I am struggling with passing context to conversational rag chain when using RunnableWithMessageHistory.

I have the following query function:

def query(query_text, prompt, session_id, metadata_context):
# History retrieval test
contextualize_q_prompt = ChatPromptTemplate.from_messages(
    [
        ("system", contextualize_q_system_prompt),
        ("system", "{context}"),
        ("system", prompt),
        MessagesPlaceholder("chat_history"),
        ("human", "{input}"),
    ]
)
history_aware_retriever = create_history_aware_retriever(
    llm, retriever, contextualize_q_prompt
)

qa_prompt = ChatPromptTemplate.from_messages(
    [   
        ("system", PROMPT_TEMPLATE),
        ("system", "{context}"),
        ("system", prompt),
        MessagesPlaceholder("chat_history"),
        ("human", "{input}"),
    ]
)

question_answer_chain = create_stuff_documents_chain(llm, qa_prompt)
rag_chain = create_retrieval_chain(history_aware_retriever, question_answer_chain)

conversational_rag_chain = RunnableWithMessageHistory(
    rag_chain,
    get_session_history,
    input_messages_key="input",
    history_messages_key="chat_history",
    output_messages_key="answer",
)
try:
    logger.info(f"Model: {LLM_MODEL} assigned. Generation of response has started.")
    response = conversational_rag_chain.invoke({"input": query_text, "context": metadata_context}, config={"configurable": {"session_id": f"{session_id}"}},)
    logger.info(f"Response generated.")
except Exception as e:
    return ({'Generation of response failed: ': str(e)})
return response["answer"]

I want to pass my own ‘context’ that is prepared and parsed from retriever. I do not want retriever to be called again but from what I’ve read – retrieving happens by itself if chat_history does not contain the answer.

prompt variable is created:

prompt_template = ChatPromptTemplate.from_template(PROMPT_TEMPLATE)
prompt = prompt_template.format(context=metadata_context, input=query_text)

As you can see I am trying to put the context everywhere but no success.

The ‘context’ I can see when calling

conversational_rag_chain.invoke({"input": query_text, "context": metadata_context}, config={"configurable": {"session_id": f"{session_id}"}},)
        logger.info(f"Response generated.")

is the result of retriever:

Document(metadata={'number_of_reviews': '16', 'price': 18999, 'product_name': 'product', 'rating': '4')

Thanks for any help.