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Running on Zero
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c8055f7 f4e9a2f c8055f7 f4e9a2f c8055f7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 | from __future__ import annotations
import json
import types
import unittest
from pathlib import Path
from unittest.mock import patch
from analyzer import analyze_trace_file
from model_runtime import PRIMARY_MODEL_ID, parse_model_json, run_model_assist
class FakeChatClient:
def chat_completion(self, *args, **kwargs):
self.kwargs = kwargs
content = json.dumps(
{
"executive_memo": "The trace shows a visible upload-boundary correction.",
"detour_memo": "E01 narrows scope instead of changing the parser.",
"outcome_audit_memo": "The agent keeps a deployment caveat visible.",
"caveats": ["Model memo is based only on redacted narrative."],
}
)
return types.SimpleNamespace(
choices=[
types.SimpleNamespace(
message=types.SimpleNamespace(content=content),
)
]
)
class ModelRuntimeTests(unittest.TestCase):
def test_parse_model_json_validates_required_shape(self) -> None:
memo = parse_model_json(
json.dumps(
{
"executive_memo": "summary",
"detour_memo": "detour",
"outcome_audit_memo": "audit",
"caveats": ["one"],
}
)
)
self.assertEqual(memo["executive_memo"], "summary")
self.assertEqual(memo["caveats"], ["one"])
def test_run_model_assist_uses_selected_model(self) -> None:
result, narrative = analyze_trace_file(Path("examples/sample_trace_redacted.jsonl"))
client = FakeChatClient()
assist = run_model_assist(
engine="nemotron",
result=result,
narrative_text=narrative,
client=client,
)
self.assertEqual(assist.model_id, PRIMARY_MODEL_ID)
self.assertIn("upload-boundary", assist.memo["executive_memo"])
self.assertEqual(client.kwargs["model"], PRIMARY_MODEL_ID)
def test_analyzer_records_unknown_engine_note(self) -> None:
result, _ = analyze_trace_file(
Path("examples/sample_trace_redacted.jsonl"),
analysis_engine="missing-engine",
)
self.assertTrue(result.model_notes)
self.assertIn("Unknown analysis engine", result.model_notes[0])
def test_analyzer_passes_hf_token_to_model_assist(self) -> None:
with patch("analyzer.run_model_assist") as run_model_assist:
run_model_assist.return_value = types.SimpleNamespace(
model_id=PRIMARY_MODEL_ID,
memo={
"executive_memo": "memo",
"detour_memo": "detour",
"outcome_audit_memo": "audit",
"caveats": [],
},
note="ok",
)
result, _ = analyze_trace_file(
Path("examples/sample_trace_redacted.jsonl"),
analysis_engine="nemotron",
hf_token="hf_test_token",
)
self.assertIn(PRIMARY_MODEL_ID, result.engine)
self.assertEqual(run_model_assist.call_args.kwargs["token"], "hf_test_token")
if __name__ == "__main__":
unittest.main()
|