- [Question Answering Notebook](/modules/indexes/chain_examples/question_answering.ipynb): A notebook walking through how to accomplish this task.
- [VectorDB Question Answering Notebook](/modules/indexes/chain_examples/vector_db_qa.ipynb): A notebook walking through how to do question answering over a vector database. This can often be useful for when you have a LOT of documents, and you don't want to pass them all to the LLM, but rather first want to do some semantic search over embeddings.
- [Question Answering Notebook](../modules/chains/index_examples/question_answering.ipynb): A notebook walking through how to accomplish this task.
- [VectorDB Question Answering Notebook](../modules/chains/index_examples/vector_db_qa.ipynb): A notebook walking through how to do question answering over a vector database. This can often be useful for when you have a LOT of documents, and you don't want to pass them all to the LLM, but rather first want to do some semantic search over embeddings.
- [QA With Sources Notebook](/modules/indexes/chain_examples/qa_with_sources.ipynb): A notebook walking through how to accomplish this task.
- [VectorDB QA With Sources Notebook](/modules/indexes/chain_examples/vector_db_qa_with_sources.ipynb): A notebook walking through how to do question answering with sources over a vector database. This can often be useful for when you have a LOT of documents, and you don't want to pass them all to the LLM, but rather first want to do some semantic search over embeddings.
- [QA With Sources Notebook](../modules/chains/index_examples/qa_with_sources.ipynb): A notebook walking through how to accomplish this task.
- [VectorDB QA With Sources Notebook](../modules/chains/index_examples/vector_db_qa_with_sources.ipynb): A notebook walking through how to do question answering with sources over a vector database. This can often be useful for when you have a LOT of documents, and you don't want to pass them all to the LLM, but rather first want to do some semantic search over embeddings.