gpt4all VS promptr

I don’t know if Ollama can do this but https://gpt4all.io/ can.

Gpt4all is a local desktop app with a Python API that can be trained on your documents: https://gpt4all.io/

The readme page is cryptic. What does 'mature' mean in this context? What is the sample text a continuation of?

Hving a gif the thing in use would be great, similar to the gpt4all readme page. (https://github.com/nomic-ai/gpt4all)

Check https://github.com/nomic-ai/gpt4all instead.

"I ran performance tests on two systems, here's the results of system 1, and heres the results of system 2. Summarize the results, and build a markdown table containing x,y,z rows."

"extract the reusable functions out of this bash script"

"write me a cfssl command to generate a intermediate CA"

"What is the regex for _____"

"Here are my accomplishments over the last 6 months, summarize them into a 1 page performance report."

etc etc etc

If you're not using GPT4 or some LLM as part of your daily flow you're working too hard.

Get GPT4All (https://gpt4all.io), log into OpenAI, drop $20 on your account, get a API key, and start using GPT4.

offline versija, nors ir ne tokia pažengus - https://github.com/nomic-ai/gpt4all ; https://gpt4all.io/index.html

Take a look at https://gpt4all.io, their docs are pretty awesome

I run one. I built an iMessage-like frontend to it using plain JS and a Python websocket backend. I mostly just use it for curiosity and playing with different prompts. I only have 16GB of RAM to dedicate to it, so I use an 8B parameter model which is enough for fun and chitchat, but I don't find it good enough to replace ChatGPT.

https://github.com/nomic-ai/gpt4all

I taught https://github.com/KillianLucas/open-interpreter how to use https://github.com/ferrislucas/promptr

Then I asked it to add a test suite to a rails side project. It created missing factories, corrected a broken test database configuration, and wrote tests for the classes and controllers that I asked it to.

I didn't have to get involved with mundane details. I did have to intervene here and there, but not much. The tests aren't the best in the world, but IMO they're adding value by at least covering the happy path. They're not as good as an experienced person would write.

I did spend a non-trivial amount of time fiddling with the prompts I used to teach OI about Promptr as well as the prompts I used to get it to successfully create the test suite.

The total cost was around $11 using GPT4 turbo.

I think in this case it was a fun experiment. I think in the future, this type of tooling will be ubiquitous.

I made a CLI tool called Promptr that allows you to make changes to a codebase via plain English instructions:

https://github.com/ferrislucas/promptr

There’s a templating system (liquidjs) included which is useful if you have a library of prompts that you want to reference often.

You can think of it as a junior engineer that needs explicit instructions.

Here are a few example PR’s implemented by Promptr - see the commits for the prompt that was used to produce the code:

https://github.com/ferrislucas/promptr/pull/38

https://github.com/ferrislucas/promptr/pull/41

https://github.com/ferrislucas/promptr

You just prompt it directly or with a file, and it applies the changes to your file system. There's also a templating system that allows you to reference other files from your prompt file if you want to have a shared prompt file that contains project conventions etc.

This is exactly the use that Promptr is intended for https://github.com/ferrislucas/promptr

* full disclosure: I’m the author of Promptr

I’ve been experimenting with pairing a tool I wrote called Promptr [1] with another tool called Open Interpreter [2].

I start with a prompt that teaches Open Interpreter how to use Promptr, and then I discuss what I’m trying to accomplish. It’s certainly not perfect, but there’s definitely something good that happens when you can iterate using dialog with a robot that can modify your file system and execute commands locally.

[1] Promptr: https://github.com/ferrislucas/promptr

[2] Open Interpreter: https://github.com/KillianLucas/open-interpreter

I wrote a great tool for this: https://github.com/ferrislucas/promptr

It’s great for making changes to existing code because it automatically includes the relevant files for context.

For those looking for specific examples of useful code being authored by AI, you can check out this tool:

https://github.com/ferrislucas/promptr

The README links to example PR’s comprised of commits written by GPT4. The prompts used to produce the code are noted in the commit messages.

Promptr is a coding assistant tool that allows you to ask GPT to produce or modify code, and the results will be automatically applied to your file system.

https://github.com/ferrislucas/promptr

From the README:

I'm also interested in this problem. It can be theoretically solved by giving GPT long-term memory about a specific codebase through vector embedding generation (using OpenAI's embeddings API). The semantic embeddings can then be stored in a vector (or vector-supported) database such as Pinecone alongside metadata for querying. Some of the key considerations are how to compare vectors for similarity (there are many algorithms) and how to use metadata to better support your use case. The following resources can be helpful to further understand this technique: - https://platform.openai.com/docs/guides/embeddings - https://www.mlq.ai/fine-tuning-gpt-3-question-answer-bot/ - https://www.pinecone.io/learn/javascript-chatbot/ A couple of semi-related projects I've been looking into: - https://github.com/ferrislucas/promptr - https://github.com/pashpashpash/vault-ai

Promptr is a CLI tool for operating on your codebase using GPT. (https://github.com/ferrislucas/promptr)