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60 lines
1.7 KiB
60 lines
1.7 KiB
"""Pipeline control primitives for agent operation.
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Thin execution wrappers. The agent decides which stages to run and in what order.
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"""
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from __future__ import annotations
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import logging
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from typing import Any, Dict, List, Optional
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logger = logging.getLogger(__name__)
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def pipeline_run_stage(
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db_path: str,
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stage: str,
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window_id: Optional[str] = None,
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dry_run: bool = False,
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) -> Dict[str, Any]:
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"""Run a single pipeline stage.
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Args:
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db_path: Path to DuckDB database
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stage: Pipeline stage name (e.g. "ingestion", "svd", "similarity")
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window_id: Optional window identifier (e.g. "2024", "current_parliament")
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dry_run: If True, return planned actions without executing
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Returns:
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dict with status and metadata
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"""
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result = {
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"stage": stage,
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"window_id": window_id,
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"dry_run": dry_run,
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"status": "planned" if dry_run else "not_implemented",
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}
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if dry_run:
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return result
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# Actual execution would delegate to pipeline/run_pipeline.py
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# For now, mark as not implemented — the agent can still plan and diagnose
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logger.info("pipeline_run_stage: %s (dry_run=%s)", stage, dry_run)
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return result
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def pipeline_get_logs(
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db_path: str,
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stage: Optional[str] = None,
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lines: int = 50,
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) -> List[str]:
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"""Return recent log lines for a stage.
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Note: This is a placeholder. In a full implementation, this would read
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from a structured log store or log files.
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"""
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# Placeholder: return empty list
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# Real implementation would read from logging infrastructure
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logger.info("pipeline_get_logs requested for stage=%s lines=%d", stage, lines)
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return []
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