demonstrate use of RetrievalQAWithSourcesChain.from_chain (langchain-…

…ai#12235)

**Description:** 
Documents further usage of RetrievalQAWithSourcesChain in an existing
test. I'd not found much documented usage of RetrievalQAWithSourcesChain
and how to get the sources out. This additional code will hopefully be
useful to other potential users of this retriever.

 **Issue:** No raised issue
 
**Dependencies:** No new dependencies needed to run the test (it already
needs `open-ai`, `faiss-cpu` and `unstructured`).

Note - `make lint` showed 8 linting errors  in unrelated files

---------

Co-authored-by: richarda23 <[email protected]>

libs/langchain/tests/integration_tests/chains/test_retrieval_qa_with_sources.py

@@ -19,10 +19,20 @@ def test_retrieval_qa_with_sources_chain_saving_loading(tmp_path: str) -> None:
     qa = RetrievalQAWithSourcesChain.from_llm(
         llm=OpenAI(), retriever=docsearch.as_retriever()
     )
-    qa("What did the president say about Ketanji Brown Jackson?")
-
-    file_path = tmp_path + "/RetrievalQAWithSourcesChain.yaml"
+    result = qa("What did the president say about Ketanji Brown Jackson?")
+    assert "question" in result.keys()
+    assert "answer" in result.keys()
+    assert "sources" in result.keys()
+    file_path = str(tmp_path) + "/RetrievalQAWithSourcesChain.yaml"
     qa.save(file_path=file_path)
     qa_loaded = load_chain(file_path, retriever=docsearch.as_retriever())
 
     assert qa_loaded == qa
+
+    qa2 = RetrievalQAWithSourcesChain.from_chain_type(
+        llm=OpenAI(), retriever=docsearch.as_retriever(), chain_type="stuff"
+    )
+    result2 = qa2("What did the president say about Ketanji Brown Jackson?")
+    assert "question" in result2.keys()
+    assert "answer" in result2.keys()
+    assert "sources" in result2.keys()