Source identity
| Field | Recorded value |
|---|---|
| Source type | GitHub source |
| Original record | Janady13/AI_Brain / tests/test_quantum_harness.py |
| Date | Not specified in source |
| Repository | Janady13/AI_Brain |
| Revision | 5cd0bbf744b0aee9445913337e852889d9a8098e |
| Branch | codex/build-online-github-ani-7v4kug |
| Path or archive member | tests/test_quantum_harness.py |
| Original SHA-256 | b3dd916010480a9dd7096b8374149a03596980d7d550f6eb68fd989442f83f8d |
| Git blob SHA | 72fb71f5659f48a038f18ec34a9947e0b13ef20c |
| Reading-copy SHA-256 | b3dd916010480a9dd7096b8374149a03596980d7d550f6eb68fd989442f83f8d |
Recovered source transcript
Download complete source text ↓41 lines · 1.6 KB
from services.quantum_harness import QuantumDeploymentHarness
from services.seeder_api.intelligence import (
MarketingIntelligenceEngine,
MiniQuantumSimulator,
QuantumSimulationProcess,
)
def test_quantum_deployment_harness_runs_without_monte_carlo():
engine = MarketingIntelligenceEngine.from_file()
prompt = "Quantum stress for payments and growth"
ranked = engine.recommend_statistical(prompt, limit=2)
simulator = MiniQuantumSimulator(shots=512)
process = QuantumSimulationProcess(simulator=simulator)
plan = process.plans(prompt, ranked, limit=1)[0]
harness = QuantumDeploymentHarness(simulator=simulator)
result = harness.stress(plan, nodes=3, iterations=2, shots=256, monte_carlo=False)
assert result["summary"]["average_agents_supported"] >= 1
assert result["summary"]["peak_nodes_required"] >= 1
assert isinstance(result["summary"]["sustained_operation"], bool)
assert result["plan"]["simulator"] == plan.simulator
def test_quantum_deployment_harness_supports_monte_carlo():
engine = MarketingIntelligenceEngine.from_file()
prompt = "Quantum monte carlo trial"
ranked = engine.recommend_statistical(prompt, limit=2)
simulator = MiniQuantumSimulator(shots=128)
process = QuantumSimulationProcess(simulator=simulator)
plan = process.plans(prompt, ranked, limit=1)[0]
harness = QuantumDeploymentHarness(simulator=simulator)
result = harness.stress(plan, nodes=2, iterations=1, shots=64, monte_carlo=True)
assert result["summary"]["average_agents_supported"] >= 1
assert result["summary"]["peak_nodes_required"] >= 1