cody
sweep
cody | sweep | |
---|---|---|
22 | 37 | |
1,942 | 7,081 | |
16.0% | 2.2% | |
9.9 | 10.0 | |
1 day ago | 1 day ago | |
TypeScript | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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.
cody
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Ask HN: Cheapest way to use LLM coding assistance?
checkout the cody extension https://github.com/sourcegraph/cody available for various editors like vscode
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The lifecycle of a code AI completion
I don't think it is. There is a test file which includes C#, Kotlin, etc among supported languages, which aren't included in the file you linked: https://github.com/sourcegraph/cody/blob/main/vscode/src/com...
But this test didn't seem to include TypeScript so it's obviously not comprehensive. I'm not convinced this information is actually in one place.
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Ollama is now available on Windows in preview
Cody (https://github.com/sourcegraph/cody) supports using Ollama for autocomplete in VS Code. See the release notes at https://sourcegraph.com/blog/cody-vscode-1.1.0-release for instructions. And soon it'll support Ollama for chat/refactoring as well (https://twitter.com/sqs/status/1750045006382162346/video/1).
Disclaimer: I work on Cody.
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My 2024 AI Predictions
Have you tried Cody (https://cody.dev)? Cody has a deep understanding of your codebase and generally does much better at code gen than just one-shotting GPT4 without context.
(disclaimer: I work at Sourcegraph)
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🚀 7 AI Tools to Improve your productivity: A Deep Dive 🪄✨
3️⃣ Cody AI 🤖
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An ex-Googler's guide to dev tools
Author of the post here—as another commenter mentioned, this is indeed a bit dated now, someone should probably write an updated post!
There's been a ton of evolution in dev tools in the past 3 years with some old workhorses retiring (RIP Phabricator) and new ones (like Graphite, which is awesome) emerging... and of course AI-AI-AI. LLMs have created some great new tools for the developer inner loop—that's probably the most glaring omission here. If I were to include that category today, it would mention tools like ChatGPT, GH Copilot, Cursor, and our own Sourcegraph Cody (https://cody.dev). I'm told that Google has internal AI dev tools now that generate more code than humans.
Excited to see what changes the next 3 years bring—the pace of innovation is only accelerating!
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LocalPilot: Open-source GitHub Copilot on your MacBook
I'm sorry to hear that. We have made a lot of improvements to Cody recently. We had a big release on Oct 4 that significantly decreased latency while improving completion quality. You can read all about it here: https://about.sourcegraph.com/blog/feature-release-october-2...
We love feedback and ideas as well, and like I said are constantly iterating on the UI to improve it. I'm actually wrapping up a blog post on how to better leverage Cody w/ VS Studio, that'll be out either later today or sometime tomorrow. As far as feedback though: https://github.com/sourcegraph/cody/discussions/new?category... would be the place to share ideas :)
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Show HN: Ollama for Linux – Run LLMs on Linux with GPU Acceleration
Ollama is awesome. I am part of a team building a code AI application[1], and we want to give devs the option to run it locally instead of only supporting external LLMs from Anthropic, OpenAI, etc. Those big remote LLMs are incredibly powerful and probably the right choice for most devs, but it's good for devs to have a local option as well—for security, privacy, cost, latency, simplicity, freedom, etc.
As an app dev, we have 2 choices:
(1) Build our own support for LLMs, GPU/CPU execution, model downloading, inference optimizations, etc.
(2) Just tell users "run Ollama" and have our app hit the Ollama API on localhost (or shell out to `ollama`).
Obviously choice 2 is much, much simpler. There are some things in the middle, like less polished wrappers around llama.cpp, but Ollama is the only thing that 100% of people I've told about have been able to install without any problems.
That's huge because it's finally possible to build real apps that use local LLMs—and still reach a big userbase. Your userbase is now (pretty much) "anyone who can download and run a desktop app and who has a relatively modern laptop", which is a big population.
I'm really excited to see what people build on Ollama.
(And Ollama will simplify deploying server-side LLM apps as well, but right now from participating in the community, it seems most people are only thinking of it for local apps. I expect that to change when people realize that they can ship a self-contained server app that runs on a cheap AWS/GCP instance and uses an Ollama-executed LLM for various features.)
[1] Shameless plug for the WIP PR where I'm implementing Ollama support in Cody, our code AI app: https://github.com/sourcegraph/cody/pull/905.
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Cody – The AI that knows your entire codebase
Awesome. The repository is at https://github.com/sourcegraph/cody for anyone who hasn't seen it yet.
- Code AI with Codebase Context
sweep
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Show HN: Dewhale – GitHub-Powered AI for effortless development
What's the difference with https://sweep.dev ?
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My 2024 AI Predictions
- https://sweep.dev have a bot where you create a GitHub comment and it writes the PR to fix it. They have between 30% and 70% success rate. This is pretty bad but they're one of the best today
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🚀 7 AI Tools to Improve your productivity: A Deep Dive 🪄✨
6️⃣ Sweep AI 🧹
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CMV: People who expect AGI in 2024 will be disappointed
https://github.com/sweepai/sweep arguably already does the work of an "average" programmer
- My lightweight Docker deployment script for webhooks
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Introduction to Open Source
The GitHub repo I researched and found was a repo that utilizes UI to create code changes based on user bug reports https://github.com/sweepai/sweep. This feature works with small errors and is aimed to eliminate developers from opening tickets that involve small bug fixes or refractors. I know that learning a new language often has many set backs and learning curves. After finding this project I believe I can learn some basics of Python while also utilizing UI.
- Sweep: Turn bugs and feature requests into code changes
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[P] AI developer uses Pytorch 2.0 documentation
I wanted to share how we got Sweep, an AI-powered junior developer, to use the latest pytorch documentation. We wrote a simple webcrawler using Playwright, which bypasses a lot of issues while scraping. Also, because we only need to crawl documentation, we can filter out common tags in markdown. This lets us accurately crawl and index any docs site. Try it now at https://github.com/sweepai/sweep! You can add docs by going to your sweep.yaml and adding both the keyword and the url.
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Launch HN: Sweep (YC S23) – A bot to create simple PRs in your codebase
We have that! You can directly append to our system prompt here to customize Sweep https://github.com/sweepai/sweep/blob/main/sweep.yaml
What are some alternatives?
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
ferris - A low profile split keyboard designed to satisfy one single use case elegantly
zoekt - Fast trigram based code search
miryoku - Miryoku is an ergonomic, minimal, orthogonal, and universal keyboard layout.
lsp-cody - A Client to Connect to the Cody LSP Gateway
developer - the first library to let you embed a developer agent in your own app!
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
popcorn - 36 key corne thing but with more stagger.
llm-ls - LSP server leveraging LLMs for code completion (and more?)
github-pr-summary - Use ChatGPT to summarize & review GitHub Pull Requests
localpilot
zmk - ZMK Firmware Repository