import streamlit as st import os import openai from openai import OpenAI # App title st.set_page_config(page_title="💬 Open AI Chatbot") # Replicate Credentials with st.sidebar: st.title("💬 Open AI Chatbot") st.write("This chatbot is created using the GPT model from Open AI.") if "OPENAI_API_KEY" in st.secrets: st.success("API key already provided!", icon="✅") openai_api = st.secrets["OPENAI_API_KEY"] else: openai_api = st.text_input("Enter OpenAI API token:", type="password") if not (openai_api.startswith("sk-") and len(openai_api)==51): st.warning("Please enter your credentials!", icon="⚠️") else: st.success("Proceed to entering your prompt message!", icon="👉") os.environ["OPENAI_API_KEY"] = openai_api st.subheader("Models and parameters") selected_model = st.sidebar.selectbox("Choose an OpenAI model", ["gpt-3.5-turbo-1106", "gpt-4-1106-preview"], key="selected_model") temperature = st.sidebar.slider("temperature", min_value=0.01, max_value=2.0, value=0.1, step=0.01) st.markdown("📖 Reach out to SakiMilo to learn how to create this app!") # Store LLM generated responses if "messages" not in st.session_state.keys(): st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}] # Display or clear chat messages for message in st.session_state.messages: with st.chat_message(message["role"]): st.write(message["content"]) def clear_chat_history(): st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}] st.sidebar.button("Clear Chat History", on_click=clear_chat_history) def generate_llm_response(client, prompt_input): system_content = ("You are a helpful assistant. " "You do not respond as 'User' or pretend to be 'User'. " "You only respond once as 'Assistant'." ) completion = client.chat.completions.create( model=selected_model, messages=[ {"role": "system", "content": system_content}, ] + st.session_state.messages, temperature=temperature, stream=True ) return completion # User-provided prompt if prompt := st.chat_input(disabled=not openai_api): client = OpenAI() st.session_state.messages.append({"role": "user", "content": prompt}) with st.chat_message("user"): st.write(prompt) # Generate a new response if last message is not from assistant if st.session_state.messages[-1]["role"] != "assistant": with st.chat_message("assistant"): with st.spinner("Thinking..."): response = generate_llm_response(client, prompt) placeholder = st.empty() full_response = "" for chunk in response: if chunk.choices[0].delta.content is not None: full_response += chunk.choices[0].delta.content placeholder.markdown(full_response) placeholder.markdown(full_response) message = {"role": "assistant", "content": full_response} st.session_state.messages.append(message)