feat(module): add param ids to ElasticVectorSearch.from_texts method (#7425)

# add param ids to ElasticVectorSearch.from_texts method.

- Description: add param ids to ElasticVectorSearch.from_texts method.
- Issue: NA. It seems `add_texts` already supports passing in document
ids, but param `ids` is omitted in `from_texts` classmethod,
- Dependencies: None,
- Tag maintainer: @rlancemartin, @eyurtsev please have a look, thanks

```
    # ElasticVectorSearch add_texts
    def add_texts(
        self,
        texts: Iterable[str],
        metadatas: Optional[List[dict]] = None,
        refresh_indices: bool = True,
        ids: Optional[List[str]] = None,
        **kwargs: Any,
    ) -> List[str]:
        ...

```

```
    # ElasticVectorSearch from_texts
    @classmethod
    def from_texts(
        cls,
        texts: List[str],
        embedding: Embeddings,
        metadatas: Optional[List[dict]] = None,
        elasticsearch_url: Optional[str] = None,
        index_name: Optional[str] = None,
        refresh_indices: bool = True,
        **kwargs: Any,
    ) -> ElasticVectorSearch:

```


Co-authored-by: charosen <charosen@bupt.cn>

langchain/vectorstores/elastic_vector_search.py

@@ -157,8 +157,8 @@ class ElasticVectorSearch(VectorStore, ABC):
         self,
         texts: Iterable[str],
         metadatas: Optional[List[dict]] = None,
-        refresh_indices: bool = True,
         ids: Optional[List[str]] = None,
+        refresh_indices: bool = True,
         **kwargs: Any,
     ) -> List[str]:
         """Run more texts through the embeddings and add to the vectorstore.
@@ -166,6 +166,7 @@ class ElasticVectorSearch(VectorStore, ABC):
         Args:
             texts: Iterable of strings to add to the vectorstore.
             metadatas: Optional list of metadatas associated with the texts.
+            ids: Optional list of unique IDs.
             refresh_indices: bool to refresh ElasticSearch indices
 
         Returns:
@@ -260,6 +261,7 @@ class ElasticVectorSearch(VectorStore, ABC):
         texts: List[str],
         embedding: Embeddings,
         metadatas: Optional[List[dict]] = None,
+        ids: Optional[List[str]] = None,
         elasticsearch_url: Optional[str] = None,
         index_name: Optional[str] = None,
         refresh_indices: bool = True,
@@ -292,7 +294,7 @@ class ElasticVectorSearch(VectorStore, ABC):
         index_name = index_name or uuid.uuid4().hex
         vectorsearch = cls(elasticsearch_url, index_name, embedding, **kwargs)
         vectorsearch.add_texts(
-            texts, metadatas=metadatas, refresh_indices=refresh_indices
+            texts, metadatas=metadatas, ids=ids, refresh_indices=refresh_indices
         )
         return vectorsearch