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>

application/api/user/routes.py

@@ -10,6 +10,7 @@ from .agents import agents_ns, agents_sharing_ns, agents_webhooks_ns
 from .analytics import analytics_ns
 from .attachments import attachments_ns
 from .conversations import conversations_ns
+from .models import models_ns
 from .prompts import prompts_ns
 from .sharing import sharing_ns
 from .sources import sources_chunks_ns, sources_ns, sources_upload_ns
@@ -27,6 +28,9 @@ api.add_namespace(attachments_ns)
 # Conversations
 api.add_namespace(conversations_ns)
 
+# Models
+api.add_namespace(models_ns)
+
 # Agents (main, sharing, webhooks)
 api.add_namespace(agents_ns)
 api.add_namespace(agents_sharing_ns)