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

[AB-Law]

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