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https://github.com/johndoe6345789/AutoMetabuilder.git
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johndoe6345789
877ba64de8
- Implement core components: CLI argument parsing, environment loading, GitHub service creation, and logging configuration. - Add support for OpenAI client setup and model resolution. - Develop SDLC context loader from GitHub and repository files. - Implement workflow context and engine builders. - Introduce major workflow packages: `game_tick_loop` and `contextual_iterative_loop`. - Update localization files with new package descriptions and labels. - Streamline web navigation by loading items from a dedicated JSON file.
38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
import subprocess
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import os
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import logging
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logger = logging.getLogger("autometabuilder.docker")
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def run_command_in_docker(image: str, command: str, volumes: dict = None, workdir: str = None):
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"""
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Run a command inside a Docker container.
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:param image: Docker image to use.
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:param command: Command to execute.
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:param volumes: Dictionary of volume mappings {host_path: container_path}.
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:param workdir: Working directory inside the container.
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:return: Standard output of the command.
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"""
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docker_command = ["docker", "run", "--rm"]
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if volumes:
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for host_path, container_path in volumes.items():
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docker_command.extend(["-v", f"{os.path.abspath(host_path)}:{container_path}"])
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if workdir:
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docker_command.extend(["-w", workdir])
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docker_command.append(image)
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docker_command.extend(["sh", "-c", command])
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logger.info(f"Executing in Docker ({image}): {command}")
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result = subprocess.run(docker_command, capture_output=True, text=True, check=False)
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output = result.stdout
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if result.stderr:
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output += "\n" + result.stderr
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logger.info(output)
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return output
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