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Merge pull request #36 from lox/add-o3-pro-support

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feat: Add o3-pro model support
This commit is contained in:
Beehive Innovations
2025-06-14 19:44:14 +04:00
committed by GitHub
parent 68a75a7791 40aa1eaeb6
commit 9f973b90e5
5 changed files with 118 additions and 11 deletions
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9
conf/custom_models.json
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@@ -148,6 +148,15 @@
"supports_function_calling": true,
"description": "OpenAI's o3-mini with high reasoning effort - optimized for complex problems"
},
{
"model_name": "openai/o3-pro",
"aliases": ["o3-pro", "o3pro"],
"context_window": 200000,
"supports_extended_thinking": false,
"supports_json_mode": true,
"supports_function_calling": true,
"description": "OpenAI's o3-pro model - professional-grade reasoning and analysis"
},
{
"model_name": "openai/o4-mini",
"aliases": ["o4-mini", "o4mini"],

1
config.py
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@@ -50,6 +50,7 @@ MODEL_CAPABILITIES_DESC = {
# OpenAI models - Available when OPENAI_API_KEY is configured
"o3": "Strong reasoning (200K context) - Logical problems, code generation, systematic analysis",
"o3-mini": "Fast O3 variant (200K context) - Balanced performance/speed, moderate complexity",
"o3-pro": "Professional-grade reasoning (200K context) - EXTREMELY EXPENSIVE: Only for the most complex problems requiring universe-scale complexity analysis OR when the user explicitly asks for this model. Use sparingly for critical architectural decisions or exceptionally complex debugging that other models cannot handle.",
"o4-mini": "Latest reasoning model (200K context) - Optimized for shorter contexts, rapid reasoning",
"o4-mini-high": "Enhanced O4 mini (200K context) - Higher reasoning effort for complex tasks",
# Full model names also supported (for explicit specification)

6
providers/openai.py
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@@ -26,6 +26,10 @@ class OpenAIModelProvider(OpenAICompatibleProvider):
"context_window": 200_000, # 200K tokens
"supports_extended_thinking": False,
},
"o3-pro": {
"context_window": 200_000, # 200K tokens
"supports_extended_thinking": False,
},
"o4-mini": {
"context_window": 200_000, # 200K tokens
"supports_extended_thinking": False,
@@ -66,7 +70,7 @@ class OpenAIModelProvider(OpenAICompatibleProvider):
config = self.SUPPORTED_MODELS[resolved_name]
# Define temperature constraints per model
if resolved_name in ["o3", "o3-mini", "o4-mini", "o4-mini-high"]:
if resolved_name in ["o3", "o3-mini", "o3-pro", "o4-mini", "o4-mini-high"]:
# O3 and O4 reasoning models only support temperature=1.0
temp_constraint = FixedTemperatureConstraint(1.0)
else:

106
simulator_tests/test_o3_model_selection.py
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@@ -125,6 +125,51 @@ class O3ModelSelectionTest(BaseSimulatorTest):
self.logger.info(" ✅ O3-mini model call completed")
# Test 2.5: Explicit O3-pro model selection
self.logger.info(" 2.5: Testing explicit O3-pro model selection")
response2_5, _ = self.call_mcp_tool(
"chat",
{
"prompt": "Simple test: What is 4 + 4? Just give a brief answer.",
"model": "o3-pro",
"temperature": 1.0, # O3-pro only supports default temperature of 1.0
},
)
if not response2_5:
self.logger.error(" ❌ O3-pro model test failed")
return False
self.logger.info(" ✅ O3-pro model call completed")
# Test 2.6: O3-pro with codereview tool
self.logger.info(" 2.6: Testing O3-pro with codereview tool")
test_code_pro = """def calculate_tax(amount, rate):
return amount * rate
def format_currency(value):
return f"${value:.2f}"
"""
test_file_pro = self.create_additional_test_file("tax_calc.py", test_code_pro)
response2_6, _ = self.call_mcp_tool(
"codereview",
{
"files": [test_file_pro],
"prompt": "Quick review of this tax calculation code",
"model": "o3-pro",
"temperature": 1.0, # O3-pro only supports default temperature of 1.0
},
)
if not response2_6:
self.logger.error(" ❌ O3-pro with codereview tool failed")
return False
self.logger.info(" ✅ O3-pro with codereview tool completed")
# Test 3: Another tool with O3 to ensure it works across tools
self.logger.info(" 3: Testing O3 with different tool (codereview)")
@@ -177,12 +222,12 @@ def multiply(x, y):
line for line in logs.split("\n") if "Sending request to openai API for codereview" in line
]
# Validation criteria - we expect 3 OpenAI calls (2 chat + 1 codereview)
openai_api_called = len(openai_api_logs) >= 3 # Should see 3 OpenAI API calls
openai_model_usage = len(openai_model_logs) >= 3 # Should see 3 model usage logs
openai_responses_received = len(openai_response_logs) >= 3 # Should see 3 responses
chat_calls_to_openai = len(chat_openai_logs) >= 2 # Should see 2 chat calls (o3 + o3-mini)
codereview_calls_to_openai = len(codereview_openai_logs) >= 1 # Should see 1 codereview call
# Validation criteria - we expect 5 OpenAI calls (3 chat + 2 codereview)
openai_api_called = len(openai_api_logs) >= 5 # Should see 5 OpenAI API calls
openai_model_usage = len(openai_model_logs) >= 5 # Should see 5 model usage logs
openai_responses_received = len(openai_response_logs) >= 5 # Should see 5 responses
chat_calls_to_openai = len(chat_openai_logs) >= 3 # Should see 3 chat calls (o3 + o3-mini + o3-pro)
codereview_calls_to_openai = len(codereview_openai_logs) >= 2 # Should see 2 codereview calls (o3-pro + o3)
self.logger.info(f" OpenAI API call logs: {len(openai_api_logs)}")
self.logger.info(f" OpenAI model usage logs: {len(openai_model_logs)}")
@@ -272,6 +317,51 @@ def multiply(x, y):
self.logger.info(" ✅ O3-mini model call via OpenRouter completed")
# Test 2.5: O3-pro model via OpenRouter
self.logger.info(" 2.5: Testing O3-pro model via OpenRouter")
response2_5, _ = self.call_mcp_tool(
"chat",
{
"prompt": "Simple test: What is 4 + 4? Just give a brief answer.",
"model": "o3-pro",
"temperature": 1.0,
},
)
if not response2_5:
self.logger.error(" ❌ O3-pro model test via OpenRouter failed")
return False
self.logger.info(" ✅ O3-pro model call via OpenRouter completed")
# Test 2.6: O3-pro with codereview tool via OpenRouter
self.logger.info(" 2.6: Testing O3-pro with codereview tool via OpenRouter")
test_code_pro_or = """def calculate_discount(price, discount_rate):
return price * (1 - discount_rate)
def validate_price(price):
return price > 0
"""
test_file_pro_or = self.create_additional_test_file("discount_calc.py", test_code_pro_or)
response2_6, _ = self.call_mcp_tool(
"codereview",
{
"files": [test_file_pro_or],
"prompt": "Quick review of this discount calculation code",
"model": "o3-pro",
"temperature": 1.0,
},
)
if not response2_6:
self.logger.error(" ❌ O3-pro with codereview tool via OpenRouter failed")
return False
self.logger.info(" ✅ O3-pro with codereview tool via OpenRouter completed")
# Test 3: Codereview with O3 via OpenRouter
self.logger.info(" 3: Testing O3 with codereview tool via OpenRouter")
@@ -325,8 +415,8 @@ def multiply(x, y):
self.logger.info(f" OpenRouter response logs: {len(openrouter_response_logs)}")
# Success criteria for OpenRouter
openrouter_used = len(openrouter_api_logs) >= 3 or len(openrouter_model_logs) >= 3
all_calls_succeeded = response1 and response2 and response3
openrouter_used = len(openrouter_api_logs) >= 5 or len(openrouter_model_logs) >= 5
all_calls_succeeded = response1 and response2 and response2_5 and response2_6 and response3
success_criteria = [
("All O3 model calls succeeded", all_calls_succeeded),

7
tests/test_auto_mode.py
View File

@@ -47,7 +47,7 @@ class TestAutoMode:
from config import MODEL_CAPABILITIES_DESC
# Check all expected models are present
expected_models = ["flash", "pro", "o3", "o3-mini"]
expected_models = ["flash", "pro", "o3", "o3-mini", "o3-pro", "o4-mini", "o4-mini-high"]
for model in expected_models:
assert model in MODEL_CAPABILITIES_DESC
assert isinstance(MODEL_CAPABILITIES_DESC[model], str)
@@ -225,7 +225,10 @@ class TestAutoMode:
schema = tool.get_model_field_schema()
assert "enum" in schema
assert all(model in schema["enum"] for model in ["flash", "pro", "o3"])
assert all(
model in schema["enum"]
for model in ["flash", "pro", "o3", "o3-mini", "o3-pro", "o4-mini", "o4-mini-high"]
)
assert "select the most suitable model" in schema["description"]
# Test normal mode