cortex
harlequin
cortex | harlequin | |
---|---|---|
8 | 14 | |
1,661 | 2,665 | |
3.7% | - | |
9.8 | 9.3 | |
6 days ago | 13 days ago | |
C++ | Python | |
GNU Affero General Public License v3.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
cortex
-
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.
-
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
-
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.
...
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
harlequin
- DBeaver – open-source Database client
- FLaNK Stack 29 Jan 2024
- FLaNK Weekly 08 Jan 2024
- Harlequin: SQL IDE for Your Terminal
- Harlequin: DuckDB IDE for the terminal
- Harlequin.sh DuckDB IDE for your terminal
-
Show HN: Harlequin, the DuckDB IDE for Your Terminal
For the past four months I've been working (part-time, this is OSS after all) on Harlequin, a SQL IDE for DuckDB that runs in your terminal. I built this because I work in Data, and I found myself often reaching for the DuckDB CLI to quickly query CSV or Parquet data, but then hitting a wall when using the DuckDB CLI as my queries got more complex and my result sets got larger.
Harlequin is a drop-in replacement for the DuckDB CLI that runs in any terminal (even over SSH), but adds a browsable data catalog, full-powered text editor (with multiple buffer support), and a scrollable results viewer that can display thousands of records.
Harlequin is written in Python, using the Textual framework. It's licensed under MIT.
Today I released v1.0.0, and I'm excited to share Harlequin with HN for the first time. You can try it out with `pip install harlequin`, or visit https://harlequin.sh for docs and other info.
- FLaNK Stack Weekly for 07August2023
What are some alternatives?
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
hugging-chat-api - HuggingChat Python API🤗
bionic-gpt - BionicGPT is an on-premise replacement for ChatGPT, offering the advantages of Generative AI while maintaining strict data confidentiality
opensms - Open-source solution to programmatically send and receive SMS using your own SIM cards
csvlens - Command line csv viewer
llama2_aided_tesseract - Enhance Tesseract OCR output for scanned PDFs by applying Large Language Model (LLM) corrections, complete with options for text validation and hallucination filtering.
nnl - a low-latency and high-performance inference engine for large models on low-memory GPU platform.
OpenBuddy - Open Multilingual Chatbot for Everyone
Tribuo - Tribuo - A Java machine learning library
examples - Analyze the unstructured data with Towhee, such as reverse image search, reverse video search, audio classification, question and answer systems, molecular search, etc.
hyperfine - A command-line benchmarking tool
textadept - Textadept is a fast, minimalist, and remarkably extensible cross-platform text editor for programmers.