Spaces:
Running
Running
File size: 3,442 Bytes
db694c4 d026604 db694c4 d026604 db694c4 d026604 db694c4 d026604 db694c4 d026604 db694c4 d026604 db694c4 c6352d6 db694c4 5abcb47 db694c4 b6cdc6a db694c4 09f2e2a db694c4 c6352d6 db694c4 d026604 09f2e2a c3572db db694c4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 |
import streamlit as st
import os
import openai
from openai import OpenAI
# App title
st.set_page_config(page_title="π¬ Open AI Chatbot")
# Replicate Credentials
with st.sidebar:
st.title("π¬ 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="β
")
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="β οΈ")
else:
st.success("Proceed to entering your prompt message!", icon="π")
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("π 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) |