docs: use InjectedStore in semantic search guide (#2995)

When I tried to follow the How-to guide for [How to add semantic search
to your agent's
memory](https://langchain-ai.github.io/langgraph/how-tos/memory/semantic-search/#using-in-create_react_agent)
using `create_react_agent`, I got this error message when my agent used
the tool:

```python
1 validation error for upsert_memory
store
  Field required [type=missing, input_value={'content': '@jimmy works...ny.', 'memory_id': None}, input_type=dict]
    For further information visit https://errors.pydantic.dev/2.10/v/missingTraceback (most recent call last):

  File "/usr/local/lib/python3.9/site-packages/langchain_core/tools/base.py", line 688, in run
    tool_args, tool_kwargs = self._to_args_and_kwargs(tool_input, tool_call_id)

  File "/usr/local/lib/python3.9/site-packages/langchain_core/tools/base.py", line 611, in _to_args_and_kwargs
    tool_input = self._parse_input(tool_input, tool_call_id)

  File "/usr/local/lib/python3.9/site-packages/langchain_core/tools/base.py", line 532, in _parse_input
    result = input_args.model_validate(tool_input)

  File "/usr/local/lib/python3.9/site-packages/pydantic/main.py", line 627, in model_validate
    return cls.__pydantic_validator__.validate_python(

pydantic_core._pydantic_core.ValidationError: 1 validation error for upsert_memory
store
  Field required [type=missing, input_value={'content': '@jimmy works...ny.', 'memory_id': None}, input_type=dict]
    For further information visit https://errors.pydantic.dev/2.10/v/missing
```

I believe it’s because the graph did not inject the store into the tool
if we use `InjectedToolArg`.

When looking at the guide for [How to pass runtime values to
tools](https://langchain-ai.github.io/langgraph/how-tos/pass-run-time-values-to-tools/),
it suggests to use `InjectedStore` with `create_react_agent`. After
changing my code to use `InjectedStore`, my agent was able to save to
the store.

docs/docs/how-tos/memory/semantic-search.ipynb

@@ -208,7 +208,7 @@
     "from typing import Optional\n",
     "\n",
     "from langchain.chat_models import init_chat_model\n",
-    "from langchain_core.tools import InjectedToolArg\n",
+    "from langgraph.prebuilt import InjectedStore\n",
     "from langgraph.store.base import BaseStore\n",
     "from typing_extensions import Annotated\n",
     "\n",
@@ -232,7 +232,7 @@
     "    content: str,\n",
     "    *,\n",
     "    memory_id: Optional[uuid.UUID] = None,\n",
-    "    store: Annotated[BaseStore, InjectedToolArg],\n",
+    "    store: Annotated[BaseStore, InjectedStore],\n",
     "):\n",
     "    \"\"\"Upsert a memory in the database.\"\"\"\n",
     "    # The LLM can use this tool to store a new memory\n",