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https://github.com/open-jarvis/OpenJarvis.git
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Prathap PandGitHub
c2756964a7
* fix(channels): wire channel→agent handler and fix Telegram send pipeline * format code * add supported tests
91 lines
3.2 KiB
Python
91 lines
3.2 KiB
Python
"""Tests for the DSPy agent optimizer (mocked -- no dspy dependency required)."""
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from __future__ import annotations
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import time
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from unittest.mock import MagicMock, patch
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class TestDSPyOptimizerConfig:
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def test_default_config(self) -> None:
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from openjarvis.core.config import DSPyOptimizerConfig
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cfg = DSPyOptimizerConfig()
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assert cfg.optimizer == "BootstrapFewShotWithRandomSearch"
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assert cfg.max_bootstrapped_demos == 4
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assert cfg.min_traces == 20
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def test_optimizer_init(self) -> None:
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from openjarvis.core.config import DSPyOptimizerConfig
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from openjarvis.learning.agents.dspy_optimizer import DSPyAgentOptimizer
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cfg = DSPyOptimizerConfig()
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optimizer = DSPyAgentOptimizer(cfg)
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assert optimizer.config is cfg
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class TestDSPyOptimizerTraceConversion:
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def test_too_few_traces_skipped(self) -> None:
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from openjarvis.core.config import DSPyOptimizerConfig
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from openjarvis.learning.agents.dspy_optimizer import DSPyAgentOptimizer
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optimizer = DSPyAgentOptimizer(DSPyOptimizerConfig(min_traces=10))
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mock_store = MagicMock()
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mock_store.list_traces.return_value = []
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result = optimizer.optimize(mock_store)
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assert result["status"] == "skipped"
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def test_optimize_returns_toml_updates(self) -> None:
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from openjarvis.core.config import DSPyOptimizerConfig
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from openjarvis.core.types import StepType, Trace, TraceStep
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from openjarvis.learning.agents.dspy_optimizer import DSPyAgentOptimizer
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cfg = DSPyOptimizerConfig(min_traces=1)
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optimizer = DSPyAgentOptimizer(cfg)
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# Create mock traces
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now = time.time()
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traces = []
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for i in range(5):
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traces.append(
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Trace(
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query=f"test query {i}",
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agent="native_react",
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model="qwen3:8b",
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result=f"result {i}",
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outcome="success",
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feedback=0.9,
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started_at=now,
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ended_at=now + 1,
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total_tokens=100,
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total_latency_seconds=1.0,
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steps=[
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TraceStep(
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step_type=StepType.GENERATE,
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timestamp=now,
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duration_seconds=0.5,
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)
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],
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)
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)
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mock_store = MagicMock()
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mock_store.list_traces.return_value = traces
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# Mock dspy so the test works without the dependency
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import openjarvis.learning.agents.dspy_optimizer as mod
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with patch.object(mod, "HAS_DSPY", True):
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with patch.object(
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optimizer,
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"_run_dspy_optimization",
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return_value={
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"system_prompt": "You are a helpful assistant.",
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"few_shot_examples": [{"input": "hi", "output": "hello"}],
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},
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):
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result = optimizer.optimize(mock_store)
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assert result["status"] == "completed"
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assert "config_updates" in result
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