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Cortex Alternatives
Similar projects and alternatives to cortex
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text-generation-webui
A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
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InfluxDB
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.
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FLiPStackWeekly
FLaNK AI Weekly covering Apache NiFi, Apache Flink, Apache Kafka, Apache Spark, Apache Iceberg, Apache Ozone, Apache Pulsar, and more...
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dns.toys
A DNS server that offers useful utilities and services over the DNS protocol. Weather, world time, unit conversion etc.
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nitro
Next Generation Server Toolkit. Create web servers with everything you need and deploy them wherever you prefer.
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jan
Jan is an open source alternative to ChatGPT that runs 100% offline on your computer. Multiple engine support (llama.cpp, TensorRT-LLM)
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metal-cpp
Metal-cpp is a low-overhead C++ interface for Metal that helps developers add Metal functionality to graphics apps, games, and game engines that are written in C++.
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bionic-gpt
BionicGPT is an on-premise replacement for ChatGPT, offering the advantages of Generative AI while maintaining strict data confidentiality
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nnl
a low-latency and high-performance inference engine for large models on low-memory GPU platform.
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durdraw
Versatile ASCII and ANSI Art text editor for drawing in the Linux/Unix/macOS terminal, with animation, 256 and 16 colors, Unicode and CP437, and customizable themes
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better cortex alternative or higher similarity.
cortex reviews and mentions
Posts with mentions or reviews of cortex.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-05-05.
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Introducing Jan
Jan incorporates a lightweight, built-in inference server called Nitro. Nitro supports both llama.cpp and NVIDIA's TensorRT-LLM engines. This means many open LLMs in the GGUF format are supported. Jan's Model Hub is designed for easy installation of pre-configured models but it also allows you to install virtually any model from Hugging Face or even your own.
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Ollama Python and JavaScript Libraries
I'd like to see a comparison to nitro https://github.com/janhq/nitro which has been fantastic for running a local LLM.
- FLaNK Weekly 08 Jan 2024
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Nitro: A fast, lightweight 3MB inference server with OpenAI-Compatible API
Look... I appreciate a cool project, but this is probably not a good idea.
> Built on top of the cutting-edge inference library llama.cpp, modified to be production ready.
It's not. It's literally just llama.cpp -> https://github.com/janhq/nitro/blob/main/.gitmodules
Llama.cpp makes no pretense at being a robust safe network ready library; it's a high performance library.
You've made no changes to llama.cpp here; you're just calling the llama.cpp API directly from your drogon app.
Hm.
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Look... that's interesting, but, honestly, I know there's this wave of "C++ is back!" stuff going on, but building network applications in C++ is very tricky to do right, and while this is cool, I'm not sure 'llama.cpp is in c++ because it needs to be fast' is a good reason to go 'so lets build a network server in c++ too!'.
I mean, I guess you could argue that since llama.cpp is a C++ application, it's fair for them to offer their own server example with an openai compatible API (which you can read about here: https://github.com/ggerganov/llama.cpp/issues/4216, https://github.com/ggerganov/llama.cpp/blob/master/examples/...).
...but a production ready application?
I wrote a rust binding to llama.cpp and my conclusion was that llama.cpp is pretty bleeding edge software, and bluntly, you should process isolate it from anything you really care about, if you want to avoid undefined behavior after long running inference sequences; because it updates very often, and often breaks. Those breaks are usually UB. It does not have a 'stable' version.
Further more, when you run large models and run out of memory, C++ applications are notoriously unreliable in their 'handle OOM' behaviour.
Soo.... I know there's something fun here, but really... unless you had a really really compelling reason to need to write your server software in c++ (and I see no compelling reason here), I'm curious why you would?
It seems enormously risky.
The quality of this code is 'fun', not 'production ready'.
- Apple Silicon Llama 7B running in docker?
- Is there any LLM that can be installed with out python
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Stats
Basic cortex repo stats
8
1,635
9.8
7 days ago
janhq/cortex is an open source project licensed under GNU Affero General Public License v3.0 which is an OSI approved license.
The primary programming language of cortex is C++.
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