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import logging
import random
import json5
import streamlit as st
from langchain_community.chat_message_histories import (
StreamlitChatMessageHistory
)
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables.history import RunnableWithMessageHistory
from global_config import GlobalConfig
from helpers import llm_helper
APP_TEXT = json5.loads(open(GlobalConfig.APP_STRINGS_FILE, 'r', encoding='utf-8').read())
# langchain.debug = True
# langchain.verbose = True
logger = logging.getLogger(__name__)
progress_bar = st.progress(0, text='Setting up SlideDeck AI...')
def display_page_header_content():
"""
Display content in the page header.
"""
st.title(APP_TEXT['app_name'])
st.subheader(APP_TEXT['caption'])
st.markdown(
'Powered by'
' [Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)'
)
def display_page_footer_content():
"""
Display content in the page footer.
"""
st.text(APP_TEXT['tos'] + '\n\n' + APP_TEXT['tos2'])
# st.markdown(
# '' # noqa: E501
# )
def build_ui():
"""
Display the input elements for content generation.
"""
display_page_header_content()
with st.expander('Usage Policies and Limitations'):
display_page_footer_content()
progress_bar.progress(50, text='Setting up chat interface...')
set_up_chat_ui()
def set_up_chat_ui():
"""
Prepare the chat interface and related functionality.
"""
history = StreamlitChatMessageHistory(key='chat_messages')
llm = llm_helper.get_hf_endpoint()
with open(GlobalConfig.CHAT_TEMPLATE_FILE, 'r', encoding='utf-8') as in_file:
template = in_file.read()
prompt = ChatPromptTemplate.from_template(template)
chain = prompt | llm
chain_with_history = RunnableWithMessageHistory(
chain,
lambda session_id: history, # Always return the instance created earlier
input_messages_key='question',
history_messages_key='chat_history',
)
with st.expander('Usage Instructions'):
st.write(GlobalConfig.CHAT_USAGE_INSTRUCTIONS)
st.chat_message('ai').write(
random.choice(APP_TEXT['ai_greetings'])
)
for msg in history.messages:
st.chat_message(msg.type).markdown(msg.content)
progress_bar.progress(100, text='Done!')
progress_bar.empty()
if prompt := st.chat_input(
placeholder=APP_TEXT['chat_placeholder'],
max_chars=GlobalConfig.LLM_MODEL_MAX_INPUT_LENGTH
):
logger.debug('User input: %s', prompt)
st.chat_message('user').write(prompt)
# As usual, new messages are added to StreamlitChatMessageHistory when the Chain is called
config = {'configurable': {'session_id': 'any'}}
response = chain_with_history.invoke({'question': prompt}, config)
st.chat_message('ai').markdown('```json\n' + response)
def main():
"""
Trigger application run.
"""
build_ui()
if __name__ == '__main__':
main()
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