xg2xg
cody
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xg2xg | cody | |
---|---|---|
15 | 22 | |
14,071 | 1,812 | |
- | 20.6% | |
1.0 | 9.9 | |
29 days ago | 3 days ago | |
TypeScript | ||
- | 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.
xg2xg
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An ex-Googler's guide to dev tools
What about Mendel and Streamz? I don't see those in https://github.com/jhuangtw/xg2xg
- A lookup table of similar tech and services by ex-googlers
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To the people trying to get into FAANG
Infact most of the tech stack that the world uses is also used by these companies but in the form of internal tools so I don't think there should be a problem switching. Here is an example for Google https://github.com/jhuangtw/xg2xg
- [GitHub] jhuangtw/xg2xg: by ex-googlers, for ex-googlers - a lookup table of similar tech & services
- GitHub - jhuangtw/xg2xg: by ex-googlers, for ex-googlers - a lookup table of similar tech & services
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I feel like I’m only learning the company tools and no actual skills. Is that common?
Was able to find it yes :) https://github.com/jhuangtw/xg2xg
- Company internal tools
- Open Source Alternative To
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I recently joined a data engineering team, and my boss wants to consolidate all of our projects into one single git repository. Is this a bad practice?
Google first did their monorepo presentation back in 2015. Also, look at xg2xg to understand how much customize internal tooling Google has.
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Will it be difficult for me to find job in my future?
Tools could be anything like Unix command line tools, build tools, frameworks, other libraries, or some of the larger pieces of infrastructure like those listed at xg2xg.
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
What are some alternatives?
awesome-oss-alternatives - Awesome list of open-source startup alternatives to well-known SaaS products 🚀
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
xy2xy - A list of technologies similar to inner Yandex technologies
zoekt - Fast trigram based code search
hiring-without-whiteboards - ⭐️ Companies that don't have a broken hiring process
lsp-cody - A Client to Connect to the Cody LSP Gateway
ansible-role-docker - Ansible Role - Docker
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
mongodb-cheatsheet - Kick start with mongodb
llm-ls - LSP server leveraging LLMs for code completion (and more?)
naming-cheatsheet - Comprehensive language-agnostic guidelines on variables naming. Home of the A/HC/LC pattern.
localpilot