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from langchain_community.llms import OpenAI | |
from langchain_google_genai import ChatGoogleGenerativeAI | |
def GetLLMResponse(selected_topic_level, selected_topic,num_quizzes, model): | |
question_prompt = ('I want you to just generate question with this specification: Generate a {selected_topic_level} math quiz on the topic of {selected_topic}. Generate only {num_quizzes} questions not more and without providing answers.') | |
if model == "Open AI": | |
llm = OpenAI(temperature=0.7, openai_api_key=st.secrets["OPENAI_API_KEY"]) | |
questions = llm(question_prompt) | |
# return questions | |
elif model == "Gemini": | |
llm = ChatGoogleGenerativeAI(model="gemini-pro", google_api_key=st.secrets["GOOGLE_API_KEY"]) | |
questions = llm.invoke(question_prompt) | |
# return questions.content | |
answer_prompt = ( "I want you to become a teacher answer this specific Question:\n {questions}\n\n. You should gave me a straightforward and consise explanation and answer to each one of them") | |
if model == "Open AI": | |
llm = OpenAI(temperature=0.7, openai_api_key=st.secrets["OPENAI_API_KEY"]) | |
answers = llm(answer_prompt) | |
# return questions | |
elif model == "Gemini": | |
llm = ChatGoogleGenerativeAI(model="gemini-pro", google_api_key=st.secrets["GOOGLE_API_KEY"]) | |
answers = llm.invoke(answer_prompt) | |
# return questions.content | |
return(questions,answers) | |