feat: faiss filter from list (#6537)

### Feature

Using FAISS on a retrievalQA task, I found myself wanting to allow in
multiple sources. From what I understood, the filter feature takes in a
dict of form {key: value} which then will check in the metadata for the
exact value linked to that key.
I added some logic to be able to pass a list which will be checked
against instead of an exact value. Passing an exact value will also
work.

Here's an example of how I could then use it in my own project:

```
    pdfs_to_filter_in = ["file_A", "file_B"]
    filter_dict = {
        "source": [f"source_pdfs/{pdf_name}.pdf" for pdf_name in pdfs_to_filter_in]
    }
    retriever = db.as_retriever()
    retriever.search_kwargs = {"filter": filter_dict}
```

I added an integration test based on the other ones I found in
`tests/integration_tests/vectorstores/test_faiss.py` under
`test_faiss_with_metadatas_and_list_filter()`.

It doesn't feel like this is worthy of its own notebook or doc, but I'm
open to suggestions if needed.

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>

langchain/vectorstores/faiss.py

@@ -192,7 +192,7 @@ class FAISS(VectorStore):
         Args:
             embedding: Embedding vector to look up documents similar to.
             k: Number of Documents to return. Defaults to 4.
-            filter (Optional[Dict[str, str]]): Filter by metadata. Defaults to None.
+            filter (Optional[Dict[str, Any]]): Filter by metadata. Defaults to None.
             fetch_k: (Optional[int]) Number of Documents to fetch before filtering.
                       Defaults to 20.
             **kwargs: kwargs to be passed to similarity search. Can include:
@@ -218,7 +218,11 @@ class FAISS(VectorStore):
             if not isinstance(doc, Document):
                 raise ValueError(f"Could not find document for id {_id}, got {doc}")
             if filter is not None:
-                if all(doc.metadata.get(key) == value for key, value in filter.items()):
+                filter = {
+                    key: [value] if not isinstance(value, list) else value
+                    for key, value in filter.items()
+                }
+                if all(doc.metadata.get(key) in value for key, value in filter.items()):
                     docs.append((doc, scores[0][j]))
             else:
                 docs.append((doc, scores[0][j]))

tests/integration_tests/vectorstores/test_faiss.py

@@ -96,6 +96,34 @@ def test_faiss_with_metadatas_and_filter() -> None:
     assert output == [Document(page_content="bar", metadata={"page": 1})]
 
 
+def test_faiss_with_metadatas_and_list_filter() -> None:
+    texts = ["foo", "bar", "baz", "foo", "qux"]
+    metadatas = [{"page": i} if i <= 3 else {"page": 3} for i in range(len(texts))]
+    docsearch = FAISS.from_texts(texts, FakeEmbeddings(), metadatas=metadatas)
+    expected_docstore = InMemoryDocstore(
+        {
+            docsearch.index_to_docstore_id[0]: Document(
+                page_content="foo", metadata={"page": 0}
+            ),
+            docsearch.index_to_docstore_id[1]: Document(
+                page_content="bar", metadata={"page": 1}
+            ),
+            docsearch.index_to_docstore_id[2]: Document(
+                page_content="baz", metadata={"page": 2}
+            ),
+            docsearch.index_to_docstore_id[3]: Document(
+                page_content="foo", metadata={"page": 3}
+            ),
+            docsearch.index_to_docstore_id[4]: Document(
+                page_content="qux", metadata={"page": 3}
+            ),
+        }
+    )
+    assert docsearch.docstore.__dict__ == expected_docstore.__dict__
+    output = docsearch.similarity_search("foor", k=1, filter={"page": [0, 1, 2]})
+    assert output == [Document(page_content="foo", metadata={"page": 0})]
+
+
 def test_faiss_search_not_found() -> None:
     """Test what happens when document is not found."""
     texts = ["foo", "bar", "baz"]