fix: Refactor conversational_qa_chain initialization in KnowledgeBrainQA (#2629)

# Description

Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.

## Checklist before requesting a review

Please delete options that are not relevant.

- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
- [ ] I have commented hard-to-understand areas
- [ ] I have ideally added tests that prove my fix is effective or that
my feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged

## Screenshots (if appropriate):

backend/modules/brain/knowledge_brain_qa.py

@@ -331,9 +331,10 @@ class KnowledgeBrainQA(BaseModel, QAInterface):
     async def generate_stream(
         self, chat_id: UUID, question: ChatQuestion, save_answer: bool = True
     ) -> AsyncIterable:
-        conversational_qa_chain = (
-            self.get_chain() if self.get_chain() else self.knowledge_qa.get_chain()
-        )
+        if hasattr(self, "get_chain") and callable(getattr(self, "get_chain")):
+            conversational_qa_chain = self.get_chain()
+        else:
+            conversational_qa_chain = self.knowledge_qa.get_chain()
         transformed_history, streamed_chat_history = (
             self.initialize_streamed_chat_history(chat_id, question)
         )

backend/modules/brain/rags/quivr_rag.py

@@ -6,8 +6,7 @@ from uuid import UUID
 
 from langchain.chains import ConversationalRetrievalChain
 from langchain.llms.base import BaseLLM
-from langchain.prompts import (HumanMessagePromptTemplate,
-                               SystemMessagePromptTemplate)
+from langchain.prompts import HumanMessagePromptTemplate, SystemMessagePromptTemplate
 from langchain.retrievers import ContextualCompressionRetriever
 from langchain.retrievers.document_compressors import FlashrankRerank
 from langchain.schema import format_document
@@ -89,7 +88,8 @@ system_message_template = (
 )
 
 system_message_template += """
-When answering use markdown neat.
+When answering use markdown.
+Use markdown code blocks for code snippets.
 Answer in a concise and clear manner.
 Use the following pieces of context from files provided by the user to answer the users.
 Answer in the same language as the user question.