Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| from openai import OpenAI | |
| from app_kb_handler import * | |
| # model = "gpt-3.5-turbo" | |
| model = "gpt-4-turbo" | |
| # ------------------------------------------------------------------------------------------------ | |
| # SIDEBAR | |
| # ------------------------------------------------------------------------------------------------ | |
| st.sidebar.title('OpenAI Knowledge Base of Irembo') | |
| st.sidebar.write('This chat bot is build with RAG architecture and OpenAI as LLM. All the Knowledge Base have been crawl automatically from the website https://support.irembo.gov.rw/ ') | |
| def onchange_openai_key(): | |
| print(st.session_state.openai_key) | |
| openai_key = st.sidebar.text_input('OpenAI key', on_change=onchange_openai_key, key='openai_key') | |
| def submit_openai_key(model=model): | |
| if(openai_key == None or openai_key==''): | |
| st.sidebar.write('Please provide the key before') | |
| return | |
| else: | |
| client = OpenAI(api_key=openai_key) | |
| model = model | |
| completion = client.chat.completions.create( | |
| model=model, | |
| messages=[ | |
| {"role": "system", "content": "You are an assistant giving simple and short answer for question of child"}, | |
| {"role": "user", "content": "count from 0 to 10"} | |
| ] | |
| ) | |
| st.sidebar.write(f'Simple count : {completion.choices[0].message.content}') | |
| submit_key = st.sidebar.button(label='Submit', on_click=submit_openai_key) | |
| # ------------------------------------------------------------------------------------------------ | |
| # CHAT TITLE | |
| # ------------------------------------------------------------------------------------------------ | |
| st.title('OpenAI Knowledge Base of Irembo') | |
| st.write(f'Ask any question regarding using Irembo platform to apply for any services.') | |
| def askQuestion(model=model, question=''): | |
| if(openai_key == None or openai_key==''): | |
| print('Please provide the key before') | |
| return 'LLM API is not defined. Please provide the key before' | |
| else: | |
| if "df" not in st.session_state: | |
| st.session_state.df = get_embeddings() | |
| return answer_question(api_key=openai_key, question=f'{question}', df=st.session_state.df, model=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"]) | |
| # React to user input | |
| if prompt := st.chat_input("What is up?"): | |
| with st.status('Running', expanded=True) as status: | |
| # Display user message in chat message container | |
| st.chat_message("user").markdown(prompt) | |
| # Add user message to chat history | |
| st.session_state.messages.append({"role": "user", "content": prompt}) | |
| response = askQuestion(question=prompt) | |
| # Display assistant response in chat message container | |
| with st.chat_message("assistant"): | |
| st.markdown(response) | |
| # Add assistant response to chat history | |
| st.session_state.messages.append({"role": "assistant", "content": response}) | |
| status.update(label='Reponse of last question', state="complete", expanded=True) | |