retrieve_text.py

def retrieve_text(self, query):
        self.text_deeplake_schema = DeepLake(
            dataset_path=cfg.TEXT_VECTORSTORE_PATH,
            read_only=True,
            embedding_function=self.embeddings,
        )

        prompt_template = """You are an intelligent AI which analyses text from documents and 
        answers the user's questions. Please answer in as much detail as possible, so that the user does not have to 
        revisit the document. If you don't know the answer, say that you don't know, and avoid making up things.
        {context}
        Question: {question} 
        Answer:
        """

        PROMPT = PromptTemplate(
            template=prompt_template, input_variables=["context", "question"]
        )
        chain_type_kwargs = {"prompt": PROMPT}

        model = ChatOpenAI(
            model_name="gpt-3.5-turbo",
            openai_api_key=cfg.OPENAI_API_KEY,
        )

        qa = RetrievalQA.from_chain_type(
            llm=model,
            chain_type="stuff",
            retriever=self.text_retriever,
            return_source_documents=False,
            verbose=False,
            chain_type_kwargs=chain_type_kwargs,
            memory=self.memory,
        )

        response = qa({"query": query})
        return response["result"]