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chore: import upstream snapshot with attribution
2026-07-13 12:03:20 +08:00

315 lines
12 KiB
Python

"""Tests for the model registry and capabilities database."""
from __future__ import annotations
from unittest.mock import patch
import pytest
from headroom.models import (
ModelInfo,
ModelRegistry,
get_model_info,
list_models,
register_model,
)
class TestModelInfo:
"""Tests for ModelInfo dataclass."""
def test_default_values(self):
"""Test default values."""
info = ModelInfo(name="test", provider="test-provider")
assert info.context_window == 128000
assert info.max_output_tokens == 4096
assert info.supports_tools is True
assert info.supports_vision is False
assert info.supports_streaming is True
def test_custom_values(self):
"""Test custom values."""
info = ModelInfo(
name="custom-model",
provider="custom",
context_window=32000,
max_output_tokens=8192,
supports_tools=False,
supports_vision=True,
)
assert info.context_window == 32000
assert info.max_output_tokens == 8192
assert info.supports_tools is False
assert info.supports_vision is True
def test_frozen(self):
"""Test that ModelInfo is frozen (immutable)."""
info = ModelInfo(name="test", provider="test")
with pytest.raises(AttributeError):
info.name = "changed"
class TestModelRegistry:
"""Tests for ModelRegistry."""
def test_get_openai_model(self):
"""Test getting OpenAI model info."""
info = ModelRegistry.get("gpt-4o")
assert info is not None
assert info.provider == "openai"
assert info.context_window == 128000
def test_get_anthropic_model(self):
"""Test getting Anthropic model info."""
info = ModelRegistry.get("claude-3-5-sonnet-20241022")
assert info is not None
assert info.provider == "anthropic"
assert info.context_window == 200000
def test_get_google_model(self):
"""Test getting Google model info."""
info = ModelRegistry.get("gemini-1.5-pro")
assert info is not None
assert info.provider == "google"
assert info.context_window == 2000000 # 2M!
def test_get_by_alias(self):
"""Test getting model by alias."""
info = ModelRegistry.get("gpt-4o-2024-11-20")
assert info is not None
assert info.name == "gpt-4o"
def test_get_unknown_model(self):
"""Test getting unknown model returns None."""
info = ModelRegistry.get("unknown-model-xyz")
assert info is None
def test_get_prefix_matching(self):
"""Test prefix matching for versioned models."""
info = ModelRegistry.get("gpt-4o-new-version")
assert info is not None
assert info.name == "gpt-4o"
def test_get_prefix_matching_prefers_longest_registered_name(self):
"""`gpt-4-32k-0613` must resolve to `gpt-4-32k` (32768), not the
shorter `gpt-4` (8192) that is registered first."""
info = ModelRegistry.get("gpt-4-32k-0613")
assert info is not None
assert info.name == "gpt-4-32k"
assert ModelRegistry.get_context_limit("gpt-4-32k-0613") == 32768
def test_get_prefix_matching_requires_version_boundary(self):
"""`gpt-4.1`/`gpt-4.5` are distinct models, not variants of `gpt-4`.
A `.`-separated suffix must not match `gpt-4`, so they no longer
inherit gpt-4's 8192-token window (they fall back to the default)."""
assert ModelRegistry.get("gpt-4.1") is None
assert ModelRegistry.get("gpt-4.5-preview") is None
# Not silently reported as an 8192-token model:
assert ModelRegistry.get_context_limit("gpt-4.1") != 8192
assert ModelRegistry.get_context_limit("gpt-4.1", default=100) == 100
def test_resolve_future_google_family_fallback(self):
"""Resolve should return provider-scoped fallbacks for plausible future models."""
with patch("headroom.models.registry.get_model_pricing", return_value=None):
info = ModelRegistry.resolve("gemini-3-pro-preview", provider="google")
assert info is not None
assert info.provider == "google"
assert info.context_window == 1000000
assert info.tokenizer_backend == "google"
def test_resolve_google_litellm_prefixed_family_fallback(self):
"""Resolve should support LiteLLM-style Gemini provider prefixes."""
with patch("headroom.models.registry.get_model_pricing", return_value=None):
info = ModelRegistry.resolve("gemini/gemini-3-pro-preview", provider="google")
assert info is not None
assert info.provider == "google"
assert info.context_window == 1000000
assert info.tokenizer_backend == "google"
def test_resolve_does_not_claim_unrelated_models_for_google(self):
"""Provider-scoped resolution should not mask unrelated model catalogs."""
assert ModelRegistry.resolve("not-a-google-model", provider="google") is None
assert ModelRegistry.resolve("gpt-4o", provider="google") is None
def test_register_custom_model(self):
"""Test registering custom model."""
info = ModelRegistry.register(
"my-custom-model",
provider="custom",
context_window=64000,
supports_vision=True,
)
assert info.name == "my-custom-model"
assert info.provider == "custom"
assert info.context_window == 64000
# Should be retrievable
retrieved = ModelRegistry.get("my-custom-model")
assert retrieved is not None
assert retrieved.context_window == 64000
def test_list_models_all(self):
"""Test listing all models."""
models = ModelRegistry.list_models()
assert len(models) > 0
def test_list_models_by_provider(self):
"""Test listing models by provider."""
openai_models = ModelRegistry.list_models(provider="openai")
assert len(openai_models) > 0
assert all(m.provider == "openai" for m in openai_models)
def test_list_models_with_tools(self):
"""Test listing models with tool support."""
models = ModelRegistry.list_models(supports_tools=True)
assert len(models) > 0
assert all(m.supports_tools for m in models)
def test_list_models_with_vision(self):
"""Test listing models with vision support."""
models = ModelRegistry.list_models(supports_vision=True)
assert len(models) > 0
assert all(m.supports_vision for m in models)
def test_list_models_min_context(self):
"""Test listing models with minimum context."""
models = ModelRegistry.list_models(min_context=1000000)
assert len(models) > 0
assert all(m.context_window >= 1000000 for m in models)
def test_list_providers(self):
"""Test listing all providers."""
providers = ModelRegistry.list_providers()
assert "openai" in providers
assert "anthropic" in providers
assert "google" in providers
def test_get_context_limit(self):
"""Test getting context limit."""
limit = ModelRegistry.get_context_limit("gpt-4o")
assert limit == 128000
def test_get_context_limit_unknown(self):
"""Test getting context limit for unknown model."""
limit = ModelRegistry.get_context_limit("unknown", default=32000)
assert limit == 32000
def test_estimate_cost(self):
"""Test cost estimation."""
cost = ModelRegistry.estimate_cost(
model="gpt-4o",
input_tokens=1000000,
output_tokens=500000,
)
assert cost is not None
# GPT-4o: $2.50/1M input + $10.00/1M output * 0.5 = $2.50 + $5.00 = $7.50
assert abs(cost - 7.50) < 0.01
def test_estimate_cost_with_cache(self):
"""Test cost estimation with cached tokens.
Note: LiteLLM's basic cost estimation doesn't support cached token pricing.
The cached_tokens parameter is accepted but not currently factored into cost.
"""
cost = ModelRegistry.estimate_cost(
model="gpt-4o",
input_tokens=1000000,
output_tokens=0,
cached_tokens=500000, # Not currently used by LiteLLM
)
assert cost is not None
# With LiteLLM, all 1M tokens are charged at input rate: $2.50
assert abs(cost - 2.50) < 0.01
def test_estimate_cost_unknown_model(self):
"""Test cost estimation for unknown model."""
cost = ModelRegistry.estimate_cost(
model="unknown-model",
input_tokens=1000,
output_tokens=500,
)
assert cost is None
class TestConvenienceFunctions:
"""Tests for convenience functions."""
def test_get_model_info(self):
"""Test get_model_info function."""
info = get_model_info("gpt-4o")
assert info is not None
assert info.name == "gpt-4o"
def test_list_models(self):
"""Test list_models function."""
models = list_models(provider="anthropic")
assert len(models) > 0
def test_register_model(self):
"""Test register_model function."""
info = register_model(
"test-function-model",
provider="test",
context_window=16000,
)
assert info.name == "test-function-model"
class TestBuiltInModels:
"""Tests for built-in model data."""
def test_gpt4o_info(self):
"""Test GPT-4o model info."""
info = get_model_info("gpt-4o")
assert info.provider == "openai"
assert info.context_window == 128000
assert info.supports_tools is True
assert info.supports_vision is True
# Pricing is now fetched from LiteLLM, not stored in ModelInfo
pricing = ModelRegistry.get_pricing("gpt-4o")
assert pricing is not None
assert pricing[0] == 2.50 # input cost per 1M
assert pricing[1] == 10.00 # output cost per 1M
def test_o1_info(self):
"""Test o1 model info."""
info = get_model_info("o1")
assert info.provider == "openai"
assert info.context_window == 200000 # 200K context
assert info.max_output_tokens == 100000 # 100K output
def test_claude_info(self):
"""Test Claude model info."""
info = get_model_info("claude-3-5-sonnet-20241022")
assert info.provider == "anthropic"
assert info.context_window == 200000
# Pricing fetched from LiteLLM (falls back to alias for retired models)
pricing = ModelRegistry.get_pricing("claude-sonnet-4-20250514")
assert pricing is not None
assert pricing[0] == 3.00 # input cost per 1M
assert pricing[1] == 15.00 # output cost per 1M
# Retired model alias should also resolve
alias_pricing = ModelRegistry.get_pricing("claude-3-5-sonnet-20241022")
assert alias_pricing is not None
def test_gemini_info(self):
"""Test Gemini model info."""
info = get_model_info("gemini-1.5-pro")
assert info.provider == "google"
assert info.context_window == 2000000 # 2M tokens!
def test_llama_info(self):
"""Test Llama model info."""
info = get_model_info("llama-3.1-8b")
assert info.provider == "meta"
assert info.context_window == 128000
assert info.tokenizer_backend == "huggingface"
def test_mistral_info(self):
"""Test Mistral model info."""
info = get_model_info("mistral-large")
assert info.provider == "mistral"
assert info.supports_tools is True