Use the new flash model

Updated tests

config.py

@@ -26,7 +26,7 @@ DEFAULT_MODEL = os.getenv("DEFAULT_MODEL", "auto")
 
 # Validate DEFAULT_MODEL and set to "auto" if invalid
 # Only include actually supported models from providers
-VALID_MODELS = ["auto", "flash", "pro", "o3", "o3-mini", "gemini-2.0-flash-exp", "gemini-2.5-pro-preview-06-05"]
+VALID_MODELS = ["auto", "flash", "pro", "o3", "o3-mini", "gemini-2.0-flash", "gemini-2.5-pro-preview-06-05"]
 if DEFAULT_MODEL not in VALID_MODELS:
     import logging
 
@@ -47,7 +47,7 @@ MODEL_CAPABILITIES_DESC = {
     "o3": "Strong reasoning (200K context) - Logical problems, code generation, systematic analysis",
     "o3-mini": "Fast O3 variant (200K context) - Balanced performance/speed, moderate complexity",
     # Full model names also supported
-    "gemini-2.0-flash-exp": "Ultra-fast (1M context) - Quick analysis, simple queries, rapid iterations",
+    "gemini-2.0-flash": "Ultra-fast (1M context) - Quick analysis, simple queries, rapid iterations",
     "gemini-2.5-pro-preview-06-05": "Deep reasoning + thinking mode (1M context) - Complex problems, architecture, deep analysis",
 }
 

providers/gemini.py

@@ -13,7 +13,7 @@ class GeminiModelProvider(ModelProvider):
 
     # Model configurations
     SUPPORTED_MODELS = {
-        "gemini-2.0-flash-exp": {
+        "gemini-2.0-flash": {
             "max_tokens": 1_048_576,  # 1M tokens
             "supports_extended_thinking": False,
         },
@@ -22,7 +22,7 @@ class GeminiModelProvider(ModelProvider):
             "supports_extended_thinking": True,
         },
         # Shorthands
-        "flash": "gemini-2.0-flash-exp",
+        "flash": "gemini-2.0-flash",
         "pro": "gemini-2.5-pro-preview-06-05",
     }
 

providers/registry.py

@@ -67,7 +67,7 @@ class ModelProviderRegistry:
         """Get provider instance for a specific model name.
 
         Args:
-            model_name: Name of the model (e.g., "gemini-2.0-flash-exp", "o3-mini")
+            model_name: Name of the model (e.g., "gemini-2.0-flash", "o3-mini")
 
         Returns:
             ModelProvider instance that supports this model
@@ -125,6 +125,50 @@ class ModelProviderRegistry:
 
         return os.getenv(env_var)
 
+    @classmethod
+    def get_preferred_fallback_model(cls) -> str:
+        """Get the preferred fallback model based on available API keys.
+
+        This method checks which providers have valid API keys and returns
+        a sensible default model for auto mode fallback situations.
+
+        Priority order:
+        1. OpenAI o3-mini (balanced performance/cost) if OpenAI API key available
+        2. Gemini 2.0 Flash (fast and efficient) if Gemini API key available
+        3. OpenAI o3 (high performance) if OpenAI API key available
+        4. Gemini 2.5 Pro (deep reasoning) if Gemini API key available
+        5. Fallback to gemini-2.0-flash (most common case)
+
+        Returns:
+            Model name string for fallback use
+        """
+        # Check provider availability by trying to get instances
+        openai_available = cls.get_provider(ProviderType.OPENAI) is not None
+        gemini_available = cls.get_provider(ProviderType.GOOGLE) is not None
+
+        # Priority order: prefer balanced models first, then high-performance
+        if openai_available:
+            return "o3-mini"  # Balanced performance/cost
+        elif gemini_available:
+            return "gemini-2.0-flash"  # Fast and efficient
+        else:
+            # No API keys available - return a reasonable default
+            # This maintains backward compatibility for tests
+            return "gemini-2.0-flash"
+
+    @classmethod
+    def get_available_providers_with_keys(cls) -> list[ProviderType]:
+        """Get list of provider types that have valid API keys.
+
+        Returns:
+            List of ProviderType values for providers with valid API keys
+        """
+        available = []
+        for provider_type in cls._providers:
+            if cls.get_provider(provider_type) is not None:
+                available.append(provider_type)
+        return available
+
     @classmethod
     def clear_cache(cls) -> None:
         """Clear cached provider instances."""

simulator_tests/test_model_thinking_config.py

@@ -55,7 +55,7 @@ class TestModelThinkingConfig(BaseSimulatorTest):
                 "chat",
                 {
                     "prompt": "What is 3 + 3? Give a quick answer.",
-                    "model": "flash",  # Should resolve to gemini-2.0-flash-exp
+                    "model": "flash",  # Should resolve to gemini-2.0-flash
                     "thinking_mode": "high",  # Should be ignored for Flash model
                 },
             )
@@ -80,7 +80,7 @@ class TestModelThinkingConfig(BaseSimulatorTest):
             ("pro", "should work with Pro model"),
             ("flash", "should work with Flash model"),
             ("gemini-2.5-pro-preview-06-05", "should work with full Pro model name"),
-            ("gemini-2.0-flash-exp", "should work with full Flash model name"),
+            ("gemini-2.0-flash", "should work with full Flash model name"),
         ]
 
         success_count = 0

tests/conftest.py

@@ -23,7 +23,7 @@ if "OPENAI_API_KEY" not in os.environ:
 
 # Set default model to a specific value for tests to avoid auto mode
 # This prevents all tests from failing due to missing model parameter
-os.environ["DEFAULT_MODEL"] = "gemini-2.0-flash-exp"
+os.environ["DEFAULT_MODEL"] = "gemini-2.0-flash"
 
 # Force reload of config module to pick up the env var
 import importlib

tests/mock_helpers.py

@@ -5,7 +5,7 @@ from unittest.mock import Mock
 from providers.base import ModelCapabilities, ProviderType, RangeTemperatureConstraint
 
 
-def create_mock_provider(model_name="gemini-2.0-flash-exp", max_tokens=1_048_576):
+def create_mock_provider(model_name="gemini-2.0-flash", max_tokens=1_048_576):
     """Create a properly configured mock provider."""
     mock_provider = Mock()
 

tests/test_claude_continuation.py

@@ -72,7 +72,7 @@ class TestClaudeContinuationOffers:
             mock_provider.generate_content.return_value = Mock(
                 content="Analysis complete.",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -129,7 +129,7 @@ class TestClaudeContinuationOffers:
             mock_provider.generate_content.return_value = Mock(
                 content="Continued analysis.",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -162,7 +162,7 @@ class TestClaudeContinuationOffers:
             mock_provider.generate_content.return_value = Mock(
                 content="Analysis complete. The code looks good.",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -208,7 +208,7 @@ I'd be happy to examine the error handling patterns in more detail if that would
             mock_provider.generate_content.return_value = Mock(
                 content=content_with_followup,
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -253,7 +253,7 @@ I'd be happy to examine the error handling patterns in more detail if that would
             mock_provider.generate_content.return_value = Mock(
                 content="Continued analysis complete.",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -309,7 +309,7 @@ I'd be happy to examine the error handling patterns in more detail if that would
             mock_provider.generate_content.return_value = Mock(
                 content="Final response.",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -358,7 +358,7 @@ class TestContinuationIntegration:
             mock_provider.generate_content.return_value = Mock(
                 content="Analysis result",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -411,7 +411,7 @@ class TestContinuationIntegration:
             mock_provider.generate_content.return_value = Mock(
                 content="Structure analysis done.",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -448,7 +448,7 @@ class TestContinuationIntegration:
             mock_provider.generate_content.return_value = Mock(
                 content="Performance analysis done.",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
 

tests/test_collaboration.py

@@ -41,7 +41,7 @@ class TestDynamicContextRequests:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = False
         mock_provider.generate_content.return_value = Mock(
-            content=clarification_json, usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content=clarification_json, usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -82,7 +82,7 @@ class TestDynamicContextRequests:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = False
         mock_provider.generate_content.return_value = Mock(
-            content=normal_response, usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content=normal_response, usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -106,7 +106,7 @@ class TestDynamicContextRequests:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = False
         mock_provider.generate_content.return_value = Mock(
-            content=malformed_json, usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content=malformed_json, usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -146,7 +146,7 @@ class TestDynamicContextRequests:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = False
         mock_provider.generate_content.return_value = Mock(
-            content=clarification_json, usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content=clarification_json, usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -233,7 +233,7 @@ class TestCollaborationWorkflow:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = False
         mock_provider.generate_content.return_value = Mock(
-            content=clarification_json, usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content=clarification_json, usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -272,7 +272,7 @@ class TestCollaborationWorkflow:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = False
         mock_provider.generate_content.return_value = Mock(
-            content=clarification_json, usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content=clarification_json, usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -299,7 +299,7 @@ class TestCollaborationWorkflow:
         """
 
         mock_provider.generate_content.return_value = Mock(
-            content=final_response, usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content=final_response, usage={}, model_name="gemini-2.0-flash", metadata={}
         )
 
         result2 = await tool.execute(

tests/test_config.py

@@ -32,7 +32,7 @@ class TestConfig:
     def test_model_config(self):
         """Test model configuration"""
         # DEFAULT_MODEL is set in conftest.py for tests
-        assert DEFAULT_MODEL == "gemini-2.0-flash-exp"
+        assert DEFAULT_MODEL == "gemini-2.0-flash"
         assert MAX_CONTEXT_TOKENS == 1_000_000
 
     def test_temperature_defaults(self):

tests/test_conversation_field_mapping.py

@@ -74,7 +74,7 @@ async def test_conversation_history_field_mapping():
                         mock_provider = MagicMock()
                         mock_provider.get_capabilities.return_value = ModelCapabilities(
                             provider=ProviderType.GOOGLE,
-                            model_name="gemini-2.0-flash-exp",
+                            model_name="gemini-2.0-flash",
                             friendly_name="Gemini",
                             max_tokens=200000,
                             supports_extended_thinking=True,

tests/test_conversation_history_bug.py

@@ -115,7 +115,7 @@ class TestConversationHistoryBugFix:
                 return Mock(
                     content="Response with conversation context",
                     usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                    model_name="gemini-2.0-flash-exp",
+                    model_name="gemini-2.0-flash",
                     metadata={"finish_reason": "STOP"},
                 )
 
@@ -175,7 +175,7 @@ class TestConversationHistoryBugFix:
                 return Mock(
                     content="Response without history",
                     usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                    model_name="gemini-2.0-flash-exp",
+                    model_name="gemini-2.0-flash",
                     metadata={"finish_reason": "STOP"},
                 )
 
@@ -213,7 +213,7 @@ class TestConversationHistoryBugFix:
                 return Mock(
                     content="New conversation response",
                     usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                    model_name="gemini-2.0-flash-exp",
+                    model_name="gemini-2.0-flash",
                     metadata={"finish_reason": "STOP"},
                 )
 
@@ -297,7 +297,7 @@ class TestConversationHistoryBugFix:
                 return Mock(
                     content="Analysis of new files complete",
                     usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                    model_name="gemini-2.0-flash-exp",
+                    model_name="gemini-2.0-flash",
                     metadata={"finish_reason": "STOP"},
                 )
 

tests/test_cross_tool_continuation.py

@@ -111,7 +111,7 @@ I'd be happy to review these security findings in detail if that would be helpfu
             mock_provider.generate_content.return_value = Mock(
                 content=content,
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -158,7 +158,7 @@ I'd be happy to review these security findings in detail if that would be helpfu
             mock_provider.generate_content.return_value = Mock(
                 content="Critical security vulnerability confirmed. The authentication function always returns true, bypassing all security checks.",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -279,7 +279,7 @@ I'd be happy to review these security findings in detail if that would be helpfu
             mock_provider.generate_content.return_value = Mock(
                 content="Security review of auth.py shows vulnerabilities",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider

tests/test_intelligent_fallback.py

@@ -0,0 +1,181 @@
+"""
+Test suite for intelligent auto mode fallback logic
+
+Tests the new dynamic model selection based on available API keys
+"""
+
+import os
+from unittest.mock import Mock, patch
+
+import pytest
+
+from providers.base import ProviderType
+from providers.registry import ModelProviderRegistry
+
+
+class TestIntelligentFallback:
+    """Test intelligent model fallback logic"""
+
+    def setup_method(self):
+        """Setup for each test - clear registry cache"""
+        ModelProviderRegistry.clear_cache()
+
+    def teardown_method(self):
+        """Cleanup after each test"""
+        ModelProviderRegistry.clear_cache()
+
+    @patch.dict(os.environ, {"OPENAI_API_KEY": "sk-test-key", "GEMINI_API_KEY": ""}, clear=False)
+    def test_prefers_openai_o3_mini_when_available(self):
+        """Test that o3-mini is preferred when OpenAI API key is available"""
+        ModelProviderRegistry.clear_cache()
+        fallback_model = ModelProviderRegistry.get_preferred_fallback_model()
+        assert fallback_model == "o3-mini"
+
+    @patch.dict(os.environ, {"OPENAI_API_KEY": "", "GEMINI_API_KEY": "test-gemini-key"}, clear=False)
+    def test_prefers_gemini_flash_when_openai_unavailable(self):
+        """Test that gemini-2.0-flash is used when only Gemini API key is available"""
+        ModelProviderRegistry.clear_cache()
+        fallback_model = ModelProviderRegistry.get_preferred_fallback_model()
+        assert fallback_model == "gemini-2.0-flash"
+
+    @patch.dict(os.environ, {"OPENAI_API_KEY": "sk-test-key", "GEMINI_API_KEY": "test-gemini-key"}, clear=False)
+    def test_prefers_openai_when_both_available(self):
+        """Test that OpenAI is preferred when both API keys are available"""
+        ModelProviderRegistry.clear_cache()
+        fallback_model = ModelProviderRegistry.get_preferred_fallback_model()
+        assert fallback_model == "o3-mini"  # OpenAI has priority
+
+    @patch.dict(os.environ, {"OPENAI_API_KEY": "", "GEMINI_API_KEY": ""}, clear=False)
+    def test_fallback_when_no_keys_available(self):
+        """Test fallback behavior when no API keys are available"""
+        ModelProviderRegistry.clear_cache()
+        fallback_model = ModelProviderRegistry.get_preferred_fallback_model()
+        assert fallback_model == "gemini-2.0-flash"  # Default fallback
+
+    def test_available_providers_with_keys(self):
+        """Test the get_available_providers_with_keys method"""
+        with patch.dict(os.environ, {"OPENAI_API_KEY": "sk-test-key", "GEMINI_API_KEY": ""}, clear=False):
+            ModelProviderRegistry.clear_cache()
+            available = ModelProviderRegistry.get_available_providers_with_keys()
+            assert ProviderType.OPENAI in available
+            assert ProviderType.GOOGLE not in available
+
+        with patch.dict(os.environ, {"OPENAI_API_KEY": "", "GEMINI_API_KEY": "test-key"}, clear=False):
+            ModelProviderRegistry.clear_cache()
+            available = ModelProviderRegistry.get_available_providers_with_keys()
+            assert ProviderType.GOOGLE in available
+            assert ProviderType.OPENAI not in available
+
+    def test_auto_mode_conversation_memory_integration(self):
+        """Test that conversation memory uses intelligent fallback in auto mode"""
+        from utils.conversation_memory import ThreadContext, build_conversation_history
+
+        # Mock auto mode - patch the config module where these values are defined
+        with (
+            patch("config.IS_AUTO_MODE", True),
+            patch("config.DEFAULT_MODEL", "auto"),
+            patch.dict(os.environ, {"OPENAI_API_KEY": "sk-test-key", "GEMINI_API_KEY": ""}, clear=False),
+        ):
+
+            ModelProviderRegistry.clear_cache()
+
+            # Create a context with at least one turn so it doesn't exit early
+            from utils.conversation_memory import ConversationTurn
+
+            context = ThreadContext(
+                thread_id="test-123",
+                created_at="2023-01-01T00:00:00Z",
+                last_updated_at="2023-01-01T00:00:00Z",
+                tool_name="chat",
+                turns=[ConversationTurn(role="user", content="Test message", timestamp="2023-01-01T00:00:30Z")],
+                initial_context={},
+            )
+
+            # This should use o3-mini for token calculations since OpenAI is available
+            with patch("utils.model_context.ModelContext") as mock_context_class:
+                mock_context_instance = Mock()
+                mock_context_class.return_value = mock_context_instance
+                mock_context_instance.calculate_token_allocation.return_value = Mock(
+                    file_tokens=10000, history_tokens=5000
+                )
+                # Mock estimate_tokens to return integers for proper summing
+                mock_context_instance.estimate_tokens.return_value = 100
+
+                history, tokens = build_conversation_history(context, model_context=None)
+
+                # Verify that ModelContext was called with o3-mini (the intelligent fallback)
+                mock_context_class.assert_called_once_with("o3-mini")
+
+    def test_auto_mode_with_gemini_only(self):
+        """Test auto mode behavior when only Gemini API key is available"""
+        from utils.conversation_memory import ThreadContext, build_conversation_history
+
+        with (
+            patch("config.IS_AUTO_MODE", True),
+            patch("config.DEFAULT_MODEL", "auto"),
+            patch.dict(os.environ, {"OPENAI_API_KEY": "", "GEMINI_API_KEY": "test-key"}, clear=False),
+        ):
+
+            ModelProviderRegistry.clear_cache()
+
+            from utils.conversation_memory import ConversationTurn
+
+            context = ThreadContext(
+                thread_id="test-456",
+                created_at="2023-01-01T00:00:00Z",
+                last_updated_at="2023-01-01T00:00:00Z",
+                tool_name="analyze",
+                turns=[ConversationTurn(role="assistant", content="Test response", timestamp="2023-01-01T00:00:30Z")],
+                initial_context={},
+            )
+
+            with patch("utils.model_context.ModelContext") as mock_context_class:
+                mock_context_instance = Mock()
+                mock_context_class.return_value = mock_context_instance
+                mock_context_instance.calculate_token_allocation.return_value = Mock(
+                    file_tokens=10000, history_tokens=5000
+                )
+                # Mock estimate_tokens to return integers for proper summing
+                mock_context_instance.estimate_tokens.return_value = 100
+
+                history, tokens = build_conversation_history(context, model_context=None)
+
+                # Should use gemini-2.0-flash when only Gemini is available
+                mock_context_class.assert_called_once_with("gemini-2.0-flash")
+
+    def test_non_auto_mode_unchanged(self):
+        """Test that non-auto mode behavior is unchanged"""
+        from utils.conversation_memory import ThreadContext, build_conversation_history
+
+        with patch("config.IS_AUTO_MODE", False), patch("config.DEFAULT_MODEL", "gemini-2.5-pro-preview-06-05"):
+
+            from utils.conversation_memory import ConversationTurn
+
+            context = ThreadContext(
+                thread_id="test-789",
+                created_at="2023-01-01T00:00:00Z",
+                last_updated_at="2023-01-01T00:00:00Z",
+                tool_name="thinkdeep",
+                turns=[
+                    ConversationTurn(role="user", content="Test in non-auto mode", timestamp="2023-01-01T00:00:30Z")
+                ],
+                initial_context={},
+            )
+
+            with patch("utils.model_context.ModelContext") as mock_context_class:
+                mock_context_instance = Mock()
+                mock_context_class.return_value = mock_context_instance
+                mock_context_instance.calculate_token_allocation.return_value = Mock(
+                    file_tokens=10000, history_tokens=5000
+                )
+                # Mock estimate_tokens to return integers for proper summing
+                mock_context_instance.estimate_tokens.return_value = 100
+
+                history, tokens = build_conversation_history(context, model_context=None)
+
+                # Should use the configured DEFAULT_MODEL, not the intelligent fallback
+                mock_context_class.assert_called_once_with("gemini-2.5-pro-preview-06-05")
+
+
+if __name__ == "__main__":
+    pytest.main([__file__])

tests/test_large_prompt_handling.py

@@ -75,7 +75,7 @@ class TestLargePromptHandling:
             mock_provider.generate_content.return_value = MagicMock(
                 content="This is a test response",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -100,7 +100,7 @@ class TestLargePromptHandling:
             mock_provider.generate_content.return_value = MagicMock(
                 content="Processed large prompt",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -212,7 +212,7 @@ class TestLargePromptHandling:
             mock_provider.generate_content.return_value = MagicMock(
                 content="Success",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -245,7 +245,7 @@ class TestLargePromptHandling:
             mock_provider.generate_content.return_value = MagicMock(
                 content="Success",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -276,7 +276,7 @@ class TestLargePromptHandling:
             mock_provider.generate_content.return_value = MagicMock(
                 content="Success",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider
@@ -298,7 +298,7 @@ class TestLargePromptHandling:
             mock_provider.generate_content.return_value = MagicMock(
                 content="Success",
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
             mock_get_provider.return_value = mock_provider

tests/test_prompt_regression.py

@@ -31,7 +31,7 @@ class TestPromptRegression:
             return Mock(
                 content=text,
                 usage={"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
-                model_name="gemini-2.0-flash-exp",
+                model_name="gemini-2.0-flash",
                 metadata={"finish_reason": "STOP"},
             )
 

tests/test_providers.py

@@ -49,7 +49,7 @@ class TestModelProviderRegistry:
         """Test getting provider for a specific model"""
         ModelProviderRegistry.register_provider(ProviderType.GOOGLE, GeminiModelProvider)
 
-        provider = ModelProviderRegistry.get_provider_for_model("gemini-2.0-flash-exp")
+        provider = ModelProviderRegistry.get_provider_for_model("gemini-2.0-flash")
 
         assert provider is not None
         assert isinstance(provider, GeminiModelProvider)
@@ -80,10 +80,10 @@ class TestGeminiProvider:
         """Test getting model capabilities"""
         provider = GeminiModelProvider(api_key="test-key")
 
-        capabilities = provider.get_capabilities("gemini-2.0-flash-exp")
+        capabilities = provider.get_capabilities("gemini-2.0-flash")
 
         assert capabilities.provider == ProviderType.GOOGLE
-        assert capabilities.model_name == "gemini-2.0-flash-exp"
+        assert capabilities.model_name == "gemini-2.0-flash"
         assert capabilities.max_tokens == 1_048_576
         assert not capabilities.supports_extended_thinking
 
@@ -103,13 +103,13 @@ class TestGeminiProvider:
         assert provider.validate_model_name("pro")
 
         capabilities = provider.get_capabilities("flash")
-        assert capabilities.model_name == "gemini-2.0-flash-exp"
+        assert capabilities.model_name == "gemini-2.0-flash"
 
     def test_supports_thinking_mode(self):
         """Test thinking mode support detection"""
         provider = GeminiModelProvider(api_key="test-key")
 
-        assert not provider.supports_thinking_mode("gemini-2.0-flash-exp")
+        assert not provider.supports_thinking_mode("gemini-2.0-flash")
         assert provider.supports_thinking_mode("gemini-2.5-pro-preview-06-05")
 
     @patch("google.genai.Client")
@@ -133,11 +133,11 @@ class TestGeminiProvider:
 
         provider = GeminiModelProvider(api_key="test-key")
 
-        response = provider.generate_content(prompt="Test prompt", model_name="gemini-2.0-flash-exp", temperature=0.7)
+        response = provider.generate_content(prompt="Test prompt", model_name="gemini-2.0-flash", temperature=0.7)
 
         assert isinstance(response, ModelResponse)
         assert response.content == "Generated content"
-        assert response.model_name == "gemini-2.0-flash-exp"
+        assert response.model_name == "gemini-2.0-flash"
         assert response.provider == ProviderType.GOOGLE
         assert response.usage["input_tokens"] == 10
         assert response.usage["output_tokens"] == 20

tests/test_server.py

@@ -56,7 +56,7 @@ class TestServerTools:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = False
         mock_provider.generate_content.return_value = Mock(
-            content="Chat response", usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content="Chat response", usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 

tests/test_thinking_modes.py

@@ -45,7 +45,7 @@ class TestThinkingModes:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = True
         mock_provider.generate_content.return_value = Mock(
-            content="Minimal thinking response", usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content="Minimal thinking response", usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -82,7 +82,7 @@ class TestThinkingModes:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = True
         mock_provider.generate_content.return_value = Mock(
-            content="Low thinking response", usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content="Low thinking response", usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -114,7 +114,7 @@ class TestThinkingModes:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = True
         mock_provider.generate_content.return_value = Mock(
-            content="Medium thinking response", usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content="Medium thinking response", usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -145,7 +145,7 @@ class TestThinkingModes:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = True
         mock_provider.generate_content.return_value = Mock(
-            content="High thinking response", usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content="High thinking response", usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -175,7 +175,7 @@ class TestThinkingModes:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = True
         mock_provider.generate_content.return_value = Mock(
-            content="Max thinking response", usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content="Max thinking response", usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 

tests/test_tools.py

@@ -37,7 +37,7 @@ class TestThinkDeepTool:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = True
         mock_provider.generate_content.return_value = Mock(
-            content="Extended analysis", usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content="Extended analysis", usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -88,7 +88,7 @@ class TestCodeReviewTool:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = False
         mock_provider.generate_content.return_value = Mock(
-            content="Security issues found", usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content="Security issues found", usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -133,7 +133,7 @@ class TestDebugIssueTool:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = False
         mock_provider.generate_content.return_value = Mock(
-            content="Root cause: race condition", usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content="Root cause: race condition", usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -181,7 +181,7 @@ class TestAnalyzeTool:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = False
         mock_provider.generate_content.return_value = Mock(
-            content="Architecture analysis", usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content="Architecture analysis", usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 
@@ -295,7 +295,7 @@ class TestAbsolutePathValidation:
         mock_provider.get_provider_type.return_value = Mock(value="google")
         mock_provider.supports_thinking_mode.return_value = False
         mock_provider.generate_content.return_value = Mock(
-            content="Analysis complete", usage={}, model_name="gemini-2.0-flash-exp", metadata={}
+            content="Analysis complete", usage={}, model_name="gemini-2.0-flash", metadata={}
         )
         mock_get_provider.return_value = mock_provider
 

utils/conversation_memory.py

@@ -74,7 +74,7 @@ class ConversationTurn(BaseModel):
         files: List of file paths referenced in this specific turn
         tool_name: Which tool generated this turn (for cross-tool tracking)
         model_provider: Provider used (e.g., "google", "openai")
-        model_name: Specific model used (e.g., "gemini-2.0-flash-exp", "o3-mini")
+        model_name: Specific model used (e.g., "gemini-2.0-flash", "o3-mini")
         model_metadata: Additional model-specific metadata (e.g., thinking mode, token usage)
     """
 
@@ -249,7 +249,7 @@ def add_turn(
         files: Optional list of files referenced in this turn
         tool_name: Name of the tool adding this turn (for attribution)
         model_provider: Provider used (e.g., "google", "openai")
-        model_name: Specific model used (e.g., "gemini-2.0-flash-exp", "o3-mini")
+        model_name: Specific model used (e.g., "gemini-2.0-flash", "o3-mini")
         model_metadata: Additional model info (e.g., thinking mode, token usage)
 
     Returns:
@@ -454,10 +454,19 @@ def build_conversation_history(context: ThreadContext, model_context=None, read_
 
     # Get model-specific token allocation early (needed for both files and turns)
     if model_context is None:
-        from config import DEFAULT_MODEL
+        from config import DEFAULT_MODEL, IS_AUTO_MODE
         from utils.model_context import ModelContext
 
-        model_context = ModelContext(DEFAULT_MODEL)
+        # In auto mode, use an intelligent fallback model for token calculations
+        # since "auto" is not a real model with a provider
+        model_name = DEFAULT_MODEL
+        if IS_AUTO_MODE and model_name.lower() == "auto":
+            # Use intelligent fallback based on available API keys
+            from providers.registry import ModelProviderRegistry
+
+            model_name = ModelProviderRegistry.get_preferred_fallback_model()
+
+        model_context = ModelContext(model_name)
 
     token_allocation = model_context.calculate_token_allocation()
     max_file_tokens = token_allocation.file_tokens