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

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

frontend/src/store.ts

@@ -15,6 +15,7 @@ const prompt = localStorage.getItem('DocsGPTPrompt');
 const chunks = localStorage.getItem('DocsGPTChunks');
 const token_limit = localStorage.getItem('DocsGPTTokenLimit');
 const doc = localStorage.getItem('DocsGPTRecentDocs');
+const selectedModel = localStorage.getItem('DocsGPTSelectedModel');
 
 const preloadedState: { preference: Preference } = {
   preference: {
@@ -47,6 +48,9 @@ const preloadedState: { preference: Preference } = {
     agents: null,
     sharedAgents: null,
     selectedAgent: null,
+    selectedModel: selectedModel ? JSON.parse(selectedModel) : null,
+    availableModels: [],
+    modelsLoading: false,
   },
 };
 const store = configureStore({