Alternatives
Products that do what Simple OpenAI Library with Caching does
I found a lot of my experiments / tests ended up calling the OpenAI API service with the same content over and over again, which can be time consuming - particularly for longer completions. This is a very simple thing but if you need something like this in your C# project and don't feel like building it yourself, you may find it useful. This library also doesn't have any dependencies which is kind of nice imo.
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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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Hey, OpenAI recently released "assistants" - These have RAG built into the API, which means that you can provide up to 10.000 files to the assistant without the overhead of dealing with vector databases, splitting files into chunks and more. They work surprisingly well, so I've built a free simple tool to embed them on websites. It has no dependencies and simply uses fetch to communicate to my backend which proxies openai. In the future I plan to add more widget embedding options (currently only chat is available). Let me know if you have any specific questions about either the tool or…
2024 · rispose.com
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Threw this little application together today. It uses the OpenAI API to help you figure out what you want to cook next! Please note that the OpenAI API response times are really slow - sorry about that! If someone has suggestions on how I can improve the prompt response time, please share!
2023 · mehungry.app
- 7CH
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
- 8MA
Hi, I'm working on a project that regroups all best AI (AIaaS) from different providers (GCP, AWS, Azure, DeepL, etc.) in one API (https://github.com/edenai/edenai-apis). I've got asked the question : why aren't you regrouping Open Source models (instead of proprietary APIs) into one repo? Well because it doesn't make sens to deploy and maintain large pytorch (or other framework) AI models (especially for document parsing, image and video moderation or speech recognition) in every solution that wants AI capabilities. So using APIs makes way more sens. Deployed OpenSource…
2023 · github.com
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Hi HN! I am an undergrad student trying to build interesting things with AI. Recently, I was looking for a dataset I could use for a new project. I realized that it is really frustrating to go through all the government websites (with terrible UX) just to find some usable dataset. I set out to build a GitHub for datasets, named DataHub. Right now, we have more than 1000 datasets from Montréal and New York City, with more cities coming soon (and possible government agencies). All of this is wrapped into a powerful search. It's a breeze to find a dataset to work on. I'd be interested to know…
2017
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Today you can easily adopt AI coding tools because you have git for branching and rolling back if AI writes bad code. We haven't seen this same capability for data and decided to build it ourselves. Nile is a new kind of data lake, purpose built for using with AI. It can act as your data engineer or data analyst creating new tables and rolling back bad changes in seconds. We support real versions for data, schema, and ETL. We'd love your feedback on any part of what we are building - https://getnile.ai/ What do you think?
Jan 2026
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Hello HN, new user here, so please let me know if I break some rules. Currently I've been working on training reinforcement learning agents, and OpenAI gym, while is great, runs only one agent at a time. Hence I decided to extend it. I built a wrapper around OpenAI gym, such that it now runs several environments concurrently. All while (mostly) having the same call signature as OpenAI gym. And it is published to PyPI for anyone interested. For more details, please visit: https://github.com/Chimpan-Z/agymc Feedback really appreciated! Have a good day everyone!
2020
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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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Drop in replacement for OpenAI's embedding API. Can be used with official OpenAPI libraries. Written in python3
2023 · 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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LLM observability is an absolute must-have for anyone running something in prod (or prod-like). While all the observability startups are great, you're essentially sending all your OpenAI usage history - prompts, generations, chats - to a random third party. So this script deploys a basic proxy in your Azure account, catches all incoming OpenAI requests, stores logs in your own resource group, and comes with visualizations premade (charts, timelines, chat history, cost estimation, etc). Thanks for any thoughts and feedback!
2023 · github.com
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Hi there, I've created this side project to make it easier to find interesting repositories using AI. There's still a lot of work to be done to improve it, so any suggestions for enhancements would be greatly appreciated. Thank you!
2024 · awesome-repositories.com
- 17IM
I built this library because I kept rewriting the same fetch wrapper for every project. Each time, I needed the same core features: - Make fetch throw errors to integrate smoothly with libraries like TanStack Query - Add sensible defaults to the Fetch API, like a base URL and authentication headers - Validate responses for type safety when OpenAPI isn’t an option I also wanted the library to feel exactly like using fetch — no new API to learn, and no extra friction for my teammates. While there are other great options out there, I found many were either too rigid or too bulky. Doesn’t it…
2025 · github.com
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2025 · gist.github.com
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Hey HN! My brothers and I have worked on this for the last 2 weeks. We use OpenAI's `text-embedding-ada-002` model to embed queries and a vector database to search for similar verses / blocks of verses. We'd like to see what you think and appreciate any feedback!
2023 · siliconscripture.org
- 20UI
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
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Dear HN Community, I am a long time fan and first-time contributor. I just launched a developer focused semantic search platform and wanted to share it with the community. The idea is simple: upload structured or unstructured documents, select the fields you want to index and tag as metadata, and instantly get a clean search API you can use in your own app. Here is what it currently supports: - Manage your own tenants and projects - Upload .json and .txt files (support for .pdf, .docx, .xlsx, .yml, etc. coming soon) - Expose 3 APIs: search, upload document (embeddings), and delete document -…
2025 · aisearch.vpuna.com
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Hey HN! I love the OpenAI Playground UI but I don't love the Auth0 implementation causing me to waste precious minutes entering 2FA codes... so I spent a week cloning the basic features of the OpenAI Playground UI, all in a single HTML file. You can try it on github pages[0] or run it locally in your browser. Just paste your API key and hit start to begin using it. You can also add your key to the URI fragment[1] and bookmark it to start immediately. [0] https://minwidth0px.github.io/gpt-playground [1] like https://minwidth0px.github.io/gpt-playground#API_KEY
2023 · github.com
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Library makes requests asynchronously across models, so you can spend a lot of $$ quickly if you want XD. But seriously I hope this enables folks to create and run evals (especially safety ones) a lot easier than before.
2024 · github.com
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Hey HN! I wanted to practice "vibe coding" and see how far and fast I can go by only prompting, without actual coding. I decided to make a simple CLI app that scrapes web docs into a single md file (I was annoyed that LLM keeps writing Tailwind 3 code for a Tailwind 4 project). In just a couple of hours, the CLI app was ready! Then iterated on arguments for another couple of hours. Result: https://github.com/vladstudio/web2llm Then I decided to go further and "productize" the CLI by making a web app for it. Another half-day, and the web app is ready!…
2025 · web2llm.dev
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