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eba892d969
* feat: Add awk regex generator custom commands * feat: Add include and exlude for file pattern filter support
33 lines
2.0 KiB
Plaintext
33 lines
2.0 KiB
Plaintext
# Description: Environment variables for Local Code Review Only
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# Usage: Copy this file to .env and replace the values with your own
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# WARNING: Do not commit the actual .env file to version control as it may contain sensitive information.
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# CHAT_TOKEN: Obtain this token from your Deepseek account settings
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CHAT_TOKEN='Your Deepseek API token'
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# GITHUB_TOKEN: Your GitHub API token to query GitHub PR changes
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# Generate this token from your GitHub account with the necessary permissions
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GITHUB_TOKEN='Your GitHub API token'
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# MAX_LENGTH: The maximum length of the content for review, 0 means no limit.
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MAX_LENGTH='0'
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# The comma separated file patterns to include in the code review.
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INCLUDE_PATTERNS=''
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# The comma separated file patterns to exclude in the code review.
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EXCLUDE_PATTERNS='pnpm-lock.yaml,package-lock.json,*.lock'
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# Default GitHub repository name to fetch PR changes
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DEFAULT_GITHUB_REPO='hustcer/deepseek-review'
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# Default local repository absolute path to query commit changes
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DEFAULT_LOCAL_REPO='/Users/hustcer/deepseek-review'
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# BASE_URL: Deepseek API base URL
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# Replace with the actual API base URL if different
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BASE_URL='https://api.deepseek.ai'
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# USER_PROMPT: User prompt message, customize as needed
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# OR a yaml file path with key name specified to load the prompt message,
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# e.g., USER_PROMPT='/User/abc/prompts.yaml:usr-prompt'
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# Will load the prompt message from the 'usr-prompt' key in the 'prompts.yaml' file
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USER_PROMPT='Please review the following code changes'
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# SYSTEM_PROMPT: System prompt message, customize as needed
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# OR a yaml file path with key name specified to load the prompt message,
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# e.g., SYSTEM_PROMPT='/User/abc/prompts.yaml:sys-prompt'
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# Will load the prompt message from the 'sys-prompt' key in the 'prompts.yaml' file
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SYSTEM_PROMPT='You are a professional code review assistant responsible for analyzing code changes in GitHub Pull Requests. Identify potential issues such as code style violations, logical errors, security vulnerabilities, and provide improvement suggestions. Clearly list the problems and recommendations in a concise manner.'
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