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cody
HISTORICAL RECORD2023–2024
sourcegraph / cody · Not publicly available

cody

Discover this repository through its Hacker News conversations.

10Distinct people
27Mentions
0Explicit recommenders
REPOSITORY AT A GLANCE

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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 12:54:37 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month27 dated mentions

Observed mentions: 2023-07-21 02:05:04 UTC to 2024-08-27 01:44:11 UTC.

0369122023-07-01 00:00:00 UTC to 2023-08-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsJul 20232023-08-01 00:00:00 UTC to 2023-09-01 00:00:00 UTC (exclusive): 11 mentions; 0 submissions, 11 comments2023-09-01 00:00:00 UTC to 2023-10-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2023-10-01 00:00:00 UTC to 2023-11-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2023-11-01 00:00:00 UTC to 2023-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-12-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2024-02-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsJan 20242024-02-01 00:00:00 UTC to 2024-03-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024-03-01 00:00:00 UTC to 2024-04-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024-04-01 00:00:00 UTC to 2024-05-01 00:00:00 UTC (exclusive): 4 mentions; 0 submissions, 4 comments2024-05-01 00:00:00 UTC to 2024-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-06-01 00:00:00 UTC to 2024-07-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2024-07-01 00:00:00 UTC to 2024-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-08-01 00:00:00 UTC to 2024-09-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 commentsAug 2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
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PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jul 20232023-07-01 00:00:00 UTC2023-08-01 00:00:00 UTC110
Aug 20232023-08-01 00:00:00 UTC2023-09-01 00:00:00 UTC11011
Sep 20232023-09-01 00:00:00 UTC2023-10-01 00:00:00 UTC202
Oct 20232023-10-01 00:00:00 UTC2023-11-01 00:00:00 UTC101
Nov 20232023-11-01 00:00:00 UTC2023-12-01 00:00:00 UTC000
Dec 20232023-12-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
Jan 20242024-01-01 00:00:00 UTC2024-02-01 00:00:00 UTC101
Feb 20242024-02-01 00:00:00 UTC2024-03-01 00:00:00 UTC101
Mar 20242024-03-01 00:00:00 UTC2024-04-01 00:00:00 UTC101
Apr 20242024-04-01 00:00:00 UTC2024-05-01 00:00:00 UTC404
May 20242024-05-01 00:00:00 UTC2024-06-01 00:00:00 UTC000
Jun 20242024-06-01 00:00:00 UTC2024-07-01 00:00:00 UTC202
Jul 20242024-07-01 00:00:00 UTC2024-08-01 00:00:00 UTC000
Aug 20242024-08-01 00:00:00 UTC2024-09-01 00:00:00 UTC303

What Hacker News says

27 sources
Yes, Cody can use Ollama for both chat and autocomplete. See https://sourcegraph.com/docs/cody/clients/install-vscode#sup.... This lets you use Cody fully offline, but it doesn't /prevent/ API calls to third parties; you are still able to select online models like Claude 3.5 Sonnet. I have a WIP PR right now (like literally coding on it right now) making Cody support strict offline mode better (i.e., not even showing online models if you choose to be offline): https://github.com/sourcegraph/cody/pull/5221.
In Cursor Has Raised $60M
Sourcegraph CEO here. We made our main internal codebase (for our code search product) private. We did this to focus. It added a lot of extra work and risk to have stuff be open source and public. We gotta stay focused on building a great code search/intelligence product for our customers. That's what ultimately lets us still do plenty of things for devs and the OSS community: (1) Our super popular public code search is at https://sourcegraph.com/search, which is the same product customers use internally on their own codebases. We spend millions of dollars annually on this public instance with almost 1M OSS repositories to help out everyone using OSS (and we love when they like it so much they bring it into their company :-). (2) We also have still have a ton of open-source code, like https://sourcegraph.com/github.com/sourcegraph/cody (o
Read the rest
ur code AI tool). BTW, if any founders out there are wondering whether they should make their own code open-source or public, happy to chat! Email in profile. I think it could make sense for a lot of companies, but more so for infrastructure products or client tools, not so much for full server-side end-user applications.
In Sourcegraph went dark
Yeah, that is needed to make everything more accurate. We are working on 3 related things to make Cody better understand the structure of your code and take feedback from the compiler (and other tools). All are experimental and not enabled by default, but you can peek at them if you're interested. 1. (experimental) LSP-based context — https://github.com/sourcegraph/cody/pull/3493 2. (experimental) TypeScript tsc context — https://github.com/sourcegraph/cody/pull/3843 3. (experimental) OpenCtx, which can pull in diagnostics from tools outside your editor — https://openctx.org/ And then of course the agent to actually iterate on the generated code based on this feedback. We're really excited about this stuff, and it'll arrive in Cody when we can get it to a high quality bar and prove it helps.
In Enhancing Code Completion for Rust in Cody
> Because of the language-specific nature of this heuristic, we generally do not support multi-line completions for all languages. However, we’re always happy to extend our list of supported languages and, since Cody is open-source, you can also contribute and improve the list. (link to https://github.com/sourcegraph/cody/blob/main/vscode/src/com...) That link to the list of supported languages is broken. I couldn't find a similar file elsewhere in the repo: maybe the list got folded up into a function in another file? Also a bit annoying that I couldn't find the info on the company's website (though I gave up pretty quickly).
In The lifecycle of a code AI completion
You can try it with Sourcegraph Cody. https://sourcegraph.com/cody And instructions on how to change the provider to use Ollama w/ whatever model you want: Install and run Ollama - Put ollama in your $PATH. E.g. ln -s ./ollama /usr/local/bin/ollama. - Download Code Llama 70b: ollama pull codellama:70b - Update Cody's VS Code settings to use the unstable-ollama autocomplete provider. - Confirm Cody uses Ollama by looking at the Cody output channel or the autocomplete trace view (in the command palette). - Update the cody settings to use "codellama:70b" as the ollama model https://github.com/sourcegraph/cody/pull/2635
In Meta AI releases Code Llama 70B
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 :)
In LocalPilot: Open-source GitHub Copilot on your MacBook
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
Read the rest
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.
In Ollama for Linux – Run LLMs on Linux with GPU Acceleration

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