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@ -63,6 +63,11 @@ class BaseConversationalRetrievalChain(Chain):
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a new standalone question to be used later on."""
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output_key: str = "answer"
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"""The output key to return the final answer of this chain in."""
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rephrase_question: bool = True
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"""Whether or not to pass the new generated question to the combine_docs_chain.
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If True, will pass the new generated question along.
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If False, will only use the new generated question for retrieval and pass the
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original question along to the combine_docs_chain."""
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return_source_documents: bool = False
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"""Return the retrieved source documents as part of the final result."""
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return_generated_question: bool = False
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@ -131,7 +136,8 @@ class BaseConversationalRetrievalChain(Chain):
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else:
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docs = self._get_docs(new_question, inputs) # type: ignore[call-arg]
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new_inputs = inputs.copy()
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new_inputs["question"] = new_question
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if self.rephrase_question:
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new_inputs["question"] = new_question
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new_inputs["chat_history"] = chat_history_str
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answer = self.combine_docs_chain.run(
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input_documents=docs, callbacks=_run_manager.get_child(), **new_inputs
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@ -178,7 +184,8 @@ class BaseConversationalRetrievalChain(Chain):
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docs = await self._aget_docs(new_question, inputs) # type: ignore[call-arg]
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new_inputs = inputs.copy()
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new_inputs["question"] = new_question
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if self.rephrase_question:
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new_inputs["question"] = new_question
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new_inputs["chat_history"] = chat_history_str
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answer = await self.combine_docs_chain.arun(
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input_documents=docs, callbacks=_run_manager.get_child(), **new_inputs
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@ -212,8 +219,9 @@ class ConversationalRetrievalChain(BaseConversationalRetrievalChain):
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2. This new question is passed to the retriever and relevant documents are
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returned.
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3. The retrieved documents are passed to an LLM along with the new question to
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generate a final answer.
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3. The retrieved documents are passed to an LLM along with either the new question
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(default behavior) or the original question and chat history to generate a final
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response.
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Example:
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.. code-block:: python
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