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https://github.com/open-jarvis/OpenJarvis.git
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Jon Saad-FalconandClaude Opus 4.6
301e9cd2d4
Complete implementation across six development phases (v0.1 through v1.0): - Core: Registry system, config, event bus, types (Phase 0) - Intelligence + Inference: Model routing, Ollama/vLLM/llama.cpp/Cloud engines (Phase 1) - Memory: SQLite/FAISS/ColBERT/BM25/Hybrid backends, document ingest, context injection (Phase 2) - Agents: Simple/Orchestrator/Custom/OpenClaw agents, tool system (Phase 3) - Learning: HeuristicRouter, reward functions, GRPO stub, telemetry aggregation (Phase 4) - SDK: Jarvis class, OpenClaw protocol/transport, benchmarks, Docker deployment (Phase 5) 520 tests passing, 8 skipped (optional deps). Ruff lint clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
57 lines
1.9 KiB
Python
57 lines
1.9 KiB
Python
"""Tests for LearningConfig and its integration into JarvisConfig."""
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from __future__ import annotations
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from pathlib import Path
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from openjarvis.core.config import (
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HardwareInfo,
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JarvisConfig,
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LearningConfig,
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generate_default_toml,
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load_config,
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)
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class TestLearningConfig:
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def test_defaults(self) -> None:
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cfg = LearningConfig()
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assert cfg.default_policy == "heuristic"
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assert cfg.reward_weights == ""
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def test_custom_values(self) -> None:
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cfg = LearningConfig(
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default_policy="grpo",
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reward_weights="latency=0.4,cost=0.3,efficiency=0.3",
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)
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assert cfg.default_policy == "grpo"
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assert cfg.reward_weights == "latency=0.4,cost=0.3,efficiency=0.3"
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def test_jarvis_config_has_learning(self) -> None:
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cfg = JarvisConfig()
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assert hasattr(cfg, "learning")
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assert isinstance(cfg.learning, LearningConfig)
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assert cfg.learning.default_policy == "heuristic"
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def test_toml_loading_with_learning(self, tmp_path: Path) -> None:
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toml_file = tmp_path / "config.toml"
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toml_file.write_text(
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'[learning]\ndefault_policy = "grpo"\n'
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'reward_weights = "latency=0.5"\n'
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)
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cfg = load_config(toml_file)
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assert cfg.learning.default_policy == "grpo"
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assert cfg.learning.reward_weights == "latency=0.5"
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def test_toml_loading_without_learning(self, tmp_path: Path) -> None:
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toml_file = tmp_path / "config.toml"
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toml_file.write_text("[engine]\n")
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cfg = load_config(toml_file)
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assert cfg.learning.default_policy == "heuristic"
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def test_generate_default_toml_includes_learning(self) -> None:
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hw = HardwareInfo()
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toml_str = generate_default_toml(hw)
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assert "[learning]" in toml_str
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assert 'default_policy = "heuristic"' in toml_str
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