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# Improving GPT-4's codebase understanding with ctags
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While GPT-4 excels at coding tasks, it struggles with modifying
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code in larger code bases.
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Many common
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types of code changes require knowledge and context from multiple files
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scattered throughout a large repo.
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This is a challenge for GPT-4, which can only fit 8k-tokens
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worth of code in its context window.
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GPT-4 is extremely useful for "self-contained" coding tasks,
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like generating new code or modifying a pure function without dependencies.
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But it's difficult to use GPT-4 to modify code with dependencies
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that are scattered across many files of a codebase.
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To modify such code, GPT needs to see all of these dependencies.
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And depending on the assigned coding task, it may not be obvious
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how to even determine which parts of the repo are relevent a priori.
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Further, all of this context needs to fit within GPT-4's 8k-token
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context window.
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To address this issue, `aider` has
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a new experimental feature that utilizes `ctags` to provide
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