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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):
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@ -331,9 +331,10 @@ class KnowledgeBrainQA(BaseModel, QAInterface):
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async def generate_stream(
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self, chat_id: UUID, question: ChatQuestion, save_answer: bool = True
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) -> AsyncIterable:
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conversational_qa_chain = (
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self.get_chain() if self.get_chain() else self.knowledge_qa.get_chain()
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)
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if hasattr(self, "get_chain") and callable(getattr(self, "get_chain")):
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conversational_qa_chain = self.get_chain()
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else:
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conversational_qa_chain = self.knowledge_qa.get_chain()
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transformed_history, streamed_chat_history = (
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self.initialize_streamed_chat_history(chat_id, question)
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)
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@ -6,8 +6,7 @@ from uuid import UUID
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from langchain.chains import ConversationalRetrievalChain
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from langchain.llms.base import BaseLLM
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from langchain.prompts import (HumanMessagePromptTemplate,
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SystemMessagePromptTemplate)
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from langchain.prompts import HumanMessagePromptTemplate, SystemMessagePromptTemplate
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from langchain.retrievers import ContextualCompressionRetriever
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from langchain.retrievers.document_compressors import FlashrankRerank
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from langchain.schema import format_document
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@ -89,7 +88,8 @@ system_message_template = (
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)
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system_message_template += """
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When answering use markdown neat.
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When answering use markdown.
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Use markdown code blocks for code snippets.
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Answer in a concise and clear manner.
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Use the following pieces of context from files provided by the user to answer the users.
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Answer in the same language as the user question.
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