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* chore: create learning subdirectory structure (routing, agents, intelligence) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: extract classify_query to routing/_utils.py Move the classify_query() function and its regex patterns into a shared utility module so multiple routing policies can import it without depending on the full trace_policy module. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor: move routing files to learning/routing/ subdirectory Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: create LearnedRouterPolicy merging trace-driven + SFT routing Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add conditional Algolia DocSearch integration Add Algolia DocSearch as an optional search upgrade — native lunr.js search remains the default until credentials are configured. Includes CDN assets, Jinja2 conditional config injection, init script with graceful fallback, light/dark theme CSS, improved search tokenization for snake_case/dotted identifiers, and search boosts for key pages. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor: move agent_evolver and skill_discovery to learning/agents/ Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor: move learning/orchestrator to learning/intelligence/orchestrator Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor: delete removed learning policies, rewrite __init__.py, clean up api_routes Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add SFT/GRPO/DSPy/GEPA config dataclasses, update LearningConfig Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add general-purpose SFT trainer (intelligence/sft_trainer.py) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: update stale imports in multi_model_router example Update imports to use new learning/routing/ paths after the subdirectory reorganization. Replace BanditRouterPolicy with LearnedRouterPolicy. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add general-purpose GRPO trainer (intelligence/grpo_trainer.py) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add DSPy agent optimizer (agents/dspy_optimizer.py) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add GEPA agent optimizer (agents/gepa_optimizer.py) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add learning-dspy and learning-gepa optional dependency extras Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: update integration test to check for learned policy instead of grpo Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: clean up stale APIs and unused params in examples - deep_research: remove system_prompt and max_turns params not accepted by Jarvis.ask(), inline system prompt into the query instead - doc_qa: remove unused --top-k CLI arg that was never passed to the API - multi_model_router: fix select_model() call to match single-arg signature Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: import SFT/GRPO trainers in intelligence/__init__.py for registry Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * chore: remove .md file changes from PR Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * chore: restore search boost frontmatter for key docs pages Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
51 lines
2.0 KiB
Python
51 lines
2.0 KiB
Python
"""Tests for LearningOrchestrator integration with SystemBuilder."""
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class TestSystemLearningIntegration:
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def test_learning_orchestrator_not_created_when_disabled(self):
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"""Default config has training_enabled=False, so no orchestrator."""
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from openjarvis.core.config import JarvisConfig
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from openjarvis.system import SystemBuilder
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config = JarvisConfig()
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assert config.learning.training_enabled is False
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result = SystemBuilder._setup_learning_orchestrator(config)
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assert result is None
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def test_learning_orchestrator_created_when_enabled(self):
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"""When training_enabled=True, orchestrator is created."""
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from openjarvis.core.config import JarvisConfig
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from openjarvis.learning.learning_orchestrator import LearningOrchestrator
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from openjarvis.system import SystemBuilder
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config = JarvisConfig()
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config.learning.training_enabled = True
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result = SystemBuilder._setup_learning_orchestrator(config)
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assert isinstance(result, LearningOrchestrator)
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def test_config_has_training_fields(self):
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"""LearningConfig has the training pipeline fields."""
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from openjarvis.core.config import LearningConfig
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config = LearningConfig()
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assert config.training_enabled is False
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assert config.training_schedule == ""
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assert config.intelligence.sft.lora_rank == 16
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assert config.intelligence.sft.lora_alpha == 32
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assert config.intelligence.sft.min_pairs == 10
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assert config.min_improvement == 0.02
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def test_training_components_exported(self):
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"""Learning package exports all training components."""
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from openjarvis.learning import (
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AgentConfigEvolver,
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LearningOrchestrator,
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LoRATrainer,
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TrainingDataMiner,
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)
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assert TrainingDataMiner is not None
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assert LoRATrainer is not None
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assert AgentConfigEvolver is not None
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assert LearningOrchestrator is not None
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