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37 lines
1.8 KiB
Python
37 lines
1.8 KiB
Python
from app.config import config
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from app.tool.python_execute import PythonExecute
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class NormalPythonExecute(PythonExecute):
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"""A tool for executing Python code with timeout and safety restrictions."""
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name: str = "python_execute"
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description: str = """Execute Python code for in-depth data analysis / data report(task conclusion) / other normal task without direct visualization."""
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parameters: dict = {
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"type": "object",
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"properties": {
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"code_type": {
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"description": "code type, data process / data report / others",
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"type": "string",
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"default": "process",
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"enum": ["process", "report", "others"],
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},
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"code": {
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"type": "string",
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"description": """Python code to execute.
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# Note
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1. The code should generate a comprehensive text-based report containing dataset overview, column details, basic statistics, derived metrics, timeseries comparisons, outliers, and key insights.
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2. Use print() for all outputs so the analysis (including sections like 'Dataset Overview' or 'Preprocessing Results') is clearly visible and save it also
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3. Save any report / processed files / each analysis result in worksapce directory: {directory}
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4. Data reports need to be content-rich, including your overall analysis process and corresponding data visualization.
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5. You can invode this tool step-by-step to do data analysis from summary to in-depth with data report saved also""".format(
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directory=config.workspace_root
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),
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},
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},
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"required": ["code"],
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}
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async def execute(self, code: str, code_type: str | None = None, timeout=5):
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return await super().execute(code, timeout)
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