64b800c6cf
Items completed: 1. Merged PR #2 (starlette/httpx deps) 2. Fixed async race condition in multimodal_ui.py 3. Wired TTSAdapter (ElevenLabs, Azure) in API routes 4. Moved super_big_brain.py from core/ to reasoning/ (backward compat shim) 5. Added API authentication middleware (Bearer token via FUSIONAGI_API_KEY) 6. Added async adapter interface (acomplete/acomplete_structured) 7. Migrated FastAPI on_event to lifespan (fixes 20 deprecation warnings) 8. Liquid Neural Networks (continuous-time adaptive weights) 9. Quantum-AI Hybrid compute backend (simulator + optimization) 10. Embodied Intelligence / Robotics bridge (actuator + sensor protocols) 11. Consciousness Engineering (formal self-model with introspection) 12. ASI Scoring Rubric (C/A/L/N/R self-assessment harness) 13. GPU integration tests for TensorFlow backend 14. Multi-stage production Dockerfile 15. Gitea CI/CD pipeline (lint, test matrix, Docker build) 16. API rate limiting middleware (per-IP sliding window) 17. OpenAPI docs cleanup (auth + rate limiting descriptions) 18. Benchmarking suite (decomposition, multi-path, recomposition, e2e) 19. Plugin system (head registry for custom heads) 427 tests passing, 0 ruff errors, 0 mypy errors. Co-Authored-By: Nakamoto, S <defi@defi-oracle.io>
114 lines
3.6 KiB
Python
114 lines
3.6 KiB
Python
"""Tests for Quantum-AI Hybrid compute backend."""
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from __future__ import annotations
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import math
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from fusionagi.gpu.quantum_backend import QuantumBackend, QuantumCircuit, Qubit
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class TestQubit:
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def test_initial_state(self) -> None:
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q = Qubit()
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p0, p1 = q.probabilities()
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assert abs(p0 - 1.0) < 1e-10
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assert abs(p1 - 0.0) < 1e-10
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def test_measure_collapses(self) -> None:
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q = Qubit()
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result = q.measure()
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assert result == 0 # |0> always measures 0
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assert abs(q.alpha) == 1.0
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def test_probabilities_sum_to_one(self) -> None:
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q = Qubit(alpha=1 / math.sqrt(2) + 0j, beta=1 / math.sqrt(2) + 0j)
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p0, p1 = q.probabilities()
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assert abs(p0 + p1 - 1.0) < 1e-10
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class TestQuantumCircuit:
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def test_hadamard_creates_superposition(self) -> None:
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circ = QuantumCircuit(num_qubits=1)
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circ.h(0)
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p0, p1 = circ.qubits[0].probabilities()
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assert abs(p0 - 0.5) < 1e-10
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assert abs(p1 - 0.5) < 1e-10
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def test_x_gate_flips(self) -> None:
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circ = QuantumCircuit(num_qubits=1)
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circ.x(0)
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result = circ.qubits[0].measure()
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assert result == 1
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def test_z_gate(self) -> None:
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circ = QuantumCircuit(num_qubits=1)
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circ.z(0)
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p0, p1 = circ.qubits[0].probabilities()
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assert abs(p0 - 1.0) < 1e-10
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def test_ry_rotation(self) -> None:
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circ = QuantumCircuit(num_qubits=1)
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circ.ry(0, math.pi) # Full rotation: |0> -> |1>
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p0, p1 = circ.qubits[0].probabilities()
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assert p1 > 0.99
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def test_measure_all(self) -> None:
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circ = QuantumCircuit(num_qubits=3)
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results = circ.measure_all()
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assert len(results) == 3
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assert all(r in (0, 1) for r in results)
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def test_reset(self) -> None:
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circ = QuantumCircuit(num_qubits=2)
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circ.h(0)
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circ.x(1)
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circ.reset()
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for q in circ.qubits:
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assert abs(q.alpha - 1.0) < 1e-10
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class TestQuantumBackend:
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def test_quantum_sample(self) -> None:
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qb = QuantumBackend(num_qubits=4, num_shots=50)
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samples = qb.quantum_sample([0.5, -0.3, 0.8, 0.1])
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assert len(samples) == 50
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assert all(len(s) == 4 for s in samples)
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assert all(bit in (0, 1) for s in samples for bit in s)
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def test_quantum_sample_custom_shots(self) -> None:
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qb = QuantumBackend(num_qubits=2)
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samples = qb.quantum_sample([0.5, 0.5], num_samples=10)
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assert len(samples) == 10
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def test_quantum_optimize(self) -> None:
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qb = QuantumBackend()
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def cost_fn(params: list[float]) -> float:
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return sum((p - 0.5) ** 2 for p in params)
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result = qb.quantum_optimize(cost_fn, num_params=3, max_iterations=20)
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assert "best_cost" in result
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assert "best_params" in result
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assert result["best_cost"] <= cost_fn([0.0] * 3)
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def test_quantum_similarity_same_vector(self) -> None:
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qb = QuantumBackend()
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sim = qb.quantum_similarity([1.0, 0.0, 0.0], [1.0, 0.0, 0.0])
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assert sim > 0.9
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def test_quantum_similarity_orthogonal(self) -> None:
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qb = QuantumBackend()
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sim = qb.quantum_similarity([1.0, 0.0], [0.0, 1.0])
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assert sim < 0.6
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def test_quantum_similarity_empty(self) -> None:
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qb = QuantumBackend()
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assert qb.quantum_similarity([], []) == 0.0
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def test_get_summary(self) -> None:
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qb = QuantumBackend(num_qubits=6, num_shots=200)
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summary = qb.get_summary()
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assert summary["type"] == "QuantumBackend"
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assert summary["num_qubits"] == 6
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assert summary["backend"] == "simulator"
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