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import streamlit as st
import html
from openai import OpenAI
import os
# Load environment variables
from dotenv import load_dotenv
load_dotenv()
api_key = os.getenv("OPENAI_API_KEY")
# Initialize the OpenAI client
client = OpenAI(api_key=api_key)
def openai_chat(prompt, chat_log):
context_messages = [
{"role": "system", "content": """You are a gifted C++ professor. You explain complex C++
concepts clearly using words that a
college student would understand, and generate typical exam questions for a C++ course. After a few questions,
three or four, check in with the student to ask if you are helpful and if the student is prepared for the exam
or stuck on a particular topic, or just needs a cram session before the exam. Be supportive and motivational.
Suggest getting a good night's sleep and eating properly before the exam when saying goodbye. After answering
a question from the student, suggest three or four C++ final exam questions and related topics when asked anything."""
},
{"role": "user", "content": "Explain recursion in C++ programming."}
] + chat_log + [{"role": "user", "content": prompt}]
try:
completion = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=context_messages,
max_tokens=500
)
response_text = html.unescape(completion.choices[0].message.content)
chat_log.append({"role": "assistant", "content": response_text})
return response_text, chat_log
except Exception as e:
return str(e), chat_log
def format_response(answer):
# Only apply Markdown to code responses
if 'int main()' in answer or '#include' in answer or 'std::' in answer:
code_block = "```cpp\n" + answer + "\n```"
return code_block
return answer
def main():
st.title("Professor CplusPlus")
st.write("Ask any question about C++, and I'll explain!")
if 'chat_log' not in st.session_state:
st.session_state.chat_log = []
if 'history' not in st.session_state:
st.session_state.history = ""
user_input = st.text_input("Type your question here:", key="user_input")
if st.button("Ask") and user_input:
answer, st.session_state.chat_log = openai_chat(user_input, st.session_state.chat_log)
formatted_answer = format_response(answer)
new_entry = f"Q: {user_input}\n\nA: {formatted_answer}\n\n"
st.session_state.history = new_entry + st.session_state.history
st.rerun() # Using the updated rerun method
st.write("Chat History:")
st.markdown(st.session_state.history, unsafe_allow_html=True)
if __name__ == "__main__":
main()
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