Query returned from azure:
{‘query’: ‘Please provide rationale.. ‘, ‘result’: ‘Creative Output: The rationale behind the process is to ensure that all actions taken are based on sound reasoning and logic, and are aligned with the overall objectives and goals of the organization. This helps to minimize risks, optimize resources, and improve performance.’, ‘source_documents’: []}

Query returned locally:
{‘query’: ‘Please provide rationale.. ‘, ‘result’: ‘Extracted Output: Could you please provide more context or specify which process or policy you are referring to? Without additional information, it is difficult to provide a concise response.’, ‘source_documents’: [Document(page_content=’Please provide evidence that this occurred in the last twelve months.’, metadata={‘source_page’: ‘Third Party-Vendor Audit Process Version 378′}), Document(page_content=’Please provide evidence that this occurred in the last twelve months.’, metadata={‘source_page’: ‘Third Party-Vendor Audit Process Version 371′}), Document(page_content=’Please Provide evidence such as emails or other notifications showing periodic access reviews.’, metadata={‘source_page’: ‘Third Party-Vendor Audit Process Version 352′}), Document(page_content=’Please provide evidence that this has occurred within the last twelve months.’, metadata={‘source_page’: ‘Third Party-Vendor Audit Process Version 331’})]}

For azure I am saving the vectordatabase in github> i have created a directory called vdb_langchain_small in Github while for local I have created the same folder locally. I am getting two different outputs.

I am using the same code for both i.e

 PROMPT=PromptTemplate(template=Prompt_Template,input_variables=["context","question"])
 chain_type_kwargs={"prompt":PROMPT}
 qa_chain = RetrievalQA.from_chain_type(llm=self.llm_open,
                                            chain_type="stuff",
                                            retriever=self.retriever,
                                            return_source_documents=True,
                                            chain_type_kwargs=chain_type_kwargs,
                                            verbose=True)
 qa_results = {}

I was expecting the query to return list of source documents along instead I got none for all the answers I got.