Support running GitHub App using gunicorn, adjust Dockerfile accordingly

[okotek]

PR Type

Enhancement, Configuration changes

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Description

• Added a new Gunicorn configuration file (pr_agent/servers/gunicorn_config.py) with detailed settings for server socket, worker processes, server mechanics, logging, and process naming.
• Updated the Dockerfile to use Gunicorn for running the GitHub App, modifying the CMD instruction to start the app with Gunicorn and Uvicorn worker.
• Added gunicorn to the list of dependencies in requirements.txt.

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Changes walkthrough 📝

	Relevant files
Configuration changes	gunicorn_config.py Add Gunicorn configuration file for server settings            pr_agent/servers/gunicorn_config.py Added a new Gunicorn configuration file with detailed settings for server socket, worker processes, server mechanics, logging, and process naming. Configured environment variable handling for the number of workers. Set default values for various Gunicorn settings such as bind, backlog, timeout, and loglevel. +191/-0  Dockerfile Update Dockerfile to use Gunicorn for GitHub App                  docker/Dockerfile Updated the Dockerfile to use Gunicorn for running the GitHub App. Modified the CMD instruction to start the GitHub App with Gunicorn and Uvicorn worker. +1/-1
Dependencies	requirements.txt Add Gunicorn to project dependencies                                          requirements.txt Added gunicorn to the list of dependencies. +1/-0

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[codiumai-pr-agent-pro]

PR Reviewer Guide 🔍

⏱️ Estimated effort to review [1-5]	3
🏅 Score	85
🧪 Relevant tests	No
🔒 Security concerns	No
🔀 Multiple PR themes	Sub-PR theme: Add Gunicorn configuration for server settings Relevant files: pr_agent/servers/gunicorn_config.py
	Sub-PR theme: Update Docker configuration and dependencies for Gunicorn integration Relevant files: docker/Dockerfile requirements.txt
⚡ Key issues to review	Configuration Validation: Ensure that all configurations in gunicorn_config.py are appropriate and optimized for production use. Review the settings such as workers, worker_connections, timeout, and loglevel to ensure they meet the application's requirements.
	Environment Variables: The use of environment variables to set the number of workers (GUNICORN_WORKERS) is a good practice. However, ensure that these variables are documented and managed securely.

[codiumai-pr-agent-pro]

PR Code Suggestions ✨

Category	Suggestion	Score
Possible issue	Add a check to ensure the number of CPU cores is greater than zero before calculating the number of workers Consider adding a check to ensure that cores is greater than zero before calculating the number of workers. This will prevent potential issues if multiprocessing.cpu_count() returns zero. pr_agent/servers/gunicorn_config.py [77-78] cores = multiprocessing.cpu_count() -workers = cores * 2 + 1 +if cores > 0: + workers = cores * 2 + 1 +else: + workers = 1 # Fallback to a single worker if cores is zero Apply this suggestion Suggestion importance[1-10]: 8 Why: This suggestion correctly identifies a potential issue where multiprocessing.cpu_count() might return zero, which would lead to an invalid calculation for the number of workers. It's a significant improvement for robustness.	8
Enhancement	Make the bind address configurable via an environment variable The bind address should be configurable via an environment variable to allow for more flexibility in different deployment environments. pr_agent/servers/gunicorn_config.py [27] -bind = '0.0.0.0:3000' +bind = os.getenv('GUNICORN_BIND', '0.0.0.0:3000') Apply this suggestion Suggestion importance[1-10]: 7 Why: Making the bind address configurable via an environment variable is a good practice for flexibility in deployment environments. This suggestion correctly identifies the line and provides a suitable improvement.	7
Maintainability	Add a comment explaining the reason for the increased timeout value Consider adding a comment or a note explaining why the timeout value is set to 240 seconds, as this is significantly higher than the typical default of 30 seconds. pr_agent/servers/gunicorn_config.py [80] -timeout = 240 +timeout = 240 # Increased timeout to handle long-running requests Apply this suggestion Suggestion importance[1-10]: 6 Why: Adding a comment to explain why a non-standard configuration value was chosen (such as a high timeout value) is beneficial for maintainability. This suggestion is correct and improves code readability.	6

[okotek]

/improve

[codiumai-pr-agent-pro]

PR Code Suggestions ✨

Category	Suggestion	Score
Enhancement	Make the bind address configurable via an environment variable The bind address is hardcoded to 0.0.0.0:3000. Consider making this configurable via an environment variable to allow flexibility in different deployment environments. pr_agent/servers/gunicorn_config.py [27] -bind = '0.0.0.0:3000' +bind = os.getenv('GUNICORN_BIND', '0.0.0.0:3000') Apply this suggestion Suggestion importance[1-10]: 8 Why: Making the bind address configurable enhances flexibility for different deployment environments, which is crucial for a scalable application.	8
	Make the log level configurable via an environment variable The loglevel is set to info. For production environments, it might be beneficial to make this configurable via an environment variable to allow for more flexible logging configurations. pr_agent/servers/gunicorn_config.py [155] -loglevel = 'info' +loglevel = os.getenv('GUNICORN_LOGLEVEL', 'info') Apply this suggestion Suggestion importance[1-10]: 6 Why: Allowing configuration of the log level via an environment variable provides flexibility in logging, which is beneficial but not critical.	6
Possible issue	Add error handling for multiprocessing.cpu_count() to ensure robustness The workers calculation does not account for the possibility of multiprocessing.cpu_count() raising an exception. Consider adding a try-except block to handle this scenario gracefully. pr_agent/servers/gunicorn_config.py [77-78] -cores = multiprocessing.cpu_count() -workers = cores * 2 + 1 +try: + cores = multiprocessing.cpu_count() + workers = cores * 2 + 1 +except NotImplementedError: + workers = 3 # Fallback to a default value Apply this suggestion Suggestion importance[1-10]: 7 Why: Adding error handling for potential exceptions from multiprocessing.cpu_count() increases the robustness of the application, although it's not a critical issue.	7
Performance	Use the gunicorn executable directly in the Dockerfile CMD instruction for efficiency The CMD instruction for the github_app stage uses python -m gunicorn. It would be more efficient to use the gunicorn executable directly, which avoids the overhead of the Python interpreter. docker/Dockerfile [11] -CMD ["python", "-m", "gunicorn", "-k", "uvicorn.workers.UvicornWorker", "-c", "pr_agent/servers/gunicorn_config.py", "--forwarded-allow-ips", "*", "pr_agent.servers.github_app:app"] +CMD ["gunicorn", "-k", "uvicorn.workers.UvicornWorker", "-c", "pr_agent/servers/gunicorn_config.py", "--forwarded-allow-ips", "*", "pr_agent.servers.github_app:app"] Apply this suggestion Suggestion importance[1-10]: 6 Why: Using the gunicorn executable directly can slightly improve the efficiency by reducing the overhead of the Python interpreter, but the impact might be minimal.	6