Alternatives
Products that do what Content Studio does
Generate social posts with a local LLM. $0 API cost
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I spent a few hours last weekend testing whether AI can replace code by executing directly. Built a contact manager where every HTTP request goes to an LLM with three tools: database (SQLite), webResponse (HTML/JSON/JS), and updateMemory (feedback). No routes, no controllers, no business logic. The AI designs schemas on first request, generates UIs from paths alone, and evolves based on natural language feedback. It works—forms submit, data persists, APIs return JSON—but it's catastrophically slow (30-60s per request), absurdly expensive ($0.05/request), and has zero UI…
Nov 2025 · github.com
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This lets you talk to local LLMs in Apple Notes. I saw Obsidian Ollama (https://github.com/hinterdupfinger/obsidian-ollama) and thought it was handy, but I'm too lazy to migrate away from the Apple ecosystem, so I quickly hacked this together. I tend to use Notes as a scratchpad for prompts, so it's nice to do some quick inference without leaving the app. Notes doesn't really support plugins so I'm using the macOS accessibility API for reading selections and then stream responses using the clipboard (not ideal but it works).
2024 · smallest.app
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Hi everyone, we’re a small team, supported by Mozilla, who are working on re-imagining a UI for training, tuning and testing local LLMs. Everything is open source. If you’ve been training your own LLMs or have always wanted to, we’d love for you to play with the tool and give feedback on what the future development experience for LLM engineering could look like.
2025 · github.com
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- 9AP
Hey HN! We've run our privacy-focused open-source inference company for a while now, and we're launching a flat monthly subscription similar to Anthropic's. It should work with Cline, Roo, KiloCode, Aider, etc — any OpenAI-compatible API client should do. The rate limits at every tier are higher than the Claude rate limits, so even if you prefer using Claude it can be a helpful backup for when you're rate limited, for a pretty low price. Let me know if you have any feedback!
2025 · synthetic.new
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My puny version of ChatGPT. This was based on the excellent LLM lecture series by Andrej Karpathy: https://www.youtube.com/watch?v=kCc8FmEb1nY The main points of differentiation are that my version is token-based (tiktoken) with code to load up multiple text files as a trining set. Plus, it has a minimal server which is a drop-in replacement for the OpenAI REST API. So you can train the default tiny 15M parameter model, and use that in your projects instead of ChatGPT. I trained it on 20Mb of Project Gutenberg encyclopaedias, then fine-tuned it on 120 dad jokes, to get a Q: A:…
2023 · github.com
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Hi HN, I was once given the advice: Don't waste expensive frontier model credits (GPT/Claude/etc.) on bulk work. Send the boring, repetitive, high-volume jobs to a smaller model, and save the expensive prompts for when you actually need frontier-level reasoning. I complained and told my manager that I shouldnt have to think about using certain models for certain coding tasks, and that one model should handle everything. Well, here we are anyway. If anyone needs a place to absolutely abuse an LLM with high-volume tasks, come beat ours up at https://yolo-auto.com. Here are…
Jul 2026 · yolo-auto.com
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I built an open source web app that generates cover letters using local AI models (Ollama, LM Studio, vLLM, etc.) so your resume and job application data never leaves your machine. No placeholders. No typing. Letters are ready to copy and paste. The workflow is: 1. Upload your resume (PDF) - it gets parsed and cached in your browser. 2. Paste the job description 3. Get a personalized cover letter in ~5 seconds It connects to any OpenAI-compatible local LLM endpoint. I use it with Ollama + llama3.2, but it works with any local model server. Key features: - 100% local and private depending on…
Dec 2025 · github.com
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Social media these days feels like swimming through a feed of AI generated slop rather than actual human thoughts. Sometimes I wonder what the prompts behind the posts are. I bet there's more creativity going into the prompts than the final content that actually gets shared. What if people just shared their prompts, and the completion was rendered on-demand, client side? Disclaimer: This is a vibe coded proof-of-concept, not a functional service, built in the no-code builder Mocha. It's seeded with a few fake posts. You can create your own posts but they're just saved locally on your own…
2025 · 2fjxieoiipm32.mocha.app
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I'm a solo dev in Taiwan. I built 4 AI agents that handle content, sales leads, security scanning, and ops for my tech agency — all on Gemini 2.5 Flash free tier (1,500 req/day). I use ~105. Monthly LLM cost: $0. Architecture: 4 agents on OpenClaw (open source), running on WSL2 at home with 25 systemd timers. What they do every day: - Generate 8 social posts across platforms (quality-gated: generate → self-review → rewrite if score < 7/10) - Engage with community posts and auto-reply to comments (context-aware, max 2 rounds) - Research via RSS + HN API + Jina Reader → feed…
Mar 2026
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Hi HN! Here's a local-only stack I built over the weekend - hope it can be useful for you! I have been building a lot of AI apps - https://github.com/a16z-infra/ai-town https://github.com/a16z-infra/companion-app ... And there were definitely times I spent way too much $$ before deploying the app to production. So I was looking for a "local only" stack and found a few tools that worked well together. I used the following set of tools but may add more options later: - Inference: Ollama - VectorDB: Supabase pg-vector - LLM orchestration: langchain -…
2023 · github.com
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2024 · github.com
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Hi HN, I'm excited to share Bodhi App, a tool designed to simplify running open-source Large Language Models (LLMs) locally on your laptops. While we currently support M2 Macs, we plan to support other platforms as our community grows. # Problem To use LLMs, you typically need to purchase a subscription from providers like OpenAI or Anthropic, or use OpenAI API credits with compatible Chat UIs. These options can not only burden you financially, but also raise data security and privacy concerns. Many laptops are capable of running powerful open-source LLMs, but for non-tech users, setting…
2024 · github.com
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2023 · lmstudio.ai
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I’ve always found it funny how simple feedback widgets end up as $20–$30/month products. The tech is dead simple, infra is cheap, and most of us here could rebuild one in a weekend. So as a “principle experiment” I built my own today as a side project and priced it at 1 dollar. Just because if something is cheap to run and easy to replicate, it should be priced accordingly, and it’s also fun marketing. 1$ feedback tool. Shipped today, got the first users/moneys today, writing this post today. Side Sunday project, then back to the main product tomorrow.
Dec 2025 · onedollarfeedback.com
- 23IB
Building integrations for TikTok, X, Facebook, Instagram, YouTube, and LinkedIn got frustrating with how different every platform is with auth setup, rate limits, and media requirements. So we built Post for Me: one REST API that handles scheduling and publishing posts for TikTok, Facebook, Instagram, X, YouTube, LinkedIn, Pinterest, Bluesky, and Threads. It's built for developers. You bring your own app credentials from the social platform, so you're in control of your data. There's no limitations on account connections, and pricing is based on usage (not some arbitrary limitations). We…
2025 · postforme.dev
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