feat(tests): introduce inference record/replay to increase test reliability (#2941)

Implements a comprehensive recording and replay system for inference API
calls that eliminates dependency on online inference providers during
testing. The system treats inference as deterministic by recording real
API responses and replaying them in subsequent test runs. Applies to
OpenAI clients (which should cover many inference requests) as well as
Ollama AsyncClient.

For storing, we use a hybrid system: Sqlite for fast lookups and JSON
files for easy greppability / debuggability.

As expected, tests become much much faster (more than 3x in just
inference testing.)

```bash
LLAMA_STACK_TEST_INFERENCE_MODE=record LLAMA_STACK_TEST_RECORDING_DIR=<...> \
  uv run pytest -s -v tests/integration/inference \
  --stack-config=starter \
  -k "not( builtin_tool or safety_with_image or code_interpreter or test_rag )" \
  --text-model="ollama/llama3.2:3b-instruct-fp16" \
  --embedding-model=sentence-transformers/all-MiniLM-L6-v2
```

```bash
LLAMA_STACK_TEST_INFERENCE_MODE=replay LLAMA_STACK_TEST_RECORDING_DIR=<...> \
  uv run pytest -s -v tests/integration/inference \
  --stack-config=starter \
  -k "not( builtin_tool or safety_with_image or code_interpreter or test_rag )" \
  --text-model="ollama/llama3.2:3b-instruct-fp16" \
  --embedding-model=sentence-transformers/all-MiniLM-L6-v2
```

- `LLAMA_STACK_TEST_INFERENCE_MODE`: `live` (default), `record`, or
`replay`
- `LLAMA_STACK_TEST_RECORDING_DIR`: Storage location (must be specified
for record or replay modes)

llama_stack/distribution/routers/inference.py

@@ -79,11 +79,9 @@ class InferenceRouter(Inference):
 
     async def initialize(self) -> None:
         logger.debug("InferenceRouter.initialize")
-        pass
 
     async def shutdown(self) -> None:
         logger.debug("InferenceRouter.shutdown")
-        pass
 
     async def register_model(
         self,