simba-k

6 ms·

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by simba-k 1y ago
Yes, I think its a good comparison
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by simba-k 1y ago
Currently would have to be done on the SQLAlchemy side, but someone asked to contribute django directly. Let me see if they are still planning to do that and create/link an issue if you want to keep up with it. You could also build an
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by simba-k 1y ago
Yeah to restricted read, still a lot of API work to do here and we're a bit blocked by MCP itself changing its auth spec (was just republished yesterday). If you use the lower-level enrichMCP API (without SQLAlchemy) you can fully cont
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by simba-k 1y ago
Yeah, think of it as a data analyst. If I give you a Postgres account with all of our tables in it, you wouldn't even know when to start and would spend tons of time just running queries to figure out what you were looking at. If I exp
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by simba-k 1y ago
Yes but the agent reasoning is going to use an LLM, I sometimes run our openai_chat_agent example just to test things out. Try giving it a shot, ask it to do something then ask it to explain its tool use. Obviously, it can (and sometimes wi
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by simba-k 1y ago
So one big difference is that we aren't doing text2sql here, and the framework requires clear descriptions on all fields, entities, and relationships (it literally won't run otherwise). We also generate a few tools for the LLM spe
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by simba-k 1y ago
Not sure exactly what you mean here. Prisma is an ORM for developers working with databases in TypeScript. EnrichMCP is more like an ORM for AI agents. It’s not focused on replacing Prisma in your backend stack, but it serves a similar role
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by simba-k 1y ago
Imagine you're building a support agent for DoorDash. A user asks, "Why is my order an hour late?" Most teams today would build a RAG system that surfaces a help center article saying something like, "Here are common rea
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by simba-k 1y ago
Yep, we can essentially convert from SQLAlchemy into an MCP server. Auth/Security is interesting in MCP. As of yesterday a new spec was released with MCP servers converted to OAuth resource servers. There's still a lot more work t
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by simba-k 1y ago
Very! We had quite a few people do this at a hackathon we hosted this past weekend.
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by simba-k 1y ago
I feel like I see a new company doing this every week. I know there is Skyvern and browser-use in particular. Is there something special about this one?
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MCP on AWS Lambda with MCPEngine(featureform.com)
117 points by simba-k 1y ago|14 comments
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by simba-k 1y ago
I don't think so, I write about why I think this one warrants it though in the article. Do you disagree with any specific points?
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by simba-k 1y ago
MCP's "security nightmare" and toll poising was all is due to people downloading and `exec`ing random untrusted executables. I mention and link it in the article. Same would be true if you downloaded a random REST server, ran
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Web 3.0 Is MCP, Not Crypto(featureform.com)
9 points by simba-k 1y ago|7 comments
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What MCP Gets Wrong – and How We Solved It(featureform.com)
30 points by simba-k 1y ago|5 comments
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by simba-k 2y ago
https://www.featureform.com/post/what-mcp-gets-wrong We just wrote a ton about this, after using it. tl;dr The spec and implementation orients towards stdio. We think this is a mistake and have created our own implemen
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ML Feature Store Architectures(featureform.com)
7 points by simba-k 4y ago|0 comments
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by simba-k 4y ago
Our also has a local mode, the goal is to solve organisational problems as well such as versioning. It solves the problem of having a Google doc full of SQL snippets that people pass around, or digging for a notebook called untitled_110.ipy
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by simba-k 4y ago
Up for a call? Would love to get your Api feedback, email me at simba@featureform.com , I’ll buy you lunch :)
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by simba-k 4y ago
Yes, we essentially have three components: the serving layer, the orchestrator, and the metadata layer. All three of these work across different infrastructure by design. We already have users who use Google Cloud services like BigQuery for
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by simba-k 4y ago
Imagine you're Spotify and you have a stream of user-song-timestamp triplets per listen. You'll likely want to transform it into features such as: top genre per user in last 30 days. As a data scientist, you'll write your tra
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by simba-k 4y ago
The client libraries are all in Python. Much like Tensorflow, even though most of the heavy-lifting is done in a different language, the client feels like native Python. The internals of Featureform's deployed solution benefit from Go&
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by simba-k 4y ago
A feature is an input to a machine learning model. You can think of a model as a black-box function that takes features and outputs a prediction: prediction = model(features) For example, If you're building a recommendation model at Sp
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by simba-k 4y ago
Mozilla Public License 2.0 is standard, well-known, and OSI approved: https://opensource.org/licenses
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by simba-k 4y ago
Great question! We wrote about this in our blog post: https://www.featureform.com/post/feature-stores-explained-th... Feast is a literal feature store. it exclusively stores features, it does not manage the transformat
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by simba-k 4y ago
Hey everyone, I'm Simba Khadder, Co-Founder & CEO of Featureform. I'm super stoked to be sharing our open-source feature store with you all. At my last company, we were building models that served to <100M MAU. Most of our
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Show HN: Featureform – An open-source Feature Store for ML(github.com)
136 points by simba-k 4y ago|27 comments