somew1nd
a45daf23f8
Report device actions as dispatched and preserve full failure details. Route Flash through McpActionExecutor and use ToolFailure across helper tools and agent loops instead of inferring failure from response text. Require model-provided descriptions for coordinate targets. Keep observed element metadata separate from those descriptions in safety checks, visual summaries, history, and frontend labels. Add Gemini Interactions API video analysis with configurable processing mode, chunk size, and timeouts. Centralize Google provider capabilities and token usage normalization, and update google-genai to 2.22.0. Preserve system instructions on follow-up interactions, replan pending chunks when falling back to static processing, and reject unanswered native video and audio segments instead of caching placeholder results. Keep helper-tool failure status intact through history tools and committee calls. Validation: 1,762 Python unit tests passed (3 skipped), 40 frontend formatter tests passed, and the production UI build completed. Ruff lint, formatting, the quality ratchet, and git diff checks passed.
81 lines
3.0 KiB
Python
81 lines
3.0 KiB
Python
# Copyright 2026 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Element hit testing: which indexed element covers a pixel point.
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Used by the Explorer to deduplicate candidates against the screen index.
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Recorded coordinate actions use the model's ``target_description``.
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"""
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from typing import Any
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from artemis.utils.visualization import parse_bounds
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def _element_bounds(element: dict[str, Any]) -> tuple[int, int, int, int] | None:
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"""Returns (left, top, right, bottom) pixel bounds of an indexed element.
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Accepts both list bounds (``[l, t, r, b]``, the shape produced by
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``format_minimal_list_with_elements``) and Android bounds strings
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(``"[l,t][r,b]"``). Returns None for missing or malformed bounds.
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"""
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bounds = element.get("bounds")
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if isinstance(bounds, str):
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return parse_bounds(bounds)
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if isinstance(bounds, (list, tuple)) and len(bounds) == 4:
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try:
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left, top, right, bottom = (int(v) for v in bounds)
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except (TypeError, ValueError):
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return None
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return left, top, right, bottom
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return None
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def find_element_at_point(
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elements: list[dict[str, Any]] | None, x: int, y: int
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) -> tuple[dict[str, Any] | None, str]:
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"""Finds the smallest indexed element whose bounds contain pixel point (x, y).
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XML-derived elements are preferred over OCR-derived ones (OCR boxes carry
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text but weaker structure); within each group the smallest covering area
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wins. Returns ``(element, source)`` where source is ``"hit_test"``,
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``"ocr"``, or ``"none"`` (with element None). Malformed element data is
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skipped; the function never raises on it.
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"""
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best_xml: tuple[int, dict[str, Any]] | None = None
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best_ocr: tuple[int, dict[str, Any]] | None = None
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for element in elements or []:
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if not isinstance(element, dict):
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continue
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rect = _element_bounds(element)
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if rect is None:
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continue
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left, top, right, bottom = rect
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if not (left <= x <= right and top <= y <= bottom):
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continue
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area = max(1, (right - left)) * max(1, (bottom - top))
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if element.get("is_ocr"):
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if best_ocr is None or area < best_ocr[0]:
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best_ocr = (area, element)
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else:
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if best_xml is None or area < best_xml[0]:
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best_xml = (area, element)
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if best_xml is not None:
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return best_xml[1], "hit_test"
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if best_ocr is not None:
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return best_ocr[1], "ocr"
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return None, "none"
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