Spaces:
Sleeping
Sleeping
import streamlit as st | |
import openai | |
import os | |
# Set up OpenAI API key | |
openai.api_key = os.getenv("OPENAI_API_KEY") | |
st.title("Coding Interview Bot") | |
# Initialize chat history | |
if "messages" not in st.session_state: | |
st.session_state.messages = [] | |
# Display chat messages from history on app rerun | |
for message in st.session_state.messages: | |
with st.chat_message(message["role"]): | |
st.markdown(message["content"]) | |
# Function to generate response using OpenAI API | |
def generate_response(prompt): | |
response = openai.ChatCompletion.create( | |
model="gpt-3.5-turbo", | |
messages=[ | |
{"role": "system", "content": "You are a coding interview bot. Your task is to ask coding interview questions, evaluate responses, and provide feedback."}, | |
{"role": "user", "content": prompt} | |
], | |
max_tokens=1000, | |
temperature=0.7, | |
) | |
return response.choices[0].message['content'] | |
# React to user input | |
if prompt := st.chat_input("What's your coding question?"): | |
# Display user message in chat message container | |
st.chat_message("user").markdown(prompt) | |
# Add user message to chat history | |
st.session_state.messages.append({"role": "user", "content": prompt}) | |
# Generate response | |
response = generate_response(prompt) | |
# Display assistant response in chat message container | |
with st.chat_message("assistant"): | |
st.markdown(response) | |
# Add assistant response to chat history | |
st.session_state.messages.append({"role": "assistant", "content": response}) | |
st.sidebar.markdown(""" | |
## About | |
This is a coding interview bot powered by OpenAI's GPT-3.5-turbo. | |
Ask coding questions and get responses to help you prepare for interviews! | |
""") |