cdc3d3c4dc
- src/models.py: typisierte Verträge (dataclasses, Stdlib-only) - src/llm/claude_client.py: Adapter um 'claude -p' mit Mock-Fallback - src/agents/: BaseAgent + Vision, Market, Listing, Chat + Orchestrator - src/workflow.py: photo_to_listing() Fassade - spike/prototype.py + concept_spike.py: lauffähige End-to-End-Demo - tests/: 28 unittest-Tests (Mock-Pfad, offline deterministisch) Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
39 lines
1.3 KiB
Python
39 lines
1.3 KiB
Python
"""Tests für den Preis-Recherche-Agenten (Mock-Pfad)."""
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import unittest
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from src.agents import PriceResearchAgent
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from src.llm import ClaudeClient
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from src.models import ItemAnalysis, PriceSuggestion
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def _item(category="Kopfhörer", score=1.0):
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return ItemAnalysis(
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title_guess="Test", category=category,
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condition="Neu", condition_score=score, brand="Marke",
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)
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class PriceResearchTest(unittest.TestCase):
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def setUp(self):
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self.agent = PriceResearchAgent(ClaudeClient(mode="mock"))
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def test_returns_price_suggestion(self):
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price = self.agent.run(_item())
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self.assertIsInstance(price, PriceSuggestion)
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self.assertEqual(price.currency, "EUR")
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self.assertLess(price.price_min, price.price_max)
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def test_condition_scales_price(self):
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good = self.agent.run(_item(score=1.0)).suggested_price
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worn = self.agent.run(_item(score=0.0)).suggested_price
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self.assertGreater(good, worn)
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def test_category_affects_base_price(self):
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headphones = self.agent.run(_item(category="Kopfhörer")).suggested_price
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unknown = self.agent.run(_item(category="Irgendwas")).suggested_price
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self.assertGreater(headphones, unknown)
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if __name__ == "__main__":
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unittest.main()
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