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feat(rag): follow-up questions and thoughts with spanish fix (#2618)

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This pull request refactors the generate_answer and generate_stream
functions in order to improve code readability and maintainability. It
also adds new fields to the cited_answer model and updates the system
message template.
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Stan Girard 2024-05-26 17:43:38 +02:00 committed by GitHub
parent c06500086c
commit 877e8500bb
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2 changed files with 50 additions and 5 deletions
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26
backend/modules/brain/knowledge_brain_qa.py
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@ -305,8 +305,16 @@ class KnowledgeBrainQA(BaseModel, QAInterface):
if self.model_compatible_with_function_calling(model=self.model):
if model_response["answer"].tool_calls:
citations = model_response["answer"].tool_calls[-1]["args"]["citations"]
followup_questions = model_response["answer"].tool_calls[-1]["args"][
"followup_questions"
]
thoughts = model_response["answer"].tool_calls[-1]["args"]["thoughts"]
if citations:
citations = citations
if followup_questions:
metadata["followup_questions"] = followup_questions
if thoughts:
metadata["thoughts"] = thoughts
answer = model_response["answer"].tool_calls[-1]["args"]["answer"]
else:
answer = model_response["answer"].content
@ -370,6 +378,24 @@ class KnowledgeBrainQA(BaseModel, QAInterface):
and "citations" in gathered.tool_calls[-1]["args"]
):
citations = gathered.tool_calls[-1]["args"]["citations"]
if (
gathered.tool_calls
and gathered.tool_calls[-1].get("args")
and "followup_questions" in gathered.tool_calls[-1]["args"]
):
followup_questions = gathered.tool_calls[-1]["args"][
"followup_questions"
]
streamed_chat_history.metadata["followup_questions"] = (
followup_questions
)
if (
gathered.tool_calls
and gathered.tool_calls[-1].get("args")
and "thoughts" in gathered.tool_calls[-1]["args"]
):
thoughts = gathered.tool_calls[-1]["args"]["thoughts"]
streamed_chat_history.metadata["thoughts"] = thoughts
else:
if chunk.get("answer"):
response_tokens += chunk["answer"].content

29
backend/modules/brain/rags/quivr_rag.py
View File

@ -1,3 +1,4 @@
import datetime
import os
from operator import itemgetter
from typing import List, Optional
@ -44,9 +45,18 @@ class cited_answer(BaseModelV1):
description="The integer IDs of the SPECIFIC sources which justify the answer.",
)
thoughts: str = FieldV1(
...,
description="Explain shortly what you did to generate the answer. Explain any assumptions you made, and why you made them.",
)
followup_questions: List[str] = FieldV1(
...,
description="Generate up to 3 follow-up questions that could be asked based on the answer given or context provided.",
)
# First step is to create the Rephrasing Prompt
_template = """Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question, in its original language. Keep as much details as possible from previous messages. Keep entity names and all.
_template = """Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question, in its original language. Keep as much details as possible from previous messages. Keep entity names and all.
Chat History:
{chat_history}
@ -64,11 +74,20 @@ User Question: {question}
Answer:
"""
system_message_template = """
When answering use markdown to make it concise and neat.
Use the following pieces of context from files provided by the user that are store in a brain to answer the users question in the same language as the user question. Your name is Quivr. You're a helpful assistant.
today_date = datetime.datetime.now().strftime("%B %d, %Y")
system_message_template = (
f"Your name is Quivr. You're a helpful assistant. Today's date is {today_date}."
)
system_message_template += """
When answering use markdown neat.
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.
If you don't know the answer with the context provided from the files, just say that you don't know, don't try to make up an answer.
User instruction to follow if provided to answer: {custom_instructions}
If not None, User instruction to follow to answer: {custom_instructions}
Don't cite the source id in the answer objects, but you can use the source to answer the question.
"""