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Products that do what An agent that tunes its own cache does

The weekend of last week I built chat.betterdb.com as a RAG over Valkey/Redis/Dragonfly docs. The goal was to eat our own dogfood and test publicly our caching libraries. It also saved me from having to come up with various demo/test scenarios, as I could extend the building in public to the demo. There is a tool-result cache sitting between the SDK and tools. Each call is normalized and then checked before executing. If it hits we return from the cache, and if not, we check the semantic cache, which embeds the prompt and checks with KNN via valkey-search. If the cosine…

  1. 1
    Kept104

    Your AI chats, saved as Markdown locally with no cloud

    May 2026

  2. 2AT

    While building a chat application I couldn't find find a free and opensource tool to store user sessions. This led to redcache-ai. The tool helps with semantic search, Retrieval Augmented Generation(RAG) and storage. This is an early version undergoing rapid iteration. Happy to answer questions and hear feedback.

    2024 · github.com

  3. 3BM

    Today we released an open, Valkey-native context layer for AI agents as part of our packages at BetterDB (agent memory, semantic + multi-tier caching, typed retrieval) that run on a Valkey instance no matter where it is - no vendor lock-in. We even started provisioning Valkey instances starting today. Packages are shipped on npm and PyPi. Why we made it: BetterDB originally started as a monitoring and observability platform for Valkey, Redis and any RESP compatible db. This is still the core of the product, but in the process of building this, we kept seeing that one of the fastest-growing…

    Jun 2026 · github.com

  4. 4CH

    Hi, I'm fiiv, and I'm the creator of Cache Horse. I built it because I wanted an easy plug-n-play solution to caching and simplifying HTTP requests - in particular, on frontend. First, I was fetching data like daily weather, historic currency exchange numbers, air quality readings - and many of those APIs have quota limits. And second, since I was already caching them, I thought it would be useful to batch them together - so I built that feature in. I would love to hear your feedback and thoughts on the project. Thanks!

    2025 · cache.horse

  5. 5SL

    So a while ago I was thinking it would be neat to build a site that had the most absolute utility. The idea I came up with was a site to store those little protips that are super useful, if you know them ahead of time. I hired a guy to work on it with me, and ClueDB was born: http://cluedb.com/ Please give it a whirl (it uses Twitter auth as login but doesn't tweet anything) and tell me what you think! (Various trivia: My first try at a project coded by someone else and "product managed" by me. Runs on Flask + MongoDB. Also, this is totally unrelated to my startup.)

    2011

  6. 6SI

    Have a look at my semantic caching project! It's built to easily integrate in existing LLM workflows, you can use it as a proxy where the cache forwards missed requests without modification to a specified upstream, automatically updating it's cache with the response. You can also use it as a cache-aside cache with a provided python library. It works by computing embedding vectors of input queries, and matches them to seen query + response pairs using a vector store. Everything is in-memory, so it should be blazing fast :)

    2025 · github.com

  7. 7LP

    I was not getting good cache utilization when including dynamic context in agent threads. After a lot of experimentation, I found a good pattern that minimizes how often long lived conversation history gets modified while still supporting dynamic context. It has flexible hooks for doing things like truncating or summarizing tool outputs when transitioning messages to the long term history. And I'm seeing >>90% of tokens hitting the cache for my agents despite including a lot of dynamic user context. There are a wide range of agent prompting strategies so I'd love to hear where this library…

    Jun 2026 · github.com

  8. 8GR

    Hey folks, As much as we love GPT-4, it's expensive and can be slow at times. That's why we built GPTCache - a semantic cache for autoregressive LMs - atop the vector database Milvus and SQLite. GPTCache provides several benefits: 1) reduced expenses due to minimizing the number of requests and tokens sent to the LLM service 2) enhanced performance by fetching cached query results directly 3) improved scalability and availability by avoiding rate limits, and 4) a flexible development environment that allows developers to verify their application's features without connecting to LLM APIs or…

    2023 · github.com

  9. 9BO

    Hey HN, I'm Kristiyan, former Engineering Manager for Redis' Visual Developer Tools (including Redis Insight). I built BetterDB because Valkey is growing fast but lacks proper observability tooling. BetterDB is a monitoring platform for Valkey (and Redis) that focuses on what existing tools miss: Historical persistence – Slowlog entries disappear when the buffer fills. BetterDB persists them so you can see what queries were running at 3am, which clients were connected, and what anomalies were detected — not just current state. Pattern analysis – Stop scrolling through raw slowlog entries.…

    Jan 2026

  10. 10MW

    I always find myself frustrated by how many steps I have to take to video chat with someone online. There's always too much software to download and install, and too many accounts to remember. The high-end, high-price Cisco conferencing systems I've used are especially fragile. So I built Vidless in a weekend for myself, and I hope you find it useful too. Just create a room and share the link, and you'll be chatting in seconds. You can invite several people (I haven't really tested a max yet), and chats on Vidless are always private. Enjoy!

    2012 · vidless.com

  11. 11IB

    I posted this a few weeks ago and the server died under the traffic. Fixed that by adding an in-mem caching layer with Redis/valkey and added CloudFront caching for static content. Also upgraded the server. Also fixed the Firefox bugs, trying again. It's a research tool for US stocks. Financials for ~10k companies pulled from SEC filings. You can chart any metric across companies, filter news by ticker, ask questions in plain English and get a chart back. There's also SQL console against the whole database, which is the part I like to use together with the AI chat (generates an SQL…

    Jun 2026 · terminal.tesseractanalytics.ai

  12. 12IM

    Hey Hacker News, I'm the maker of Kopage, a free & self-hosted Website Builder. While working on new, cool features (AI, of course), it would be great to hear some HN feedback :) Thanks, Simon

    2024 · kopage.com

  13. 13IB

    Hi HN I built a fun little tool: It uses Groq’s LLaMA 3.3 + Puppeteer to analyze a website Then it roasts the design/content/UX with humor And finishes with 3–5 genuinely helpful improvement tips You can try it here: https://ai-roast-vert.vercel.app I wanted to: Practice fast idea-to-launch cycle (built in 2 days) Experiment with a viral-friendly product Monetize with a $0.55 pro version that gives a detailed roast + download Would love your feedback — on the idea, the tone, the usefulness — anything! Thanks in advance

    Sep 2025 · ai-roast-vert.vercel.app

  14. 14CA

    Just finished the first draft of my weekend project. Sadly my industry is far away from all the exciting machine learning developments happening right now, so I wrote this project as my first exploration into the world of LLMs. It's not perfect, but I'm excited to see where the project goes from here! https://github.com/clarkmcc/chitchat My main motivations were: - Easy-of-use: Many models are supported out-of-the-box so users don't have to figure out how to download, where to save, etc. - Intuitive: A clean interface - Cross platform: The project is written in Rust and…

    2023 · clarkmccauley.com

  15. 15UI

    Hey everyone! I am excited to share updates on four of my & my teams' open-source projects that take large-scale search systems to the next level: USearch, UForm, UCall, and StringZilla. These projects are designed to work seamlessly together, end-to-end—covering everything from indexing and AI to storage and networking. And yeah, they're optimized for x86 AVX2/512 and Arm NEON/SVE hardware. USearch [1]: Think of it as Meta FAISS on steroids. It's now quicker, supports clustering of any granularity, and offers multi-index lookups. Plus, it's got more native bindings than probably…

    2023 · usearch-images.com

  16. 16IM

    I spent the past few weeks making an open source cloud code editing environment with an AI copilot and multiplayer collaboration! It's fully self-hostable in 5-10 minutes. There's a lot of minor improvements to be made, and some are already listed in the Github issues. Let me know what you think and feel free to try it out.

    2024 · github.com

  17. 17OS
  18. 18IM

    Store memories, auto-extract entities and relationships, search semantically. MCP server + REST API + SDKs. Self-hostable, cloud option, MIT license.

    May 2026 · agentrecall.cloud

  19. 19CS

    Tired of copy-pasting the same question across ChatGPT, Claude, Gemini, and Grok to find the best answer? I built ChatHawk to solve this exact problem: Ask once and get responses from all top AI models simultaneously, plus an AI-generated combined answer that pulls the best insights from each. Perfect for when you need accurate answers (verified across models), strategic decisions, or multiple AI perspectives. Stop the tedious switching between platforms – get comprehensive AI insights in one place. What questions would you want to run through all models at once?

    Oct 2025 · chathawk.co

  20. 20CS

    If you have developer documentation and want to boost your community with AI this is for you! Just pull in the base url of the site add some customization and get a sharable link for your chat, link it anywhere you want. I saw this trend in some places like gcp with Gemini, or Langchain or Supabase ask ai, but they're all custom-implemented solutions, not everyone wants to advocate developer resources to create the rag, deploy it and maintain it, you just want devs to build with your stuff, the more they can do the better, the quicker the better, and if they get a smooth experience while…

    2024 · explainit.mzslabs.com

  21. 21AN

    Hi HN! My name is Aymen, and I'm here with Kenichi. Some years ago, I launched a side project. A newsletter called DevOpsLinks, then a 2nd newsletter (Shipped), then a third one (Kaptain). These 3 newsletters are now part of a bigger project that I called FAUN (https://faun.dev). We have newsletters, a Slack team chat, and a job board, but I had a feeling that something is missing... it's a podcast, right :) Last year, I discussed the idea of creating a podcast with a member of FAUN (who is Kenichi btw), but we were not really ready. That's why it took us some months to start…

    2020

  22. 22OS

    I built an open-source research agent. You ask a question, it searches the web via Tavily, synthesizes an answer with an LLM, and shows the sources it used. Answers stream in real-time. The interesting part is the backend. It's a single JS file (~100 lines) that handles web search, LLM streaming, and per-user conversation history. No vector database, no Redis, no separate storage service. It runs inside a cell — an isolated environment with a built-in database, search index, and filesystem. The cell handles persistence and streaming natively, so the agent code only has to deal with the…

    Apr 2026 · github.com

  23. 23OY

    Hey HN, I pay for ChatGPT, Claude, Cursor, and use Gemini through work. Four vendors, four separate conversation histories, four profiles of how I think. None of them talk to each other. Switch providers and you start over. So I built a system where the memory is mine. I run a knowledge graph in Postgres (Supabase, free tier) with pgvector for semantic search. A small MCP server reads and writes to it. That server sits behind an MCP Gateway on a $6/month VPS, along with Brave Search and a GitHub server. TypingMind connects to the gateway as a BYOK client -- any model, any device, same…

    Mar 2026 · github.com

  24. 24AP

    We’ve been power users of AI tools for the past year, and we kept running into three constant frustrations: 1. Too many subscriptions – Paying separately for OpenAI, Anthropic, Perplexity, and others quickly adds up. 2. Losing memory & context – Switching between models or platforms means you start over each time. 3. Privacy concerns – With most closed-source models, your data may be stored or used for training. That’s not acceptable for sensitive or professional use cases. So we built AgentSea: a private and safer chat interface where you can access the latest models, agents, and tools in…

    2025 · agentsea.com

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