feat(brain): add GrowthBrain.select_task() + kill abstract goals config
- GrowthBrain.select_task() uses weighted random from concrete Task objects - Removed self.goals from Config (no longer reads goals: from config.yml) - Mission + plugins are now the SSOT for bot behavior The bot no longer receives abstract strings like 'Nurture my community' that the LLM Brain can't operationalize. Instead, the GoalDecomposer generates Task(browse_feed, HomeFeed, budget=7) which routes to concrete feed loops. 18/18 TDD tests passing.
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@@ -210,3 +210,110 @@ class TestGoalDecomposerGeneratesTasks:
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f"Task target_screen '{task.target_screen}' is not in ScreenTopology! "
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f"The bot cannot navigate there."
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)
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class TestGoalDecomposerFromConfig:
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"""Tests that GoalDecomposer correctly derives tasks from config-like dicts.
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Validates that the legacy `goals:` config is not needed."""
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def test_decomposer_produces_tasks_without_goals(self):
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"""Tasks come from plugins + actions, NOT from goals list."""
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from GramAddict.core.goal_decomposer import GoalDecomposer
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plugins = {"likes": {"percentage": 100}}
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actions = {"feed": "5-10"}
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mission = {"strategy": "aggressive_growth"}
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decomposer = GoalDecomposer(plugins=plugins, actions=actions, mission=mission)
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tasks = decomposer.generate_tasks()
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assert len(tasks) > 0, "Tasks must come from plugins, not goals"
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def test_decomposer_accepts_empty_mission(self):
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"""If no mission is provided, default to aggressive_growth."""
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from GramAddict.core.goal_decomposer import GoalDecomposer
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plugins = {"likes": {"percentage": 100}}
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actions = {"feed": "5-10"}
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decomposer = GoalDecomposer(plugins=plugins, actions=actions, mission={})
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tasks = decomposer.generate_tasks()
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assert len(tasks) > 0, "Empty mission must fall back to aggressive_growth"
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class TestGrowthBrainTaskSelection:
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"""Tests that GrowthBrain.select_task() picks from concrete Task objects."""
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def test_select_task_returns_task_object(self):
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from GramAddict.core.goal_decomposer import GoalDecomposer, Task
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from GramAddict.core.growth_brain import GrowthBrain
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from GramAddict.core.dopamine_engine import DopamineEngine
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plugins = {"likes": {"percentage": 100}, "story_view": {"percentage": 80}}
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actions = {"feed": "5-10", "explore": "5-10"}
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mission = {"strategy": "aggressive_growth"}
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decomposer = GoalDecomposer(plugins=plugins, actions=actions, mission=mission)
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tasks = decomposer.generate_tasks()
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dopamine = DopamineEngine()
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brain = GrowthBrain(username="test", persona_interests=[])
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selected = brain.select_task(dopamine, tasks)
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assert isinstance(selected, Task), f"Expected Task, got {type(selected)}"
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assert selected in tasks
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def test_select_task_returns_none_on_empty_tasks(self):
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from GramAddict.core.growth_brain import GrowthBrain
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from GramAddict.core.dopamine_engine import DopamineEngine
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dopamine = DopamineEngine()
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brain = GrowthBrain(username="test", persona_interests=[])
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selected = brain.select_task(dopamine, [])
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assert selected is None, "Empty task list must return None"
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def test_select_task_returns_none_on_high_boredom(self):
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from GramAddict.core.goal_decomposer import GoalDecomposer
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from GramAddict.core.growth_brain import GrowthBrain
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from GramAddict.core.dopamine_engine import DopamineEngine
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plugins = {"likes": {"percentage": 100}}
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actions = {"feed": "5-10"}
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mission = {"strategy": "aggressive_growth"}
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decomposer = GoalDecomposer(plugins=plugins, actions=actions, mission=mission)
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tasks = decomposer.generate_tasks()
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dopamine = DopamineEngine()
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dopamine.boredom = 95.0
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brain = GrowthBrain(username="test", persona_interests=[])
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selected = brain.select_task(dopamine, tasks)
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assert selected is None, "High boredom must return None (= ShiftContext signal)"
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def test_select_task_uses_weights(self):
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"""Over many selections, higher-weighted tasks should appear more often."""
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from GramAddict.core.goal_decomposer import GoalDecomposer, Task
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from GramAddict.core.growth_brain import GrowthBrain
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from GramAddict.core.dopamine_engine import DopamineEngine
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plugins = {"likes": {"percentage": 100}, "story_view": {"percentage": 80}}
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actions = {"feed": "5-10", "explore": "5-10"}
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mission = {"strategy": "aggressive_growth"}
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decomposer = GoalDecomposer(plugins=plugins, actions=actions, mission=mission)
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tasks = decomposer.generate_tasks()
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dopamine = DopamineEngine()
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brain = GrowthBrain(username="test", persona_interests=[])
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# Run 100 selections and count
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counts: dict = {}
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for _ in range(100):
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selected = brain.select_task(dopamine, tasks)
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if selected:
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counts[selected.target_screen] = counts.get(selected.target_screen, 0) + 1
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# With aggressive_growth, ExploreFeed (weight 0.45) should dominate
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assert len(counts) > 1, "Selection must pick from multiple screens"
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