tabby
aider
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tabby | aider | |
---|---|---|
24 | 61 | |
17,044 | 8,328 | |
5.4% | - | |
9.9 | 9.9 | |
2 days ago | 7 days ago | |
Rust | Python | |
GNU General Public License v3.0 or later | 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.
tabby
- Google CodeGemma: Open Code Models Based on Gemma [pdf]
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What AI assistants are already bundled for Linux?
NixOS just got tabbyml[1] which is built on llama-cpp. Working on systemsd services the weekend and updating latest tabbyml release which supports rocm in addition to cuda
- FLaNK Stack Weekly 19 Feb 2024
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Show HN: Tabby back end in 20 Python lines (self-hosted AI coding assistant)
Nice implementation! It should serve as a great reference for a minimal Tabby's backend API. Thank you for sharing it!
Yeah - ultimately, it won't be as performant or feature-rich compared to https://github.com/TabbyML/tabby, but it's still perfect for educational purposes!
- Stable Code 3B: Coding on the Edge
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Show HN: I built local copilot alternative using Codellama
Looks interesting! What are the main differences between this and https://github.com/TabbyML/tabby ?
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Ask HN: Who is hiring? (October 2023)
TabbyML | Software Engineer (Rust) | REMOTE
Self-hosted AI coding assistant. An opensource / on-prem alternative to GitHub Copilot.
Project: https://github.com/TabbyML/tabby
Tabby is seeking a Software Engineer proficient in Rust to join our core engineering team. In this role, you will be responsible for developing the following features:
- Show HN: Tabby – AI Coding Assistant Runs on Apple M1/M2 GPU
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Meta: Code Llama, an AI Tool for Coding
There are a bunch of VSCode extensions that make use of local models. Tabby seems to be the most friendly right now, but I admittedly haven't tried it myself: https://tabbyml.github.io/tabby/
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CodeCompose: Meta’s AI Coding Assistant
Check out https://github.com/TabbyML/tabby, which is fully self-hostable and comes with niche features. On M1/M2, it offers a convenient single binary deployment, thanks to Rust. You can find the latest release at https://github.com/TabbyML/tabby/releases/tag/latest.
(Disclaimer: I am the author)
aider
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Aider: AI pair programming in your terminal
Thanks for trying aider, and sorry to hear you had trouble getting the hang of it. It might be worth looking through some of the tips on the aider GitHub page [0].
In particular, this is one of the most important tips: Large changes are best performed as a sequence of thoughtful bite sized steps, where you plan out the approach and overall design. Walk GPT through changes like you might with a junior dev. Ask for a refactor to prepare, then ask for the actual change. Spend the time to ask for code quality/structure improvements.
Not sure if this was a factor in your attempts? I'd be happy to help you if you'd like to open an GitHub issue [1] our jump into our discord [2].
[0] https://github.com/paul-gauthier/aider#tips
[1] https://github.com/paul-gauthier/aider/issues/new/choose
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Ask HN: If you've used GPT-4-Turbo and Claude Opus, which do you prefer?
Have you tried something like Agentic’s Glide? (They announced it this week here on HN)
They use gpt, but they might be able to configure it so it uses Claude
Another tool to check out could be aider https://github.com/paul-gauthier/aider
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Launch HN: Glide (YC W19) – AI-assisted technical design docs
Are you aware of the work on https://github.com/paul-gauthier/aider? What's your take on generating code diffs directly instead of code editing instructions?
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A Man in Seat 61
He should add AI to his site!
Not really - the site is great as-is and there's nothing wrong with this approach. It looks like it works really well for Mr. 61.
But I'd imagine it'd be pretty helpful to write tools to help with maintaining the site which do leverage LLM models. Do a combination of search + AI to rewrite + reviewing the individual edits (e.g. through selective git adds).
I'm imagining a tool like https://github.com/paul-gauthier/aider (which I haven't tried yet, but it looks useful for this kind of effort).
- Ask HN: What is the, currently, best Programming LLM (copilot) subscriptions?
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Web Scraping in Python – The Complete Guide
I recently used [0] Playwright for Python and [1] pypandoc to build a scraper that fetches a webpage and turns the content into sane markdown so that it can be passed into an AI coding chat [2].
They are both very gentle dependencies to add to a project. Both packages contain built in or scriptable methods to install their underlying platform-specific binary dependencies. This means you don't need to ask end users to use some complex, platform-specific package manager to install playwright and pandoc.
Playwright let's you scrape pages that rely on js. Pandoc is great at turning HTML into sensible markdown. Below is an excerpt of the openai pricing docs [3] that have been scraped to markdown [4] in this manner.
[0] https://playwright.dev/python/docs/intro
[1] https://github.com/JessicaTegner/pypandoc
[2] https://github.com/paul-gauthier/aider
[3] https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turb...
[4] https://gist.githubusercontent.com/paul-gauthier/95a1434a28d...
## GPT-4 and GPT-4 Turbo
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DeepSeek Coder: Let the Code Write Itself
Thanks for trying aider, and sorry to hear you had trouble getting the hang of it. It might be worth looking through some of the tips on the aider github page:
https://github.com/paul-gauthier/aider#tips
In particular, this is one of the most important tips: Large changes are best performed as a sequence of thoughtful bite sized steps, where you plan out the approach and overall design. Walk GPT through changes like you might with a junior dev. Ask for a refactor to prepare, then ask for the actual change. Spend the time to ask for code quality/structure improvements.
Not sure if this was a factor in your attempts? But it's best not to ask for a big sweeping change all at once. It's hard to unambiguously and completely specify what you want, and it's also harder for GPT to succeed at bigger changes in one bite.
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Voxos.ai – An Open-Source Desktop Voice Assistant
How does Voxos help avoid copying & pasting code into your IDE? I had a look around the code base and don't see any indication that it allows GPT to directly edit your source files. But maybe I am missing it?
I'm asking because this is a major focus of my open source AI coding project aider [0]. I always like to see how other projects approach the challenge of letting GPT edit existing code. Most recently aider adopted unified diffs as the GPT 4 Turbo code editing format [1].
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LLMs and Programming in the first days of 2024
There is a bit of learning curve to figuring out the most effective ways to collaboratively code with GPT, either through aider or other UXs. My best piece of advice is taken from aider's tips list and applies broadly to coding with LLMs:
Large changes are best performed as a sequence of thoughtful bite sized steps, where you plan out the approach and overall design. Walk GPT through changes like you might with a junior dev. Ask for a refactor to prepare, then ask for the actual change. Spend the time to ask for code quality/structure improvements.
- Tell HN: My Favorite Tools
What are some alternatives?
fauxpilot - FauxPilot - an open-source alternative to GitHub Copilot server
gpt-engineer - Specify what you want it to build, the AI asks for clarification, and then builds it.
turbopilot - Turbopilot is an open source large-language-model based code completion engine that runs locally on CPU
gpt-pilot - The first real AI developer
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
llama-cpp-python - Python bindings for llama.cpp
refact - WebUI for Fine-Tuning and Self-hosting of Open-Source Large Language Models for Coding
ollama-ui - Simple HTML UI for Ollama
continue - ⏩ The easiest way to code with any LLM—Continue is an open-source autopilot for VS Code and JetBrains
autodistill - Images to inference with no labeling (use foundation models to train supervised models).
jsonformer - A Bulletproof Way to Generate Structured JSON from Language Models