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1.08 kB
| import streamlit as st | |
| from langchain_community.llms import OpenAI | |
| st.title("Maths Problem Solving with Adolina!") | |
| def mathematics(topic): | |
| prompt = ( | |
| f"Solve this: {topic} as a CBSE Board Mathematics Teacher. " | |
| "You need to provide solutions for the questions asked in the following format:\n\n" | |
| "1. Problem Statement: State the problem clearly.\n" | |
| "2. Solution Approach: Solve as per CBSE guidelines.\n" | |
| "3. Step-by-Step Solution: Show the method of solution.\n" | |
| "4. Final Answer: Clearly present the final answer, with any necessary units or explanations." | |
| ) | |
| llm = OpenAI(temperature=0.7, openai_api_key=st.secrets["sk-proj-q7ZheuD9p1QQ9zdOFcesT3BlbkFJ8zIk4TSUwCDpYrOIk0nV"]) | |
| response = llm(prompt) | |
| return response | |
| with st.form("my_form"): | |
| topic = st.text_area("Mathematics with Adolina") | |
| submitted = st.form_submit_button("Ask to Spot") | |
| if submitted and topic: | |
| post = mathematics(topic) | |
| st.info(post) | |
| elif submitted and not topic: | |
| st.error("Give me problems.") | |