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| 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) |