wasmedge-db-examples VS SSVM

LlamaEdge is not just a lightweight and portable runtime for chatbots. It is an app dev platform for portable LLM apps! RAG chatbots and AI agents can be developed on Mac or Windows, compiled to Wasm, and then deployed across Nvidia / AMD / ARM devices, fully taking advantage of on-device GPUs, NPUs etc.

Hence, besides the LLM runtime, those LLM apps also need to manage embeddings in vector db. This example shows how to access the Qdrant vector db from your portable Wasm apps!

https://github.com/WasmEdge/wasmedge-db-examples/tree/main/q...

The above sample program has been added to the WasmEdge database usage demonstration. You can find the full source code in the GitHub repository at https://github.com/WasmEdge/wasmedge-db-examples/tree/main/greptimedb.

https://github.com/second-state/microservice-rust-mysql

https://github.com/WasmEdge/wasmedge-db-examples

https://github.com/WasmEdge/wasmedge_hyper_demo

WasmEdge is already one of the smallest and most efficient Wasm runtimes out there. It embeds into libsql (SQLite on the server!) to execute user definited functions to perform complex tasks like HTTPS web services & AI inference from SQL statements! https://wasmedge.org/docs/embed/use-case/libsql/

The WasmEdge C++ and Rust SDKs allow host applications to embed Wasm functions asynchronously. It is critically important in many applications where the embedded Wasm function is simply not allowed to block the execution of the host applications. https://github.com/second-state/wasmedge-rustsdk-examples/bl...

Asynchronous host SDKs are complex and a lot of work still remains. We are continuously improving it with our end user and partner communities.

Preview: https://github.com/L-jasmine/WasmEdge/tree/feat/async

What's coming next?

* Support plugins in our Docker and k8s integrations

2.WasmEdge support MySQL-based databases, caches, and DOs. https://github.com/WasmEdge/wasmedge-db-examples

WasmEdge GitHub address: https://github.com/WasmEdge/WasmEdge.

I see that they recently changed the intro of WasmEdge on Github [1] to " WasmEdge is the easiest and fastest way to run LLMs on your own devices. "

Since it's a wasm runtime capable of many things I find bizarre that they now start describing it with a ultra-specific use case

- [1] https://github.com/WasmEdge/WasmEdge

Mmm…

The wasm-nn that this relies on (https://github.com/WebAssembly/wasi-nn) is a proposal that relies of arbitrary plugin backends sending arbitrarily chunks to some vendor implementation. The api is literally like set input, compute, set output.

…and that is totally non portable.

The reason this works, is because it’s relying on the abstraction already implemented in llama.cpp that allows it to take a gguf model and map it to multiple hardware targets,which you can see has been lifted here: https://github.com/WasmEdge/WasmEdge/tree/master/plugins/was...

So..

> Developers can refer to this project to write their machine learning application in a high-level language using the bindings, compile it to WebAssembly, and run it with a WebAssembly runtime that supports the wasi-nn proposal, such as WasmEdge.

Is total rubbish; no, you can’t.

This isn’t portable.

It’s not sandboxed.

If you have a wasm binary you might be able to run it if the version of the runtime you’re using happens to implement the specific ggml backend you need, which it probably doesn’t… because there’s literally no requirement for it to do so.

There’s a lot of “so portable” talk in this article which really seems misplaced.

WasmEdge isn't there yet: https://github.com/WasmEdge/WasmEdge/issues/1122#issuecommen...

Example 1: Analyze the content and risks of each commit in the PR. Then make a summary. https://github.com/WasmEdge/WasmEdge/pull/2394#issuecomment-...

There has also been a few "cloud-native" runtimes based on WASM, like WasmEdge but there's a few others (can't remember their names!)...