PM-pinou
100 lines
4.1 KiB
Python
100 lines
4.1 KiB
Python
"""Tool call dispatcher — maps tool names to handler functions."""
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import asyncio
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from ._helpers import _truncate_response
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from .load_data import _handle_load_data
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from .profile import _handle_profile_data
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from .filter import _handle_filter_data
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from .preprocess import _handle_preprocess_data
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from .clustering import _handle_run_clustering, _handle_filter_and_cluster
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from .evaluate import _handle_evaluate_clustering
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from .features import _handle_extract_features
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from .export import _handle_export_results
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from .entities import _handle_build_entity_profiles, _handle_compute_scores
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from .anomalies import _handle_detect_anomalies, _handle_visualize_anomalies
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from .diagnostics import (
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_handle_validate_data, _handle_explore_distributions, _handle_find_outliers,
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_handle_diagnose_clustering, _handle_compare_datasets,
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_handle_export_debug_sample, _handle_repair_schema,
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)
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from .analysis import (
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_handle_analyze_patterns, _handle_analyze_temporal, _handle_analyze_fft,
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_handle_analyze_tls_health, _handle_analyze_geo_distribution,
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_handle_analyze_entity_detail,
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)
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from .data_mgmt import _handle_list_datasets, _handle_drop_dataset, _handle_clone_dataset
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from .distance_matrix import _handle_compute_distance_matrix
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async def handle_call(name: str, arguments: dict) -> dict:
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"""Dispatch a tool call to the appropriate handler.
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Extracts the mandatory ``_timeout`` parameter (set by the LLM) from
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*arguments* and enforces it as an ``asyncio.wait_for`` deadline.
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Args:
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name: Tool name (must match one of the 30 tools).
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arguments: Tool-specific parameters, must include ``_timeout``.
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Returns:
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A JSON-serialisable dict.
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Raises:
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ValueError: If *name* is not a recognised tool.
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"""
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_handlers = {
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'load_data': _handle_load_data,
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'profile_data': _handle_profile_data,
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'filter_data': _handle_filter_data,
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'preprocess_data': _handle_preprocess_data,
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'run_clustering': _handle_run_clustering,
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'evaluate_clustering': _handle_evaluate_clustering,
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'extract_features': _handle_extract_features,
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'export_results': _handle_export_results,
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'list_datasets': _handle_list_datasets,
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'drop_dataset': _handle_drop_dataset,
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'clone_dataset': _handle_clone_dataset,
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'build_entity_profiles': _handle_build_entity_profiles,
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'compute_scores': _handle_compute_scores,
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'filter_and_cluster': _handle_filter_and_cluster,
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'detect_anomalies': _handle_detect_anomalies,
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'visualize_anomalies': _handle_visualize_anomalies,
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'validate_data': _handle_validate_data,
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'explore_distributions': _handle_explore_distributions,
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'find_outliers': _handle_find_outliers,
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'diagnose_clustering': _handle_diagnose_clustering,
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'compare_datasets': _handle_compare_datasets,
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'export_debug_sample': _handle_export_debug_sample,
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'repair_schema': _handle_repair_schema,
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'analyze_patterns': _handle_analyze_patterns,
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'analyze_temporal': _handle_analyze_temporal,
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'analyze_fft': _handle_analyze_fft,
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'analyze_tls_health': _handle_analyze_tls_health,
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'analyze_geo_distribution': _handle_analyze_geo_distribution,
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'analyze_entity_detail': _handle_analyze_entity_detail,
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'compute_distance_matrix': _handle_compute_distance_matrix,
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}
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handler = _handlers.get(name)
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if handler is None:
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raise ValueError(f"Unknown tool: '{name}'")
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# Extract mandatory _timeout from the LLM-provided arguments
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timeout = arguments.pop('_timeout', 0)
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cleaned_args = arguments # _timeout already removed by pop
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# Execute the handler with optional timeout
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if timeout and timeout > 0:
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try:
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result = await asyncio.wait_for(
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handler(**cleaned_args),
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timeout=timeout,
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)
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except asyncio.TimeoutError:
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result = {'error': f'工具 {name} 执行超时 ({timeout}秒)'}
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else:
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result = await handler(**cleaned_args)
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# Always ensure truncated key exists
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if 'truncated' not in result:
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result['truncated'] = False
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return _truncate_response(result)
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