llm-plugins
llm-gpt4all
| llm-plugins | llm-gpt4all | |
|---|---|---|
| 1 | 3 | |
| 39 | 184 | |
| - | - | |
| 5.4 | 6.9 | |
| 9 months ago | 13 days ago | |
| Python | ||
| - | Apache License 2.0 |
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.
llm-plugins
-
Accessing Llama 2 from the command-line with the LLM-replicate plugin
More about my LLM tool (and Python library) here: https://llm.datasette.io/
Here's the full implementation of that llm-replicate plugin: https://github.com/simonw/llm-replicate/blob/0.2/llm_replica...
If you want to write a plugin for some other LLM I have a detailed tutorial here: https://llm.datasette.io/en/stable/plugins/tutorial-model-pl... - plus a bunch of examples linked from here: https://github.com/simonw/llm-plugins
llm-gpt4all
-
LLM now provides tools for working with embeddings
I'm still iterating on that. Plugins get complete control over the prompts, so they can handle the various weirdnesses of them. Here's some relevant code:
https://github.com/simonw/llm-gpt4all/blob/0046e2bf5d0a9c369...
https://github.com/simonw/llm-mlc/blob/b05eec9ba008e700ecc42...
https://github.com/simonw/llm-llama-cpp/blob/29ee8d239f5cfbf...
I'm not completely happy with this yet. Part of the problem is that different models on the same architecture may have completely different prompting styles.
I expect I'll eventually evolve the plugins to allow them to be configured in an easier and more flexible way. Ideally I'd like you to be able to run new models on existing architectures using an existing plugin.
-
Accessing Llama 2 from the command-line with the LLM-replicate plugin
My LLM tool can be used for both. That's what the plugins are for.
It can talk to OpenAI, PaLM 2 and Llama / other models on Replicate via API, using API keys.
It can run local models on your own machine using these two plugins: https://github.com/simonw/llm-gpt4all and https://github.com/simonw/llm-mpt30b
-
The Problem with LangChain
Yeah I haven't figured out how to have it reuse the models from the desktop GPT4All installation yet, issue here: https://github.com/simonw/llm-gpt4all/issues/5
What are some alternatives?
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
llm-mpt30b - LLM plugin adding support for the MPT-30B language model
gchain - Composable LLM Application framework inspired by langchain
llm-replicate - LLM plugin for models hosted on Replicate
llm-mlc - LLM plugin for running models using MLC
gpt4all - gpt4all: run open-source LLMs anywhere
simpleaichat - Python package for easily interfacing with chat apps, with robust features and minimal code complexity.
multi-gpt - A Clojure interface into the GPT API with advanced tools like conversational memory, task management, and more
llama.cpp - LLM inference in C/C++
aipl - Array-Inspired Pipeline Language
llm-api - Fully typed & consistent chat APIs for OpenAI, Anthropic, Groq, and Azure's chat models for browser, edge, and node environments.