretical knowledge and real-world application.

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Topics: machine learning, AI, Deep Learning

Quint: Interactive Buttons for Chatbots

Quint is an innovative open-source library designed to enhance chatbot interactions by moving beyond the traditional command-line interface (CLI) approach. Developed as a React library, Quint allows developers to create structured and deterministic interactions on top of large language models (LLMs). By enabling explicit choices through interactive buttons, users can reveal information or send structured input back to the model, with full control over the output display. This separation of model input, user interface, and output rendering helps make interactions like multiple-choice questions, explanations, and role-play scenarios more predictable and less reliant on workaround solutions. One of Quint's key features is its flexibility in terms of presentation, as it only manages the state and behavior of interactions, leaving the design and styling to the developers. This means that developers can fully customize the buttons and user interface elements to fit their specific needs and aesthetic preferences. Additionally, Quint is independent of any specific AI provider, as it operates through callbacks, allowing for integration with various models such as OpenAI, Gemini, Claude, or even mock functions. This versatility ensures that Quint can be used effectively regardless of the underlying AI technology. Currently in its early stages (version 0.1.0), Quint offers a stable core abstraction that promises to evolve into a more comprehensive solution for interactive chatbot interfaces. The creator is seeking feedback to refine and improve the library, aiming to eventually render entire UI elements through LLMs, simplifying interactions for the average end user. This development matters because it represents a significant step forward in making chatbot interactions more intuitive and accessible, potentially transforming how users engage with AI-driven systems.