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import time | |
import os | |
import joblib | |
import streamlit as st | |
import google.generativeai as genai | |
disable=False | |
if 'form_submitted' not in st.session_state: | |
st.session_state['form_submitted'] = False | |
# Display the form conditionally | |
if not st.session_state['form_submitted']: | |
with st.form('myform', clear_on_submit=True): | |
google_api_key = st.text_input('Google API Key', type='password') | |
submitted = st.form_submit_button('Submit') | |
if submitted: | |
genai.configure(api_key=google_api_key) | |
st.session_state['form_submitted'] = True | |
disable=True | |
new_chat_id = f'{time.time()}' | |
MODEL_ROLE = 'ai' | |
AI_AVATAR_ICON = '✨' | |
# Create a data/ folder if it doesn't already exist | |
try: | |
os.mkdir('data/') | |
except: | |
# data/ folder already exists | |
pass | |
# Load past chats (if available) | |
try: | |
past_chats: dict = joblib.load('data/past_chats_list') | |
except: | |
past_chats = {} | |
# Sidebar allows a list of past chats | |
with st.sidebar: | |
st.write('# Past Chats') | |
if st.session_state.get('chat_id') is None: | |
st.session_state.chat_id = st.selectbox( | |
label='Pick a past chat', | |
options=[new_chat_id] + list(past_chats.keys()), | |
format_func=lambda x: past_chats.get(x, 'New Chat'), | |
placeholder='_', | |
) | |
else: | |
# This will happen the first time AI response comes in | |
st.session_state.chat_id = st.selectbox( | |
label='Pick a past chat', | |
options=[new_chat_id, st.session_state.chat_id] + list(past_chats.keys()), | |
index=1, | |
format_func=lambda x: past_chats.get(x, 'New Chat' if x != st.session_state.chat_id else st.session_state.chat_title), | |
placeholder='_', | |
) | |
# Save new chats after a message has been sent to AI | |
# TODO: Give user a chance to name chat | |
st.session_state.chat_title = f'ChatSession-{st.session_state.chat_id}' | |
st.write('# Chat with Gemini') | |
# Chat history (allows to ask multiple questions) | |
try: | |
st.session_state.messages = joblib.load( | |
f'data/{st.session_state.chat_id}-st_messages' | |
) | |
st.session_state.gemini_history = joblib.load( | |
f'data/{st.session_state.chat_id}-gemini_messages' | |
) | |
print('old cache') | |
except: | |
st.session_state.messages = [] | |
st.session_state.gemini_history = [] | |
print('new_cache made') | |
st.session_state.model = genai.GenerativeModel('gemini-pro') | |
st.session_state.chat = st.session_state.model.start_chat( | |
history=st.session_state.gemini_history, | |
) | |
# Display chat messages from history on app rerun | |
for message in st.session_state.messages: | |
with st.chat_message( | |
name=message['role'], | |
avatar=message.get('avatar'), | |
): | |
st.markdown(message['content']) | |
# React to user input | |
if prompt := st.chat_input('Your message here...'): | |
# Save this as a chat for later | |
if st.session_state.chat_id not in past_chats.keys(): | |
past_chats[st.session_state.chat_id] = st.session_state.chat_title | |
joblib.dump(past_chats, 'data/past_chats_list') | |
# Display user message in chat message container | |
with st.chat_message('user'): | |
st.markdown(prompt) | |
# Add user message to chat history | |
st.session_state.messages.append( | |
dict( | |
role='user', | |
content=prompt, | |
) | |
) | |
## Send message to AI | |
response = st.session_state.chat.send_message( | |
prompt, | |
stream=True, | |
) | |
# Display assistant response in chat message container | |
with st.chat_message( | |
name=MODEL_ROLE, | |
avatar=AI_AVATAR_ICON, | |
): | |
message_placeholder = st.empty() | |
full_response = '' | |
assistant_response = response | |
# Streams in a chunk at a time | |
for chunk in response: | |
# Simulate stream of chunk | |
# TODO: Chunk missing `text` if API stops mid-stream ("safety"?) | |
for ch in chunk.text.split(' '): | |
full_response += ch + ' ' | |
time.sleep(0.05) | |
# Rewrites with a cursor at end | |
message_placeholder.write(full_response + '▌') | |
# Write full message with placeholder | |
message_placeholder.write(full_response) | |
# Add assistant response to chat history | |
st.session_state.messages.append( | |
dict( | |
role=MODEL_ROLE, | |
content=st.session_state.chat.history[-1].parts[0].text, | |
avatar=AI_AVATAR_ICON, | |
) | |
) | |
st.session_state.gemini_history = st.session_state.chat.history | |
# Save to file | |
joblib.dump( | |
st.session_state.messages, | |
f'data/{st.session_state.chat_id}-st_messages', | |
) | |
joblib.dump( | |
st.session_state.gemini_history, | |
f'data/{st.session_state.chat_id}-gemini_messages', | |
) |