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56 lines
2.4 KiB
Markdown
56 lines
2.4 KiB
Markdown
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## Overview - Local and global metadata injection with multi-stage analysis
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(1)
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PR-Agent initially retrieves for each PR the following data:
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- PR title and branch name
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- PR original description
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- Commit messages history
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- PR diff patches, in [hunk diff](https://loicpefferkorn.net/2014/02/diff-files-what-are-hunks-and-how-to-extract-them/) format
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- The entire content of the files that were modified in the PR
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In addition, PR-Agent is able to receive from the user additional data, like [`extra_instructions` and `best practices`](https://pr-agent-docs.codium.ai/tools/improve/#extra-instructions-and-best-practices) that can be used to enhance the PR analysis.
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(2)
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By default, the first command that PR-Agent executes is [`describe`](https://pr-agent-docs.codium.ai/tools/describe/), which generates three types of outputs:
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- PR Type (e.g. bug fix, feature, refactor, etc)
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- PR Description - a bullet points summary of the PR
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- Changes walkthrough - going file-by-file, PR-Agent generate a one-line summary and longer bullet points summary of the changes in the file
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These AI-generated outputs are now considered part of the PR metadata, and can be used in subsequent commands like `review` and `improve`.
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This effectively enables chain-of-thought analysis, without doing any additional API calls which will cost time and money.
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(3)
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For example, when generating code suggestions for different files, PR-Agent can inject the AI-generated file summary in the prompt:
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```
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## File: 'src/file1.py'
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### AI-generated file summary:
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- edited function `func1` that does X
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- Removed function `func2` that was not used
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- ....
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@@ ... @@ def func1():
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__new hunk__
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11 unchanged code line0 in the PR
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12 unchanged code line1 in the PR
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13 +new code line2 added in the PR
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14 unchanged code line3 in the PR
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__old hunk__
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unchanged code line0
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unchanged code line1
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-old code line2 removed in the PR
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unchanged code line3
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@@ ... @@ def func2():
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__new hunk__
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...
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__old hunk__
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...
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```
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(4) The entire PR files that were retrieved are used to expand and enhance the PR context (see [Dynamic Context](https://pr-agent-docs.codium.ai/core-abilities/dynamic-context/)).
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(5) All the metadata described above represent several level of analysis - from hunk level, to file level, to PR level, and enables PR-Agent AI models to generate more accurate and relevant suggestions.
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## Example result for prompt with metadata injection
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TBD
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