purge: remove ALL hardcoded UI markers + model defaults from SAE
TDD cycle (RED → GREEN): SAE perceive() — Zero Maintenance: - Removed ALL hardcoded marker tuples (instagram_modal_markers, creation_flow_markers, dismiss_button_patterns, blocked_markers) - Removed ALL hardcoded model names (llava:latest, qwen3.5:latest) - Removed ALL hardcoded URLs (localhost:11434) - Removed naked except blocks with model fallback defaults New autonomous flow (zero hardcoded UI identifiers): 1. Package-based foreign app detection (Android-level, not app-specific) 2. Qdrant semantic cache (O(1) recall of learned screen types) 3. ScreenIdentity structural delegation (MODAL/FOREIGN_APP) 4. LLM autonomous classification (first-encounter learning then cached) GOAP smart UI polling: - Replaced static random.uniform(1.6, 2.8) sleep with MAX_POLLS=5 polling loop that detects actual UI transitions Model config centralized via _get_model_config(): - ALL model/URL lookups go through Config() SSOT - Fail Fast - no silent hardcoded fallbacks Tests: 9 new, 119 passing, 0 regressions
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217
tests/unit/test_sae_zero_maintenance.py
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217
tests/unit/test_sae_zero_maintenance.py
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"""
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🔴 RED: Zero-Maintenance Compliance for SituationalAwarenessEngine
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These tests enforce that the SAE contains ZERO hardcoded UI element identifiers
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and ZERO hardcoded model/URL defaults. The bot must:
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1. Detect obstacles via autonomous LLM+Qdrant pipeline — NOT via hardcoded resource-ids or text patterns.
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2. Pull ALL model names/URLs from Config() — NO fallback literals scattered across the codebase.
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3. Rely on structural package checks (app-agnostic) and ScreenIdentity delegation — NOT marker tuples.
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Violating any of these rules means the bot breaks when Instagram updates its UI.
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That is the opposite of Zero Maintenance.
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"""
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import inspect
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import re
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# ══════════════════════════════════════════════════════════
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# 1. NO HARDCODED INSTAGRAM UI ELEMENT IDENTIFIERS IN SAE
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# ══════════════════════════════════════════════════════════
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class TestSAEContainsNoHardcodedUIElements:
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"""
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The SAE perceive() must NOT contain any hardcoded Instagram resource-id
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fragments, button text patterns, or content-desc strings.
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ALL obstacle detection must flow through: package check → Qdrant cache → LLM fallback.
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"""
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FORBIDDEN_RESOURCE_ID_FRAGMENTS = [
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"survey_overlay",
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"survey_title",
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"interstitial_container",
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"mystery_interstitial",
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"nux_overlay",
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"rating_prompt",
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"feedback_dialog",
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"action_bar_browser",
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"browser_action_bar",
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"quick_capture",
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"gallery_cancel_button",
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"creation_flow",
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"reel_camera",
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]
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FORBIDDEN_BUTTON_TEXT_PATTERNS = [
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"Not Now",
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"not now",
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"Nicht jetzt",
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"Take Survey",
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"Bewerten",
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"rate \\d+ stars",
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]
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FORBIDDEN_CONTENT_DESC_PATTERNS = [
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"Close browser",
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]
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def _get_perceive_source(self):
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from GramAddict.core.situational_awareness import SituationalAwarenessEngine
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return inspect.getsource(SituationalAwarenessEngine.perceive)
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def test_no_hardcoded_resource_id_markers_in_perceive(self):
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"""perceive() must not contain hardcoded Instagram resource-id fragments."""
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source = self._get_perceive_source()
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for fragment in self.FORBIDDEN_RESOURCE_ID_FRAGMENTS:
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assert fragment not in source, (
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f"SAE.perceive() contains hardcoded resource-id fragment '{fragment}'! "
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f"This must be detected autonomously via LLM+Qdrant, not hardcoded."
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)
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def test_no_hardcoded_button_text_patterns_in_perceive(self):
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"""perceive() must not contain hardcoded dismiss button text patterns."""
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source = self._get_perceive_source()
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for pattern in self.FORBIDDEN_BUTTON_TEXT_PATTERNS:
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assert pattern not in source, (
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f"SAE.perceive() contains hardcoded button text pattern '{pattern}'! "
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f"Modal detection must be autonomous, not text-matching."
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)
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def test_no_hardcoded_content_desc_in_perceive(self):
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"""perceive() must not contain hardcoded content-desc strings."""
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source = self._get_perceive_source()
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for pattern in self.FORBIDDEN_CONTENT_DESC_PATTERNS:
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assert pattern not in source, (
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f"SAE.perceive() contains hardcoded content-desc '{pattern}'! " f"Must be discovered autonomously."
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)
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def test_no_marker_tuples_in_perceive(self):
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"""perceive() must not define any '_markers' or '_patterns' tuples."""
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source = self._get_perceive_source()
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marker_defs = re.findall(r"\b\w+_markers\s*=\s*\(", source)
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pattern_defs = re.findall(r"\b\w+_patterns\s*=\s*\(", source)
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all_defs = marker_defs + pattern_defs
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assert len(all_defs) == 0, (
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f"SAE.perceive() defines hardcoded marker/pattern tuples: {all_defs}. "
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f"All obstacle detection must be autonomous."
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)
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# ══════════════════════════════════════════════════════════
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# 2. NO HARDCODED MODEL NAMES / URLS IN SAE
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# ══════════════════════════════════════════════════════════
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class TestSAEContainsNoHardcodedModelDefaults:
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"""
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The SAE must never contain hardcoded model names or URLs as fallback strings.
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ALL model config must come from Config() — the single source of truth.
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A naked `except: model = "llava:latest"` is a maintenance bomb.
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"""
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FORBIDDEN_MODEL_LITERALS = [
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"llava:latest",
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"qwen3.5:latest",
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"llava",
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]
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FORBIDDEN_URL_LITERALS = [
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"localhost:11434",
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"http://localhost:11434/api/generate",
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]
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def _get_sae_source(self):
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from GramAddict.core.situational_awareness import SituationalAwarenessEngine
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return inspect.getsource(SituationalAwarenessEngine)
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def test_no_hardcoded_model_names(self):
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"""SAE must not contain any hardcoded model name strings."""
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source = self._get_sae_source()
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for literal in self.FORBIDDEN_MODEL_LITERALS:
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# Only check actual string literals (quoted), not comments
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pattern = rf"""['"]({re.escape(literal)})['"]"""
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matches = re.findall(pattern, source)
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assert len(matches) == 0, (
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f"SAE contains hardcoded model name '{literal}' ({len(matches)} occurrence(s)). "
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f"Model config must come exclusively from Config()."
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)
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def test_no_hardcoded_urls(self):
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"""SAE must not contain any hardcoded Ollama/API URLs."""
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source = self._get_sae_source()
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for literal in self.FORBIDDEN_URL_LITERALS:
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pattern = rf"""['"]([^'"]*{re.escape(literal)}[^'"]*)['"]"""
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matches = re.findall(pattern, source)
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assert len(matches) == 0, (
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f"SAE contains hardcoded URL '{literal}' ({len(matches)} occurrence(s)). "
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f"All URLs must come from Config()."
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)
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def test_no_naked_except_with_model_defaults(self):
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"""SAE must not have except blocks that hardcode model fallbacks."""
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source = self._get_sae_source()
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# Pattern: `except` followed within 5 lines by a model/url assignment
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except_blocks = re.findall(
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r"except.*?:\s*\n(?:.*\n){0,5}.*(?:model|url)\s*=\s*['\"]",
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source,
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)
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assert len(except_blocks) == 0, (
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f"SAE has {len(except_blocks)} except block(s) with hardcoded model/URL fallbacks. "
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f"Config() must be the SSOT — if it fails, crash loudly (Fail Fast)."
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)
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# ══════════════════════════════════════════════════════════
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# 3. GOAP SMART UI STABILIZATION (Poll instead of static sleep)
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# ══════════════════════════════════════════════════════════
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class TestGOAPSmartUIStabilization:
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"""
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After clicking an element, GOAP must poll for UI changes instead of
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using a static sleep. This prevents false 'inconclusive' results on
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slow devices/networks where UI transitions take >2s.
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"""
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def test_goap_polls_dump_hierarchy_multiple_times_after_click(self):
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"""
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The GOAP _execute_action must call dump_hierarchy multiple times
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(polling loop) instead of a single post-click dump.
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We verify this by inspecting the source code for the poll pattern.
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"""
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import inspect
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from GramAddict.core.goap import GoalExecutor
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source = inspect.getsource(GoalExecutor._execute_action)
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# Must have a polling loop with MAX_POLLS
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assert "MAX_POLLS" in source, "GOAP._execute_action must use a MAX_POLLS polling loop, not a static sleep."
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# Must NOT have the old static random.uniform sleep
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assert "random.uniform" not in source, (
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"GOAP._execute_action still uses random.uniform for static sleep! " "Must use smart UI polling instead."
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)
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# Must poll dump_hierarchy inside a loop
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assert "dump_hierarchy()" in source, "GOAP._execute_action must call dump_hierarchy() inside the poll loop."
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def test_goap_has_no_static_sleep_after_click(self):
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"""The old pattern was: click → sleep(random) → single dump. This must be gone."""
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import inspect
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from GramAddict.core.goap import GoalExecutor
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source = inspect.getsource(GoalExecutor._execute_action)
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# The click line and the next significant operation must NOT be a raw sleep with random
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click_idx = source.index("self.device.click(")
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code_after_click = source[click_idx : click_idx + 500]
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assert "random.uniform" not in code_after_click, (
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"GOAP still uses random.uniform sleep after click! "
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"Replace with smart UI polling (poll dump_hierarchy until XML changes)."
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)
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@@ -100,5 +100,4 @@ def test_telepathic_grid_selection_uses_structural_id(monkeypatch):
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engine.evaluate_grid_visuals(MockDevice(), ["travel"])
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assert grid_node in candidates_captured
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assert background_node not in candidates_captured, "Background recycler view should not be a grid candidate"
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