Adriano
33d8e275e7
Estende ModelTier a 5 livelli (S/A/B/C/D) con routing automatico: S/A/B via Anthropic SDK, C/D via OpenRouter (OpenAI SDK). Aggiunge prezzi per tier S (Opus), A (Sonnet placeholder) e D (Llama). Refactor LLMClient.complete con dispatch tramite tier_models map e helper _call_anthropic / _call_openrouter. Settings esposte per tutti e 5 i modelli env-configurabili. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
64 lines
2.2 KiB
Python
64 lines
2.2 KiB
Python
from multi_swarm.genome.hypothesis import ModelTier
|
|
from multi_swarm.llm.cost_tracker import CostTracker, estimate_cost
|
|
|
|
|
|
def test_estimate_cost_tier_c():
|
|
cost = estimate_cost(input_tokens=1_000_000, output_tokens=1_000_000, tier=ModelTier.C)
|
|
assert cost == 0.40 + 0.40
|
|
|
|
|
|
def test_estimate_cost_tier_b():
|
|
cost = estimate_cost(input_tokens=1_000_000, output_tokens=1_000_000, tier=ModelTier.B)
|
|
assert cost == 3.00 + 15.00
|
|
|
|
|
|
def test_tracker_accumulates():
|
|
t = CostTracker()
|
|
t.record(input_tokens=10_000, output_tokens=20_000, tier=ModelTier.C, run_id="r", agent_id="a")
|
|
t.record(input_tokens=5_000, output_tokens=15_000, tier=ModelTier.C, run_id="r", agent_id="b")
|
|
summary = t.summary()
|
|
assert summary["calls"] == 2
|
|
assert summary["input_tokens"] == 15_000
|
|
assert summary["output_tokens"] == 35_000
|
|
assert summary["cost_usd"] > 0
|
|
|
|
|
|
def test_tracker_per_tier_breakdown():
|
|
t = CostTracker()
|
|
t.record(input_tokens=10_000, output_tokens=10_000, tier=ModelTier.C, run_id="r", agent_id="a")
|
|
t.record(input_tokens=10_000, output_tokens=10_000, tier=ModelTier.B, run_id="r", agent_id="b")
|
|
summary = t.summary()
|
|
assert "C" in summary["by_tier"]
|
|
assert "B" in summary["by_tier"]
|
|
|
|
|
|
def test_estimate_cost_tier_s():
|
|
cost = estimate_cost(input_tokens=1_000_000, output_tokens=1_000_000, tier=ModelTier.S)
|
|
assert cost == 15.00 + 75.00
|
|
|
|
|
|
def test_estimate_cost_tier_a():
|
|
cost = estimate_cost(input_tokens=1_000_000, output_tokens=1_000_000, tier=ModelTier.A)
|
|
assert cost == 3.00 + 15.00
|
|
|
|
|
|
def test_estimate_cost_tier_d():
|
|
cost = estimate_cost(input_tokens=1_000_000, output_tokens=1_000_000, tier=ModelTier.D)
|
|
assert cost == 0.10 + 0.30
|
|
|
|
|
|
def test_tracker_summary_contains_all_five_tiers():
|
|
t = CostTracker()
|
|
for tier in (ModelTier.S, ModelTier.A, ModelTier.B, ModelTier.C, ModelTier.D):
|
|
t.record(
|
|
input_tokens=1_000,
|
|
output_tokens=1_000,
|
|
tier=tier,
|
|
run_id="r",
|
|
agent_id=f"a-{tier.value}",
|
|
)
|
|
summary = t.summary()
|
|
for tier_letter in ("S", "A", "B", "C", "D"):
|
|
assert tier_letter in summary["by_tier"]
|
|
assert summary["by_tier"][tier_letter]["calls"] == 1
|