generated from coulomb/repo-seed
55 lines
1.7 KiB
Python
55 lines
1.7 KiB
Python
import json
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from datetime import datetime, timezone
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from llm_connect.cli import main
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from llm_connect.quality import QualityLedger, QualityObservation
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def test_rates_show_json_outputs_default_registry(capsys):
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assert main(["rates", "show", "--json"]) == 0
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payload = json.loads(capsys.readouterr().out)
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assert payload["openai/gpt-4o-mini"]["prompt_per_1k"] == 0.00015
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def test_classes_show_lists_builtins(capsys):
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assert main(["classes", "show"]) == 0
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output = capsys.readouterr().out
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assert "chunk-summarization" in output
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assert "entity-extraction" in output
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def test_classes_fit_reads_quality_ledger(tmp_path, capsys):
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ledger = QualityLedger(tmp_path / "quality.jsonl")
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for _ in range(3):
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ledger.append(
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QualityObservation(
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task_type="extract",
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adapter_id="openrouter",
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model_id="openai/gpt-4o-mini",
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cost_usd=0.001,
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quality_score=0.9,
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latency_ms=100,
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tokens_in=500,
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tokens_out=350,
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recorded_at=datetime(2026, 5, 19, tzinfo=timezone.utc),
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tags={
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"problem_class": "entity-extraction",
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"dimensions": {
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"chunk_words": 300,
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"template_words": 100,
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"expected_entities": 5,
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},
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},
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)
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)
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assert main(["classes", "fit", str(ledger.path), "--class", "entity-extraction", "--json"]) == 0
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payload = json.loads(capsys.readouterr().out)
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assert payload["entity-extraction"]["params"]["tokens_per_entity"] == 70
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