Add o3-pro model support and extend test coverage

- Added o3-pro model configuration to custom_models.json with 200K context
- Updated OpenAI provider to support o3-pro with fixed temperature constraint
- Extended simulator tests to include o3-pro validation scenarios

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

conf/custom_models.json

@@ -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"],

config.py

@@ -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)

providers/openai.py

@@ -22,6 +22,10 @@ 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,
@@ -54,8 +58,13 @@ class OpenAIModelProvider(OpenAICompatibleProvider):
         config = self.SUPPORTED_MODELS[resolved_name]
 
         # Define temperature constraints per model
+<<<<<<< HEAD
         if resolved_name in ["o3", "o3-mini", "o4-mini", "o4-mini-high"]:
             # O3 and O4 reasoning models only support temperature=1.0
+=======
+        if model_name in ["o3", "o3-mini", "o3-pro"]:
+            # O3 models only support temperature=1.0
+>>>>>>> 155c4ec (Add o3-pro model support and extend test coverage)
             temp_constraint = FixedTemperatureConstraint(1.0)
         else:
             # Other OpenAI models support 0.0-2.0 range

simulator_tests/test_o3_model_selection.py

@@ -125,6 +125,24 @@ 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 3: Another tool with O3 to ensure it works across tools
             self.logger.info("  3: Testing O3 with different tool (codereview)")
 
@@ -177,11 +195,11 @@ 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)
+            # Validation criteria - we expect 4 OpenAI calls (3 chat + 1 codereview)
+            openai_api_called = len(openai_api_logs) >= 4  # Should see 4 OpenAI API calls
+            openai_model_usage = len(openai_model_logs) >= 4  # Should see 4 model usage logs
+            openai_responses_received = len(openai_response_logs) >= 4  # Should see 4 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) >= 1  # Should see 1 codereview call
 
             self.logger.info(f"   OpenAI API call logs: {len(openai_api_logs)}")
@@ -272,6 +290,24 @@ 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 3: Codereview with O3 via OpenRouter
             self.logger.info("  3: Testing O3 with codereview tool via OpenRouter")
 
@@ -325,8 +361,8 @@ 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) >= 4 or len(openrouter_model_logs) >= 4
+            all_calls_succeeded = response1 and response2 and response2_5 and response3
 
             success_criteria = [
                 ("All O3 model calls succeeded", all_calls_succeeded),

tests/test_auto_mode.py

@@ -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 +225,7 @@ 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