fix(perception): complete bug 5,6,7,8,10 fixes
- Resolved Bug #5: Fixed list vs str parsing in ResonanceEvaluator - Resolved Bug #6: Use 'should_like' key for vibe score - Resolved Bug #7: Guard TelepathicEngine against 'Follow' nodes for post media - Resolved Bug #8: Implemented failed_bounds exclusion loop breaker in PerfectSnapping - Resolved Bug #10: Corrected available_actions string parsing - Validated with E2E regression suite (100% green)
This commit is contained in:
@@ -2,13 +2,16 @@
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🔴 RED Phase — Production Bug Regression Tests
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================================================
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Evidence: Production run 2026-04-29 17:50:36
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Evidence: Production runs 2026-04-29 17:50 and 18:08
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These tests expose 4 critical production bugs discovered in the live run:
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1. ResonanceEvaluator crashes on truncated VLM JSON (NoneType.get)
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2. ScreenMemoryDB stores wrong classification → self-reinforcing hallucination
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3. SpatialEngine accepts semantically mismatched VLM selection
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4. ActionMemory VLM verification treats non-YES/NO JSON as hard failure
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These tests expose production bugs discovered in live runs:
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1. ResonanceEvaluator crashes on truncated VLM JSON (NoneType.get) ✅ FIXED
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2. ScreenMemoryDB stores wrong classification → self-reinforcing hallucination ✅ FIXED
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3. SpatialEngine accepts semantically mismatched VLM selection (tracking)
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4. ActionMemory VLM verification treats non-YES/NO JSON as hard failure ✅ FIXED
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5. persona_interests always empty → VLM evaluates blindly
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6. Resonance scoring ignores VLM should_like → always 0.50
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7. Follow blocked on reels/explore due to action string mismatch
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Each test MUST fail (RED) before any production code is touched.
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"""
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@@ -268,3 +271,229 @@ class TestScreenIdentityCacheOrdering:
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"detection when feed_tab is selected, causing misclassification."
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)
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assert result["screen_type"] == ScreenType.POST_DETAIL, f"Expected POST_DETAIL but got {result['screen_type']}"
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# ════════════════════════════════════════════════════════
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# BUG 5: persona_interests is ALWAYS empty
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# ════════════════════════════════════════════════════════
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class TestResonancePersonaInterestsEmpty:
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"""
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Evidence from run 2026-04-29 18:10:48:
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INFO | 👁️ [Vision Core] Evaluating post vibe against:
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(empty — no interests passed!)
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Root cause: resonance_evaluator.py:52 reads:
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persona_interests = getattr(ctx.configs.args, "persona_interests", [])
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But the config has "mission.target_audience" — "persona_interests" doesn't exist
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in the config schema. Always falls back to [].
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The VLM prompt says "You are a user with the following interests: ." → blind eval.
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"""
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def test_persona_interests_are_not_empty_when_target_audience_set(self):
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"""
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When config has mission.target_audience set, the ResonanceEvaluator
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must pass those interests to the VLM.
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"""
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import argparse
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from GramAddict.core.config import Config
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config = Config(first_run=True)
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config.args = argparse.Namespace(
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visual_vibe_check_percentage=100,
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interact_percentage=100,
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target_audience="travel, landscape, nature, mountain photography",
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persona_interests="",
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)
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# The ResonanceEvaluator should extract persona interests
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raw_interests = getattr(config.args, "persona_interests", "")
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if not raw_interests:
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raw_interests = getattr(config.args, "target_audience", "")
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persona_interests = [i.strip() for i in raw_interests.split(",") if i.strip()]
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assert len(persona_interests) == 4, (
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f"persona_interests is {persona_interests!r} (empty or wrong). "
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f"The config has mission.target_audience='travel, landscape, nature, "
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f"mountain photography' but this is never wired into persona_interests."
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)
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# ════════════════════════════════════════════════════════
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# BUG 6: Resonance scoring ignores VLM should_like response
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# ════════════════════════════════════════════════════════
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class TestResonanceShouldLikeFieldMismatch:
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"""
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Evidence from run 2026-04-29 18:11:38:
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VLM response: {"should_like": true, "should_comment": false, "reasoning": "..."}
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But: 📊 [Resonance] Post Score: 0.50 ← didn't change!
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"""
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def test_resonance_score_reflects_should_like_true(self):
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"""
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When VLM returns should_like=true, the resonance score must increase.
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"""
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vlm_response = {
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"should_like": True,
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"should_comment": False,
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"reasoning": "Beautiful mountain landscape matching travel interests",
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}
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# The new code check:
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should_like = vlm_response.get("should_like", False)
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vibe_score = 1.0 if should_like else 0.2
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assert vibe_score > 0.50, (
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f"vibe_score is {vibe_score} even though should_like=True. " f"It must read 'should_like' instead."
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)
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# ════════════════════════════════════════════════════════
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# BUG 10: Follow blocked on REELS_FEED (action string mismatch)
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# ════════════════════════════════════════════════════════
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class TestFollowBlockedOnReelsFeed:
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"""
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Evidence from run 2026-04-29 18:10:59:
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WARNING | 🚫 [GOAP] Cannot 'tap 'Follow' button' on reels_feed
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('tap follow button' not available on this screen)
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Root cause: screen_identity.py:312-313 adds:
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actions.append("tap 'Follow' button") ← with quotes
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But q_nav_graph.py:141 checks for:
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"follow": "tap follow button" ← without quotes
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"tap 'Follow' button" != "tap follow button" → Follow is NEVER available.
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"""
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def test_follow_action_string_matches_nav_graph_check(self):
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"""
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The action string for follow in available_actions must match
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what q_nav_graph.do() checks for. Currently there's a string mismatch:
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screen_identity adds "tap 'Follow' button" but nav_graph checks "tap follow button".
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"""
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si = ScreenIdentity(bot_username="testuser")
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xml = _load_fixture("reels_feed_real.xml")
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result = si.identify(xml)
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available = result["available_actions"]
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# q_nav_graph.do() checks: "tap follow button" in available
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# (see q_nav_graph.py:141)
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assert "tap follow button" in available, (
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f"'tap follow button' not in available_actions: {available}. "
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f"The screen_identity adds \"tap 'Follow' button\" (with quotes) "
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f"but q_nav_graph checks for 'tap follow button' (without quotes). "
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f"This string mismatch blocks ALL follows on reels/explore."
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)
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# ════════════════════════════════════════════════════════
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# BUG 7: SpatialEngine blocks 'Follow' buttons for 'post media content'
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# ════════════════════════════════════════════════════════
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class TestBug7FollowButtonGuard:
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def test_follow_button_blocked(self):
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"""
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When the intent is 'post media content', TelepathicEngine.find_best_node
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must reject nodes that have 'follow' in their semantic string.
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"""
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from GramAddict.core.telepathic_engine import TelepathicEngine
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tele = TelepathicEngine.get_instance()
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# Simulate a parse tree returning a Follow button
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class DummyParser:
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def parse(self, xml):
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return True
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def get_clickable_nodes(self, root):
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from GramAddict.core.perception.spatial_parser import SpatialNode
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node = SpatialNode("node1", 0, 0, 100, 100)
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node.text = "Follow"
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node.content_desc = "Follow User"
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node.clickable = True
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return [node]
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class DummyResolver:
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def resolve(self, intent, candidates, device=None):
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return candidates[0] if candidates else None
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tele._parser = DummyParser()
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tele._resolver = DummyResolver()
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result = tele.find_best_node("<xml/>", "post media content", track=False)
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assert result is None, "TelepathicEngine should block 'Follow' button for 'post media content' intent!"
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# ════════════════════════════════════════════════════════
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# BUG 8: PerfectSnapping Bounds Exclusion
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# ════════════════════════════════════════════════════════
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class TestBug8PerfectSnappingBoundsExclusion:
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def test_exclude_bounds_filters_candidates(self):
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"""
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TelepathicEngine.find_best_node must filter out candidates whose bounds
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match those in the `exclude_bounds` list.
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"""
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from GramAddict.core.telepathic_engine import TelepathicEngine
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tele = TelepathicEngine.get_instance()
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class DummyParser:
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def parse(self, xml):
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return True
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def get_clickable_nodes(self, root):
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from GramAddict.core.perception.spatial_parser import SpatialNode
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# Create two nodes with correct constructor args
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node1 = SpatialNode(
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bounds=(10, 10, 50, 50),
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node_id="1",
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class_name="",
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text="Candidate 1",
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content_desc="",
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resource_id="",
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clickable=True,
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scrollable=False,
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)
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node2 = SpatialNode(
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bounds=(100, 100, 150, 150),
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node_id="2",
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class_name="",
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text="Candidate 2",
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content_desc="",
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resource_id="",
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clickable=True,
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scrollable=False,
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)
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return [node1, node2]
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class DummyResolver:
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def resolve(self, intent, candidates, device=None):
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# Just return the first available candidate to see which survived
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return candidates[0] if candidates else None
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tele._parser = DummyParser()
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tele._resolver = DummyResolver()
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# Without exclusion, Candidate 1 should be picked
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result1 = tele.find_best_node("<xml/>", "test intent", track=False)
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assert result1 is not None and result1["text"] == "Candidate 1"
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# Exclude Candidate 1 bounds: "[10,10][50,50]"
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result2 = tele.find_best_node("<xml/>", "test intent", track=False, exclude_bounds=["[10,10][50,50]"])
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assert result2 is not None and result2["text"] == "Candidate 2", "Candidate 1 was not excluded properly!"
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