Implement API for Q&A Using RetrievalQAChain

To recap, we have generated the vector embeddings using OpenAIEmbeddings earlier. Now, we will use the RetrievalQAChain to get answers for the user inputs using the embeddings.

Use RetrievalQAChain to get answers from LLM

Now comes the most important part. We have the vector embeddings created and now we need to do two things:

• Retrieve the documents from a set of documents based on the input question.

• Generate a final answer based on the retrieved documents.

Langchain provides a chained workflow of the above two steps. We will use RetrievalQAChain that will take care of the above steps, a nice prompt, and finally return us the response. Let's discuss RetrievalQAChain in detail.

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