[Feature]: Implement Provider Strategy Pattern for Multi-Model LLM Support

### Is your feature request related to a problem? Please describe.

Provider strategy pattern created for different LLM model families (GPT-5, GPT-4o, LM Studio, Ollama) with automatic routing based on model prefixes.
Scenario generation failing due to JSON parsing errors when using GPT-5 models. Character background isn't created correctly on gpt-5 models.

The scenario generation system fails when using GPT-5 models (gpt-5-nano, gpt-5-mini) due to malformed JSON responses that cannot be parsed by the fallback JSON extraction logic.
Error Details:
fallback
Root Cause: GPT-5 models generate JSON responses with formatting issues (unterminated strings, extra commas, malformed structures) that the current simple extraction logic cannot handle.

### Describe the solution you'd like

1. Provider Capabilities Matrix (backend/providers/capabilities.py)
Model family detection and capability mapping
API family routing (responses vs chat_completions vs openai_compatible)
2. Strategy Pattern Implementation
OpenAIGPT5Strategy: GPT-5 Responses API integration
OpenAIGPT4oStrategy: GPT-4o Chat Completions via LangChain
OpenAICompatibleStrategy: LM Studio/Ollama support
3. Provider Routing (backend/providers/openai.py)
Automatic strategy selection based on model name prefix
Unified ProviderResponse interface

Testing - Test suite needs to be updated for new architecture

### Describe alternatives you've considered

_No response_

### Additional context

_No response_

### Would you like to contribute this feature?

- [ ] Yes, I would like to implement this feature