Cache LLM model instances in registry

[ishaanxgupta]

💡 What:
Added @lru_cache(maxsize=16) to the get_model function in src/models/registry.py.

🎯 Why:
The get_model function was creating a new LLM client instance on every call. Instantiating these clients can be expensive (setting up connections, validating keys). By caching the result, we reuse the same client instance for the same configuration (provider, model_name, temperature).

📊 Impact:
Reduces unnecessary object creation and potential connection overhead. While strict benchmarking wasn't possible due to environment constraints, this is a standard optimization for service clients.

🔬 Measurement:
Verified using a reproduction script that get_model now returns the same instance for identical arguments. Existing unit tests passed.

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PR created automatically by Jules for task 2149973887280083142 started by @ishaanxgupta

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