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import openai
import streamlit as st
from PIL import Image
st.title("Movies Etc")
# Streamlit Secrets
openai.api_key = st.secrets["OPENAI_API_KEY"]
grounding = st.secrets["GROUNDING"]
image = Image.open('logo.jpeg')
st.image(image)
if "openai_model" not in st.session_state:
st.session_state["openai_model"] = "gpt-3.5-turbo"
if "messages" not in st.session_state:
st.session_state.messages = []
st.session_state.messages.append({"role": "system", "content": grounding})
for message in st.session_state.messages:
if message["role"] != "system":
with st.chat_message(message["role"]):
st.markdown(message["content"])
if prompt := st.chat_input("How can I help you today?"):
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.markdown(prompt)
with st.chat_message("assistant"):
message_placeholder = st.empty()
full_response = ""
for response in openai.ChatCompletion.create(
model=st.session_state["openai_model"],
messages=[
{"role": m["role"], "content": m["content"]}
for m in st.session_state.messages
],
stream=True,
):
full_response += response.choices[0].delta.get("content", "").replace('\\$','$').replace('$','\\$')
message_placeholder.markdown(full_response + "▌")
message_placeholder.markdown(full_response)
print(full_response)
st.session_state.messages.append({"role": "assistant", "content": full_response}) |