Sourcegraph Cody is an advanced AI coding assistant designed to accelerate software development by leveraging Sourcegraph's comprehensive code graph and Large Language Models (LLMs). Unlike standard chatbots, Cody understands your entire codebase, context, and coding standards, allowing it to answer complex queries, generate code, and refactor existing files with high accuracy. Available as an editor extension for VS Code and JetBrains or through the web, it supports tasks ranging from generating unit tests and documentation to fixing bugs via natural language commands. The platform emphasizes enterprise-grade security and scalability, ensuring data privacy while enhancing developer productivity across large and complex repositories.
Cody is an AI code assistant that uses Sourcegraph's code graph and LLMs to help developers write, fix, and understand code within their existing workflow.
Cody reads your entire codebase and uses Sourcegraph's code graph to understand the structure, context, and dependencies of your project.
Yes, Cody can generate unit tests for selected code snippets, taking into account the context of the rest of the codebase.
Sourcegraph emphasizes enterprise-grade security, stating that they do not retain user code or use it to train their base models.
Cody is available as an extension for VS Code and JetBrains IDEs (like IntelliJ and PyCharm), and also accessible via the web.
Fixup allows developers to highlight code and provide natural language instructions (e.g., 'refactor this function'), which Cody then executes directly in the file.
Yes, when connected to a Sourcegraph enterprise instance, Cody can fetch context from multiple repositories across an organization.
Absolutely. You can highlight a block of code and ask Cody to explain what it does, how it fits into the architecture, or identify potential bugs.
Yes, Cody is available for individual developers, often with a free tier or trial, though enterprise features have separate pricing.
By analyzing your existing codebase, Cody attempts to mirror your project's specific coding conventions, variable naming styles, and architectural patterns.
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