665 lines
34 KiB
Python
665 lines
34 KiB
Python
"""MCP domain dispatch reuses Server repositories and services, never an HTTP loopback."""
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import asyncio
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import math
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from contextlib import nullcontext
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from typing import Any
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from pydantic import BaseModel
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from app.mcp.scope import QueryScope
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from app.mcp.catalog import QueryTool, TOOLS
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from app.mcp.models import BoundContext
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from datetime import datetime, timezone
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from uuid import uuid4
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from fastapi import HTTPException
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from fastapi.encoders import jsonable_encoder
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from app.core.config import settings
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from app.auth.permissions import permissions_for_context
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from app.infra.db.postgresql import read_queries as reads
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from app.infra.db.postgresql.spatial_queries import nearby_elements
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from app.infra.db.postgresql.analysis import AnalysisRepository
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from app.infra.db.postgresql.gis_attributes import GisAttributeRepository
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from app.infra.db.postgresql.network_settings import NetworkSettingsRepository
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from app.infra.db.postgresql.operational_tasks import OperationalTaskRepository
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from app.services.operational_tasks import OperationalTaskService
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from app.services.burst_location_demo import location_demo_result
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from app.mcp.models import QueryResult, PageInfo
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from app.mcp.scenario_service import SCENARIO_TOOLS
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from app.mcp.work_order_skills import read_work_order_skill
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def finite_data(value: Any) -> tuple[Any, int]:
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"""JSON cannot represent infinity/NaN; preserve the gap as null with provenance."""
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if isinstance(value, float) and not math.isfinite(value):
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return None, 1
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count = 0
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if isinstance(value, dict):
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result = {}
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for key, item in value.items():
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result[key], replaced = finite_data(item)
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count += replaced
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return result, count
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if isinstance(value, list):
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result = []
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for item in value:
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clean, replaced = finite_data(item)
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result.append(clean)
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count += replaced
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return result, count
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return value, 0
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def task_service(scope: QueryScope) -> OperationalTaskService:
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return OperationalTaskService(
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OperationalTaskRepository(scope.connection, scope.project.project_id),
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scope.project,
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set(permissions_for_context(scope.project)),
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execution_scope=settings.operational_task_execution_scope,
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)
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def page_result(rows, args):
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has_more = len(rows) > args.limit
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return (
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rows[: args.limit],
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PageInfo(limit=args.limit, offset=args.offset, total=None, has_more=has_more),
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has_more,
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)
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async def authorize_query(
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scope: QueryScope, binding: BoundContext, tool: QueryTool, args: BaseModel
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) -> None:
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replay_context = getattr(binding, "replay_context", None)
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if tool.name not in binding.tool_cap:
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raise HTTPException(403, "Query is outside the captured tool catalog")
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if replay_context:
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from app.services.scada_replay_queries import check_replay_window
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allowed = {"get_task_context", "get_task_evidence", "list_scada_devices", "get_scada_device",
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"query_scada_readings", "get_network_schema", "run_burst_location", "run_contaminant_source_trace",
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"get_element_properties", "list_elements", "query_nearby_elements", "get_network_options",
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"get_node_connections", "get_element_gis_properties", "query_network_extent",
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"list_regions", "get_region", "get_region_nodes",
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"analyze_valve_isolation", "generate_node_coverage", "run_burst_simulation", "run_contaminant_simulation", "analyze_flushing",
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"get_calculation_job", "get_calculation_result", "list_calculation_jobs"}
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if tool.name not in allowed:
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raise HTTPException(403, "回放调查仅开放冻结 SCADA、资产、拓扑分析及指定模型情景；时序观测请使用 query_scada_readings")
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if tool.name == "run_burst_simulation":
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if not args.include_impact_coverage:
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raise HTTPException(422, "回放爆管情景必须启用影响覆盖，按当前模型估计并保存同刻在线基线")
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check_replay_window(replay_context, args.start_time, args.start_time)
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if tool.name == "run_contaminant_simulation":
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if not args.include_impact_coverage:
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raise HTTPException(422, "回放污染情景必须启用影响覆盖，按当前模型估计传播范围")
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check_replay_window(replay_context, args.start_time, args.start_time)
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if tool.name == "analyze_flushing":
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check_replay_window(replay_context, args.start_time, args.start_time)
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if tool.name == "query_scada_readings":
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check_replay_window(replay_context, args.start, args.end)
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if tool.name == "run_contaminant_source_trace":
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check_replay_window(replay_context, args.start, args.end)
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if tool.name == "run_burst_location":
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if args.data_source != "monitoring" or args.scada_normal_start is None or args.scada_normal_end is None:
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raise HTTPException(422, "回放定位只支持显式异常窗和正常对照窗的 monitoring 输入")
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check_replay_window(replay_context, args.scada_burst_start, args.scada_burst_end)
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check_replay_window(replay_context, args.scada_normal_start, args.scada_normal_end)
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permissions = permissions_for_context(scope.project)
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if tool.mutating:
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if binding.purpose != "ordinary_chat" or binding.task_id is not None or scope.project.project_role != "member":
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raise HTTPException(403, "Writes require a project member's ordinary interactive chat")
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required = {tool.permission}
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if tool.name == "save_simulation_scenario":
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required.add("scada.view")
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if not required.issubset(permissions) or not required.issubset(binding.permission_cap):
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raise HTTPException(403, "Write and input data permissions are required")
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if tool.computation:
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if tool.name == "optimize_sensor_placement" and scope.project.project_role != "member":
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raise HTTPException(403, "Sensor placement requires project member access")
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if binding.purpose == "task_reader":
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raise HTTPException(403, "Read-only task agents cannot start calculations")
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required = {tool.permission}
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if tool.name in SCENARIO_TOOLS:
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required.add("scada.view")
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if tool.name == "run_burst_simulation" and args.include_impact_coverage:
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required.add("simulation.view")
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if tool.name in {"run_burst_detection", "run_burst_location", "run_leakage_identification"}:
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required.add("simulation.view" if getattr(args, "data_source", "monitoring") == "simulation" else "scada.view")
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if not required.issubset(permissions) or not required.issubset(binding.permission_cap):
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raise HTTPException(403, "Calculation and input data permissions are required")
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permission = (
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"scada.view"
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if tool.name == "get_network_schema" and args.kind == "scada-device"
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else tool.permission
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)
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if tool.task_only and binding.task_id is None:
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raise HTTPException(403, "This query requires a bound task")
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granted = permission in permissions and permission in binding.permission_cap
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source = {
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"list_scada_devices": "scada_devices",
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"get_scada_device": "scada_devices",
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"query_scada_readings": "scada_readings",
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"query_element_history": "scada_readings",
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"get_workbench_runtime": "workbench_runtime",
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}.get(tool.name)
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if tool.name == "query_peripheral_data":
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source = args.source
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if not granted and binding.task_id and source in binding.task_scope_cap:
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async with scope.connection.transaction():
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granted = await task_service(scope).can_read_source(binding.task_id, source)
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if granted and tool.name == "query_scada_readings" and args.device_ids is None:
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granted = (
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"scada_devices" in binding.task_scope_cap
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and await task_service(scope).can_read_source(binding.task_id, "scada_devices")
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)
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if not granted:
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raise HTTPException(403, "Data source permission is required")
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if tool.name == "run_burst_location" and args.burst_leakage is None:
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from app.services.burst_location_demo import is_location_demo
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if not is_location_demo(getattr(scope.project, "project_code", None), args):
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raise HTTPException(422, "水力定位需要有依据的 burst_leakage；仅已开放的候选定位路径可省略漏量")
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if (
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tool.name == "query_element_history"
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and args.mode != "observed"
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and (
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"simulation.view" not in permissions
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or "simulation.view" not in binding.permission_cap
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)
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):
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raise HTTPException(403, "Model comparison permission is required")
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async def execute_query(
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scope: QueryScope,
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binding: BoundContext,
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tool: QueryTool,
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args: BaseModel,
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*,
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full_snapshot: bool = False,
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) -> QueryResult:
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await authorize_query(scope, binding, tool, args)
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if tool.name in {"get_calculation_job", "get_calculation_result", "cancel_calculation_job", "list_calculation_jobs"}:
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from app.mcp.calculation_jobs import read_calculation_job
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return await read_calculation_job(scope, binding, tool, args)
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if tool.mutating:
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from app.mcp.mutation_service import execute_mutation
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return await execute_mutation(scope, binding, tool, args)
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from app.mcp.extended_service import EXTENDED_READ_TOOLS, execute_extended
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if tool.name in EXTENDED_READ_TOOLS:
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return await execute_extended(scope, binding, tool, args)
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name = tool.name
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conn = scope.connection
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page = None
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truncated = False
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units = {}
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origin = "system_data"
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gaps = []
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source_ref = "mcp:" + str(uuid4())
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evidence_id = None
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replay_context = getattr(binding, "replay_context", None)
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if name == "run_contaminant_source_trace":
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from app.services.contaminant_source_trace import trace_contaminant_source
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data = {"parameters": args.model_dump(mode="json", exclude={"context_handle"}),
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"result": await trace_contaminant_source(conn, args)}
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origin = "synthetic"
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if data["result"]["located_node"] is None:
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gaps.append(data["result"]["notice"])
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elif name == "query_scada_readings" and args.device_ids is None:
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from app.mcp.scada_readings import read_complete_scada
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data, units, gaps, origin = await read_complete_scada(scope, binding, args)
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elif name == "query_scada_readings" and replay_context:
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from app.services.scada_replay_queries import replay_snapshot_rows
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rows = await replay_snapshot_rows(conn, scope.project.project_id, replay_context,
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args.device_ids, args.start, args.end, args.limit + 1, args.offset)
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data, page, truncated = page_result(rows, args)
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origin = "synthetic"
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elif name == "run_burst_simulation" and replay_context:
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from app.mcp.analysis_service import calculate_replay_burst_simulation
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await conn.commit()
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async with scope.simulation_routing():
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result = await calculate_replay_burst_simulation(
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args, network=scope.project.project_code, username=scope.user.username,
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)
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data = {"parameters": args.model_dump(mode="json", exclude={"context_handle"}), "result": result}
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origin = "synthetic"
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gaps = ["回放爆管影响为当前模型的独立假设情景，不读取实时SCADA；同刻在线模拟为计算时读取的模型参考，非冻结观测或历史模型重建。未来模拟样本仅为预测。"]
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elif name == "run_contaminant_simulation" and replay_context:
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from app.mcp.analysis_service import calculate_replay_contaminant_simulation
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await conn.commit()
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async with scope.simulation_routing():
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result = await calculate_replay_contaminant_simulation(
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args, network=scope.project.project_code, username=scope.user.username,
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)
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data = {"parameters": args.model_dump(mode="json", exclude={"context_handle"}), "result": result}
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origin = "synthetic"
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gaps = ["回放污染传播为当前模型的独立假设情景，不读取实时SCADA，不代表冻结观测或历史模型重建。未来模拟样本仅为预测；浓度阈值仅用于情景展示，不是饮用水安全限值。"]
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elif name == "analyze_flushing" and replay_context:
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from app.mcp.analysis_service import calculate_replay_flushing
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await conn.commit()
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async with scope.simulation_routing():
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result = await calculate_replay_flushing(
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args, network=scope.project.project_code, username=scope.user.username,
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)
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data = {"parameters": args.model_dump(mode="json", exclude={"context_handle"}), "result": result}
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origin = "synthetic"
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gaps = ["回放冲洗为当前模型的独立水力情景，不读取实时SCADA，不继承上次模拟；未来模拟样本仅为预测，不验证污染清除、水质合格或现场操作。"]
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elif name == "run_burst_location" and replay_context:
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from app.mcp.analysis_service import calculate_replay_burst_location
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from app.services.scada_replay_queries import replay_burst_location_inputs
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parameters = await replay_burst_location_inputs(
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conn, scope.project.project_id, replay_context, args,
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)
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result = await location_demo_result(conn, scope.project.project_code, args)
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await conn.commit()
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if result is None:
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async with scope.simulation_routing():
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result = await calculate_replay_burst_location(
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parameters,
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network=scope.project.project_code,
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username=scope.user.username,
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)
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data = {
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"parameters": args.model_dump(mode="json", exclude={"context_handle"}),
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"result": result,
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}
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origin = "synthetic"
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gaps = [result["notice"]] if result.get("notice") else []
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elif name == "run_burst_location" and (
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demo_result := await location_demo_result(conn, scope.project.project_code, args)
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) is not None:
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data = {"parameters": args.model_dump(mode="json", exclude={"context_handle"}),
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"result": demo_result}
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origin = "synthetic"
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gaps = [demo_result["notice"]] if demo_result.get("notice") else []
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elif tool.computation:
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from app.mcp.analysis_service import TIMESCALE_CALCULATIONS, calculate
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# Context/receipt reads may have started an implicit transaction. Release
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# it before potentially long CPU/IO work; evidence uses a new transaction.
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await conn.commit()
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async with (
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scope.simulation_routing()
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if name in TIMESCALE_CALCULATIONS
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else nullcontext()
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):
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data = await calculate(
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name, args, network=scope.project.project_code,
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username=scope.user.username,
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)
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data = {
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"parameters": args.model_dump(mode="json", exclude={"context_handle"}),
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"result": data,
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}
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gaps = [{
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"run_simulation": "Online hydraulic recalculation updated the realtime baseline; results cover requested elements only, not observed SCADA data. No standalone analysis run was saved.",
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"run_contaminant_simulation": "Forward model simulation for an assumed source, not source inversion or observed contamination. Selected series only; opt-in impact coverage uses all native nodes over the simulation window, with an explicit display threshold and existing model initial quality/reactions, not a drinking-water safety limit.",
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"analyze_valve_closure": "Simulated hydraulic impact for requested elements only; no physical valves were operated.",
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"analyze_flushing": "Simulated flushing hydraulics only; no field action or water-quality clearance was verified.",
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"analyze_pressure_regulation": "Evaluation of a supplied pump schedule, not automatic optimization or device control; requested elements only.",
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"optimize_sensor_placement": "Candidate pressure monitoring locations, not a saved deployment scheme or a guarantee of contaminant source observability.",
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"run_leakage_identification": "DMA leakage estimates depend on the total leakage constraint and aligned model/SCADA time; they do not confirm an exact leak location.",
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"run_burst_detection": "Pressure anomalies alone do not confirm a burst or locate a pipe.",
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"run_burst_location": "Candidate ranking depends on the leakage assumption, model and sensor coverage; field confirmation is required.",
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"analyze_valve_isolation": "Topology-only isolation advice; valve operability, hydraulic impact and field actions are not verified or executed.",
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"generate_node_coverage": "Derived node coverage for display only; geometry does not establish a fault, contamination, outage or service boundary. Missing GIS positions are reported separately.",
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"calculate_demand_allocation": "Pipe-length-weighted allocation only; model demands were not modified. Units follow the current model.",
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"run_burst_simulation": "Forward hydraulic simulation for assumed orifice areas; selected series only. Opt-in impact coverage compares all native nodes at the start time with existing online results, using current model settings for baseline units. This is an estimated pre-intervention range, not a confirmed outage or historical model reconstruction.",
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}[name]]
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if name == "calculate_demand_allocation":
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truncated = data["result"]["has_more"] or args.offset > 0
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page = PageInfo(limit=args.limit, offset=args.offset, total=data["result"]["total"], has_more=data["result"]["has_more"])
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if getattr(args, "data_source", None) == "simulation":
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gaps.append("Input is an existing analysis run and model baseline, not observed SCADA data.")
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elif name == "query_nearby_elements":
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rows = await nearby_elements(
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conn, args.element_type, center=args.center, radius_m=args.radius_m,
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limit=args.limit + 1, offset=args.offset,
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)
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items, page, truncated = page_result(rows, args)
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truncated = truncated or args.offset > 0
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data = {
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"source": "model_network", "element_type": args.element_type,
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"center": list(args.center), "center_crs": "EPSG:4326",
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"radius_m": args.radius_m, "distance_method": "WGS84_spheroid",
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"items": items,
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}
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units = {"distance_m": "m", "radius_m": "m"}
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gaps = ["Spatial proximity does not establish hydraulic connectivity or a supply relationship"]
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elif name in {"get_element_properties", "list_elements"}:
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rows = await reads.asset_rows(
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conn,
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args.element_type,
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element_id=getattr(args, "element_id", None),
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limit=getattr(args, "limit", 1) + 1,
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offset=getattr(args, "offset", 0),
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)
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if name == "get_element_properties":
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if not rows:
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raise HTTPException(404, "Element was not found")
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data = rows[0]
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else:
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data, page, truncated = page_result(rows, args)
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elif name in {"list_scada_devices", "get_scada_device"}:
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rows = await reads.scada_devices(
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conn,
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device_id=getattr(args, "device_id", None),
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limit=getattr(args, "limit", 1) + 1,
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offset=getattr(args, "offset", 0),
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)
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if name == "get_scada_device":
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if not rows:
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raise HTTPException(404, "SCADA device was not found")
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data = rows[0]
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else:
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data, page, truncated = page_result(rows, args)
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elif name == "get_network_schema":
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from app.services import tjnetwork
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mapping = {
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"option": "get_option_v3_schema",
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"scada-device": "get_scada_info_schema",
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"pump-energy": "get_pump_energy_schema",
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}
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function = getattr(
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tjnetwork, mapping.get(args.kind, "get_" + args.kind.replace("-", "_") + "_schema")
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)
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data = await asyncio.to_thread(function, scope.project.project_code)
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elif name == "get_network_options":
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if args.kind == "pump-energy":
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rows = await reads.read_rows(
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conn,
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"SELECT price,pattern_id AS pattern,efficiency_curve_id AS effic FROM network.pump_energy_settings WHERE pump_id=%s",
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(args.pump_id,),
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)
|
|
data = {"pump": args.pump_id, "price": None, "pattern": None, "effic": None}
|
|
if rows:
|
|
data.update(rows[0])
|
|
else:
|
|
table = {
|
|
"time": "time_settings",
|
|
"energy": "energy_settings",
|
|
"network": "simulation_settings",
|
|
}[args.kind]
|
|
where = " WHERE engine_version='v3'" if args.kind == "network" else ""
|
|
rows = await reads.read_rows(
|
|
conn,
|
|
"SELECT key,value FROM network."
|
|
+ table
|
|
+ where
|
|
+ " ORDER BY key LIMIT 501",
|
|
)
|
|
data = {str(row["key"]): str(row["value"]) for row in rows[:500]}
|
|
truncated = len(rows) > 500
|
|
elif name in {
|
|
"query_scada_readings",
|
|
"query_model_baseline_series",
|
|
"get_model_baseline_at_time",
|
|
"query_model_baseline_field",
|
|
"query_analysis_series",
|
|
"query_analysis_values",
|
|
}:
|
|
source = (
|
|
"scada"
|
|
if name == "query_scada_readings"
|
|
else "analysis"
|
|
if name.startswith("query_analysis")
|
|
else "realtime"
|
|
)
|
|
ids = (
|
|
getattr(args, "device_ids", None)
|
|
or getattr(args, "element_ids", None)
|
|
or ([args.element_id] if hasattr(args, "element_id") else [])
|
|
)
|
|
async with scope.timescale() as ts:
|
|
rows = await reads.series_rows(
|
|
ts,
|
|
source=source,
|
|
element_type=getattr(args, "element_type", "junction"),
|
|
ids=ids,
|
|
start=getattr(args, "start", None),
|
|
end=getattr(args, "end", None),
|
|
time=getattr(args, "time", None),
|
|
field=getattr(args, "field", None),
|
|
run_id=getattr(args, "run_id", None),
|
|
limit=getattr(args, "limit", 1) + 1,
|
|
offset=getattr(args, "offset", 0),
|
|
)
|
|
if name == "get_model_baseline_at_time":
|
|
data = rows[:1]
|
|
else:
|
|
data, page, truncated = page_result(rows, args)
|
|
if source != "scada":
|
|
async with conn.transaction():
|
|
units = await NetworkSettingsRepository.get_result_units(conn)
|
|
if source == "analysis":
|
|
run = await AnalysisRepository.get_run(conn, args.run_id)
|
|
if not run:
|
|
raise HTTPException(404, "Analysis run was not found")
|
|
recorded = (run.get("parameters") or {}).get("result_units")
|
|
if isinstance(recorded, dict):
|
|
units = recorded
|
|
else:
|
|
gaps.append(
|
|
"Analysis units inferred from current network settings"
|
|
)
|
|
if hasattr(args, "field") and args.field not in units:
|
|
gaps.append(f"Unit metadata is unavailable for field {args.field}")
|
|
else:
|
|
# Keep the selected field in durable evidence; `value` alone cannot
|
|
# distinguish raw observations from cleaned observations.
|
|
data = [{**row, args.field: row["value"]} if "value" in row else row for row in data]
|
|
metadata = [
|
|
r
|
|
for device in ids
|
|
for r in await reads.scada_devices(conn, device_id=device, limit=1)
|
|
]
|
|
units = {
|
|
r["device_id"]: r["measurement_unit"]
|
|
for r in metadata
|
|
if r["device_id"] in ids
|
|
}
|
|
elif name in {"list_analysis_runs", "get_analysis_run", "list_analysis_results"}:
|
|
async with conn.transaction():
|
|
if name == "get_analysis_run":
|
|
data = await AnalysisRepository.get_run(conn, args.run_id)
|
|
if not data:
|
|
raise HTTPException(404, "Analysis run was not found")
|
|
elif name == "list_analysis_runs":
|
|
# Fetch one additional row with the repository's supported summary-page bound.
|
|
rows = await AnalysisRepository.list_run_summaries(
|
|
conn, limit=args.limit + 1, offset=args.offset
|
|
)
|
|
data, page, truncated = page_result(rows, args)
|
|
else:
|
|
rows = await AnalysisRepository.list_results(
|
|
conn,
|
|
args.run_id,
|
|
args.result_type,
|
|
limit=args.limit,
|
|
lookahead=True,
|
|
offset=args.offset,
|
|
)
|
|
data, page, truncated = page_result(rows, args)
|
|
elif name in {"list_sensor_placement_runs", "get_sensor_placement_run"}:
|
|
rows = await reads.sensor_runs(
|
|
conn,
|
|
run_id=getattr(args, "run_id", None),
|
|
limit=getattr(args, "limit", 1) + 1,
|
|
offset=getattr(args, "offset", 0),
|
|
)
|
|
if name == "get_sensor_placement_run":
|
|
if not rows:
|
|
raise HTTPException(404, "Sensor placement run was not found")
|
|
data = rows[0]
|
|
else:
|
|
data, page, truncated = page_result(rows, args)
|
|
elif name == "query_element_history":
|
|
from app.domain.schemas.timeseries_history import ElementHistoryQuery
|
|
from app.services.timeseries_history import TimeseriesHistoryService
|
|
|
|
query = ElementHistoryQuery(
|
|
start_time=args.start,
|
|
end_time=args.end,
|
|
mode=args.mode,
|
|
run_id=args.run_id,
|
|
elements=[e.model_dump() for e in args.elements],
|
|
)
|
|
async with scope.timescale() as ts, conn.transaction(), ts.transaction():
|
|
result = await TimeseriesHistoryService.query(
|
|
ts, conn, query, row_limit=args.limit, row_offset=args.offset
|
|
)
|
|
data = result.model_dump(mode="json")
|
|
truncated = result.truncated
|
|
page = PageInfo(limit=args.limit, offset=args.offset, has_more=truncated)
|
|
truncated = truncated or args.offset > 0
|
|
elif name in {"get_element_gis_properties", "get_source_gis_properties"}:
|
|
async with conn.transaction():
|
|
if name == "get_element_gis_properties":
|
|
data = await GisAttributeRepository.list_element_groups(
|
|
conn, args.element_type, args.element_id
|
|
)
|
|
else:
|
|
data = await GisAttributeRepository.get_source_feature_group(
|
|
conn, args.layer_key, args.source_fid
|
|
)
|
|
if data is None:
|
|
raise HTTPException(404, "Source GIS feature was not found")
|
|
elif name == "get_task_context":
|
|
if args.section in {"summary", "skill"}:
|
|
data = await reads.task_context_summary(conn, project_id=binding.project_id,
|
|
task_id=binding.task_id, report_revision=args.report_revision)
|
|
skill = read_work_order_skill(
|
|
data.get("task", {}).get("workflow"), include_content=args.section == "skill",
|
|
replay_context=replay_context,
|
|
)
|
|
if args.section == "skill":
|
|
data = {"section": "skill", "skill": skill}
|
|
else:
|
|
data["handling_skill"] = skill
|
|
data["display_time_zone"] = "Asia/Shanghai"
|
|
data["approved_data_scopes"] = binding.task_scope_cap
|
|
data["bound_run_id"] = str(binding.run_id) if binding.run_id else None
|
|
data["available_sections"] = ["task", "report", "evidence", "actions", "progress", "access_requests", "plan", "run", "skill", "questions"]
|
|
truncated = True
|
|
gaps.append("Task context is a bounded summary; use section, data_path, limit and offset for detail. Previews are not complete reports.")
|
|
if skill.get("name") == "water-pollution-event":
|
|
data["source_trace_capability"] = {
|
|
"available": "run_contaminant_source_trace" in binding.tool_cap,
|
|
"tool": "run_contaminant_source_trace",
|
|
"algorithm_status": "provisional",
|
|
"required_inputs": ["candidate_node_ids", "start", "end"],
|
|
"next_steps": ["present_node", "interim_report", "propose_task_action", "run_contaminant_simulation",
|
|
"source_control", "analyze_valve_isolation", "generate_node_coverage",
|
|
"analyze_flushing", "field_feedback", "clearance_verification", "report"],
|
|
"work_order_wait_blocks_analysis": False,
|
|
"simulation_parameters": {"include_impact_coverage": True},
|
|
}
|
|
if (skill.get("name") == "scada-anomaly" and replay_context
|
|
and "run_burst_location" in binding.tool_cap):
|
|
from app.services.burst_location_demo import location_demo_context
|
|
|
|
data["location_capability"] = location_demo_context(
|
|
getattr(scope.project, "project_code", None), replay_context,
|
|
)
|
|
else:
|
|
projection = await reads.task_context_page(conn, project_id=binding.project_id, task_id=binding.task_id,
|
|
section=args.section, report_revision=args.report_revision, data_path=args.data_path, limit=args.limit, offset=args.offset)
|
|
total = projection["total"]
|
|
if args.section in {"evidence", "actions", "access_requests", "questions"} and not args.data_path:
|
|
total = projection["snapshot_metadata"].get("total", total)
|
|
if projection["value_type"] in {"array", "object", "string"}:
|
|
page = PageInfo(limit=args.limit, offset=args.offset, total=total, has_more=args.offset + args.limit < total)
|
|
elif args.offset:
|
|
raise HTTPException(422, "Scalar task detail cannot use an offset")
|
|
truncated = bool(projection.get("nested") or args.offset or page and page.has_more)
|
|
data = {"section": args.section, "selected_path": args.data_path, "value": projection["value"], "metadata": projection["snapshot_metadata"]}
|
|
if projection.get("nested"):
|
|
gaps.append("Nested values have data_path descriptors; select a descriptor path for its values")
|
|
elif name == "get_task_evidence":
|
|
projection = await reads.evidence_page(
|
|
conn, project_id=scope.project.project_id, task_id=binding.task_id,
|
|
evidence_id=args.evidence_id, data_path=args.data_path,
|
|
limit=args.limit, offset=args.offset, mcp_sources=list(TOOLS),
|
|
full_snapshot=full_snapshot,
|
|
)
|
|
document = projection if full_snapshot else projection["snapshot_metadata"]
|
|
origin = document["origin"]
|
|
source_ref = document["source_ref"]
|
|
evidence_id = args.evidence_id
|
|
truncated = document.get("truncated", False)
|
|
if full_snapshot:
|
|
data = document
|
|
else:
|
|
selected = projection["value"]
|
|
if projection["value_type"] in {"array", "object", "string"}:
|
|
total = projection["total"]
|
|
page = PageInfo(
|
|
limit=args.limit,
|
|
offset=args.offset,
|
|
total=total,
|
|
has_more=args.offset + args.limit < total,
|
|
)
|
|
truncated = truncated or page.has_more or args.offset > 0
|
|
elif args.offset:
|
|
raise HTTPException(422, "Scalar evidence cannot use an offset")
|
|
if projection.get("nested"):
|
|
truncated = True
|
|
gaps.append(
|
|
"Nested collections have data_path descriptors; query a descriptor path for their values"
|
|
)
|
|
data = {
|
|
"snapshot_metadata": document,
|
|
"query_metadata": projection["query_metadata"],
|
|
"selected_path": args.data_path,
|
|
"value": selected,
|
|
}
|
|
elif name == "get_workbench_runtime":
|
|
from app.services.workbench_runtime import read_workbench_runtime
|
|
|
|
data = (await read_workbench_runtime(scope.project, conn)).model_dump(
|
|
mode="json"
|
|
)
|
|
elif name == "query_peripheral_data":
|
|
from app.mcp.peripheral import read_peripheral_query
|
|
|
|
snapshot = await read_peripheral_query(scope, args)
|
|
data = snapshot.data
|
|
origin = snapshot.origin
|
|
truncated = snapshot.truncated
|
|
else:
|
|
raise ValueError("query handler is not registered")
|
|
window = (
|
|
{"start": args.start, "end": args.end}
|
|
if hasattr(args, "start") and args.start is not None
|
|
else None
|
|
)
|
|
data, nonfinite = finite_data(jsonable_encoder(data))
|
|
semantics = (
|
|
"comparison"
|
|
if name == "query_element_history" and args.mode != "observed"
|
|
else tool.semantics
|
|
)
|
|
return QueryResult(
|
|
source=name,
|
|
source_ref=source_ref,
|
|
evidence_id=evidence_id,
|
|
queried_at=datetime.now(timezone.utc),
|
|
semantics=semantics,
|
|
data=data,
|
|
data_gaps=gaps
|
|
+ (
|
|
[f"{nonfinite} non-finite numeric values were returned as null"]
|
|
if nonfinite
|
|
else []
|
|
),
|
|
page=page,
|
|
window=window,
|
|
units=units,
|
|
truncated=truncated,
|
|
origin=origin,
|
|
)
|