Spaces:
Running
Running
File size: 4,444 Bytes
c76bbac |
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 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 |
import time
import os
import joblib
import streamlit as st
import google.generativeai as genai
from dotenv import load_dotenv
load_dotenv()
GOOGLE_API_KEY=os.environ.get('GOOGLE_API_KEY')
genai.configure(api_key=GOOGLE_API_KEY)
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-2.0-flash')
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',
) |