Go, Python, Rust, and production AI applications

• gonb

  5 421 9.3 Go

  GoNB, a Go Notebook Kernel for Jupyter

I've had these strong feelings and the OP describes it really well. Despite being a polyglot programmer, I really struggle with Python, both in expression and performance (unless it's just config for GPUs).

Some of this frustration was recently an "Unpopular Opinion" on the Go Time Podcast regarding Python being great for "data exploration" but not for "data engineering": https://changelog.com/gotime/304#t=3196

I've been yearning for better interactive tooling and ML-related libraries bridge this gap and started using some even in just the last week:

* GoNB (Golang-support for Jupyter notebooks, also from a Googler) https://github.com/janpfeifer/gonb

* That uses Go-Plotly for graphs/UI: https://github.com/MetalBlueberry/go-plotly

* GoMLX (GoNB author is also on that project, many thanks Jan!) https://github.com/gomlx/gomlx

* Hidden at the end of OP is LangChainGo for LLMs, which I haven't used yet: https://github.com/tmc/langchaingo

Pick those up and let's make the Go community stronger together!

• llm_client

  1 18 6.6 Rust

  Rust library for integrating local LLMs (with llama.cpp) and external LLM APIs.

I switched from python to rust for my AI stuff. Honestly, I don't care about the things people say rust is used for. I like it because the package manager, testing, and typings being built into the ecosystem by default makes it so easy to build. VS Python where it all can be done, but you need to then maintain all of those separate tools. The overhead of writing Rust is less than the overhead of dealing with the Python ecosystem. And then you have all the benefits of Rust everyone mentions more often... one other thing no one mentions is the feedback loop between a strongly typed language and copilots ability to more accurately generate code.

That being said, there is a real shortage of Rust software for Rust only projects. I ended up writing a wrapper for Llama.cpp and open ai API [0] because I needed it and couldn't find anything out there. Eventually, I do intend to implement Hugging Face's Candle library [1] (A rust version of Torch). There is something appealing about doing everything in a single lang especially as the monopoly of CUDA inevitably gets chipped away.

[0] https://github.com/ShelbyJenkins/llm_client

• InfluxDB

  www.influxdata.com sponsored

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• nimCSO

  1 19 9.6 Nim

  nim Composition Space Optimization is a high-performance tool leveraging metaprogramming to implement several methods for selecting components (data dimensions) in compositional datasets, as to optimize the data availability and density for applications such as machine learning.

Nim has also a powerful deep learning library called Arraymancer. It's selling point is that you don't have to rewrite your code from research to production. It's used in various machine learning projects, but one recent one that caught my eye was https://github.com/amkrajewski/nimCSO "Composition Space Optimization"

https://github.com/mratsim/Arraymancer

• Arraymancer

  21 1,304 8.2 Nim

  A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends

Nim has also a powerful deep learning library called Arraymancer. It's selling point is that you don't have to rewrite your code from research to production. It's used in various machine learning projects, but one recent one that caught my eye was https://github.com/amkrajewski/nimCSO "Composition Space Optimization"

https://github.com/mratsim/Arraymancer

Suggest a related project