feat: model registry and capabilities for multi-provider support (#2158)

* feat: Implement model registry and capabilities for multi-provider support

- Added ModelRegistry to manage available models and their capabilities.
- Introduced ModelProvider enum for different LLM providers.
- Created ModelCapabilities dataclass to define model features.
- Implemented methods to load models based on API keys and settings.
- Added utility functions for model management in model_utils.py.
- Updated settings.py to include provider-specific API keys.
- Refactored LLM classes (Anthropic, OpenAI, Google, etc.) to utilize new model registry.
- Enhanced utility functions to handle token limits and model validation.
- Improved code structure and logging for better maintainability.

* feat: Add model selection feature with API integration and UI component

* feat: Add model selection and default model functionality in agent management

* test: Update assertions and formatting in stream processing tests

* refactor(llm): Standardize model identifier to model_id

* fix tests

---------

Co-authored-by: Alex <a@tushynski.me>

tests/api/answer/routes/test_base.py

@@ -274,8 +274,8 @@ class TestGPTModelRetrieval:
         with flask_app.app_context():
             resource = BaseAnswerResource()
 
-            assert hasattr(resource, "gpt_model")
-            assert resource.gpt_model is not None
+            assert hasattr(resource, "default_model_id")
+            assert resource.default_model_id is not None
 
 
 @pytest.mark.unit
@@ -412,7 +412,7 @@ class TestCompleteStreamMethod:
                     resource.complete_stream(
                         question="Test?",
                         agent=mock_agent,
-                            conversation_id=None,
+                        conversation_id=None,
                         user_api_key=None,
                         decoded_token=decoded_token,
                         should_save_conversation=True,
@@ -500,9 +500,10 @@ class TestProcessResponseStream:
 
             result = resource.process_response_stream(iter(stream))
 
-            assert len(result) == 5
+            assert len(result) == 6
             assert result[0] is None
             assert result[4] == "Test error"
+            assert result[5] is None
 
     def test_handles_malformed_stream_data(self, mock_mongo_db, flask_app):
         from application.api.answer.routes.base import BaseAnswerResource