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| import streamlit as st | |
| from PIL import Image | |
| from .constants import QUERIES, PLAIN_GPT_ANS, GPT_WEB_RET_AUG_ANS, GPT_LOCAL_RET_AUG_ANS | |
| def set_question(): | |
| st.session_state['query'] = st.session_state['q_drop_down'] | |
| def set_q1(): | |
| st.session_state['query'] = QUERIES[0] | |
| def set_q2(): | |
| st.session_state['query'] = QUERIES[1] | |
| def set_q3(): | |
| st.session_state['query'] = QUERIES[2] | |
| def set_q4(): | |
| st.session_state['query'] = QUERIES[3] | |
| def set_q5(): | |
| st.session_state['query'] = QUERIES[4] | |
| def main_column(): | |
| placeholder = st.empty() | |
| with placeholder: | |
| search_bar, button = st.columns([3, 1]) | |
| with search_bar: | |
| username = st.text_area(f" ", max_chars=200, key='query') | |
| with button: | |
| st.write(" ") | |
| st.write(" ") | |
| run_pressed = st.button("Run", key="run") | |
| st.write(" ") | |
| st.radio("Answer Type:", ("Retrieval Augmented (Static news dataset)", "Retrieval Augmented with Web Search"), key="query_type") | |
| # st.sidebar.selectbox( | |
| # "Example Questions:", | |
| # QUERIES, | |
| # key='q_drop_down', on_change=set_question) | |
| st.markdown(f"<h5> {PLAIN_GPT_ANS} </h5>", unsafe_allow_html=True) | |
| placeholder_plain_gpt = st.empty() | |
| st.text(" ") | |
| st.text(" ") | |
| if st.session_state.get("query_type", "Retrieval Augmented (Static news dataset)") == "Retrieval Augmented (Static news dataset)": | |
| st.markdown(f"<h5> {GPT_LOCAL_RET_AUG_ANS} </h5>", unsafe_allow_html=True) | |
| else: | |
| st.markdown(f"<h5>{GPT_WEB_RET_AUG_ANS} </h5>", unsafe_allow_html=True) | |
| placeholder_retrieval_augmented = st.empty() | |
| return run_pressed, placeholder_plain_gpt, placeholder_retrieval_augmented | |
| def right_sidebar(): | |
| st.markdown("<h5> Example questions </h5>", unsafe_allow_html=True) | |
| # c1, c2, c3, c4, c5 = st.columns(5) | |
| # with c1: | |
| st.button(QUERIES[0], on_click=set_q1) | |
| # with c2: | |
| st.button(QUERIES[1], on_click=set_q2) | |
| # with c3: | |
| st.button(QUERIES[2], on_click=set_q3) | |
| # with c4: | |
| st.button(QUERIES[3], on_click=set_q4) | |
| # with c5: | |
| st.button(QUERIES[4], on_click=set_q5) | |
| def left_sidebar(): | |
| with st.sidebar: | |
| image = Image.open('logo/haystack-logo-colored.png') | |
| st.markdown("Thanks for coming to this 🤗 Space.\n\n" | |
| "This is an effort towards showcasing how can you use Haystack for Retrieval Augmented QA, " | |
| "with local document store as well as WebRetriever (coming soon!) \n\n" | |
| "For more on how this was built, instructions along with a Repository " | |
| "will be published soon and updated here.") | |
| # st.markdown( | |
| # "## How to use\n" | |
| # "1. Enter your [OpenAI API key](https://platform.openai.com/account/api-keys) below\n" | |
| # "2. Enter a Serper Dev API key\n" | |
| # "3. Enjoy 🤗\n" | |
| # ) | |
| # api_key_input = st.text_input( | |
| # "OpenAI API Key", | |
| # type="password", | |
| # placeholder="Paste your OpenAI API key here (sk-...)", | |
| # help="You can get your API key from https://platform.openai.com/account/api-keys.", | |
| # value=st.session_state.get("OPENAI_API_KEY", ""), | |
| # ) | |
| # if api_key_input: | |
| # set_openai_api_key(api_key_input) | |
| st.markdown("---") | |
| st.markdown( | |
| "## How this works\n" | |
| "This app was built with [Haystack](https://haystack.deepset.ai) using the" | |
| " [`PromptNode`](https://docs.haystack.deepset.ai/docs/prompt_node) and [`Retriever`](https://docs.haystack.deepset.ai/docs/retriever#embedding-retrieval-recommended).\n\n" | |
| " You can find the source code in **Files and versions** tab." | |
| ) | |
| st.markdown("---") | |
| st.image(image, width=250) | |