Bash One-Liners for LLMs

• ollama

  203 64,536 9.9 Go

  Get up and running with Llama 3, Mistral, Gemma, and other large language models.

  

Curious about what HN things about llamafile and modelfile (https://github.com/jmorganca/ollama/blob/main/docs/modelfile...)

Both invoke a Dockerfile like experience. Modelfile immediately seems like a Dockerfile, but llamafile looks harder to use. It is not immediately clear what it looks like. Is it a sequence of commands at the terminal?

My theory question is, why not use a Dockerfile for this?

• blip-caption

  2 101 4.0 Python

  Generate captions for images with Salesforce BLIP

I've been gleefully exploring the intersection of LLMs and CLI utilities for a few months now - they are such a great fit for each other! The unix philosophy of piping things together is a perfect fit for how LLMs work.

I've mostly been exploring this with my https://llm.datasette.io/ CLI tool, but I have a few other one-off tools as well: https://github.com/simonw/blip-caption and https://github.com/simonw/ospeak

I'm puzzled that more people aren't loudly exploring this space (LLM+CLI) - it's really fun.

• InfluxDB

  www.influxdata.com featured

  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.

  

• ospeak

  2 140 6.7 Python

  CLI tool for running text through OpenAI Text to speech

I've been gleefully exploring the intersection of LLMs and CLI utilities for a few months now - they are such a great fit for each other! The unix philosophy of piping things together is a perfect fit for how LLMs work.

I've mostly been exploring this with my https://llm.datasette.io/ CLI tool, but I have a few other one-off tools as well: https://github.com/simonw/blip-caption and https://github.com/simonw/ospeak

I'm puzzled that more people aren't loudly exploring this space (LLM+CLI) - it's really fun.

• llm

  23 2,991 9.4 Python

  Access large language models from the command-line (by simonw)

I've been gleefully exploring the intersection of LLMs and CLI utilities for a few months now - they are such a great fit for each other! The unix philosophy of piping things together is a perfect fit for how LLMs work.

I've mostly been exploring this with my https://llm.datasette.io/ CLI tool, but I have a few other one-off tools as well: https://github.com/simonw/blip-caption and https://github.com/simonw/ospeak

I'm puzzled that more people aren't loudly exploring this space (LLM+CLI) - it's really fun.

• chatblade

  20 2,545 5.9 Python

  A CLI Swiss Army Knife for ChatGPT

Those are great links. I’ve been using:

https://github.com/npiv/chatblade

• sgpt

  3 164 9.7 Go

  SGPT is a command-line tool that provides a convenient way to interact with OpenAI models, enabling users to run queries, generate shell commands and produce code directly from the terminal.

https://github.com/tbckr/sgpt

I totally agree with LLM+CLI are perfect fit.

One pattern I used recently was httrack + w3m dump + sgpt images with gpt vision to generate a 278K token specific knowledge base with a custom perl hack for a RAG that preserved the outline of the knowledge.

Which brings me to my question for you - have you seen anything unix philosophy aligned for processing inputs and doing RAG locally?

• geppetto

  4 66 9.3 Go

  golang GPT3 tooling (by go-go-golems)

  

I'm heavily using https://github.com/go-go-golems/geppetto for my work, which has a CLI mode and TUI chat mode. It exposes prompt templates as command line verbs, which it can load from multiple "repositories".

I maintain a set of prompts for each repository I am working in (alongside custom "prompto" https://github.com/go-go-golems/prompto scripts that generate dynamic prompting context, i made quite a few for thirdparty libraries for example: https://github.com/go-go-golems/promptos ).

Here's some of the public prompts I use: https://github.com/go-go-golems/geppetto/tree/main/cmd/pinoc...

I am currently working on a declarative agent framework.

• SaaSHub

  www.saashub.com featured

  SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

  

• prompto

  1 3 7.1 Go

  Quickly get custom prompt contexts

  

I'm heavily using https://github.com/go-go-golems/geppetto for my work, which has a CLI mode and TUI chat mode. It exposes prompt templates as command line verbs, which it can load from multiple "repositories".

I maintain a set of prompts for each repository I am working in (alongside custom "prompto" https://github.com/go-go-golems/prompto scripts that generate dynamic prompting context, i made quite a few for thirdparty libraries for example: https://github.com/go-go-golems/promptos ).

Here's some of the public prompts I use: https://github.com/go-go-golems/geppetto/tree/main/cmd/pinoc...

I am currently working on a declarative agent framework.

• promptos

  1 2 4.8 Shell

  A collection of promptos for thirdparty packages

  

I'm heavily using https://github.com/go-go-golems/geppetto for my work, which has a CLI mode and TUI chat mode. It exposes prompt templates as command line verbs, which it can load from multiple "repositories".

I maintain a set of prompts for each repository I am working in (alongside custom "prompto" https://github.com/go-go-golems/prompto scripts that generate dynamic prompting context, i made quite a few for thirdparty libraries for example: https://github.com/go-go-golems/promptos ).

Here's some of the public prompts I use: https://github.com/go-go-golems/geppetto/tree/main/cmd/pinoc...

I am currently working on a declarative agent framework.

• unstructured

  12 6,515 9.8 HTML

  Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.

  

I’ve been looking at this

https://freeling-user-manual.readthedocs.io/en/v4.2/modules/...

at the freeling library in general, also spaCy and NLTK. The chunking algorithms being used in the likes of LangChain are remarkably bad surprisingly.

There is also

https://github.com/Unstructured-IO/unstructured

But I don’t like it, can’t explain why yet.

My intuition is that 1st step is clean sentences and paragraphs and titles/labels/headers. Then probably an LLM can handle outlining and table of contents generation using a stripped down list of objects in the text.

BRIO/BERT summarization could also have a role of some type.

Those are my ideas so far.

Suggest a related project