140 lines
5.3 KiB
Python
140 lines
5.3 KiB
Python
import atexit
|
|
import Levenshtein
|
|
import os
|
|
import sys
|
|
|
|
sys.path.append(os.path.join(os.path.dirname(__file__), os.path.pardir))
|
|
|
|
import streamlit as st
|
|
from streamlit_chat import message
|
|
from query_methods import query, avail_query_methods
|
|
import pickle
|
|
|
|
conversations_file = "conversations.pkl"
|
|
|
|
def load_conversations():
|
|
try:
|
|
with open(conversations_file, "rb") as f:
|
|
return pickle.load(f)
|
|
except FileNotFoundError:
|
|
return []
|
|
except EOFError:
|
|
return []
|
|
|
|
|
|
def save_conversations(conversations, current_conversation):
|
|
updated = False
|
|
for idx, conversation in enumerate(conversations):
|
|
if conversation == current_conversation:
|
|
conversations[idx] = current_conversation
|
|
updated = True
|
|
break
|
|
if not updated:
|
|
conversations.append(current_conversation)
|
|
|
|
temp_conversations_file = "temp_" + conversations_file
|
|
with open(temp_conversations_file, "wb") as f:
|
|
pickle.dump(conversations, f)
|
|
|
|
os.replace(temp_conversations_file, conversations_file)
|
|
|
|
|
|
def exit_handler():
|
|
print("Exiting, saving data...")
|
|
# Perform cleanup operations here, like saving data or closing open files.
|
|
save_conversations(st.session_state.conversations, st.session_state.current_conversation)
|
|
|
|
|
|
# Register the exit_handler function to be called when the program is closing.
|
|
atexit.register(exit_handler)
|
|
|
|
st.header("Chat Placeholder")
|
|
|
|
if 'conversations' not in st.session_state:
|
|
st.session_state['conversations'] = load_conversations()
|
|
|
|
if 'input_text' not in st.session_state:
|
|
st.session_state['input_text'] = ''
|
|
|
|
if 'selected_conversation' not in st.session_state:
|
|
st.session_state['selected_conversation'] = None
|
|
|
|
if 'input_field_key' not in st.session_state:
|
|
st.session_state['input_field_key'] = 0
|
|
|
|
if 'query_method' not in st.session_state:
|
|
st.session_state['query_method'] = query
|
|
|
|
if 'search_query' not in st.session_state:
|
|
st.session_state['search_query'] = ''
|
|
|
|
# Initialize new conversation
|
|
if 'current_conversation' not in st.session_state or st.session_state['current_conversation'] is None:
|
|
st.session_state['current_conversation'] = {'user_inputs': [], 'generated_responses': []}
|
|
|
|
input_placeholder = st.empty()
|
|
user_input = input_placeholder.text_input(
|
|
'You:', value=st.session_state['input_text'], key=f'input_text_-1'#{st.session_state["input_field_key"]}
|
|
)
|
|
submit_button = st.button("Submit")
|
|
|
|
if (user_input and user_input != st.session_state['input_text']) or submit_button:
|
|
output = query(user_input, st.session_state['query_method'])
|
|
|
|
escaped_output = output.encode('utf-8').decode('unicode-escape')
|
|
|
|
st.session_state['current_conversation']['user_inputs'].append(user_input)
|
|
st.session_state.current_conversation['generated_responses'].append(escaped_output)
|
|
save_conversations(st.session_state.conversations, st.session_state.current_conversation)
|
|
st.session_state['input_text'] = ''
|
|
st.session_state['input_field_key'] += 1 # Increment key value for new widget
|
|
user_input = input_placeholder.text_input(
|
|
'You:', value=st.session_state['input_text'], key=f'input_text_{st.session_state["input_field_key"]}'
|
|
) # Clear the input field
|
|
|
|
# Add a button to create a new conversation
|
|
if st.sidebar.button("New Conversation"):
|
|
st.session_state['selected_conversation'] = None
|
|
st.session_state['current_conversation'] = {'user_inputs': [], 'generated_responses': []}
|
|
st.session_state['input_field_key'] += 1 # Increment key value for new widget
|
|
st.session_state['query_method'] = st.sidebar.selectbox("Select API:", options=avail_query_methods, index=0)
|
|
|
|
# Proxy
|
|
st.session_state['proxy'] = st.sidebar.text_input("Proxy: ")
|
|
|
|
# Searchbar
|
|
search_query = st.sidebar.text_input("Search Conversations:", value=st.session_state.get('search_query', ''), key='search')
|
|
|
|
if search_query:
|
|
filtered_conversations = []
|
|
indices = []
|
|
for idx, conversation in enumerate(st.session_state.conversations):
|
|
if search_query in conversation['user_inputs'][0]:
|
|
filtered_conversations.append(conversation)
|
|
indices.append(idx)
|
|
|
|
filtered_conversations = list(zip(indices, filtered_conversations))
|
|
conversations = sorted(filtered_conversations, key=lambda x: Levenshtein.distance(search_query, x[1]['user_inputs'][0]))
|
|
|
|
sidebar_header = f"Search Results ({len(conversations)})"
|
|
else:
|
|
conversations = enumerate(st.session_state.conversations)
|
|
sidebar_header = "Conversation History"
|
|
|
|
# Sidebar
|
|
st.sidebar.header(sidebar_header)
|
|
|
|
for idx, conversation in conversations:
|
|
if st.sidebar.button(f"Conversation {idx + 1}: {conversation['user_inputs'][0]}", key=f"sidebar_btn_{idx}"):
|
|
st.session_state['selected_conversation'] = idx
|
|
st.session_state['current_conversation'] = conversation
|
|
|
|
if st.session_state['selected_conversation'] is not None:
|
|
conversation_to_display = conversations[st.session_state['selected_conversation']]
|
|
else:
|
|
conversation_to_display = st.session_state.current_conversation
|
|
|
|
if conversation_to_display['generated_responses']:
|
|
for i in range(len(conversation_to_display['generated_responses']) - 1, -1, -1):
|
|
message(conversation_to_display["generated_responses"][i], key=f"display_generated_{i}")
|
|
message(conversation_to_display['user_inputs'][i], is_user=True, key=f"display_user_{i}") |