chore: made inbuilt tools blocking calls into async non blocking calls (#1509)

# What does this PR do?
This PR converts blocking calls for in built tools like wolfram, brave,
tavily and bing into non blocking async calls
[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan
[Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.*]
pytest -s -v tool_runtime/test_builtin_tools.py --stack-config=together
--text-model=meta-llama/Llama-3.1-8B-Instruct
Used the command above to get the below results
<img width="1710" alt="image"
src="https://github.com/user-attachments/assets/76b0ca06-f6e4-45fa-a114-0449bef2325b"
/>


<img width="1389" alt="image"
src="https://github.com/user-attachments/assets/5220ccbb-7882-4240-b17e-f362ad46d25b"
/>

<img width="1432" alt="image"
src="https://github.com/user-attachments/assets/bb93a41e-e82a-4c98-a22d-6b0e320aa974"
/>

[//]: # (## Documentation)

---------

Co-authored-by: sarthakdeshpande <sarthak.deshpande@engati.com>

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

@@ -4,6 +4,7 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
+import asyncio
 import base64
 import io
 import json
@@ -99,7 +100,7 @@ class FaissIndex(EmbeddingIndex):
         await self._save_index()
 
     async def query(self, embedding: NDArray, k: int, score_threshold: float) -> QueryChunksResponse:
-        distances, indices = self.index.search(embedding.reshape(1, -1).astype(np.float32), k)
+        distances, indices = await asyncio.to_thread(self.index.search, embedding.reshape(1, -1).astype(np.float32), k)
 
         chunks = []
         scores = []