Ed_
d1ce0eaaeb
- Add cost tracking with new cost_tracker.py module - Enhance Track Proposal modal with editable titles and goals - Add Conductor Setup summary and New Track creation form to MMA Dashboard - Implement Task DAG editing (add/delete tickets) and track-scoped discussion - Add visual polish: color-coded statuses, tinted progress bars, and node indicators - Support live worker streaming from AI providers to GUI panels - Fix numerous integration test regressions and stabilize headless service
31 lines
1.0 KiB
Python
31 lines
1.0 KiB
Python
import cost_tracker
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def test_estimate_cost():
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# Test unknown model
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assert cost_tracker.estimate_cost("unknown-model", 1000, 1000) == 0.0
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# Test empty model
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assert cost_tracker.estimate_cost("", 1000, 1000) == 0.0
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# Test Gemini 3.1 Pro Preview
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# input: 3.50 per M, output: 10.50 per M
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# 1M input + 1M output = 14.00
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cost = cost_tracker.estimate_cost("gemini-3.1-pro-preview", 1_000_000, 1_000_000)
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assert abs(cost - 14.00) < 0.0001
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# Test Claude Sonnet
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# input: 3.0 per M, output: 15.0 per M
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# 100k input + 10k output = 0.3 + 0.15 = 0.45
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cost = cost_tracker.estimate_cost("claude-3-5-sonnet-20241022", 100_000, 10_000)
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assert abs(cost - 0.45) < 0.0001
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# Test DeepSeek V3
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# input: 0.27 per M, output: 1.10 per M
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# 1M input + 1M output = 1.37
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cost = cost_tracker.estimate_cost("deepseek-v3", 1_000_000, 1_000_000)
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assert abs(cost - 1.37) < 0.0001
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if __name__ == "__main__":
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test_estimate_cost()
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print("All cost_tracker tests passed!")
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