File size: 2,191 Bytes
1ef298a 0f046d0 1ef298a 0f046d0 c1a68be 0f046d0 c1a68be 1ef298a 0f046d0 1ef298a 0f046d0 1ef298a 0f046d0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 |
from typing import List
import json
from langchain_core.prompts import ChatPromptTemplate
from langchain_openai import ChatOpenAI
from langchain_core.runnables import RunnablePassthrough
from langchain_core.output_parsers import StrOutputParser
from langchain.output_parsers.openai_functions import JsonOutputFunctionsParser
from backend.app.vectorstore import get_vector_db
class ProblemGenerator:
def __init__(self):
# Initialize prompts
self.system_role_prompt = """
You are a helpful assistant that generates questions based on a given context.
"""
self.user_role_prompt = """
Based on the following context about {query}, generate 5 relevant and specific questions.
Make sure the questions can be answered using only the provided context.
Context: {context}
Generate 5 questions that test understanding of the material in the context.
Return only a json object with the following format:
{{
"questions": ["question1", "question2", "question3", "question4", "question5"]
}}
"""
# Initialize chain components
self.chat_prompt = ChatPromptTemplate.from_messages([
("system", self.system_role_prompt),
("user", self.user_role_prompt)
])
self.llm = ChatOpenAI(model="gpt-3.5-turbo", temperature=0.7)
self.retriever = get_vector_db().as_retriever(search_kwargs={"k": 2})
# Build the RAG chain
self.rag_chain = (
{"context": self.retriever, "query": RunnablePassthrough()}
| self.chat_prompt
| self.llm
| StrOutputParser()
)
def generate_problems(self, query: str) -> List[str]:
"""
Generate problems based on the user's query using RAG.
Args:
query (str): The topic to generate questions about
Returns:
List[str]: A list of generated questions
"""
raw_result = self.rag_chain.invoke(query)
result = json.loads(raw_result)
return result["questions"] |