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quinta-feira, 23 de abril de 2026
Show HN: Cartoon Studio – an open-source desktop app for making 2D cartoon shows https://ift.tt/CLMDW7n
Show HN: Cartoon Studio – an open-source desktop app for making 2D cartoon shows Hi HN — I built Cartoon Studio, an open-source desktop app for making simple 2D cartoon scenes and shows. The basic flow is: place SVG characters on a scene, write dialogue, pick voices, and render to MP4. It handles word timestamps, mouth cues, and lip-sync automatically. This started as me playing around with Jellypod's Speech SDK and HeyGen's HyperFrames. I wanted a small tool that could go from script to video without a big animation pipeline and next thing I knew I was trying to create my own South Park style show and here we are. :D A few details: - desktop app built with Electron - supports multiple TTS providers through Jellypod's Speech SDK - renders via HyperFrames - lets you upload or generate characters and backdrop scenes - includes default characters/scenes so you can try it quickly - open source It runs from source today. AI features use bring-your-own API keys, but the app itself is fully inspectable and local-first in the sense that there’s no hosted backend or telemetry. Here are some fun examples of the the types of videos you can create: https://ift.tt/sOU8Map https://ift.tt/tpIfRSA And the repo: https://ift.tt/tHF81J9 Happy to answer questions and appreciate any feedback! https://ift.tt/tHF81J9 April 22, 2026 at 11:56PM
Show HN: Real-Real-Time Chat https://ift.tt/wG1gfrh
Show HN: Real-Real-Time Chat Hi HN! Few months ago I've shared a new kind of markdown editor that we (a team of three from the Czech Republic) have been working on (HN post: https://ift.tt/rtFkxZ4 ). What resonated with folks the most was Kraa's unique ‘real-real-time’ chat feature. We have now acted on this feedback, improved the chat features, and made what we call Kraa Trees. Trees allow anyone to create a light-weight community / chat channels. It would be a stretch to call it an alternative to Discord, yet, but we hope that the frictionless nature of Trees will make them useful for small groups that want something simpler, more immediate, and less cluttered. With the live-typing being one of the key differentiating features. You can create your own community/rooms by selecting "Tree of leaves" in the New leaf button dropdown. You don't need an account to try Kraa nor Kraa Trees. We would love to know what you think! https://ift.tt/TJkuqoj April 23, 2026 at 12:50AM
quarta-feira, 22 de abril de 2026
Show HN: Gemini Plugin for Claude Code https://ift.tt/bEOALK7
Show HN: Gemini Plugin for Claude Code I built a plugin that lets Claude Code delegate work to Gemini CLI. I started this after finding myself reaching for Gemini more often on long context repo work. I have been especially liking Gemini’s codebaseinvestigator for long context. This is inspired by openai/codex-plugin-cc. Code Review, adversarial review. Under the hood its Gemini CLI over ACP Would love feedback from people using Claude Code, Gemini CLI, or ACP. I am especially curious whether this feels useful outside my own workflow. Its a great combo with Opus 4.7 + Gemini 3.1 workflows https://ift.tt/my1DKkq April 22, 2026 at 01:41AM
Show HN: MemFactory: Unified Inference and Training Framework for Agent Memory https://ift.tt/wh4qfHG
Show HN: MemFactory: Unified Inference and Training Framework for Agent Memory Memory-augmented Large Language Models (LLMs) are essential for developing capable, long-term AI agents. Recently, applying Reinforcement Learning (RL) to optimize memory operations, such as extraction, updating, and retrieval, has emerged as a highly promising research direction. However, existing implementations remain highly fragmented and task-specific, lacking a unified infrastructure to streamline the integration, training, and evaluation of these complex pipelines. To address this gap, we present MemFactory, the first unified, highly modular training and inference framework specifically designed for memory-augmented agents. Inspired by the success of unified fine-tuning frameworks like LLaMA-Factory, MemFactory abstracts the memory lifecycle into atomic, plug-and-play components, enabling researchers to seamlessly construct custom memory agents via a "Lego-like" architecture. Furthermore, the framework natively integrates Group Relative Policy Optimization (GRPO) to fine-tune internal memory management policies driven by multi-dimensional environmental rewards. MemFactory provides out-of-the-box support for recent cutting-edge paradigms, including Memory-R1, RMM, and MemAgent. We empirically validate MemFactory on the open-source MemAgent architecture using its publicly available training and evaluation data. Across the evaluation sets, MemFactory improves performance over the corresponding base models on average, with relative gains of up to 14.8%. By providing a standardized, extensible, and easy-to-use infrastructure, MemFactory significantly lowers the barrier to entry, paving the way for future innovations in memory-driven AI agents. https://ift.tt/hDjMl8f April 21, 2026 at 11:26PM
terça-feira, 21 de abril de 2026
Show HN: A fake small claims court for petty complaints https://ift.tt/wtRk5NY
Show HN: A fake small claims court for petty complaints https://ift.tt/efwMzxP April 21, 2026 at 01:04AM
Show HN: Mediator.ai – Using Nash bargaining and LLMs to systematize fairness https://ift.tt/Jwot548
Show HN: Mediator.ai – Using Nash bargaining and LLMs to systematize fairness Eight years ago, my then-fiancée and I decided to get a prenup, so we hired a local mediator. The meetings were useful, but I felt there was no systematic process to produce a final agreement. So I started to think about this problem, and after a bit of research, I discovered the Nash bargaining solution. Yet if John Nash had solved negotiation in the 1950s, why did it seem like nobody was using it today? The issue was that Nash's solution required that each party to the negotiation provide a "utility function", which could take a set of deal terms and produce a utility number. But even experts have trouble producing such functions for non-trivial negotiations. A few years passed and LLMs appeared, and about a year ago I realized that while LLMs aren’t good at directly producing utility estimates, they are good at doing comparisons, and this can be used to estimate utilities of draft agreements. This is the basis for Mediator.ai, which I soft-launched over the weekend. Be interviewed by an LLM to capture your preferences and then invite the other party or parties to do the same. These preferences are then used as the fitness function for a genetic algorithm to find an agreement all parties are likely to agree to. An article with more technical detail: https://ift.tt/uDECh0M https://mediator.ai/ April 20, 2026 at 12:07PM
Show HN: Palmier – bridge your AI agents and your phone https://ift.tt/BreA43l
Show HN: Palmier – bridge your AI agents and your phone Hi HN — I built Palmier. Palmier bridges your AI agents and your phone. It does two things: 1. It lets you use your phone to directly control AI agents running on your computer, from anywhere. 2. It gives your AI agents access to your phone, wherever you are — including things like push notifications, SMS, calendar, contacts, sending email, creating calendar events, location, and more. A few details: * Supports 15+ agent CLIs * Supports Linux, Windows, and macOS * What runs on your computer and your phone is fully open source * Works out of the box — no need to set up GCP or API keys just to let agents use phone capabilities * Your phone can act as an agent remote: start tasks, check progress, review results, and respond to requests while away from your desk * Your phone can also act as an agent tool: agents can reach into phone capabilities directly when needed * Optional MCP server: if you want, Palmier exposes an MCP endpoint so your agent can access phone capabilities as native MCP tools. This is optional — you can also use Palmier directly from the phone app/PWA, with those capabilities already built in * Still in alpha stage, with bugs. Opinions and bug reports very welcome The basic idea is that AI agents become much more useful if they can both: * interact with the device you actually carry around all day * be controlled when you are away from your computer Palmier is my attempt at that bridge. It already works with agent CLIs like Claude Code, Gemini CLI, Codex CLI, Cursor CLI, OpenClaw, and others. You can run tasks on demand, on a schedule, or in response to events. Would especially love feedback on: * whether this feels genuinely useful * which phone capabilities are most valuable * which agent CLIs I should support next * what feels broken, awkward, or confusing Site: https://www.palmier.me Github: * https://ift.tt/KD5g0XR * https://ift.tt/zsZqDLM Happy to answer questions. https://ift.tt/KD5g0XR April 20, 2026 at 11:31PM
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