cody
1filellm
cody | 1filellm | |
---|---|---|
22 | 6 | |
1,942 | 224 | |
16.0% | - | |
9.9 | 9.0 | |
about 22 hours ago | 4 days ago | |
TypeScript | Python | |
Apache License 2.0 | MIT License |
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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š 7 AI Tools to Improve your productivity: A Deep Dive šŖāØ
3ļøā£ Cody AI š¤
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An ex-Googler's guide to dev tools
Author of the post hereāas 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 loopāthat'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 bringāthe 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 ā 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 wellāfor 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 LLMsāand 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 ā 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
1filellm
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Show HN: FileKitty ā Combine and label text files for LLM prompt contexts
I created something similar, https://github.com/jimmc414/1filellm
It converts papers, repositories, PRs and web docs into one text file for llm ingestion
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The lifecycle of a code AI completion
I created a cli tool that copies a GitHub or local repo into a text file for llm ingestion. It only pulls the filetypes you specify.
https://github.com/jimmc414/1filellm
- Show HN: Command Line Data Aggregation Tool for LLM Ingestion
- Show HN: Simple CLI to aggregate repos, papers and docs for LLM ingestion
- Code Repo-Prep for LLM Ingestion
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Show HN: GPT Repo Loader ā load entire code repos into GPT prompts
Nice. I guess we are all thinking the same things. I created something similar today where you can choose the file extensions to pull and handles Jupiter notebooks pulling only text and code. I included a script to strip out superfluous characters, stop words, and converts everything to lowercase.
It also works if you supply a local folder of source files instead of a github repo.
https://github.com/jimmc414/onefilerepo
What are some alternatives?
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
gpt-repository-loader - Convert code repos into an LLM prompt-friendly format. Mostly built by GPT-4.
zoekt - Fast trigram based code search
langchain - ā” Building applications with LLMs through composability ā” [Moved to: https://github.com/langchain-ai/langchain]
lsp-cody - A Client to Connect to the Cody LSP Gateway
llama_index - LlamaIndex is a data framework for your LLM applications
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
AutoPR - Run AI-powered workflows over your codebase
llm-ls - LSP server leveraging LLMs for code completion (and more?)
aidev - AI developer: ask GPT-4 to modify an entire folder full of files
localpilot
react-agent - The open-source React.js Autonomous LLM Agent