feat: add batch inference API to llama stack inference (#1945)

# What does this PR do?

This PR adds two methods to the Inference API:
- `batch_completion`
- `batch_chat_completion`

The motivation is for evaluations targeting a local inference engine
(like meta-reference or vllm) where batch APIs provide for a substantial
amount of acceleration.

Why did I not add this to `Api.batch_inference` though? That just
resulted in a _lot_ more book-keeping given the structure of Llama
Stack. Had I done that, I would have needed to create a notion of a
"batch model" resource, setup routing based on that, etc. This does not
sound ideal.

So what's the future of the batch inference API? I am not sure. Maybe we
can keep it for true _asynchronous_ execution. So you can submit
requests, and it can return a Job instance, etc.

## Test Plan

Run meta-reference-gpu using:
```bash
export INFERENCE_MODEL=meta-llama/Llama-4-Scout-17B-16E-Instruct
export INFERENCE_CHECKPOINT_DIR=../checkpoints/Llama-4-Scout-17B-16E-Instruct-20250331210000
export MODEL_PARALLEL_SIZE=4
export MAX_BATCH_SIZE=32
export MAX_SEQ_LEN=6144

LLAMA_MODELS_DEBUG=1 llama stack run meta-reference-gpu
```

Then run the batch inference test case.

tests/integration/test_cases/inference/chat_completion.json

@@ -537,5 +537,31 @@
         }
       ]
     }
+  },
+  "batch_completion": {
+    "data": {
+      "qa_pairs": [
+        {
+          "question": "What is the capital of France?",
+          "answer": "Paris"
+        },
+        {
+          "question": "Who wrote the book '1984'?",
+          "answer": "George Orwell"
+        },
+        {
+          "question": "Which planet has rings around it with a name starting with letter S?",
+          "answer": "Saturn"
+        },
+        {
+          "question": "When did the first moon landing happen?",
+          "answer": "1969"
+        },
+        {
+          "question": "What word says 'hello' in Spanish?",
+          "answer": "Hola"
+        }
+      ]
+    }
   }
 }

tests/integration/test_cases/inference/completion.json

@@ -44,5 +44,18 @@
                 "year_retired": "2003"
             }
         }
+    },
+    "batch_completion": {
+        "data": {
+            "contents": [
+                "Micheael Jordan is born in ",
+                "Roses are red, violets are ",
+                "If you had a million dollars, what would you do with it? ",
+                "All you need is ",
+                "The capital of France is ",
+                "It is a good day to ",
+                "The answer to the universe is "
+            ]
+        }
     }
 }