cody
web-llm
cody | web-llm | |
---|---|---|
22 | 43 | |
1,942 | 9,102 | |
16.0% | 2.4% | |
9.9 | 9.1 | |
1 day ago | 10 days ago | |
TypeScript | TypeScript | |
Apache License 2.0 | 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.
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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đ 7 AI Tools to Improve your productivity: A Deep Dive đŞâ¨
3ď¸âŁ Cody AI đ¤
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An ex-Googler's guide to dev tools
Author of the post hereâas 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 loopâthat'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 bringâthe 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 â 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 wellâfor 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 LLMsâand 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 â 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
web-llm
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Show HN: I built a free in-browser Llama 3 chatbot powered by WebGPU
Looks like it uses this: https://github.com/mlc-ai/web-llm
- What stack would you recommend to build a LLM app in React without a backend?
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When LLM doesnât fit into memory, how to make it work?
So I was playing with MLC webllm locally. I got my mistral 7B model installed and quantised. Converted it using mlc lib to metal package for Apple chips. Now it takes only 3.5GB of memory
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Show HN: Ollama for Linux â Run LLMs on Linux with GPU Acceleration
Maybe they're talking about https://github.com/mlc-ai/mlc-llm which is used for web-llm (https://github.com/mlc-ai/web-llm)? Seems to be using TVM.
- Local embeddings model for javascript
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this makes deploying AI language models so much easier
Link to github for those who want to know about MLC straight from them. Web demo is cool but takes a long time to load first time. https://github.com/mlc-ai/web-llm
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April 2023
web-llm: Bringing large-language models and chat to web browsers. (https://github.com/mlc-ai/web-llm)
- Running a small model on a phone?
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Weekly Megathread - 14 May 2023
WebLLM - https://mlc.ai/web-llm/
- WebLLM - Bringing LLMs based chatbot to your web browser
What are some alternatives?
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
chainlit - Build Conversational AI in minutes âĄď¸
zoekt - Fast trigram based code search
mlc-llm - Enable everyone to develop, optimize and deploy AI models natively on everyone's devices.
lsp-cody - A Client to Connect to the Cody LSP Gateway
gpt4all - gpt4all: run open-source LLMs anywhere
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
StableLM - StableLM: Stability AI Language Models
llm-ls - LSP server leveraging LLMs for code completion (and more?)
FastChat - An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
localpilot
duckdb-wasm - WebAssembly version of DuckDB