community[patch]: import flattening fix (#20110)

This PR should make it easier for linters to do type checking and for IDEs to jump to definition of code.

See #20050 as a template for this PR.
- As a byproduct: Added 3 missed `test_imports`.
- Added missed `SolarChat` in to __init___.py Added it into test_import
ut.
- Added `# type: ignore` to fix linting. It is not clear, why linting
errors appear after ^ changes.

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>

libs/community/tests/integration_tests/chat_models/test_bedrock.py

@@ -108,7 +108,7 @@ def test_bedrock_streaming(chat: BedrockChat) -> None:
 
     full = None
     for token in chat.stream("I'm Pickle Rick"):
-        full = token if full is None else full + token
+        full = token if full is None else full + token  # type: ignore[operator]
         assert isinstance(token.content, str)
     assert isinstance(cast(AIMessageChunk, full).content, str)
 

libs/community/tests/integration_tests/utilities/test_outline.py

@@ -66,7 +66,7 @@ def assert_docs(docs: List[Document], all_meta: bool = False) -> None:
 def test_run_success(api_client: OutlineAPIWrapper) -> None:
     responses.add(
         responses.POST,
-        api_client.outline_instance_url + api_client.outline_search_endpoint,
+        api_client.outline_instance_url + api_client.outline_search_endpoint,  # type: ignore[operator]
         json=OUTLINE_SUCCESS_RESPONSE,
         status=200,
     )
@@ -80,7 +80,7 @@ def test_run_success_all_meta(api_client: OutlineAPIWrapper) -> None:
     api_client.load_all_available_meta = True
     responses.add(
         responses.POST,
-        api_client.outline_instance_url + api_client.outline_search_endpoint,
+        api_client.outline_instance_url + api_client.outline_search_endpoint,  # type: ignore[operator]
         json=OUTLINE_SUCCESS_RESPONSE,
         status=200,
     )
@@ -93,7 +93,7 @@ def test_run_success_all_meta(api_client: OutlineAPIWrapper) -> None:
 def test_run_no_result(api_client: OutlineAPIWrapper) -> None:
     responses.add(
         responses.POST,
-        api_client.outline_instance_url + api_client.outline_search_endpoint,
+        api_client.outline_instance_url + api_client.outline_search_endpoint,  # type: ignore[operator]
         json=OUTLINE_EMPTY_RESPONSE,
         status=200,
     )
@@ -106,7 +106,7 @@ def test_run_no_result(api_client: OutlineAPIWrapper) -> None:
 def test_run_error(api_client: OutlineAPIWrapper) -> None:
     responses.add(
         responses.POST,
-        api_client.outline_instance_url + api_client.outline_search_endpoint,
+        api_client.outline_instance_url + api_client.outline_search_endpoint,  # type: ignore[operator]
         json=OUTLINE_ERROR_RESPONSE,
         status=401,
     )

libs/community/tests/integration_tests/vectorstores/test_deeplake.py

@@ -8,7 +8,7 @@ from tests.integration_tests.vectorstores.fake_embeddings import FakeEmbeddings
 
 
 @pytest.fixture
-def deeplake_datastore() -> DeepLake:
+def deeplake_datastore() -> DeepLake:  # type: ignore[misc]
     texts = ["foo", "bar", "baz"]
     metadatas = [{"page": str(i)} for i in range(len(texts))]
     docsearch = DeepLake.from_texts(

libs/community/tests/integration_tests/vectorstores/test_lantern.py

@@ -85,7 +85,7 @@ def test_lantern_embeddings_distance_strategy() -> None:
         collection_name="test_collection",
         embedding=FakeEmbeddingsWithAdaDimension(),
         connection_string=CONNECTION_STRING,
-        distance_strategy="hamming",
+        distance_strategy="hamming",  # type: ignore[arg-type]
         pre_delete_collection=True,
     )
     output = docsearch.similarity_search("foo", k=1)

libs/community/tests/integration_tests/vectorstores/test_milvus.py

@@ -26,7 +26,7 @@ def _milvus_from_texts(
 
 
 def _get_pks(expr: str, docsearch: Milvus) -> List[Any]:
-    return docsearch.get_pks(expr)
+    return docsearch.get_pks(expr)  # type: ignore[return-value]
 
 
 def test_milvus() -> None:
@@ -51,7 +51,7 @@ def test_milvus_with_id() -> None:
     assert output == [Document(page_content="foo")]
 
     output = docsearch.delete(ids=ids)
-    assert output.delete_count == len(fake_texts)
+    assert output.delete_count == len(fake_texts)  # type: ignore[attr-defined]
 
     try:
         ids = ["dup_id" for _ in fake_texts]
@@ -146,7 +146,7 @@ def test_milvus_upsert_entities() -> None:
         Document(page_content="test_2", metadata={"id": 3}),
     ]
     ids = docsearch.upsert(pks, documents)
-    assert len(ids) == 2
+    assert len(ids) == 2  # type: ignore[arg-type]
 
 
 # if __name__ == "__main__":

libs/community/tests/integration_tests/vectorstores/test_tidb_vector.py

@@ -320,7 +320,7 @@ def test_relevance_score() -> None:
     except ValueError:
         pass
 
-    docsearch_l2.drop_vectorstore()
+    docsearch_l2.drop_vectorstore()  # type: ignore[attr-defined]
 
 
 def test_retriever_search_threshold() -> None:

libs/community/tests/integration_tests/vectorstores/test_vdms.py

@@ -37,7 +37,7 @@ def vdms_client() -> vdms.vdms:
 @pytest.mark.requires("vdms")
 def test_init_from_client(vdms_client: vdms.vdms) -> None:
     embedding_function = FakeEmbeddings()
-    _ = VDMS(
+    _ = VDMS(  # type: ignore[call-arg]
         embedding_function=embedding_function,
         client=vdms_client,
     )
@@ -331,7 +331,7 @@ def test_with_relevance_score(vdms_client: vdms.vdms) -> None:
 def test_add_documents_no_metadata(vdms_client: vdms.vdms) -> None:
     collection_name = "test_add_documents_no_metadata"
     embedding_function = FakeEmbeddings()
-    db = VDMS(
+    db = VDMS(  # type: ignore[call-arg]
         collection_name=collection_name,
         embedding_function=embedding_function,
         client=vdms_client,
@@ -343,7 +343,7 @@ def test_add_documents_no_metadata(vdms_client: vdms.vdms) -> None:
 def test_add_documents_mixed_metadata(vdms_client: vdms.vdms) -> None:
     collection_name = "test_add_documents_mixed_metadata"
     embedding_function = FakeEmbeddings()
-    db = VDMS(
+    db = VDMS(  # type: ignore[call-arg]
         collection_name=collection_name,
         embedding_function=embedding_function,
         client=vdms_client,