Spaces:
Runtime error
Runtime error
| """ | |
| Python Backend API to chat with private data | |
| 08/16/2023 | |
| D.M. Theekshana Samaradiwakara | |
| """ | |
| import os | |
| import time | |
| import streamlit as st | |
| from streamlit.logger import get_logger | |
| logger = get_logger(__name__) | |
| from ui.htmlTemplates import css, bot_template, user_template, source_template | |
| from config import MODELS, DATASETS | |
| from qaPipeline import QAPipeline | |
| from faissDb import create_faiss | |
| # loads environment variables | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| isHuggingFaceHubEnabled = os.environ.get('ENABLE_HUGGINGFSCE_HUB_MODELS') | |
| isOpenAiApiEnabled = os.environ.get('ENABLE_OPENAI_API_MODELS') | |
| st.set_page_config(page_title="Chat with data", | |
| page_icon=":books:") | |
| st.write(css, unsafe_allow_html=True) | |
| SESSION_DEFAULTS = { | |
| "model": MODELS["DEFAULT"], | |
| "dataset": DATASETS["DEFAULT"], | |
| "chat_history": None, | |
| "is_parameters_changed":False, | |
| "show_source_files": False, | |
| "user_question":'', | |
| } | |
| for k, v in SESSION_DEFAULTS.items(): | |
| if k not in st.session_state: | |
| st.session_state[k] = v | |
| with st.sidebar: | |
| st.subheader("Chat parameters") | |
| with st.form('param_form'): | |
| chat_model = st.selectbox( | |
| "Chat model", | |
| MODELS, | |
| key="chat_model", | |
| help="Select the LLM model for the chat", | |
| # on_change=update_parameters_change, | |
| ) | |
| st.session_state.dataset = "DEFAULT" | |
| show_source = st.checkbox( | |
| label="show source files", | |
| key="show_source", | |
| help="Select this to show relavant source files for the query", | |
| ) | |
| submitted = st.form_submit_button( | |
| "Submit", | |
| # on_click=parameters_change_button, | |
| # args=[chat_model, show_source] | |
| ) | |
| # submitted = st.button( | |
| # "Submit", | |
| # # on_click=parameters_change_button, | |
| # # args=[chat_model, show_source] | |
| # ) | |
| if submitted: | |
| st.session_state.model = chat_model | |
| st.session_state.dataset = "DEFAULT" | |
| st.session_state.show_source_files = show_source | |
| st.session_state.is_parameters_changed = False | |
| alert = st.success("chat parameters updated") | |
| time.sleep(1) # Wait for 3 seconds | |
| alert.empty() # Clear the alert | |
| st.markdown("\n") | |
| # if st.button("Create FAISS db"): | |
| # try: | |
| # with st.spinner('creating faiss vector store'): | |
| # create_faiss() | |
| # st.success('faiss saved') | |
| # except Exception as e: | |
| # st.error(f"Error : {e}")#, icon=":books:") | |
| # return | |
| st.markdown( | |
| "### How to use\n" | |
| "1. Select the chat model\n" # noqa: E501 | |
| "2. Select \"show source files\" to show the source files related to the answer.📄\n" | |
| "3. Ask a question about the documents💬\n" | |
| ) | |
| st.header("Chat with your own data:") | |
| # 👈 Add the caching decorator | |
| def load_QaPipeline(): | |
| print('> QAPipeline loaded for front end') | |
| return QAPipeline() | |
| qaPipeline = load_QaPipeline() | |
| # qaPipeline = QAPipeline() | |
| with st.form('chat_body'): | |
| user_question = st.text_input( | |
| "Ask a question about your documents:", | |
| placeholder="enter question", | |
| key='user_question', | |
| # on_change=submit_user_question, | |
| ) | |
| submitted = st.form_submit_button( | |
| "Submit", | |
| # on_click=submit_user_question | |
| ) | |
| if submitted: | |
| with st.spinner("Processing"): | |
| user_question = st.session_state.user_question | |
| # st.success(user_question) | |
| query = user_question | |
| # st.session_state.user_question='' | |
| # Get the answer from the chain | |
| try: | |
| if (not query) or (query.strip() == ''): | |
| st.error("Please enter a question!") | |
| st.stop() | |
| model = MODELS[st.session_state.model] | |
| dataset = DATASETS[st.session_state.dataset] | |
| show_source_files = st.session_state.show_source_files | |
| # Try to access openai and deeplake | |
| print(f">\n model: {model} \n dataset : {dataset} \n show_source_files : {show_source_files}") | |
| # response = qaPipeline.run(query=query, model=model, dataset=dataset) | |
| response = qaPipeline.run_agent(query=query, model=model, dataset=dataset) | |
| docs = [] | |
| if isinstance(response, dict): | |
| answer, docs = response['answer'], response['source_documents'] | |
| else: | |
| answer = response | |
| st.write(user_template.replace( | |
| "{{MSG}}", query), unsafe_allow_html=True) | |
| st.write(bot_template.replace( | |
| "{{MSG}}", answer ), unsafe_allow_html=True) | |
| if show_source_files: | |
| # st.write(source_template.replace( | |
| # "{{MSG}}", "source files" ), unsafe_allow_html=True) | |
| if len(docs)>0 : | |
| st.markdown("#### source files : ") | |
| for source in docs: | |
| # st.info(source.metadata) | |
| with st.expander(source.metadata["source"]): | |
| st.markdown(source.page_content) | |
| # st.write(response) | |
| except Exception as e: | |
| # logger.error(f"Answer retrieval failed with {e}") | |
| st.error(f"Error : {e}")#, icon=":books:") | |