add everyting for docs

docs/snippets/modules/chains/additional/qa_with_sources.mdx

@@ -0,0 +1,23 @@
+We can also perform document QA and return the sources that were used to answer the question. To do this we'll just need to make sure each document has a "source" key in the metadata, and we'll use the `load_qa_with_sources` helper to construct our chain:
+
+```python
+docsearch = Chroma.from_texts(texts, embeddings, metadatas=[{"source": str(i)} for i in range(len(texts))])
+query = "What did the president say about Justice Breyer"
+docs = docsearch.similarity_search(query)
+```
+
+```python
+from langchain.chains.qa_with_sources import load_qa_with_sources_chain
+
+chain = load_qa_with_sources_chain(OpenAI(temperature=0), chain_type="stuff")
+query = "What did the president say about Justice Breyer"
+chain({"input_documents": docs, "question": query}, return_only_outputs=True)
+```
+
+<CodeOutputBlock lang="python">
+
+```
+    {'output_text': ' The president thanked Justice Breyer for his service.\nSOURCES: 30-pl'}
+```
+
+</CodeOutputBlock>