Files
langchain/libs/model-profiles/tests/unit_tests/test_cli.py
Mason Daugherty 5d9568b5f5 feat(model-profiles): new fields + Makefile target (#35788)
Extract additional fields from models.dev into `_model_data_to_profile`:
`name`, `status`, `release_date`, `last_updated`, `open_weights`,
`attachment`, `temperature`

Move the model profile refresh logic from an inline bash script in the
GitHub Actions workflow into a `make refresh-profiles` target in
`libs/model-profiles/Makefile`. This makes it runnable locally with a
single command and keeps the provider map in one place instead of
duplicated between CI and developer docs.
2026-03-12 13:56:25 +00:00

367 lines
12 KiB
Python

"""Tests for CLI functionality."""
import importlib.util
from pathlib import Path
from unittest.mock import Mock, patch
import pytest
from langchain_model_profiles.cli import _model_data_to_profile, refresh
@pytest.fixture
def mock_models_dev_response() -> dict:
"""Create a mock response from models.dev API."""
return {
"anthropic": {
"id": "anthropic",
"name": "Anthropic",
"models": {
"claude-3-opus": {
"id": "claude-3-opus",
"name": "Claude 3 Opus",
"tool_call": True,
"limit": {"context": 200000, "output": 4096},
"modalities": {"input": ["text", "image"], "output": ["text"]},
},
"claude-3-sonnet": {
"id": "claude-3-sonnet",
"name": "Claude 3 Sonnet",
"tool_call": True,
"limit": {"context": 200000, "output": 4096},
"modalities": {"input": ["text", "image"], "output": ["text"]},
},
},
},
"openai": {
"id": "openai",
"name": "OpenAI",
"models": {
"gpt-4": {
"id": "gpt-4",
"name": "GPT-4",
"tool_call": True,
"limit": {"context": 8192, "output": 4096},
"modalities": {"input": ["text"], "output": ["text"]},
}
},
},
}
def test_refresh_generates_profiles_file(
tmp_path: Path, mock_models_dev_response: dict
) -> None:
"""Test that refresh command generates _profiles.py with merged data."""
data_dir = tmp_path / "data"
data_dir.mkdir()
# Create augmentations file
aug_file = data_dir / "profile_augmentations.toml"
aug_file.write_text("""
provider = "anthropic"
[overrides]
image_url_inputs = true
pdf_inputs = true
""")
# Mock the httpx.get call
mock_response = Mock()
mock_response.json.return_value = mock_models_dev_response
mock_response.raise_for_status = Mock()
with (
patch("langchain_model_profiles.cli.httpx.get", return_value=mock_response),
patch("builtins.input", return_value="y"),
):
refresh("anthropic", data_dir)
# Verify _profiles.py was created
profiles_file = data_dir / "_profiles.py"
assert profiles_file.exists()
# Import and verify content
profiles_content = profiles_file.read_text()
assert "DO NOT EDIT THIS FILE MANUALLY" in profiles_content
assert "PROFILES:" in profiles_content
assert "claude-3-opus" in profiles_content
assert "claude-3-sonnet" in profiles_content
# Check that augmentations were applied
assert "image_url_inputs" in profiles_content
assert "pdf_inputs" in profiles_content
def test_refresh_raises_error_for_missing_provider(
tmp_path: Path, mock_models_dev_response: dict
) -> None:
"""Test that refresh exits with error for non-existent provider."""
data_dir = tmp_path / "data"
data_dir.mkdir()
# Mock the httpx.get call
mock_response = Mock()
mock_response.json.return_value = mock_models_dev_response
mock_response.raise_for_status = Mock()
with (
patch("langchain_model_profiles.cli.httpx.get", return_value=mock_response),
patch("builtins.input", return_value="y"),
):
with pytest.raises(SystemExit) as exc_info:
refresh("nonexistent-provider", data_dir)
assert exc_info.value.code == 1
# Output file should not be created
profiles_file = data_dir / "_profiles.py"
assert not profiles_file.exists()
def test_refresh_works_without_augmentations(
tmp_path: Path, mock_models_dev_response: dict
) -> None:
"""Test that refresh works even without augmentations file."""
data_dir = tmp_path / "data"
data_dir.mkdir()
# Mock the httpx.get call
mock_response = Mock()
mock_response.json.return_value = mock_models_dev_response
mock_response.raise_for_status = Mock()
with (
patch("langchain_model_profiles.cli.httpx.get", return_value=mock_response),
patch("builtins.input", return_value="y"),
):
refresh("anthropic", data_dir)
# Verify _profiles.py was created
profiles_file = data_dir / "_profiles.py"
assert profiles_file.exists()
assert profiles_file.stat().st_size > 0
def test_refresh_aborts_when_user_declines_external_directory(
tmp_path: Path, mock_models_dev_response: dict
) -> None:
"""Test that refresh aborts when user declines writing to external directory."""
data_dir = tmp_path / "data"
data_dir.mkdir()
# Mock the httpx.get call
mock_response = Mock()
mock_response.json.return_value = mock_models_dev_response
mock_response.raise_for_status = Mock()
with (
patch("langchain_model_profiles.cli.httpx.get", return_value=mock_response),
patch("builtins.input", return_value="n"), # User declines
):
with pytest.raises(SystemExit) as exc_info:
refresh("anthropic", data_dir)
assert exc_info.value.code == 1
# Verify _profiles.py was NOT created
profiles_file = data_dir / "_profiles.py"
assert not profiles_file.exists()
def test_refresh_includes_models_defined_only_in_augmentations(
tmp_path: Path, mock_models_dev_response: dict
) -> None:
"""Ensure models that only exist in augmentations are emitted."""
data_dir = tmp_path / "data"
data_dir.mkdir()
aug_file = data_dir / "profile_augmentations.toml"
aug_file.write_text("""
provider = "anthropic"
[overrides."custom-offline-model"]
structured_output = true
pdf_inputs = true
max_input_tokens = 123
""")
mock_response = Mock()
mock_response.json.return_value = mock_models_dev_response
mock_response.raise_for_status = Mock()
with (
patch("langchain_model_profiles.cli.httpx.get", return_value=mock_response),
patch("builtins.input", return_value="y"),
):
refresh("anthropic", data_dir)
profiles_file = data_dir / "_profiles.py"
assert profiles_file.exists()
spec = importlib.util.spec_from_file_location(
"generated_profiles_aug_only", profiles_file
)
assert spec
assert spec.loader
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module) # type: ignore[union-attr]
assert "custom-offline-model" in module._PROFILES # type: ignore[attr-defined]
assert (
module._PROFILES["custom-offline-model"]["structured_output"] is True # type: ignore[index]
)
assert (
module._PROFILES["custom-offline-model"]["max_input_tokens"] == 123 # type: ignore[index]
)
def test_refresh_generates_sorted_profiles(
tmp_path: Path, mock_models_dev_response: dict
) -> None:
"""Test that profiles are sorted alphabetically by model ID."""
data_dir = tmp_path / "data"
data_dir.mkdir()
# Inject models in reverse-alphabetical order so the API response
# is NOT already sorted.
mock_models_dev_response["anthropic"]["models"] = {
"z-model": {
"id": "z-model",
"name": "Z Model",
"tool_call": True,
"limit": {"context": 100000, "output": 2048},
"modalities": {"input": ["text"], "output": ["text"]},
},
"a-model": {
"id": "a-model",
"name": "A Model",
"tool_call": True,
"limit": {"context": 100000, "output": 2048},
"modalities": {"input": ["text"], "output": ["text"]},
},
"m-model": {
"id": "m-model",
"name": "M Model",
"tool_call": True,
"limit": {"context": 100000, "output": 2048},
"modalities": {"input": ["text"], "output": ["text"]},
},
}
mock_response = Mock()
mock_response.json.return_value = mock_models_dev_response
mock_response.raise_for_status = Mock()
with (
patch("langchain_model_profiles.cli.httpx.get", return_value=mock_response),
patch("builtins.input", return_value="y"),
):
refresh("anthropic", data_dir)
profiles_file = data_dir / "_profiles.py"
spec = importlib.util.spec_from_file_location(
"generated_profiles_sorted", profiles_file
)
assert spec
assert spec.loader
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module) # type: ignore[union-attr]
model_ids = list(module._PROFILES.keys()) # type: ignore[attr-defined]
assert model_ids == sorted(model_ids), f"Profile keys are not sorted: {model_ids}"
def test_model_data_to_profile_captures_all_models_dev_fields() -> None:
"""Test that all models.dev fields are captured in the profile."""
model_data = {
"id": "claude-opus-4-6",
"name": "Claude Opus 4.6",
"status": "deprecated",
"release_date": "2025-06-01",
"last_updated": "2025-07-01",
"open_weights": False,
"reasoning": True,
"tool_call": True,
"tool_choice": True,
"structured_output": True,
"attachment": True,
"temperature": True,
"limit": {"context": 200000, "output": 64000},
"modalities": {
"input": ["text", "image", "pdf"],
"output": ["text"],
},
}
profile = _model_data_to_profile(model_data)
# Metadata
assert profile["name"] == "Claude Opus 4.6"
assert profile["status"] == "deprecated"
assert profile["release_date"] == "2025-06-01"
assert profile["last_updated"] == "2025-07-01"
assert profile["open_weights"] is False
# Limits
assert profile["max_input_tokens"] == 200000
assert profile["max_output_tokens"] == 64000
# Capabilities
assert profile["reasoning_output"] is True
assert profile["tool_calling"] is True
assert profile["tool_choice"] is True
assert profile["structured_output"] is True
assert profile["attachment"] is True
# Modalities
assert profile["text_inputs"] is True
assert profile["image_inputs"] is True
assert profile["pdf_inputs"] is True
assert profile["text_outputs"] is True
def test_model_data_to_profile_omits_absent_fields() -> None:
"""Test that fields not present in source data are omitted (not None)."""
minimal = {
"modalities": {"input": ["text"], "output": ["text"]},
"limit": {"context": 8192, "output": 4096},
}
profile = _model_data_to_profile(minimal)
assert "status" not in profile
assert "family" not in profile
assert "knowledge_cutoff" not in profile
assert "cost_input" not in profile
assert "interleaved" not in profile
assert None not in profile.values()
def test_model_data_to_profile_text_modalities() -> None:
"""Test that text input/output modalities are correctly mapped."""
# Model with text in both input and output
model_with_text = {
"modalities": {"input": ["text", "image"], "output": ["text"]},
"limit": {"context": 128000, "output": 4096},
}
profile = _model_data_to_profile(model_with_text)
assert profile["text_inputs"] is True
assert profile["text_outputs"] is True
# Model without text input (e.g., Whisper-like audio model)
audio_only_model = {
"modalities": {"input": ["audio"], "output": ["text"]},
"limit": {"context": 0, "output": 0},
}
profile = _model_data_to_profile(audio_only_model)
assert profile["text_inputs"] is False
assert profile["text_outputs"] is True
# Model without text output (e.g., image generator)
image_gen_model = {
"modalities": {"input": ["text"], "output": ["image"]},
"limit": {},
}
profile = _model_data_to_profile(image_gen_model)
assert profile["text_inputs"] is True
assert profile["text_outputs"] is False