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Products that do what Cache Horse: An HTTP cache/batch service does
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!
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Last night, while trying to figure out the best way to implement caching in my app, I had an idea for a dirt-simple caching system based on a dependency graph. The premise I started with is that one of the hardest things to manage in a cache is dependencies between entities. In order to cache items effectively, you inevitably have to duplicate "child" data inside of "parent" entries. Then, when a child is changed, you have to invalidate the child and its parents, and its parents' parents, and so on. To try to help this, I hacked together a simple Node.js library called Stash, which models…
2012
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2011 · adeel.github.com
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2018 · github.com
- 5EG
2018 · stackshare.io
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2015 · github.com
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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…
May 2026
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2019 · github.com
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2016 · m.signalvnoise.com
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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
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2018 · github.com
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2015 · github.com
- 14FC
2019 · github.com
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2021 · github.com
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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
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2015 · github.com
- 18AT
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
- 19UI
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
- 20IC
In my last project, I was struggling to create and monitor cron jobs. So, instead of creating hundreds of standalone scrips and executing them with cron, I decided to turn those scripts into multiple endpoints. Next, I created a single service that I could schedule HTTP requests to those endpoints and monitor its execution. No more scripts, now everything is endpoints that I can run manually at any time I turned this scheduler service into a Micro-SaaS so you don't have to build it yourself: beew.io I know you can Schedule HTTP requests with Zapier but come on... I will not pay 50 bucks for…
2021
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2022 · wundergraph.com
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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
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I made this as a pair programming exercise with o1-preview. o1 did most of the heavy lifting, through high level prompts, but eventually I needed to diverge from it to get to completion. My initial prompt was: --- I'm making a web app: It's like 4chan, but each thread starts with a gps coordinate. People can only post text and images. I want to build it with flask and sqlalchemy. I want just the backend and data model that supports these threads, anonymous users, and users that can register a permanent username. Write as much of it as you can for me. --- This produced a fully scaffolded…
2024 · mapchan.com
- 24SS
2015 · github.com
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