Motore v2: run_graph con recipe_dir/calibrazione/overlay, /validate, test (#46)

Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>

src/vision/runner.py

@@ -9,6 +9,7 @@ from __future__ import annotations
 import math
 import os
 import subprocess
+import tempfile
 import time
 from dataclasses import dataclass, field
 from functools import lru_cache
@@ -18,6 +19,9 @@ from typing import Any
 import numpy as np
 from visionsuite.core.image import Image
 from visionsuite.task import Task
+from visionsuite.task.graph import RecipeError  # #46: errori di ricetta v2
+from visionsuite.task.registry import load_tools
+from visionsuite.task.session import Session
 
 _SUBMODULE = Path(__file__).resolve().parents[2] / "vendor" / "visionsuite"
 
@@ -49,6 +53,10 @@ class RunOutcome:
     # Kept apart from `failures`: the tool did not raise, it just produced a
     # number the caller must not measure a part by. Value is the reason.
     invalid_outputs: dict[str, str] = field(default_factory=dict)
+    # #46: contorni di tutti gli strumenti (px immagine, con tool_id) e esito
+    # del TaskReport (informativo: il verdetto quote lo dà il backend).
+    overlay: list[dict] = field(default_factory=list)
+    outcome: str | None = None
 
 
 @lru_cache(maxsize=1)
@@ -97,12 +105,46 @@ def engine_version() -> str:
     return _engine_version_from_git()
 
 
+def _scale_calibration(calibration: dict | None):
+    """Dict {"mm_per_px"|"px_per_mm"} -> ScaleCalibration (gli strumenti di
+    quota convertono con `in_millimetres`, che non accetta un dict)."""
+    if calibration is None:
+        return None
+    from visionsuite.calibration import ScaleCalibration
+
+    if not isinstance(calibration, dict) or not (
+        calibration.get("mm_per_px") or calibration.get("px_per_mm")
+    ):
+        raise GraphBuildError(
+            "calibration must be {'mm_per_px': float} or {'px_per_mm': float}"
+        )
+    key = "mm_per_px" if calibration.get("mm_per_px") else "px_per_mm"
+    return ScaleCalibration(**{key: float(calibration[key])})
+
+
+def _open_session(graph: dict, recipe_dir: Any, calibration: dict | None,
+                  workdir: str) -> Session:
+    """Costruisce la Session v2; RecipeError e grafo malformato -> GraphBuildError."""
+    cal = _scale_calibration(calibration)
+    try:
+        return Session.from_dict(
+            graph, Path(recipe_dir) if recipe_dir else Path(workdir), cal,
+        )
+    except RecipeError as exc:
+        raise GraphBuildError(f"malformed graph: {exc}") from exc
+    except (KeyError, TypeError, AttributeError, ValueError) as exc:
+        raise GraphBuildError(
+            f"malformed graph: {type(exc).__name__}: {exc}"
+        ) from exc
+
+
 def run_graph(
     image: Any,
     graph: dict,
     calibration: dict | None = None,
+    recipe_dir: Any = None,
 ) -> RunOutcome:
-    """Run a serialised vs-task graph against one image.
+    """Run a serialised vs-task v2 graph against one image.
 
     A tool that fails does not stop the others - on a crooked piece an edge may
     simply not be there, and the other quotes are still wanted. Failures come
@@ -112,33 +154,35 @@ def run_graph(
     wrapped into the `visionsuite.core.image.Image` that vs-measure's tools
     actually read via `.pixels`; an `Image` passed in is used as-is.
 
-    Two phases, on purpose: building the task from `graph` can fail on
-    nothing but the caller's input (a bad schema version, a tool with no
-    "kind", a graph that is not a dict at all) - that is `GraphBuildError`,
-    a 422 for the worker. Once the task exists, `task.run()` is the engine's
-    own business; an exception from there is not the caller's mistake, and
-    the worker must not call it one.
+    `recipe_dir` is the folder of the recipe's files (meta.dxf, meta.models,
+    ...); without it an empty temporary folder is used, so a recipe that needs
+    a file fails as a malformed graph instead of reading from the CWD.
+
+    Two phases, on purpose: building the session can fail on nothing but the
+    caller's input (a bad schema version, a tool with no "kind", a missing
+    file) - that is `GraphBuildError`, a 422 for the worker. Once it exists,
+    running is the engine's own business; an exception from there is not the
+    caller's mistake, and the worker must not call it one.
     """
-    try:
-        task = Task.from_dict(graph)
-    except (KeyError, TypeError, AttributeError, ValueError) as exc:
-        raise GraphBuildError(
-            f"malformed graph: {type(exc).__name__}: {exc}"
-        ) from exc
-
-    wrapped_image = image if isinstance(image, Image) else Image(pixels=np.asarray(image))
-    context: dict[str, Any] = {"image": wrapped_image}
-    if calibration is not None:
-        context["calibration"] = calibration
-
-    started = time.monotonic()
-    report = task.run(context=context)
-    elapsed_ms = int((time.monotonic() - started) * 1000)
+    load_tools()  # #46: registra gli strumenti degli entry point di vs-tools
+    with tempfile.TemporaryDirectory() as empty_dir:
+        session = _open_session(graph, recipe_dir, calibration, empty_dir)
+        wrapped_image = (
+            image if isinstance(image, Image) else Image(pixels=np.asarray(image))
+        )
+        started = time.monotonic()
+        report = session.run(wrapped_image)
+        elapsed_ms = int((time.monotonic() - started) * 1000)
 
     outputs: dict[str, float] = {}
     failures: list[ToolFailure] = []
     invalid_outputs: dict[str, str] = {}
+    overlay: list[dict] = []
     for result in report:
+        # #46: overlay di ogni strumento, con il tool_id di chi lo ha prodotto
+        for item in result.overlay or []:
+            if isinstance(item, dict):
+                overlay.append({**item, "tool_id": result.tool_id})
         if not result.ok:
             failures.append(ToolFailure(
                 tool_id=result.tool_id,
@@ -164,4 +208,55 @@ def run_graph(
         engine_version=engine_version(),
         duration_ms=elapsed_ms,
         invalid_outputs=invalid_outputs,
+        overlay=overlay,
+        outcome=report.outcome,
     )
+
+
+def _is_number(value: Any) -> bool:
+    return isinstance(value, (int, float)) and not isinstance(value, bool)
+
+
+def validate_graph(
+    graph: dict, recipe_dir: Any = None
+) -> tuple[bool, list[str], list[dict]]:
+    """Validate a v2 recipe without an image: (ok, errors, numeric outputs).
+
+    Not a draft: a missing meta file is an error. `outputs` lists the numeric
+    outputs the tools declare (OUT properties with a numeric default, plus the
+    `values` of dimension tools), with quantity/unit when declared.
+    """
+    load_tools()
+    if not isinstance(graph, dict):
+        return False, ["graph must be a JSON object"], []
+    try:
+        task = Task.from_dict(
+            graph, recipe_dir=Path(recipe_dir) if recipe_dir else None
+        )
+    except RecipeError as exc:
+        return False, list(exc.errors), []
+    except (KeyError, TypeError, AttributeError, ValueError) as exc:
+        return False, [f"{type(exc).__name__}: {exc}"], []
+
+    outputs: list[dict] = []
+    for tool in task.tools:
+        value_quantities = getattr(tool, "value_quantities", None) or {}
+        values = tuple(getattr(tool, "values", ()) or ())
+        for prop in tool.outputs():
+            if not (_is_number(prop.default) or prop.name in values):
+                continue
+            quantity = value_quantities.get(prop.name, getattr(tool, "quantity", None))
+            if not isinstance(quantity, str):
+                quantity = None
+            unit = None
+            if quantity == "length":
+                nominal_unit = getattr(tool, "nominal_unit", None)
+                unit = nominal_unit if isinstance(nominal_unit, str) else None
+            elif quantity == "angle":
+                unit = "deg"
+            outputs.append({
+                "key": f"{tool.id}.{prop.name}",
+                "quantity": quantity,
+                "unit": unit,
+            })
+    return True, [], outputs