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Update app.py
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import streamlit as st
from openai import OpenAI
import os
import sys
from dotenv import load_dotenv, dotenv_values
load_dotenv()
# initialize the client
client = OpenAI(
base_url="https://api-inference.huggingface.co/v1",
api_key=os.environ.get('HUGGINGFACEHUB_API_TOKEN') # Replace with your token
)
# Create supported models
model_links = {
"Mixtral-8x7B-Instruct-v0.1": "mistralai/Mixtral-8x7B-Instruct-v0.1",
"Mistral-Nemo-Instruct-2407": "mistralai/Mistral-Nemo-Instruct-2407",
"Nous-Hermes-2-Mixtral-8x7B-DPO": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
"Mistral-7B-Instruct-v0.1": "mistralai/Mistral-7B-Instruct-v0.1",
"Mistral-7B-Instruct-v0.2": "mistralai/Mistral-7B-Instruct-v0.2",
"Mistral-7B-Instruct-v0.3": "mistralai/Mistral-7B-Instruct-v0.3",
"Mistral-Small-Instruct-2409": "mistralai/Mistral-Small-Instruct-2409",
}
def reset_conversation():
#st.session_state.conversation = []
st.session_state.messages = []
return None
def ask_assistant_stream(st_model, st_messages, st_temp_value, st_max_tokens):
response=[]
try:
stream = client.chat.completions.create(
model=st_model,
messages=[
{"role": m["role"], "content": m["content"]}
for m in st_messages
],
temperature=st_temp_value,
stream=True,
max_tokens=st_max_tokens,
)
response["stream"] = stream
except Exception as e:
pass
return response
# Define the available models
models =[key for key in model_links.keys()]
# Create the sidebar with the dropdown for model selection
selected_model = st.sidebar.selectbox("Select Model", models)
# Create a temperature slider
temp_values = st.sidebar.slider('Select a temperature value', 0.0, 1.0, (0.5))
# Create a max_token slider
max_token_value = st.sidebar.slider('Select a max_token value', 1000, 9000, (5000))
#Add reset button to clear conversation
st.sidebar.button('Reset Chat', on_click=reset_conversation) #Reset button
# Create model description
st.sidebar.write(f"You're now chatting with **{selected_model}**")
st.sidebar.markdown("*Generated content may be inaccurate or false.*")
# st.sidebar.markdown("\n[TypeGPT](https://typegpt.net).")
if "prev_option" not in st.session_state:
st.session_state.prev_option = selected_model
if st.session_state.prev_option != selected_model:
st.session_state.messages = []
# st.write(f"Changed to {selected_model}")
st.session_state.prev_option = selected_model
reset_conversation()
#Pull in the model we want to use
repo_id = model_links[selected_model]
st.subheader(f'{selected_model}')
# # st.title(f'ChatBot Using {selected_model}')
# Set a default model
if selected_model not in st.session_state:
st.session_state[selected_model] = model_links[selected_model]
# 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"])
if "retry" not in st.session_state:
st.session_state.retry= False
def retry_click():
st.session_state.retry= True
if st.session_state.retry:
lastmessage = st.session_state.messages.pop()
st.toast("popped msg: " + lastmessage["content"] + " // model: " + model_links[selected_model])
response = get_assistant_aswer(model_links[selected_model], st.session_state.messages, temp_values, max_token_value)
st.session_state.messages.append({"role": "assistant", "content": response})
st.session_state.retry= False
st.rerun()
if "remove" not in st.session_state:
st.session_state.remove= False
def remove_click():
st.session_state.remove= True
if st.session_state.remove:
lastmessage = st.session_state.messages.pop()
prelastmessage = st.session_state.messages.pop()
st.toast("popped msg: " + lastmessage["content"] + " // model: " + model_links[selected_model])
st.session_state.remove= False
st.rerun()
# Accept user input
if prompt := st.chat_input(f"Hi I'm {selected_model}, ask me a question"):
# Display user message in chat message container and Add user message to chat history
with st.chat_message("user"):
st.markdown(prompt)
st.session_state.messages.append({"role": "user", "content": prompt})
# Display assistant response in chat message container
assistant = ask_assistant_stream(model_links[selected_model], st.session_state.messages, temp_values, max_token_value)
st.write assistant
if "stream" in assistant:
with st.chat_message("assistant"):
response = st.write_stream(assistant["stream"])
else:
with st.chat_message("assistant"):
response = st.write("Failure")
st.session_state.messages.append({"role": "assistant", "content": response})
if len(st.session_state.messages)>0:
col1, col2 = st.columns(2)
col1.button("retry", key="retryButton", on_click=retry_click)
col2.button("remove", key="removeButton", on_click=remove_click)