geppetto
llm
geppetto | llm | |
---|---|---|
4 | 27 | |
69 | 3,189 | |
- | - | |
9.2 | 9.4 | |
17 days ago | 9 days ago | |
Go | Python | |
MIT License | Apache License 2.0 |
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geppetto
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Bash One-Liners for LLMs
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.
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LLMs are a revolution in open source
(author here): I am currently writing a book about programming with LLMs, I have absolutely put my money where my mouth is over the last year, and there is not doubt in my mind that we will see incredible tools in 2024.
Already the emergent tools and frameworks are impressive, and the fact that you can make them yours by adding a couple of prompting lines and really tailor them to your codebase is the killer factor.
My tooling ( https://github.com/go-go-golems/geppetto ) sucks ass UI wise, yet I get an incredible value out of it. It's hard to quantify as a 10X, because my code architecture has changed to accomodate the models.
In some ways, the trick to coding with LLMs is to... not have them produce code, but intermediate DSL representations. There's much more to it, thus the book.
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Build your own custom AI CLI tools
All of these examples were built in a couple of hours altogether. By the end of the article, you will be able to build them too, with no code involved.
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LLMs will fundamentally change software engineering
I don't bother manually writing any of this data munching / API wrapping / result validating code anymore. I had to build a server-to-server integration with Google Tag Manager recently. I literally copy pasted the webpage into a simple 3 line prompt and can now generate PHP classes, typescript interfaces, event log parsers, SQL serialization with a simple shell command.
llm
- FLaNK AI-April 22, 2024
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Show HN: I made a tool to clean and convert any webpage to Markdown
That's a great use case, you might be able to do this if you've got a copy and paste on the command line with
https://github.com/simonw/llm
In between. An alias like pdfwtf translating to "paste | llm command | copy"
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Command R+: A Scalable LLM Built for Business
I added support for this model to my LLM CLI tool via a new plugin: https://github.com/simonw/llm-command-r
So now you can do this:
pipx install llm
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The Next Generation of Claude (Claude 3)
If you're willing to use the CLI, Simon Willison's llm library[0] should do the trick.
[0] https://github.com/simonw/llm
- Show HN: I made an app to use local AI as daily driver
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Localllm lets you develop gen AI apps on local CPUs
I'm not thrilled about https://github.com/GoogleCloudPlatform/localllm/blob/main/ll... calling their Python package "llm" and installing "llm" as a CLI command, when my similar https://llm.datasette.io/ project has that namespace reserved on PyPI already: https://pypi.org/project/llm/
- FLaNK 15 Jan 2024
- Show HN: Simple Script for Enhanced LLM Interaction in Vim
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Bash One-Liners for LLMs
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.
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Semantic Kernel
Seems nice if you're using c# or java. It also supports python, but for that Simon's llm library is nice because he designed it as both a library and a command line tool: https://github.com/simonw/llm
What are some alternatives?
pyllms - Minimal Python library to connect to LLMs (OpenAI, Anthropic, AI21, Cohere, Aleph Alpha, HuggingfaceHub, Google PaLM2, with a built-in model performance benchmark.
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
oak - GO GO PARSE YOUR CODE GO GO
langroid - Harness LLMs with Multi-Agent Programming
biberon - A command-line tool to work with bibliography data
exllama - A more memory-efficient rewrite of the HF transformers implementation of Llama for use with quantized weights.
escuse-me - GO GO GOLEM ELASTIC SEARCH GO GO GADGET - ESCUSE ME???
multi-gpt - A Clojure interface into the GPT API with advanced tools like conversational memory, task management, and more
parka - Convert your CLI apps to APIs
jehuty - Fluent API to interact with chat based GPT model
majuscule
llm-replicate - LLM plugin for models hosted on Replicate