Supporting Multi-LoRA inferencing via JetStream server (#221)

Supporting Multi-LoRA inferencing via JetStream server following [LLM
Inference gateway API
protocols](https://github.com/kubernetes-sigs/gateway-api-inference-extension/tree/main/docs/proposals/003-model-server-protocol#inference-api-protocol).

- Implemented an adapter_tensorstore to load, store, manage and unload
the adapter weights
- Added and exposed [required
metrics](https://github.com/kubernetes-sigs/gateway-api-inference-extension/tree/main/docs/proposals/003-model-server-protocol#metrics-reporting)
at prometheus endpoint
- Added multi_lora_decoding service with corresponding APIs as per the
[requirement](https://github.com/kubernetes-sigs/gateway-api-inference-extension/tree/main/docs/proposals/003-model-server-protocol#inference-api-protocol).
- Implemented single LoRA functionality support.

Author: aman2930

README.md

@@ -65,6 +65,9 @@ python -m unittest -v jetstream.tests.core.test_orchestrator
 # Test JetStream core server library
 python -m unittest -v jetstream.tests.core.test_server
 
+# Test JetStream lora adapter tensorstore
+python -m unittest -v jetstream.tests.core.lora.test_adapter_tensorstore
+
 # Test mock JetStream engine implementation
 python -m unittest -v jetstream.tests.engine.test_mock_engine