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Support for allowed model restrictions per provider

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Tool escalation added to `analyze` to a graceful switch over to codereview is made when absolutely necessary
This commit is contained in:
Fahad
2025-06-14 10:56:53 +04:00
parent ac9c58ce61
commit 23353734cd
14 changed files with 1037 additions and 79 deletions
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152
tests/test_per_tool_model_defaults.py
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@@ -75,57 +75,125 @@ class TestModelSelection:
def test_extended_reasoning_with_openai(self):
"""Test EXTENDED_REASONING prefers o3 when OpenAI is available."""
with patch.object(ModelProviderRegistry, "get_provider") as mock_get_provider:
# Mock OpenAI available
mock_get_provider.side_effect = lambda ptype: MagicMock() if ptype == ProviderType.OPENAI else None
with patch.object(ModelProviderRegistry, "get_available_models") as mock_get_available:
# Mock OpenAI models available
mock_get_available.return_value = {
"o3": ProviderType.OPENAI,
"o3-mini": ProviderType.OPENAI,
"o4-mini": ProviderType.OPENAI,
}
model = ModelProviderRegistry.get_preferred_fallback_model(ToolModelCategory.EXTENDED_REASONING)
assert model == "o3"
def test_extended_reasoning_with_gemini_only(self):
"""Test EXTENDED_REASONING prefers pro when only Gemini is available."""
with patch.object(ModelProviderRegistry, "get_provider") as mock_get_provider:
# Mock only Gemini available
mock_get_provider.side_effect = lambda ptype: MagicMock() if ptype == ProviderType.GOOGLE else None
with patch.object(ModelProviderRegistry, "get_available_models") as mock_get_available:
# Mock only Gemini models available
mock_get_available.return_value = {
"gemini-2.5-pro-preview-06-05": ProviderType.GOOGLE,
"gemini-2.5-flash-preview-05-20": ProviderType.GOOGLE,
}
model = ModelProviderRegistry.get_preferred_fallback_model(ToolModelCategory.EXTENDED_REASONING)
assert model == "pro"
# Should find the pro model for extended reasoning
assert "pro" in model or model == "gemini-2.5-pro-preview-06-05"
def test_fast_response_with_openai(self):
"""Test FAST_RESPONSE prefers o3-mini when OpenAI is available."""
with patch.object(ModelProviderRegistry, "get_provider") as mock_get_provider:
# Mock OpenAI available
mock_get_provider.side_effect = lambda ptype: MagicMock() if ptype == ProviderType.OPENAI else None
"""Test FAST_RESPONSE prefers o4-mini when OpenAI is available."""
with patch.object(ModelProviderRegistry, "get_available_models") as mock_get_available:
# Mock OpenAI models available
mock_get_available.return_value = {
"o3": ProviderType.OPENAI,
"o3-mini": ProviderType.OPENAI,
"o4-mini": ProviderType.OPENAI,
}
model = ModelProviderRegistry.get_preferred_fallback_model(ToolModelCategory.FAST_RESPONSE)
assert model == "o3-mini"
assert model == "o4-mini"
def test_fast_response_with_gemini_only(self):
"""Test FAST_RESPONSE prefers flash when only Gemini is available."""
with patch.object(ModelProviderRegistry, "get_provider") as mock_get_provider:
# Mock only Gemini available
mock_get_provider.side_effect = lambda ptype: MagicMock() if ptype == ProviderType.GOOGLE else None
with patch.object(ModelProviderRegistry, "get_available_models") as mock_get_available:
# Mock only Gemini models available
mock_get_available.return_value = {
"gemini-2.5-pro-preview-06-05": ProviderType.GOOGLE,
"gemini-2.5-flash-preview-05-20": ProviderType.GOOGLE,
}
model = ModelProviderRegistry.get_preferred_fallback_model(ToolModelCategory.FAST_RESPONSE)
assert model == "flash"
# Should find the flash model for fast response
assert "flash" in model or model == "gemini-2.5-flash-preview-05-20"
def test_balanced_category_fallback(self):
"""Test BALANCED category uses existing logic."""
with patch.object(ModelProviderRegistry, "get_provider") as mock_get_provider:
# Mock OpenAI available
mock_get_provider.side_effect = lambda ptype: MagicMock() if ptype == ProviderType.OPENAI else None
with patch.object(ModelProviderRegistry, "get_available_models") as mock_get_available:
# Mock OpenAI models available
mock_get_available.return_value = {
"o3": ProviderType.OPENAI,
"o3-mini": ProviderType.OPENAI,
"o4-mini": ProviderType.OPENAI,
}
model = ModelProviderRegistry.get_preferred_fallback_model(ToolModelCategory.BALANCED)
assert model == "o3-mini" # Balanced prefers o3-mini when OpenAI available
assert model == "o4-mini" # Balanced prefers o4-mini when OpenAI available
def test_no_category_uses_balanced_logic(self):
"""Test that no category specified uses balanced logic."""
with patch.object(ModelProviderRegistry, "get_provider") as mock_get_provider:
# Mock Gemini available
mock_get_provider.side_effect = lambda ptype: MagicMock() if ptype == ProviderType.GOOGLE else None
with patch.object(ModelProviderRegistry, "get_available_models") as mock_get_available:
# Mock only Gemini models available
mock_get_available.return_value = {
"gemini-2.5-pro-preview-06-05": ProviderType.GOOGLE,
"gemini-2.5-flash-preview-05-20": ProviderType.GOOGLE,
}
model = ModelProviderRegistry.get_preferred_fallback_model()
assert model == "gemini-2.5-flash-preview-05-20"
# Should pick a reasonable default, preferring flash for balanced use
assert "flash" in model or model == "gemini-2.5-flash-preview-05-20"
class TestFlexibleModelSelection:
"""Test that model selection handles various naming scenarios."""
def test_fallback_handles_mixed_model_names(self):
"""Test that fallback selection works with mix of full names and shorthands."""
# Test with mix of full names and shorthands
test_cases = [
# Case 1: Mix of OpenAI shorthands and full names
{
"available": {"o3": ProviderType.OPENAI, "o4-mini": ProviderType.OPENAI},
"category": ToolModelCategory.EXTENDED_REASONING,
"expected": "o3",
},
# Case 2: Mix of Gemini shorthands and full names
{
"available": {
"gemini-2.5-flash-preview-05-20": ProviderType.GOOGLE,
"gemini-2.5-pro-preview-06-05": ProviderType.GOOGLE,
},
"category": ToolModelCategory.FAST_RESPONSE,
"expected_contains": "flash",
},
# Case 3: Only shorthands available
{
"available": {"o4-mini": ProviderType.OPENAI, "o3-mini": ProviderType.OPENAI},
"category": ToolModelCategory.FAST_RESPONSE,
"expected": "o4-mini",
},
]
for case in test_cases:
with patch.object(ModelProviderRegistry, "get_available_models") as mock_get_available:
mock_get_available.return_value = case["available"]
model = ModelProviderRegistry.get_preferred_fallback_model(case["category"])
if "expected" in case:
assert model == case["expected"], f"Failed for case: {case}"
elif "expected_contains" in case:
assert (
case["expected_contains"] in model
), f"Expected '{case['expected_contains']}' in '{model}' for case: {case}"
class TestCustomProviderFallback:
@@ -163,34 +231,45 @@ class TestAutoModeErrorMessages:
"""Test ThinkDeep tool suggests appropriate model in auto mode."""
with patch("config.IS_AUTO_MODE", True):
with patch("config.DEFAULT_MODEL", "auto"):
with patch.object(ModelProviderRegistry, "get_provider") as mock_get_provider:
# Mock Gemini available
mock_get_provider.side_effect = lambda ptype: MagicMock() if ptype == ProviderType.GOOGLE else None
with patch.object(ModelProviderRegistry, "get_available_models") as mock_get_available:
# Mock only Gemini models available
mock_get_available.return_value = {
"gemini-2.5-pro-preview-06-05": ProviderType.GOOGLE,
"gemini-2.5-flash-preview-05-20": ProviderType.GOOGLE,
}
tool = ThinkDeepTool()
result = await tool.execute({"prompt": "test", "model": "auto"})
assert len(result) == 1
assert "Model parameter is required in auto mode" in result[0].text
assert "Suggested model for thinkdeep: 'pro'" in result[0].text
assert "(category: extended_reasoning)" in result[0].text
# Should suggest a model suitable for extended reasoning (either full name or with 'pro')
response_text = result[0].text
assert "gemini-2.5-pro-preview-06-05" in response_text or "pro" in response_text
assert "(category: extended_reasoning)" in response_text
@pytest.mark.asyncio
async def test_chat_auto_error_message(self):
"""Test Chat tool suggests appropriate model in auto mode."""
with patch("config.IS_AUTO_MODE", True):
with patch("config.DEFAULT_MODEL", "auto"):
with patch.object(ModelProviderRegistry, "get_provider") as mock_get_provider:
# Mock OpenAI available
mock_get_provider.side_effect = lambda ptype: MagicMock() if ptype == ProviderType.OPENAI else None
with patch.object(ModelProviderRegistry, "get_available_models") as mock_get_available:
# Mock OpenAI models available
mock_get_available.return_value = {
"o3": ProviderType.OPENAI,
"o3-mini": ProviderType.OPENAI,
"o4-mini": ProviderType.OPENAI,
}
tool = ChatTool()
result = await tool.execute({"prompt": "test", "model": "auto"})
assert len(result) == 1
assert "Model parameter is required in auto mode" in result[0].text
assert "Suggested model for chat: 'o3-mini'" in result[0].text
assert "(category: fast_response)" in result[0].text
# Should suggest a model suitable for fast response
response_text = result[0].text
assert "o4-mini" in response_text or "o3-mini" in response_text or "mini" in response_text
assert "(category: fast_response)" in response_text
class TestFileContentPreparation:
@@ -218,7 +297,10 @@ class TestFileContentPreparation:
# Check that it logged the correct message
debug_calls = [call for call in mock_logger.debug.call_args_list if "Auto mode detected" in str(call)]
assert len(debug_calls) > 0
assert "using pro for extended_reasoning tool capacity estimation" in str(debug_calls[0])
debug_message = str(debug_calls[0])
# Should use a model suitable for extended reasoning
assert "gemini-2.5-pro-preview-06-05" in debug_message or "pro" in debug_message
assert "extended_reasoning" in debug_message
class TestProviderHelperMethods: