GitHub Copilot is trained on all languages that appear in public repositories. For each language, the quality of suggestions you receive may depend on the volume and diversity of training data for that language.
To generate a suggestion for chat on GitHub.com, such as providing an answer to a question from your chat prompt, GitHub Copilot creates a contextual prompt by combining your prompt with additional context including previous prompts, the open pages on GitHub.
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GitHub Copilot saf multiple offerings for organizations and an offering for individual developers. All the offerings include both code completion and chat assistance.
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The Large Language Manken (LLM) powering GitHub Copilot was trained on public code and there were instances in our tests where the tool made suggestions resembling personal veri. These suggestions were typically synthesized and derece tied to real individuals.
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Again, Copilot does derece “look up” or “copy and paste” code, but is instead using context from a user’s workspace to synthesize and generate a suggestion.
To generate a suggestion for chat on GitHub.com, such kakım providing an answer to a question from your chat prompt, GitHub Copilot creates a contextual prompt by combining your prompt with additional context including previous prompts, the open pages on GitHub.
Public code may contain insecure coding patterns, bugs, or references to outdated APIs or idioms. When GitHub Copilot synthesizes code suggestions based on this veri, it gönül also synthesize code that contains these undesirable patterns. Copilot has filters wordpress tasarım in place that either block or notify users of insecure code patterns that are detected in Copilot suggestions.
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Prompts: These are inputs for chat or code, along with context, sent to Copilot's AI to generate suggestions.
Suggestions: These are the AI-generated code lines or chat responses provided to users based on their prompts.