Introducing enhancements to Code Search and Cody, including a 2x increase in autocomplete quality
Today, we're announcing a major upgrade to Cody that achieves a best-in-class initial completion acceptance rate of 30%. Cody now supports using OpenAI and open source language models in addition to the models from Anthropic already supported, and Cody LLMs can now be hosted on Azure OpenAI and AWS Bedrock. Cody is also now available for Neovim, in addition to VS Code and JetBrains IDEs. We've also revamped the Cody onboarding experience, which no longer requires installing a separate app, greatly simplifying the installation process.
Sourcegraph Code Search 5.2 features a number of admin usability improvements, including improved admin onboarding and troubleshooting features for repository syncing on very large codebases.
Read on to learn more about what’s new. And, if you’d like to learn more about how we view the evolution of the code AI landscape, check out our other post: How we’re thinking about the levels of Code AI.
Speed & quality improvements across Cody IDE clients
Completion Acceptance Rate (CAR) has become a standard way to measure the quality of completions produced by AI coding assistants. Both response quality and latency affect CAR as high quality slow completions and low quality fast completions are more likely to be rejected.
Cody's initial CAR in June was 15%. With the latest updates, Cody's daily CAR has reached as high as 30%. Cody autocomplete is also now much quicker, with P75 multiline latency improving from 3.4 seconds to 2.4 seconds and single-line latencies from 2.0 seconds to 1.1 seconds.
A major factor in Cody’s improved performance comes from incorporating open source LLMs into Cody. Cody now uses the StarCoder model for the majority of its completions in the community edition. Cody’s StarCoder runs on Fireworks, a new platform that provides very fast inference for open source LLMs. Going forward, Cody for community users will make use of a combination of proprietary LLMs from Anthropic and open source models like StarCoder (the CAR we report comes from using Cody with StarCoder).
Another factor driving improved CAR is that Cody now uses the AST to determine when to trigger a completion and whether to generate a single-line or multi-line completion. Here's an example of where Cody opts for a one-shot multiline completion in contrast to another coding assistant that generates code line by line.
Other coding assistant:
Cody itself remains open source. We also believe our ability to integrate the best open source and proprietary LLMs in the fast-moving model landscape will be a competitive advantage and accelerator of progress for Cody that will compound over time.
Cody for Neovim, now available as experimental
Cody for Neovim is here! This new plugin brings both autocomplete and chat to Neovim, and it's available today for free.
Once you've installed and configured the plugin, Cody for Neovim will provide three major features:
- Autocomplete: Cody makes inline suggestions as you type. Cody's suggestions will be marked with
[cody]and appear above other LSP suggestions if both are configured.
- Chat: Talk with Cody in the side panel. If you connect the plugin to your Sourcegraph instance to enable codebase awareness, Cody can find & explain code using context from your team's codebase.
- Inline chat & refactors: Use the
CodyTaskcommand and Cody will refactor or adjust highlighted code snippets and replace them directly inline.
Cody for Neovim is considered experimental as we're still tweaking and fine-tuning the UX based on community feedback. If you have feedback, let us know in Discord.
Quality, performance, and onboarding improvements for Cody in JetBrains IDEs, now available in beta
The JetBrains plugin has been rewritten with a new architecture that significantly improves quality and performance for autocomplete and chat. Additionally, we have simplified onboarding so that users can start using the plugin with far fewer steps and closed some gaps in feature parity with the VS Code extension.
Cody for Neovim remains experimental as we continue to tweak the UX based on community feedback. If you have feedback, let us know in Discord.
Performance improvements and command updates for Cody in VS Code
The VS Code extension has received a similar upgrade as JetBrains, with under-the-hood changes that significantly improve quality and performance of all Cody features. Both chat and autocomplete are faster, and autocomplete offers higher quality suggestions with lower latency.
/test commands have also been updated:
/docnow adds docstrings directly to your code without you needing to copy & paste from the chat sidebar
/testnow better detects your testing framework, adds any dependency imports as needed, and includes the necessary stubs and test setup code
Choose between Anthropic and OpenAI models for Cody Enterprise
The AI field is advancing at a breakneck pace, and that includes the development of new LLMs and models to support specific use cases. We see new LLMs emerge nearly every week, tuned for performance across a host of benchmarks. To provide the best possible code AI experience, we believe Cody needs to be universal, with support for plugging in the latest-and-greatest LLMs.
Cody now supports OpenAI models, and enterprise Cody users can choose from these models to power Cody’s chat and commands features:
- OpenAI GPT-3.5 Turbo
- OpenAI GPT-4
- Anthropic Claude 2
Cody Enterprise users can bring their own LLM provider with Azure OpenAI and AWS Bedrock
Alongside support for OpenAI models, users now have more choice in how they run the LLM powering Cody. Cody now supports both Azure OpenAI and AWS Bedrock hosted LLM services. Users can run either service from within their company’s own secure cloud VPC and configure Cody to talk to the LLM service.
By default, Cody accesses LLMs directly via Anthropic & OpenAI’s respective APIs (with 0 retention on both inputs and outputs). By configuring Cody to use Azure OpenAI or Bedrock instead, users can securely route requests from Cody to their own Azure & AWS accounts, plus control their own LLM costs directly.Docs
Improved visibility into gitserver for faster debugging
Maintaining and debugging gitserver can be a challenge, especially for large instances with thousands of repositories. SSHing into a gitserver instance, looking through the logs, and piecing together what may be causing an issue is time consuming for users.
Sourcegraph admins can now enable the ability to see gitserver information and git history on a per-repository basis. From the Site Admin dashboard, users can now see:
- Which git commands recently ran on a repository
- When each repository was last re-cloned
- Gitserver instances' total and available disk space
Improved instance setup instructions for admins
The steps needed to fully configure a fresh new Sourcegraph installation were previously not clearly conveyed to instance admins, which often led to later confusion when features weren't working due to misconfigurations. We've introduced a new onboarding process, which prompts admins step-by-step as they set up a fresh instance. Admins are now walked through several critical setup steps including:
- Adding a license key
- Setting an external URL
- Configuring code hosts
- Setting user permissions
This change makes the setup process more straightforward for admins to get the best experience on their new instance.
Get started today
You can download the latest versions of the Cody IDE clients now. Code Search 5.2 will be available later today for download, and for Sourcegraph Cloud customers, your instance of Code Search will be automatically updated to the latest version.
And, if you'd like to learn more about Sourcegraph and today's release, join us for our livestream at 12pm PT where our Engineering and DevRel teams will talk about the latest new features.