fix(faiss): handle case where distance is 0 by setting d to minimum positive… (#2387)

# What does this PR do?
Adds try-catch to faiss `query_vector` function for when the distance
between the query embedding and an embedding within the vector db is 0
(identical vectors). Catches `ZeroDivisionError` and then appends `(1.0
/ sys.float_info.min)` to `scores` to represent maximum similarity.

<!-- If resolving an issue, uncomment and update the line below -->
Closes [#2381]

## Test Plan
Checkout this PR

Execute this code and there will no longer be a `ZeroDivisionError`
exception
```
from llama_stack_client import LlamaStackClient

base_url = "http://localhost:8321"
client = LlamaStackClient(base_url=base_url)

models = client.models.list()
embedding_model = (
    em := next(m for m in models if m.model_type == "embedding")
).identifier
embedding_dimension = 384

_ = client.vector_dbs.register(
    vector_db_id="foo_db",
    embedding_model=embedding_model,
    embedding_dimension=embedding_dimension,
    provider_id="faiss",
)

chunk = {
    "content": "foo",
    "mime_type": "text/plain",
    "metadata": {
        "document_id": "foo-id"
    }
}

client.vector_io.insert(vector_db_id="foo_db", chunks=[chunk])
client.vector_io.query(vector_db_id="foo_db", query="foo")
```

### Running unit tests
`uv run pytest tests/unit/rag/test_rag_query.py -v`

---------

Signed-off-by: Ben Browning <bbrownin@redhat.com>
Co-authored-by: Ben Browning <bbrownin@redhat.com>

llama_stack/providers/inline/vector_io/faiss/faiss.py

@@ -112,7 +112,7 @@ class FaissIndex(EmbeddingIndex):
             if i < 0:
                 continue
             chunks.append(self.chunk_by_index[int(i)])
-            scores.append(1.0 / float(d))
+            scores.append(1.0 / float(d) if d != 0 else float("inf"))
 
         return QueryChunksResponse(chunks=chunks, scores=scores)